DIAGNOSTIC PROCEDURES

Description

TECHNICAL FIELD

[0001] In some aspects the present invention broadly relates to the use of single nucleotide polymorphisms (SNPs) in transient receptor potential (TRP) ion channel, genes as probes, tools or reagents for identifying, screening, diagnosing, monitoring or managing / treating subjects with, or predisposed to chronic fatigue syndrome (CFS).BACKGROUND ART

[0002] It will be clearly understood that, if a prior art publication is referred to herein, this reference does not constitute an admission that the publication forms part of the common general knowledge in the art in Australia or in any other country.

[0003] Chronic fatigue syndrome / myalgic encephalomyelitis (CFS / ME) is known to affect about 1-4% of individuals worldwide [1a, 2a]. CFS / ME has an unknown aetiology and there is no specific diagnostic test. Chronic fatigue syndrome (CFS) is an unexplained disorder with multiple physiological impairments. The illness is characterised by significant impairment in physical activity and debilitating fatigue accompanied by impairment in memory, cognition and concentration, enhanced experience of pain as well as dysregulation of the gastrointestinal, cardiovascular and immune systems [14a-31a]. Research to date suggests significant immune impairment. However, the mechanism of this disorder remains to be determined. CFS patients may have reactions to a number of environmental and biological factors [11a-13a]. Moreover, there is evidence to suggest that CFS may have an allergic component [14a-16a].

[0004] Medical conditions caused by dysregulation in TRP are typified by specific symptoms or dysregulation, including: significant impairment in physical activity; debilitating fatigue accompanied by impairment in memory, cognition and concentration; enhanced experience of pain; dysregulation of the gastrointestinal, cardiovascular and immune systems; headache; fatigue; confusion; depression; shortness of breath; arthralgia; myalgia; nausea; dizziness; memory problems; gastrointestinal symptoms; respiratory symptoms; and dysregulation of the gastrointestinal, cardiovascular and immune systems.

[0005] Transient receptor potential (TRP) ion channels are expressed on almost all cells and have a significant effect on physiological functions [3b]. A number of channelopathies have been associated with TRP genes as these have consequences for cellular function [4b, 18b, 19b]. Dysregulation in TRPs has been associated with pathological conditions and diseases including chronic pain, overactive bladder, diabetes, chronic obstructive pulmonary disease, cardiac hypertrophy, familial Alzheimer's disease, skin diseases, skeletal dysplasias, motor neuropathies, neuro-sensory neuropathies (including Charcot-Marie-Tooth disease (type 2C) and cancer [4b-8b]. TRP ion channels have an important role in Ca 2+< signalling. TRP ion channels are activated following fluctuations or deviations in the cellular environment. Factors that may influence these changes are stressors including pathogens, temperature, pressure, chemicals, oxidation / reduction, toxins, osmolarity and pH [9b, 10b]. TRP ion channels are activated in the presence of irritants, inflammatory products, and xenobiotic toxins.

[0006] Mammalian TRPs are comprised of six main groups including the TRPA (ankyrin), TRPC (canonical), TRPM (melastatin), TRPML (mucolipin), TRPP (polycystin) and TRPV (vanilloid) [1b, 2b]. Generally, the TRPC channels are nonselective cation channels, only two are highly permeable Ca 2+< channels and two are impermeable for Ca 2+< . Several TRPs are permeable for Mg 2+< and Zn 2+< [3b].

[0007] Single nucleotide polymorphisms (SNPs) occur in coding sequences of genes, noncoding regions of genes, or in the intergenic regions of genes. SNPs located within a coding sequence may or may not necessarily change the amino acid sequence of the protein that is produced. As such SNPs that do not alter the polypeptide sequence are termed synonymous (sometimes called silent variants) while SNPs that result in different polypeptide sequences are referred to as non-synonymous. Non-synonymous single nucleotide polymorphisms (nsSNPs) result in changes to protein expression that may result in aberrant signalling, such as loss or gain of function in their effect. Importantly, silent variants have been reported to affect splicing and may lead to human disease [10d, 11d]. Splicing affecting gene variants can induce exon skipping and activate alternate splice isoforms of the gene transcript, potentially resulting in altered gene transcripts and disease phenotypes.

[0008] Despite intensive research, to date, the pathophysiology of CFS / ME is not yet fully understood and clear diagnostic tools remain elusive. Therefore, there remains a need for rapid, cost-effective and reliable means for identifying, screening, diagnosing, monitoring and / or managing / treating individuals having, or at risk of developing, a medical condition such as CFS / ME.

[0009] WO2010 / 097706 discloses methods of deleting genetic polymorphisms for evaluating chronic immune diseases. WO2008 / 010082 discloses methods of determining fibromyalgia or chronic fatigue syndrome phenotypes by polymorphisms.SUMMARY OF INVENTION

[0010] The present invention concerns a method of identifying a subject at risk of developing chronic fatigue syndrome (CFS) or diagnosing a subject having CFS, said method comprising teting a biological sample that has been obtained from the subject for at least one single nucleotide polymorphism (SNP) of at least one transient receptor potential (TRP) ion channel gene known to correlate with CFS, wherein the SNP of the TRP ion channel gene is rs12682832 (TRPM3), rs11142508 (TRPM3), rs655207 (TRPC4), or rs6650469 (TRPC4).

[0011] Preferred features, embodiments and variations of the invention may be discerned from the appended claims. The Detailed Description is not to be regarded as limiting the scope of the preceding Summary of Invention in any way. The Detailed Description will make reference to a number of drawings as follows.BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figures which illustrate subject matter falling outside the invention are included for illustrative purposes only. Figure 1: Natural Killer Cell Purity. The purity of NK cells represents minimal contamination from other cells types. Data shown for ME / CFS (n=39), and non-fatigued controls (n = 30), and presented as mean ± SEM. Figure 2: Reduced NK cytotoxic activity in CFS / ME. In vivo assessment of NK cytotoxic activity of tumour cell lines K562 in CFS / ME (n=39) and unfatigued controls (n=30). Lytic activity represented by percentage lysis of target cells on the y-axis. Data presented as mean ± SE *P<0.05. Figure 3. TRPM3 expression (%) on B lymphocytes and NK cells gated from HC (n=19) and CFS / ME (n=18) peripheral mononuclear cells. (A) NK cells subsets were characterized as CD56 Bright< NK cells and CD56 Dim< NK cells. Identification of TRPM3 surface expression on the NK cell subsets was analyzed using indirect flow cytometry. (B) B cells were characterized as total B cells (CD3 -< CD19 +< ) and indirect flow cytometry was employed to identify TRPM3 surface expression on B cells. Histograms report the means ±SEM. *Denotes p<0.05. HC: healthy controls; CFS: Chronic Fatigue Syndrome; ME: myalgic encephalomyelitis. Figure 4: Fura-AM cytoplasmic calcium influx in CD19 +< B cells and CD56 Bright< NK cells. (A). CD19 +< B cells calcium influx response curve reported as area under the curve was measured during Anti-IgM and anti-CD21 conjugated biotins were cross-linked with streptavidin or in the presence of ionomycin, 2-APB or Thapsigargin using flow cytometry. (B). Fura-AM cytoplasmic calcium influx response during CD56 Bright< NK cell receptors, Anti-CD314 and anti-CD335 conjugated biotins were cross-linked with streptavidin or in the presence of ionomycin, 2-APB or Thapsigargin using flow cytometry. Histograms report the means ±SEM. *Denotes statistically significance at p<0.05. Figure 5: Representative flow cytometric plot of CD56 bright< CD16 dim / -< and CD56 dim< CD16 +< NK cell phenotypes (A). Comparisons of CD56 bright< CD16 dim / -< and CD56 dim< CD16 +< NK cell phenotypes between CFS / ME and NFC revealed no significant differences (B). Data are presented as median percentage with interquartile range. Figure 6: CD56 bright< CD16 dim / -< NK cell ERK1 / 2 flow cytometric plot for a representative individual (A). ERK1 / 2 in CD56 bright< CD16 dim / -< NK cells were compared between CFS / ME and NFC groups and no significant differences were observed. PMA / I stimulation caused a significant increase in ERK1 / 2 phosphorylation compared to US (***p<0.001) and K562 cells (****p<0.0001) in both CFS / ME and NFC. Data are presented as MFI with interquartile range. Figure 7: Representative flow cytometric plot for MEK 1 / 2 in CD56 dim< CD16 +< NK cells (A). No significant differences were observed when MEK1 / 2 was compared between CFS / ME and NFC (B). In both CFS / ME and NFC, PMA / I stimulation resulted in a significant increase in phosphorylated MEK1 / 2 compared to US (****p<0.0001) and K562 stimulation (****p<0.0001). Data are presented as MFI with interquartile range. Figure 8: p38 representative flow cytometric plot in CD56 dim< CD16 +< NK cells (A). p38 was compared between CFS / ME and NFC and no significant differences were observed (B). Stimulation with PMA / I caused a significant increase in phosphorylated p38 when compared to US and K562 incubated cells (*p<0.05). Data are presented as MFI with interquartile range. Figure 9: Representative Stat-3 flow cytometric plots in CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cells. Comparison of Stat-3 in CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells between CFS / ME and NFC revealed no significant differences. In CD56 dim< CD16 +< and CD56 bright< CD16 dim / -< NK cells, stimulation with PMA / I caused a significant increase in Stat-3 when compared to US (****p<0.0001) and K562 (****p<0.0001) in both CFS / ME and NFC. Figure 10: Representative flow cytometric analysis of NF-κβ in CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cells. No significant differences were observed when NF-κβ was compared between CFS / ME and NFC in CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells. Phosphorylated NF-κβ significantly increased after PMA / I stimulation in both CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells compared to US (****p<0.0001) and K562 (****p<0.0001) in CFS / ME and NFC. Data are presented as MFI with interquartile range. Figure 11: Iκβ representative flow cytometric plots in CD56 dim< CD16 +< (A) and CD56 bright< CD1 6dim / -< (B) NK cells. Irβ was compared in CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells from CFS / ME and NFC and no significant differences were observed. Stimulation with PMA / I caused a significant reduction in Iκβ in both CD56 dim< CD16 +< (*p<0.05) and CD56 bright< CD16 dim / -< (***p<0.001) NK cells from CFS / ME and NFC. Incubation with PMA / I also caused a significant reduction (*p<0.05) in Iκβ in CD56 bright< CD16 dim / -< NK cells from CFS / ME patients. Figure 12: Representative flow cytometric plots for the analysis of PKC-α in CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cells. PKC-α was compared in CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells from CFS / ME and NFC and no significant differences were observed. In CD56 dim< CD16 +< NK cells from NFC, stimulation with PMA / I caused a significant increase (**p<0.01) in PKC-α phosphorylation compared to K562 cells. PKC-α was significantly increased in CD56 bright< CD16 dim / -< NK cells after PMA / I stimulation when compared to US (*p<0.05) and K562 (***p<0.001) in NFC. Figure 13: Flow cytometric analysis of JNK in CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cells. No significant differences were observed when JNK was compared in CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells from CFS / ME and NFC. Significant increases in phosphorylated JNK were observed in both CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells after PMA / I stimulation when compared to US (**p<0.01) and K562 (***p<0.001) in CFS / ME and NFC. Figure 14: NK cell cytotoxic activity in CFS / ME and NFC at three E:T ratios. Figure 15: Representative flow cytometry plots for CD107a in CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cells. CD107a was measured in US cells and after stimulation with either K562 cells or PMA / I. Comparison of CD107a on CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells between CFS / ME and NFC revealed no significant differences. CD107a expression significantly increased after K562 and PMA / I (****p<0.0001) stimulation in CD56 dim< CD16 +< NK cells from both CFS / ME and NFC. In CD56 bright< CD16 dim / -< NK cells, PMA / I stimulation significantly increased expression of CD107a when compared to K562 and US cells (****p<0.0001) from CFS / ME and NFC. Figure 16: Flow cytometric analysis of CD107b on CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cells. No significant differences were observed when CD107b expression was compared between CFS / ME and NFC on CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells. In CD56 dim< CD16 +< NK cells, stimulation with K562 cells (*p<0.05) and PMA / I (****p<0.0001) caused a significant increase in CD107b expression in both CFS / ME and NFC compared to US. PMA / I stimulation significantly increased CD107b expression on CD56 bright< CD16 dim / -< NK cells from CFS / ME and NFC when compared to K562 and US (****p<0.0001). Figure 17: Perforin, Granzymes A and B and CD57 from CD56 dim< CD16 +< NK cells from CFS / ME patients. Figure 18: Perforin, Granzymes A and B and CD57 from CD56 bright< CD16 dim / -< NK cells from CFS / ME patients. Figure 19: Representative flow cytometric plots for CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cell production of IFN-γ. Comparison of IFN-γ production in CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells between CFS / ME and NFC revealed no significant differences. IFN-γ production significantly increased after PMA / I stimulation in both CD56 dim< CD16 +< and CD56 bright< CD16 dim / -< NK cells when compared to US and K562 (****p<0.0001). Figure 20: Flow cytometric plots for TNF-α in CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cells. Between CFS / ME and NFC cohorts, TNF-α production in CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells were not significantly different. In CD56 dim< CD16 +< NK cells, PMA / I stimulation significantly increased TNF-α production when compared to US and K562 incubated cells (****p<0.0001) in both CFS / ME and NFC. Figure 21: Flow cytometric analysis of GM-CSF production in CD56 dim< CD16 +< (A) and CD56 bright< CD16 dim / -< (B) NK cells. Production of GM-CSF in CD56 dim< CD16 +< (C) and CD56 bright< CD16 dim / -< (D) NK cells were not significantly different when compared between CFS / ME and NFC cohorts. Stimulation with PMA / I caused a significant increase in CD56 dim< CD16 +< and CD56 bright< CD16 dim< / - GM-CSF production in both CFS / ME and NFC compared to US and K562 incubated cells (****p<0.0001, ***p<0.001). Figure 22. Natural Killer cell purity. NK cell purity measurements are represented as total % of CD3 -< CD56 +< cells. Data are presented as mean ± SD for CFS / ME group (n= 24) and control group (n=11). Figure 23. Heat map of kinase gene expression showing (A) significantly upregulated and (B) significantly downregulated genes from severe CFS / ME patients compared with non-fatigued controls. Figure 24: Frequency of SNPs per chromosome. Figure 25: Manhattan plot of Fisher's exact test on 950 SNPs. Figure 26: Frequency of top 10 SNPs from Fisher's exact test. Cases: CFS / ME group; Controls: Healthy control group; MAF: Minor allele. Figure 27: Proportion of CFS / ME patients ("Cases") and healthy control group ("Controls") being homozygous major (GG), heterozygous (AG) or homozygous minor (AA) for adrenergic α1A (ADRA1A) SNP rs2322333. DETAILED DESCRIPTION

[0013] Chronic fatigue syndrome (CFS) and myalgic encephalomyelitis (ME) are significantly debilitating medical conditions characterised by persistent fatigue and other specific symptoms that last for a minimum of six months. CFS and ME are often used interchangeably to describe the same illness, although this need not be the case. The fatigue experienced by human subjects suffering from CFS is not due to exertion or caused by other medical condition, and is not significantly relieved by rest. It is a complex disease involving dysregulation of immune and central nervous systems, dysfunction of cellular energy metabolism and ion transport, and cardiovascular abnormalities.

[0014] CFS / ME patients may further be categorised into mild, moderate, severe or very severely affected by their illness. Mild CFS / ME patients are mobile and often still employed, moderate CFS / ME patients have reduced mobility and are restricted in daily tasks, such as household chores, severe CFS / ME patients are only able to perform minimal necessary hygiene-related tasks and are wheelchair dependent while those with very severe CFS / ME are unable to carry out any daily task for themselves and are essentially bedridden [3e]. The ICC is the most recent and accurate set of criteria used for CFS / ME diagnosis and contains reference to these severity subgroups of CFS / ME patients, although it is not a necessary component of the guidelines [4e].

[0015] A number of healthcare initiatives have been undertaken to advance research into the likely cause(s), mechanism, preventive measures and potential therapeutic strategies for CFS / ME. Presently, none of these initiatives has been successful and the medical community remains baffled by the illness.

[0016] Currently there are no commercially available diagnostic tests or definitive methods for screening of CFS / ME.

[0017] The most puzzling aspect of CFS / ME is its multifactorial, multi-symptom nature and resulting difficulty in the diagnosis of CFS / ME. The current method of diagnosis is to rule out other potential causes of the symptoms presented by the patients. When symptoms are attributable to certain other conditions, the diagnosis of CFS / ME is excluded. As a result, there is a prolonged 'elimination' process often including several attempted unsuccessful treatment strategies. This process can often take from 6 to 18 months. Accordingly, it is a serious financial burden to the subject and to the healthcare system and economy.

[0018] Although there is no specific treatment for CFS / ME, it can be appropriately managed once a patient is diagnosed as suffering from CFS. Additionally, there is some evidence to suggest that earlier a management regime is adopted the greater the chance of improvement, although no cure exists and improvements are largely empirically based. A diagnostic / screening test would significantly help in diagnosis / screening of CFS / ME, thereby reducing the patient suffering and healthcare costs associated with waiting for many months before being diagnosed with CFS / ME.

[0019] The present invention is described in more detail below.

[0020] The present inventors have, for the first time, identified SNPs of TRP ion channel that correlate with CFS and ME or specific symptoms thereof. The inventors believe that the identified SNPs of TRP ion channel genes also correlate with other medical conditions or symptoms thereof such as IBS, MCS, fibromyalgia, and migraine, as well as some medical conditions caused by dysregulation in calcium, acetylcholine, TRP and ADR, and dysregulation in the gastrointestinal, cardiovascular, neurological, genitourinary and immune systems.

[0021] "Medical condition" as used hereon in the specification can include (but is not limited to): CFS or specific symptoms thereof; ME or specific symptoms thereof; GWS, IBS; MCS; non-allergic rhinitis; fibromyalgia; migraine; or rheumatoid arthritis. "Medical condition" as used hereon in the specification can also include (but is not limited to) conditions or symptoms: caused by dysregulation in calcium (especially in respect of CFS, ME, GWS, IBS, MCS, fibromyalgia or migraine); caused by dysregulation in acetylcholine (especially in respect of CFS, ME, GWS, IBS, MCS, fibromyalgia or migraine); caused by dysregulation in TRP (especially in respect of CFS, ME, GWS, IBS, MCS, fibromyalgia or migraine); caused by dysregulation in ADR; caused by dysregulation of the gastrointestinal, cardiovascular, neurological, genitourinary and immune systems (especially in respect of CFS, ME, GWS, IBS, MCS, non-allergic rhinitis, fibromyalgia or migraine).

[0022] Specific symptoms of CFS or ME include: neuromuscular fatigue, particularly fatigue upon exertion; memory and concentration difficulties; muscle and joint pain; altered blood pressure, particularly postural orthostatic tachycardia syndrome; headache; immunological dysregulation; sore throat; swollen lymph nodes / glands; gastrointestinal symptoms including IB, diarrhoea, constipation and abdominal pain; chemical sensitives; and intolerances to drugs and chemicals.

[0023] Medical conditions caused by dysregulation in TRP are typified by specific symptoms or dysregulation, including: significant impairment in physical activity; debilitating fatigue accompanied by impairment in memory, cognition and concentration; enhanced experience of pain; dysregulation of the gastrointestinal, cardiovascular and immune systems; headache; fatigue; confusion; depression; shortness of breath; arthralgia; myalgia; nausea; dizziness; memory problems; gastrointestinal symptoms; respiratory symptoms; and dysregulation of the gastrointestinal, cardiovascular and immune systems (immunological "allergic" sensitivities).

[0024] Medical conditions caused by dysregulation of the gastrointestinal, cardiovascular, neurological, genitourinary and immune systems, (especially in respect of CFS, ME, GWS, IBS, MCS, fibromyalgia or migraine), are typified by specific symptoms or dysregulation, including: significant impairment in physical activity; debilitating fatigue accompanied by impairment in memory, cognition and concentration; enhanced experience of pain; headache; fatigue; confusion; depression; shortness of breath; arthralgia; myalgia; nausea; dizziness; memory problems; gastrointestinal symptoms; urinary frequency or discomfort; respiratory symptoms; and immunological "allergic" sensitivities.

[0025] Therefore, one or more of those SNPs can be used for identifying, screening, diagnosing or monitoring subjects with, or predisposed to, those medical conditions or symptoms thereof.

[0026] Moreover, yet one or more other TRP ion channel gene / allele-based or gene product-based probes, tools, reagents, methods and assays can be used for identifying, screening, diagnosing, monitoring or managing / treating subjects with, or predisposed to, those medical conditions or symptoms thereof.

[0027] The inventon provides a method of identifying a subject at risk of developing chronic fatigue syndrome (CFS) or diagnosing a subject having CFS, said method comprising testing a biological sample that has been obtained from the subject for at least one single nucleotide polymorphism (SNP) of at least one transient receptor potential (TRP) ion channel gene known to correlate with CFS, wherein the SNP of the TRP ion channel gene is rs12682832 (TRPM3), rs11142508 (TRPM3), rs655207 (TRPC4), or rs6650469 (TRPC4).

[0028] In yet another preferred embodiment, the at least one probe, tool or reagent is for assaying TRP ion channel protein / polypeptide expression on the surface of cells, preferably blood cells such as NK, T and / or B cells.Definitions

[0029] The term 'oligonucleotide' refers to a single-stranded sequence of ribonucleotide or deoxyribonucleotide bases, known analogues of natural nucleotides, or mixtures thereof. An oligonucleotide comprises a nucleic-acid based molecule including DNA, RNA, PNA, LNA, UNA or any combination thereof. Oligonucleotides are typically less than about 50 nucleotides in length and may be prepared by direct chemical synthesis or cloning and restriction of appropriate sequences.

[0030] The term 'polynucleotide' refers to a single- or double- stranded polymer of deoxyribonucleotide, ribonucleotide bases or known analogues of natural nucleotides, or mixtures thereof. A polynucleotide comprises a nucleic-acid based molecule including DNA, RNA, PNA, LNA, UNA or any combination thereof. The term includes reference to the specified sequence as well as to the sequence complimentary thereto, unless otherwise indicated. The term

[0031] 'polynucleotide' includes chemically modified variants, as realised by those skilled in the art.

[0032] The term 'complementary' refers to the ability of two single-stranded nucleotide sequences to base pair, typically according to the Watson-Crick base pairing rules. For two nucleotide molecules to be complementary they need not display 100% complementarity across the base pairing regions, but rather there must be sufficient complementarity to enable base pairing to occur. Thus a degree of mismatching between the sequences may be tolerated and the sequences may still be complementary.

[0033] 'Nucleic acid' as used herein includes 'polynucleotide', 'oligonucleotide', and 'nucleic acid molecule', and generally means a polymer of DNA or RNA, which can be single-stranded or double-stranded, synthesized or obtained (e.g., isolated and / or purified) from natural sources, which can contain natural, non-natural or altered nucleotides, and which can contain a natural, non-natural or altered internucleotide linkage, such as a phosphoroamidate linkage or a phosphorothioate linkage, instead of the phosphodiester found between the nucleotides of an unmodified oligonucleotide.

[0034] As used herein, the term 'recombinant' refers to (i) molecules that are constructed outside living cells by joining natural or synthetic nucleic acid segments to nucleic acid molecules that can replicate in a living cell, or (ii) molecules that result from the replication of those described in (i) above. For purposes herein, the replication can be in vitro replication or in vivo replication.

[0035] The terms 'isolated', 'purified' and 'substantially purified' as used herein mean essentially free of association with other biological components / contaminants, e.g., as a naturally occurring protein that has been separated from cellular and other contaminants by the use of antibodies or other methods or as a purification product of a recombinant host cell culture.

[0036] 'Probe' as used herein may mean an oligonucleotide capable of binding to a target nucleic acid / RNA of complementary sequence through one or more types of chemical bonds, usually through complementary base pairing, usually through hydrogen bond formation. Probes may bind target sequences lacking complete complementarity with the probe sequence depending upon the stringency of the hybridization conditions. There may be any number of base pair mismatches which will interfere with hybridization between the target sequence and the single stranded nucleic acids described herein. However, if the number of mutations is so great that no hybridization can occur under even the least stringent of hybridization conditions, the sequence is not a complementary target sequence. A probe may be single stranded or partially single and partially double stranded. The strandedness of the probe is dictated by the structure, composition, and properties of the target sequence. Probes may be directly labeled or indirectly labeled such as with biotin to which a streptavidin complex may later bind. Probes may be used for screening and diagnostic methods, as described herein. The probes may be attached or immobilized to a solid substrate or apparatus, such as a biochip.

[0037] 'Target' as used herein (context allowing) can mean an oligonucleotide or portions or fragments thereof, which may be bound by one or more probes under stringent hybridization conditions.Subject

[0038] The subject can be any mammal. Mammals include humans, primates, livestock and farm animals (eg. horses, sheep and pigs), companion animals (eg. dogs and cats), and laboratory test animals (eg. rats, mice and rabbits). The subject is preferably human.

[0039] Human subjects having CFS and / or ME can be defined as per the American CDC 1994 case definition [26a] and in the following citations [75a, 76a, 77a, 78a, 79a, 80a, 81a, 82a].

[0040] Non-fatigued / healthy controls / subjects (eg. not having CFS / ME) preferably have no medical history or symptoms of persistent fatigue or illness. Human subjects also preferably exclude individuals who were smokers, pregnant / breast-feeding or immobile, or had autoimmune, thyroid or cardiac related disorders prior to the onset of CFS / ME.General techniques overview

[0041] The steps / techniques of isolating a biological sample from a subject, processing a biological sample, genomic DNA extraction, RNA extraction, polypeptide extraction, DNA detection and characterisation, RNA detection and characterisation, polypeptide detection and characterisation, DNA sequencing, DNA sequence analyses, SNP genotyping studies, RNA location and identification, RNA profiling, RNA screening, RNA sequencing, RNA sequence analyses, measuring a level of expression of RNA, comparing expression levels (differential expression or dysregulation) of an RNA, polypeptide isolation, polypeptide sequencing and characterisation, measuring a level of polypeptide expression, comparing expression levels (differential expression or dysregulation) of a polypeptide, characterisation of dysfunctional signalling through the Mitogen-Activated Protein Kinase pathway of cells (such as PBMCs or NK cells), and detecting changes in calcium-dependent kinase pathways can be carried out in any suitable way.

[0042] It is to be appreciated that methodologies generally described for SNPs, such as differential expression or characterisation of RNA or protein or protein function etc, may equally apply to other forms of the disclosure such as testing for changes in calcium metabolism, testing for dysfunctional signalling through the Mitogen-Activated Protein Kinase pathway or detecting changes in calcium-dependent kinase pathways.

[0043] It is also to be appreciated that methodologies generally described for any one form of the invention may equally be applicable to one or more other forms of the invention.Biological sample

[0044] Any biological sample that comprises nucleic acid / a polynucleotide (eg. genomic DNA or RNA) from the subject is suitable for use in the methods of the invention. The biological sample can be processed so as to isolate the nucleic acid / polynucleotide. Alternatively, whole cells or other biological samples can be used without isolation of the nucleic acid / polynucleotides contained therein.

[0045] Any biological sample that comprises polypeptide / protein from the subject is suitable for use in the methods of the invention. The biological sample can be processed so as to isolate the polypeptide / protein. Alternatively, whole cells or other biological samples can be used without isolation of the nucleic polypeptide / protein contained therein.

[0046] The invention concerns a sample that has been isolated from a subject. Any form of the invention concerns a sample that has been isolated from the subject and testing that / those. For example, testing for differences in gene expression / gene products may involve isolating more than one biological sample, even from different tissues of that subject.

[0047] The biological sample can be any suitable sample derived from the subject - obtained either non-invasively or invasively. It can be cellular- or extracellular-derived, or both. For example: 1. Buccal (mouth) cells - obtained by swishing mouthwash in the mouth or by swabbing or brushing the inside of the cheek with a swab or brush; 2. Blood - obtained by pricking the finger and collecting the drops (dried blood spot) or by venepuncture (whole blood); 3. Skin - obtained by a (punch) biopsy; 4. Organ tissue - obtained by biopsy; 5. Plasma - obtained by blood plasma fractionation; 6. Urine - obtained by urination; 7. Faeces - obtained by stool sample; 8. Cerebrospinal fluid - obtained by spinal tap; and 9. Sputum - obtained by expectoration or nasotracheal suctioning.

[0048] Techniques for biological sample collection are well known to skilled persons.

[0049] In some embodiments, the biological sample can be a biofluid such as blood, plasma, serum, other blood isolate / component, urine, sputum, cerebrospinal fluid, milk, or ductal fluid, and can be fresh, frozen or fixed. In some preferred embodiments, for example, biofluid or biological sample comprising plasma or serum can be removed surgically and preferably by extraction, e.g. by hypodermic or other types of needles.

[0050] The biofluid typically will contain at least one SNP / gene / gene product (RNA and / or polpeptide) of interest, and will be relatively stable.

[0051] In some embodiments, plasma harvesting is employed. Plasma harvesting / extraction can be performed in any suitable way, but preferably immediately after peripheral blood collection. Plasma harvesting can involve a centrifugation step so as to separate the plasma from other blood components, and frozen storage of that plasma.

[0052] In some embodiments, different biological samples can be obtained from different tissues from one and the same subject.Detection of polymorphism overview

[0053] Detection of a target polymorphism (SNP) in a polynucleotide sample derived from an individual can be accomplished by any means known in the art, including, but not limited to, amplification of a sequence with specific primers; determination of the nucleotide sequence of the polynucleotide sample; hybridization analysis; single strand conformational polymorphism analysis; denaturing gradient gel electrophoresis; mismatch cleavage detection; exome sequencing and the like.

[0054] Detection of a target polymorphism can also be accomplished by detecting an alteration in the level of an RNA / mRNA transcript of the gene; aberrant modification of the corresponding gene, e.g., an aberrant methylation pattern; the presence of a non-wild-type splicing pattern of the corresponding transcript / mRNA; an alteration in the expression or translation level of the corresponding polypeptide; an alteration in the length of the corresponding polypeptide; and / or an alteration in corresponding polypeptide activity.Polymorphism detection methodologies

[0055] As mentioned, detection of a target polymorphism by analyzing a polynucleotide sample can be conducted in a number of ways. A test nucleic acid sample can be amplified with primers which amplify a region known to comprise the target polymorphism(s). Genomic DNA or mRNA can be used directly. Alternatively, the region of interest can be cloned into a suitable vector and grown in sufficient quantity for analysis. The nucleic acid may be amplified by conventional techniques, such as a polymerase chain reaction (PCR), to provide sufficient amounts for analysis. The use of the polymerase chain reaction is described in a variety of publications, including, e.g., "PCR Protocols (Methods in Molecular Biology)" (2000) J. M.S. Bartlett and D. Stirling, eds, Humana Press; and "PCR Applications: Protocols for Functional Genomics" (1999) Innis, Gelfand, and Sninsky, eds., Academic Press. Once the region comprising a target polymorphism has been amplified, the target polymorphism can be detected in the PCR product by nucleotide sequencing, by Single Strand Conformation Polymorphism (SSCP) analysis, or any other method known in the art. In performing SSCP analysis, the PCR product may be digested with a restriction endonuclease that recognizes a sequence within the PCR product generated by using as a template a reference sequence, but does not recognize a corresponding PCR product generated by using as a template a variant sequence by virtue of the fact that the variant sequence no longer contains a recognition site for the restriction endonuclease.

[0056] PCR can also be used to determine whether a polymorphism is present by using a primer that is specific for the polymorphism. Such methods can comprise the steps of collecting from a subject a biological sample comprising the subject's genetic material as template, optionally isolating template nucleic acid (genomic DNA, mRNA, or both) from the biological sample, contacting the template nucleic acid sample with one or more primers that specifically hybridize with a target polymorphic nucleic acid molecule under conditions such that hybridization and amplification of the template nucleic acid molecules in the sample occurs, and detecting the presence, absence, and / or relative amount of an amplification product and comparing the length to a control sample. Observation of an amplification product of the expected size is an indication that the target polymorphism contained within the target polymorphic primer is present in the test nucleic acid sample. Parameters such as hybridization conditions, polymorphic primer length, and position of the polymorphism within the polymorphic primer can be chosen such that hybridization will not occur unless a polymorphism present in the primer(s) is also present in the sample nucleic acid. Those of ordinary skill in the art are well aware of how to select and vary such parameters. See, e.g., Saiki et al. (1986) Nature 324:163; and Saiki et al (1989) Proc. Natl. Acad. Sci USA 86:6230.

[0057] Alternatively, various methods are known in the art that utilize oligonucleotide ligation as a means of detecting polymorphisms. See, e.g., Riley et al. (1990) Nucleic Acids Res. 18:2887-2890; and Delahunty et al. (1996) Am. J. Hum. Genet. 58:1239-1246.

[0058] A detectable label may be included in an amplification reaction. Suitable labels include fluorochromes, e.g. fluorescein isothiocyanate (FITC), rhodamine, Texas Red, phycoerythrin, allophycocyanin, 6-carboxyfluorescein (6-FAM), 2',7'-dimethoxy-4',5'- dichloro-6-carboxyfluorescein (JOE), 6-carboxy-X-rhodamine (ROX), 6-carboxy-2',4',7',4,7-hexachlorofluorescein (HEX), 5-carboxyfluorescein (5-FAM) or N,N,N',N'-tetramethyl-6-carboxyrhodamine (TAMRA), radioactive labels, e.g. 32< P, 35< S, 3< H; etc. The label may be a two stage system, where the amplified DNA is conjugated to biotin, haptens, etc. having a high affinity binding partner, e.g. avidin, specific antibodies, etc., where the binding partner is conjugated to a detectable label. The label may be conjugated to one or both of the primers. Alternatively, the pool of nucleotides used in the amplification is labeled, so as to incorporate the label into the amplification product.

[0059] The sample nucleic acid can be sequenced by a dideoxy chain termination method or other well-known methods. Genomic DNA or mRNA may be used directly. If mRNA is used, a cDNA copy may first be made. If desired, the sample nucleic acid can be amplified using a PCR step. A variety of sequencing reactions known in the art can be used to directly sequence the relevant gene, or a portion thereof in which a specific polymorphism is known to occur, and detect polymorphisms by comparing the sequence of the sample nucleic acid with a reference polynucleotide that contains a target polymorphism. Any of a variety of automated sequencing procedures can be used. See, e.g., WO 94 / 16101; Cohen et al. (1996) Adv. Chromatography 36:127-162.

[0060] Hybridization with the variant sequence can also be used to determine the presence of a target polymorphism. Hybridization analysis can be carried out in a number of different ways, including, but not limited to Southern blots, Northern blots, dot blots, microarrays, etc. The hybridization pattern of a control and variant sequence to an array of oligonucleotide probes immobilized on a solid support, as described in U.S. 5,445,934, or in WO 95 / 35505, may also be used as a means of detecting the presence of variant sequences. Identification of a polymorphism in a nucleic acid sample can be performed by hybridizing a sample and control nucleic acids to high density arrays containing hundreds or thousands of oligonucleotide probes. Cronin et al. (1996) Human Mutation 7:244-255; and Kozal et al. (1996) Nature Med. 2:753-759.

[0061] Single strand conformational polymorphism (SSCP) analysis; denaturing gradient gel electrophoresis (DGGE); mismatch cleavage detection; and heteroduplex analysis in gel matrices can also be used to detect polymorphisms. Alternatively, where a polymorphism creates or destroys a recognition site for a restriction endonuclease (restriction fragment length polymorphism, RFLP), the sample is digested with that endonuclease, and the products size fractionated to determine whether the fragment was digested. Fractionation is performed by gel or capillary electrophoresis, particularly acrylamide or agarose gels. The aforementioned techniques are well known in the art. Detailed description of these techniques can be found in a variety of publications, including, e.g., "Laboratory Methods for the Detection of Mutations and Polymorphisms in DNA" (1997) G. R. Taylor, ed., CRC Press, and references cited therein.SNP detection

[0062] As mentioned above, various methods can be used to determine the presence or absence of a SNP in a subject / biological sample. Genotype can be determined, for example, by microarray analysis, sequencing, primer extension, ligation of allele specific oligonucleotides, mass determination of primer extension products, restriction length polymorphism analysis, single strand conformational polymorphism analysis, pyrosequencing, dHPLC or denaturing gradient gel electrophoresis (DGGE). Furthermore, having sequenced nucleic acid of a subject or sample, the sequence information can be retained and subsequently searched without recourse to the original nucleic acid itself. Thus, for example, a sequence alteration or mutation may be identified by scanning a database of sequence information using a computer or other electronic means.

[0063] In general, nucleic acid regions which contain the SNPs of interest (target regions) are preferably subjected to an amplification reaction. Any suitable technique or method may be used for amplification. In general, where multiple SNPs are to be analysed, it is preferable to simultaneously amplify all of the corresponding target regions (comprising the nucleotide variations).

[0064] Some embodiments of the invention can comprise determining the binding of an oligonucleotide probe to a genomic sample. The probe can comprise a nucleotide sequence which binds specifically to a particular SNP. Suitable oligonucleotide probes can be derived based on the SNP and nucleotide sequences of any one of Tables 1 to 7, 9, 10, 12 to 17, 26 to 28, and 34 to 36. The oligonucleotide probe may comprise a label and binding of the probe can be determined by detecting the presence of the label.

[0065] Some embodiments of the invention can comprise hybridising of one, two or more oligonucleotide probes or primers to target nucleic acid. Where the nucleic acid is double-stranded DNA, hybridisation will generally be preceded by denaturation to produce single-stranded DNA. The hybridisation can be as part of an amplification, e.g. PCR procedure, or as part of a probing procedure not involving amplification, e.g. PCR. An example procedure would be a combination of PCR and low stringency hybridisation. Any suitable screening procedure can be used to identify successful hybridisation events and isolated hybridised nucleic acid.

[0066] Binding of a probe to target nucleic acid (e.g. DNA) can be measured using any of a variety of techniques. For instance, probes may be radioactively, fluorescently or enzymatically labelled. Other methods not employing labelling of probe include examination of restriction fragment length polymorphisms, amplification using PCR, RNase cleavage and allele specific oligonucleotide probing. Probing can employ the standard Southern blotting technique. For instance, DNA can be extracted from cells and digested with different restriction enzymes. Restriction fragments can then be separated by electrophoresis on an agarose gel, before denaturation and transferred to a nitrocellulose filter. Labelled probe can be hybridised to the DNA fragments on the filter and binding determined. DNA for probing can be prepared from RNA preparations from cells. Suitable stringency for selective hybridisation, oligonucleotide length, base composition and temperature can be readily determined by the skilled addressee.

[0067] For example, suitable selective hybridisation conditions for oligonucleotides of 17 to 30 bases include hybridization overnight at 42°C in 6X SSC and washing in 6X SSC at a series of increasing temperatures from 42°C to 65°C. Other suitable conditions and protocols are described in Molecular Cloning: a Laboratory Manual: 2nd edition, Sambrook et al., 1989, Cold Spring Harbor Laboratory Press and Current Protocols in Molecular Biology, Ausubel et al. eds., John Wiley & Sons, 1992.

[0068] An oligonucleotide for use in nucleic acid amplification can be about 30 or fewer nucleotides in length (e.g. 18, 20, 22, 24 or 26). Generally, specific primers are upwards of 14 nucleotides in length. Those skilled in the art are well versed in the design of primers for use in processes such as PCR. Various techniques for synthesizing oligonucleotide primers are well known in the art, including phosphotriester and phosphodiester synthesis methods.

[0069] Nucleic acid can also be screened using a variant- or allele-specific probe. Such a probe can correspond in sequence to a region of genomic nucleic acid, or its complement, which contains one or more of the SNPs of interest. Under suitably stringent conditions, specific hybridisation of such a probe to test nucleic acid is indicative of the presence of the sequence alteration in the test nucleic acid. For efficient screening purposes, more than one probe can be used on the same test sample.

[0070] Nucleic acid in a test sample, which can be a genomic sample or an amplified region thereof, can be sequenced to identify or determine the identity of a polymorphic allele. The allele of the SNP in the test nucleic acid can therefore be compared with the SNP as described herein to determine whether the test nucleic acid contains one or more alleles which are associated with the medical condition or symptom thereof.

[0071] Since it will not generally be time- or labour-efficient to sequence all nucleic acid in a test sample, a specific amplification reaction such as PCR using one or more pairs of primers can be employed to amplify the region of interest in the nucleic acid, for instance the particular region in which the SNPs of interest occur. The amplified nucleic acid can then be sequenced as above, and / or tested in any other way to determine the presence or absence of a particular nucleotide. Nucleic acid for testing can be prepared from nucleic acid removed from cells or in a library using a variety of other techniques such as restriction enzyme digest and electrophoresis.

[0072] Sequencing of an amplified product can involve precipitation with isopropanol, resuspension and sequencing using a TaqFS+ Dye terminator sequencing kit. Extension products may be electrophoresed on an ABI 377 DNA sequencer and data analysed using Sequence Navigator software.

[0073] Nucleic acid in a test sample can be probed under conditions for selective hybridisation and / or subjected to a specific nucleic acid amplification reaction such as the polymerase chain reaction (PCR) (reviewed for instance in "PCR protocols; A Guide to Methods and Applications", Eds. lnnis et al, 1990, Academic Press, New York, Mullis et al, Cold Spring Harbor Symp. Quant. Biol., 51 :263, (1987), Ehrlich (ed), PCR technology, Stockton Press, NY, 1989, and Ehrlich et al, Science, 252:1643-1650, (1991)). PCR comprises steps of denaturation of template nucleic acid (if double-stranded), annealing of primer to target, and polymerisation. The nucleic acid probed or used as template in the amplification reaction may be genomic DNA, cDNA or RNA.

[0074] Other specific nucleic acid amplification techniques include strand displacement activation, the QB replicase system, the repair chain reaction, the ligase chain reaction, rolling circle amplification and ligation activated transcription. Methods of the present invention may therefore comprise amplifying the region in said genomic sample containing the one or more positions of single nucleotide polymorphism of interest.

[0075] Allele-specific oligonucleotides can be used in PCR to specifically amplify particular sequences if present in a test sample. Assessment of whether a PCR band contains a gene variant may be carried out in a number of ways familiar to those skilled in the art. The PCR product may for instance be treated in a way that enables one to display the polymorphism on a denaturing polyacrylamide DNA sequencing gel, with specific bands that are linked to the gene variants being selected.

[0076] In some embodiments, the region of genomic sample comprising a polymorphism can be amplified using a pair of oligonucleotide primers, of which the first member of the pair comprises a nucleotide sequence which hybridises to a complementary sequence which is proximal to and 5' of the position of single nucleotide polymorphism, and the second member of the primer pair comprises a nucleotide sequence which hybridises to a complementary sequence which is proximal to and 3' of the position of single nucleotide polymorphism.

[0077] In other embodiments, the first member of the pair of oligonucleotide primers can comprise a nucleotide sequence which hybridises to a complementary sequence which is proximal to and 5' or 3' of the polymorphism, and the second member of the pair can comprise a nucleotide sequence which hybridises under stringent conditions to a particular allele of the polymorphism and not to other alleles, such that amplification only occurs in the presence of the particular allele.

[0078] A further aspect of the present disclosure provides a pair of oligonucleotide amplification primers. A suitable pair of amplification primers according to this aspect can have a first member comprising a nucleotide sequence which hybridises to a complementary sequence which is proximal to and 5' of a single nucleotide polymorphism and a second member comprising a nucleotide sequence which hybridises to a complementary sequence which is proximal to and 3' of the single nucleotide polymorphism.

[0079] The allele of the at least one polymorphism (i.e. the identity of the nucleotide at the position of single nucleotide polymorphism) can then be determined by determining the binding of an oligonucleotide probe to the amplified region of the genomic sample. A suitable oligonucleotide probe comprises a nucleotide sequence which binds specifically to a particular allele of the at least one polymorphism and does not bind specifically to other alleles of the at least one polymorphism.

[0080] Other suitable pairs of amplification primers can have a first member comprising a nucleotide sequence which hybridises to a complementary sequence which is proximal to and 5' or 3' of a single nucleotide polymorphism and a second member of the pair comprising a nucleotide sequence which hybridises under stringent conditions to a particular allele of the polymorphism and not to other alleles, such that amplification only occurs in the presence of the particular allele.

[0081] PCR primers suitable for amplification of target DNA regions comprising the SNPs of the invention can be readily prepared by the skilled addressee. A further aspect of the present disclosure provides an oligonucleotide which hybridises specifically to a nucleic acid sequence which comprises a particular allele of a polymorphism of the invention, and does not bind specifically to other alleles of the SNP. Hybridisation may be determined under suitable selective hybridisation conditions as described herein.

[0082] Such oligonucleotides may be used in a method of screening nucleic acid.

[0083] In some preferred embodiments, oligonucleotides according to the present disclosure are at least about 10 nucleotides in length, more preferably at least about 15 nucleotides in length, more preferably at least about 20 nucleotides in length. Oligonucleotides may be up to about 100 nucleotides in length, more preferably up to about 50 nucleotides in length, more preferably up to about 30 nucleotides in length. The boundary value 'about X nucleotides' as used above includes the boundary value 'X nucleotides'.

[0084] Approaches which rely on hybridisation between a probe and test nucleic acid and subsequent detection of a mismatch may be employed. Under appropriate conditions (temperature, pH etc.), an oligonucleotide probe will hybridise with a sequence which is not entirely complementary. The degree of base-pairing between the two molecules will be sufficient for them to anneal despite a mis-match. Various approaches are well known in the art for detecting the presence of a mis- match between two annealing nucleic acid molecules. For instance, RNase A cleaves at the site of a mis-match. Cleavage can be detected by electrophoresis test nucleic acid to which the relevant probe or probe has annealed and looking for smaller molecules (i.e. molecules with higher electrophoretic mobility) than the full length probe / test hybrid.

[0085] Genotype analysis may be carried out by microarray analysis. Any suitable microarray technology may be used. Preferably the methodology reported in International Patent Application No. PCT / IB2006 / 00796 filed 12 January 2006 is used. This technology uses a low-density DNA array and hybridisation to allele-specific oligonucleotide probes to screen for SNPs.

[0086] Typically in this technology, nucleic acid regions which contain the SNPs of interest (target regions) may be subjected to an amplification reaction. Any suitable technique or method may be used for amplification. In general, where multiple SNPs are to be analysed, it is preferable to simultaneously amplify all of the corresponding target regions (comprising the variations).

[0087] For example, multiplex PCR may be carried out, using appropriate pairs of oligonucleotide PCR primers. Any suitable pair of primers which allow specific amplification of a target region may be used. In one aspect, the primers allow amplification in the fewest possible number of PCR reactions.

[0088] Following amplification, the amplified nucleic acid may undergo fragmentation, e.g. by digestion with a suitable nuclease such as DNAse I. Typically the amplified (optionally fragmented) DNA is then labelled. Suitable labels are known in the art.

[0089] A microarray typically comprises a plurality of probes deposited on a solid support. In general the solid support comprises oligonucleotide probes suitable for discrimination between possible nucleotides at each SNP variable to be determined in the method. The microarray typically also comprises additional positive and / or negative controls.

[0090] Typically, for a SNP with the possible alleles A and B, there will be at least one probe which is capable of hybridising specifically to allele A (probe 1) and one probe which is capable of hybridising specifically to allele B (probe 2) under the selected hybridisation conditions. These probes form a probe pair. Typically the probes can be used to discriminate between A and B (e.g. the wildtype and mutant alleles). The probes may examine either the sense or the antisense strand. Typically, probes 1 and 2 examine the same nucleic acid strand (e.g. the sense strand or antisense strand) although in some cases the probes may examine different strands. In one aspect probes 1 and 2 have the same sequence except for the site of the genetic variation.

[0091] In one instance, the probes in a probe pair have the same length. In some aspects, where two or more pairs of probes are provided for analysis of a genetic variation, the probes may all have the same length.

[0092] Preferably more than one probe pair is provided for detection of each genetic variation. Thus, at least 2, 3, 4, 5, 6, 7, 8, 9, 10 or more probe pairs may be provided per genetic variation. In one aspect, (at least) 2 probe pairs are provided. The aim is to reduce the rate of false positives and negatives in the present methods.

[0093] For example, for a given genetic variation there may be: Probe 1 which is capable of hybridising to genetic variation A (e.g. a normal allele) Probe 2 which is capable of hybridising to genetic variation B (e.g. a mutant allele) Probe 3 which is capable of hybridising to genetic variation A (e.g. a normal allele) Probe 4 which is capable of hybridising to genetic variation B (e.g. a mutant allele).

[0094] The probes may examine the same or different strands. Thus in one embodiment, probes 3 and 4 are the complementary probes of probes 1 and 2 respectively and are designed to examine the complementary strand. In one aspect it is preferred that the probes provided for detection of each genetic variation examine both strands.

[0095] More than 2 pairs of probes may be provided for analysis of a genetic variation as above. For example, where a genetic variation exists as any one of 4 bases in the same strand (e.g. there are three mutant possibilities), at least one pair of probes may be provided to detect each possibility. Preferably, at least 2 pairs of probes are provided for each possibility.

[0096] A number of methods are known in the art for designing oligonucleotide probes suitable for use in DNA-chips. These include "standard tiling", "alternative tiling" "block tiling" and "alternative block tiling". Any one or more of these strategies may be used to design probes for the present invention. Preferably standard tiling is used, in particular with 2 pairs of probes e.g. 2 pairs of complementary probes as above. Thus it is preferable that the oligonucleotide sequence is complementary to the target DNA or sequence in the regions flanking the variable nucleotide(s). However, in some cases, one or more mismatches may be introduced. The oligonucleotide probes for use in the present invention typically present the base to be examined (the site of the genetic variation) at the centre of the oligonucleotide.

[0097] In general the probes for use in the present invention comprise or in some embodiments consist (essentially) of 17 to 27 nucleotides, for example, 19, 21, 23, or 25 nucleotides or 18, 20, 22, 24 or 26 nucleotides.

[0098] The probes provided for detection of each genetic variation (as described above) are typically capable of discriminating between genetic variants A and B (e.g. the normal and mutant alleles) under the selected hybridisation conditions. Preferably the discrimination capacity of the probes is substantially 100%. If the discrimination capacity is not 100%, the probes are preferably redesigned. Preferably the melting temperature of the probe / target complexes is in the range of 75-85 ° C.

[0099] In general probes are provided on the support in replicate. Typically, at least 4, 6, 8, 10, 12, 14, 16, 18 or 20 replicates are provided of each probe, in particular, 6, 8 or 10 replicates. Thus for example, the support (or DNA-chip) may comprise or include 10 replicates for each of (at least) 4 probes used to detect each genetic variation (i.e. 40 probes). Alternatively the support (or DNA- chip) may comprise or include 8 replicates for each of (at least) 4 probes used to detect each genetic variation (i.e. 32 probes). Still further the support (or DNA-chip) may comprise or include 6 replicates for each of (at least) 4 probes used to detect each genetic variation (i.e. 24 probes). In general the support also comprises one or more control oligonucleotide probes which are useful as positive and / or negative controls of the hybridisation reactions. These are also provided in replicate as above.

[0100] Typically the chip or array will include positive control probes, e.g., probes known to be complementary and hybridisable to sequences in the target polynucleotide molecules, probes known to hybridise to an external control DNA, and negative control probes, e.g., probes known to not be complementary and hybridizable to sequences in the target polynucleotide molecules. The chip may have one or more controls specific for each target, for example, 2, 3, or more controls. There may also be at least one control for the array.

[0101] Positive control probes are generally designed to hybridise equally to all target DNA samples and provide a reference signal intensity against which hybridisation of the target DNA (sample) to the test probes can be compared. Negative controls comprise either "blanks" where only solvent (DMSO) has been applied to the support or control oligonucleotides that have been selected to show no, or only minimal, hybridisation to the target, e.g. human, DNA (the test DNA). The intensity of any signal detected at either blank or negative control oligonucleotide features is an indication of non-specific interactions between the sample DNA and the array and is thus a measure of the background signal against which the signal from real probe-sample interactions must be discriminated.

[0102] Desirably, the number of sequences in the array will be such that where the number of nucleic acids suitable for detection of genetic variations is n, the number of positive and negative control nucleic acids is n', where n' is typically from 0.01 to 0.4n.

[0103] One example of a DNA chip / microarray which may be used is Fibrochip.

[0104] A Fibro-chip comprises oligonucleotide probes suitable for detection of some or all of the genetic variations (SNPs).

[0105] In general an array comprises a support or surface with an ordered array of binding (e.g. hybridisation) sites or probes. Each probe (i.e. each probe replicate) is located at a known predetermined position on the solid support such that the identity (i.e. the sequence) of each probe can be determined from its position in the array. Preferably, the probes deposited on the support, although they maintain a predetermined arrangement, are not grouped by genetic variation but have a random distribution. Typically they are also not grouped within the same genetic variation. If desired, this random distribution can be always the same. Probes may be arranged on the support in subarrays.

[0106] The support, on which the plurality of probes is deposited, can be any solid support to which oligonucleotides can be attached. For example, the said support can be of a non-porous material, for example, glass, silicon, plastic, or a porous material such as a membrane or filter (for example, nylon, nitrocellulose) or a gel. In one embodiment, the said support is a glass support, such as a glass slide.

[0107] Probes may be attached to the support using conventional techniques for immobilization of oligonucleotides on the surface of the supports.

[0108] In one embodiment, the support is a glass slide and in this case, the probes, in the number of established replicates (for example, 6, 8 or 10) are printed on pre-treated glass slides, for example coated with aminosilanes, using equipment for automated production of DNA-chips by deposition of the oligonucleotides on the glass slides ("micro-arrayer"). Deposition is carried out under appropriate conditions, for example, by means of crosslinking with ultraviolet radiation and heating (80°C), maintaining the humidity and controlling the temperature during the process of deposition, typically at a relative humidity of between 40-50% and typically at a temperature of 20°C.

[0109] The replicate probes are distributed uniformly amongst the areas or sectors (subarrays), which typically constitute a DNA-chip. The number of replicas and their uniform distribution across the DNA-chip minimizes the variability arising from the printing process that can affect experimental results. Likewise, positive and negative hybridisation controls (as described herein) may be printed.

[0110] To control the quality of the manufacturing process of the DNA-chip, in terms of hybridization signal, background noise, specificity, sensitivity and reproducibility of each replica as well as differences caused by variations in the morphology of the spotted probe features after printing, a commercial DNA can be used. For example, as a quality control of the printing of the DNA-chips, hybridization may be carried out with a commercial DNA (e.g. k562 DNA High Molecular Weight, Promega)

[0111] In general, methods for using microarrays for genotyping are known in the art.

[0112] In one aspect the data from the present microarrays may be analysed and used to determine genotype according to the methods in International Patent Application No. PCT / IB2006 / 00796 filed 12 January 2006. Typically, following amplification of the target DNA and optional fragmentation (e.g. by digestion with DNase I), the target DNA is labelled as described herein.

[0113] The labelled DNA may then be hybridised with a microarray under suitable hybridisation conditions which may be determined by the skilled person. For example, an automatic hybridisation station may be used.

[0114] In general the microarray is then scanned and the label intensities at the specific probe positions determined in order to determine which allele is present in the target DNA hybridised to the array.

[0115] In one aspect, following hybridisation, the signal intensity of the label is detected at each probe position on the microarray to determine extent of hybridisation at each position. This may be done by any means suitable for detecting and quantifying the given label. For example, fluorescent labels may be quantified using a confocal fluorescent scanner.

[0116] This signal intensity value is typically corrected to eliminate background noise by means of controls on the array. Where a microarray includes probe pairs and probe replicates as described herein, a hybridisation signal mean can then be calculated for each probe (based on the signals from the probes replicates). The ratio of the hybridisation signal mean of the A allele to the sum of the hybridisation signal means of the A and B alleles can then be defined for each probe pair used for genotyping of each SNP (ratios 1 and 2).

[0117] The 2 ratio values corresponding to each of the 3 possible genotypes (AA, AB and BB) may be calculated using target DNA from control individuals of each genotype identified previously by, e.g. sequence analysis (at least 10 per genotype).

[0118] By comparison of test DNA results with the control ratios, a genotype may be assigned to a test individual. This may be done using the MG 1.0 software.

[0119] As mentioned above, genotyping may also be carried out using sequencing methods. Typically, nucleic acid comprising the SNPs of interest is isolated and amplified as described herein. Primers complementary to the target sequence are designed so that they are a suitable distance (e.g. 50-400 nucleotides) from the polymorphism. Sequencing is then carried out using conventional techniques. For example, primers may be designed using software that aims to select sequence(s) within an appropriate window which have suitable Tm values and do not possess secondary structure or that will hybridise to non-target sequence.

[0120] Additional references describing various protocols for detecting the presence of a target polymorphism include, but are not limited to, those described in: US Patent Nos. 6,703,228; 6,692,909; 6,670,464; 6,660,476; 6,653,079; 6,632,606; 6,573,049.Exome sequencing

[0121] SNPs can be identified and characterised using exome sequencing. Exome sequencing (also known as Whole Exome Sequencing or WES) is a technique for sequencing all the protein-coding genes in a genome (known as the exome). It consists of first selecting only the subset of DNA that encodes proteins (known as exons), and then sequencing that DNA using any high throughput DNA sequencing technology. Different target-enrichment techniques are briefly described below:

[0122] PCR - PCR is technology to amplify specific DNA sequences. It uses a single stranded piece of DNA as a start for DNA amplification. Uniplex PCR uses only one starting point (primer) for amplification and multiplex PCR uses multiple primers.

[0123] Molecular inversion probes (MIP) - Molecular inversion probe uses probes of single stranded DNA oligonucleotides flanked by target-specific ends. The gaps between the flanking sequences are filled and ligated to form a circular DNA fragment. Probes that did not undergo reaction remain linear and are removed using exonucleases.

[0124] Hybrid capture - Microarrays contain single-stranded oligonucleotides with sequences from the human genome to tile the region of interest fixed to the surface. Genomic DNA is sheared to form double-stranded fragments. The fragments undergo end-repair to produce blunt ends and adaptors with universal priming sequences are added. These fragments are hybridized to oligos on the microarray. Unhybridized fragments are washed away and the desired fragments are eluted. The fragments are then amplified using PCR.

[0125] In-solution capture - To capture genomic regions of interest using in-solution capture, a pool of custom oligonucleotides (probes) is synthesized and hybridized in solution to a fragmented genomic DNA sample. The probes (labeled with beads) selectively hybridize to the genomic regions of interest after which the beads (now including the DNA fragments of interest) can be pulled down and washed to clear excess material. The beads are then removed and the genomic fragments can be sequenced allowing for selective DNA sequencing of genomic regions (e.g., exons) of interest.

[0126] Sequencing - Sequencing platforms include the classical Sanger sequencing, the Roche 454 sequencer, the Illumina Genome Analyzer II and the Life Technologies SOLiD & Ion Torrent - all of which have been used for exome sequencing.

[0127] Sequencing types: Sanger sequencing; SNP sequencing of exome; pyrosequencing; RNA sequencing; and, protein sequencing.Expression level detection methodologies

[0128] Biochemical studies may be performed to determine whether a sequence polymorphism in a coding region or control region of interest is associated with the medical condition. Condition-associated polymorphisms may include deletion or truncation of the gene, mutations that alter expression level, that affect the activity of the polypeptide, etc.

[0129] A number of methods are available for determining the expression level of a polymorphic nucleic acid molecule, e.g., RNA / mRNA or a polymorphic polypeptide (protein) in a particular sample. Diagnosis may be performed by a number of methods to determine the absence or presence or altered amounts of normal or abnormal RNA / mRNA or polypeptide in a patient sample.Characterisation of RNA expression

[0130] Methods of the subject disclosure in which the level of (polymorphic) gene expression is of interest will typically involve comparison of the relevant nucleic acid abundance of a sample of interest with that of a control value to determine any relative differences, where the difference may be measured qualitatively and / or quantitatively, which differences are then related to the presence or absence of an abnormal gene expression pattern.

[0131] A variety of different methods for determining the nucleic acid abundance in a sample are known to those of skill in the art, where particular methods of interest include those described in: Pietu et al., Genome Res. (June 1996) 6: 492-503; Zhao et al., Gene (April 24, 1995) 156: 207-213; Soares , Curr. Opin. Biotechnol. (October 1997) 8: 542-546; Raval, J. Pharmacol Toxicol Methods (November 1994) 32: 125-127; Chalifour et al., Anal. Biochem (February z, 1994) 216: 299-304; Stolz & Tuan, MoI. Biotechnol. (December 19960 6: 225-230; Hong et al., Bioscience Reports (1982) 2: 907; and McGraw, Anal. Biochem. (1984) 143: 298. Also of interest are the methods disclosed in WO 97 / 27317.

[0132] RNA manipulation techniques are described, for example, in the following references, the entire contents of which are incorporated herein: PureLink (Invitrogen), Trizol reagent (Invitrogen), Stratagene (total and small RNA), TRI-Reagent (Sigma-Aldrich), Nucleospin (Machery-Nagel) and RNA-Bee (Tel-test). Reference [89a].

[0133] The degree to which RNA expression differs need only be large enough to quantify via standard characterization techniques such as expression arrays, RT-qPCR, Northern analysis and RNase protection. Blotting and hybridization assays: [103a,104a]. Microarrays: [105a]. Next generation assays covering all platforms: [107a]. Different ways of assaying expression: Real time PCR, Affymetrix, Agilent, Illumina, and Nanostring. Profiling methods: Agilent microarray, exiqon array, exiqon microarray, miRCURY LNA ncode array, LC Sciences array ABI Taqman array, affymetrix , illumine array, SOLiD ligation sequencing, Illumina HiSeq and TaqMan miR assay. Tools or reagents for assaying for RNA differential expression: SYBR green probes and TaqMan probes. Radiolabeled splinted ligation detection: [110a, 111a].

[0134] Preferably, for one or more methods of the disclosure invention, the level of RNA expression or differential expression can be carried out using: Northern analysis and a probe that specifically binds to the RNA; RNase protection; or, reverse transcription-polymerase chain reaction (RT-PCR) using one or more oligonucleotides / primers that will amplify transcribed RNA. A universal primer can be used in combination with the one or more oligonucleotides / primers that will amplify transcribed RNA. Preferably, RT-qPCR is used. Preferably, the method / s can comprise the step of statistical analysis so as to identify differential expression.

[0135] In some embodiments, RNA can be extracted from plasma using a commercially available kit. The size, quantity and quality of the extracted RNA can be assessed using a small RNA chip on an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA).

[0136] RNA profiling and sequencing can be carried out in any suitable way. Preferably high throughput sequencing (HTS) is utilised. RNA libraries can be constructed using the TruSeq Small RNA Sample Preparation kit (Illumina, San Diego, CA). RNA samples can be ligated with 5' and 3' adapters, followed by reverse transcription-polymerase chain reaction (RT-PCR) for cDNA library construction and incorporation of index tags. The cDNA library fragments can be separated and size fractioned. cDNA library samples can be pooled in equimolar amounts and used for cluster generation and sequence analysis.

[0137] Sequence data that has been generated can be analysed in any suitable way. In some embodiments, raw FASTQ sequences can be generated.

[0138] In some embodiments, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) may be used for expression and comparison.Polypeptide characterisation

[0139] One may screen for polymorphisms at the protein level. Screening for mutations in a polymorphic polypeptide may be based on the functional or antigenic characteristics of the protein. Functional assays include cofactor binding assays, enzyme activity assays, substrate binding assays or surface expression assays. For example, protein truncation assays are useful in detecting deletions that may affect the biological activity of the protein. The activity of the encoded a polymorphic polypeptide may be determined by comparison with a reference polypeptide lacking a specific polymorphism. Alternatively, the three-dimensional structure of the protein may be assayed, for example by fluorescence polarization or circular dichroism spectroscopy, wherein the three-dimensional structure of the encoded a polymorphic polypeptide may be determined by comparison with purified protein carrying the opposing allele of the polymorphism.

[0140] Alternatively, various immunoassays designed to detect polymorphisms in polymorphic polypeptides may be used. The absence or presence of antibody binding to a polymorphic polypeptide may be determined by various methods, including flow cytometry of dissociated cells, microscopy, radiography, scintillation counting, etc. Immunocytochemistry and flow cytometry, particularly fluorescence-activated cell sorting (FACS), can be used to evaluate cell-surface expression of proteins on cells, including on the different types of blood cells.

[0141] Detailed descriptions of how to make antibodies, including antibodies that are specific for epitopes, for example, single amino acid substitutions within epitopes, can be found in a variety of publications, including, e.g. "Making and using Antibodies: A Practical Handbook" (2006) G.C. Howard and M.R. Kaser, eds. CRC Press; "Antibody Engineering: Methods and Protocols" (2004) B.K.C. Lo, ed, Humana Press; and US Patent No. 6,054,632, the disclosure of which is herein incorporated by reference.

[0142] Methods for performing protein sequencing include: Edman degradation; peptide mass fingerprinting; mass spectrometry; and, protease digests. For example, detection may utilize staining of cells or histological sections with labeled antibodies, performed in accordance with conventional methods. Cells are permeabilized to stain cytoplasmic molecules. The antibodies of interest are added to the cell sample, and incubated for a period of time sufficient to allow binding to the epitope, usually at least about 10 minutes. The antibody may be labeled with radioisotopes, enzymes, fluorescers, chemiluminescers, or other labels for direct detection. Alternatively, a second stage antibody or reagent is used to amplify the signal. Such reagents are well known in the art. For example, the primary antibody may be conjugated to biotin, with horseradish peroxidase-conjugated avidin added as a second stage reagent. Alternatively, the secondary antibody conjugated to a fluorescent compound, e.g. fluorescein, rhodamine, Texas red, etc. Final detection uses a substrate that undergoes a color change in the presence of the peroxidase.

[0143] The absence or presence of antibody binding may be determined by various methods, including flow cytometry of dissociated cells, microscopy, radiography, scintillation counting, etc. Detailed descriptions of how to make antibodies can be found in a variety of publications, including, e.g. "Making and using Antibodies: A Practical Handbook" (2006) G.C. Howard and M.R. Kaser, eds. CRC Press; "Antibody Engineering: Methods and Protocols" (2004) B.K.C. Lo, ed, Humana Press.Kits and assays

[0144] The kit or assay for identifying a subject having CFS or at risk of developing CFS can comprise one or more probes, tools or reagents, including nucleic acid oligonucleotides or primers, arrays of nucleic acid probes, antibodies to polymorphic polypeptides (e.g., immobilized on a substrate), signal producing system reagents, labelling and detection means, controls and / or other reagents such as buffers, nucleotides or enzymes e.g. polymerase, nuclease or transferase, depending on the particular protocol to be performed. Other examples of reagents include arrays that comprise probes that are specific for one or more of the genes of interest or one or more polymorphisms thereof, and antibodies to epitopes of the proteins encoded by these genes of interest, wherein the epitope may comprise a polymorphism of interest.

[0145] A kit or assay can include one or more articles and / or reagents for performance of the method, such as means for providing the test sample itself, e.g. a swab for removing cells from the buccal cavity or a syringe for removing a blood sample (such components generally being sterile).

[0146] In addition to the above components, the kits or assay can further include instructions. These instructions may be present in the subject kits in a variety of forms, one form in which these instructions may be present is as printed information on a suitable medium or substrate, e.g., a piece or pieces of paper on which the information is printed, in the packaging of the kit, in a package insert, etc. Yet another form would be a computer readable medium, e.g., diskette, CD, etc., on which the information has been recorded. Yet another form that may be present is a website address which may be used via the internet to access the information at a removed site.Biochip

[0147] The biochip is an apparatus which may be used in conjunction with methods of the invention, in certain embodiments, it comprises a solid substrate comprising an attached probe or plurality of probes / oligonucleotides. The probes may be capable of hybridizing to a target sequence under stringent hybridization conditions. The probes may be attached at spatially defined address on the substrate. More than one probe per target sequence may be used, with either overlapping probes or probes to different sections of a particular target sequence. In an embodiment, two or more probes per target sequence are used. The probes may be capable of hybridizing to different targets, such as a TRP ion channel gene / allele or gene product.

[0148] The probes may be attached to the biochip in a wide variety of ways, as will be appreciated by those of skill in the art. The probes may either be synthesized first, with subsequent attachment to the biochip, or may be directly synthesized on the biochip.

[0149] The solid substrate may be a material that may be modified to contain discrete individual sites appropriate for the attachment or association of the probes and is amenable to at least one detection method. Representative examples of substrates include glass and modified or functionalized glass, plastics (including acrylics, polystyrene and copolymers of styrene and other materials, polypropylene, polyethylene, polybutylene, polyurethanes, Teflon, etc.), polysaccharides, nylon or nitrocellulose, resins, silica or silica-based materials including silicon and modified silicon, carbon, metals, inorganic glasses and plastics. The substrates may allow optical detection without appreciably fluorescing.

[0150] The substrate may be planar, although other configurations of substrates may be used as well. For example, probes may be placed on the inside surface of a tube, for flow-through sample analysis to minimize sample volume. Similarly, the substrate may be flexible, such as a flexible foam, including closed cell foams made of particular plastics.

[0151] The biochip and the probe may be derivatized with chemical functional groups for subsequent attachment of the two. For example, the biochip may be derivatized with a chemical functional group including, but not limited to, amino groups, carboxyl groups, oxo groups or thiol groups. Using these functional groups, the probes may be attached using functional groups on the probes either directly or indirectly using linkers. The probes may be attached to the solid support by either the 5' terminus, 3' terminus, or via an internal nucleotide.

[0152] The probe may also be attached to the solid support non-covalently. For example, biotinylated oligonucleotides can be made, which may bind to surfaces covalently coated with streptavidin, resulting in attachment. Alternatively, probes may be synthesized on the surface using techniques such as photopolymerization and photolithography.

[0153] A variety of hybridization conditions may be used, including high, moderate and low stringency conditions as outlined above. The assays may be performed under stringency conditions which allow hybridization of the probe only to the target. Stringency can be controlled by altering a step parameter that is a thermodynamic variable, including, but not limited to, temperature, formamide concentration, salt concentration, chaotropic salt concentration pH, or organic solvent concentration.

[0154] Hybridization reactions may be accomplished in a variety of ways. Components of the reaction may be added simultaneously, or sequentially, in different orders. In addition, the reaction may include a variety of other reagents. These include salts, buffers, neutral proteins, e.g., albumin, detergents, etc. which may be used to facilitate optimal hybridization and detection, and / or reduce non-specific or background interactions. Reagents that otherwise improve the efficiency of the assay, such as protease inhibitors, nuclease inhibitors and anti-microbial agents may also be used as appropriate, depending on the sample preparation methods and purity of the target.

[0155] Exemplary biochips include an organized assortment of oligonucleotide probes described above immobilized onto an appropriate platform. Each probe selectively binds a nucleic acid target in a sample.

[0156] In accordance with another embodiment, the biochip can also include one or more positive or negative controls. For example, oligonucleotides with randomized sequences can be used as positive controls, indicating orientation of the biochip based on where they are placed on the biochip, and providing controls for the detection time of the biochip.

[0157] Embodiments of the biochip can be made in the following manner. The oligonucleotide probes to be included in the biochip are selected and obtained. The probes can be selected, for example, based on particular SNPs of interest. The probes can be synthesized using methods and materials known to those skilled in the art, or they can be synthesized by and obtained from a commercial source, such as GeneScript USA (Piscataway, N.J.).

[0158] Each discrete probe is then attached to an appropriate platform in a discrete location, to provide an organized array of probes. Appropriate platforms include membranes and glass slides. Appropriate membranes include, for example, nylon membranes and nitrocellulose membranes. The probes are attached to the platform using methods and materials known to those skilled in the art. Briefly, the probes can be attached to the platform by synthesizing the probes directly on the platform, or probe-spotting using a contact or non-contact printing system. Probe-spotting can be accomplished using any of several commercially available systems, such as the GeneMachines(TM) OmniGrid (San Carlos, Calif.).

[0159] Particularly preferred embodiments of the invention are defined in the claims.

[0160] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0161] Other advantages of the invention will become apparent from a reading of this specification.EXAMPLES

[0162] The following examples are illustrative only and should not be construed as limiting in any way the general nature of the disclosure of the description throughout this specification. Examples which lie outside the scope of the invention are included as comparative examples.Example 1: The role of the transient receptor potential (TRP) superfamily in CFS.

[0163] The transient receptor potential (TRP) superfamily in humans comprises 27 cation channels with permeability to monovalent and divalent cations. These channels are widely expressed within humans on cells and tissues, and have significant sensory and regulatory roles in most physiological functions.Methodology Subjects

[0164] The study comprised 115 CFS patients (age=48.68±1.06years) and 90 non-fatigued controls (age=46.48±1.22 years). CFS patients were defined in accordance with the 1994 CDC criteria for CFS [20b]. 10 mL of whole blood samples were collected from all participants into EDTA tubes.DNA Extraction

[0165] Genomic DNA was extracted from all whole blood samples using the Qiagen DNA blood mini-kit as per manufacturer's instructions (Qiagen). The Nanodrop (Nanodrop) was used to assess the quality and quantity of the DNA extracted. Approximately 2 µg of genomic DNA was used in the SNP assay.SNP Genotyping Studies

[0166] SNP analysis was performed by Geneworks using the MassARRAY iPLEX Gold Assay (Sequenom Inc.) as previously described. Customized assays were developed for 240 SNPs across the 21 TRP genes (TRPA1, TRPC1, TRPC2, TRPC3, TRPC4, TRPC6, TRPC7, TRPM1, TRPM2, TRPM3, TRPM4, TRPMS, TRPM6, TRPM7, TRPM8, TRPVI, TRPV2, TRPV3, TRPV4, TRPV5 and TRPV6). Primers and extension primers were created for each of the SNPs using the Assay Designer (Sequenom Inc.) according to the manufacturer's instructions. Briefly, DNA was amplified via PCR under the follow conditions: 94°C for 2 minutes, 94°C for 30 seconds, 56°C for 30 seconds and 72°C for 1 minute. Amplification products were then treated with shrimp alkaline phosphatase (SAP) at 37°C for 40 min, 85°C for 5 min reaction and a final incubation at 4°C. Extension primers were optimized to control signal-to-noise ratio where un-extended primers (UEPs) were examined on the spectroCHIP and evaluated in Typer 4.0 to enable the division into low mass UEP, medium mass UEP and high mass UEP. To perform the iPLEX extension reaction, a mixture containing iPLEX Gold reaction was carried out using iPLEX Gold Buffer Plus, iPLEX termination mix, iPLEX enzyme and primer mix was prepared. iPLEX reaction was cycled at an initial denaturation of 94°C for 30 s, annealing at 52°C for 5 min, extension at 80°C for 5 min (5 cycles of annealing and extension were performed, however the whole reaction was performed in 40 cycles) and extension again at 72°C for 3 min. Resin beads were used to rinse all iPLEX Gold reaction products. Following iPLEX Gold reaction, MassARRAY was performed using the MassARRAY mass spectrometer, the data generated was analysed using the TyperAnalyzer software.Statistical analysis

[0167] The PLINK v1.07 [21b] whole genome analysis tool set was used to determine associations between the CFS patients and the non-fatigued control group. A two column χ2 test was used to determine significance where p value of ≤0.05 was determined to be significant.Results Participants

[0168] Of the 115 CFS patients (age=48.68±1.06 years), 84 (73.04%) were females and 31 (26.96%) were males. The 90 non-fatigued controls (age=46.48±1.22 years) comprised 59 (65.56%) females and 31 (34.44%) males. All participants in the patient and non-fatigued control groups were of European decent and were all residents of Australia at the time of blood collection.SNP Association Studies

[0169] Of the 240 SNPs that were examined in the present study, 233 were successfully identified in both participants groups. Of the 233, thirteen were observed to be significantly associated with CFS (Table 1). Table 1: Analysis of the frequency distribution and significance of TRP Single Nucleotide Polymorphisms (SNPs) in CFS patients and non-fatigued controls in rank order of significance.Gene Chromosome RefSNP ID A1 A2 Frequency_A Frequency_U χ 2< P TRPM39rs12682832AG0.4440.2938.8080.003 TRPM39rs11142508CT0.4450.2988.4380.004 TRPM39rs1160742AG0.4700.3337.0630.008 TRPM39rs4454352CT0.2400.1376.2320.013 TRPM39rs1328153CT0.2400.1376.2320.013 TRPM39rs3763619AC0.4400.3165.9900.014 TRPC413rs6650469TC0.5050.3805.7750.016 TRPC413rs655207GT0.5050.3815.6390.018 TRPA18rs4738202AG0.3690.2535.5910.018 TRPM39rs7865858AG0.4500.3315.3400.021 TRPA18rs2383844GA0.5050.3984.2180.040 TRPM39rs1504401TC0.1000.1734.1720.041 TRPM39rs10115622AC0.3350.4353.8370.050 TRPM419rs10403114GA0.2930.3903.8020.051TRPV317rs9909424GA0.1150.0603.4420.064TRPC413rs612308AG0.4390.5373.3930.065TRPM39rs7860377AC0.3500.2623.3140.069TRPC75rs2673930CA0.2000.2803.2180.073TRPC413rs603955CT0.4450.5363.0080.083TRPM39rs11142798CG0.1350.2022.9980.083TRPM39rs4744611GA0.3600.4462.8430.092TRPM221rs1785452TC0.2150.2892.670.102TRPM39rs1566838GT0.4600.3752.6690.102TRPA18rs1384002TC0.4950.4102.6640.103TRPM69rs2274924GA0.1150.1752.6520.103TRPM39rs1394309GA0.0300.0652.6080.106TRPC413rs2985167GA0.3400.4222.5770.108TRPM511rs2301698GT0.5300.4462.5510.110TRPM69rs944857CT0.1850.1252.4760.116TRPM221rs762426GA0.1600.2232.3250.127

[0170] Nine of these SNPs were associated with TRPM3 (rs12682832; p=0.003, rs11142508; p=0.004, rs1160742; p=0.08, rs4454352; p=0.013, rs1328153; p=0.013, rs3763619; p=0.014, rs7865858; p=0.021, rs1504401; p=0041, rs10115622; p=0.050), while the remainder were associated with TRPA1 (rs2383844; p=0.040, rs4738202; p=0.018) and TRPC4 (rs6650469; p=0.016, rs655207; p=0.018).Discussion

[0171] The purpose of this study was to determine the presence of possible SNP variations in CFS patients with a specific focus on SNPs within the coding sequences of 21 TRP ion channel genes. Out of the 240 SNPs examined, thirteen alleles were found to be significantly associated with CFS patients compared with the non-fatigued controls. These alleles were located in the gene sequence of one of the canonical TRPs ion channels (TRPC4), one ankyrin (TRPA1) and one melastatin TRP ion channel (TRPM3).

[0172] There is limited information available on the role of these SNPs, however TRPs may mediate the potential onset of CFS. TRPC4 is activated via receptor-dependent activation of the G q / 11 / PLC β / γ pathway but also via G αi proteins, PI(4,5)P 2 proteins and also intracellular Ca 2+< [22b]. It is mainly involved in vasomotor function, aggregation of platelets and smooth muscle function. Incidentally, Ca 2+< is known to be required for the regulation of immune cells as Ca 2+< acts as a second messenger for most cells, particularly T cells and B cells. Intracellular Ca 2+< increases when lymphocytes receptors are exposed to antigens [23b]. In CFS patients, there are numerous reports on compromises to immune function although there is limited information on the role of Ca 2+< in these patients. However, dysregulation in TRPCs may affect intracellular calcium concentration and incidentally lymphocyte function. Lymphocytes such as Natural Killer (NK) cells and T cells have been shown to be compromised in CFS. In NK cells, Ca 2+< enhances cytotoxic activity and its depletion or excessive influx may have severe consequences on NK cells function. In CFS reduced cytotoxic activity has been consistently reported [24b-29b] and this may be related to dysregulation in Ca 2+< .

[0173] Dysregulation of TRPCs may affect neuronal responses in particular those associated with the stimulation of muscarinic receptors. Following activation of TRPCs by PLCs an influx of Ca 2+< occurs causing an induction in muscarinic receptors, and maintained incessant neuronal firing [30b, 31b]. Hence, secretion of Ca 2+< and availability of TRPCs in the neuronal environment is paramount to optimal muscarinic receptor function and overall function of the brain. Importantly, this process is essential for memory, attention, sensory acuity, emotion, pain and motor control [32b, 33b] and occurs in the amygdala, entorhinal cortex, hippocampus and prefrontal cortex [34b]. Neuronal deficits involving memory and attention have been identified in CFS [35b-37b]. Deletion or compromises to TRPC4 may also affect intestinal function. TRPC4 and TRPC6 pair with muscarinic receptors in the intestine activating smooth muscle depolarization, inflow of Ca 2+< and smooth muscle contraction [38b]. Intestinal dysfunction is a component of CFS [39b], however the extent of damage to the intestinal wall or the exact role of ion channels in the intestine remains to be determined. TRPC4 may be simultaneously regulated by G protein coupled receptors (GPCRs) Gαi and Gαq [40b].

[0174] TRPA1 is a multiple chemical receptor that has been identified on nociceptive sensory neurons (C fibers) and has a role in the regulation of the release of neuropeptides, pain sensation and inflammation [41b]. It may be activated by both exogenous and endogenous inflammatory agents resulting in inflammation and pain [42b]. GPCRs also activate TRPA1 via PLC signalling sensitising the ion channel to various stimuli [43b]. TRPA1 may be activated and subsequently inactivated in the presence of intracellular and extracellular calcium concentrations [44b, 45b]. TRPA1 gene has been proposed to affect sensitivity to nociceptive stimuli [46b], hence CFS patients expressing SNPs in the TRPA1 gene may increase their sensitivity to nociceptive stimuli. In the CNS astrocytes express TRPA1 channels and these channels are necessary for calcium uptake and neuronal regulation in the astrocytes. Changes in the level of calcium may therefore affect the function of astrocytes and interneuron communication [45b, 47b]. Activation of TRPA1 has been shown to induce acute headache and this may occur through the calcitonin gene related peptide (CGRP) causing vasodilation in the meningeal artery [45b, 48b]. Importantly, headache is a prominent symptom of CFS. TRPA1 is also a key player in migraine, neuropathic, joint and muscle pain which is most often experienced by patients with fibromyalgia [49b, 50b]. TRPA1 forms functional heterotetramers with TRPV1 hence variations in the TRPA1 gene may suggest functional deficits to TRPV1 that may not be related to polymorphism in nucleotides [51b]. Analgesics and antinociceptive drugs target TRPV1 and TRPA1 respectively to alleviate pain sensation [52b-54b] and these drugs are routinely prescribed to CFS patients. Perhaps in CFS these drugs may not be effective due to impairments or variations in these ion channels.

[0175] TRPM channels are mostly permeable to magnesium and calcium. Only TRPM4 and TRPM5 are impermeable for divalent cations. TRPM3 is permeable for cations including Ca 2+< and Zn 2+< . However, the permeation profile highly depends on the expressed spliced variant [55b]. No hereditary TRPM3 channelopathy has been described to date. TRPM3 has been implicated in inflammatory pain syndromes, rheumatoid arthritis, and secretion of proinflammatory cytokines. As pancreatic β cells also have a high proportion of TRPM3 channels [45b, 56b-58b], there is the likelihood of perturbations in insulin / glucose regulation in CFS patients. Metabolic disturbance has also long been identified as a cardinal feature of CFS. The most characterised TRPM3 in humans is in the central nervous system (CNS) and eye [55b]. TRPM3 is involved in the detection of heat and in pain transmission. TRPM3-deficient mice exhibit clear deficits in their avoidance responses to noxious heat and in the development of inflammatory heat hyperalgesia [55b]. Dysregulation in thermoregulatory responses has been reported in CFS patients [59b]. Generalised pain is a characteristic of CFS and occurs in the absence of tissue damage and this is suggestive of potential CNS impairments [60b]. As TRPM3 has a role in nociception and thermoregulation, it may have a role in the pathomechansim of CFS. Additionally, TRPM3 is activated by pregnenolone sulfate suggesting that it has neuroendocrine effects [61b, 62b] and might also be involved in the regulation of glutamatergic signalling in the brain [63b].

[0176] These findings implicate TRP ion channels (predominantly TRPM3) in the aetiology and pathomechanism of CFS. Dysregulation of TRPs, including the TRPM3 family, is likely pertinent in predisposing CFS patients to calcium metabolism perturbations and aligns with symptom presentation. Potentially, dysregulated influx of calcium ions into cells will impact a number of vital components of cell regulatory machinery. These components include calcium sensitive adenylate cyclases (ACs) and hence cAMP expression and function.Example 2: The role of ACh Receptor (nAChRs and mAChRs) SNPs in CFS / ME. Methodology Subjects

[0177] The study comprised 115 CFS / ME patients (age=48.68±1.06years) and 90 non-fatigued controls (age=46.48±1.22 years). CFS patients were defined in accordance with the 1994 CDC criteria for CFS [36c]. Avolume of 10 mL of whole blood was collected from all participants into EDTA tubes.DNA Extraction

[0178] Genomic DNA was extracted from all whole blood samples using the Qiagen DNA blood mini-kit as per manufacturer's instructions (Qiagen). Quality and quantity of the DNA extracted was determined by the Nanodrop (Nanodrop), where approximately 2 µg of genomic DNA was used to perform the SNP assay.SNP Genotyping Studies

[0179] A total of 464 single nucleotide polymorphisms (SNPs) for nine mammalian ACh receptor genes (M1, M2, M3, M4, M5, alpha 2, 5, 7 and 10) were examined via the Agena Biosciences iPLEX Gold assay. Geneworks completed the SNP analysis as previously defined (MassARRAY iPLEX Gold Assay) [37c]. Customized assays were developed for 464 SNPs across the 9 mammalian acetylcholine receptor genes (M1, M2, M3, M4, M5, alpha 2, 5, 7 and 10). Primers and extension primers were created for each of the SNPs using the Assay Designer [37c] according to the manufacturer's instructions. The amplification of the DNA was as previously described. Briefly, DNA was amplified via PCR under the follow conditions 94°C for 2 minutes, 94°C for 30 seconds, 56°C for 30 seconds and 72°C for 1 minute. Amplification products were then treated with shrimp alkaline phosphatase (SAP) at 37°C for 40 min, 85°C for 5 min reaction and a final incubation at 4°C. Extension primers were optimized to control signal-to-noise ratio where un-extended primers (UEPs) were examined on the spectroCHIP and evaluated in Typer 4.0 to enable the division into low mass UEP, medium mass UEP and high mass UEP. To perform the iPLEX extension reaction, a mixture containing iPLEX Gold reaction was carried out using iPLEX Gold Buffer Plus, iPLEX termination mix, iPLEX enzyme and primer mix was prepared. iPLEX reaction was cycled at an initial denaturation of 94°C for 30 s, annealing at 52°C for 5 min, extension at 80°C for 5 min (5 cycles of annealing and extension were performed, however the whole reaction was performed in 40 cycles) and extension again at 72°C for 3 min. Resin beads were used to rinse all iPLEX Gold reaction products. Following iPLEX Gold reaction, MassARRAY was performed using the MassARRAY mass spectrometer, the data generated was analysed suing the TyperAnalyzer software.Statistical analysis

[0180] The PLINK v1.07 [39c] whole genome analysis tool set was implemented to determine associations between the CFS patients and the non-fatigued control group. A two column χ2 test was used where alpha level of significance was set at p value of ≤0.05.Results Participants

[0181] Of the 115 CFS patients (age=48.68±1.06 years), 84 (73.04%) were females and 31 (26.96%) were males. 90 non-fatigued controls (age=46.48±1.22 years) comprised 59 (65.56%) females and 31 (34.44%) males. All participants in both groups were of European decent. All were residents of Australia at the time of blood collection.SNP Association Studies

[0182] Of the 464 SNPs that were examined in the present study, 393 were successfully identified in both participants groups. Of the 393, seventeen were observed to be significantly associated with CFS (Table 2). Table 2: Analysis of the frequency distribution and significance of acetylcholine receptor Single Nucleotide Polymorphisms (SNPs) in CFS patients and non-fatigued controls in rank order of significance.Gene Chromosome RefSNP ID A1 Frequency_A Frequency_U A2 χ 2< p mAchM31rs4463655T0.30770.4671C8.9320.00mAchM31rs589962C0.24160.3919T8.5390.00mAchM31rs1072320G0.32420.1842A8.4230.00mAchM31rs7543259A0.31870.1842G7.8340.01mAchM31rs6661621C0.30220.1711G7.7550.01nAchα1011rs2672211C0.37360.2434T6.5150.01nAchα1011rs2672214C0.37080.24T6.4980.01nAchα515rs951266T0.39440.2632C6.3820.01nAchα1011rs2741868T0.36930.24A6.3330.01nAchα1011rs2741870G0.37080.2434C6.1950.01nAchα28rs2565048C0.09890.1933T6.0340.01mAchM31rs7520974G0.42050.5533A5.7270.02mAchM31rs726169G0.28330.4013A5.1320.02mAchM31rs6669810G0.42130.5467C5.1230.02nAchα1011rs2741862C0.28570.1842T4.6850.03nAchα515rs7180002T0.38460.2763A4.3590.043mAchM31rs6429157G0.5220.4079A4.3270.04nAchα28rs55828312G0.23860.1513A3.9140.05nAchα515rs2175886c0.49440.3867T3.8470.05mAchM31rs12036141A0.41210.3092G3.7810.05mAchM31rs6429147C0.44440.34G3.7280.05mAchM31rs1594513G0.21980.3133T3.7220.05nAchα28rs16891561T0.24720.1597C3.6960.05nAchα1011rs2672215A0.46070.36C3.3990.07nAchα28rs6474413C0.23080.1513T3.3360.07mAchM31rs10926008G0.37220.277A3.3330.07nAchα28rs2741343C0.53370.4324T3.3170.07nAchα515rs7178270G0.35710.4539C3.2310.07nAchα515rs4243084G0.39770.3026C3.2270.07nAchα515rs601079A0.39010.4868T3.1550.08nAchα515rs12911602C0.39010.4868T3.1550.08nAchα515rs588765T0.38460.4803C3.0950.08nAchα515rs680244A0.38460.4803G3.0950.08nAchα515rs6495306G0.38950.4863A3.010.08nAchα515rs6495307T0.41110.5068C2.9970.08mAchM31rs12093821A0.4890.3947G2.9790.08mAchM31rs16838637G0.48890.3947A2.9570.09nAchα28rs6997909A0.23330.1579G2.9450.09nAchα1011rs2672216C0.48880.3947T2.9340.09mAchM31rs6429165A0.24730.1711G2.8730.09nAchα28rs891398C0.5330.4392T2.8720.09nAchα515rs4366683G0.39560.4868A2.8020.09nAchα28rs6985052C0.23080.1579T2.7740.10nAchα28rs4950C0.23080.1579T2.7740.10

[0183] Seventeen SNPs were significantly associated with CFS / ME patients compared with the controls. Nine of these SNPs were associated with mAChRM3 (rs4463655; p=0.00, rs589962; p=0.00, rs1072320; p=0.00, rs7543259; p=0.01, rs6661621; p=0.01 rs7520974; p=0.02, rs726169; p=0.02, rsrs6669810; p=0.02, rsrs6429157; p=0.04), while the remainder were associated with nACh alpha 10 (rs2672211; p=0.01, rs2672214; p=0.01, rs2741868; p=0.01, rs2741870; p=0.01, rs2741862; p=0.03) alpha 5 (rs951266; p=0.012; rs7180002, p=0.04) and alpha 2 (rs2565048; p=0.01).Discussion

[0184] This study revealed a number of AChR SNP variations in CFS / ME patients. Specifically, within the coding sequences of nine AChR genes out of 464 SNPs examined, 17 significant alleles associated with CFS / ME patients were found compared with the non-fatigued controls. Moreover these alleles were located in the gene sequence of one of the muscarinic acetylcholine receptors (mAChRM3) and three nicotinic acetylcholine alpha receptors (nAChRα2, nAChRα5 and nAChRα10). Interestingly, in Example 1 the inventors identified a number of SNPs in the TRP family, namely TRPC4. The significance of SNPs in mAChRM3 and TRPC4 is that the latter couples to mAChRM3 and can be activated by ACh [40c-42c].

[0185] There is limited information available on the role of these AChR SNPs, however the role of ACh in calcium (Ca 2+< ) cell signalling suggests these AChRs may mediate, in part, the clinical expression of CFS / ME. Moreover, the inventors have shown in Example 1 significant SNPs in the TRP ion channel family, namely TRPA1, TRPM3 and TRPC4, using the same cohort of CFS / ME patients. These findings suggest the potential for significant aberrations in Ca 2+< cell signalling possibly reflected in the clinical presentation of CFS / ME patients.

[0186] mAChR receptors are responsible for initiating smooth muscle contraction, such as in the gastrointestinal and genitourinary tracts, as well as effects in immune cells, epithelial, ovarian and ocular skin cells, respiratory and secretory glands [43c-46c, 33c, 34c, 32c, 47c-52c, 35c, 5c]. nAChRs are also reported on T and B lymphocytes [53c, 54c]. Human T lymphocytes express the α3, α4, α7, β2 and β4 receptor subunits [55c] while in the mouse and human thymus mAChR expression has been found to play a role in T lymphocyte development and proliferation [53c, 56c-58c]. The α4 or α7 subunits have also been reported on B lymphocytes and found to stimulate proliferation, while decreasing antibody production [59c]. Such findings provide possible insight regarding the SNPs characterised in this Example noting that previous investigations have reported compromise to immune function in CFS / ME patients. Significantly, changes in numbers and function of lymphocytes such as Natural Killer (NK) lymphocytes, T and B lymphocytes in these studies suggests increased influx of Ca 2+< .

[0187] The mAChRM3 receptors are located in the gastrointestinal tract and are controlled in part by the parasympathetic nervous system, through the vagus nerve [60c]. Where nerve fibres make synapse within the gut wall, the main neurotransmitter, acetylcholine, usually stimulates GI motility. Moreover, clinical data reports nAChRs are involved in inflammatory bowel disease [61c]. Dysregulation of Ca 2+< mediated channels such as influx or reduction of Ca 2< flow could cause significant changes in GI motility. CFS / ME patients often exhibit gastrointestinal associated issues, such as irritable bowel syndrome and constipation [12c, 28c].

[0188] Dysregulation of mAChRM3 receptors may affect metabolic and cardiac responses. In normal pancreas, mAChRM3 receptors play a role in regulating insulin and glucagon secretion [62c, 63c]. Muscarinic acetylcholine receptors expressed by pancreatic β-cells have been reported to play a significant role in maintaining proper insulin release and in maintaining whole body glucose homeostasis [62c]. Changes in Ca 2+< mediated channels may result in adverse glucose metabolic outcomes as implied in CFS / ME patients [64c]. AChR SNPs in CFS patients will likely affect Ca 2+< modulation in intracellular pathways through the influx of Ca 2+< ions. Pancreatic β-cells rely on a transient decrease in Ca 2+< to initiate the complex sequence of events resulting in insulin secretion following glucose exposure. Hellman et al. [65c] report that elevation of glucose induces transient inhibition of insulin release by lowering cytoplasmic Ca 2+< below baseline in pancreatic β-cells. This period was found to coincide with increased glucagon release and hence was asserted to be the starting point for anti-synchronous pulses of insulin and glucagon. They conclude that the period of initial decrease of cytoplasmic calcium ion concentration regulates the subsequent β-cell response to glucose. Thus it may be argued that aberrant elevated intracellular Ca 2+< concentrations through permissive TRP and AChR activity will impede the usual and necessary sequence of events required to initiate insulin response to glucose in CFS patients.

[0189] Cardiac mAChRM3 receptors perform an array of pathological and physiological functions. mAChM2 is not the only muscarinic receptor involved in cardiac function, rather mAChRM3 parasympathetic control of cardiac function is well established [66c]. A report by van Borren et al. [67c] shows the effect of muscarinic AChR stimulation on Ca 2+< transients, cAMP production and pacemaker frequency in sinoatrial (SA) nodes of the rabbit. They found that the pacemaker slowing effects of muscarinic agonists are augmented by Ca 2+< transient inhibition, suggesting a negative chronotropic effect of muscarinic agonists is, in part, obtained by Ca 2+< transient inhibition and subsequent reduction in cAMP. These findings imply that muscarinic agonism will have an effect on SA node function exacerbating disturbances of proper cardio-regulatory mechanisms, particularly in an environment where Ca 2+< intracellular concentrations are likely to be altered due to direct effects of receptor activity. Clinical consequences such as altered orthostatic cardiovascular responses could be predicted and could align with symptom presentation in CFS / ME [13c, 21c, 25c, 27c, 29c].

[0190] In the vascular system, the endothelium contains nAChRs, including α3, α5, α7, α10, β2, β and β4 [68c, 48c, 69c]. Depending upon the type of smooth muscle a specific subtype of nAChR is present; α3 and α5 are found in arteries, while α7 is widespread, although not present in the renal circulatory system. nAChR α5, α7, β2 and β3 have been found in brain endothelial cells [70c] and are an important component of the blood-brain barrier (BBB). nAChR receptor assembly is important for ion permeability and desensitisation. nAChR α7 subunits are known to desensitise rapidly as well as have a high Ca 2+< :Na +< permeability. A combination of α7 with α5 nAChR subunits results in receptors with distinct desensitisation properties and ion permeability relative to the homomeric α7 nAChR [71c, 72c]. More dramatic changes in nAChR channel kinetics are observed when the α5 nAChR subunit incorporates into receptors with the α3 and β4 nAChR subunits, suggesting subunit conformations may impact on functional properties [73c, 74c] of these receptors. This current Example identified SNPs in α5 and α3 nAChR subunits, implying anomalies of signal transduction in the inventor's patient cohort. nAChRs are reported to be involved in arousal, sleep and fatigue as well as those functions that are responsible for processing of pain, memory and cognition [75c-77c].

[0191] Voltage-gated Ca 2+< -selective channels (CaVs) and intracellular Ca 2+< Signalling Networks and nonselective ion channels are known to play a significant role in cell integrity, function and cell cycle. The results in this current Example suggest there is an intrinsic role between SNPs of both TRP and ACh receptors that may underpin CFS / ME pathology.

[0192] Adenylate cyclases (AC) are critical in producing cAMP from ATP through a non-redundant mechanism. Ca 2+< promotes cAMP production via the Ca 2+< sensitive AC1 in the guinea pig sinoatrial (SA) node, although the role of the other Ca 2+< -stimulated AC subtype (AC8), in the guinea pig SA node is uncertain [78c]. The five muscarinic ACh receptors (M(1)-M(5)) are differentially expressed in the brain. M(2) and M(4) are coupled to inhibition of stimulated adenylyl cyclase, while M(1), M(3) and M(5) are mainly coupled to the phosphoinositide pathway [79c]. However as ACh is largely mediated through Ca 2+< the question is raised as to whether permissive influx of Ca 2+< occurs through TRP and AChR SNPs and whether this combination of factors may result in dysregulation of AC activity and cAMP / Ca 2+< interactions. Support for this argument is highlighted where TRPC4 couples to mAChRM3 and is activated by ACh [40c-42c].

[0193] A key component of AC regulation and cAMP production is achieved through two AC stimulating vasoactive neuropeptides, namely vasoactive intestinal peptide (VIP) and the pituitary adenylate cyclase activating polypeptide (PACAP). In cardiac neurons which express TRPC transcripts, PACAP activates calcium-permeable non-selective cationic channels, which are likely members of the TRPC family [80c]. Inhibition of intracellular calcium increases by the application of calcium channel blockers indicates that PACAP acts on calcium influx [81c]. Notably it is calcium ion influx, not release from calcium ion stores, which is required for PACAP-induced increase in excitability in guinea pig intra-cardiac neurons. Importantly, the expression of PACAP genes is controlled by calcium and cAMP signals in neurons, suggesting that dysregulated calcium influx into cells will have effects on PACAP expression. The activity-dependent gene expression is jointly controlled by Ca 2+< and cAMP signals not only at the transcriptional level but also at the post-translational level for the cumulative mRNA expression in neurons [82c]. Earlier research has shown in isolated NK lymphocytes a significant increase in VPAC1R numbers for CFS / ME patients compared with controls [15c]. An increase in VPAC1R numbers found on these lymphocytes may have occurred to compensate for impaired AC and cAMP signalling.

[0194] In conclusion, the inventors report for the first time the presence of SNPs in receptors for ACh (predominantly M3 and CFS) and in association with TRP SNPs in patients with CFS / ME. Many detrimental consequences for physiological homeostasis are possible through aberrant ACh and TRP function in these patients. These scenarios conceivably are associated with CFS / ME pathomechanisms and symptomatology and require further investigation.Example 3 - Non-Synonymous Single Nucleotide Polymorphisms in AChR and TRP in Myalgic Encephalomyelitis / Chronic Fatigue Syndrome

[0195] In Examples 1 and 2 the inventors identified single nucleotide polymorphisms (SNPs) in genes for transient receptor potential (TRP) ion channels and acetylcholine receptors (AChRs), which have important roles in calcium (Ca 2+< ) and acetylcholine (ACh) signalling. Non-synonymous single nucleotide polymorphisms (nsSNPs) are those SNPs resulting in changes to protein expression of these receptors which may be responsible for aberrant signalling and hence potentially change of function.

[0196] In this Example the inventors determine that nsSNPs are present in those SNPs previously identified in TRP ion channel and AChR genes in CFS / ME patients.Method Subjects

[0197] CFS patients were defined in accordance with the 1994 CDC criteria for CFS [32d]. 115 CFS / ME patients (age=48.68±1.06 years) and 90 non-fatigued controls (age=46.48±1.22 years) were examined for nsSNPs in genes for TRP ion channels and AChRs.Blood collection and DNA extraction

[0198] A volume of 10 mL of whole blood was collected from all participants into EDTA tubes. Genomic DNA was extracted from all whole blood samples using the Qiagen DNA blood mini-kit as per manufacturer's instructions (Qiagen). SNP genotyping studies were performed as previously described.nsSNP analysis

[0199] A total of 81 SNPs were examined in the present study: 53 nsSNPs for four AChR genes (M3, and alpha 2, 5 and 10) and 28 nsSNPs for TRP ion channel genes (TRPA1, TRPC4, TRPM3 and TRPM4).nsSNP Statistical analysis

[0200] All 81 SNPs resulting from the PLINK analysis with p values of < 0.1, were taken and used as input into the Variant Effect Predictor, to determine the effect of the variants. The resulting variants set at an alpha level of p<0.05 and their consequences can be found in Table 3-4 and 5-6 for TRP and AChR, respectively. Analyses were performed at the Australian Genome Research Facility Ltd, The Walter and Eliza Hall Institute, Parkville, Victoria, Australia. Table 3: Frequency distribution and significance of Transient Receptor Potential (TRP) nsSNPs in CFS / ME patients and non-fatigued controls in rank order of significance.CHR SNP BP A1 F_A F_U A2 P Location Allele Consequence IMPACT Gene Feature_type Feature BIOTYPE HGVSc 9rs1268283270605775A0.44440.2927G0.0029999:70605775-70605775Gintron_variantMODIFIER80036TranscriptNM_020952.4protein_codingNM_020952.4:c.2173-2305N>C9:70605775-70605775Gintron_variant,non_coding_traMODIFIER101927086TranscriptXR_428546.1lncRNAXR_428546.1 n.1265-1283N>G9:70605775-70605775Gintron_variantMODIFIER80036TranscriptNM_001007471.2protein_codingNM_001007471.2 c.2632-2305N>C9:70605775-70605775Gintron_variantMODIFIER80036TranscriptNM_206946.3protein_codingNM_206946.3:c.2248-2305N>C9:70605775-70605775Gdownstream_gene_variantMODIFIER101927086TranscriptXR_242612.2lncRNA-9:70605775-70605775Gintron_variantMODIFIER80036TranscriptNM_206944.3protein_codingNM_206944.3:c.2143-2305N>C9:70605775-70605775Gintron_variantMODIFIER80036TranscriptNM_024971.5protein_codingNM_024971.5:c.2209-2305N>C9:70605775-70605775Gintron_variantMODIFIER80036TranscriptNM_206947.3protein_codingNM_206947.3:c.2218-2305N>C9:70605775-70605775Gintron_variantMODIFIER80036TranscriptXM_005252218.2protein_codingXM_005252218.2:¢.2713-2305N>C9:70605775-70605775Gintron_variantMODIFIER80036TranscriptNM_206945.3protein_codingNM_206945.3:c.2179-2305N>C9rs1114250870616746C0.4450.2976T0.0036759:70616746-70616746Tintron_variantMODIFIER80036TranscriptNM_020952.4protein_codingNM_020952.4:c.1864-671N>A9:70616746-70616746Tintron_variantMODIFIER80036TranscriptNM_001007471.2protein_codingNM_001007471.2 c.2323-671N>A9:70616746-70616746Tintron_variantMODIFIER80036TranscriptNM_206946.3protein_codingNM_206946.3:¢.1939-671N>A9:70616746-70616746Tintron_variantMODIFIER80036TranscriptNM_206944.3protein_codingNM_206944.3:¢.1834-671N>A9:70616746-70616746Tintron_variantMODIFIER80036TranscriptNM_024971.5protein_codingNM_024971.5:¢.1900-671N>A9:70616746-70616746Tintron_variantMODIFIER80036TranscriptNM_206947.3protein_codingNM_206947.3:¢.1909-671N>A9:70616746-70616746Tintron_variantMODIFIER80036TranscriptXM_005252218.2protein_codingXM_0052522182:c2404-671N>A9:70616746-70616746Tintron_variantMODIFIER80036TranscriptNM_206945.3protein_codingNM_206945.3:c.1870-671N>A9rs116074270699095A0.470.3333G0.0078719:70699095-70699095Gintron_variantMODIFIER80036TranscriptNM_020952.4protein_codingNM_020952.4:c.814-1751 7N>C9:70699095-70699095Gintron_variantMODIFIER80036TranscriptNM_001007471.2protein_codingNM_001007471.2 c.1273-17517N>C9:70699095-70699095Gintron_variantMODIFIER80036TranscriptNM_206946.3protein_codingNM_206946.3:c.889-1751 7N>C9:70699095-70699095Gintron_variantMODIFIER80036TranscriptNM_206944.3protein_codingNM_206944.3:c.814-17517N>C9:70699095-70699095Gintron_variantMODIFIER80036TranscriptNM_024971.5protein_codingNM_024971.5:c.814-17517N>C9:70699095-70699095Gintron_variantMODIFIER80036TranscriptNM_206947.3protein_codingNM_206947.3:c.889-17517N>C9:70699095-70699095Gintron_variantMODIFIER80036TranscriptXM_005252218.2protein_codingXM_005252218 2 :c13 54 -17517N>C9:70699095-70699095Gintron_variantMODIFIER80036TranscriptNM_206945.3protein_codingNM_206945.3:c.814-1751 7N>C9rs445435270795494C0.240.1369T0.012549:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_020952.4protein_codingNM_020952.4:c.515-11215N>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_001007470.1protein_codingNM_001007470.1 c.590-11215N>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_001007471.2protein_codingNM_001007471.2 c.974-11215N>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_206948.2protein_codingNM_206948.2:c.515-11215N>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_206946.3protein_codingNM_206946.3:c.590-11215N>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_206944.3protein_codingNM_206944.3:c.515-11215N>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_024971.5protein_codingNM_024971.5:c.515-11215N>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_206947.3protein_codingNM_206947.3:¢.590-1121 SN>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptNM_206945.3protein_codingNM_206945.3:c.515-11215N>A9:70795494-70795494Tintron_variantMODIFIER80036TranscriptXM_005252218.2protein_codingXM_005252218 2 :c1055-11215N>A Table 4: Frequency distribution and significance of Transient Receptor Potential (TRP) nsSNPs in CFS / ME patients and non-fatigued controls in rank order of significance. CHR SNP BP A1 F_A F_U A2 PLocation Allele Consequence IMPACT Gene Feature_type Feature BIOTYPE HGVSc 13rs665046937793812T0.5050.3795C0.0162513:37793812-37793812Tintron_variantMODIFIER7223TranscriptNM 016179.2protein_codingNM_016179.2:c.-27-10452N>A13:37793812-37793812Tintron_variantMODIFIER7223TranscriptNM 003306.1protein_codingNM_0033061:c-27-10452N>A13:37793812-37793812Tintron_variantMODIFIER7223TranscriptNM_001135958.1protein_codingNM_0011359581:c-27-10452N>A13:37793812-37793812Tintron_variantMODIFIER7223TranscriptNM_001135955.1protein_codingNM_0011359551:c-27-10452N>A13:37793812-37793812Tintron_variantMODIFIER7223TranscriptNM_001135956.1protein_codingNM_0011359561:c-27-10452N>A13:37793812-37793812Tintron_variantMODIFIER7223TranscriptNM_001135957.1protein_codingNM_001135957.1: c.-27-10452N>A13rs65520737793875G0.50510.381T0.0175713 37793875-37793875Tintron_variantMODIFIER7223TranscriptNM 016179.2protein_codingNM_016179.2:c.-27-10515N>A13:37793875-37793875Tintron_variantMODIFIER7223TranscriptNM 003306.1protein_codingNM_003306.1:c.-27-10515N>A13:37793875-37793875Tintron_variantMODIFIER7223TranscriptNM_001135958.1protein_codingNM_001135958.1:c.-27-10515N>A13:37793875-37793875Tintron_variantMODIFIER7223TranscriptNM_001135955.1protein_coding13 37793875-37793875Tintron_variantMODIFIER7223TranscriptNM_001135956.1protein_codingNM_001135956.1:c.-27-10515N>A13 37793875-37793875Tintron_variantMODIFIER7223TranscriptNM_001135957.1protein_codingNM_001135957.1:c.-27-10515N>A8rs473820272028626A0.36870.253G0.018068:72028626-72028626Gintron_variant,non_coding_traj MODIFIERMODIFIER100132891TranscriptNR 033652.1lncRNANR_033652.1 n.1029-23913N>G8:72028626-72028626Gintron_variant,non_coding_traj MODIFIERMODIFIER100132891TranscriptNR_033651.1lncRNANR_033651.1:n.434-23913N>G8:72028626-72028626Gintron_variantMODIFIER8989TranscriptNM 007332.2protein_codingNM_007332.2:c.2937+1275N>C9rs786585870589515A0.450.3313G0.020849:70589515-70589515Gintron_variantMODIFIER80036TranscriptNM_020952.4protein_codingNM_020952.4:c.2728+1516N>C9:70589515-70589515Gintron_variantMODIFIER80036TranscriptNM_001007471.2protein_codingNM_001007471.2:c.3187+1516N>C9:70589515-70589515Gintron_variantMODIFIER80036TranscriptNM_206946.3protein_codingNM_206946.3:c.2803+1516N>C9:70589515-70589515Gintron_variantMODIFIER80036TranscriptNM_206944.3protein_codingNM_206944.3:c.2698+1516N>C9:70589515-70589515Gintron_variantMODIFIER80036TranscriptNM_024971.5protein_codingNM_024971.5:c.2764+1516N>C9:70589515-70589515Gintron_variantMODIFIER80036TranscriptNM_206947.3protein_codingNM_001135955.1:c.-27-10515N>A NM_206947.3:c.2773+1516N>C9:70589515-70589515Gintron_variantMODIFIER80036TranscriptXM_005252218.2protein_codingXM_005252218.2:c.3268+1516N>C9:70589515-70589515Gintron_variantMODIFIER80036TranscriptNM_206945.3protein_codingNM_206945.3:c.2734+1516N>C9:70589515-70589515Gregulatory_region_variantMODIFIER-RegulatoryFeatureENSR00001471087promoter_flanking_region-8rs238384472049017G0.5050.3976A0.039998:72049017-72049017Aintron_variant,non_coding_traj MODIFIERMODIFIER100132891TranscriptNR _033652.1lncRNANR_033652.1 n.1029-3522N>A8:72049017-72049017Aintron_variant,non_coding_traj MODIFIERMODIFIER100132891TranscriptNR_033651.1lncRNANR_033651.1:n.434-3522N>A8:72049017-72049017Aintron_variantMODIFIER8989TranscriptNM 007332.2protein_codingNM_007332.2:c.1905+1761N>T9rs150440171302037T0.10.1726C0.041119:71302037-71302037Cintron_variantMODIFIER80036TranscriptXM_005252218.2protein_codingXM_005252218.2:c.183+144616N>G9rs1011562270691635A0.3350.4345C0.050149:70691635-70691635Aintron_variantMODIFIER80036TranscriptNM_020952.4protein_codingNM_020952.4:c.814-10057N>T9:70691635-70691635Aintron_variantMODIFIER80036TranscriptNM_001007471.2protein_codingNM_001007471.2:c.1273-10057N>T9:70691635-70691635Aintron_variantMODIFIER80036TranscriptNM_206946.3protein_codingNM_206946.3:c.889-10057N>T9:70691635-70691635Aintron_variantMODIFIER80036TranscriptNM_206944.3protein_codingNM_206944.3:c.814-10057N>T9:70691635-70691635Aintron_variantMODIFIER80036TranscriptNM_024971.5protein_codingNM_024971.5:c.814-10057N>T9:70691635-70691635Aintron_variantMODIFIER80036TranscriptNM_206947.3protein_codingNM_206947.3:c.889-10057N>T9:70691635-70691635Aintron_variantMODIFIER80036TranscriptXM_005252218.2protein_codingXM_005252218.2:c.1354-10057N>T9:70691635-70691635Aintron_variantMODIFIER80036TranscriptNM_206945.3protein_codingNM_206945.3:c.814-10057N>T19rs1040311449200507G0.29290.3902A0.0511919:49200507-49200507Gintron_variantMODIFIER54795TranscriptXM 005259017.1protein_codingXM_005259017.1:c.1491+75N>G19:49200507-49200507Gintron_variantMODIFIER54795TranscriptNM001195227.1protein_codingNM_0011952271:c2343+ 75N>G19:49200507-49200507Gintron_variantMODIFIER54795TranscriptXM 005259018.1protein_codingXM_005259018.1:c.1170+75N>G19:49200507-49200507Gintron_variantMODIFIER54795TranscriptXM 006723249.1protein_codingXM_006723249.1:c.2523+75N>G19:49200507-49200507Gintron_variantMODIFIER54795TranscriptNM_017636.3protein_codingNM_017636.3:c.2778+75N>G Table 5: Frequency distribution and significance of acetylcholine receptor (AChR) nsSNPs in CFS / ME patients and non-fatigued controls in rank order of significance. CHR SNP BP A1 F_A F_U A2 P Location Allele Consequence IMPACT Gene Feature_type Feature BIOTYPE HGVSc 3rs4463655239820994T0.30770.4671C0.0028031:239820994-239820994Cintron_variantMODIFIER1131TranscriptXM_005273033.1protein_codingXM_005273033.1:c.-146-6258T>C1:239820994-239820994Cintron_variantMODIFIER1131TranscriptXM _005273032.1protein_codingXM_005273032.1:c.-146-6258T>C1:239820994-239820994Cintron_variantMODIFIER1131TranscriptXM_006711732.1protein_codingXM_006711732.1:c.-19-86439T>C1:239820994-239820994Cintron_variantMODIFIER1131TranscriptNM _000740.2protein_codingNM_000740.2:c.-146-6258T>C3rs589962239826664C0.24160.3919T0.0034761:239826664-239826664Cintron_variantMODIFIER1131TranscriptXM_005273033.1protein_codingXM_005273033.1:c-146-588T>C1:239826664-239826664Cintron_variantMODIFIER1131TranscriptXM_005273032.1protein_codingXM_005273032.1:c-146-588T>C1:239826664-239826664Cupstream gene _variantMODIFIER1131TranscriptXM_005273034.1protein_coding1:239826664-239826664Cintron_variantMODIFIER1131TranscriptXM_006711732.1protein_codingXM_006711732.1:c.-19-80769T>C1:239826664-239826664Cintron_variantMODIFIER1131TranscriptNM _000740.2protein_codingNM_000740.2:c.-146-588T>C3rs1072320239819076G0.32420.1842A0.0037041:239819076-239819076Gintron_variantMODIFIER1131TranscriptXM_005273033.1protein_codingXM_005273033.1:c.-146-8176.4>G1:239819076-239819076Gintron_variantMODIFIER1131TranscriptXM_005273032.1protein_codingXM_005273032.1 c.-146-8176A>G1:239819076-239819076Gintron_variantMODIFIER1131TranscriptXM_006711732.1protein_codingXM006711732.1:c.-19-88357.4>G1:239819076-239819076Gintron_variantMODIFIER1131TranscriptNM _000740.2protein_codingNM_0007402:c.-146-8176.4>G1:239819076-239819076Gregulatory _region_variantMODIFIER-RegulatoryFeatureENSR00000555822CTCF_binding _site3rs7543259239815886A0.31870.1842G0.0051281:239815886-239815886Aintron_variantMODIFIER1131TranscriptXM_005273033.1protein_codingXM_005273033.1:c.-146-11366G>A1:239815886-239815886Aintron_variantMODIFIER1131TranscriptXM_005273032.1protein_codingXM_005273032.1 c.-146-11366G>A1:239815886-239815886Aintron_variantMODIFIER1131TranscriptXM_006711732.1protein_codingXM_006711732.1:c.-19-91547G>A1:239815886-239815886Aintron_variantMODIFIER1131TranscriptNM _000740.2protein_codingNM_000740.2:c.-146-11366G>A1:239815886-239815886Aregulatory _region_variantMODIFIER-RegulatoryFeatureENSR00000555821promoter_flanking_region3rs6661621239821503C0.30220.1711G0.0053581:239821503-239821503Cintron_variantMODIFIER1131TranscriptXM_005273033.1protein_codingXM_005273033.1:c.-146-5749G>C1:239821503-239821503Cintron_variantMODIFIER1131TranscriptXM_005273032.1protein_codingXM_005273032.1 c.-146-5749G>C1:239821503-239821503Cintron_variantMODIFIER1131TranscriptXM_006711732.1protein_codingXM_006711732.1:c.-19-85930G>C1:239821503-239821503Cintron_variantMODIFIER1131TranscriptNM _000740.2protein_codingNM_000740.2:c.-146-5749G>C1:239905329-239905329Cintron_variantMODIFIER1131TranscriptXM _005273033.1protein_codingXM_005273033.1:c.-19-2104G>C11rs26722113669048C0.37360.2434T0.0107113669048-3669048Tdownstream_gene_variantMODIFIER417TranscriptXM _005252933.2protein_coding-113669048-3669048Tdownstream_gene_variantMODIFIER417TranscriptNM_004314.2protein_coding-113669048-3669048Tintron_variantMODIFIER57053TranscriptNM _020402.2protein_codingNM_020402.2:c.362+148G>A113669048-3669048Tintron_variantMODIFIER417TranscriptXM_006718236.1protein_codingXM_006718236.1 c.886+7635C>T113669048-3669048Tdownstream_gene_variantMODIFIER417TranscriptXM _006718237.1protein_coding-11rs26722143670282C0.37080.24T0.010811 3670282-3670282Tdownstream_gene_variantMODIFIER4928TranscriptXM_006718241.1protein_coding-11 3670282-3670282Tdownstream_gene_variantMODIFIER4928TranscriptXM_006718242.1protein_coding-11 3670282-3670282Tdownstream_gene_variantMODIFIER4928TranscriptNM_016320.4protein_coding-11 3670282-3670282Tdownstream_gene_variantMODIFIER4928TranscriptXM_006718240.1protein_coding-11 3670282-3670282Tintron_variantMODIFIER417TranscriptXM_006718236.1protein_codingXM_006718236.1:c.886+8869C>T11 3670282-3670282Tintron_variantMODIFIER57053TranscriptNM _020402.2protein_codingNM_020402.2:c.62-341 G>A11 3670282-3670282Tdownstream_gene_variantMODIFIER4928TranscriptXM_005252950.1protein_coding-11:3670282-3670282Tdownstream_gene_variantMODIFIER4928TranscriptNM_139132.3protein_coding-11rs27418683668953T0.36930.24A0.0118511:3668953-3668953Tdownstream_gene_variantMODIFIER417TranscriptXM_005252933.2protein_coding-11:3668953-3668953Tdownstream_gene_variantMODIFIER417TranscriptNM _004314.2protein_coding-11:3668953-3668953Tintron_variantMODIFIER57053TranscriptNM _020402.2NM_020402.2:c.362+243T>A11:3668953-3668953Tintron_variantMODIFIER417TranscriptXM_006718236.1protein_coding protein_codingXM_006718236.1:c.886+7540.4>T11:3668953-3668953Tdownstream_gene_variantMODIFIER417TranscriptXM_006718237.1protein_coding-11rs27418703668879G0.37080.2434C0.0128111:3668879-3668879Gdownstream_gene_variantMODIFIER417TranscriptXM_005252933.2protein_coding-11:3668879-3668879Gdownstream_gene_variantMODIFIER417TranscriptNM _004314.2protein_coding-11:3668879-3668879Gintron_variantMODIFIER57053TranscriptNM _020402.2protein_codingNM_020402.2:c.362+317G>C11:3668879-3668879Gintron_variantMODIFIER417TranscriptXM_006718236.1protein_codingXM_006718236.1c.886+7466C>G11:3668879-3668879Gdownstream_gene_variantMODIFIER417TranscriptXM_006718237.1protein_coding- Table 6: Frequency distribution and significance of acetylcholine receptor (AChR) nsSNPs in CFS / ME patients and non-fatigued controls in rank order of significance. CHR SNP BP A1 F_A F_U A2 P Location Allele Consequence IMPACT Gene Feature_type Feature BIOTYPE HGVSc 3rs7520974239903960G0.42050.5533A0.01671:239903960-239903960Aintron_variantMODIFIER1131TranscriptXM_005273033.1protein_codingXM_005273033.1:c.-19-3473G=>A1:239903960-239903960Aintron_variantMODIFIER1131TranscriptXM005273032.1protein_codingXM_005273032.1:c.-19-3473G>A.1:239903960-239903960Aintron_variantMODIFIER1131TranscriptXM005273034.1protein_codingXM_005273034.1:c.-19-3473G>A1:239903960-239903960Aintron_variantMODIFIER1131TranscriptXM_006711732.1protein_codingXM_006711732.1:c.-19-3473G,A1:239903960-239903960A uupstream_gene_variantMODIFIER100873984TranscriptNR_046582.1IncRNA1:239903960-239903960Aintron_variantMODIFIER1131TranscriptNM000740.2protein_codingNM_000740.2:c.-19-3473G>A3rs6669810239905329G0.42130.5467C0.023611:239905329-239905329Cintron_variantMODIFIER1131TranscriptXM_005273032.1protein_codingXM_005273032.1:¢.-19-2104G>C1:239905329-239905329Cintron_variantMODIFIER1131TranscriptXM005273034.1protein_codingXM_005273034.1:¢.-19-2104G>C1:23 9905329-239905329Cintron_veriantMODIFIER1131TranscriptXM_006711732.1protein_codingXM_006711732. L:c.-19-2104G>C1:239905329-139905329Cintron_variantMODIFIER1131TranscriptNM_000740.2protein_codingNM_000740.2:c.-19-2104G>C3rs718000278581651T0.38460.2763A0.0368215:78581651-78581651Tintron_variantMODIFIER1138TranscriptNM_000745.3protein_codingNM_000745.3:c.258+689A>T15:78581651-78581651Tintron_variantMODIFIER1138TranscriptXM_005254142.1protein_codingXM_005254142.1:c. 258+689A>T3rs6429157239818343G0.5220.4079A0.03751:239818343-239818343Gintron_variantMODIFIER1131TranscriptXM005273033.1protein_codingXM_005273033.1 : c -146-8909A>G1:239818343-239818343Gintron_variantMODIFIER1131TranscriptXM005273032.1protein_codingXM_005273032.1:c.-146-8909A>G1:239818343-239818343Gintron_variantMODIFIER1131TranscriptXM006711732.1protein_codingXM_006711732.1:c.-19-89090A>G1:239818343-239δ18343Gintron_variantMODIFIER1131TranscriptNM000740.2protein_codingNM_000740.2:c.-146-8909A>G8rs5582831242734459G0.23860.1513A0.047898:42734459-42734459Gintron_variantMODIFIER1142TranscriptNM_000749.3protein_codingNM_000749.3:c.1242+1910A>G3rs12036141239902696A0.41210.3092G0.051841:239902696-239902696Aintron_variantMODIFIER1131TranscriptXM005273033.1protein_codingXM_005273033.1 :c-19-4737G>A1:239902696-239902696Aintron__variantMODIFIER1131TranscriptXM005273032.1protein_codingXM_005273032.1:c.-19-4737G>A1:239902696-239902696Aintron_variantMODIFIER1131TranscriptXM005273034.1protein_codingXM_005273034.1:c.-19-4737G>A1:239902696-239902696Aintron_variantMODIFIER1131TranscriptXM_006711732.1protein_codingXM_006711732.1:c.-19-4737G>A1:239902696-239902696A uupstream_gene_variantMODIFIER100873984TranscriptNR_046582.1IncRNA1:239902696-239902696Aintron_variantMODIFIER1131TranscriptNM_000740.2protein_codingNM_000740.2:c.-19-4737G>A3rs6429147239631494C0.44440.34G0.053491:239631494-239631494Gintron_variantMODIFIER1131TranscriptXM _005273033.1protein_codingXM_005273033..1:c.-249-46692C>G1:239631494-239631494Gintron_variantMODIFIER1131TranscriptXM_005273032.1protein_codingXM_005273032.1:c.-312-730C>G1:239631494-239631494Gintron_variantMODIFIER1131TranscriptXM_006711732.1protein_codingXM_006711732.1:c.-185-730C>G1:239631494-239631494Gintron_variantMODIFIER1131TranscriptNM000740.2protein_codingNM_000740.2:c.-312-730C>G8rs1689156142724596T0.24720.1597C0.054548:42724596-42724596Cintron_variantMODIFIER1142TranscriptNM 000749.3protein_codingNM_000749.3:c-250-5998T>C Results Participants

[0201] There were 115 CFS patients (age=48.68±1.06 years), of which 84 (73.04%) were females and 31 (26.96%) were males. There were 90 non-fatigued controls (age=46.48±1.22 years) comprising 59 (65.56%) females and 31 (34.44%) males. All participants in both groups were of European decent and were residents of Australia at the time of blood collection.

[0202] Of 81 SNPs identified in TRP ion channel and AChR genes, 29 nsSNPs were located at intron variants, as well as regulatory region variants, and up-stream and down-stream variants. A total of 12 nsSNPs for TRP ion channel genes (TRPA1, TRPC4 and TRPM3 and TRPM4) were identified in the CFS / ME group. Specifically, 7 nsSNPs featured for TRPM3, 2 nsSNPs for TRPC4, 2 nsSNPs for TRPA1 and 1 nsSNP for TRPM4. A total of 17 nsSNPs for AChR were found, where 10 nsSNPs were identified for mAChM3, 4 nsSNPs for nAChα10, 1 nsSNP for nAChα5 and 2 nsSNPs for nAChα2. Tables 3-4 and Tables 5-6 represent the nsSNPs for TRP ion channel and AChR genes, respectively.

[0203] The predominant gene where these nsSNPs for TRP ion channels were reported was gene 80036 as it had 51 significant reportable events (66%) from a total of 77 events. The remaining nsSNPs for TRP ion channels were found in genes 7223, 101927086 and 54795 where each reported 12 (15%), 2 (2%) and 5 (6%) events, respectively.

[0204] Analysis of the nsSNPs for AChRs found the gene 1131 had 44 reportable (59%) events from a total number of 74 events. The remaining nsSNPs for AChR genes were found in genes 417, 4928, 57053, 100873984, 1138 and 1142 where each reported 12 (16%), 6 (8%), 4 (5%), 2 (3%), 2 (3%) and 2 (3%) events, respectively.Discussion

[0205] This is the first study to report the presence of nsSNP variations in TRP ion channel genes and AChR genes in CFS / ME patients. Collectively, 29 nsSNPs were identified in genes for TRP ion channels and AChRs. A total of 12 nsSNPs were identified for TRP ion channel genes (TRPA1, TRPC4, TRPM3 and TRPM4) and 17 nsSNPs were identified for AChR genes (10 nsSNPs for mAChM3, 4 nsSNPs for nAchα10, 1 nsSNP for nAchα5 and 2 nsSNPs for nAchα2).

[0206] There is limited information available on the role of nsSNPs in these AChR and TRP ion channels in disease. The inventors now report nsSNPs located in intron variants, regulatory region variants and up-stream and down-stream variants of the TRP ion channel and AChR genes in their patient cohort. These variants are likely to be critical in contributing to perturbations of TRP ion channel and AChR function mediated through altered calcium and ACh signalling and manifested as physiological system compromise. Therefore, the critical role of AChRs and TRP ion channels in Ca 2+< cell signalling suggests these nsSNPs may contribute to the clinical manifestation of CFS / ME.

[0207] Identification of the genes containing these nsSNPs for both TRP ion channels and AChRs revealed important roles in calcium cell signalling as well as acetylcholine function with additional roles in adenylate cyclase inhibition respectively. Importantly, genes 80036 and 1131 which accounted for the majority of nsSNPs influence these functions. For example, gene 80036 is associated with calcium signalling mechanisms and calcium store depletion via different isoforms which have been identified through alternative splicing [33d]. Gene 1131 codes for muscarinic cholinergic receptors which demonstrate features including binding of acetylcholine as well as adenylate cyclase inhibition, phosphoinositide degeneration, and potassium channel mediation. As noted above muscarinic receptors mediate acetylcholine activity in the central and peripheral nervous systems. The muscarinic cholinergic receptor 3 (mAChRM3), controls smooth muscle contraction and glandular secretion [34d].

[0208] The significance of the inventors' findings is supported by others who suggest that alternate splicing in the coding and also in the non-coding sequences may have significant unexpected outcomes on the splicing mechanism of the gene transcripts [10d, 11d]. Splicing genetic variants found in the exons and deep intronic variants, as well as down and up-stream variants have a role in alternative splicing mechanisms resulting in diverse protein isoforms. Such altered protein isoform expression may be an important contributing factor affecting changes in protein function. Incidentally, the human gene has the largest average number of mRNA isoforms per gene [35d] with an average of seven mRNA isoforms per gene [36d, 37d]. Furthermore, the regulatory elements in the intron sequences as well as the assembly of the spliceosome add a significant level of complexity to the splicing mechanism for the correct coding of a protein sequence. Enhancers and silencers that are located either in the exons or introns are integral in recognition of the correct exon sequence [38d]. Additionally, others have shown introns are able to generate active spliceosomes, giving rise to alternative splicing events [39d, 40d]. Importantly, the inventors' data show that the greatest proportion of intron variants as well as regulatory region variants occur in the nsSNPs in TRPM3 and mAChM3 genes and may alter the gene transcripts.

[0209] Research to date highlights the importance of such variants in affecting gene transcripts by causing alternative splicing resulting in anomalies in mRNA and translation products. Alternative splicing in TRPM3 and mAChM3 genes may result in aberrant Ca 2+< signalling because of the known secondary pathways involving Ca 2+< which mediate effects for both TRPM ion channels and AChRs. Changes in AChRs and TRP ion channel signalling may have important physiological implications for CFS / ME patients as these TRP ion channels and AChRs are located on nearly all cells in the body. The predominance of CNS symptoms in CFS / ME may result in part from TRPM3 being substantially distributed in the CNS [41d]. Calcium metabolism and signalling in the context of TRPC ion channel as well as muscarinic receptor function is vital for the function of the CNS. Memory, attention, sensory acuity, emotion, pain and motor control [42d, 43d] are critical functions localised throughout a number of regions in the brain [44d]. These CNS functions have been reported to be significantly impaired in CFS / ME patients [45d-47d]. TRPM3 ion channels also function in the roles of heat detection, nociception and transmission of pain [48d, 49d]. Dysregulation in thermoregulatory responses as well as central and peripheral pain have also been reported in CFS / ME patients [50d], suggesting the nsSNPs reported in this study may contribute to the potential CNS impairments in these patients.

[0210] Interestingly, TRPM3 is the only TRP ion channel discovered so far to have a second embedded channel or Omega pore [51d]. This pore is characterised to have features distinguishing it from the TRPM3 main channel, such as activation and current flow characteristics and permeability to Na +< and K +< rather than Ca 2+< , which may be relevant in signalling. For example, it appears the Omega channel acts to potentiate the signal mediated via the main TRPM3 channel, thus giving TRPM3 unique qualities of magnified signalling, particularly nociception and pain transmission. As there have been a number of previous findings reporting significant changes in inflammatory cytokines from CFS / ME patients [52d-54d] the question is asked if an inflammatory mediator may act on the Omega pore to exert an effect on pore opening and promulgation of a nociceptive signal [55d]. The possibility therefore exists that the reportable nsSNPs for TRPM3 in conjunction with this omega pore may potentiate and amplify pathological signalling of TRPM3 when stimulated by inflammatory or other agents.

[0211] mAChM3 receptors have been documented in the gastrointestinal tract and are controlled in part by the parasympathetic nervous system, through the vagus nerve [56d]. ACh has been shown to mediate gut motility via the nerve fibres that make synapses within the gut wall. Ca 2+< mediated channel perturbations through excessive influx or reduction of Ca 2+< flow could cause significant changes in GI motility. It is plausible that nsSNPs' alternative splicing in intron and regulatory regions of mAChM3 genes and TRPC4 genes may cause irregular gastrointestinal motility through activating smooth muscle depolarization [57d]. Additionally, TRPC4 couples to mAChRM3 in the intestine, activating smooth muscle depolarization, inflow of Ca 2+< and smooth muscle contraction [57d]. TRPC4 may be simultaneously regulated by G protein-coupled receptors (GPCRs) [58d]. Enhanced cholinergic-mediated increase in the pro-inflammatory cytokines IL-6 and IL-8 has also been reported in patients with irritable bowel syndrome [59d]. CFS / ME patients report intestinal dysfunction or irritable bowel syndrome including diarrhoea [14d, 30d], while other researchers have reported elevated IL-6 and IL-8 in this patient group [60d].

[0212] nsSNPs of intron or regulatory regions of mAChRM3 receptors may affect metabolic and cardiac responses. mAChRM3 receptors, along with TRPM3 ion channels, play a role in regulating insulin and glucagon secretion [61d, 62d]. Muscarinic acetylcholine receptors (mAChRs) expressed by pancreatic β-cells function to maintain homeostasis of whole body glucose [61d]. nsSNPs documented in mAChM3R genes may mediate changes in Ca 2+< channels thus influencing pancreatic β-cell function and impact glucose metabolism in CFS / ME patients [63d]. Cardiac function via mAChRM3 parasympathetic control is well established [37d] and pacemaker slowing effects of muscarinic agonists are augmented by Ca 2+< transient inhibition, resulting in altered cardio-regulatory mechanisms. Importantly the nsSNPs (intron variants or regulatory regions) found in mAChM3 may alter intracellular Ca 2+< concentrations, resulting in changes in insulin response to glucose or other stimuli as well as contributing to orthostatic cardiovascular effects. Both these physiological disturbances are reported in CFS / ME patients [15d, 23d, 27d, 29d, 31d].

[0213] TRPA1 ion channels are reported on astrocytes of the CNS and contribute to calcium uptake and regulation of astrocytes [64d-67d]. TRPA1 ion channels also initiate acute headache as well as mediating pain and migraine in fibromyalgia patients [68d]. Both symptoms are identified in CFS / ME patients, suggesting nsSNPs for TRPA1 may play a role in the pathology of this illness.Conclusion

[0214] This Example shows a high proportion of nsSNPs (i.e. non-synonymous SNPs) in intronic variants and regulatory variants for TRP ion channels and AChR genes in the inventors' CFS / ME patient cohort. Silent alternative splicing has been suggested to be involved in disease phenotypes, e.g. through exon skipping, alternative splice isoforms of the gene transcript or alternate spliceosomes. The inventors' results suggest such gene variants may result in phenotype anomalies in TRP ion channel expression and AChR expression leading to altered calcium and acetylcholine regulation in CFS / ME and provide a possible rationale for the development of, or predisposition to this debilitating illness.Example 4: Genotype frequencies of TRPM3 ion channels and mAChM3 receptors gene polymorphisms in CFS / ME patients

[0215] In the Examples above the inventors describe SNPs in genes for TRP ion channels and AChRs, which have important roles in calcium (Ca 2+< ) and acetylcholine (ACh) signalling. The inventors now report from this same cohort of patients additional data showing the prevalence of both melastatin TRP (TRPM3) ion channel and muscarinic acetylcholine receptor (mAChM3R) SNP genotypes in CFS / ME patients.

[0216] Genomic DNA extraction and SNP genotyping studies were performed as previously described. The PLINK v1.07 whole genome analysis toolset and IBM ®< SPSS ®< Statistics (version 21) was used to determine the genotype frequency between the CFS patients and the nonfatigued controls. A two column χ2 test was used, where the alpha level of significance was set at a p<0.05 and their consequences can be found in Table 7 for TRPM3 and mAChM3, respectively. Analysis of SNP genotype frequencies in TRPM3 family (rs12682832; rs11142508; rs3763619) and mAChM3R (rs12036141; rs589962; rs1072320; rs7543259; rs7520974; rs726169; rsrs6669810; rsrs6429157) demonstrated high prevalence in this cohort of CFS / ME patients as compared to non-fatigued controls (Table 7). Table 7: Genotype frequencies of TRPM3 and mAChM3 gene polymorphisms in CFS patients and nonfatigued controls.GeneChromosomeRefSNPIDGenotypeCFS (%)Non fatigued controls (%)χ2P-VALUEORmAchM31rs589962TT52 (65%)28 (35 %)6.8390.0092.286mAchM31rs1072320AG47 (66.2%)24 (33.8%)6.8250.0092.314mAchM31rs7543259AG46 (65.7%)24 (34.3%)6.1220.0132.215mAchM31rs7520974AA30 (68.2%)14 (31.8%)4.5150.0342.178mAchM31rs726169AA49 (67.1%)24 (32.9%)8.3450.0042.528mAchM31rs6669810CC29 (67.4%)14 (32.6%)3.9170.0482.071mAchM31rs6429157GG25 (71.4%)10 (28.6%)5.1230.0242.500mAchM31rs12036141AA15 (75%)5 (25%)3.8540.0502.803TRPM39rs12682832AA24 (75%)8 (25%)5.5010.0192.703TRPM39rs11142508CC25 (73.5%)9 (26.5%)5.0290.0252.500TRPM39rs3763619AA25 (71.4%)10 (28.6%)4.0280.0452.222Notes: Data presented for gene TRPM3 (100 CFS / ME patients and 90 controls) and muscarinic M3 (91 CFS patients and 76 controls), chromosome location (CHR), reference SNP identification (Ref SNP ID), genotype, number and percentage of CFS patients and non-fatigued controls with a genotype, Pearson Chi-Square test was used for genotype frequency (1df) and p-value for this test was set at a significance of p <0.05, odds ratio (OR).

[0217] mAChRs are involved in autonomic function, particularly parasympathetic and exocrine function, such as in pancreas, exocrine glands and inotropic and chronotropic cardiac regulation. Given AChRs are distributed differentially around the body it is axiomatic that tissues expressing a predominance of AChRs will be affected differentially by SNPs in muscarinic vs nicotinic ACh receptors. Similarly, TRPs are distributed differentially around the body in all tissues. Adding to the complexity is the relative lack of knowledge about interactions between TRP and AChRs in humans. Interestingly, certain muscarinic ACh receptors are antagonists of TRPM3 via e.g. phospholipase C-coupled mAChM1R [21h, 22h]. Given this developing research regarding the interdependence of mAChRs and TRP families, the inventors question whether mAChM3R and TRPM3 SNP genotype combinations in CFS / ME patients contribute to the pathomechanism and phenotypes of this illness.

[0218] Even though the distribution of these receptors varies in peripheral blood mononuclear cells, SNP genotypes such as those identified in this patient cohort are likely to contribute to perturbations of TRP ion channel and AChR function mediated through altered calcium and ACh signalling and manifest as physiological system compromise. The critical role of AChRs and TRP ion channels in Ca 2+< cell signalling suggests further characterisation of TRPM3 and mAChM3R may elucidate perturbations of second messenger signalling in CFS / ME. Moreover changes in structure of these receptors may contribute to potential autoimmune responses. A recent publication by Loebel et al [23h] suggests a possible autoimmune mechanism in a subgroup of CFS patients affecting muscarinic acetylcholine receptors (mAChR) and β adrenergic receptors (βAdR). However the evidence for an autoimmune pathology is modest as only a minority (29.5%) of patients expressed antibodies against these receptors. Despite multiple Rituximab infusions only 15 of 25 patients responded. However the possibility of some autoimmune mechanisms contributing to pathomechanisms of CFS / ME could be a response to altered structure of SNP affected receptors or ion channels.Example 5: Natural killer cytotoxicity and SNPs in TRP ion channel and AChR genes of isolated natural killer cells in ME / CFS patients

[0219] NK cells are granular lymphocytes found in peripheral blood, bone marrow, spleen and lymph nodes [1j-4j]. In peripheral blood, NK cells comprise 15% of lymphocytes and can be grouped into four subtypes according to the surface expression and density of CD56 (neural cell adhesion molecule) and CD16 [Fcγ III receptor, the low-affinity receptor for immunoglobulin G (IgG)] [1j-3j, 5j, 6j]. These phenotypes include CD56 bright< CD16 - / dim< , CD56 dim< CD16 bright< , CD56 dim< CD16 -< , CD56 -< CD16 bright< [1j-3j]. Approximately 90% of NK cells in peripheral blood are CD56 dim< CD16 bright< and CD56 bright< comprise approximately 10% [2j-4j, 7j]. NK cell cytotoxic activity requires a number of regulated processes to ensure apoptosis of the target cell [8j].

[0220] Though little is known about calcium signaling in NK cells, it has been observed that the granule-dependent pathway of apoptosis is calcium dependent whereas the death-receptor pathway is not [9j, 10j]. In this instance lytic protein transport, exocytosis and fusion have clearly shown calcium dependence [11j-13j]. Calcium is also required for the reorientation of microtubules and actin skeleton as well as activation of cytokine gene transcription [13j]. Moreover, studies have demonstrated the relationship between calcium mobilisation and the abrogation of degranulation in NK phospholipase C (PLC)-γ2-deficient cells [13j-15j].

[0221] Transient receptor potential (TRP) ion channels are expressed on almost all cells and have a significant effect on physiological functions [16j]. Dysregulation in TRPs has been associated with pathological conditions and diseases [17j-21j]. TRP ion channels are activated in the presence of irritants, inflammatory products, and xenobiotic toxins. TRP ion channels have an important role in Ca 2+< signaling.

[0222] Acetylcholine (ACh) binds to two membrane proteins, namely the muscarinic (mAChR) and nicotinic receptors (nAChR) of which there are multiple isoforms. ACh performs non-neuronal functions, termed the non-neuronal cholinergic system (NNCS), where ACh performs endocrine and paracrine functions of tissue located on smooth muscle, β pancreatic cells, glial cells, lymphocytes, ocular lens cells and brain vascular endothelium [17j-26j] that is mediated through Ca 2+< signaling. Acetylcholine receptors (AChRs) transmit activation signals in a variety of human tissues including skeletal and smooth muscle, all preganglionic autonomic nerve fibers, post ganglionic autonomic parasympathetic nerves as well as in many locations throughout the central nervous system (CNS) [27j-29j].

[0223] CFS / ME is characterized by significant impairment in physical activity and debilitating fatigue accompanied by impairment in memory, cognition and concentration, enhanced experience of pain as well as dysregulation of the gastrointestinal, cardiovascular and immune systems [30j-42j]. Importantly, NK cell dysfunction, in particular reduced NK cell cytotoxic activity is a consistent finding in CFS / ME patients [32j-36j, 39j, 43j]. The inventors have described above SNPs in TRP ion channel genes and AChR genes, namely for TRP ion channels TRPM3, TRPA1, TRPC4, the muscarinic receptor mAChRM3 and the nicotinic alpha receptors nAChR alpha 10, alpha 5 and alpha 2 in peripheral blood mononuclear cells from CFS / ME patients. These SNP anomalies in genes for TRP ion channels and AChRs may produce altered receptor proteins, potentially changing TRP ion channel and AChR structures and also functions.

[0224] The aim of the present study was to determine NK cytotoxic activity as well as whether SNPs and their genotypes were present in TRP ion channel and AChR genes in isolated NK cells from CFS / ME patients.Method Subjects

[0225] CFS patients were defined in accordance with the 1994 CDC criteria for CFS [45j]. A total of 39 CFS / ME patients and 30 non-fatigued controls were recruited for this study with no medical history or symptoms of prolonged fatigue or illness of any kind [45j].Sample Preparation and Measurements

[0226] A volume of 80 ml of blood was collected from the antecubital vein of participants into lithium heparinized and EDTA collection tubes between 9 am and 11 am. Routine blood samples were analyzed within 6 hours of collection and analyzed for red blood cell counts, lymphocytes, granulocytes and monocytes using an automated cell counter (ACT Differential Analyzer, Beckman Coulter, Miami, FL). Refer to Table 8. Table 8: Participant Characteristics for Chronic Fatigue Syndrome and Non Fatigued ControlsVariableCFS n=39Non-fatigued controls n=30p-valueGender (% F)71.80%23.70%0.228Mean Age (years)51.69 ± 2.0047.60 ± 2.390.191Hemoglobin (g / L)136.05 ± 2.07138.80 ± 2.240.375Hematocrit (%)0.41 ± 0.010.41 ± 0.010.702Red Cell Count (x10 12< / L)4.54 ± 0.074.58 ± 0.080.697Mean Corpuscular Volume (fL)89.97 ± 0.5590.07 ± 0.700.917White Cell Count (x10 9< / L)5.95 ± 0.266.38 ± 0.310.747Neutrophils x10 9< / L)3.53 ± 0.193.96 ± 0.260.173Lymphocytes (x10 9< / L)1.91 ± 0.101.97 ± 0.080.64Monocytes (x10 9< / L)0.34 ± 0.020.32 ± 0.020.41Eosinophils (x10 9< / L)0.33 ± 0.180.37 ± 0.230.892Basophils (x10 9< / L)0.20 ± 0.180.02 ± 0.000.385Platelets (x10 9< / L)262.56 ± 8.41256.79 ± 9.580.653 NK Cell Isolation

[0227] Peripheral blood mononuclear cells were isolated from 20 mL of whole blood for NK cells using Ficoll-Hypaque (GE Healthcare, Uppsala, Sweden). Enrichment of NK was performed using NK Isolation Kit (Miltenyi Biotech, Bergisch Gladbach, Germany) according to the manufacturer's instructions. Enriched NK purity was examined on the FACS Calibur flow cytometer (BD Bioscience, San Diego, CA) after staining with CD16 / CD56 as previously described [35j] (BD Bioscience, San Diego, CA). Flow cytometry and hemocytometer assessment were used to determine the purity of the NK cells isolated. The recovery of isolated cells was calculated based on the observation that NK represent 2% of peripheral blood lymphocytes respectively [46j]. Recovery was expressed as the ratio of percentage of the total number of NK cells isolated to the percentage of cells present in the volume of blood collected. Enriched cells were snap frozen in liquid nitrogen and stored at - 80°C until further assessment.NK Cell Cytotoxicity

[0228] NK cytotoxic activity was conducted as previously described [36j, 39j]. Briefly, following NK lymphocytes isolation using density gradient centrifugation and labelled with 0.4% PKH-26 (Sigma, St Louis, MO), NK cells were incubated with K562 cells, for 4 hours at 37°C in 95% air, 5% CO 2 at an effector to target ratio of 25 (NK cells):1 (K562). An E:T ratio of 25:1 has been previously been shown by the inventors and other researchers to be the most optimal ratio for assessing cytotoxic activity [36j, 39j]. NK cell lysis was determined following four hours of NK cells with K562 cells, NK lysis was calculated to determine induced tumor cell death or apoptosis [47j]. Fortessa X-20 flow cytometry (BD Bioscience, San Jose, CA), using Annexin V-FITC and 7-AAD reagents (BD Pharmingen, San Diego, CA) was employed. NK cytotoxic activity was performed within 2-4 hours upon receipt of all blood samples.DNA extraction

[0229] A volume of 40 mL was collected into EDTA tubes for SNP analysis. Genomic DNA was extracted from all whole blood samples using the Qiagen DNA blood mini-kit as per manufacturer's instructions (Qiagen). SNP genotyping studies were performed as previously described.SNP analysis

[0230] A total of 678 SNPs from isolated NK cells were examined for twenty-one mammalian TRP ion channel genes (TRPA1, TRPC1, TRPC2, TRPC3, TRPC4, TRPC6, TRPC7, TRPM1, TRPM2, TRPM3, TRPM4, TRPM5, TRPM6, TRPM7, TRPM8, TRPV1, TRPV2, TRPV3, TRPV4, TRPV5 and TRPV6) and for nine mammalian ACh receptor genes (muscarinic M1, M2, M3, M4, M5, nicotinic alpha 2, 3, 5, 7, 10 and epsilon) and were examined using MassARRAY iPLEX Gold Assay (Sequenom Inc.). Quality and quantity of the DNA extracted was determined by the Nanodrop (Nanodrop), where approximately 2 µg of genomic DNA was used to perform the SNP analysis. SNP analysis was performed as previously described. Briefly, MassARRAY (MALTI-TOF mass spectrometry platform) was employed to discriminate alleles based on single-base extension of an extension primer of known mass that is designed to attach directly next to the SNP site of interest. Custom multiplexed wells were designed in silico using Agena's Assay Design Suite. The designed multiplexes were then built using custom synthesized oligonucleotides that are pooled together for sample processing. The iPLEX Gold chemistry utilized two multiplexed oligo pools for each genotyping well. These were pooled and balanced prior to running against DNA samples. First a multiplexed PCR pool was utilized to generate short amplicons that include all the genomic markers of interest in that particular well. After PCR and clean-up steps were undertaken, a secondary PCR 'extension' step was undertaken utilizing pools of extension primers that were designed to attached directly next to the SNP sites of interest. A termination mix was added to the extension phase which allowed these extension primers to be extended by a single base only. As the molecular weight of the extension primer is known, discrimination of the allele was able to be measured using the peak heights of the unextended primer and this primer plus the possible single-base extension possibilities for the SNP.TRP ion channel and AChR SNP assays

[0231] Primers and extension primers were created for each of the SNPs using the Assay Designer (Sequenom Inc.) according to the manufacturer's instructions. DNA was amplified via polymerase chain reaction (PCR) under the following conditions: 94°C for 2 minutes, 94°C for 30 seconds, 56°C for 30 seconds, and 72°C for 1 minute. Amplification products were then treated with shrimp alkaline phosphatase at 37°C for 40 minutes, 85°C for 5 minutes reaction, and a final incubation at 4°C. Extension primers are optimized to control the signal-to-noise ratio where unextended primers (UEPs) are examined on the spectroCHIP and evaluated in Typer 4.0 to enable the division into low-mass UEP, medium-mass UEP, and high-mass UEP. To perform the iPLEX extension reaction, a mixture containing iPLEX Gold reaction was prepared using iPLEX Gold Buffer Plus, iPLEX termination mix, iPLEX enzyme, and primer mix. The iPLEX reaction was cycled at an initial denaturation of 94°C for 30 seconds, annealing at 52°C for 5 minutes, extension at 80°C for 5 minutes (five cycles of annealing and extension were performed, but the whole reaction was performed in 40 cycles) and extension again at 72°C for 3 minutes. Resin beads were used to rinse all iPLEX Gold reaction products. Following the iPLEX Gold reaction, MassARRAY was performed using the MassARRAY mass spectrometer, and the data generated were analyzed using the TyperAnalyzer software.Statistical analysis

[0232] Statistical analysis was performed using SPSS software version 22 [IBM Corp]. The experimental data represented in this study are reported as means plus / minus standard error of the mean (±SEM) while all the clinical data are reported as means plus / minus standard deviation (±SD). Comparative assessments among participants (CFS / ME and non-fatigued controls) were performed with the analysis of variance test (ANOVA) and the criterion for significance was set at p<0.05.

[0233] The PLINK v1.07 (http: / / pngu.mgh.harvard.edu / purcell / plink / ) whole genome analysis tool set was used to determine associations between the CFS patients and the non-fatigued control group. A two column χ2 test was used to examine differences where p value of <0.05 was determined to be significant and the resulting variants and their consequences can be found in Table 9 for TRP and AChR, respectively. Further genotype analysis for differences between CFS and the non-fatigued group was also completed according to a two column χ2 test with significance of p <0.05 and results are presented in Table 10. Analyses were performed at the Australian Genome Research Facility Ltd, The Walter and Eliza Hall Institute, Parkville, Victoria, Australia. Table 9: Analysis of the frequency, distribution and significance of SNPs in genes for TRP ion channels and AChRs in CFS / ME patients (n=39_) and non-fatigued controls (n=30) in rank order of significanceGeneCHRSNPBPA1F AF_UA2CHISQORp-valueTRPM82rs178656782.34E+08A0.45950.1667G12.884.250.000332TRPM82rs115632042.34E+08A0.35530.1167G10.184.1720.00142nAChRβ415rs1244108878635922G0.17950.3793T6.8240.3580.008993TRPC413rs298516737656405G0.28210.5A6.7420.39290.009418TRPM39rs656020071365306T0.39740.6207C6.6330.40310.01001TRPM39rs110694871402258C0.39740.6167T6.5210.410.01066TRPM82rs67586532.34E+08A0.24360.45G6.5020.39360.01078nAChRα315rs1291438578606381T0.48720.2833C5.8792.4030.01532nAChRα28rs89139827467305C0.55260.3448T5.7142.3470.01683TRPM39rs1235023271417232G0.39740.6T5.5710.43970.01826nAChRα28rs274134327468610C0.55260.35T5.5372.2940.01862TRPM39rs1114282271427327T0.038460.15G5.3140.22670.02115nAChRα315rs286954678615003C0.27630.4667T5.2710.43640.02168TRPM39rs189130171403580T0.57690.3833C5.0852.1940.02414nAChRα315rs95126678586199T0.43590.2586C4.5362.2150.03319TRPC211rs71086123628856T0.19230.06667G4.5093.3330.03372TRPC211rs65783983616831A0.34620.1833G4.5062.3580.03378mAChRM111rs657839862920797A0.24360.1034G4.3542.7910.03691mAChRM31rs46205302.4E+08T0.47440.3G4.3012.1060.03809mAChRM111rs1182372862909330T0.052630.1607C4.2420.29010.03943nAChRα315rs424308478619330G0.43590.2667C4.2042.1250.04034nAChRα315rs374307578617110A0.28210.45G4.1770.48020.04097nAChRα315rs374307478617138C0.28210.45T4.1770.48020.04097nAChRε17rs339701194901607A0.038460.1333G4.1610.260.04136nAChRα515rs718000278581651T0.43420.2667A4.0842.110.0433SNPs of 39 CFS / ME patients and 30 non-fatigued controls. Data presented are included for p<0.05. Data are presented for gene (TRPM3, TRPM8, TRPC2, TRPC4, AChRM1, M3, alpha 2, 3, 5, 10 and epsilon), chromosome location (CHR), reference SNP identification (RefSNPID), base pair (BP) location of SNP, alleles (A1 and A2), allelic frequency A (Frequency_A) of this allele in CFS cases, frequency U (Frequency_U) of this allele in controls, chi-square (χ2) for basic allelic test (1 df), odds ratio (OR) and (*) P-value for this test set at a significance of <0.05. Table 10: Analysis of the genotype, odds ratio and significance of SNPs in genes for TRP ion channels and AChRs in CFS / ME patients (n=39) and non-fatigued controls (n=30) in rank order of significance GeneCHRSNPGenotypeCFS (n%)Non-Fatigued Control (n%)χ2ORp-valueTRPM82rs11563204GA23 (82.1%)5 (17.9%)12.597.190nAChRα28rs891398CC11 (91.7%)1 (8.3%)7.3111.390.007nAChRα28rs2741343CC11 (91.7%)1 (8.3%)7.311.390.007TRPC413rs2985167AA20 (76.9%)6 (23.1%)7.074.210.008TRPM39rs6560200CC15 (83.3%)3 (16.7%)7.125.630.008TRPC413rs1570612GG30 (68.2%)14 (31.8%)6.723.810.01nAChRβ415rs12441088TT25 (71.4%)10 (28.6%)6.423.570.011TRPM82rs17865678AG22 (73.3%)8 (26.7%)6.13.560.013TRPC413rs655207GG12 (85.7%)2 (14.3%)6.096.220.014nAChRα315rs12914385TT12 (85.7%)2 (14.3%)6.096.220.014TRPM39rs11142822GG36 (63.2%)21 (36.8%)5.875.140.015TRPM39rs1106948TT15 (78.9%)4 (21.1%)5.374.060.021TRPC211rs7108612GT15 (78.9%)4 (21.1%)5.374.060.021nAChRε17rs33970119GG36 (62.1%)22 (37.9%)4.564.360.033TRPM39rs1891301TT14 (77.8%)4 (22.2%)4.483.640.034TRPM39rs12350232TT15 (75%)5 (25%)3.913.130.048Genotype with 39 CFS / ME patients and 30 non-fatigued controls. Data presented are included for p<0.05. Data are presented for gene (TRPM3, TRPM8, TRPC2, TRPC4, AChRM3, alpha 2, 3, and epsilon), chromosome location (CHR), reference SNP identification (RefSNPID), genotype percentage of CFS patients with genotype (%), percentage of non-fatigued controls (5), chi-square (χ2) for basic allelic test (1 df), odds ratio (OR) and (*) P-value for this test set at a significance of <0.05. Results Participants

[0234] There were 39 CFS patients (age=51.69± 2.00years), of which 72% were females and 18% were males. There were 30 non-fatigued controls (age = 47.60 ± 2.39 years) comprising 24% females and 76% males. All participants in both groups were of European decent and were residents of Australia at the time of blood collection. There were no significant changes in white blood cell counts between CFS / ME patients and the non-fatigued control group. Table 8 outlines participants' characteristics.NK Cell Purity

[0235] There was no significant difference between groups for levels of NK purity. Figure 1 outlined the high levels of purity (> 93%) of NK cells following isolation and enrichment.NK Cell Cytotoxic Activity

[0236] There was a significant difference for NK cytotoxic activity between groups at the E:T ratio of 25:1. CFS / ME patients had a significant reduction in NK % lysis (17 ± 4.68) compared with the control group (31 ± 6.78) (Figure 2).SNP Analysis

[0237] Of 678 SNPs identified in TRP ion channel and AChR genes from isolated NK cells there were 11 SNPs for TRP ion channel genes (TRPC4, TRPC2, TRPM3 and TRPM8) significantly associated in the CFS / ME group. Five of these SNPs were associated with TRPM3 (rs rs6560200; p= 0.010, rs1106948; p= 0.010, rs12350232; p= 0.018, rs11142822; p= 0.021, rs1891301; p= 0.024) while the remainder were associated with TRPM8 (rs17865678;p=0.000, rs1156320; p=0.001), TRPC2 (rs7108612; p= 0.034, rs6578398; p= 0.0334) and TRPC4 (rs2985167; p=0.001, rs655207; p=0.018).

[0238] Fourteen SNPs were associated with nicotinic and muscarinic acetylcholine receptor genes, where six were nAChR alpha 3 (rs12914385; p=0.015, rs2869546; p=0.021, rs951266; p=0.033, rs4243084; p=0.040, rs3743075; p=0.041, rs3743074; p=0.041), while the remainder were associated with nAChR alpha 2 (rs891398; p=0.017, rs2741343; p=0.019), nAChR beta 4 (rs12441088; p=0.009), nAChR alpha 5 (rs7180002; p=0.043) and nAChR epsilon (rs33970119; p=0.041). Table 9 represents the SNPs for TRP ion channel and AChR genes isolated from NK cells, respectively.Genotype Analysis

[0239] There were sixteen genotypes identified from SNPs that were reported significant for TRPM3 (n=5), TRPM8 (n=2), TRPC4 (n=3), TRPC2 (n=1), nAChR epsilon (n=1), nAChR alpha 2 (n=2), nAChR alpha 3 (n=1) and nAChR beta 4 (n=1). Table 10 represents the genotypes for SNPs in TRP and AChR genes from isolated NK cells that were reported as statistically significant between groups. The odds ratio for specific genotypes for SNPs in TRP and AChR genes from isolated NK cells ranged between 3.13 - 11.39 for CFS / ME compared with the non-fatigued control group.Discussion

[0240] Reduced NK cell cytotoxic activity has previously been reported in CFS / ME and the current investigation supports those findings. The current investigation reports novel findings for a number of SNPs in genes for AChR and TRP variants and genotypes from isolated NK cells from CFS / ME patients. A further novel finding from this investigation is the identification of SNPs in TRPM3 and TRPM8 from isolated NK cells, suggesting TRPM3 and TRPM8 receptors are located on NK cells.

[0241] This investigation reports a significant reduction in NK lysis in CFS / ME patients compared with the non-fatigued controls. TRP ion channels have an important role in Ca 2+< signaling and immune cells have been documented to express TRPC and TRPM subfamilies, mainly TRPC-1, 3, 5 and TRPM-2, 4, 7 [49j]. These channels are non-selective and permeable to calcium. In NK cells Ca 2+< plays a key role in lytic granule fusion [11j, 50j, 51j] as well as ensuring lytic granules mobilize to the immune synapse to release perforin and granzymes to kill target cells [11j, 50j, 51j]. Rho-GTPase Miro, provides a link between the mitochondria and the microtubules, where it mediates the Ca 2+< dependent arrest of mitochondrial motility [52j]. As Rho GTPase Miro modifies mitochondrial polarization, it also may alter lytic granule transport to the immune synapse as well as lytic function due to modulation by cytosolic Ca 2 +< concentration through TRPM and AChR genotypes. Clearly mitochondria play a key role in NK cell function. A recent discovery that mitochondria express a range of AChR subtypes including nicotinic alpha 3, although differentially expressed according to tissue type [53j] suggests that nAChR may impact mitochondrial function and regulate oxidant stress. Interestingly the inventors have previously reported a significant decrease in respiratory bust function of neutrophils from CFS / ME patients [34j].

[0242] TRPM2 and TRPM3 mobilize Ca 2+< , where the latter has been shown to mediate Ca 2+< signaling for cytolytic granule polarization and degranulation [54j]. ADPR targets TRPM2 channels on cytolytic granules resulting in TRPM2-mediated Ca 2+< signaling, subsequently inducing cytolytic granule polarization and degranulation, which results in antitumor activity. Further, NK cells treated with ADPR antagonist had reduced tumor-induced granule polarization, degranulation, granzyme B secretion, and cytotoxicity of NK cells. Interestingly similar findings for NK cell functions have been reported from previous CFS / ME research [32j-36j], potentially suggesting the genotype changes reported in this present study for TRPM3 may also play a similar role for cytolytic granule polarization and degranulation.

[0243] Out of the 678 SNPs examined, eleven variants for TRP ion channels and fourteen variants for AChRs were found to be significantly associated with CFS / ME patients compared with the non-fatigued controls. The variant TRP SNPs were located in the gene sequence of two of the canonical TRP ion channels (TRPC2 and TRPC4) and two melastatin TRP ion channels (TRPM3 and TRPM8). The inventors also report variant SNPs on genes for two of the muscarinic acetylcholine three receptors (mAChRM3), two muscarinic acetylcholine one receptors (mAChRM1), six nicotinic acetylcholine alpha three receptors (nAChRα3), three nicotinic acetylcholine alpha two receptors (nAChRα2), one nicotinic acetylcholine alpha five receptor (nAChRα5) as well as one nicotinic acetylcholine beta four receptor (nAChRβ4) and one nicotinic acetylcholine epsilon receptor (nAChRε).

[0244] The inventors' current research reports significant SNP associations of genotypes for AChRs in isolated NK cells from CFS / ME patients. Lymphocytes express both muscarinic and nicotinic acetylcholine (ACh) receptors, where T and B cells and monocytes express all five subtypes of mAChRs (M(1)-M(5)), while nAChR are found for 2- 6, 2-4, and 9 / 10 subunits [55j-58j]. Lymphocytes constitute a cholinergic system that is independent of cholinergic nerves, resulting in the regulation of immune function [55j, 56j]. AChR agonists have been shown to enhance lymphocyte cytotoxicity, increase their intracellular cGMP and inositol-1,4,5-triphosphate (IP3) [55j-59j], suggesting the lymphocytic cholinergic system is involved in the regulation of immune function via AChRs coupled to phospholipase-C (PLC) via changes in [Ca 2 +< ] [60j-65j]. Previous research has highlighted the importance of variants in affecting gene transcripts by causing alternative splicing resulting in anomalies in mRNA and translation products [66j]. The inventors have also identified SNPs and genotype in nAChRε in CFS / ME patients. Interestingly, this SNP is located in the 3' untranslated region (3'-UTR), an important coding region that often contains regulatory regions that post-transcriptionally influence gene expression. 3'-UTR is a binding site for regulatory proteins as well as microRNAs (miRNAs) [67j]. Binding to specific sites within the 3'-UTR, miRNAs can decrease gene expression of various mRNAs by either inhibiting translation or directly causing degradation of the transcript. The inventors' previous research has found significant differences in NK cytotoxic activity as well as miRNAs from isolated NK cells from CFS / ME patients [32j].

[0245] Previous investigators suggest that alternate splicing in the coding and also in the non-coding sequences may have significant unexpected outcomes on the splicing mechanism of the gene transcripts [68j, 69j]. Splicing genetic variants located in the exons, introns, as well as the assembly of the spliceosome all contribute to the splicing mechanism for the correct coding of a protein sequence. Moreover, silencers and enhancers located either in the exons or introns are integral in recognition of the correct exon sequence [70j]. Importantly introns are able to generate active spliceosomes, giving rise to alternative splicing events [71j, 72j]. Gene 80036 (TRPM3) is associated with calcium entry and calcium store depletion via different isoforms which have been identified through alternative splicing [Fruhwald, Julia, et al. "Alternative splicing of a protein domain indispensable for function of transient receptor potential melastatin 3 (TRPM3) ion channels." Journal of Biological Chemistry 287.44 (2012): 36663-36672]. The 'indispensable for channel function' (ICF) is an 18 amino acid residue region whose absence renders the channels functionally unable to mediate calcium entry, and is found devoid in a TRPM3 variant [73j]. Co-expression of these TRPM3 ICF variants with functional TRPM3 ion channels additionally show impaired calcium mobilization [73j]. As TRPM3 ICF variants show ubiquitous expression in many tissues and cell types and constitute 15% of all TRPM3 isoforms, expression on NK cells may provide a potential explanation for reduced cytotoxic activity in CFS / ME patients. Additionally, ion selectivity occurs through the selective splicing of exon 24 and results in two variants, TRPM3α1 and TRPM3α2 [73j, 74j]. The significance of these two isoforms is highlighted as TRPM3α1 preferentially mediates monovalent cation conduction, while TRPM3α2 shows high and specific permeability towards divalent cations, particularly calcium [73j, 74j]. This alteration in function may be attributed to the introduction of positively charged amino acid residues to the pore region [74j], resulting in increases in electrostatic repulsion of divalent cations, thus promoting increases in monovalent selectivity [74j]. Therefore, particular splice variants such as TRPM3α1 may potentially be favoured, culminating in a diminished NK cell cytotoxic response as well as heat detection including dysregulation of thermoregulatory responses, nociception and transmission of pain such as central and peripheral pain perception. Moreover, TRPM8 has also been identified to be activated by cold and noxious stimuli [75j-77j], suggesting the genotype changes reported in this investigation align to the clinical presentation of thermoregulatory responses, nociception and transmission of central and peripheral pain perception seen in CFS / ME patients [78j].

[0246] The inventors' results suggest SNP variants and genotypes reported in NK cells may not be exclusive to this immune cell type. Acetylcholine receptors and TRP ion channel receptors are located ubiquitously on multiple cell types and control other functions in body systems. Ca 2+< signaling in the context of TRP ion channels as well as AChR function is vital for the function of the CNS and there is wide variety in nicotinic receptors expressed in animal and human immune cells [58j]. Inferences regarding differential effects on function between these systems should note limitations depending on sub-types respectively expressed. The endothelium contains nicotinic receptors; nAChRα3, α5 and β4.α3 and α5 are found in arteries [79j-81j] and nAChR α5, α7, β2, and β3 are found in brain endothelial cells [82j], which are important components of the blood-brain barrier. Others have reported various nAChR receptors located on mitochondria, and depending upon tissues, mitochondria express several nicotinic receptor subtypes in a tissue-specific manner; brain and liver mitochondria contain α7β2, α4β2 and less α3β2 nicotinic receptors, while mitochondria from the lung express preferentially α3β4 receptor subtype [53j]. Interestingly this epsilon sub-type has been identified in thymomas from patients with myasthenia gravis [83j]. Of note, nAChRs are reported to be involved in arousal, sleep, and fatigue as well as those functions that are responsible for processing of pain, memory, and cognition all of which are clinical symptoms reported in CFS / ME patients [84j-86j].Conclusion

[0247] In this study the inventors identified, for the first time, SNPs in genes for TRPM3 and TRPM8 ion channels on isolated NK cells. The inventors also identified numerous SNPs of nAChRs along with other TRP channels on isolated NK cells, indicating the non-neuronal acetylcholine system has an important role in NK cell function. Anomalies in genotypes for TRP ion channels and AChRs suggest altered calcium would be an important functional consequence not only for NK cells but also depending upon tissue type, susceptibility or predisposition to CFS / ME.Example 6: SNPs and genotypes in TRP ion channel and AChR genes from isolated B lymphocytes in ME / CFS patients

[0248] The pathomechanism of CFS / ME is unknown. However, a small subgroup of patients has shown muscarinic antibodies and reduced symptom presentation following anti-CD20 intervention. Given the important roles in calcium (Ca 2+< ) and acetylcholine (ACh) signaling in B cell activation and potential antibody development, the inventors' aim in this Example was to determine SNPs and their genotypes from isolated B cells from CFS / ME patients.

[0249] Acetylcholine (Ach) is a neuronal cholinergic neurotransmitter where it performs a vital role through transmitting activation signals to receptors located in the central nervous system (CNS) as well as in skeletal and smooth muscle, all preganglionic autonomic nerve fibers and post ganglionic autonomic parasympathetic nerves as well immune cells and other tissues through the non-neuronal cholinergic system [1x-4x].

[0250] There are two types of membrane proteins that bind ACh known as muscarinic receptors (mAChRs) and nicotinic receptors (nAChRs). Importantly, both receptor proteins (mAChR and nAChR) have multiple isoforms. While muscarinic receptors are metabotropic receptors classified M1-M5, nicotinic receptors are ion channels and, with the exception of homomeric nicotinic alpha 7, are heteromers with various combinations of usually two sub-types (selected from 9 alpha and 3 beta) [5x]. The ratio of subtypes affects signal conducting speed through the receptor [6x]. Importantly one receptor subtype may impact receptor function of the other linked subtype.

[0251] ACh also functions within the non-neuronal cholinergic system (NNCS) where ACh binds AChRs that have been found on immune and other cell types. ACh is produced by lymphocytes where nAChRs have been shown to influence B lymphocyte function including development in the bone marrow as well as regulating B lymphocyte activation and autoantibody response [7x-9x]. ACh also performs endocrine and paracrine functions on tissues such as smooth muscle, beta pancreatic cells, glial cells, lymphocytes, ocular lens cells and brain vascular endothelium [10x-14x]. Calcium signaling is highly important for the activation of cell surface receptors on immune cells. Moreover, these ACh functions are mediated through Ca 2+< signaling.

[0252] Interestingly, muscarinic acetylcholine receptors have been found to be inhibited by another calcium channel [15x]. Mammalian Transient receptor potential (TRP) ion channels are Ca 2+< permeable cation channels that when open act as an excitatory signal to induce depolarisation of the cell and cause Ca 2+< influx which plays a role in intracellular signalling pathways. (TRPs) are comprised of six main groups including the TRPA (ankyrin), TRPC (canonical), TRPM (melastatin), TRPML (mucolipin), TRPP (polycystin) and TRPV (vanilloid) [16x]. TRPs are present on almost all cells and dysregulation in TRPs has been associated with pathological conditions and diseases [17x-22x].

[0253] The inventors have previously described single nucleotide polymorphisms (SNPs) in genes for receptors where Ca 2+< calcium is an important key component in their function. Additionally, the inventors have shown changes in Ca 2+< mobilization intracellularly for TRPM3 from NK cells and B lymphocytes. Hence, these SNPs and their genotypes for TRP ion channels and AChRs may produce altered receptor proteins, potentially changing TRP ion channel and AChR structures and functions. A recent study reported a subgroup of CFS / ME patients had muscarinic antibodies and a modest positive response occurred with reduced symptom presentation following anti-CD20 intervention [39x]. Given the important roles in Ca 2+< and acetylcholine (ACh) signaling in B cell activation as well as the potential for antibody development, the aim of this investigation was to determine SNPs and their genotypes for TRP and AChRs from isolated B cells from CFS / ME patients.Method Subjects

[0254] CFS / ME patients were defined in accordance with the 1994 CDC criteria for CFS / ME [40x]. A total of 11 CFS / ME patients and 11 non-fatigued controls were recruited for this study with no medical history or symptoms of prolonged fatigue or illness of any kind [40x].Sample Preparation and Measurements

[0255] A volume of 40 ml of blood was collected from the antecubital vein of participants into lithium heparinized and EDTA collection tubes between 9 am and 11 am. Routine blood samples were analyzed within 6 hours of collection and analyzed for red blood cell counts, lymphocytes, granulocytes and monocytes using an automated cell counter (ACT Differential Analyzer, Beckman Coulter, Miami, FL). Refer to Table 11. Table 11: Participant Characteristics for CFS / ME and Non Fatigued Controls.DescriptiveCFS / ME n=11Controls n=11P-VALUEGender (% F)8 (72.7%)7 (63.6%)0.497Mean Age (Years)31.82 (5.50)33.91 (5.06)0.783Haemoglobin (g / L)133 ± 2.70134.70 ± 3.850.728Haematocrit (%)0.36 ± 0.020.30 ± 0.020.967Red Cell Count (x10 12< / L)4.40 ± 0.134.50 ± 0.110.591Mean Corposcular Volume (fL)89.56 ± 1.5488.20 ± 0.610.406White Cell Count (x10 9< / L)7.09 ± 0.695.80 ± 0.320.097Neutrophils (x10 9< / L)4.15 ± 0.513.21 ± 0.210.096Lymphocytes (x10 9< / L)2.35 ± 0.232.13 ± 0.240.549Monocytes (x10 9< / L)0.36 ± 0.020.30 ± 0.020.043Eosinophils (x10 9< / L)0.19 ± 0.040.14 ± 0.030.275Basophils (x10 9< / L)0.03 ± 0.000.03 ± 0.010.752Platelets (x10 9< / L)241.56 ± 19.55248.10 ± 18.350.810 B cell isolation

[0256] A volume of 40 ml of blood was collected from the antecubital vein of participants into EDTA blood collection tubes between 8 am and 11 am. Routine blood samples were analyzed within 6 hours of collection and analyzed for red blood cell counts, lymphocytes, granulocytes and monocytes using an automated cell counter (ACT Differential Analyzer, Beckman Coulter, Miami, FL). Refer to Table 11.

[0257] Peripheral blood mononuclear (PBMCs) cells were isolated from 40 mL of whole blood for B cell isolation using method previously described Jamies et al. (2004) [69x]. Briefly, PBMCs were isolated by density gradient with Ficoll-Paque (GE Healthcare, Uppsala, Sweden). Subsequently, cells were then washed twice with phosphate-buffered saline (PBS) (Gibco-BRL, Gaithersburg, Md.).

[0258] Cells were then resuspended in autoMACs separation buffer, which contains PBS containing bovine serum albumin, EDTA and 0.09% azide (Miltenyi Biotec, Auburn, Calif.). Immunomagnetic negative selection of B cells was performed with a B-cell isolation kit II (Miltenyi Biotec, Auburn, Calif.), according to the manufacturer's instructions. Briefly, non-B cells, such as T cells, NK cells, dendritic cells, monocytes, granulocytes, and erythroid cells, are indirectly magnetically labeled by using a cocktail of biotin conjugated antibodies against CD2, CD14, CD16, CD36, CD43 and CD235a (Glycophorin A). Consequently, isolation of B cell populations is achieved by depletion of magnetically labeled cells.

[0259] Untouched B-cells were measured with LSR Fortessa X-20 flow cytometry where cells were fluorescently stained with anti-CD19-BV421 and anti-CD3-PerCP. Cell debris and dead cells were excluded from the analysis based on scatter signals. Mean purity was 85.66% ± 9.6% for non-fatigued controls and 76.5% ±13.1% for CFS / ME patients, where there was no significant difference between groups for levels of B lymphocytes.DNA extraction

[0260] A volume of 40 mL was collected into EDTA tubes for SNP analysis. Genomic DNA was extracted from all whole blood samples using the Qiagen DNA blood mini-kit as per manufacturer's instructions (Qiagen). SNP genotyping studies were performed as previously described.SNP analysis

[0261] A total of 661 SNPs from B cells were examined for twenty-one mammalian TRP ion channel genes (TRPA1, TRPC1, TRPC2, TRPC3, TRPC4, TRPC6, TRPC7, TRPM1, TRPM2, TRPM3, TRPM4, TRPM5, TRPM6, TRPM7, TRPM8, TRPV1, TRPV2, TRPV3, TRPV4, TRPV5 and TRPV6) and for nine mammalian ACh receptor genes (muscarinic M1, M2, M3, M4, M5, nicotinic alpha 2, 3, 5, 7, 9, 10, beta 1, 4 and epsilon) and were examined using MassARRAY iPLEX Gold Assay (Sequenom Inc.).

[0262] Quality and quantity of the DNA extracted was conducted as previously described [44x, 48x]. Briefly a Nanodrop (Nanodrop) was used to quantify genomic DNA where approximately 2 µg of genomic DNA was used to perform the SNP analysis. MassARRAY (MALTI-TOF mass spectrometry platform) was employed to discriminate alleles based on single-base extension of an extension primer of known mass that is designed to attach directly next to the SNP site of interest. Custom multiplexed wells were designed in silico using Agena's Assay Design Suite. The designed multiplexes were then built using custom synthesized oligonucleotides that are pooled together for sample processing. The iPLEX Gold chemistry utilized two multiplexed oligo pools for each genotyping well. A multiplexed PCR pool was utilized to generate short amplicons that include all the genomic markers of interest in that particular well. Following PCR and clean-up steps, a secondary PCR 'extension' step was undertaken utilizing pools of extension primers that were designed to attach directly next to the SNP sites of interest. During the extension phase a termination mix was added that enabled these extension primers to be extended by a single base only. Given the molecular weight of the extension primer is known, discrimination of the allele was able to be measured using the peak heights of the unextended primer and this primer plus the possible single-base extension possibilities for the SNP.TRP ion channel and AChR SNP assays

[0263] Primers and extension primers were created for each of the SNPs using the Assay Designer (Sequenom Inc.) according to the manufacturer's instructions and previously described [44x, 45x]. Briefly, DNA was amplified via polymerase chain reaction (PCR) under the following conditions: 94°C for 2 minutes, 94°C for 30 seconds, 56°C for 30 seconds, and 72°C for 1 minute, where the amplification products were then treated with shrimp alkaline phosphatase at 37°C for 40 minutes, 85°C for 5 minutes reaction, and a final incubation at 4°C. Extension primers are optimized to control the signal-to-noise ratio where unextended primers (UEPs) are examined on the spectroCHIP and evaluated in Typer 4.0 to enable the division into low-mass UEP, medium-mass UEP, and high-mass UEP. A mixture containing iPLEX Gold reaction was prepared using iPLEX Gold Buffer Plus, iPLEX termination mix, iPLEX enzyme, and primer mix to perform the iPLEX extension reaction. This reaction consisted of cycling at an initial denaturation of 94°C for 30 seconds, annealing at 52°C for 5 minutes, extension at 80°C for 5 minutes (five cycles of annealing and extension were performed, but the whole reaction was performed in 40 cycles) and extension again at 72°C for 3 minutes. Resin beads were used to rinse all iPLEX Gold reaction products. Following the iPLEX Gold reaction, MassARRAY was performed using the MassARRAY mass spectrometer, and the data generated were analyzed using the TyperAnalyzer software.Statistical analysis

[0264] Statistical analysis was performed using SPSS software version 22 [IBM Corp]. The experimental data represented in this study are reported as means plus / minus standard error of the mean (±SEM) while all the clinical data are reported as means plus / minus standard deviation (±SD). Comparative assessments among participants (CFS / ME and non-fatigued controls) were performed with the analysis of variance test (ANOVA) and the criterion for significance was set at p<0.05.

[0265] The PLINK v1.07 (http: / / pngu.mgh.harvard.edu / purcell / plink / ) whole genome analysis tool set was used to determine associations between the CFS / ME patients and the non-fatigued control group. A two column χ2 test was used to examine differences where p value of <0.05 was determined to be significant and the resulting variants and their consequences can be found in Table 12 for TRP and AChR, respectively. Table 12: Analysis of the frequency, distribution and significance of SNPs in B cells for TRP ion channels and AChRs in Chronic Fatigue Syndrome / Myalgic Encephalomyelitis patients and non-fatigued controls in rank order of significanceGeneCHRSNPBPA1F_AF_UA2CHISQPORCHRNA420rs1169856363360932A0.28850.7083C11.8800.1669CHRND2rs116746082.33E+08G0.340.7778C10.2300.1472CHRNA94rs1000922840354404A0.17860.5G8.70600.2174CHRM31rs18672642.40E+08A0.280.6364T8.16400.2222CHRNA94rs486132340353797G0.17860.4583A6.7920.010.2569CHRNA28rs274134127472768C0.51790.2083T6.5860.014.081TRPC611rs112248161.02E+08T0.51920.2083C6.5110.014.104CHRND2rs124639892.33E+08C0.35710.6667T6.5030.010.2778CHRND2rs27672.33E+08C0.35710.6667T6.5030.010.2778CHRND2rs1120018802.33E+08D0.35710.6667I6.5030.010.2778CHRNB117rs41511347443803C0.32140.625T6.3890.010.2842CHRM31rs18996162.40E+08A0.32690.6667G6.3610.010.2429CHRNB415rs1244029878635246G0.017860.1667T6.3490.010.09091TRPV317rs47905193553440C0.55560.25T6.2420.013.75TRPM39rs131710370580786C0.35190.08333T6.0890.015.971CHRND2rs675835102.33E+08A0.18520.4545G5.8490.020.2727CHRM31rs120938212.40E+08A0.29630.5833G5.7840.020.3008CHRM31rs108028022.40E+08A0.3750.6667G5.7490.020.3CHRNA94rs486106540342377C0.39290.125T5.610.024.529CHRNA94rs766988240348633A0.39290.125G5.610.024.529CHRM31rs66846222.40E+08C0.380.6818G5.5840.020.286CHRM31rs11342.40E+08T0.34620.625C5.1970.020.3176CHRND2rs37625292.33E+08C0.34620.625T5.1970.020.3176CHRND2rs124663582.33E+08G0.17310.4167T5.1970.020.293CHRND2rs38282462.33E+08T0.17310.4167C5.1970.020.293CHRM31rs115852812.40E+08T0.38890.6667C5.1420.020.3182CHRM31rs120297012.40E+08C0.38890.6667T5.1420.020.3182CHRND2rs130264092.33E+08T0.17860.4167C5.0790.020.3043CHRNG2rs130184232.33E+08T0.17860.4167C5.0790.020.3043CHRM31rs6192142.40E+08G0.30.6111T5.0210.030.2727CHRM31rs21658722.40E+08T0.31480.5833C5.0030.030.3282CHRM31rs20838172.40E+08A0.31480.5833T5.0030.030.3282CHRND2rs49735372.33E+08G0.35710.625A4.8980.030.3333CHRND2rs37917292.33E+08T0.35710.625C4.8980.030.3333TRPV217rs354002744900415A0.071430.25G4.8980.030.2308CHRM31rs168386372.40E+08G0.32140.5833A4.8020.030.3383CHRM31rs18672652.40E+08A0.32140.5833G4.8020.030.3383CHRM31rs75510012.40E+08G0.32140.5833A4.8020.030.3383CHRM515rs60315234002435A0.46430.2083C4.6370.033.293CHRM31rs11556122.40E+08G0.40.6667A4.6160.030.3333CHRM27rs14245691.37E+08G0.40.6667A4.6160.030.3333TRPV217rs35144898298C0.074070.25G4.6010.030.24TRPV217rs129425404900777C0.074070.25G4.6010.030.24TRPM419rs1108396349162082G0.28260.5417A4.5340.030.3333CHRM27rs13644031.37E+08T0.41070.1667C4.4750.033.485TRPM39rs462034371121726T0.41070.1667C4.4750.033.485CHRM31rs127430422.40E+08C0.37040.6364T4.4730.030.3361CHRM31rs66885372.40E+08A0.40740.6667C4.470.030.3438CHRM515rs64695033999458T0.46150.2083C4.4610.033.257CHRM31rs21635462.40E+08G0.53850.2727A4.3960.043.111CHRM31rs15441702.40E+08A0.37040.625G4.3550.040.3529TRPM39rs381253270868677A0.37040.625C4.3550.040.3529CHRND2rs28534572.33E+08A0.50.25G4.2970.043CHRM31rs64291472.40E+08C0.29630.5417G4.2830.040.3563CHRM31rs67006432.40E+08C0.29630.5417T4.2830.040.3563CHRM31rs109259412.40E+08A0.29630.5417G4.2830.040.3563CHRM31rs5763862.40E+08C0.51920.25G4.240.043.24CHRNA94rs1001523140335548T0.19640.4167C4.2090.040.3422TRPV217rs339701194901606A0.035710.1667G4.1530.040.1852CHRM31rs18672632.40E+08A0.30360.5417G4.0630.040.3688CHRM515rs51142233990780C0.44640.2083T4.0630.043.065TRPM39rs1078095070578511T0.28850.08333C3.9790.054.459TRPV217rs20757634899389T0.037040.1667C3.9320.050.1923CHRM31rs6855502.40E+08C0.22220.04167T3.90.056.571CHRM31rs66942202.40E+08G0.42310.6667A3.8970.050.3667TRPV217rs1260200616433973G0.26920.5A3.8850.050.3684TRPV217rs722275416426430T0.44230.2083C3.8630.053.014CHRNB117rs38296037443722A0.25930.5C3.860.050.35CHRM31rs107546772.40E+08G0.38460.625A3.8190.050.375CHRM31rs75137462.40E+08G0.38890.625A3.7270.050.3818CHRM31rs108027952.40E+08C0.38890.625T3.7270.050.3818CHRM31rs37384362.40E+08A0.38890.625C3.7270.050.3818CHRM31rs75119702.40E+08A0.38890.625G3.7270.050.3818CHRM31rs11556112.40E+08T0.38890.625C3.7270.050.3818CHRM31rs10198822.40E+08G0.38890.625A3.7270.050.3818CHRM31rs14167892.40E+08G0.38890.625A3.7270.050.3818CHRM31rs109259642.40E+08A0.38890.625T3.7270.050.3818CHRNB117rs23027677447224C0.27780.5T3.7250.050.3846

[0266] Further genotype analysis for differences between CFS / ME and the non-fatigued group was also completed according to a two column χ2 test with significance of p <0.05 and results are presented in Table 13. Analyses were performed at the Australian Genome Research Facility Ltd, The Walter and Eliza Hall Institute, Parkville, Victoria, Australia. Table 13: Analysis of the genotype, odds ratio and significance of SNPs in B cell genes for TRP ion channels and AChRs in Chronic Fatigue Syndrome / Myalgic Encephalomyelitis patients and non-fatigued controls in rank order of significance.GeneCHRMRef SNPGenotypeCFS (%)Non Fatigued Controls (%)χ2ORP-VALUECHRNB117rs3829603CC8 (72.7%)1 (9.1%)9.2126.670.002CHRNB117rs4151134TT7 (63.6%)1 (9.1%)7.0717.500.008CHRNB117rs2302767TT7 (63.6%)1 (9.1%)7.0717.500.008CHRNA420rs11698563CC6 (54.5%)1 (9.1%)5.2412.000.022CHRNB117rs7210231CA7 (63.6%)2 (18.2%)4.707.880.030TRPM39rs7038646AG9 (81.8%)4 (36%)4.707.880.030TRPC611rs10791504GG7 (63.6%)2 (18.2%)4.707.880.030CHRM31rs1867264TA8 (72.7%)3 (27.3%)4.557.110.033CHRM31rs6688537CA8 (72.7%)3 (27.3%)4.557.110.033 Results Participants

[0267] There were 11 CFS / ME patients (age=31.82 ± 5.50 years) of which 72.7% were females. There were 11 non-fatigued controls (age= 33.91 ± 5.06 years), comprising 63.6% females. All participants in both groups were of European decent and were residents of Australia at the time of blood collection. There were no significant changes in white blood cell counts between CFS / ME patients and the non-fatigued control group. Table 11 outlines participants' characteristics.SNP Analysis

[0268] Of 661 SNPs identified in TRP ion channel and AChR genes from B cells a total of seventy-seven SNPs were associated with nicotinic and muscarinic acetylcholine receptor genes in CFS / ME patients. A total of thirty-five SNPs for mAChM3 featured, while the remaining predominate SNPs were identified for nAChR delta (n=12), nAChR alpha 9 (n= 5), TRPV2 (n= 7), TRPM3 (n=4), TRPM4 (n=1), mAChRM2 (n=2) and mAChRM5 (n=3). Table 12 represents the SNPs for TRP ion channel and AChR genes in B lymphocytes.Genotype Analysis

[0269] Nine genotypes were identified from SNPs that reported significant for TRPM3 (n=1), TRPC6 (n=1), mAChRM3 (n=2), nAChR alpha 4 (n=1) and nAChR beta 1 (n=4). Table 13 represents the genotypes for SNPs in TRP and AChR genes from B lymphocytes that were reported as statistically significant between groups. The odds ratio for specific genotypes for SNPs in TRP and AChR genes from B lymphocytes ranged between 7.11 - 26.67 for CFS / ME compared with the non-fatigued control group.

[0270] Genotype with 11 CFS / ME patients and 11 non-fatigued controls. Data presented are included for p<0.05. Data are presented for gene (TRPM3, TRPC6, AChRM3, alpha 3,4, 7 and beta 1), chromosome location (CHR), reference SNP identification (RefSNPID), genotype percentage of CFS / ME patients with genotype (%), percentage of non-fatigued controls (5), chi-square (χ2) for basic allelic test (1 df), odds ratio (OR) and (*) P-value for this test set at a significance of <0.05.Discussion

[0271] The current investigation reports novel findings for a number of SNPs in genes for AChR and TRP variants and genotypes from B cells from CFS / ME patients. These data are consistent the inventors' findings above in PBMCs and NK cells, showing B cells of high SNP prevalence and genotypes in TRP and AChR genes in CFS / ME patients.

[0272] Intracellular Ca 2+< levels are substantially modulated by receptor induced alterations and are critical for lymphocyte differentiation and function. Ca 2+< regulates antigen receptors, co-receptors, signal transduction, mitochondrial function, transcriptional factors and gene expression [42x-45x]. For example Ca 2+< entry is regulated by plasma membrane channels, intracellular receptor channels, non-selective cation channels, specific membrane transporters and cell membrane potential [20x, 45x, 46x].

[0273] The immune system is dependent on cholinergic signaling as B and T cells express cholinergic receptors and regulate cytokines in inflammatory responses [47x, 48x] and immune function [49x]. Cholinergic signaling influences both B cell [9x] and T cell [50x] responses and has been found to initiate B cell autoimmunity [51x]. In cholinergic receptor SNPs, mAChM3R featured significantly (45%) which is consistent with the inventors' findings of SNPs and their genotype in NK cells. In this current investigation there were two SNP genotypes reported for mAChM3R. However, given the small sample number as well as noting the inventors' previous results of SNP genotypes from isolated NK cells and PBMCs, other genotypes for this receptor may be present in CFS / ME patients. A recent study has reported a subgroup of CFS / ME patients who had muscarinic antibodies (mAChM3R) and a modest positive response occurred with reduced symptom presentation following anti-CD20 intervention [39x]. As this finding was only reported in a small group of patients and genotype SNPs were not reported, the inventors' current findings, along with their previous SNP genotype findings in isolated NK cells from a larger cohort, suggest these SNP genotype changes and their combinations may play a role in B cell function. Moreover, the ubiquitous distribution of cholinergic receptors throughout the body suggests that anomalies in SNP genotypes and their heterodimer configuration and pattern may contribute to the various clinical symptoms of CFS / ME.

[0274] The inventors have identified SNPs in muscarinic and nicotinic receptors from diverse blood cells, such as PBMC and isolated natural killer cells in larger cohorts of CFS / ME patients, suggesting cholinergic signaling may be impeded in this disorder. Muscarinic signaling has a role in gastrointestinal function [52x] as antibodies to mAChM3Rs have been found to inhibit gastrointestinal motility and cholinergic neurotransmission [53x]. The mAChM3Rs are widely distributed in the heart, where they regulate intracellular phosphoinositide hydrolysis to improve cardiac contraction, haemodynamic function [54x] and provide a protective effect against ischaemia [55x]. The mAChM3Rs are located in the pancreas where they mediate acetylcholine control over insulin secretion and have other important regulatory functions [56x-58x].

[0275] Nicotinic signaling via nAChRs is widely distributed in organisms demonstrating the universal character of cholinergic signaling. Muscle-type nAChRs, such as β1, are similar in all parts of the body [7x]. In the inventors' data, there is high demonstration of SNPs and genotypes in nAChRs, suggesting the extent of SNP genotypes in cholinergic receptors may play a role in B cell function, as acetylcholine functions as a paracrine / autocrine regulator of immune and other physiological functions [59x]. The present data highlights the SNP genotypes for nAChR beta 1 where SNPs rs3829603 (C / C) and rs4151134 (T / T) are located in the 3' untranslated region and demonstrate significant odds ratio for these genotypes that range between 17.50-26.67 for the CFS / ME group. This location is a regulatory region that post-transcriptionally influences gene expression: 3'-UTR is a binding site for regulatory proteins [60x]. Binding to specific sites within the 3'-UTR may decrease gene expression of various mRNAs by either inhibiting translation or directly causing degradation of the transcript. Additionally, the agonist-binding site of nAChRs is located at the interface between adjacent subunits. Binding of the agonist that is located at the α subunit (α1, α2, α3, α4, α6, α7, or α9), and the binding of the negative agonist-binding site is composed by α10, β2, β4, δ, γ, or ε subunit. Importantly α5, β1, and β3 subunits assemble in the receptor complex assumes the fifth subunit position, where they do not directly participate in the formation of the agonist-binding site, however, they form an integral configuration for the binding agonists and ligand selectivity [61x]. Given the number of SNP genotypes for nAChR β1 that were located at the 3'UTR, the fifth subunit may alter ligand selectivity. Moreover, various subunit combinations have been shown to result in different nAChR subtypes that vary in the kinetic parameters and selectivity of the ion channels, as well as ligand specificity, signaling pathways and functions that are performed in different tissues [62x]. The density of distribution of AChRs throughout the body means that many tissues are likely to be affected where AChR expression occurs, suggesting a potential loss of function of neuronal and non-neuronal cholinergic signaling pathways in virtually all body tissues. Interestingly, the inventors and others have previously reported changes in B cell phenotypes from CFS / ME patients [26x, 63x] and in a study above the inventors reported a reduction in calcium mobilisation into B cells via TRPM3 where this receptor was identified to have 3'UTR SNP genotypes.

[0276] Cholinergic signaling in the brain is primarily focused on two main loci, the basal forebrain and the pedunculo-pontine area of the hindbrain [64x]. Acute vasoconstriction occurs after removal of the cholinergic parasympathetic input to forebrain cerebral arteries [65x], indicating the critical importance of intact cholinergic signaling in the brain. Both nicotinic and muscarinic cholinergic signaling influence hippocampal synaptic plasticity and processing cholinergic-dependent higher cognitive functions [66x]. Cholinergic and glutamatergic signaling demonstrate interdependence in cortical glial cell function in sleep / wake studies [67x]. Key CNS functions such as memory formation are associated with long term potentiation (LTP) in hippocampal synapses. This memory mechanism is Ca 2+< dependent through its association with cholinergic signaling [68x].Conclusion

[0277] These findings of SNP genotypes in cholinergic and TRP receptor genes in B cells, and previously in PBMCs and isolated NK cells, suggest a potential contribution to widespread pathology across all organ systems of the body including immune, CNS, heart, gastrointestinal and hormonal systems. The effects of these SNP genotypes on cholinergic signaling are likely to be particularly important in the central nervous system, peripheral nervous system, autonomic nervous system as well as other organ systems. Taken together, the functional effects of these SNP genotypes and their combinations suggest they may be contributing factors in the aetiology and clinical phenotypes of CFS / ME.Example 7 - Reduction in TRPM3 cell surface expression in NK cells and B lymphocytes from CFS / ME patients as well as decreased intracellular calcium

[0278] The inventors in the Examples above identify SNPs in TRP ion channels, namely from the TRPM3 family (rs12682832; rs11142508; rs1160742; rs4454352; rs1328153; rs3763619; rs7865858; rs1504401; rs10115622), as well as TRPA1 (rs2383844; rs4738202) and TRPC4 (rs6650469; rs655207) in CFS / ME patients, as well as SNPs in ACh receptors, mainly muscarinic M3 receptors (mAChRm3), (rs4463655; rs589962; rs1072320; rs7543259; rs6661621; rs7520974; rs726169; rsrs6669810; rsrs6429157), as well as nicotinic ACh receptors (nAChR) alpha 10 (rs2672211; rs2672214; rs2741868; rs2741870; rs2741862), alpha 5 (rs951266; rs7180002), and alpha 2 (rs2565048; P = 0.01403. These ion channels and receptors are widely expressed in cells and tissues throughout the body and are strongly associated with the symptomatology often reported in CFS / ME. The inventors demonstrated that these are exhibited in 99-100% of n=115 CFS / ME patients compared to 0-1% in healthy controls of n=90 (see Table 7).

[0279] Data presented for gene (TRPM3 and mAChR3), chromosome location (CHR), reference SNP identification (Ref SNP ID), base pair (BP) location of SNP, alleles (A1 and A2), chi-square (χ2) for basic allelic test (1 df), p-value for this test set at a significance of p <0.05, odds ratio (OR), percentage of CFS patients with SNP and percentage of non-fatigue controls with SNPs.

[0280] Recently others have reported muscarinic acetylcholine receptors (mAChR3) have been found to inhibit TRPM3 via the action of phospholipase C [41y]. Given the present inventors found a significant association with SNPs in TRPM3 and mAChR3 in CFS / ME patients and both these receptors mediate calcium mobilization intracellularly for cell function, such as NK lysis, the present inventors investigated TRPM3 surface expression on NK cells and B lymphocytes and determined this phenotype in CFS / ME patients compared to healthy controls.

[0281] In this Example the inventors describe, for the first time, significant reduction in TRPM3 cell surface expression in NK cells and B lymphocytes from CFS / ME patients as well as decreased intracellular calcium.Methods

[0282] Sample preparation and other steps were carried out largely as described in Example 5.TRPM3 immunophenotyping assay

[0283] PBMCs were incubated in 20µl of FCR blocking reagent (Miltenyi Biotech) for 10 minutes at room temperature and washed with phosphate buffer saline (PBS) and centrifuged at 400g for 5 minutes. Supernatant was removed and incubated with primary fluorochrome labelled antibodies (CD19-BV421, CD3-PerCP, CD56-BV421 and CD16-APC Cy7, BD Bioscience) for 30 minutes at room temperature in the dark. Labelled cells were washed and incubated with 10µg final concentration of goat anti-human TRPM3 antibody for 30 minutes, followed by a wash and resuspended in a final concentration of 5% (v / v) of Bovine Serum Albumin (Sigma) for 30 minutes. Cells were washed again and incubated with 5 µg final concentration of donkey anti-goat IgG FITC (Santa Cruz) for 30 minutes. Cells were washed cells and resuspended in 200 µl of staining buffer (BD Bioscience) and acquired at 50, 000 events using LSRFortessa X-20 (BD Bioscience). Lymphocyte populations were identified using forward scatter and side scatter (FSC, SSC) dot plots. Exclusions were CD3 +< cells and only CD3 -< lymphocytes were further used to characterize B lymphocytes and NK cell subset populations using CD19, CD56 and CD16. Total B cells were identified as CD19 +< , whereas NK cell subsets were characterized using the expression of CD56 Bright< CD16 Dim-< NK cells, CD56 Dim< CD16 Bright+< NK cells and CD56 -< CD16 +< NK cells. NK lysis, degranulation and lytic proteins were conducted as previously described [42y].

[0284] LSRFotessa X-20 Flow cytometry was utilized for sequential determination of cytoplasmic calcium [Ca2 +< ]C and mitochondrial [Ca2 +< ]M, to help compare cytoplasmic or mitochondrial Ca 2+< influx kinetics in B lymphocytes and NK cells. Characterizing kinetic measurements using median florescence of Fura-AM or Rhod-2 AM dye were used and smoothing curve method was applied to measure the area under the curve (AUC).Cytoplasmic calcium influx assay

[0285] Following phenotypic staining, the cells were incubated with 0.5ml staining buffer that contained 0.02% Pluronic ®< F-127 and 1µM Fura-red AM or Rhod-2 AM for 30 minutes in the incubator at 37°C. Stained cells were washed with DPBS without calcium and magnesium. Fura AM stained cells were stimulated after 30 seconds of flow cytometric acquisition in the presence of either a final concentration of 1.4 µg streptavidin, 714ng ionomycin, 50µg 2-APB or 14µg Thapsigargin. Data was recorded over 4 minutes. Rhod-2 AM stain cells were incubated for a further 12 hours, prior to acquisition. Thapsigargin is a potent inhibitor for Calcium-ATPases receptors and raises cytoplasmic calcium concentration by inhibiting the ability for the cells to pump calcium into the endoplasmic reticulum (ER). 50µg 2-aminoethoxydiphenyl borate (2-APB) was used given its inhibition of ER and IP 3 R. NK receptors (NG2DA and NKp46) were identified for cross-linking for calcium influx for activation, co-activation, and co-stimulation of resting human NK cells, whereas, CD19 and complement receptor CR2 (CD21) responsible for signal transduction and activation of Immunoglobulin M (IgM) were identified for cross-linking for induced calcium influx to enhanced activation of CD19+ B cells.Statistical analysis

[0286] Statistical analysis was performed using IBM SPSS Statistics version 22 software (SPSS, Chicago, USA). Significance was tested by MANOVA (p<0.05 for significance) between healthy and CFS / ME groups using parameters including TRPM3, intracellular and calcium influx in B lymphocytes and NK cells. Flowjo was employed to analyze FCS files extracted from FACSDiva 8 software (BD Bioscience). Post Hoc test was performed to determine specifically where the significance was between groups (Control and CFS / ME). Levene test was used to analyze homogeneity of variance between groups.Discussion

[0287] The inventors have identified, for the first time, TRPM3 on NK cells and B lymphocytes, and also report a significant reduction of TRPM3 surface expression on B lymphocytes and NK cells in CFS / ME patients compared with healthy controls (see Figure 3A and Figure 3B).

[0288] The inventors also report, for the first time, a significant reduction in cytoplasmic calcium ion concentration in CD19 +< B lymphocytes during cross-linking between CD21 and IgM following treatment with stepadividin or thapsigargin in CFS / ME patients (Figure 4A) as well as CD56 Bright< NK cells also had a significant decrease in cytoplasmic calcium in the presence of 2-APB and thapsigargin in CFS / ME patients (Figure 4B). Collectively, these findings suggest TRPM3 play a role in impaired calcium cytoplasmic influx in B lymphocytes and NK cells from CFS / ME patients.Example 8 - Other SNPs and genotypes in TRP ion channel and AChR genes from peripheral blood mononuclear cells (PBMCs), isolated B lymphocytes and NK cells in CFS / ME patients

[0289] Examples above describe SNPs of TRP ion channel and AChR genes from PBMCs, isolated B lymphocytes and NK cells that scored significantly in a cohort of 115 CFS / ME patients. Using larger cohorts, the inventors believe that other identified SNPs will also score significantly, thus also being useful as probes, tools or reagents for identifying, screening, diagnosing, monitoring or treating subjects with, or predisposed to, medical conditions (or symptoms thereof), such as chronic fatigue syndrome (CFS), myalgic encephalomyelitis (ME), Gulf war syndrome (GWS), irritable bowel syndrome (IBS), multiple chemical sensitivity (MCS), fibromyalgia, and migraine, as well as some medical conditions caused by dysregulation in calcium, acetylcholine and TRP, and dysregulation in the gastrointestinal, cardiovascular, neurological, genitourinary and immune systems.

[0290] Identified SNPs that have p values of 0.05 to 0.1, which the inventors believe may score significantly in a larger cohort of patients, are listed in the tables below (Tables 14 to 17). Table 14: Analysis of the frequency distribution and significance of AChR gene SNPs in PBMCs in CFS / ME patients and non-fatigued controls that were not significant in n=115, in rank order of significance.GeneChromosomeRefSNP IDA1Frequency_AFrequency_UA2χ2PnAchα1011rs2672215A0.46070.36C3.3990.07nAchα28rs6474413C0.23080.1513T3.3360.07mAchM33rs10926008G0.37220.277A3.3330.07nAchα28rs2741343C0.53370.4324T3.3170.07nAchα515rs7178270G0.35710.4539C3.2310.07nAchα515rs4243084G0.39770.3026C3.2270.07nAchα515rs601079A0.39010.4868T3.1550.08nAchα515rs12911602C0.39010.4868T3.1550.08nAchα515rs588765T0.38460.4803C3.0950.08nAchα515rs680244A0.38460.4803G3.0950.08nAchα515rs6495306G0.38950.4863A3.010.08nAchα515rs6495307T0.41110.5068C2.9970.08mAchM33rs12093821A0.4890.3947G2.9790.08mAchM33rs16838637G0.48890.3947A2.9570.09nAchα28rs6997909A0.23330.1579G2.9450.09nAchα1011rs2672216C0.48880.3947T2.9340.09mAchM33rs6429165A0.24730.1711G2.8730.09nAchα28rs891398C0.5330.4392T2.8720.09nAchα515rs4366683G0.39560.4868A2.8020.09nAchα28rs6985052C0.23080.1579T2.7740.10nAchα28rs4950C0.23080.1579T2.7740.10 Table 15: Analysis of the frequency distribution and significance of TRP receptor gene SNPs in PBMCs in CFS / ME patients and non-fatigued controls that were not significant in n=115, in rank order of significance. GeneChromosomeRefSNP IDA1Frequency_AFrequency_UA2χ2PTRPM419rs10403114GA0.2930.3903.8020.051TRPV317rs9909424GA0.1150.0603.4420.064TRPC413rs612308AG0.4390.5373.3930.065TRPM39rs7860377AC0.3500.2623.3140.069TRPC75rs2673930CA0.2000.2803.2180.073TRPC413rs603955CT0.4450.5363.0080.083TRPM39rs11142798CG0.1350.2022.9980.083TRPM39rs4744611GA0.3600.4462.8430.092TRPM221rs1785452TC0.2150.2892.670.102TRPM39rs1566838GT0.4600.3752.6690.102TRPA18rs1384002TC0.4950.4102.6640.103TRPM69rs2274924GA0.1150.1752.6520.103TRPM39rs1394309GA0.0300.0652.6080.106TRPC413rs2985167GA0.3400.4222.5770.108TRPM511rs2301698GT0.5300.4462.5510.110TRPM69rs944857CT0.1850.1252.4760.116TRPM221rs762426GA0.1600.2232.3250.127 Table 16: Analysis of the frequency distribution and significance of AChR and TRP gene SNPs in isolated NK cells in CFS / ME patients (n=39) and non-fatigued controls (n=30) that were not significant, in rank order of significance. GeneCHRSNPBPMAFA1F_AF_UA2CHISQPORCHRM515rs623941340603770.362221C0.42110.25A3.760.052492.182CHRNA315rs615470785936460.291134T0.28950.45C3.7490.052850.4979CHRNA315rs7182583786068680.271565C0.28950.45G3.7490.052850.4979CHRM31rs5360712.4E+080.352236C0.46150.3T3.7150.053912CHRM31rs6939482.4E+080.446486G0.46050.3A3.6330.056651.992TRPM39rs4620343711217270.428115T0.37180.5345C3.5710.058790.5155CHRNA515rs495956785775880.308307G0.29490.45A3.5320.060190.5111CHRNA515rs692780785841630.5G0.29490.45C3.5320.060190.5111CHRNA515rs11637635785848080.254593A0.29490.45G3.5320.060190.5111CHRNA315rs17408276785892760.208866C0.29490.45T3.5320.060190.5111CHRNA315rs660652785954900.256989A0.29490.45G3.5320.060190.5111CHRNA315rs472054785956520.256989T0.29490.45C3.5320.060190.5111TRPC413rs6650469377938120.399561T0.52560.3667C3.4540.063081.914CHRNB415rs1316971786381680.442492A0.1410.2667G3.4020.065130.4515CHRNA315rs4887070786238450.339457C0.26920.4167T3.3170.068550.5158CHRM515rs8035849340581320.34385A0.3590.2167C3.2890.069762.025CHRM31rs6067092.4E+080.347444T0.43420.2833C3.2830.071.941TRPC211rs289893436238270.14996C0.17950.07143A3.2730.070422.844TRPM82rs101706472.34E+080.207867G0.10530.2167T3.1870.074230.4253CHRNA715rs2337980321519950.375T0.39740.55C3.1740.074820.5397CHRNA315rs514743785918850.241214T0.30260.45A3.1320.076760.5304CHRND2rs28534462.33E+080.480232C0.55260.4T3.1270.0771.853CHRND2rs22456012.33E+080.483427T0.55130.4C3.1070.077951.843CHRM31rs67011812.4E+080.491014T0.38460.5333C3.0310.081670.5469TRPV412rs38253941.1E+080.245607A0.38460.5333C3.0310.081670.5469TRPV412rs18618091.1E+080.239617T0.38460.5333C3.0310.081670.5469CHRND2rs22784782.33E+080.272564C0.19740.3276T2.9460.08610.5047TRPC413rs655207377938750.388179G0.51280.3667T2.9280.087071.818CHRNE17rs207576348993900.10623T0.051280.1333C2.8760.089930.3514TRPM39rs10123815710689150.1248G00.03571A2.8280.092640TRPC611rs657839736143800.427516T0.38460.25A2.7970.094471.875CHRM31rs120361412.4E+080.473442A0.35530.5G2.7790.095510.551TRPV412 1 s108507831.1E+080.273163A0.39470.5333C2.5960.10710.5707 Table 17: Analysis of the frequency distribution and significance of AChR and TRP gene SNPs in isolated B lymphocytes in CFS / ME patients (n=11) and non-fatigued controls (n=11) that were not significant, in rank order of significance. GeneCHRSNPBPA1F AF_UA2CHISQPORCHRM31rs10754677239669799G0.38460.625A3.8190.050660.375CHRM31rs7513746239699110G0.38890.625A3.7270.053530.3818CHRM31rs10802795239707474C0.38890.625T3.7270.053530.3818CHRM31rs3738436239709192A0.38890.625C3.7270.053530.3818CHRM31rs7511970239719954A0.38890.625G3.7270.053530.3818CHRM31rs1155611239734526T0.38890.625C3.7270.053530.3818CHRM31rs1019882239735555G0.38890.625A3.7270.053530.3818CHRM31rs1416789239738344G0.38890.625A3.7270.053530.3818CHRM31rs10925964239739213A0.38890.625T3.7270.053530.3818TRPV217rs807901016425640C0.48150.25T3.680.055082.786CHRM31rs6429154239713965G0.39290.625A3.6420.056340.3882CHRNB117rs23027677447224C0.27780.5T3.6250.056910.3846TRPM39rs703864670822907A0.48080.25G3.6210.057062.778CHRNA28rs274134227472578A0.17860.375G3.5790.05850.3623CHRND2rs4973536232527170C0.35710.5909G3.5360.060040.3846C17orf10717rs339789194899033A0.074070.2273G3.5140.060850.272TRPM39rs189130171403579T0.55770.3333C3.3090.068922.522CHRM31rs12406493239689804C0.55560.3333A3.2840.069952.5CHRM31rs6429152239690836G0.55560.3333A3.2840.069952.5CHRM31rs2355237239694223A0.55560.3333G3.2840.069952.5CHRM31rs988231239696189C0.55560.3333T3.2840.069952.5CHRM31rs717227239719298C0.55560.3333T3.2840.069952.5TRPM39rs110694871402257T0.55360.3333C3.2620.070922.48CHRNA28rs256504827472614C0.1250.2917T3.2320.07220.3469CHRNB117rs23027627455541T0.27780.5C3.2220.072670.3846CHRM31rs1431719239717902G0.40380.625A3.2210.072680.4065AVEN15rs270228234023860G0.46430.25T3.2140.0732.6CHRM31rs6693851239678896C0.31820.5455T3.1730.074860.3889CHRM31rs2278642239703842T0.40740.625G3.1550.075690.4125CHRM31rs12751235239706520T0.40740.625C3.1550.075690.4125CHRM31rs6663632239714420A0.40740.625C3.1550.075690.4125CHRM31rs665159239798701C0.40740.625T3.1550.075690.4125TRPM419rs1246121649160966C0.071430.2083G3.1540.075750.2923CHRM31rs714803239631122T0.37040.5833A3.0650.080010.4202CHRM31rs2120241239645190T0.28850.5A3.0350.081460.4054AC009264.17rs1455858136946955A0.50.2917G2.9630.085192.429AC009264.17rs1378646136950253G0.50.2917A2.9630.085192.429AC009264.17rs1158586136952388G0.50.2917A2.9630.085192.429AC009264.17rs1455857136955193A0.50.2917G2.9630.085192.429CHRM31rs685548239831605T0.50.2917G2.9330.08682.429CHRM31rs16839070239900649T0.35710.1667A2.9020.088442.778CHRNG2rs2697782232542805C0.35710.1667G2.9020.088442.778CHRNB21rs2072660154576244T0.19640.375C2.8570.090970.4074TRPM715rs477589450611402T0.43750.2273C2.8560.091052.644CHRM31rs6657343239728210T0.5370.3333A2.7650.096342.32CHRM31rs891700239718625A0.53570.3333G2.7590.096692.308AC018890.62rs2600685174762319G0.44640.25A2.7310.098412.419AVEN15rs168511933984851G0.44640.25A2.7310.098412.419AVEN15rs48983233985705A0.44640.25G2.7310.098412.419AC009264.17rs2113550136881785G0.29630.5A2.6570.10310.4211AC009264.17rs6944132136885528T0.44440.25A2.6540.10332.4CHRNA1011rs26722143670281C0.42590.2273T2.6510.10352.523CHRM31rs658842239785334T0.42590.625A2.6360.10450.4452TRPV217rs812116422653C0.3750.1667T2.6190.10563 Example 9 - Exome sequencing for determining SNPs and genotypes in TRP ion channel and AChR genes from isolated B lymphocytes in CFS / ME patients

[0291] Example 6 above describes SNPs and genotypes in TRP ion channel and AChR genes from isolated B lymphocytes in ME / CFS patients. In this Example the inventors utilise exome sequencing to characterise SNPs and genotypes in TRP ion channel and AChR genes from isolated B lymphocytes in ME / CFS patients.Methods

[0292] For details of the subjects and sample preparation, see Example 6.DNA extraction

[0293] Genomic DNA was extracted from all whole blood samples using the Qiagen DNA blood mini-kit as per manufacturer's instructions (Qiagen). The Nanodrop (Nanodrop) was used to assess the quality and quantity of the DNA extracted. Approximately 2µg of genomic DNA was used in the SNP assay.DNA quantification and qualification

[0294] DNA degradation and contamination was monitored on 1% agarose gels. (1) DNA purity was checked using the NanoPhotometer ®< spectrophotometer (IMPLEN, CA, USA). (2) DNA concentration was measured using Qubit ®< DNA Assay Kit in Qubit ®< 2.0 Flurometer (Life Technologies, CA, USA). (3) Fragment distribution of DNA library was measured using the DNA Nano 6000 Assay Kit of Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Library preparation for sequencing

[0295] A total amount of 1µg genomic DNA per sample was used as input material for the DNA sample preparation. Sequencing libraries were generated using Agilent SureSelect Human All ExonV5 kit (Agilent Technologies, CA, USA) following manufacturer's recommendations and x index codes were added to attribute sequences to each sample. Briefly, fragmentation was carried out by hydrodynamic shearing system (Covaris, Massachusetts, USA) to generate 180-280bp fragments. Remaining overhangs were converted into blunt ends via exonuclease / polymerase activities and enzymes were removed. After adenylation of 3' ends of DNA fragments, adapter oligonucleotides were ligated. DNA fragments with ligated adapter molecules on both ends were selectively enriched in a PCR reaction. After PCR reaction, the library was hybridized with Liquid phase with biotin labeled probe, then magnetic beads with streptomycin were used to capture the 334,378 exons in 20, 965 genes. Captured libraries were enriched in a PCR reaction to add index tags to prepare for hybridization. Products were purified using AMPure XP system (Beckman Coulter, Beverly, USA) and quantified using the Agilent high sensitivity DNA assay on the Agilent Bioanalyzer 2100 system.Clustering and sequencing

[0296] If library qualifies, the clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v4-cBot-HS (Illumia, San Diego, USA) according to the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an Illumina platform and 125 bp paired-end reads were generated.Analysis ResultRaw data

[0297] The original raw data obtained from high throughput sequencing platforms (e.g. illumina platform) was transformed to sequenced reads by base calling and recorded in FASTQ file (which contains sequence information (reads) and corresponding sequencing quality information) as explained in Section 4.1 of Novogene Bioinformatics Technology Co., Ltd's document entitled "Novogene - Cancer Project Report (2014, 11), which is accessible at www.filgen.jp / Product / Bioscience5-seq / Cancer_WGS_report_V1.1_pdf.Quality controlSequencing data filtration

[0298] The steps of data processing undertaken were as explained in Section 4.2.1 of Novogene Bioinformatics Technology Co., Ltd's document entitled "Novogene - Cancer Project Report (2014, 11), which is accessible at www.filgen.jp / Product / Bioscience5-seq / Cancer_WGS_report_V1.1.pdf.Sequencing error rate distribution

[0299] A Phred score of a base (Phred score, Qphred) was calculated as explained in Section 4.2.2 of Novogene Bioinformatics Technology Co., Ltd's document entitled "Novogene - Cancer Project Report (2014, 11), which is accessible at www.filgen.jp / Product / Bioscience5-seq / Cancer_WGS_report_V1.1.pdf.Sequencing quality distribution

[0300] Sequence quality distribution was carried out as explained in Section 4.2.4 of Novogene Bioinformatics Technology Co., Ltd's document entitled "Novogene - Cancer Project Report (2014, 11), which is accessible at www.filgen.jp / Product / Bioscience5-seq / Cancer_WGS_report_V1.1.pdf.To ensure downstream analysis, most base quality is required to be greater than Q20. According to sequencing feature, base quality in sequence end is usually lower than that in sequence beginning.Statistics summary of sequencing quality

[0301] According to the illumina platform sequencing feature, for PE data the average percentage of Q20 was required to be above 90%, Q30 was required to be above 80%, average error rate was required to be below 0.1%. (See Section 4.2.5 of Novogene Bioinformatics Technology Co., Ltd's document entitled "Novogene - Cancer Project Report (2014, 11), which is accessible at www.filgen.jp / Product / Bioscience5-seq / Cancer_WGS_report_V1.1.pdf. Table 18 - Overview of data production qualitySample name Library Lane Raw reads Raw data( G) Raw depth( x) Effective( %) Error( %) Q20( %) Q30( %) GC( %) SEV11140 47DHE015 87HCWL3CCXX _L6258146 407.74153.698.920.0494.2886.8248.55SEV11140 46DHE015 95HF5KJCCXX_ L5276685 418.3164.7198.960.0396.2990.7848.45SEV11140 65DHE015 85HCWL3CCXX _L3211955 326.36126.2198.890.0494.8288.2548.64SEV11140 64DHE015 94HF5KJCCXX_ L5211469 206.34125.8298.930.0396.2590.6948.89SEV11140 01DHE016 05HF5KJCCXX_ L4276470 158.29164.5198.870.0396.3690.9748.77SEV11140 66DHE016 02HF5KJCCXX_ L7221544 176.65131.9798.710.0395.0888.4149.27SEV11140 06DHE015 84HCWL3CCXX _L6208590 726.26124.2398.800.0494.2886.8448.28SEV11140 49DHE015 82HCWL3CCXX _L4237312 737.12141.398.980.0495.0688.6848.86SEV11140 20DHE016 01HF5KJCCXX_ L5250660 037.52149.2398.370.0396.4491.0849.22SEV11140 22DHE015 98HF5KJCCXX_ L5204847 646.15122.0598.870.0396.2690.6848.52SEV11140 25DHE015 91HF5KJCCXX_ L5253430 557.6150.8298.870.0396.890.849.0SEV11140 26DHE015 93HF5KJCCXX_ L5242107 787.26144.0799.060.0396.1890.5748.98SEV11140 29DHE016 04HF5KJCCXX_ L4228250 906.85135.9498.770.0396.2290.6947.81SEV11140 52DHE015 92HF5KJCCXX_ L5228624 296.86136.1498.980.0396.1390.4148.09SEV11140 54DHE015 86HCWL3CCXX _L6185079 706.76134.1598.850.0594.0386.4148.08SEV11140 54DHE015 86H3LLHBBXX_ L2404468 298.820.0395.1689.0247.95SEV11140 55DHE016 03HF5KJCCXX_ L4284998 108.55169.6798.800.0396.4391.0949.28SEV11140 56DHE015 90HCWL3CCXX _L3223384 486.7132.9698.920.0493.9186.4348.62SEV11140 33DHE015 88HCWL3CCXX _L6243510 607.31145.0798.820.0792.0683.2448.48SEV11140 17DHE015 80HCWL3CCXX _L3198119 086.79134.7598.650.0494.8488.2248.42SEV11140 17DHE015 80H3LLHBBXX_ L2284161 598.650.0395.2289.1148.33SEV11140 36DHE015 99HF5KJCCXX_ L5292496 828.77174.0498.760.0396.591.1949.01SEV11140 13DHE015 97HF5KJCCXX_ L5207993 946.24123.8398.850.0396.3190.8148.97SEV11140 38DHE015 83HCWL3CCXX _L6227370 756.82135.3498.350.0494.2786.9344.61SEV11140 35DHE016 00HF5KJCCXX_ L5238642 537.16142.0998.860.0395.9490.0149.42SEV11140 18DHE015 96HF5KJCCXX_ L5260462 857.81154.9998.890.0396.3490.8748.28SEV11140 19DHE015 81HCWL3CCXX _L6228476 216.85135.9498.750.0494.3787.0148.7SEV11140 67DHE015 89HCWL3CCXX _L6296362 408.89176.4299.090.0594.0686.5248.18Note: Sample name: Sample name Library: Library name Lane: The flowcell ID and lane number of the sequencing machine Raw reads: The number of sequencing reads pairs; According to the format of FASTQ, four lines will be considered as one unit Raw data: The original sequence data Raw depth: The original sequence depth Effective: The percentage of clean reads in all raw reads Error: The average error rate of all bases on read1 and read2; the error rate of a base is obtained from equation No.1 Q20, Q30: Percentage of reads with average quality>Q20 and percentage of reads with average quality>Q30 GC: Percentage of G and C in the total bases Sequence alignment

[0302] Sequence alignment was carried out as explained in Section 4.3 of Novogene Bioinformatics Technology Co., Ltd's document entitled "Novogene - Cancer Project Report (2014, 11), which is accessible at www.filgen.jp / Product / Bioscience5-seq / Cancer_WGS_report_V1.1.pdf.Sequencing depth, coverage distribution

[0303] Sequence depth, coverage and distribution was carried out as explained in Section 4.3.1 of Novogene Bioinformatics Technology Co., Ltd's document entitled "Novogene - Cancer Project Report (2014, 11), which is accessible at www.filgen.jp / Product / Bioscience5-seq / Cancer_WGS_report_V1.1.pdf.Statistics of coverage

[0304] Variation detection resultSNV detection resultSNV statistical result

[0305] Generally, the whole genome of human has about 3.6M SNV. Most (above 95%) SNVs with high frequency (the allele frequency in population is above 5%) have records in dbSNP (Sherry S T, Ward M H, Kholodov M, et al. dbSNP: the NCBI database of genetic variation[J]. Nucleic acids research, 2001, 29(1): 308-311.(dbSNP)). The ration of Ts / Tv can reflect the accuracy of sequencing. Generally, the ratio in genome is about 2.2 and in coding region is about 3.2.

[0306] GATK was used to detect SNV, and the statistics of SNVs are as follows: Table 20 - The number of SNV in different genomic regionSample exo nic intr onic UT R3 UT R5 interg enic ncRNA_ exonic ncRNA_i ntronic upstr eam downst ream splic ing ncRNA_ UTR3 ncRNA_ UTR5 ncRNA_s plicing SEV11 14055226 93108 83651 2530 106293 02703760441371766249 910344100SEV11 14029221 52969 9045 9827 164933 62425667933351342243 81094790SEV11 14001219 59107 58149 4329 286102 12619737338651674243 11034392SEV11 14025221 04103 87248 1928 555938 82490725637211600245 7944679SEV11 14052213 97988 7846 8927 135186 02476655833471462238 21054890SEV11 14026218 34105 54449 1029 435962 725767014386716281241 71073584SEV11 14064219 87948 0646 5127 454964 82520628034011437234 0973572SEV11 14046219 13110 28950 5129 006701 92473760738341758240 01115973SEV11 14018221 32106 05648 9028 526413 42555763937491621247 512341104SEV11 14013220 38907 4845 4926 524407 02419574530541233249 11064292SEV11 14022230 40911 7145 2126 984442 92502594030021349250 71074687SEV11 14036219 00103 18648 2028 396161 42609730036301564242 71004387SEV11 14035221 05960 0746 6627 904928 02455628034281477244 81084277SEV11 14020223 06982 3846 8229 025208 72621660635141460243 611344101SEV11 14006219 61923 5844 2826 305061 62495636431361503239 3884384SEV11 14019222 56971 6545 0126 625644 92494648533591458244 3984191SEV11 14033219 03100 33746 8027 265630 22445673134841538235 11074685SEV11 14038199 32888 5538 2614 785543 31984618219131322219 7831879SEV11 14047224 93104 44147 8428 366248 42606724435531709246 01004582SEV11 14049223 47103 536474128 8161941245271103724166523971025086SEV11 14056220 15927 7746 6227 434793 32498614132731397244 0994191SEV11 14065223 24959 2449 8527 295280 02535652633061458241 51334385SEV11 14067221 92117 54651 7029 297583 52611811840291901248 41174293SEV11 14066219 87954 4945 2127 794679 62429599333881281238 81114577SEV11 14017225 04974 9853 5727 525892 92584681532911630243 21814694SEV11 14054223 57986 7250 0127 025837 92684681032211464241 61183584Note: Sample: Sample name exonic: The number of SNV in exonic region intronic: The number of SNV in intronic region UTR3: The number of SNV in 3'UTR region UTR5: The number of SNV in 5'UTR region intergnic: The number of SNV in intergenic region ncRNA_exonic: The number of SNV in non-coding RNA exonic region ncRNA_intronic: The number of SNV in non-coding RNA intronic region upstream: The number of SNV in the 1kb upstream region of transcription start site downstream: The number of SNV in the 1kb downstream region of transcription ending site splicing: The number of SNV in 4bp splicing junction region ncRNA_UTR3: The number of SNV in 3'UTR of non-coding RNA ncRNA_UTR5: The number of SNV in 5'UTR of non-coding RNA ncRNA _splicing: The number of SNV in 4bp splicing junction of non-coding RNA Table 21 - The number of SNV of different types in coding region Sample synonymous_SNV missense_SNV stopgain stoploss unknown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ote: Sample: Sample name synonymous_SNV: A single nucleotide change that does not cause an amino acid change missense_SNV: A single nucleotide change that cause an amino acid change stopgain: A nonsynonymous SNV that lead to the immediate creation of stop codon at the variant site stoploss: A nonsynonymous SNV that lead to the immediate elimination of stop codon at the variant site unknown: Unknown function (due to various errors in the gene structure definition in the database file) InDel detection resultIndel statistical result

[0307] See Section 4.4.2 of Novogene Bioinformatics Technology Co., Ltd's document entitled "Novogene - Cancer Project Report (2014, 11), which is accessible at www.filgen.jp / Product / Bioscience5-seq / Cancer_WGS_report_V1.1.pdf. Generally, the genome of human has about 350K InDel (insertion and deletion, less than 50bp insertion and deletion).

[0308] The InDel in coding region or splicing site may change the protein translation. Frameshift mutation, in which the number of inserted or deleted bases is not an integral multiple of three, may lead to the change of the whole reading frame. Compared to non-frameshift mutation, frameshift mutation is more limited by selective pressure.

[0309] GATK was used to detect Indel, and obtained InDel result is as follows: Table 22 - The number of InDel in different genomic regionsSample exo nic intr onic UT R3 UT R5 interg enic ncRNA_e xonic ncRNA_i ntronic upstr eam downst ream splic ing ncRNA_ UTR3 ncRNA_ UTR5 ncRNA_s plicing SEV11 14055672178 7379 449 21095 329913067802885589913SEV11 14029683158 5873 343 491172691156601223557131123SEV11 14001647176 2681 345 91038 2293123568528252820911SEV11 14025691169 9379 249 91046 12301274672266527121314SEV11 14052641161 9372 443 594942731111612258525141314SEV11 14026674169 0281 550 21015 82851153689275520101312SEV11 14064684153 9571 243 388332911039621237516141113SEV11 14046669179 4881 647 51190 32871307700302537111420SEV11 14018714174 8876 446 51173 9295131863628952315919SEV11 14013655147 2870 243 7810728398259220254691212SEV11 14022701146 2368 241 68114270102253923554213816SEV11 14036710172 1377 345 81108 02801308661268480111015SEV11 14035694153 2070 345 187752761056601229509161112SEV11 14020688161 6674 747 095013051124675278531141210SEV11 14006681144 1666 540 3896826510145492355067920SEV11 14019632157 3966 944 51008 0288113061424253512109SEV11 14033646149 0667 041 591642621074586231479141217SEV11 14038525147 8461 418 41064 8216112030623947516317SEV11 14047667163 1272 744 71051 5293120663228152491217SEV11 14049653164 1371 645 11063 62741142621230491101415SEV11 14056642144 5174 843 282092771002578228501131214SEV11 14065680149 0279 842 792622531051590255521141113SEV11 14067662180 5777 245 41195 52761297705296535121015SEV11 14066654149 2972 849 58035266969618225531101410SEV11 14017680158 4793 243 21070 72691167565297530381415SEV11 14054661154 0676 644 01009 8289112156124749511711Note: Sample: Sample name exonic: The number of InDel in exonic region intronic: The number of InDel in intronic region UTR3: The number of InDel in 3'UTR region UTR5: The number of InDel in 5'UTR region intergnic: The number of InDel in intergenic region ncRNA_exonic: The number of InDel in non-coding RNA exonic region ncRNA_intronic: The number of InDel in non-coding RNA intronic region upstream: The number of InDel in the 1kb upstream region of transcription start site downstream: The number of InDel in the 1kb downstream region of transcription ending site splicing: The number of InDel in 4bp splicing junction region ncRNA_UTR3: The number of InDel in 3'UTR of non-coding RNA ncRNA_UTR5: The number of InDel in 5'UTR of non-coding RNA ncRNA_splicing: The number of InDel in 4bp splicing junction of non-coding RNA Table 23 - The number of different type InDel in coding regions Sample frameshift_dele tion frameshift_inse rtion nonframeshift_del etion nonframeshift_inse rtion stoplo ss stopga in unkno wn SEV1114 0551061042031581694SEV1114 0291311011961551792SEV1114 001110901991520591SEV1114 02512310020316801186SEV1114 052107901901561790SEV1114 026119842041692591SEV1114 0641351001831700690SEV1114 0461179419216801088SEV1114 0181351052011740990SEV1114 013123871921571689SEV1114 022134952001761689SEV111403612511020716601091SEV1114 035134991891720991SEV1114 0201161072061571992SEV1114 00612010320015711090SEV1114 019102861741750491SEV1114 033113841931611787SEV1114 03899901391130776SEV1114 047126891961580692SEV1114 049109932001571588SEV1114 056114891831601787SEV1114 065124941921690794SEV1114 067115881961660790SEV1114 066112891991611686SEV1114 017119972001671789SEV1114 054123851871681789 Note: Sample: Sample name frameshift_deletion: A deletion of one or more nucleotides that cause frameshift changes in protein coding sequence. the deletion length is not multiple of 3 frameshift_insertion: An insertion of one or more nucleotides that cause frameshift changes in protein coding sequence.the insertion length is not multiple of 3 nonframeshift_deletion: Non-frameshift deletion, does not change coding protein frame deletion, the deletion length is multiple of 3 nonframeshift_insertion: Non-frameshift insertion, does not change coding protein frame insertion: the insertion length is multiple of 3 stopgain: Frameshift insertion / deletion, nonframeshift insertion / deletion or block substitution that lead to the immediate creation of stop codon at the variant site stoploss: Frameshift insertion / deletion, nonframeshift insertion / deletion or block substitution that lead to the immediate elimination of stop codon at the variant site unknown: Unknown function (due to various errors in the gene structure definition in the database file) Table 24 - InDel and genotype distribution Sample all genotype.Het genotype.Hom novel novel_proportion SEV111405534046118172222974440.218645362SEV111402929678106511902764440.217130534SEV111400132990115952139573540.222916035SEV111402532444111062133871580.220626310SEV111405230307105861972164030.211271323SEV111402632008103992160968060.212634341SEV11140642879996041919562370.216570020SEV111404634989117122327776250.217925634SEV111401834274116352263974040.216023808SEV11140132726799511731659580.218505886SEV111402227181100921708957430.211287296SEV111403633267115232174473580.221180148SEV111403528653103611829262930.219627962SEV111402030521104542006765670.215163330SEV11140062773889981874056880.205061648SEV11140193040598812052464070.210721921SEV11140332847694791899756930.199922742SEV11140382914788412030660290.206848046SEV111404731642107102093265160.205928829SEV111404931666103562131066030.208520179SEV11140562710794511765657970.213856200SEV11140652877796531912460940.211766341SEV111406735046120152303174380.212235348SEV11140662748499151756958260.211977878SEV111401731493100552143871950.228463468SEV11140543011399192019464860.215388703 Note: Sample: Sample name all: The total number of InDel genotype.Het: The genotype of heterozygote genotype.Hom: The genotype of homozygote novel: InDel not in dbSNP novel_proportion: Is calculated as novel Indel / total number of Indel Software used for analysis

[0310] The softwares which were applied in the bioinformatic analysis are listed as below: Table 25 - The list of exome analysis softwareAnalytical content Software Comments Version Quality controlin-houseQuality control1.0AlignmentBWAMap the sequencing reads to the reference genome and the BAM file was obtained0.7.8-r455SAMtoolsSort bam1.0PicardMerge the bam file from the same sample and mark the duplicate reads1.111SNP / INDEL detectionGATKDetect and filter SNP, InDelv3.1Functional annotationANNOVARAnnotate variation site2013Aug23

[0311] Analysis was conducted using association software such as PLINK.Statistical analysis

[0312] The PLINK v1.0721 whole genome analysis tool set was used to determine associations between the CFS patients and the non-fatigued control group. A two column χ2 test was used to determine significance where p value of <0.05 was determined to be significant. Data analysis was performed by the Australian Genome Research Facility.Results

[0313] Exome sequencing identified SNP variants in the TRP channel and AChR genes TRPV1, TRPC6, TRPV4, TRPC1, TRPM8, TRPC4, TRPV2, TRPV5, TRPC5, TRPM6, TRPC7, TRPM5, TRPC3, PKD1, TRPV6, PKD2, TRPA1, TRPM7, TRPM2, TRPM4, TRPM3, TRPV3, and CHRNA7, CHRM3, CHRNA4, CHRNA3, CHRNB4, CHRNB2 and CHRNE. These, together with their annotated consequences, are described in Tables 26, 27 and 28 below Table 26: SNP variants of TRP channel or ACh receptors (TRP family, TRPV1, TRPC6, TRPV4, TRPC1, TRPM8, TRPC4, TRPV2, TRPV5, TRPC5, TRPM6, TRPC7, TRPM5, TRPC3, PKD1, TRPV6, PKD2, TRPA1, TRPM7, TRPM2, TRPM4, TRPM3, TRPV3, and CHRNA7, CHRM3, CHRNA4, CHRNA3, CHRNB4, CHRNB2 and CHRNE) annotated with their consequences.Chromosome Location Reference allele Alternative allele Consequences (intronic or exonic) 1532322929GAExonicFunc=synonymous_SNV1240070784TCExonicFunc=synonymous_SNV1240070944GAExonicFunc=missense_SNV2061981104CTExonicFunc=synonymous_SNV2061981134GAExonicFunc=synonymous_SNV2061981253CTExonicFunc=missense_SNV2061981362GAExonicFunc=synonymous_SNV2061981411GAExonicFunc=missense_SNV2061981536AGExonicFunc=synonymous_SNV2061981554CAExonicFunc=synonymous_SNV2061982085AGExonicFunc=synonymous_SNV2061982124AGExonicFunc=synonymous_SNV2061990939GAExonicFunc=synonymous_SNV2061992467CTExonicFunc=synonymous_SNV2061992509TCExonicFunc=synonymous_SNV1578880752GAExonicFunc=missense SNV1578882925GAExonicFunc=missense_SNV1578885574TAExonicFunc=missense_SNV1578894339GAExonicFunc=synonymous_SNV1578894357GTExonicFunc=synonymous_SNV1578909452TCExonicFunc=synonymous_SNV1578911181TCExonicFunc=synonymous_SNV1578911230CTExonicFunc=missense_SNV1578913131GAExonicFunc=synonymous_SNV1578917399AGExonicFunc=synonymous_SNV1578921762GAExonicFunc=synonymous_SNV1578922194GAExonicFunc=synonymous_SNV1578922229TCExonicFunc=missense_SNV1578922240CTExonicFunc=missense_SNV1578923505GAExonicFunc=missense_SNV174796274TCExonicFunc=missense_SNV174796286CTExonicFunc=missense_SNV174797305GAExonicFunc=missense_SNV174797910GAExonicFunc=missense_SNV174802317TCExonicFunc=synonymous_SNV174802329GAExonicFunc=synonymous_SNV174802829GAExonicFunc=synonymous_SNV174803711GAExonicFunc=stopgain174804902GAExonicFunc=synonymous_SNV174805777CGExonicFunc=missense_SNV174806052CAExonicFunc=missense_SNV173475490CTExonicFunc=synonymous_SNV173476990GAExonicFunc=synonymous_SNV173480433GCExonicFunc=missense_SNV173480447TCExonicFunc=missense_SNV173480910AGExonicFunc=synonymous_SNV173486702GAExonicFunc=missense_SNV173493200CGExonicFunc=missense_SNV173494361GAExonicFunc=synonymous_SNV173495374GAExonicFunc=missense_SNV173495465CTExonicFunc=synonymous_SNV11101323770CTExonicFunc=synonymous_SNV11101325788GAExonicFunc=synonymous_SNV11101342958GAExonicFunc=synonymous_SNV11101347093AGExonicFunc=synonymous_SNV11101359750GAExonicFunc=missense_SNV11101454192GAExonicFunc=missense_SNV12110222146CGExonicFunc=synonymous_SNV12110226379GAExonicFunc=synonymous_SNV12110230597CTExonicFunc=missense SNV12110238481GAExonicFunc=synonymous_SNV12110238487AGExonicFunc=synonymous_SNV12110240838TGExonicFunc=synonymous_SNV12110240848GAExonicFunc=synonymous_SNV12110252547GAExonicFunc=missense SNV3142443441GAExonicFunc=missense SNV3142503605GAExonicFunc=synonymous_SNV3142523349GAExonicFunc=synonymous_SNV3142524858GAExonicFunc=synonymous_SNV2234854540GCExonicFunc=missense SNV2234854547ATExonicFunc=synonymous_SNV2234854550GCExonicFunc=synonymous_SNV2234854552AGExonicFunc=missense_SNV2234858645CTExonicFunc=missense_SNV2234863788GAExonicFunc=missense_SNV2234875354GAExonicFunc=synonymous_SNV2234905078CTExonicFunc=synonymous_SNV2234915540CGExonicFunc=synonymous_SNV1338211105TCExonicFunc=missense_SNV1338211313TCExonicFunc=synonymous_SNV1338237564AGExonicFunc=synonymous_SNV1338357384GAExonicFunc=synonymous_SNV2033585437CTExonicFunc=synonymous_SNV2033586193CTExonicFunc=synonymous_SNV2033587198GCExonicFunc=missense_SNV2033587596GAExonicFunc=synonymous_SNV2033589107GAExonicFunc=synonymous_SNV2033657126GAExonicFunc=synonymous_SNV2033665969CTExonicFunc=synonymous_SNV1716320994CTExonicFunc=synonymous_SNV1716321032GCExonicFunc=missense SNV1716325968AGExonicFunc=synonymous_SNV1716326005ACExonicFunc=synonymous_SNV1716326990CGExonicFunc=missense_SNV1716336992CGExonicFunc=synonymous_SNV7142609749CTExonicFunc=missense_SNV7142622714GAExonicFunc=synonymous_SNV7142625249TCExonicFunc=synonymous_SNV7142625258GAExonicFunc=synonymous_SNV7142625882GAExonicFunc=synonymous_SNV7142625933GAExonicFunc=synonymous_SNV7142626549CTExonicFunc=missense_SNV7142626656CTExonicFunc=synonymous_SNV7142630534GAExonicFunc=missense_SNVX111078236GCExonicFunc=synonymous_SNV977376633AGExonicFunc=synonymous_SNV977376647TCExonicFunc=missense_SNV977376652ACExonicFunc=missense_SNV977377410CTExonicFunc=missense_SNV977407636CTExonicFunc=synonymous_SNV977415284ACExonicFunc=synonymous_SNV977416972CTExonicFunc=synonymous_SNV977436641GAExonicFunc=synonymous_SNV977448950AGExonicFunc=synonymous_SNV977502160GAExonicFunc=missense_SNV5135692575GAExonicFunc=synonymous_SNV5135692743CAExonicFunc=synonymous_SNV112423913ACExonicFunc=missense_SNV112424105AGExonicFunc=missense_SNV112424541CGExonicFunc=missense_SNV112424684ACExonicFunc=missense_SNV112427291ACExonicFunc=synonymous_SNV112432666CTExonicFunc=missense_SNV112432964TCExonicFunc=synonymous_SNV112434402CTExonicFunc=synonymous_SNV112435946AGExonicFunc=synonymous_SNV112435956CTExonicFunc=missense_SNV112436464CTExonicFunc=missense_SNV112438963CAExonicFunc=missense_SNV112439542AGExonicFunc=missense_SNV112439767TCExonicFunc=missense_SNV112442364GAExonicFunc=synonymous_SNV112444188CTExonicFunc=missense_SNV4122800987TCExonicFunc=synonymous_SNV4122824052CTExonicFunc=synonymous_SNV4122854116GCExonicFunc=synonymous_SNV4122872719GAExonicFunc=synonymous_SNV747835027AGExonicFunc=missense_SNV747840310CGExonicFunc=missense_SNV747840387CTExonicFunc=missense_SNV747851578GAExonicFunc=missense_SNV747851623CTExonicFunc=missense_SNV747852837CTExonicFunc=missense_SNV747854956CTExonicFunc=synonymous_SNV747869038TCExonicFunc=synonymous_SNV747872845AGExonicFunc=synonymous_SNV747874630GAExonicFunc=missense_SNV747876567GAExonicFunc=synonymous_SNV747879049GAExonicFunc=missense_SNV747892745AGExonicFunc=missense_SNV747913560GTExonicFunc=missense_SNV747913579TCExonicFunc=missense_SNV747913580GAExonicFunc=synonymous_SNV747917087CTExonicFunc=synonymous_SNV747917126TCExonicFunc=synonymous_SNV747920345GAExonicFunc=synonymous_SNV747921682ATExonicFunc=synonymous_SNV747925331CGExonicFunc=missense_SNV747927744CTExonicFunc=missense_SNV747930148CTExonicFunc=synonymous_SNV747930280CTExonicFunc=synonymous_SNV747968927CAExonicFunc=missense_SNV747970707GAExonicFunc=missense_SNV747971575AGExonicFunc=synonymous_SNV747971626GAExonicFunc=synonymous_SNV162138269TCExonicFunc=synonymous_SNV162138584GCExonicFunc=synonymous_SNV162139814GAExonicFunc=missense_SNV162139935GAExonicFunc=synonymous_SNV162140010AGExonicFunc=synonymous_SNV162140321GAExonicFunc=synonymous_SNV162140454TCExonicFunc=synonymous_SNV162140554GAExonicFunc=missense_SNV162140680TCExonicFunc=missense_SNV162140912GCExonicFunc=synonymous_SNV162141454GAExonicFunc=synonymous_SNV162144176GAExonicFunc=missense_SNV162144182GAExonicFunc=missense_SNV162147421CTExonicFunc=missense_SNV162152387AGExonicFunc=missense_SNV162152388CGExonicFunc=synonymous_SNV162156021AGExonicFunc=synonymous_SNV162158871CAExonicFunc=synonymous_SNV162159405CTExonicFunc=synonymous_SNV162159522CTExonicFunc=synonymous_SNV162159750GAExonicFunc=synonymous_SNV162159996GAExonicFunc=synonymous_SNV162160494CTExonicFunc=synonymous_SNV162160503TGExonicFunc=synonymous_SNV162160973AGExonicFunc=missense_SNV162161113CTExonicFunc=missense_SNV162161150GAExonicFunc=missense_SNV162161489CAExonicFunc=missense_SNV162161793GAExonicFunc=synonymous_SNV162161796GAExonicFunc=synonymous_SNV162162955AGExonicFunc=missense_SNV162164808CTExonicFunc=missense_SNV162167970GAExonicFunc=synonymous_SNV1671967886GAExonicFunc=unknown1671967927CTExonicFunc=unknown1671983772GCExonicFunc=unknown1671986946AGExonicFunc=unknown1671988106CTExonicFunc=unknown1672001110GAExonicFunc=unknown1672001136GAExonicFunc=unknown1672003952GCExonicFunc=unknown1672007232GAExonicFunc=unknown1672007399CTExonicFunc=unknown1672011162GCExonicFunc=unknown1672011181GTExonicFunc=unknown1672011193ACExonicFunc=unknown1672011261AGExonicFunc=unknown1672012239CGExonicFunc=unknown1672013797GCExonicFunc=unknown1672020134TCExonicFunc=unknown1672020294GAExonicFunc=unknown1672020323AGExonicFunc=unknown1672027191TAExonicFunc=unknown1672032221GAExonicFunc=unknown1672032231TAExonicFunc=unknown1672033801GTExonicFunc=unknown1681129822GAExonicFunc=missense_SNV1681134860CGExonicFunc=unknown1681142257TCExonicFunc=unknown1681145807CGExonicFunc=unknown1681145976CTExonicFunc=unknown1681151122ACExonicFunc=unknown1681151123CGExonicFunc=unknown1681157324GAExonicFunc=unknown1681157353GAExonicFunc=unknown1681157385GTExonicFunc=unknown1681161552CTExonicFunc=unknown1681161569TGExonicFunc=unknown1681161571TCExonicFunc=unknown1681161578GAExonicFunc=unknown1681161608TCExonicFunc=unknown1681161635CAExonicFunc=unknown1681173136TCExonicFunc=unknown1681173193CTExonicFunc=unknown1681174978AGExonicFunc=unknown1681174992GTExonicFunc=unknown1681174999AGExonicFunc=unknown1681175103GAExonicFunc=unknown1681180988CGExonicFunc=unknown1681180995TCExonicFunc=unknown1681181066GAExonicFunc=unknown1681181097GTExonicFunc=unknown1681181783TCExonicFunc=unknown1681181821TCExonicFunc=unknown1681181869TCExonicFunc=unknown1681183325TAExonicFunc=unknown1681183492TGExonicFunc=unknown1681185412CTExonicFunc=unknown1681185416AGExonicFunc=unknown1681185419GCExonicFunc=unknown1681187685GAExonicFunc=unknown1681190598TCExonicFunc=unknown1681190601TC,AExonicFunc=unknown1681190613AGExonicFunc=unknown1681193321CTExonicFunc=unknown1681193358CGExonicFunc=unknown1681194382TC,AExonicFunc=unknown1681197218GAExonicFunc=unknown1681198306CAExonicFunc=unknown1681199468GCExonicFunc=unknown1681199520TCExonicFunc=unknown1681199538TCExonicFunc=unknown1681199544GAExonicFunc=unknown1681199554CTExonicFunc=unknown1681199555AGExonicFunc=unknown1681201620CAExonicFunc=unknown1681201625GAExonicFunc=unknown1681204396GAExonicFunc=synonymous_SNV1681204635GCExonicFunc=synonymous_SNV1681208515GAExonicFunc=missense_SNV1681209234CTExonicFunc=synonymous_SNV1681211496CAExonicFunc=missense_SNV1681211548GAExonicFunc=synonymous_SNV1681211587TCExonicFunc=synonymous_SNV1681213378AGExonicFunc=missense_SNV1681213381ACExonicFunc=missense_SNV1681219187CTExonicFunc=missense_SNV1681232275GAExonicFunc=missense_SNV1681232294TCExonicFunc=missense_SNV1681232336TCExonicFunc=missense_SNV1681232564TGExonicFunc=missense_SNV1681241098CTExonicFunc=synonymous_SNV1681241100GCExonicFunc=missense_SNV1681242102GAExonicFunc=missense_SNV1681242107TCExonicFunc=missense_SNV1681242151TCExonicFunc=synonymous_SNV1681242194TCExonicFunc=missense_SNV1681242198GAExonicFunc=stopgain1681248716CTExonicFunc=missense_SNV1681248745AGExonicFunc=missense_SNV1681249927CTExonicFunc=missense_SNV1681249954TAExonicFunc=missense_SNV1681253745CGExonicFunc=missense_SNV1681253759AGExonicFunc=missense_SNV1681253917AGExonicFunc=missense_SNV7142565385GAExonicFunc=synonymous_SNV7142565776GAExonicFunc=synonymous_SNV7142568070GAExonicFunc=missense_SNV7142569556AGExonicFunc=synonymous_SNV7142569596AGExonicFunc=missense_SNV7142569701CTExonicFunc=missense_SNV7142570142TCExonicFunc=synonymous_SNV7142570217CTExonicFunc=synonymous_SNV7142572304GAExonicFunc=synonymous_SNV7142572908TCExonicFunc=missense_SNV7142573263CTExonicFunc=synonymous_SNV7142573614GAExonicFunc=missense_SNV7142573644ATExonicFunc=missense_SNV7142574913AGExonicFunc=missense_SNV488928968GCExonicFunc=missense_SNV488929305GAExonicFunc=synonymous_SNV488929453GAExonicFunc=missense_SNV488964586CTExonicFunc=synonymous_SNV5137244517GAExonicFunc=missense_SNV5137259179TCExonicFunc=missense_SNV5137278682TCExonicFunc=missense_SNV10102046380TGExonicFunc=missense_SNV10102048208GTExonicFunc=missense_SNV10102050242CAExonicFunc=missense_SNV10102056745CTExonicFunc=missense_SNV10102089663CTExonicFunc=missense_SNV872936145TCExonicFunc=missense_SNV872948588CTExonicFunc=synonymous_SNV872951118TCExonicFunc=synonymous_SNV872964965GAExonicFunc=synonymous_SNV872966002GAExonicFunc=synonymous_SNV872975801TGExonicFunc=missense_SNV872977703CTExonicFunc=missense_SNV872981318GAExonicFunc=synonymous_SNV872981327AGExonicFunc=synonymous_SNV872984041CGExonicFunc=missense_SNV872987638GAExonicFunc=missense_SNV1550867082GAExonicFunc=synonymous_SNV1550867142CTExonicFunc=synonymous_SNV1550878630GAExonicFunc=missense_SNV1550888568AGExonicFunc=synonymous_SNV1550897114AGExonicFunc=synonymous_SNV2145811343TGExonicFunc=missense_SNV2145820196CTExonicFunc=missense_SNV2145825799CTExonicFunc=missense_SNV2145833864CTExonicFunc=missense_SNV2145844751AGExonicFunc=missense_SNV2145855100GTExonicFunc=missense_SNV1949657613GTExonicFunc=missense_SNV1949658084GAExonicFunc=synonymous_SNV1949658209ACExonicFunc=missense_SNV1949658367CTExonicFunc=missense_SNV1949658390TCExonicFunc=synonymous_SNV1949671214AGExonicFunc=missense_SNV1949671281GAExonicFunc=synonymous_SNV1949675017GTExonicFunc=synonymous_SNV1949699866CTExonicFunc=synonymous_SNV973150873TGExonicFunc=missense_SNV973150918CTExonicFunc=missense_SNV973150984CTExonicFunc=missense_SNV973151715CTExonicFunc=synonymous_SNV973151970CTExonicFunc=synonymous_SNV973240431TGExonicFunc=synonymous_SNV973255554GAExonicFunc=synonymous_SNV973461337TAExonicFunc=synonymous_SNV173417253AGExonicFunc=synonymous_SNV173422032GAExonicFunc=synonymous_SNV173422073CTExonicFunc=missense_SNV173422077GAExonicFunc=synonymous_SNV173436080CTExonicFunc=synonymous_SNV173436209TCExonicFunc=synonymous_SNV173445901TGExonicFunc=synonymous_SNV173446885TCExonicFunc=missense_SNV173447914CTExonicFunc=synonymous_SNV173458072TCExonicFunc=missense_SNV Table 27: Frequency distribution and significance of Transient Receptor Potential (TRP) SNPs in CFS / ME patients (n=14) and non-fatigued controls (n=11 from isolated B cells in rank order of significance. Ch rPositionA 1F_AF_UA 2CHISQPORExonicFuncGene4122,872,719G0.10.45A6.1440.0131 80.135 8synonymous_SNVGene=NM_0011306981681,253,759A0.06250.3333G3.80.0512 40.133 3missense_SNVGene=NM_001076780,NM_0528921681,253,917A0.06250.3333G3.80.0512 40.133 3missense_SNVGene=NM_001076780,NM_052892973,151,715C0.23080.0454 5T3.2850.06996.3synonymous_SNVGene=NM_001007471,NM_020952,NM_024971, NM_206944,NM_206945,NM_206946,NM_206947112,439,542A0.38460.15G3.0690.0797 93.542missense_SNVGene=NM_014555112,435,946A0.29170.1111G1.9920.15823.294synonymous_SNVGene=NM_014555173,493,200C0.30770.1364G1.980.15942.815missense_SNVGene=NM_018727,NM_080704,NM_080705,NM_08070612110,226,379G0.50A1.7140.1904NAsynonymous_SNVGene=NM_001177428,NM_001177431,NM_001177433, NM_021625,NM_1472041716,325,968A0.250.5G1.6990.19240.333 3synonymous_SNVGene=NM_0161131716,326,005A0.250.5C1.6990.19240.333 3synonymous_SNVGene=NM_016113747,913,579T0.23080.0909 1C1.6780.19513missense_SNVGene=NM_1382951681,249,954T0.1250.3125A1.6460.19950.314 3missense_SNVGene=NM_001076780,NM_052892173,446,885T0.50.2857C1.4290.2322.5missense_SNVGene=NM_001258205,NM_145068872,975,801T0.36360.2G1.3750.2412.286missense_SNVGene=NM_007332872,981,327A0.36360.2G1.3750.2412.286synonymous_SNVGene=NM_007332973,150,873T0.50.25G1.250.26363missense_SNVGene=NM_001007471,NM_020952,NM_024971,NM_206944, NM_206945,NM_206946,NM_206947973,150,918C0.50.25T1.250.26363missense_SNVGene=NM _001007471,NM_020952,NM_024971,NM_206944, NM_206945,NM_206946,NM_206947872,966,002G0.38890.2143A1.1170.29052.333synonymous_SNVGene=NM_0073321681,241,098C0.0833 30.1818T0.98160.32180.409 1synonymous_SNVGene=NM_001076780,NM_0528921681,242,194T0.083330.1818C0.98160.32180.4091missense_SNVGene=NM_001076780,NM_0528921716,336,992C0.31250.5G0.91410.3390.454 5synonymous_SNVGene=NM_016113173,480,447T0.350.5C0.7650.38180.538 5missense SNVGene=NM_018727,NM_080704,NM_080705,NM_08070611101,347,093A0.50.3G0.74810.38712.333synonymous_SNVGene=NM_004621173,422,032G0.250.3889A0.74660.38760.523 8synonymous_SNVGene=NM_001258205,NM_145068112,432,964T0.27780.4C0.62880.42780.576 9synonymous_SNVGene=NM_0145551550,878,630G0.250.5A0.6250.42920.333 3missense SNVGene=NM_017672162,160,973A0.250.5G0.53330.46520.333 3missense SNVGene=NM_000296,NM_001009944173,436,080C0.43750.3125T0.53330.46521.711synonymous_SNVGene=NM_001258205,NM_145068173,494,361G0.250.5A0.53330.46520.333 3synonymous_SNVGene=NM_018727,NM_080704,NM_080705,NM_080706747,872,845A0.20830.3G0.48890.48440.614synonymous_SNVGene=NM_138295112,427,291A0.16670.25C0.46560.4950.6synonymous_SNVGene=NM_0145551681,211,496C0.16670.3333A0.44440.5050.4missense_SNVGene=NM_001076780,NM_001278423,NM_001278425,NM_052 8921681,211,548G0.16670.3333A0.44440.5050.4synonymous_SNVGene=NM_001076780,NM_001278423,NM_001278425,NM_052 8923142,443,441G0.250.5A0.3750.54030.333 3missense_SNVGene=NM_001251845,NM_003304747,913,580G0.20.3333A0.35560.5510.5synonymous_SNVGene=NM_138295747,920,345G0.20.3333A0.35560.5510.5synonymous_SNVGene=NM_138295872,987,638G0.33330.5A0.34290.55820.5missense_SNVGene=NM_0073321550,888,568A0.33330.5G0.34290.55820.5synonymous_SNVGene=NM_017672173,486,702G0.3750.5A0.34290.55820.6missense_SNVGene=NM_018727,NM_080704,NM_080705,NM_0807061681,232,275G0.0833 30.1364A0.33320.56380.575 8missense_SNVGene=NM_001076780,NM_0528921681,232,564T0.0833 30.1364G0.33320.56380.575 8missense_SNVGene=NM_001076780,NM_05289212110,240,838T0.30.3889G0.33260.56410.673 5synonymous_SNVGene=NM_001177 428,NM_001177431,NM_001177433, NM_021625,NM_147204173,422,077G0.3750.5A0.32080.57110.6synonymous_SNVGene=NM_001258205,NM_1450685137,244,517G0.250.1818A0.31360.57551.5missense_SNVGene=NM_001258448,NM_0143863142,523,349G0.3750.25A0.29090.58961.8synonymous_SNVGene=NM_001251845,NM_0033043142,524,858G0.3750.25A0.29090.58961.8synonymous_SNVGene=NM_001251845,NM_0033041681,208,515G0.40.3A0.28710.59211.556missense_SNVGene=NM_001076780,NM_001278423,NM_001278425,NM_052 892977,415,284A0.38890.5C0.28010.59660.636 4synonymous_SNVGene=NM_001177310,NM_001177311,NM_0176622234,854,550G0.3750.5C0.2540.61430.6synonymous_SNVGene=NM_0240801681,242,102G0.31820.25A0.23860.62521.4missense_SNVGene=NM_001076780,NM_052892977,502,160G0.38890.3A0.22120.63811.485missense_SNVGene=NM_0011773112234,905,078C0.50.4T0.220.6391.5synonymous_SNVGene=NM_0240803142,503,605G0.40.3A0.21980.63921.556synonymous_SNVGene=NM_001251845,NM_003304747,876,567G0.50.3333A0.17780.67332synonymous_SNVGene=NM_138295973,150,984C0.22220.1667T0.17730.67371.429missense_SNVGene=NM_001007471,NM_020952,NM_024971,NM_206944, NM_206945,NM_206946,NM_2069472234,915,540C0.3750.5G0.17140.67880.6synonymous_SNVGene=NM_024080112,438,963C0.3750.5A0.17140.67880.6missense_SNVGene=NM_014555488,928,968G0.250.3333C0.15870.69030.666 7missense_SNVGene=NM_000297747,925,331C0.350.2857G0.15550.69331.346missense_SNVGene=NM_138295872,936,145T0.50.4C0.15240.69631.5missense_SNVGene=NM_007332973,151,970C0.22220.2778T0.14810.70030.742 9synonymous_SNVGene=NM_001007471,NM_020952,NM_024971,NM_206944, NM_206945,NM_206946,NM_206947977,436,641G0.40.3333A0.14220.70611.333synonymous_SNVGene=NM_001177310,NM_001177311,NM_017662112,439,767T0.42860.5C0.13270.71570.75missense_SNVGene=NM_0145554122,854,116G0.50.4C0.11670.73271.5synonymous_SNVGene=NM_001130698,NM_0033051681,242,198G0.41670.5A0.11250.73730.714 3stopgainGene=NM_001076780,NM_052892973,461,337T0.33330.2857A0.09280.76071.25synonymous_SNVGene=NM_001007470,NM_001007471,NM_020952,NM _024971, NM_206944,NM_206945,NM_206946,NM_206947,NM_206948173,445,901T0.26920.3125G0.090870.76310.810 5synonymous_SNVGene=NM_001258205,NM_1450681681,241,100G0.31820.2778C0.076960.78151.213missense_SNVGene=NM_001076780,NM_0528921681,242,151T0.31820.2778C0.076960.78151.213synonymous_SNVGene=NM_001076780,NM_052892747,971,575A0.27270.3125G0.071240.78950.825synonymous_SNVGene=NM_1382951681,253,745C0.28570.3333G0.068780.79310.8missense_SNVGene=NM_001076780,NM_052892162,140,010A0.3750.4286G0.060440.80580.8synonymous_SNVGene=NM_000296,NM_001009944162,160,503T0.3750.4286G0.060440.80580.8synonymous_SNVGene=NM_000296,NM_0010099441550,867,082G0.31820.3571A0.058440.8090.84synonymous_SNVGene=NM_0176724122,824,052C0.40.4375T0.051430.82060.857 1synonymous_SNVGene=NM_001130698,NM_0033051681,213,378A0.0833 30.1G0.036670.84810.818 2missense_SNVGene=NM_001076780,NM_001278423,NM_001278425,NM_052 892162,159,996G0.3750.4167A0.034720.85220.84synonymous_SNVGene=NM_000296,NM_0010099441681,248,716C0.33330.3T0.027940.86731.167missense_SNVGene=NM)001076780,NM)052892112,435,956C0.44440.4167T0.022620.88041.12missense_SNVGene=NM_014555173,447,914C0.23080.25T0.020190.8870.9synonymous_SNVGene=NM_001258205,NM_145068162,140,454T0.40.4286C0.019590.88870.888 9synonymous_SNVGene=NM_000296,NM_001009944162,140,680T0.40.4286C0.019590.88870.888 9missense_SNVGene=NM_000296,NM_001009944747,921,682A0.3750.4T0.016250.89860.9synonymous_SNVGene=NM_1382951681,248,745A0.35710.3333G0.016180.89881.111missense_SNVGene=NM_001076780,NM_0528927142,626,549C0.35710.375T0.00701 50.93320.925 9missense_SNVGene=NM_019841747,968,927C0.31820.3125A0.00138 40.97031.027missense_SNVGene=NM_1382952234,854,540G0.50.5C011missense_SNVGene=NM_0240802234,854,552A0.50.5G011missense_SNVGene=NM_0240802234,863,788G0.50.5A011missense_SNVGene=NM_024080488,929,305G0.50.5A011synonymous_SNVGene=NM_0002975135,692,575G0.50.5A011synonymous_SNVGene=NM_001167576,NM_001167577,NM_020389747,840,387C0.50.5T011missense_SNVGene=NM_138295747,851,623C0.50.5T011missense_SNVGene=NM_138295747,852,837C0.50.5T011missense_SNVGene=NM_138295747,854,956C0.50.5T011synonymous_SNVGene=NM_138295747,869,038T0.50.5C011synonymous_SNVGene=NM_138295747,874,630G0.50.5A011missense_SNVGene=NM_138295747,879,049G0.50.5A011missense_SNVGene=NM_138295747,913,560G0.33330.3333T011missense_SNVGene=NM_138295747,917,087C0.50.5T011synonymous_SNVGene=NM_138295747,927,744C0.50.5T011missense_SNVGene=NM_138295747,930,148C0.50.5T011synonymous_SNVGene=NM_138295747,971,626G0.50.5A011synonymous_SNVGene=NM_1382957142,569,596A0.50.5G011missense_SNVGene=NM_0186467142,570,142T0.50.5C011synonymous_SNVGene=NM_0186467142,572,304G0.50.5A011synonymous_SNVGene=NM_0186467142,572,908T0.50.5C011missense_SNVGene=NM_0186467142,573,263C0.50.5T011synonymous_SNVGene=NM_0186467142,574,913A0.50.5G011missense_SNVGene=NM_0186467142,622,714G0.50.5A011synonymous_SNVGene=NM_0198417142,625,249T0.50.5C011synonymous_SNVGene=NM_0198417142,625,258G0.50.5A011synonymous_SNVGene=NM_0198417142,625,882G0.50.5A011synonymous_SNVGene=NM_0198417142,625,933G0.50.5A011synonymous_SNVGene=NM_0198417142,626,656C0.50.5T011synonymous_SNVGene=NM_019841872,977,703C0.50.5T011missense_SNVGene=NM_007332872,981,318G0.50.5A011synonymous_SNVGene=NM_007332872,984,041C0.50.5G011missense_SNVGene=NM_007332973,240,431T0.50.5G011synonymous_SNVGene=NM_024971,NM_206945977,376,633A0.50.5G011synonymous_SNVGene=NM_001177310,NM_001177311,NM_017662977,376,647T0.50.5C011missense_SNVGene=NM_001177310,NM_001177311,NM_017662977,377,410C0.50.5T011missense_SNVGene=NM_001177310,NM_001177311,NM_017662977,407,636C0.50.5T011synonymous_SNVGene=NM_001177310,NM_001177311,NM_017662977,416,972C0.50.5T011synonymous_SNVGene=NM_001177310,NM_001177311,NM_01766210102,048,208G0.50.5T011missense_SNVGene=NM_001253837,NM_01611210102,050,242C0.50.5A011missense_SNVGene=NM_001253837,NM_01611210102,056,745C0.50.5T011missense_SNVGene=NM_001253837,NM_01611210102,089,663C0.50.5T011missense_SNVGene=NM_001253837,NM_016112112,432,666C0.50.5T011missense_SNVGene=NM_01455511101,323,770C0.50.5T011synonymous_SNVGene=NM_00462111101,359,750G0.50.5A011missense_SNVGene=NM_00462112110,238,487A0.50.5G011synonymous_SNVGene=NM_001177431,NM_021625,NM_1472041338,211,105T0.50.5C011missense_SNVGene=NM _001135955,NM 001135956,NM _001135957, NM 001135958,NM 003306,NM 0161791338,357,384G0.50.5A011synonymous_SNVGene=NM _001135955,NM 001135956,NM _001135957, NM 001135958,NM 003306,NM 016179162,140,321G0.50.5A011synonymous_SNVGene=NM_000296,NM_001009944162,140,554G0.50.5A011missense_SNVGene=NM_000296,NM_001009944162,144,176G0.50.5A011missense_SNVGene=NM_000296,NM_001009944162,144,182G0.50.5A011missense_SNVGene=NM_000296,NM_001009944162,159,405C0.50.5T011synonymous_SNVGene=NM_000296,NM_0010099441681,219,187C0.33330.3333T011missense_SNVGene=NM_001076780,NM_0528921681,232,336T0.50.5C011missense_SNVGene=NM_001076780,NM_0528921681,249,927C0.50.5T011missense_SNVGene=NM_001076780,NM_052892173,475,490C0.50.5T011synonymous_SNVGene=NM_018727,NM_080704,NM_080705,NM_080706173,476,990G0.50.5A011synonymous_SNVGene=NM_018727,NM_080704,NM_080705,NM_080706173,480,910A0.50.5G011synonymous_SNVGene=NM_018727,NM 080704,NM_080705,NM_080706173,495,374G0.50.5A011missense_SNVGene=NM_018727,NM 080704,NM_080705,NM_0807061716,321,032G0.50.5C011missense_SNVGene=NM_0161131949,671,281G0.50.5A011synonymous_SNVGene=NM_001195227,NM_0176361949,675,017G0.50.5T011synonymous_SNVGene=NM_001195227,NM_0176361949,699,866C0.50.5T011synonymous_SNVGene=NM_0176362033,657,126G0.250.25A011synonymous_SNVGene=NM_015638,NM_1993682033,665,969C0.50.5T011synonymous_SNVGene=NM_015638,NM_1993682145,811,343T0.50.5G011missense_SNVGene=NM_0033072145,820,196C0.50.5T011missense_SNVGene=NM_0033072234,854,547A0.5NATNANANAsynonymous_SNVGene=NM_0240802234,858,645C0.5NATNANANAmissense_SNVGene=NM_0240802234,875,354GNA0.5ANANANAsynonymous_SNVGene=NM_024080488,929,4530NA0ANANANAmissense_SNVGene=NM_000297488,964,586CNA0.5TNANANAsynonymous_SNVGene=NM_0002974122,800,987T0.5NACNANANAsynonymous_SNVGene=NM_001130698,NM_0033055135,692,743C0.5NAANANANAsynonymous_SNVGene=NM_001167576,NM_001167577,NM_0203895137,259,179000CNANANAmissense_SNVGene=NM_001258448,NM_001258449,NM_014386747,840,310C0.5NAGNANANAmissense_SNVGene=NM_138295747,851,578G0.5NAANANANAmissense_SNVGene=NM_138295747,892,745A0.5NAGNANANAmissense_SNVGene=NM_138295747,917,126TNA0.5CNANANAsynonymous_SNVGene=NM_138295747,930,280C0.5NATNANANAsynonymous_SNVGene=NM_138295747,970,707G0.5NAANANANAmissense_SNVGene=NM_1382957142,569,556A0.5NAGNANANAsynonymous_SNVGene=NM_0186467142,569,701CNA0.5TNANANAmissense_SNVGene=NM_0186467142,570,217C0.5NATNANANAsynonymous_SNVGene=NM_0186467142,573,614GNA0.5ANANANAmissense_SNVGene=NM_0186467142,573,644ANA0.5TNANANAmissense_SNVGene=NM_0186467142,609,749C0.5NATNANANAmissense_SNVGene=NM_0198417142,630,534G0.5NAANANANAmissense_SNVGene=NM_019841872,948,588C0.5NATNANANAsynonymous_SNVGene=NM_007332872,951,118TNA0.5CNANANAsynonymous_SNVGene=NM_007332872,964,965G0.5NAANANANAsynonymous_SNVGene=NM_007332973,255,554G0.5NAANANANAsynonymous_SNVGene=NM_001007471,NM_020952,NM_024971,NM_206944, NM_206945,NM 206946,NM_206947977,376,652ANA0.5CNANANAmissense_SNVGene=NM_001177310,NM_001177311,NM_017662977,448,950A0.5NAGNANANAsynonymous_SNVGene=NM_001177310,NM_001177311,NM_017662112,434,402C0.5NATNANANAsynonymous_SNVGene=NM_014555112,436,464C0.5NATNANANAmissense_SNVGene=NM_014555112,442,364G0.5NAANANANAsynonymous_SNVGene=NM_014555112,444,188C0.5NATNANANAmissense_SNVGene=NM_01455511101,325,788GNA0.5ANANANAsynonymous_SNVGene=NM_00462111101,342,958GNA0.5ANANANAsynonymous_SNVGene=NM_00462111101,454,192GNA0.5ANANANAmissense_SNVGene=NM_00462112110,222,146C0.5NAGNANANAsynonymous_SNVGene=NM_001177428,NM_001177431,NM_001177433, NM 021625,NM 14720412110,230,597C0.5NATNANANAmissense_SNVGene=NM_001177428,NM_001177431,NM_001177433, NM_021625,NM_14720412110,238,481GNA0.5ANANANAsynonymous_SNVGene=NM_001177431,NM_021625,NM_14720412110,240,848GNA0.5ANANANAsynonymous_SNVGene=NM_001177428,NM_001177431,NM_001177433, NM_021625,NM_14720412110,252,547GNA0.5ANANANAmissense_SNVGene=NM_001177428,NM_001177431,NM_001177433, NM_021625,NM_1472041338,211,313T0.5NACNANANAsynonymous_SNVGene=NM_001135955,NM_001135956,NM_001135957, NM_001135958,NM_003306,NM_0161791338,237,564ANA0.5GNANANAsynonymous_SNVGene=NM_001135955,NM_001135956,NM_001135957, NM_001135958,NM_003306,NM_0161791550,867,142C0.5NATNANANAsynonymous_SNVGene=NM_0176721550,897,114A0.5NAGNANANAsynonymous_SNVGene=NM_017672162,139,814GNA0.5ANANANAmissense_SNVGene=NM_000296,NM_001009944162,139,935G0.5NAANANANAsynonymous_SNVGene=NM_000296,NM_001009944162,140,912G0.5NACNANANAsynonymous_SNVGene=NM_000296,NM_001009944162,141,454GNA0.5ANANANAsynonymous_SNVGene=NM_000296,NM_001009944162,152,3870NA0GNANANAmissense_SNVGene=NM_000296,NM_001009944162,152,3880NA0GNANANAsynonymous_SNVGene=NM_000296,NM_001009944162,156,021A0.5NAGNANANAsynonymous_SNVGene=NM_000296,NM_001009944162,158,871CNA0.5ANANANAsynonymous_SNVGene=NM_000296,NM_001009944162,159,522C0.5NATNANANAsynonymous_SNVGene=NM_000296,NM_001009944162,159,750G0.5NAANANANAsynonymous_SNVGene=NM_000296,NM_001009944162,160,494C0.5NATNANANAsynonymous_SNVGene=NM_000296,NM_001009944162,161,113C0.5NATNANANAmissense_SNVGene=NM_000296,NM_001009944162,161,150GNA0.5ANANANAmissense_SNVGene=NM_000296,NM_001009944162,161,489CNA0.5ANANANAmissense_SNVGene=NM_000296,NM_001009944162,161,793GNA0.5ANANANAsynonymous_SNVGene=NM_000296,NM_001009944162,161,796GNA0.5ANANANAsynonymous_SNVGene=NM_000296,NM_001009944162,162,95500NAGNANANAmissense_SNVGene=NM_000296,NM_001009944162,164,808C0.5NATNANANAmissense_SNVGene=NM_000296,NM_001009944162,167,970G0.5NAANANANAsynonymous_SNVGene=NM_000296,NM_0010099441681,204,396G0.5NAANANANAsynonymous_SNVGene=NM_001076780,NM_0012784231681,204,635G0.5NACNANANAsynonymous_SNVGene=NM_001076780,NM_001278423,NM_001278425,NM_052 8921681,209,234CNA0.5TNANANAsynonymous_SNVGene=NM_001076780,NM_001278423,NM_001278425,NM_052 8921681,211,587T0.5NACNANANAsynonymous_SNVGene=NM_001076780,NM_001278423,NM_001278425,NM_052 8921681,213,381ANA0.5CNANANAmissense_SNVGene=NM_001076780,NM_001278423,NM_001278425,NM_052 8921681,232,294T0.5NACNANANAmissense_SNVGene=NM_001076780,NM_0528921681,242,107T0.5NACNANANAmissense_SNVGene=NM_001076780,NM_052892173,417,253ANA0.5GNANANAsynonymous_SNVGene=NM_001258205,NM_145068173,422,073CNA0.5TNANANAmissense_SNVGene=NM_001258205,NM_145068173,436,209TNA0.5CNANANAsynonymous_SNVGene=NM_001258205,NM_145068173,458,072000CNANANAmissense_SNVGene=NM_001258205,NM 145068173,480,433GNA0.5CNANANAmissense_SNVGene=NM_018727,NM_080704,NM_080705,NM_080706173,495,465CNA0.5TNANANAsynonymous_SNVGene=NM_018727,NM_080704,NM_080705,NM_0807061716,320,994CNA0.5TNANANAsynonymous_SNVGene=NM_0161131716,326,990C0.5NAGNANANAmissense_SNVGene=NM_0161131949,671,214ANA0.5GNANANAmissense_SNVGene=NM_001195227,NM_0176362145,825,799CNA0.5TNANANAmissense_SNVGene=NM_0033072145,833,864CNA0.5TNANANAmissense_SNVGene=NM_0033072145,844,751000GNANANAmissense_SNVGene=NM_0033072145,855,100GNA0.5TNANANAmissense_SNVGene=NM_003307 Table 28: Frequency distribution and significance of AChR SNPs in CFS / ME (n=14) patients and non-fatigued controls (n=11) from isolated B cells in rank order of significance. ChrPositionA1F_AF_UA2CHISQPORExonicFuncGene2061981554C0.041670.1818A2.3270.12710.1957synonymous_SNVGene=NM_000744,NM_0012565732061982124A0.041670.1818G2.3270.12710.1957synonymous_SNVGene=NM_000744,NM_0012565732061981134G0.27270.4A0.76360.38220.5625synonymous_SNVGene=NM_000744,NM_0012565731578909452T0.20830.3182C0.71830.39670.5639synonymous_SNVGene=NM_000743,NM_0011666942061981104C0.29170.4T0.56980.45030.6176synonymous_SNVGene=NM_000744,NM_0012565731578894339G0.38890.3A0.22120.63811.485synonymous_SNVGene=NM_000743,NM_0011666941578911181T0.40.3333C0.1810.67061.333synonymous_SNVGene=NM_000743,NM_0011666942061982085A0.076920.09091G0.030510.86130.8333synonymous_SNVGene=NM_000744,NM_0012565732061981536A0.038460.04545G0.014590.90380.84synonymous_SNVGene=NM_000744,NM_0012565731578917399A0.20830.2222G0.011780.91360.9211synonymous_SNVGene=NM_0012565671532322929G0.50.5A011synonymous_SNVGene=NM_0011904551578911230C0.50.5T011missense_SNVGene=NM_000743,NM_0011666941578923505G0.50.5A011missense_SNVGene=NM_000750,NM_001256567174802329G0.50.5A011synonymous_SNVGene=NM_000080174806052C0.50.5A011missense_SNVGene=NM_0000802061990939G0.50.5A011synonymous_SNVGene=NM_0007441240070784T0.5NACNANANAsynonymous_SNVGene=NM_0007401240070944G0.5NAANANANAmissense_SNVGene=NM_0007401578894357G0.5NATNANANAsynonymous_SNVGene=NM_000743,NM_0011666941578913131GNA0.5ANANANAsynonymous_SNVGene=NM_000743,NM_0011666941578921762GNA0.5ANANANAsynonymous_SNVGene=NM_000750157892219400NAANANANAsynonymous_SNVGene=NM_0007501578922229TNA0.5CNANANAmissense_SNVGene=NM_0007501578922240C0.5NATNANANAmissense_SNVGene=NM_000750174802317TNA0.5CNANANAsynonymous_SNVGene=NM_000080174802829G0.5NAANANANAsynonymous_SNVGene=NM_000080174804902GNA0.5ANANANAsynonymous_SNVGene=NM_000080174805777CNA0.5GNANANAmissense_SNVGene=NM_0000802061981253CNA0.5TNANANAmissense_SNVGene=NM_000744,NM_0012565732061981362G0.5NAANANANAsynonymous_SNVGene=NM_000744,NM_0012565732061981411G0.5NAANANANAmissense_SNVGene=NM_000744,NM_0012565732061992467C0.5NATNANANAsynonymous_SNVGene=NM_0007442061992509T0.5NACNANANAsynonymous_SNVGene=NM_000744

[0314] Further information on these SNPs can be found at http: / / www .ncbi.nlm.nih.gov / projects / SNP / .

[0315] The SNPs and genotypes of Tables 26, 27 and 28 are consistent with those identified for isolated B lymphocytes in Example 6.

[0316] PLINK analysis highlighted missense, synonomous and genes for SNPs of the TRP families and PKD1L2.

[0317] 81,253,759 and 81,253,917 SNPs were identified as missense SNPs for the exon sequence for PKD1L2:NM_001076780:exon1:c.T217C:p.W73R and PKD1L2:NM_001076780:exon1:c.T59C:p.V20A. SNP 122,872,719, a TRPC3 receptor, was also found to be significantly associated with CSF / ME patients compared to controls from isolated B cells.

[0318] These finds are significant as TRPC3 has shown a direct association with PKCbeta that is required for downstream activation in B cells [43y]. Addtionally, TRPP subunits can be divided into two subcategories depending on structural similarity. The first group, polycystic kidney disease 1 (PKD1)-like, contains polycystin-1 (Previously known as TRPP1), PKDREJ, PKD1L1, PKD1L2, and PKD1L3.Example 10 - ERK1 / 2, MEK1 / 2 and p38 Downstream Signalling Molecules Impaired in CD56 dim< CD16 +< and CD56 bright< CD16 dim / -< Natural Killer Cells in Chronic Fatigue Syndrome / Myalgic Encephalomyelitis Patients

[0319] Natural Killer (NK) cells are innate immune cells which comprise approximately 10-15% of lymphocytes circulating in the peripheral blood [1m]. Two predominant NK cell phenotypes identified by the surface expression of cluster of differentiation (CD) 56 and CD16 and an absence of CD3 provide host immunity through the production of immunoregulatory cytokines and the cytotoxic lysis of target cells [2m-4m].

[0320] Ten percent of peripheral NK cells are CD56 bright< CD16 dim / -< NK cells which constitutively express receptors for monocyte derived cytokines (monokines) [5m, 6m]. Monokine receptor ligation rapidly stimulates CD56 bright< CD16 dim / -< NK cells to produce cytokines including interferon gamma (IFN-γ), tumour necrosis factor alpha and beta (TNF-α and β), granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin (IL)-10 and IL-13 [5m, 6m]. CD56 bright< CD16 dim / -< NK cell cytokine production provides an early source of cytokines which augments NK cell cytotoxic activity and regulates the function of other lymphocytes [2m, 5m, 4m]. Approximately 90% of peripheral NK cells are cytotoxic CD56 dim< CD16 +< NK cells [7m, 5m]. Cytotoxic NK cells contain high numbers of secretory granules which constitutively express apoptotic inducing lytic proteins perforin, Granzyme A and Granzyme B [3m, 8m].

[0321] Following CD56 dim< CD16 +< NK cell recognition of a target cell, the lytic proteins are released by a process known as degranulation to induce cytotoxic lysis and subsequent removal of target cells infected with viruses, bacteria or cells which have been malignantly transformed [9m, 10m].

[0322] Unlike T and B lymphocytes, the effector function of NK cells is governed by a myriad of surface receptors which integrate activating or inhibiting signals into intracellular signalling cascades [11m-13m]. After NK cell receptor ligation, intracellular activation signals are propagated through protein phosphorylation cascades by mitogen-activated protein kinases (MAPKs) [14m-16m]. Three main subgroups of MAPKs include extracellular signal-regulated kinases (ERK) 1 / 2, p38 MAPK (p38) and the c-Jun N-terminal kinase (JNK) [14m-16m]. In response to extra cellular stimuli, the MAPK signalling pathways transduce signals to specific intracellular targets to mediate cellular responses including gene expression, mitosis, motility, cell survival, apoptosis and differentiation [17m]. Within the NK cells, phosphorylation of MEK1 / 2 and p38 regulate cytokine production and ERK1 / 2 phosphorylation polarises the secretory granule towards the immune synapse for degranulation [16m, 18m]. In addition to MAPK signalling for normal cellular responses, impairments in MAPK signalling have been suggested to contribute to the pathology of disease processes relating to leukaemia, diabetes, Alzheimer's and Parkinson's disease, atherosclerosis, arthritis and airway inflammation [19m-25m].

[0323] Longitudinal reports of significantly reduced NK cell cytotoxic activity in Chronic Fatigue Syndrome / Myalgic Encephalomyelitis (CFS / ME) patients suggests the presence of an NK cell functional deficiency which may contribute to the illness pathogenesis [26m-34m]. Current investigations into NK cell phenotypes, receptors and lytic proteins in CFS / ME have reported equivocal findings and importantly, intracellular signalling by MAPKs in NK cells remains to be examined [27m, 35m, 36m]. Therefore, the purpose of the present study was to investigate NK cell phosphorylation of the MAPK signalling cascade, including signalling via the MAPK kinase (MAPKK / MEK1 / 2) and extracellular signal-regulated kinase (ERK)1 / 2 as well as p38, cytotoxic activity, degranulation, lytic proteins and cytokine production in CD56 dim< CD16 +< and CD56 bright< CD16 dim / -< NK cells from CFS / ME patients.Methods Participant recruitment and inclusion criteria

[0324] CFS / ME patients and non-fatigued controls (NFC) were recruited from a participant database at the National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland. All participants completed an online questionnaire based on the 1994 Fukuda definition for fatigue and symptom presentation to determine suitability for study inclusion [37m]. From the questionnaire responses, CFS / ME patients meeting the 1994 Fukuda definition and NFC were included. All participants were screened for exclusionary conditions such as epilepsy, thyroid conditions, psychosis, diabetes, cardiac disorders, smoking, pregnant or breastfeeding and immunological, inflammatory or autoimmune diseases.Blood collection and cell isolation

[0325] Forty millilitres of sodium heparin blood was collected by venepuncture from the antecubital vein of each participant. To avoid the influence of circadian variation, all blood samples were collected in the morning between 7:30-10am. Laboratory analysis commenced within four hours of blood collection to maintain cell viability. Routine blood parameters including a full blood count, erythrocyte sedimentation rate, electrolytes and high sensitivity C-reactive protein were assessed on each participant sample by Queensland Pathology. The whole blood samples were diluted with unsupplemented Roswell Park Memorial Institute medium (RPMI) 1640 media (Life Technologies, Carlsbad, USA) and peripheral blood mononuclear cells (PBMCs) were isolated by density gradient centrifugation with Ficoll-Hypaque (GE Health Care, Uppsala, UP).NK cell MAPK phosphorylation

[0326] Phosphorylation of signalling proteins in the MAPK pathway including signalling via the MAPK kinase (MAPKK / MEK1 / 2) and extracellular signal-regulated kinase (ERK)1 / 2 as well as p38, was examined under two stimulatory conditions using phospho-specific antibodies as previously described [38m-40m]. Following isolation, the PBMCs in RPMI 1640 media supplemented with ten percent FBS were incubated for a minimum of two hours at 37 °< C with five percent CO 2 to reduce background phosphorylation. After resting, the PBMCs were stained with mAbs for CD56-APC (Miltenyi Biotech, Cologne, BG) or CD56-phycoerythrin-cyanine (PE-Cy)7, CD16- brilliant violet (BV)711 and CD3-BV510 (BD Biosciences, San Diego, USA) for 25 minutes and subsequently washed. The PBMCs were stimulated with either K562 cells (E:T of 25:1) or PMA (50ng / ml) plus ionomycin (I, 0.5µg / ml) as a positive control for 15 minutes in a water bath at 37°C. A parallel sample of unstimulated (US) cells in RPMI media alone was used to determine basal levels of phosphorylation. BD Phosflow fix buffer 1 (San Diego, USA) containing 4.2% formaldehyde was pre-warmed to 37°C and added to the PBMCs, incubated for ten minutes at 37°C and subsequently washed off. The cells were then incubated in BD perm / wash buffer 1 (San Diego, USA) containing FBS and saponin for ten minutes which was followed by staining with phosospecific mAbs including signal transducer and activator of transcription (Stat)-3 (pS727)- alexa fluor (AF) 488, MEK1 (pS218) / MEK2 (pS222)-AF488, p38 (pT180 / pY182)-PerCP Cy5.5, ERK1 / 2 (pT202 / pY204)-BV421, nuclear factor kappa beta (NF-κβ, pS529)-AF488, inhibitory kappa beta (Iκβ)-AF647, PKCα (pT497)-AF488 and JNK (pT183 / pY185)-AF647 for 30 minutes and subsequent flow cytometry analysis.NK cell cytotoxic activity

[0327] Flow cytometry was used to measure NK cell cytotoxic activity against the human chronic myelogenous leukaemia K562 cell line as previously described [41m, 29m]. Briefly, K562 cells (Sigma-Aldrich, St Louis, USA) were cultured in RPMI 1640 media (Life Technologies, Carlsbad, USA) supplemented with ten percent fetal bovine serum (FBS) (Life Technologies, Carlsbad, USA). Following isolation, the PBMCs were stained with Paul Karl Horan-26 fluorescent cell linker dye (Sigma-Aldrich, St Louis, USA) and washed with RPMI supplemented with ten percent FBS. The concentrations of the PBMCs and K562 cells were adjusted to 2.5x10 6< cells / ml and 1x10 5< cells / ml respectively and combined at three effector to target (E:T) ratios including 25:1, 12.5:1 and 6.25:1. A control sample of only K562 cells was also included to determine K562 cells undergoing apoptosis not induced by NK cell cytotoxic activity. The PBMCs and K562 cells were incubated for four hours at 37 C with five percent CO 2 and then stained with fluorescein isothiocyanate (FITC) annexin V and 7-aminoactinomycin (Becton Dickinson [BD] Pharminogen, San Diego, USA) for flow cytometric analysis on a BD Calibur (BD Biosciences, San Diego, USA) dual laser four colour flow cytometer. NK cytotoxic activity was calculated as percent specific death of the K562 cells for the three E:T ratios as previously described [41m].NK cell degranulation

[0328] NK cell surface expression of CD107a and CD107b was measured as a marker for NK cell degranulation as previously reported [9m]. PBMCs in the presence of mAbs for CD107a-PE and CD107b-FITC (BD Biosciences, San Diego, USA) were stimulated with either K562 cells (E:T of 25:1) or PMA (50ng / ml) plus ionomycin (0.5µg / ml) for one hour at 37 °< C with five percent CO 2 . Monensin (BD Biosciences, San Diego, USA) was added to the PBMCs and the cells were then incubated for an additional three hours. An unstimulated control sample included PBMCs incubated in only RPMI 1640 media. Post four hours incubation, the cells were washed and incubated with mAbs against CD56-APC, CD16-BV711 and CD3-BV510 (BD Biosciences, San Diego, USA) for 25 minutes which was followed by flow cytometric analysis.NK cell lytic proteins and maturation marker

[0329] Intracellular staining was used to measure the lytic proteins perforin, granzyme A and granzyme B contained within the secretory granules of NK cells [27m, 42m]. Surface expression of CD57 was measured as a marker for NK cell maturation [43m]. The PBMCs were incubated with mAbs for CD56-PE-Cy7, CD16-BV711, CD3-BV510 and CD57-PE-cyanin-based fluorescent dye (CF)594 for 25 minutes. The PBMCs were then permeabilised with BD fixation / permeabilisation solution for 20 minutes, washed in BD perm / wash buffer and then incubated with mAbs including perforin-APC (Miltenyi Biotec, Cologne, BG), granzyme A-FITC and granzyme B-V450 (BD Biosciences, San Diego, USA) for 30 minutes which was followed by flow cytometric analysis.NK cell cytokines

[0330] NK cell production of the cytokines IFN-γ, TNF-α and GM-CSF was determined by intracellular staining under two stimulatory conditions as described previously [9m, 44m]. After isolation, PBMCs were incubated in the presence of either K562 cells (E:T of 25:1) or phorbol-12-myristate-13-acetate (PMA, 50ng / ml) (Sigma-Aldrich, St Louis, USA) plus ionomycin (I, 0.5µg / ml) (Sigma-Aldrich, St Louis, USA) for one hour at 37 °< C with five percent CO 2 . Brefeldin A (BD Biosciences, San Diego, USA) was added to prevent cytokine secretion during stimulation and the cells were incubated for an additional five hours [9m, 44m]. PBMCs incubated in RPMI 1640 media alone served as the unstimulated control sample. Following six hours incubation, the PBMCs were washed and incubated with monoclonal antibodies (mAbs) for CD56-PE-Cy7, CD16-BV711 and CD3-BV510 (BD Biosciences, San Diego, USA) for 25 minutes. The PBMCs were subsequently washed, incubated in BD fixation / permeabilisation solution (BD Biosciences, San Diego, USA) for 20 minutes, washed in BD perm / wash buffer (BD Biosciences, San Diego, USA) and then incubated for 30 minutes with mAbs against IFN-γ- allophycocyanin (APC), TNF-α- peridinin chlorophyll protein-cyanine (PerCP-Cy)-5.5 (BD Biosciences, San Diego, USA) and GM-CSF-PE (Biolegend, San Diego, USA) for flow cytometric detection of intracellular cytokines.Multiparametric flow cytometry analysis

[0331] Data were collected on a 14-parameter LSR-Fortessa X20 flow cytometer (BD Biosciences, San Diego, USA). Cell signalling technology beads (BD Biosciences, San Diego, USA) were run on a daily basis to ensure optimal flow cytometry performance and application settings were employed to standardise target values for the duration of the experiments. A total of 2500 to 5000 CD56 positive events were acquired. Data generated for NK cell cytokines, degranulation, lytic proteins and cell maturation was analysed on FlowJo (version 10.0.8) and phosphorylation data were analysed on Cytobank (version 5.0) [45m]. NK cell analysis was performed on cells which fell within the lymphocyte population according to forward and side scatter properties. CD56 +< CD3 -< NK cells were gated to determine total NK cells which was extrapolated to a plot of CD56 and CD16 to identify CD56 bright< CD16 dim / -< and CD56 dim< CD16 +< NK cells for the analysis of each marker for cytokines, degranulation, phosphorylation, lytic proteins and cell maturation. A combination of appropriate fluorescence minus one controls, isotype controls matched to antibody concentrations and unstimulated samples were used to determine NK cell gating for each analysis.Statistical Analysis

[0332] Statistical analysis of the data was performed on the Statistical Package for the Social Sciences (version 22) and GraphPad Prism (version 6). All data sets were tested for normality using the Shapiro-Wilk test. The independent Mann-Whitney U-test was used to identify any significant differences in the NK cell parameters between the CFS / ME and NFC groups. A Kruskal-Wallis multiple comparisons test was used to identify significant differences in NK cell parameters before and after stimulation within the CFS / ME and NFC cohorts. Significance was set at p<0.05 and the data is presented as median ± interquartile range unless otherwise stated.Abbreviations

[0333] APC: allophycocyanin, AF: alexa fluor, BD: Becton Dickinson, BV: brilliant violet, CD: cluster of differentiation, CF: cyanin-based fluorescent dye, ERK: extracellular signal-regulated kinases, E:T: effector to target, FBS: fetal bovine serum, FITC: fluorescein isothiocyanate, GM-CSF: granulocyte-macrophage colony-stimulating factor, Iκβ: inhibitory kappa beta, I: ionomycin , IFN-y: interferon gamma, IL: interleukin, JNK: Jun N-terminal kinase, mABs: monoclonal antibodies, MAPK: mitogen-activated protein kinase, MFI: median fluorescence intensity, NK: Natural killer, NFC: non-fatigued control, NF-κβ: nuclear factor kappa beta, PBMCs: peripheral, blood mononuclear cells, PE: phycoerythrin, PE-Cy: phycoerythrin-cyanine, PerCP-Cy: peridinin chlorophyll protein-cyanine, PMA: phorbol-12-myristate-13-acetate, p38: p38 mitogen-activated protein kinase, RPMI: Roswell Park Memorial Institute, Stat: signal transducer and activator of transcription, TNF: tumour necrosis factor, US: unstimulated.Results Participant inclusion, blood parameters and NK cell phenotypes

[0334] 14 CFS / ME patients meeting the 1994 Fukuda definition (mean age [years] ± standard error of the mean (SEM) = 53.5 ± 2.17) and 11 NFC (mean age [years] ± SEM = 48.82 ± 3.46) were included in this study. Comparison of the group ages and blood parameters including erythrocyte sedimentation rate, high sensitivity C-reactive protein and full blood counts of white and red blood cells between CFS / ME and the NFC revealed no significant differences (Table 29). Total NK cells were compared according to two phenotype populations, which were CD56 dim< CD16 +< and CD56 bright< CD16 dim / -< - between CFS / ME and NFC cohorts and no significant differences were observed (See Figure 5). Table 29: CFS / ME and NFC blood parameters.CFS / ME (n= 14) NFC (n=11) P value ESR (mm / Hr)7.85 ± 0.778.45 ± 1.440.700High sensitivity C-reactive protein (mg / L)0.99 ± 0.300.91 ± 0.410.873White and red blood cells White blood cells (10 9< / L)5.16 ± 0.385.26 ± 0.410.860Lymphocytes (10 9< / L)1.67 ± 0.151.67 ± 0.131.000Monocytes (10 9< / L)0.32 ± 0.030.27 ± 0.030.258Neutrophils (10 9< / L)2.96 ± 0.243.15 ± 0.280.610Eosinophils (10 9< / L)0.17 ± 0.030.15 ± 0.030.647Basophils (10 9< / L)0.03 ± 0.0010.03 ± 0.0011.000Platelets (10 9< / L)238.54 ± 15.50248.00 ± 18.010.693Red blood cells (10 12< / L)4.55 ± 0.124.61 ± 0.150.755Haemoglobin (g / L)138.85 ± 3.82138.82 ± 4.260.996Haematocrit0.42 ± 0.010.41 ± 0.010.493Mean cell volume (fL)91.62 ± 0.9489.27 ± 0.930.094Electrolytes Sodium (mmol / L)137.92 ± 0.46137.09 ± 0.530.249Potassium (mmol / L)4.10 ± 0.104.16 ± 0.120.702Chloride (mmol / L)100.69 ± 0.61101.64 ± 0.650.301Bicarbonate (mmol / L)28.62 ± 0.6327.27 ± 0.450.112Anion gap (mmol / L)8.54 ± 0.638.36 ± 0.640.845 ERK1 / 2 significantly reduced in CD56 dim< CD16 +< NK cells from CFS / ME patients

[0335] After incubation with K562 cells at an E:T ratio of 25:1, ERK1 / 2 was significantly reduced in CD56 dim< CD16 +< NK cells from CFS / ME patients when compared to NFC. (See Figure 5.) PMA / I induced a significant increase in ERK1 / 2 phosphorylation in CD56 dim< CD16 +< NK cells compared to the US and K562 stimulated cells from CFS / ME and NFC participants. Comparison of ERK1 / 2 in CD56 bright< CD16 dim / -< NK cells revealed no significant differences between CFS / ME and NFCs. (See Figure 6.)MEKl / 2 and p38 significantly increased CD56 bright< CD16 dim / < -< NK cells from CFS / ME patients

[0336] In CFS / ME patients, phosphorylation of MEK1 / 2 and p38 was significantly increased in CD56 bright< CD16 dim / -< NK cells following incubation with K562 cells at an E:T ratio of 25:1 compared to the NFC. (See Figure 6.) Stimulation with PMA / I induced a significant increase in MEK1 / 2 and p38 compared to US and K562 stimulated cells in both CFS / ME and NFC cohorts. Comparison of MEK1 / 2 and p38 in CD56 dim< CD16 +< NK cells from CFS / ME and NFC revealed no significant differences. (See Figures 7 and 8.) Measurement of additional MAPK proteins including Stat-3, NF-κβ, Iκβ, protein kinase c-α and JNK revealed no significant differences between CFS / ME and the NFC cohorts. (See Figures 9-13.)NK cell cytotoxic activity reduced in CFS / ME

[0337] In both CFS / ME patients and NFC, NK cell cytotoxic activity at 25:1 wa...

Claims

1. A method of identifying a subject at risk of developing chronic fatigue syndrome (CFS) or diagnosing a subject having CFS, said method comprising testing a biological sample that has been obtained from the subject for at least one single nucleotide polymorphism (SNP) of at least one transient receptor potential (TRP) ion channel gene known to correlate with CFS, wherein the SNP of the TRP ion channel gene is rs12682832 (TRPM3), rs11142508 (TRPM3), rs655207 (TRPC4), or rs6650469 (TRPC4).

2. The method of claim 1, wherein the SNP of the TRP ion channel gene is rs12682832 (TRPM3).

3. The method of claim 1, wherein the SNP of the TRP ion channel gene is rs11142508 (TRPM3).

4. The method of claim 1, wherein the SNP of the TRP ion channel gene is rs655207 (TRPC4).

5. The method of claim 1, wherein the SNP of the TRP ion channel gene is rs6650469 (TRPC4).

6. The method of any one of claims 1 to 5, wherein the testing is carried out using an array, biochip or kit.