A novel and improved method of differentiating infection from inflammation

Abstract

A method of determining a health status of an individual, the method comprising the steps of assaying a biological sample from the individual for the positive expression of SAA1 and / or SAA2, and wherein the positive expression of the SAA1 and / or SAA2 above or below a threshold expression level in a control sample correlates with the health status of the individual.

Description

[0001]Title A novel and improved method of differentiating infection from inflammation. Field of the Invention The invention relates to the use of biomarkers in a diagnostic test. In particular, the invention relates to biomarkers for distinguishing between infectious and inflammatory processes and conditions, and treating said infectious and inflammatory conditions. Background to the Invention Serum Amyloid A (SAA) is an apolipoprotein encoded by a family of genes. In humans, there are four different genes that encode SAA1, SAA2, SAA3 and SAA4. SAA1 and SAA2, also known as acute-phase SAA (A-SAA) elevate in humans in response to inflammation and infection. SAA3 is considered a pseudogene, while SAA4 is known as constitutive SAA (C-SAA). SAA is used as a biomarker of inflammation and infection. However, it has been found to be elevated in both conditions, which complicates clinical interpretation and decision making. Current SAA tests are not specific to SAA1 or SAA2 and while they detect inflammation and infection they do not adequately differentiate between the two to give an optimal outcome. CRP and PCT tests also claim to detect inflammation and infection, but they do not accurately differentiate between cases of infection and inflammation and have been shown to elevate in both conditions. Problems arise when inflammation and infection cannot be distinguished from one another, as patients with inflammation may be mistakenly diagnosed with infection and thereby treated unnecessarily with antibiotics, lending to the issue of irresponsible antibiotic use and antibiotic resistance. Additionally, patients with chronic inflammatory conditions cannot be accurately diagnosed with infection as existing biomarkers such as CRP are reported to be chronically elevated. The lack of reliable and specific biomarkers hampers clinical management of patient conditions. Optimal management of patients presenting with serious illness requires early and accurate distinction between infectious and non-infectious causes as quickly as possible and without ambiguity. Laboratory tests to detect pathogens and thereby identify infection are associated with a turnaround time and require trained technicians. Cleary there remains a continuous need to provide improved biomarkers for use in conditions involving inflammation, particularly conditions that require differentiation from inflammation associated with inflammatory conditions and inflammation associated with infectious causes. It is an object of the present invention to overcome at least one of the above-mentioned problems. Summary of the Invention There is a continuous need for additional and preferably improved methods for early and / or accurate prediction, detection, diagnosis, prognosis and / or monitoring of diseases and conditions to guide clinical decision making and to provide a stronger basis for therapeutic administration and for monitoring the effect of treatments. The Applicant has found that SAA1 is preferentially associated with inflammation compared to SAA2. The invention therefore provides a novel and inventive method for the quantitative determination and differentiation of SAA1 from SAA2 (for example, by using isoform specific antibodies), and in the process providing an improved method of detecting and differentiating infection from inflammation. SAA1 has a selective and stronger association with inflammatory conditions than SAA2 and therefore measuring SAA1 and SAA2 as individual biomarkers rather combined as total SAA provides information which is not currently available using existing test methods. The Applicant has utilised SAA1- and SAA2-specific antibodies conjugated to labelled particles on, for example, an Enzyme-linked Immunosorbent Assay (ELISA), a dipstick assay platform, or a lateral flow assay (or across a combination of said platforms). Across two studies, samples from patients with either healthy, infectious, or inflammatory conditions, or having a non-infectious infection, were assessed on these platforms. The advantages of the invention lie in being capable of detecting one and / or both isoforms of acute-phase SAA, that is, SAA1 and / or SAA2, in whole blood, serum or plasma, whereby the result of which can directly and strongly differentiate between inflammation and infection. Elevated levels of SAA1 above a control value or threshold is more specific to inflammation, while elevation of SAA2 levels when compared to a control or threshold is specific to infection. The test device can be a lateral flow device (LFD) which consists of 1 or 2 test lines, where SAA1 and / or SAA2-specific antibodies are present to detect SAA1 and / or SAA2, respectively. An electronic device adapted to accept the LFD consists of reflectometric technology to interpret the signal or signals from the LFD and can use an algorithm to convert the signal(s) to an SAA1 and / or an SAA2 concentration, and calculate either the ratio between the levels or concentrations of the two proteins SAA1 and SAA2, or providing a concentration (threshold) level of SAA1 and / or SAA2 (if present in the sample). Other devices of similar technology may be modified to work with the invention. By differentiating between SAA1 and SAA2, patients with inflammation and infection are more accurately diagnosed. Patients correctly diagnosed with inflammation alone will be treated with anti-inflammatory therapeutics (e.g., steroids), while patients correctly diagnosed with infection will be treated with an anti-microbial treatment (e.g., an antibiotic). This also greatly helps patients with chronic inflammatory conditions such as chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF), diabetes, atherosclerosis etc., to detect infection more accurately, when infection arises from their underlying inflammatory condition. In one aspect, there is provided a method as set out in the appended claims. In one aspect, there is provided a method of determining a health status of an individual, the method comprising the steps of assaying a biological sample from the individual for the positive expression of SAA1 and / or SAA2, and wherein the positive expression of the SAA1 and / or SAA2 above or below an expression threshold level of SAA1 and / or SAA2 in control sample correlates with the health status of the individual. When the expression levels of SAA1 are above the expression threshold levels in a control sample (e.g. a sample from a healthy individual with no underlying infection or inflammatory event), an inflammatory event is occurring; while when the expression levels of SAA2 are above the expression threshold levels of SAA2 in the control sample, an infection is present. When the expression levels of SAA1 are above the expression threshold levels of SAA1 in a control sample (e.g. a sample from a healthy individual with no underlying infection or inflammatory event), an inflammatory event is occurring. SAA1 expression elevates more frequently and significantly in response to inflammation than SAA2, making SAA1 a more specific marker for determining the health status of an individual. If SAA1 is elevated and SAA2 reaches a certain threshold expression level (though not necessarily exceeding SAA1) relative to a control or a threshold control level, then infection is more likely due to the presence of an elevated SAA2. SAA2 elevation is more directly associated with the presence of infection rather than inflammation, which SAA1 levels are linked to inflammation. In one aspect, there is provided a method of monitoring the effectiveness of treatment of an infectious disease (or an infection) in an individual with an infectious disease (or an infection), the method comprising the step of assaying a biological sample from the individual with an infectious disease (or an infection) for the positive expression of SAA1 and / or SAA2, wherein the positive expression of SAA1 below a specified threshold expression level and the positive expression of SAA2 below a specified threshold expression level correlates with the effectiveness of treatment of the infectious disease (or the infection) in the individual. If the expression levels of both proteins are above their respective expression threshold (control) levels, the treatment is ineffective. In this case, a new treatment plan can be devised for the individual. In one aspect, there is provided method of identifying an individual with an infection or an infectious disease that is suitable for treatment with a therapy for treating the infectious disease, the method comprising the steps of assaying a biological sample from the individual with the infection or infectious disease for the positive expression SAA2, wherein the positive expression of SAA2 above or below a specified SAA2 threshold expression (control) level correlates with identifying that the individual has an infection or an infectious disease and / or with the effectiveness of treatment of the infection or infectious disease in the individual. In one aspect, there is provided a method of determining the progression of treatment of an individual with an inflammatory disease, the method comprising the step of assaying a biological sample from the individual with the inflammatory disease for the positive expression of SAA1, wherein the positive expression of SAA1 above or below a specified threshold expression (control) level of SAA1 in a control sample, correlates with the effectiveness of treatment of the inflammatory disease or disorder in the individual. In one aspect, there is provided a method of determining the progression of treatment of an individual with an infection, the method comprising the step of assaying a biological sample from the individual with the infection for the positive expression of SAA2, wherein the positive expression of SAA2 above or below a threshold level of SAA2 in a control sample, correlates with the effectiveness of treatment of the infection in the individual. In one aspect, when the expression levels of SAA1 and / or SAA2 are below the threshold expression (control) level of SAA1 and / or SAA2 in the control sample, the individual is not suffering from an infection, an infectious disease, an inflammatory event, or an inflammatory condition. In one aspect, when the expression levels of SAA1 are above a specified threshold expression (control) level of SAA1 in the control sample, the individual is experiencing an inflammatory event or is suffering from an inflammatory condition. In one aspect, when the expression levels of SAA2 are above the specified threshold expression (control) level of SAA2 in the control sample, the individual is experiencing an infection. In one aspect, when the expression levels of SAA1 are above a specified threshold expression (control) level of SAA1 in the control sample, the individual is at risk of onset of an autoimmune condition and / or an autoinflammatory condition. In one aspect, when the expression levels of SAA2 are above the specified threshold expression (control) level of SAA2 in the controls ample, the individual still has the infection and is not responding to treatment. In one aspect, when the expression levels of SAA1 is below the threshold expression (control) level of SAA1 in the control sample, the individual is responding to treatment; and wherein when the expression level of SAA1 is above the threshold expression (control) level of SAA1 in the control sample, the individual is experiencing an inflammatory response and is not responding to treatment. In one aspect, when the expression levels of SAA2 is greater than the threshold expression (control) level of SAA2 in the control sample, the individual is not responding to treatment. In one aspect, wherein a combination of the expression levels of SAA1 and SAA2 in the biological sample from the individual greater than the combined expression threshold levels of SAA1 and SAA2 in the control sample correlates with differentiating between inflammation and infection. In one aspect, wherein determining the difference in the expression levels of SAA1 and SAA2 differentiates between inflammation and infection, wherein a negative expression value of SAA1 following subtraction of SAA2 levels indicates an infection, while a positive expression value of SAA1 following subtraction of SAA2 indicates an inflammation event. In one aspect, when the combined expression levels of SAA1 and SAA2 in the biological sample obtained from the individual are greater than 18 ug / ml, infection is ruled out and an inflammation event is confirmed or diagnosed; and when the subtracted levels of SAA1 and SAA2 in the biological sample obtained from the individual are greater than 33 ug / ml, inflammation is ruled out and infection is confirmed or diagnosed. In one aspect, the infection or infectious disease is selected from septicaemia, meningitis, an eye infection, an ear infection, tuberculosis, an upper respiratory tract infection, pneumonia, gastritis, a nail infection, a soft tissue infection, a skin infection, a central nervous system infection, a sexually transmitted infection, a bone infection, a joint infection, and a general post-surgical infection. In one aspect, the inflammatory condition is selected from allergies, asthma, colitis, ulcerative colitis, and Crohn’s disease, lupus, rheumatoid arthritis, multiple sclerosis, endocrine disorders, chronic inflammatory demyelinating polyneuropathy, Guillain-Barre syndrome, psoriasis, vasculitis, Grave’s disease, myasthenia gravis, Hashimoto’s thyroiditis, celiac disease, glomerulonephritis, hepatitis, cryopyrinopathies or cryopyrin- associated periodic syndromes (CAPS), hives, skin rash, bronchitis, tissue injury, bone and skin non-infectious inflammation, kidney and urinary tract inflammatory conditions, acne, chronic prostatitis, diverticulitis, chronic obstructive pulmonary disease (COPD), cystic fibrosis, atherosclerosis, Alzheimer’s disease, cancer, and heart disease. In one aspect, the individual is a mammal. In one aspect, the mammal is a human. In one aspect, there is provided a method of treating an infection, an infectious disease, an inflammatory condition, or an autoinflammatory condition in a subject, the method comprising: receiving the results of an assay that indicates that the level of SAA1 and SAA2 in a sample obtained from the subject is above or below a threshold expression (control) level in a control sample; and administering a treatment for the disease or condition. In one aspect, there is provided a method of treating an infectious disease in a subject in need thereof, the method comprising administering a suitable antibiotic to a subject determined to have an expression level of SAA2 above a threshold expression (control) level in a control sample. In one aspect, there is provided a method of treating an inflammatory disease in a subject in need thereof, the method comprising: a) determining the expression level of SAA1 in a sample obtained from a subject; and b) administering an anti-inflammatory drug to the subject if the expression level of SAA1 is above a threshold expression (control) level in a control sample. In one aspect, the method further comprises administering a suitable treatment as set out in Table 1 to a subject previously determined to have an expression level of SAA1 and / or SAA2 that is above or below the threshold expression (control) levels in the control sample. In one aspect, the infection, the infectious disease, the inflammatory condition, or the autoinflammatory condition is selected from the disease or condition set out in Table 1. In one aspect, there is provided a method of treating a disease or condition set out in Table 1 in a subject in need thereof, the method comprising: a) determining the expression level of SAA1 and / or SAA2 in a sample obtained from a subject; and b) administering a suitable treatment as set out in Table 1 to the subject if the expression level of SAA1 and / or SAA2 are above or below a threshold expression (control) level in a control sample. In one aspect, there is provided a method for differentiating whether an individual is healthy, has an inflammatory condition or has a viral or bacterial infection, the method comprising the steps of assaying a biological sample from the individual for the positive expression of SAA1 and / or SAA2 and wherein the positive expression of SAA1 and / or SAA2 above or below a threshold expression (control) level in a control sample correlates with the health status of the individual, wherein if the concentration of SAA2 is above the threshold expression (control) level of SAA2 in the control sample the individual is determined to have a bacterial or viral infection; wherein if the concentration of SAA1 is above the threshold expression (control) level of SAA1 in the control sample the individual is determined to have an inflammatory condition; and wherein if the concentration of SAA1 and / or SAA2 is below the (control) threshold expression level of SAA1 and / or SAA2 in the control sample, the individual is determined to be healthy. In one aspect, when a negative expression of SAA1 and / or SAA2, or when the expression levels of SAA1 and / or SAA2 are below the threshold expression (control) level of SAA1 and / or SAA2 in the control sample, the result indicates a healthy status in the subject, and the treatment, if being administered, can be stopped. In one aspect, there is provided the detection and monitoring of SAA1 to diagnose and monitor inflammation. In one aspect, there is provided the detection and monitoring of SAA2 to diagnose and monitor infection. In one aspect, there is provided the detection and monitoring of both SAA1 and SAA2 to diagnose and monitor inflammation and infection. In one aspect, there is provided the detection of both SAA1 and SAA2 individually but on the same cartridge to differentiate between inflammation and infection. In one aspect, there is provided the use of SAA1 and SAA2 ratios to differentiate between inflammation and infection. In one aspect, there is provided the use of SAA1 and total SAA ratios to differentiate between inflammation and infection. In one aspect, there is provided the use of SAA2 and total SAA ratios to differentiate between inflammation and infection. In one aspect, there is provided the use of SAA1 and SAA2 ratios to differentiate between bacterial and viral infection. In one aspect, there is provided the use of SAA1 and total SAA ratios to differentiate between bacterial and viral infection. In one aspect, there is provided the use of SAA2 and total SAA ratios to differentiate between bacterial and viral infection. All of the above methods can be performed on immune-based detection devices or platforms with SAA1-specific and SAA2-specific antibodies such as a lateral flow platform, an ELISA platform, a dipstick platform, or a combination thereof. All the above platforms, such as on a lateral flow platform, are capable of being interpreted by an electronic device such as a handheld reader. All the above platforms, such as on a lateral flow platform, are capable of being interpreted by an electronic device such as a handheld reader where the ratio calculations or the expression values compared to a threshold or control values are performed by an algorithm in the electronic device. In one aspect, there is provided an algorithm comprising a decision tree (and clinical protocol) for categorizing patient health-status based on SAA1 and SAA2 isoform levels (for example, as set out in Figure 3), the decision tree set out as (1) determining a Patient Health Status, where a healthy patient is characterized by low SAA1 levels (below a first threshold “1A”, that is, below the levels of a first threshold when compared to a reference sample); wherein an unhealthy (not healthy) patient is characterised by high SAA1 levels (above the first threshold “1A” when compared to the reference sample); (2) further characterising the unhealthy (not healthy) patient status when SAA1 levels are high (above the levels of “1A” when compared to the reference sample), wherein when SAA1 levels are elevated, inflammation status is confirmed; wherein when SAA2 levels are elevated and above a second threshold level “2A”, infection status is confirmed; and (3) further characterising the infection status when SAA1 levels and SAA2 levels are elevated, wherein when SAA2 levels are between the second threshold level “2A” and a third threshold level “2B”, a viral infection status is confirmed; while when SAA2 levels are above the third threshold level “2B”, a bacterial infection status is confirmed. In one aspect of any of the embodiments, described herein is a method of treating a disease or condition as set out in Table 1 in a subject in need thereof, the method comprising: a) determining if the subject has a positive expression of SAA1 and / or SAA2 above or below a threshold (control) level; and b) instructing or directing that the subject be administered a suitable treatment as set out in Table 1 if the level of SAA1 and / or SAA2 is above or below a specified threshold (control) level. In some embodiments of any of the aspects, the step of determining if the subject has a specified expression level above or below a specified threshold or control level of SAA1 and / or SAA2 can comprise i) obtaining or having obtained a sample from the subject and ii) performing or having performed an assay on the sample obtained from the subject to determine / measure the level of SAA1 and / or SAA2 in the subject. In some embodiments of any of the aspects, the step of determining if the subject has positive expression of SAA1 and / or SAA2 can comprise performing or having performed an assay on a sample obtained from the subject to determine / measure the expression level of SAA1 and / or SAA2 in the subject. In some embodiments of any of the aspects, the step of determining if the subject has a specified threshold (control) level of expression level of SAA1 and / or SAA2 can comprise ordering or requesting an assay on a sample obtained from the subject to determine / measure the expression level of SAA1 and / or SAA2, in the subject. In some embodiments of any of the aspects, the step of instructing or directing that the subject be administered a particular treatment can comprise providing a report of the assay results. In some embodiments of any of the aspects, the step of instructing or directing that the subject be administered a particular treatment can comprise providing a report of the assay results and / or treatment recommendations in view of the assay results. In some embodiments of any of the aspects, the step of instructing or directing that the subject undergoing a particular treatment as set out in Table 1 for a particular disease or condition as set out in Table 1 is to cease receiving that particular treatment can comprise providing a report of the assay results. In some embodiments of any of the aspects, the step of instructing or directing that the subject stop being administered a particular treatment can comprise providing a report of the assay results and / or treatment recommendations in view of the assay results. In one aspect, the method can use SAA1 and SAA2 expression ratios or expression levels relative to a control or threshold level to differentiate between inflammation and infection. In one aspect, the method can use SAA1 and total SAA expression ratios or expression levels relative to a control or threshold level to differentiate between inflammation and infection. In one aspect, the method can use SAA2 and total SAA expression ratios or expression levels relative to a control or threshold level to differentiate between inflammation and infection. In one aspect, the method can use SAA1 and SAA2 expression ratios or expression levels relative to a control or threshold level to differentiate between bacterial and viral infection. In one aspect, the method can use SAA1 and total SAA expression ratios or expression levels relative to a control or threshold level to differentiate between bacterial and viral infection. In one aspect, the method can use of SAA2 and total SAA expression ratios or expression levels relative to a control or threshold level to differentiate between bacterial and viral infection. The above methods can be performed on immune-based detection devices or platforms such as a lateral flow platform, an ELISA platform, a dipstick platform, or a combination thereof, with SAA1-specific and SAA2-specific antibodies. All the above platforms, such as on a lateral flow platform, are capable of being used with an electronic device such as a handheld reader. The handheld reader is adapted to calculate the expression levels and / or the expression level ratios using an algorithm. Table 1: Diseases and Conditions, and their prescribed treatments* Infectious Disease Common Treatment Sepsis Intravenous broad-spectrum antibiotics (selected from ceftriaxone, azithromycin, ciprofloxacin, vancomycin, piperacillin-tazobactam); Intravenous fluids; and / or vasopressors Meningitis Intravenous antibiotics (selected from cephalosporins, various penicillin-type antibiotics, aminoglycoside drugs such as gentamicin); and / or corticosteroids. Eye Infection Antibiotic eye drops and / or aminoglycosides and cephalosporins. Bacterial Pneumonia Antibiotics (macrolides, fluoroquinolones, tetracyclines), cough medicine, fever reducer / pain reliever, acetaminophen / NSAIDs, or combinations thereof. Tuberculosis Antibiotics such as isoniazid, rifampin (Rifadin®, Rimactane®), ethambutol (Myambutol®), pyrazinamide. Viral Pneumonia Anti-virals (such as oseltamivir, zanamivit, peramivir, Ribavirin), cough medicine, fever reducer / pain reliever, acetaminophen / NSAIDs. Gastritis Antibiotics (such as clarithromycin, amoxicillin, metronidazole), proton pump inhibitors (PPIs), histamine blockers, and / or antacids. Nail Infection Antibiotics such as amoxicillin, clavulanic acid, clindamycin, or combinations thereof. Skin Infection Antibiotics such as dicloxacillin, erythromycin, tetracycline; or combinations thereof. Influenza Pneumonia Antivirals (such as oseltamivir, zanamivit, peramivir), cough medicine, fever reducer / pain reliever, acetaminophen / NSAIDs, or combinations thereof. Rhinovirus Pneumonia Antivirals (such as ribavirin), cough medicine, fever reducer / pain reliever, acetaminophen / NSAIDs, or combinations thereof. Whooping cough Antibiotics (such as erythromycin), cough medicine, fever reducer / pain reliever, acetaminophen / NSAIDs, or combinations thereof. Gastrointestinal Fever reducer / pain reliever, acetaminophen / NSAIDs, or o Rotavirus combinations thereof. o Norovirus Urinary Tract Infection (UTI) Antibiotics (such as Levaquin® (levofloxacin), ciprofloxacin, Keflex® (cefalexin), Zotrim® (sulfamethoxazole, trimethoprim, phenazopyridine), Bactrim® (rimethoprim / sulfamethoxazole)), fever reducer / pain reliever, acetaminophen / NSAIDs, or combinations thereof. Inflammatory Disease Acne Topical ointment (benzoyl peroxide), hormonal treatment, or bomcinations thereof Autoimmune disorders Inflammatory bowel disease Anti-inflammatories (corticosteroids, aminosalicylates), immunosuppressors (azathioprine, mercaptopurine, cyclosporine, methotrexate, TNF-alpha inhibitors (infliximab, adalimumab, golimumab)), anti-diarrheal medication, pain relievers (acetaminophen, NSAIDs), iron supplements, calcium & Vitamin D supplements, or combinations thereof. Lupus Non-steroidal anti-inflammatory drugs (NSAIDS) (e.g. Ibuprofen, naproxen), anti-malarial drugs, BLyS-specific inhibitors, immunosuppressive agents, chemotherapy, or combinations thereof. Rheumatoid Arthritis Anti-inflammatories (NSAIDs), corticosteroids, disease- modifying antirheumatic drugs (DMARDs), biologic agents (abatacept, adalimumab, anakinra, baricitinib, certolizumab, etanercept, golimumab, infliximab, rituximab, sarilumab, tocilizumab, tofacitinib), or combinations thereof. Multiple Sclerosis Corticosteroids, plasma exchange, ocrelizumab, beta interferons, glatiramer acetate, fingolimod, dimethyl fumarate, teriflunomide, siponimod, ocrelizumab, natalizumab, alemtuzumab, mitoxantrone, or combinations thereof. Type 1 diabetes Diet management, insulin, or combinations thereof. Chronic Inflammatory Corticosteroids, immunosuppressant drugs, plasmapheresis, demyelinating intravenous immunoglobulin therapy, or combinations thereof. polyneurophathy Guillian-Barre syndrome Plasmapheresis, intravenous immunoglobulin therapy, pain relievers, laxatives, or combinations thereof. Psoriasis Topical treatments (corticosteroids, Vitamin D and analogues thereof, anthralin, topical retinoids, calcineurin inhibitors, salicylic acid, coal tar), light therapy, oral / intravenous medication (retinoids, methotrexate, cyclosporin), or combinations thereof. Vasculitis Corticosteroids, steroid-sparing medication (methotrexate, azathioprine, mycophenolate, cyclophosphamide), surgery, o combinations thereof. Grave’s disease Radioactive iodine therapy, anti-thyroid medication, beta- blockers (propranolol, atenolol, metoprolol, nadolol), surgery, corticosteroids, or combinations thereof. Myasthenia gravis Cholinesterase inhibitors, corticosteroids, immunosuppressants, plasmapheresis, intravenous immunoglobulin therapy, monoclonal antibodies, surgery, or combinations thereof. Hashimoto’s thyroiditis Synthetic hormones (such as levothyroxine) Autoinflammatory conditions Cystic Fibrosis Medication targeting gene mutation (cystic fibrosis transmembrane conductance regulator (CTFR) modulators); antibiotics (to treat and prevent infection); anti-inflammatories; mucus-thinning drugs (for example, hypertonic saline); bronchodilators; oral pancreatic enzymes; stool softeners; acid-reducing medication; vest therapy; pulmonary rehabilitation; surgery; lung / liver transplant; or combinations thereof. Chronic Obstruction Smoking cessation; short-acting bronchodilators (albuterol, Pulmonay Disease (COPD) Ipratropium, Levalbuterol); long-acting bronchodilators (aclidinium, arformoterol, formoterol, indacaterol, tiotropium, salmeterol, umeclidinium); inhaled steroids (fluticasone, budesonide); combination inhalers; oral steroids (corticosteroids); phosphodiesterase-4 inhibitors; theophylline; Antibiotics (if infection present); lung therapies (oxygen therapy, pulmonary rehabilitation program); surgery; lung transplant, or combinations thereof. Alllergy Antihistamines, corticosteroids, decongestants, NSAIDs, or combinations thereof. Asthma Corticosteroids, albuterol, or combinations thereof. Celiac disease Diet management, anti-inflammatories, or combinations thereof. Glomerulonephritis Dialysis Hepatitis Anti-virals (entecavir, tenofovir, lamivudine, adefovir, telbivudine), interferon injections, surgery (liver transplant), or combinations thereof. Chronic Prostatitis NSAIDs, alpha blockers, or combinations thereof. Diverticulitis Pain relievers (acetaminophens), antibiotics (if infectious), surgery, or combinations thereof. Cancer Surgery, radiotherapy, chemotherapy, immunotherapy, hormone therapy, targeted drug therapy, cryoablation, radiofrequency ablation, or combinations thereof. Heart disease ACE inhibitors, aldosterone inhibitors, angiotension II receptor blockers, beta-blockers, vasodilators, or combinations thereof. *other diseases which are associated with those listed above are also described below. In one aspect, the method of the claimed invention can be used to detect respiratory infections (e.g., SARS-CoV-2 coronavirus, influenza, pneumonia, rhinovirus, respiratory syncytial virus (RSV), tonsillitis, and the like) in a subject caused by bacteria or a virus, and monitoring the subject’s response to treatment; detect UTIs (such as pyelonephritis, cystitis, urethritis) in a subject and monitor the subject’s response to treatment; detect blood system and systemic infections (including sepsis) in a subject and monitor the subject’s response to treatment; determine the severity and / or prognosis of infection in a subject; and distinguish between infectious and non-infectious inflammation in a subject and monitor the subject’s response to treatment. Definitions In the specification, the term “healthy” should be understood to mean where the individual or patient has no underlying medical condition or does not have or is not suffering from an infection, an inflammatory response, event, disorder, condition or otherwise. In the specification, the term “health status” should be understood to mean whether a subject is healthy (see above), or is found to be, or is, suffering from one or more from an infection, an infectious disease, an infectious condition, an inflammatory disease, an inflammatory condition, an autoinflammatory condition, an autoimmune condition, inflammatory bowel disease, heart disease, cancer, or combinations thereof. In the specification, the term “infection” or “infectious condition” should be understood to mean infections or diseases caused by microorganisms or microbes such as viruses, bacteria, fungi, protozoa and helminths. Examples of infections include septicaemia, meningitis, eye infections, ear infections, tuberculosis, upper respiratory tract infections, pneumonia, gastritis, nail, soft tissue and skin infections, central nervous system infections, sexually transmitted infections (such as chlamydia, genital herpes, genital warts, gonorrhoea, hepatitis A, hepatitis B, human immunodeficiency virus, Lymphogranuloma venereum, Mycoplasma genitalium, Shigella, syphilis, Trichomonas vaginalis), bone infections, joint infections, general post-surgical infections, and the like. Common bacteria that cause disease and infections include Staphylococcus, Streptococcus, Pseudomonas, Clostridium difficile, Escherichia coli and Listeria monocytogenes. In the specification, the term “inflammatory condition” should be understood to mean immune-related conditions resulting in allergic reactions, myopathies and abnormal inflammation and non-immune related conditions having causal origins in inflammatory processes. Inflammation includes acute inflammation and chronic inflammatory diseases. Acute inflammation includes allergies, headaches, hives, skin rash, bronchitis, tissue injury (such as cuts, bruises, wounds, burns), bone and skin non-infectious inflammation, kidney and urinary tract inflammatory conditions, etc. Chronic inflammatory includes examples such as acne, autoimmune conditions, autoinflammatory condition, chronic prostatitis, diverticulitis, chronic obstructive pulmonary disease (COPD), cystic fibrosis, atherosclerosis, Alzheimer’s disease, cancer, heart disease, and the like. In the specification, the term “autoinflammatory condition” should be understood to mean a group of diseases characterised by seemingly unprovoked episodes of fever and inflammation of skin, joints, serosal surfaces and other organ involvement including the nervous system. Examples of autoinflammatory conditions include allergy, asthma, autoimmune conditions, celiac disease, glomerulonephritis, hepatitis, cryopyrinopathies or cryopyrin-associated periodic syndromes (CAPS) (a group of three rare autoinflammatory diseases that includes familial cold autoinflammatory syndrome (FCAS), Muckle-Wells syndrome (MWS) and chronic infantile neurologic cutaneous articular syndrome (CINCA)), and the like. In the specification, the term “autoimmune condition” should be understood to mean a condition in which your immune system mistakenly attacks your body. Examples of autoimmune conditions include asthma, inflammatory bowel diseases, lupus, rheumatoid arthritis, multiple sclerosis, endocrine disorders (for example, Type 1 diabetes, type 2 diabetes), Chronic inflammatory demyelinating polyneuropathy, Guillian-Barre syndrome, psoriasis, vasculitis, Grave’s disease, myasthenia gravis, Hashimoto’s thyroiditis, and the like. In the specification, the term “inflammatory bowel disease” should be understood to mean disorders that involve chronic inflammation of the digestive tract. Examples of inflammatory bowel disease include colitis, ulcerative colitis, and Crohn’s disease. In the specification, the term “cancer” should be understood to mean a cancer selected from the group comprising node-negative, ER-positive breast cancer; early stage, node positive breast cancer; multiple myeloma, prostate cancer, glioblastoma, lymphoma, fibrosarcoma; myxosarcoma; liposarcoma; chondrosarcoma; osteogenic sarcoma; chordoma; angiosarcoma; endotheliosarcoma; lymphangiosarcoma; lymphangioendotheliosarcoma; synovioma; mesothelioma; Ewing's tumour; leiomyosarcoma; rhabdomyosarcoma; colon carcinoma; pancreatic cancer; breast cancer; ovarian cancer; squamous cell carcinoma; basal cell carcinoma; adenocarcinoma; sweat gland carcinoma; sebaceous gland carcinoma; papillary carcinoma; papillary adenocarcinomas; cystadenocarcinoma; medullary carcinoma; bronchogenic carcinoma; renal cell carcinoma; hepatoma; bile duct carcinoma; choriocarcinoma; seminoma; embryonal carcinoma; Wilms' tumour; cervical cancer; uterine cancer; testicular tumour; lung carcinoma; small cell lung carcinoma; bladder carcinoma; epithelial carcinoma; glioma; astrocytoma; medulloblastoma; craniopharyngioma; ependymoma; pinealoma; hemangioblastoma; acoustic neuroma; oligodendroglioma; meningioma; melanoma; retinoblastoma; and leukemias. Also included are metastases selected from the group comprising: bone metastases; lung metastases; liver metastases; bone marrow metastases; breast metastases; and brain metastases. In the specification, the term “heart disease” should be understood to mean cardiovascular disease selected from the group comprising: ischemic heart disease, cardiac hypertrophy; myocardial infarction; stroke; arteriosclerosis; and heart failure. In the specification, the term “subject”, “individual” or “patient” should be understood to mean all mammals, for example, a human, primates, non-human primates, farm animals (such as pigs, horses, goats, sheep, cows (including bulls, bullocks, heifers etc.), donkey, reindeer, etc.), veterinary mammals (such as dogs, cats, rabbits, hamsters, guinea pigs, mice, rats, ferrets, etc.), and mammals kept in captivity (such as lions, tigers, cheetahs, leopards, lynx, elephants, zebras, giraffes, pandas, rhino, hippopotamus, etc.), and other mammals and higher mammals for which the use of the invention is practicable. In this specification, the term “biological sample” should be understood to mean blood or blood derivatives (serum, plasma etc.), urine, saliva or cerebrospinal fluid. In the specification, the term “treatment” should be understood to mean prohibiting, preventing, restraining, and slowing, stopping or reversing progression or severity of a disease or condition associated with inflammatory or non-inflammatory diseases, conditions or infections. Serum Amyloid A (SAA) is small protein primarily associated with the innate response and is predominantly secreted by hepatocytes. The protein responds very quickly to the onset of a challenge with levels increasing 1000-fold or more within 24hours. The SAA sequence is remarkably conserved across many species indicating an important role. The literature widely reports SAA as being associated with non-specific inflammatory responses. In the specification, the term “test platform” in relation to determining the levels of the biomarkers should be understood to mean determining biomarker concentrations by immunoassay-based methods such as lateral flow immunoassays (LFAs), enzyme- linked immunosorbent assay (ELISA), immunoturbidimetric assays, quantitative polymerase chain reaction (PCR), reverse transcriptase PCR (RT-PCR), quantitative real time RT-PCR (qRT-PCR), Western Blot, protein determination on polyacrylamide gels, and the like. In the specification, the term “expression threshold level” or “control expression level” should be understood to mean the level of expression of SAA1 and / or SAA2 in a control sample. The control sample is one where the individual has neither an infection nor an inflammatory event occurring. The control level or the threshold level of SAA1 and SAA2 can be derived from healthy donor samples, baseline samples from the same individual prior to an inflammatory or an infection event (or prior to and post administration of a treatment), pooled normal samples and laboratory-generated samples that can be included in a reference database. This information can be stored in, for example, the LFD (for example, using a bar code) or an LFD reader for use in determining the health status of an individual. In the case of differentiating the onset of an inflammatory event in healthy individuals, where SAA1 levels are elevated compared to levels of SAA1 in the control sample (the threshold level), an inflammatory event is occurring. In the case of differentiating between an infection and an inflammatory event, where the levels of SAA2 are increased relative to the SAA2 levels in the control sample (the threshold level), an infection event is occurring. Deviation from the threshold or control level correlates with the individual’s health status. In the specification, the term “control sample” or “reference sample” (the terms can be used interchangeably) is a sample obtained from an individual has neither an infection nor an inflammatory event occurring, or obtained from the individual who has either an infection or an inflammatory event occurring and one wants to monitor the effectiveness of a treatment being administered. The control sample or reference sample can be derived from healthy donor samples, baseline samples from the same individual prior to an inflammatory or an infection event (or prior to and post administration of a treatment), pooled normal samples, and laboratory-generated samples that can be included in a reference database. In the specification, the term “variant” should be understood to mean proteins having amino acid sequences which are substantially identical to wild-type SAA, wild-type SAA1, wild-type SAA2, wild-type SAA3, or wild-type SAA4. Thus, for example, the term should be taken to include proteins or polypeptides that are altered in respect of one or more amino acid residues. Preferably such alterations involve the insertion, addition, deletion and / or substitution of 5 or fewer amino acids, more preferably of 4 or fewer, even more preferably of 3 or fewer, most preferably of 1 or 2 amino acids only. Insertion, addition and substitution with natural and modified amino acids is envisaged. The variant may have conservative amino acid changes, wherein the amino acid being introduced is similar structurally, chemically, or functionally to that being substituted. Generally, the variant will have at least 70% amino acid sequence identity, preferably at least 80% sequence identity, more preferably at least 90% sequence identity, and ideally at least 95%, 96%, 97%, 98% or 99% sequence identity with wild-type human proteins described herein. In this context, sequence identity is a polypeptide sequence that shares 70% amino acid identity with wild-type human protein is one in which any 70% of aligned residues are either identical to, or conservative substitutions of, the corresponding residues in the wild-type human proteins. It should be noted that this is the amount of characters which match exactly between two different sequences. Hereby, gaps are not counted, and the measurement is relational to the shorter of the two sequences. The term “variant” is also intended to include chemical derivatives of the wild-type protein, i.e. where one or more residues of Cf5 is chemically derivatized by reaction of a functional side group. Also included within the term variant are Cf5 molecules in which naturally occurring amino acid residues are replaced with amino acid analogues. The protein sequences encoded by the human genes of SAA1, SAA2, SAA3, and SAA4, in SEQ ID NO: 1, 3, 5, and 7, respectively. The Accession Numbers for the human proteins are also provided. The nucleotide sequences of the human genes of SAA1, SAA2, SAA3, and SAA4 are provided in SEQ ID NO: 2, 4, 6, and 8, respectively. The Accession Numbers for the human genes are also provided. In the specification, the term “Youden Index (J)” should be understood to mean the sum of sensitivity and specificity minus one and reflects the overall capacity of an early warning model to detect outbreaks and non-outbreaks. In some embodiments of any of the aspects, measurement of the level of a target and / or detection of the level or presence of a target, e.g. of an expression product (nucleic acid or polypeptide of one of the genes described herein) or a mutation can comprise a transformation. As used herein, the term “transforming” or “transformation” refers to changing an object or a substance, e.g., biological sample, nucleic acid or protein, into another substance. The transformation can be physical, biological or chemical. Exemplary physical transformation includes, but is not limited to, pre-treatment of a biological sample, e.g., from whole blood to blood serum by differential centrifugation. A biological / chemical transformation can involve the action of at least one enzyme and / or a chemical reagent in a reaction. For example, a DNA sample can be digested into fragments by one or more restriction enzymes, or an exogenous molecule can be attached to a fragmented DNA sample with a ligase. In some embodiments of any of the aspects, a DNA sample can undergo enzymatic replication, e.g., by polymerase chain reaction (PCR). Transformation, measurement, and / or detection of a target molecule, e.g. an SAA1 mRNA or polypeptide, can comprise contacting a sample obtained from a subject with a reagent (e.g. a detection reagent) which is specific for the target, e.g., a target-specific reagent. In some embodiments of any of the aspects, the target-specific reagent is detectably labeled. In some embodiments of any of the aspects, the target-specific reagent can generate a detectable signal. In some embodiments of any of the aspects, the target-specific reagent generates a detectable signal when the target molecule is present. Methods to measure gene expression products are known to a skilled artisan. Such methods to measure gene expression products, e.g., protein level, include ELISA (enzyme linked immunosorbent assay), western blot, immunoprecipitation, and immunofluorescence using detection reagents such as an antibody or protein binding agents. Alternatively, a peptide can be detected in a subject by introducing into a subject a labeled anti-peptide antibody and other types of detection agent. For example, the antibody can be labeled with a detectable marker whose presence and location in the subject is detected by standard imaging techniques. For example, antibodies for the various targets described herein are commercially available and can be used for the purposes of the invention to measure protein expression levels, e.g. anti-SAA (Cat. No. ab687; Abcam, Cambridge MA). Other antibodies for each of SAA are available from Abcam, Lifespan Bioscience, Novus Biological, Bio-Rad, and the like. Examples of the available antibodies can be found in Table 2 below. Alternatively, since the amino acid sequences for the targets described herein are known and publicly available at the NCBI website, one of skill in the art can raise their own antibodies against these polypeptides of interest for the purpose of the methods described herein. The amino acid and nucleotide sequences of the polypeptides described herein have been assigned NCBI accession numbers for different species such as human, mouse and rat. In particular, the NCBI accession numbers for the amino acid sequence of human SAA1, SAA2, SAA3, and SAA4 is included herein, e.g., SEQ ID NO: 1, 3, 5, and 7, respectively. The NCBI accession numbers for the nucleotide sequence of human SAA1, SAA2, SAA3, and SAA4 is included herein, e.g., SEQ ID NO: 2, 4, 6, and 8, respectively. In some embodiments of any of the aspects, immunohistochemistry (“IHC”) and immunocytochemistry (“ICC”) techniques can be used. IHC is the application of immunochemistry to tissue sections, whereas ICC is the application of immunochemistry to cells or tissue imprints after they have undergone specific cytological preparations such as, for example, liquid-based preparations. Immunochemistry is a family of techniques based on the use of an antibody, wherein the antibodies are used to specifically target molecules inside or on the surface of cells. The antibody typically contains a marker that will undergo a biochemical reaction, and thereby experience a change of color, upon encountering the targeted molecules. In some instances, signal amplification can be integrated into the particular protocol, wherein a secondary antibody, that includes the marker stain or marker signal, follows the application of a primary specific antibody. In some embodiments of any of the aspects, the assay can be a Western blot analysis. Alternatively, proteins can be separated by two-dimensional gel electrophoresis systems. Two-dimensional gel electrophoresis is well known in the art and typically involves iso- electric focusing along a first dimension followed by SDS-PAGE electrophoresis along a second dimension. These methods also require a considerable amount of cellular material. The analysis of 2D SDS-PAGE gels can be performed by determining the intensity of protein spots on the gel or can be performed using immune detection. In other embodiments, protein samples are analyzed by mass spectroscopy. Immunological tests can be used with the methods and assays described herein and include, for example, competitive and non-competitive assay systems using techniques such as Western blots, radioimmunoassay (RIA), ELISA (enzyme linked immunosorbent assay), "sandwich" immunoassays, immunoprecipitation assays, immunodiffusion assays, agglutination assays, e.g. latex agglutination, complement-fixation assays, immunoradiometric assays, fluorescent immunoassays, e.g. FIA (fluorescence-linked immunoassay), chemiluminescence immunoassays (CLIA), electrochemiluminescence immunoassay (ECLIA, counting immunoassay (CIA), lateral flow tests or immunoassay (LFIA), magnetic immunoassay (MIA), and protein A immunoassays. Methods for performing such assays are known in the art, provided an appropriate antibody reagent is available. In some embodiments of any of the aspects, the immunoassay can be a quantitative or a semi-quantitative immunoassay. An immunoassay is a biochemical test that measures the concentration of a substance in a biological sample, typically a fluid sample such as blood or serum, using the interaction of an antibody or antibodies to its antigen. The assay takes advantage of the highly specific binding of an antibody with its antigen. For the methods and assays described herein, specific binding of the target polypeptides with respective proteins or protein fragments, or an isolated peptide, or a fusion protein described herein occurs in the immunoassay to form a target protein / peptide complex. The complex is then detected by a variety of methods known in the art. An immunoassay also often involves the use of a detection antibody. Enzyme-linked immunosorbent assay, also called ELISA, enzyme immunoassay or EIA, is a biochemical technique used mainly in immunology to detect the presence of an antibody or an antigen in a sample. The ELISA has been used as a diagnostic tool in medicine and plant pathology, as well as a quality control check in various industries. In one embodiment, an ELISA involving at least one antibody with specificity for the particular desired antigen (e.g., any of the targets as described herein) can also be performed. A known amount of sample and / or antigen is immobilized on a solid support (usually a polystyrene micro titer plate). Immobilization can be either non-specific (e.g., by adsorption to the surface) or specific (e.g. where another antibody immobilized on the surface is used to capture antigen or a primary antibody). After the antigen is immobilized, the detection antibody is added, forming a complex with the antigen. The detection antibody can be covalently linked to an enzyme or can itself be detected by a secondary antibody which is linked to an enzyme through bio-conjugation. Between each step the plate is typically washed with a mild detergent solution to remove any proteins or antibodies that are not specifically bound. After the final wash step the plate is developed by adding an enzymatic substrate to produce a visible signal, which indicates the quantity of antigen in the sample. Older ELISAs utilize chromogenic substrates, though newer assays employ fluorogenic substrates with much higher sensitivity. In another embodiment, a competitive ELISA is used. Purified antibodies that are directed against a target polypeptide or fragment thereof are coated on the solid phase of multi-well plate, i.e., conjugated to a solid surface. A second batch of purified antibodies that are not conjugated on any solid support is also needed. These non- conjugated purified antibodies are labeled for detection purposes, for example, labeled with horseradish peroxidase to produce a detectable signal. A sample (e.g., a blood sample) from a subject is mixed with a known amount of desired antigen (e.g., a known volume or concentration of a sample comprising a target polypeptide) together with the horseradish peroxidase labeled antibodies and the mixture is then are added to coated wells to form competitive combination. After incubation, if the polypeptide level is high in the sample, a complex of labeled antibody reagent-antigen will form. This complex is free in solution and can be washed away. Washing the wells will remove the complex. Then the wells are incubated with TMB (3,3´,5,5´-tetramethylbenzidene) color development substrate for localization of horseradish peroxidase-conjugated antibodies in the wells. There will be no color change or little color change if the target polypeptide level is high in the sample. If there is little or no target polypeptide present in the sample, a different complex in formed, the complex of solid support bound antibody reagents-target polypeptide. This complex is immobilized on the plate and is not washed away in the wash step. Subsequent incubation with TMB will produce significant color change. Such a competitive ELSA test is specific, sensitive, reproducible and easy to operate. There are other different forms of ELISA, which are well known to those skilled in the art. The standard techniques known in the art for ELISA are described in "Methods in Immunodiagnosis", 2nd Edition, Rose and Bigazzi, eds. John Wiley & Sons, 1980; and Oellerich, M. 1984, J. Clin. Chem. Clin. Biochem. 22:895-904. These references are hereby incorporated by reference in their entirety. In one embodiment, the levels of a polypeptide in a sample can be detected by a lateral flow immunoassay test (LFIA), also known as the immunochromatographic assay, or strip test. LFIAs are a simple device intended to detect the presence (or absence) of antigen, e.g. a polypeptide, in a fluid sample. There are currently many LFIA tests used for medical diagnostics, either for home testing, point of care testing, or laboratory use. LFIA tests are a form of immunoassay in which the test sample flows along a solid substrate via capillary action. After the sample is applied to the test strip it encounters a colored reagent (generally comprising antibody specific for the test target antigen) bound to microparticles which mixes with the sample and transits the substrate encountering lines or zones which have been pretreated with another antibody or antigen. Depending upon the level of target polypeptides present in the sample the colored reagent can be captured and become bound at the test line or zone. LFIAs are essentially immunoassays adapted to operate along a single axis to suit the test strip format or a dipstick format. Strip tests are extremely versatile and can be easily modified by one skilled in the art for detecting an enormous range of antigens from fluid samples such as urine, blood, water, and / or homogenized tissue samples etc. Strip tests are also known as dip stick tests, the name bearing from the literal action of "dipping" the test strip into a fluid sample to be tested. LFIA strip tests are easy to use, require minimum training and can easily be included as components of point-of-care test (POCT) diagnostics to be use on site in the field. LFIA tests can be operated as either competitive or sandwich assays. Sandwich LFIAs are similar to sandwich ELISA. The sample first encounters colored particles which are labeled with antibodies raised to the target antigen. The test line will also contain antibodies to the same target, although it may bind to a different epitope on the antigen. The test line will show as a colored band in positive samples. In some embodiments of any of the aspects, the lateral flow immunoassay can be a double antibody sandwich assay, a competitive assay, a quantitative assay or variations thereof. Competitive LFIAs are similar to competitive ELISA. The sample first encounters colored particles which are labeled with the target antigen or an analogue. The test line contains antibodies to the target / its analogue. Unlabelled antigen in the sample will block the binding sites on the antibodies preventing uptake of the colored particles. The test line will show as a colored band in negative samples. There are a number of variations on lateral flow technology. It is also possible to apply multiple capture zones to create a multiplex test. The use of "dip sticks" (also known as dipsticks) or LFIA test strips and other solid supports have been described in the art in the context of an immunoassay for a number of antigen biomarkers. U.S. Pat. Nos. 4,943,522; 6,485,982; 6,187,598; 5,770,460; 5,622,871; 6,565,808, U. S. patent applications Ser. No. 10 / 278,676; U.S. Ser. No. 09 / 579,673 and U.S. Ser. No.10 / 717,082, which are incorporated herein by reference in their entirety, are non-limiting examples of such lateral flow test devices. Examples of patents that describe the use of "dip stick" technology to detect soluble antigens via immunochemical assays include but are not limited to US Patent Nos. 4,444,880; 4,305,924; and 4,135,884; which are incorporated by reference herein in their entireties. The apparatuses and methods of these three patents broadly describe a first component fixed to a solid surface on a "dip stick" which is exposed to a solution containing a soluble antigen that binds to the component fixed upon the "dip stick," prior to detection of the component-antigen complex upon the stick. It is within the skill of one in the art to modify the teachings of this "dip stick" technology for the detection of polypeptides using antibody reagents as described herein. Other techniques can be used to detect the level of a polypeptide in a sample. One such technique is the dot blot, an adaptation of Western blotting (Towbin et al., Proc. Nat. Acad. Sci.76:4350 (1979)). In a Western blot, the polypeptide or fragment thereof can be dissociated with detergents and heat and separated on an SDS-PAGE gel before being transferred to a solid support, such as a nitrocellulose or PVDF membrane. The membrane is incubated with an antibody reagent specific for the target polypeptide or a fragment thereof. The membrane is then washed to remove unbound proteins and proteins with non-specific binding. Detectably labeled enzyme-linked secondary or detection antibodies can then be used to detect and assess the amount of polypeptide in the sample tested. A dot blot immobilizes a protein sample on a defined region of a support, which is then probed with antibody and labelled secondary antibody as in Western blotting. The intensity of the signal from the detectable label in either format corresponds to the amount of enzyme present, and therefore the amount of polypeptide. Levels can be quantified, for example by densitometry. In some embodiments of any of the aspects, the level of a target can be measured, by way of non-limiting example, by Western blot; immunoprecipitation; enzyme-linked immunosorbent assay (ELISA); radioimmunological assay (RIA); sandwich assay; fluorescence in situ hybridization (FISH); immunohistological staining; radioimmunometric assay; immunofluoresence assay; mass spectroscopy and / or immunoelectrophoresis assay. In certain embodiments, the gene expression products as described herein can be instead determined by determining the level of messenger RNA (mRNA) expression of the genes described herein. Such molecules can be isolated, derived, or amplified from a biological sample, such as a blood sample. Techniques for the detection of mRNA expression is known by persons skilled in the art, and can include but not limited to, PCR procedures, RT-PCR, quantitative RT-PCR Northern blot analysis, differential gene expression, RNAse protection assay, microarray based analysis, next-generation sequencing; hybridization methods, etc. In general, the PCR procedure describes a method of gene amplification which is comprised of (i) sequence-specific hybridization of primers to specific genes or sequences within a nucleic acid sample or library, (ii) subsequent amplification involving multiple rounds of annealing, elongation, and denaturation using a thermostable DNA polymerase, and (iii) screening the PCR products for a band of the correct size. The primers used are oligonucleotides of sufficient length and appropriate sequence to provide initiation of polymerization, i.e., each primer is specifically designed to be complementary to a strand of the genomic locus to be amplified. In an alternative embodiment, mRNA level of gene expression products described herein can be determined by reverse-transcription (RT) PCR and by quantitative RT-PCR (QRT-PCR) or real-time PCR methods. Methods of RT-PCR and QRT-PCR are well known in the art. In some embodiments of any of the aspects, the level of an mRNA can be measured by a quantitative sequencing technology, e.g., a quantitative next-generation sequence technology. Methods of sequencing a nucleic acid sequence are well known in the art. Briefly, a sample obtained from a subject can be contacted with one or more primers which specifically hybridize to a single-strand nucleic acid sequence flanking the target gene sequence and a complementary strand is synthesized. In some next-generation technologies, an adaptor (double or single-stranded) is ligated to nucleic acid molecules in the sample and synthesis proceeds from the adaptor or adaptor compatible primers. In some third-generation technologies, the sequence can be determined, e.g., by determining the location and pattern of the hybridization of probes, or measuring one or more characteristics of a single molecule as it passes through a sensor (e.g., the modulation of an electrical field as a nucleic acid molecule passes through a nanopore). Exemplary methods of sequencing include, but are not limited to, Sanger sequencing, dideoxy chain termination, high-throughput sequencing, next generation sequencing, 454 sequencing, SOLiD sequencing, polony sequencing, Illumina sequencing, Ion Torrent sequencing, sequencing by hybridization, nanopore sequencing, Helioscope sequencing, single molecule real time sequencing, RNAP sequencing, and the like. Methods and protocols for performing these sequencing methods are known in the art, see, e.g. “Next Generation Genome Sequencing” Ed. Michal Janitz, Wiley-VCH; “High- Throughput Next Generation Sequencing” Eds. Kwon and Ricke, Humanna Press, 2011; and Sambrook et al., Molecular Cloning: A Laboratory Manual (4 ed.), Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., USA (2012); which are incorporated by reference herein in their entireties. The nucleic acid sequences of the genes described herein have been assigned NCBI accession numbers for different species such as human, mouse and rat. For example, the human SAA1 nucleotide sequence (e.g., SEQ ID NO: 2) is known. Accordingly, a skilled artisan can design an appropriate primer based on the known sequence for determining the mRNA level of the respective gene. Nucleic acid and ribonucleic acid (RNA) molecules can be isolated from a particular biological sample using any of a number of procedures, which are well-known in the art, the particular isolation procedure chosen being appropriate for the particular biological sample. For example, freeze-thaw and alkaline lysis procedures can be useful for obtaining nucleic acid molecules from solid materials; heat and alkaline lysis procedures can be useful for obtaining nucleic acid molecules from urine; and proteinase K extraction can be used to obtain nucleic acid from blood (Roiff, A et al. PCR: Clinical Diagnostics and Research, Springer (1994)). In some embodiments of any of the aspects, one or more of the reagents (e.g., an antibody reagent and / or nucleic acid probe) described herein can comprise a detectable label and / or comprise the ability to generate a detectable signal (e.g. by catalyzing reaction converting a compound to a detectable product). Detectable labels can comprise, for example, a light-absorbing dye, a fluorescent dye, or a radioactive label. Detectable labels, methods of detecting them, and methods of incorporating them into reagents (e.g. antibodies and nucleic acid probes) are well known in the art. In some embodiments of any of the aspects, detectable labels can include labels that can be detected by spectroscopic, photochemical, biochemical, immunochemical, electromagnetic, radiochemical, or chemical means, such as fluorescence, chemifluoresence, or chemiluminescence, or any other appropriate means. The detectable labels used in the methods described herein can be primary labels (where the label comprises a moiety that is directly detectable or that produces a directly detectable moiety) or secondary labels (where the detectable label binds to another moiety to produce a detectable signal, e.g., as is common in immunological labeling using secondary and tertiary antibodies). The detectable label can be linked by covalent or non-covalent means to the reagent. Alternatively, a detectable label can be linked such as by directly labeling a molecule that achieves binding to the reagent via a ligand- receptor binding pair arrangement or other such specific recognition molecules. Detectable labels can include, but are not limited to radioisotopes, bioluminescent compounds, chromophores, antibodies, chemiluminescent compounds, fluorescent compounds, metal chelates, and enzymes. In other embodiments, the detection reagent is label with a fluorescent compound. When the fluorescently labeled reagent is exposed to light of the proper wavelength, its presence can then be detected due to fluorescence. In some embodiments of any of the aspects, a detectable label can be a fluorescent dye molecule, or fluorophore including, but not limited to fluorescein, phycoerythrin, phycocyanin, o-phthaldehyde, fluorescamine, Cy3TM, Cy5TM, allophycocyanine, Texas Red, peridenin chlorophyll, cyanine, tandem conjugates such as phycoerythrin-Cy5TM, green fluorescent protein, rhodamine, fluorescein isothiocyanate (FITC) and Oregon GreenTM, rhodamine and derivatives (e.g., Texas red and tetrarhodimine isothiocynate (TRITC)), biotin, phycoerythrin, AMCA, CyDyesTM, 6-carboxyfhiorescein (commonly known by the abbreviations FAM and F), 6-carboxy-2',4',7',4,7-hexachlorofiuorescein (HEX), 6- carboxy-4',5'-dichloro-2',7'-dimethoxyfiuorescein (JOE or J), N,N,N',N'-tetramethyl-6- carboxyrhodamine (TAMRA or T), 6-carboxy-X-rhodamine (ROX or R), 5- carboxyrhodamine-6G (R6G5 or G5), 6-carboxyrhodamine-6G (R6G6 or G6), and rhodamine 110; cyanine dyes, e.g. Cy3, Cy5 and Cy7 dyes; coumarins, e.g umbelliferone; benzimide dyes, e.g. Hoechst 33258; phenanthridine dyes, e.g. Texas Red; ethidium dyes; acridine dyes; carbazole dyes; phenoxazine dyes; porphyrin dyes; polymethine dyes, e.g. cyanine dyes such as Cy3, Cy5, etc.; BODIPY dyes and quinoline dyes. In some embodiments of any of the aspects, a detectable label can be a radiolabel including, but not limited to3H,125I,35S,14C,32P, and33P. In some embodiments of any of the aspects, a detectable label can be an enzyme including, but not limited to horseradish peroxidase and alkaline phosphatase. An enzymatic label can produce, for example, a chemiluminescent signal, a color signal, or a fluorescent signal. Enzymes contemplated for use to detectably label an antibody reagent include, but are not limited to, malate dehydrogenase, staphylococcal nuclease, delta-V-steroid isomerase, yeast alcohol dehydrogenase, alpha-glycerophosphate dehydrogenase, triose phosphate isomerase, horseradish peroxidase, alkaline phosphatase, asparaginase, glucose oxidase, beta-galactosidase, ribonuclease, urease, catalase, glucose-VI-phosphate dehydrogenase, glucoamylase and acetylcholinesterase. In some embodiments of any of the aspects, a detectable label is a chemiluminescent label, including, but not limited to lucigenin, luminol, luciferin, isoluminol, theromatic acridinium ester, imidazole, acridinium salt and oxalate ester. In some embodiments of any of the aspects, a detectable label can be a spectral colorimetric label including, but not limited to colloidal gold or colored glass or plastic (e.g., polystyrene, polypropylene, and latex) beads. In some embodiments of any of the aspects, detection reagents can also be labeled with a detectable tag, such as c-Myc, HA, VSV-G, HSV, FLAG, V5, HIS, or biotin. Other detection systems can also be used, for example, a biotin-streptavidin system. In this system, the antibodies immunoreactive (i.e., specific for) with the biomarker of interest is biotinylated. Quantity of biotinylated antibody bound to the biomarker is determined using a streptavidin-peroxidase conjugate and a chromagenic substrate. Such streptavidin peroxidase detection kits are commercially available, e.g., from DAKO; Carpinteria, CA. A reagent can also be detectably labeled using fluorescence emitting metals such as152Eu, or others of the lanthanide series. These metals can be attached to the reagent using such metal chelating groups as diethylenetriaminepentaacetic acid (DTPA) or ethylenediaminetetraacetic acid (EDTA). A level which is less than a reference level or threshold level can be a level which is less by at least about 10%, at least about 20%, at least about 50%, at least about 60%, at least about 80%, at least about 90%, or less relative to the reference level. In some embodiments of any of the aspects, a level which is less than a reference level can be a level which is statistically significantly less than the reference level. A level which is more than a reference level or threshold level can be a level which is greater by at least about 10%, at least about 20%, at least about 50%, at least about 60%, at least about 80%, at least about 90%, at least about 100%, at least about 200%, at least about 300%, at least about 500% or more than the reference level. In some embodiments of any of the aspects, a level which is more than a reference level can be a level which is statistically significantly greater than the reference level. In some embodiments of any of the aspects, the reference level can be a level of the target molecule in a population of subjects who do not have or are not diagnosed as having, and / or do not exhibit signs or symptoms of infection, inflammation or diseases associated with these symptoms. In some embodiments of any of the aspects, the reference level can also be a level of expression of the target molecule in a control sample, a pooled sample of control individuals or a numeric value or range of values based on the same. In some embodiments of any of the aspects, the reference level can be the level of a target molecule in a sample obtained from the same subject at an earlier point in time, e.g., the methods described herein can be used to determine if a subject’s sensitivity or response to a given therapy is changing over time. In some embodiments of any of the aspects, the level of expression products of no more than 200 other genes is determined. In some embodiments of any of the aspects, the level of expression products of no more than 100 other genes is determined. In some embodiments of any of the aspects, the level of expression products of no more than 20 other genes is determined. In some embodiments of any of the aspects, the level of expression products of no more than 10 other genes is determined. In some embodiments of the foregoing aspects, the expression level of a given gene or protein can be normalized relative to the expression level of one or more reference genes or reference proteins. In some embodiments, the reference level can be the level in a sample of similar cell type, sample type, sample processing, and / or obtained from a subject of similar age, sex and other demographic parameters as the sample / subject for which the level of SAA1 and / or SAA2 is to be determined. In some embodiments, the test sample and control reference sample are of the same type, that is, obtained from the same biological source, and comprising the same composition, e.g., the same number and type of cells. The term “sample” or “test sample” as used herein denotes a sample taken or isolated from a biological organism, e.g., a blood or plasma sample from a subject. In some embodiments of any of the aspects, the present invention encompasses several examples of a biological sample. In some embodiments of any of the aspects, the biological sample is cells, or tissue, or peripheral blood, or bodily fluid. Exemplary biological samples include, but are not limited to, a biopsy, a tumor sample, biofluid sample; blood; serum; plasma; urine (and urine derivatives); sperm; mucus; tissue biopsy; organ biopsy; synovial fluid; bile fluid; cerebrospinal fluid; mucosal secretion; effusion; sweat; saliva; and / or tissue sample etc. The term also includes a mixture of the above-mentioned samples. The term “test sample” also includes untreated or pretreated (or pre-processed) biological samples. In some embodiments of any of the aspects, a test sample can comprise cells from a subject. In some embodiments of any of the aspects, the test sample can be whole blood, venous blood, arterial blood, capillary blood, serum, buffy coat (white blood cells and platelets), plasma from processed blood tubes (EDTA, K2 EDTA, sodium or lithium heparin, sodium citrate, potassium oxalate). The test sample can be obtained by removing a sample from a subject but can also be accomplished by using a previously isolated sample (e.g., isolated at a prior timepoint and isolated by the same or another person). In some embodiments of any of the aspects, the test sample can be an untreated test sample. As used herein, the phrase “untreated test sample” refers to a test sample that has not had any prior sample pre-treatment except for dilution and / or suspension in a solution. Exemplary methods for treating a test sample include, but are not limited to, centrifugation, filtration, sonication, homogenization, heating, freezing, and thawing, and combinations thereof. In some embodiments of any of the aspects, the test sample can be a frozen test sample, e.g., a frozen tissue. The frozen sample can be thawed before employing methods, assays and systems described herein. After thawing, a frozen sample can be centrifuged before being subjected to methods, assays and systems described herein. In some embodiments of any of the aspects, the test sample is a clarified test sample, for example, by centrifugation and collection of a supernatant comprising the clarified test sample. In some embodiments of any of the aspects, a test sample can be a pre-processed test sample, for example, supernatant or filtrate resulting from a treatment selected from the group consisting of centrifugation, filtration, thawing, purification, and any combinations thereof. In some embodiments of any of the aspects, the test sample can be treated with a chemical and / or biological reagent. Chemical and / or biological reagents can be employed to protect and / or maintain the stability of the sample, including biomolecules (e.g., nucleic acid and protein) therein, during processing. One exemplary reagent is a protease inhibitor, which is generally used to protect or maintain the stability of protein during processing. The skilled artisan is aware of methods and processes appropriate for pre-processing of biological samples required for determination of the level of an expression product as described herein. In some embodiments of any of the aspects, the methods, assays, and systems described herein can further comprise a step of obtaining or having obtained a test sample from a subject. In some embodiments of any of the aspects, the subject can be a human subject. In some embodiments of any of the aspects, the subject can be a subject in need of treatment for (e.g., having or diagnosed as having an infection, a non- infectious disease, an inflammatory disease) an infection, a non-infectious disease, an inflammatory disease or a subject at risk of or at increased risk of developing an infection, a non-infectious disease, an inflammatory disease as described elsewhere herein. In some embodiments of any of the aspects, the sample obtained from a subject can be a biopsy sample. In some embodiments of any of the aspects, the sample obtained from a subject can be a blood or serum sample. Sequences SEQ ID NO: 1, human SAA1 (GenBank: CAG47037.1) MKLLTGLVFCSLVLGVSSRSFFSFLGEAFDGARDMWRAYSDMREANYIGSDKYFHARGNYDAAKRGPGGV WAAEAISDARENIQRFFGHGAEDSLADQAANEWGRSGKDPNHFRPAGLPEKY SEQ ID NO: 2, human SAA1 (GenBank: CR542241.1) ATGAAGCTTCTCACGGGCCTGGTTTTCTGCTCCTTGGTCCTGGGTGTCAGCAGCCGAAGCTTCTTTTCGT TCCTTGGCGAGGCTTTTGATGGGGCTCGGGACATGTGGAGAGCCTACTCTGACATGAGAGAAGCCAATTA CATCGGCTCAGACAAATACTTCCATGCTCGGGGGAACTATGATGCTGCCAAAAGGGGACCTGGGGGTGCC TGGGCTGCAGAAGTGATCAGCGATGCCAGAGAGAATATCCAGAGATTCTTTGGCCATGGTGCGGAGGACT CGCTGGCTGATCAGGCTGCCAATGAATGGGGCAGGAGTGGCAAAGACCCCAATCACTTCCGACCTGCTGG CCTGCCTGAGAAATAC SEQ ID NO: 3, human SAA2 (NCBI Reference Sequence: NP_001372595.1) MKLLTGLVFCSLVLSVSSRSFFSFLGEAFDGARDMWRAYSDMREANYIGSDKYFHARGNYDAAKRGPGGA WAAEVISNARENIQRLTGRGAEDSLADQAANKWGRSGRDPNHFRPAGLPEKY SEQ ID NO: 4, human SAA2 (NCBI Reference Sequence: NM_030754.5) ACTATAAATAGCAGCCACCTCTCCCTGGCAGACAGGGACCCGCAGCTCAGCTACAGCACAGATCAGCACC ATGAAGCTTCTCACGGGCCTGGTTTTCTGCTCCTTGGTCCTGAGTGTCAGCAGCCGAAGCTTCTTTTCGT TCCTTGGCGAGGCTTTTGATGGGGCTCGGGACATGTGGAGAGCCTACTCTGACATGAGAGAAGCCAATTA CATCGGCTCAGACAAATACTTCCATGCTCGGGGGAACTATGATGCTGCCAAAAGGGGACCTGGGGGTGCC TGGGCTGCAGAAGTGATCAGCAATGCCAGAGAGAATATCCAGAGACTCACAGGCCGTGGTGCGGAGGACT CGCTGGCCGATCAGGCTGCCAATAAATGGGGCAGGAGTGGCAGAGACCCCAATCACTTCCGACCTGCTGG CCTGCCTGAGAAATACTGAGCTTCCTCTTCACTCTGCTCTCAGGAGACCTGGCTATGAGGCCCTCGGGGC AGGGATACAAAGTTAGTGAGGTCTATGTCCAGAGAAGCTGAGATATGGCATATAATAGGCATCTAATAAA TGCTTAAGAGGTGGAA SEQ ID NO: 5, human SAA3 (GenBank: BAQ56008.1) MKLLTGLVFCSLVLSVSSRSFFSFLGEAFDGARDMWRAYSDMREANYIGSDKYFHARGNYDAAKRGPGGA WAAEVISRMKLSTGIIFCSLVLGVSSQGWLTFLKAAGQGTKDMWKAYSDMKEANYKKFRQILPCLGEL SEQ ID NO: 6, human SAA3 (GenBank: S73444.1) CCACCTTTTCCAATGAATGGAAGTTGTGTAGGGAATATTCAAATGTTGCTTAGCATTGCCTTAGATAAGA ACCAAAGGGACAGGGAAATCCTCTGACAGCTATCTGCCTTATAACTTTCATTTTACTGTGCCTAAAATAT GCTCAGAACCCAGAAAGAGGCATAATTCCTAATTTTGGCAGGCTCTAATCTAAAATAATGATTCTCAAAC ATGGTGTGACTTTTGTCTATTTTGCTTTATCCTGGGTCACTGCTCCTCTTCTGTCAGATACTGGGATTCC AATGAGACAAAATGGAAATGAGACGTAGACCCTCTGACCTTCTATCTTTATCTATCACATACACATGTGT GTGTGTGTGTGTGTGTGTGCGTGTGTAAAACCGAGTGGGTTTTTTTCTTGGAATGAAAGAATGGACTAAC ATTACAAAAAATAAAAACTTGAAACAGAATGTGTATTATCCTTGGTTGTGTTTCCTTGGCCCTGCAGCAG GATGAAGCTCTCCACTGGCATCATTTTCTGCTCCCTGGTCCTGGGTGTCAGCAGCCAAGGATGGTTAACA TTCCTCAAGGCAGCTGGCCAAGGTGAGGTCCACAGGATAGGGGGCAGGAGGCTGCTTCTGGCTGCCCCCA GGATGCAGCTGAGCAGAGGCCACATCCCCCACTGGGCAAAGGTGCTAGTGATGCCACAGATGGATAGAGA AGGGGAAGCTTTCTTAGGTAACTCACCTTTATCACTTGCTGACTGAATTCTGACAGATGTCAGTTTCTAA TTATAGCCTGGACATTCAGATGTATTCAGGACCAAGTTGTCCTCACTCTACCTACAGGCATGAATTTCTC TCATTGACTAGGTTAGGAGCGCCATATGTCTGCAGCCTCCCTCAGAATCCCCTGTGTTCTCACACAGGAA CTGAGGGTTCCCTGGGTCTTCCAGGTAGAAGTTCATTGTACAATGAAACATCCCTTAAGGACCATTTCAT CTCTTCTTTAGGTGCATCACACATGGTTAAAACAAAGTAATAACAGAACTTAGAATGGAATCAAACAGAA TGAAACTTACACCAAGTACAATTCTCATTACATTAACCCAGAGAAGTGAAAAGTAGAAGAATATTTATTT CAAGCCAATATAATTTCCAAGGGCTTTGTTGAAGGCTGAAATCTTCGGGAGGAAAGTAGTGAGAAGAAAA CTGTTCATTCCTCTATTTCCAGTATATAATTGTTTTGATCATTTTCTTTCCTTTCCAGGGACTAAAGACA TGTGGAAAGCCTACTCTGACATGAAAGAAGCCAATTACAAAAAATTCAGACAAATACTTCCATGCTTGGG GGAACTATGATGCTGTACAAAGGGGGCTTGGGGCTGTCTGGGCTACAGAAGTGATCAGGTAATGCACATT CCTGATGTTGCCAGGAATGAGTGAGCAGAGCTTGACTGCCTTGGACAGTCAGGAGAGAGGTAAGCTCCTT GCAGAGAAGTTAGAGGCTGCAGCCCCTCCTCCTCTTGCCCTCTCTCTGCCTGTGTGCTTAGTGCGAGGGT CTGAGTGGATGGTAGAAGTGAGTGATTCCTCACCCTCCCTCTCTGGGTGCTGTTCATCCAGCCTAGGGGT GCCCAGCCTGGCTGAGTGGGGCAGTGCCAGGCAGGGTCATTGTTTTCACCCCTCCTTCCTTGGCCTTCCT GGGCTTCTCCCAGAGTCCTCCCTTGGAAAGCAGAGAATGGGAAGGTGGGCTGTTGCTCACTGGCCTGGTG ATTAATCTCCTTGCTTGCCTGGACTACAGCGATGCCAGAGAGAACGTCCAGAGACTCACAGGAGACCATG CAGAGGATTCGCTGGCTGGCCAGGCTACCAACAAATGGGGCCAGAGTGGCAAAGACCCCAATCACTTCCG ACCTGCTGGCCTGCCAGAGAAATACTGAGCTTCCTTTTCAATCTGCTCTCAGGAGACCTGGCTGTGAGCC CCTGAGGGCAGGGACATTTGTTGACCTACAGTTACTGAATTCTATATCCCTAGTACTTGATATAGAACAC ATAAAAATGCTTAATAAA SEQ ID NO: 7, human SAA4 ( MRLFTGIVFCSLVMGVTSESWRSFFKEALQGVGDMGRAYWDIMISNHQNSNRYLYARGNYDAAQRGPGGV WAAKLISRSRVYLQGLIDCYLFGNSSTVLEDSKSNEKAEEWGRSGKDPDRFRPDGLPKKY SEQ ID NO: 8, human SAA4 (NCBI Reference Sequence: NM_006512.4) AGCAGAGGTACCAACTATAGCTCCACGGCCAGAAGATACCAGCAGCTCTGCCTTTACTGAAATTTCATCT GGAGAAAGGTCCACAGCACAATGAGGCTTTTCACAGGCATTGTTTTCTGCTCCTTGGTCATGGGAGTCAC CAGTGAAAGCTGGCGTTCGTTTTTCAAGGAGGCTCTCCAAGGGGTTGGGGACATGGGCAGAGCCTATTGG GACATAATGATATCCAATCACCAAAATTCAAACAGATATCTCTATGCTCGGGGAAACTATGATGCTGCCC AAAGAGGACCTGGGGGTGTCTGGGCTGCTAAACTCATCAGCCGTTCCAGGGTCTATCTTCAGGGATTAAT AGACTGCTATTTATTTGGAAACAGCAGCACTGTATTGGAGGACTCGAAGTCCAACGAGAAAGCTGAGGAA TGGGGCCGGAGTGGCAAAGACCCCGACCGCTTCAGACCTGACGGCCTGCCTAAGAAATACTGAGCTTCCT GCTCCTCTGCTCTCAGGGAAACTGGGCTGTGAGCCACACACTTCTCCCCCCAGACAGGGACACAGGGTCA CTGAGCTTTGTGTCCCCAGGAACTGGTATAGGGCACCTAGAGGTGTTCAATAAATGTTTGTCAAATTGAA Brief Description of the Drawings The invention will be more clearly understood from the following description of an embodiment thereof, given by way of example only, with reference to the accompanying drawings, in which:- Figure 1 depicts an SAA1-specific (or an SAA2-specific) lateral flow test strip capable of detecting SAA1 in human samples. Figure 2 depicts a lateral flow test strip that can detect both SAA1 and SAA2 by means of a dual conjugate and dual test line system. It is also representative of a lateral flow test strip that can detect both SAA1 and SAA2 by using an A-SAA conjugate paired with dual test lines- one specific to SAA1-specific and the other specific to SAA2; and it is also representative of a lateral flow test strip that can detect both SAA1 and SAA2 by using an A-SAA conjugate paired with dual test lines – one specific to A-SAA and the other specific to SAA1 or SAA2, where SAA1 and SAA2 levels are determined by subtracting SAA1 or SAA2 from total A-SAA. Figure 3 is a decision tree and clinical protocol for categorizing patient health- status based on SAA isoform levels ( SAA1 and SAA2). Figure 4 is a Receiver Operating Characteristic (ROC) curve for diagnostic accuracy of SAA1 and SAA2 metrics in differentiating infection from inflammation. Figure 5 is a ROC Curve for diagnostic accuracy of combining SAA1 and SAA2 in differentiating infection from inflammation. Detailed Description of the Drawings Materials and Methods The diagnostic test can be carried out on a lateral flow test strip of the claimed invention and is configured such that the analyte is SAA1 or SAA2 and where the conjugate pad is impregnated with colloidal gold bound to SAA1-specific or SAA2-specific antibodies, where the test line is made up of an SAA1-specific antibody or an SAA2-specific antibody, and where the control line is made up of anti-mouse antibody. Another configuration for the lateral flow test strip of the claimed invention is where the analyte is SAA1 and / or SAA2, where the conjugate pad is impregnated with two types of colloidal gold: one bound to SAA1-specific antibodies and the other bound to SAA2- specific antibodies, where test line 1 is made up SAA1-specific antibody, where test line 2 is made up of SAA2-specific antibody (or vice versa), and where the control line is made up of anti-mouse antibody. A further configuration for the lateral flow test strip of the claimed invention is where analyte is SAA1 and / or SAA2, where the conjugate pad is impregnated with colloidal gold bound to A-SAA antibody (pan-specific to SAA1 and SAA2), where test line 1 is made up SAA1-specific antibody, where test line 2 is made up of SAA2-specific antibody (or vice versa), and where the control line is made up of anti-mouse antibody. A further configuration for the lateral flow test strip of the claimed invention is where the analyte is SAA1 and / or SAA2, where the conjugate pad is impregnated with colloidal gold bound to A-SAA antibody (pan-specific to SAA1 and SAA2), where test line 1 is made up A-SAA antibody, where test line 2 is made up of SAA1-specific or SAA2-specific antibody (or vice versa), and where the control line is made up of anti-mouse antibody. Another configuration for the lateral flow test strip of the claimed invention is where the analyte is SAA1 and / or SAA2, where the conjugate pad is impregnated colloidal gold- bound to A-SAA, where test line 1 is made up SAA2-specific antibody, and where the control line is made up of anti-mouse antibody. A further configuration for the lateral flow test strip of the claimed invention is where the analyte is SAA1 and / or SAA2, where the conjugate pad is impregnated with colloidal gold bound to biotinylated A-SAA antibody (pan-specific to SAA1 and SAA2), and also impregnated with an unlabelled biotinylated SAA2 specific antibody, where the test line is polystreptavidin, and where the control line is made up of anti-mouse antibody. A further configuration for the lateral flow test strip of the claimed invention is where the analyte is SAA1 and / or SAA2, where the conjugate pad is impregnated with cellulose nanobeads (CNB) bound to a labelled A-SAA antibody (pan-specific for SAA1 and SAA2), and also impregnated with an unlabelled biotinylated SAA2-specific antibody, and where the test line is polystreptavidin and where the control line is made up of anti- mouse antibody. The conjugate may also be colloidal gold, latex particles, coloured polymers, carbon nanoparticles, fluorescent particles, silver nanoparticles. Alternatives to polystreptavidin include avidin and neutravidin. Examples EXAMPLE 1: STUDY ON PERFORMANCE PARAMETERS TO DIFFERENTIATE HEALTHY PATIENTS USING SAA1 AND SAA2 ISOFORMS The Applicants undertook a study using an immunoassay format to measure the SAA isoforms SAA1 and SAA2 to establish performance parameters to distinguish between healthy and non-infectious inflammatory conditions. Accurately differentiating between healthy and non-healthy patients, particularly those with non-infectious inflammation, is critical in clinical diagnostics. Traditional markers often lack the specificity required to make clear distinctions, leading to potential misdiagnosis or unnecessary treatments. Measuring SAA isoforms SAA1and SAA2 offer a promising solution. Methods The study included samples from clinically healthy individuals and patients presenting with non-infectious inflammation (n=60). Samples were assessed, and levels of SAA1 and SAA2 were measured using immunoassays. Statistical analyses were performed to evaluate the specificity and sensitivity of each marker in distinguishing healthy individuals from those with inflammation and infection. Results SAA1 levels were significantly elevated in patients with non-infectious inflammation compared to healthy individuals. High levels of SAA1 effectively ruled out healthy cases, indicating superior specificity as an inflammation marker. Conversely, while SAA2 levels were also elevated in patients with inflammation, they showed a stronger association with infection once inflammation was established (see Example 2 below). Table 3: Diagnostic performance metrics of SAA1 and SAA2 when differentiating healthy patients from patients with inflammation. SAA1 SAA2 Cut-off (ug / ml) >5.9 >3.4 Sensitivity (%) 53.3 46.7 Specificity (%) 93.33 76.7 The study found that SAA1 is a more specific marker for inflammation, effectively ruling out healthy cases, while SAA2 is preferentially associated with infection once inflammation is confirmed. These findings suggest that SAA1 and SAA2 can be used individually and in tandem to improve diagnostic accuracy, presenting a significant advancement in clinical practices. In a clinical context, where patients presenting for a clinical assessment are generally experiencing some symptoms, confirmatory testing (specificity) is preferred to general screening (sensitivity). A highly specific test helps ensure accuracy by confirming that the symptoms are associated with an inflammation and that any treatments prescribed are truly necessary. In the current testing landscape, CRP is a commonly used marker for inflammation which has reportedly high sensitivity. While useful for detecting a wide range of inflammatory conditions, its specificity is widely reported as moderate and it can produce false positives indicating a need for a specific test. The preferential association of SAA1 with non-infectious inflammation highlights a useful role in clinical diagnostics. The high specificity of SAA1 in identifying inflammation presents an advancement over current practices that rely on less specific markers, which can lead to diagnostic ambiguities. By utilizing SAA1 clinicians can more accurately determine the presence of inflammation and subsequently identify infections, improving patient outcomes through targeted treatments. EXAMPLE 2: STUDY ON DIAGNOSTIC EFFICACY OF SAA2 AND CRP IN DIFFERENTIATING INFLAMMATION FROM INFECTION Biomarkers are essential tools in diagnosing and differentiating various medical conditions. This study examines the efficacy of two biomarkers, SAA2 and CRP, in diagnosing and differentiating between inflammation and infection. Previous research has established that SAA1 is a highly specific marker for inflammation, making it suitable for distinguishing inflammation from healthy patients. This study validates the higher specificity of SAA2 for differentiating inflammation from infectious conditions, highlighting its potential to rule out inflammation and thereby aid in diagnosing infections. CRP, traditionally considered the gold standard for diagnosing both inflammation and infection, was found to have lower sensitivity and specificity compared to SAA2. Materials and Methods This study involved biobanked patient samples (n=65) diagnosed with either inflammation or infection. Inclusion criteria included confirmed diagnoses of non- infectious inflammation or infection-related conditions based on clinical assessments and existing diagnostic criteria contained with the patient sample notes. SAA2 Measurement SAA2 levels were measured using ELISA (for example, as supplied by Aviva Biology Systems, CA, USA; LSBio, MA, USA; Elabscience, TX, USA; Abbexa, Cambridge, USA; and Biomatik, Ontario, Canada). CRP Measurement CRP levels were measured using a commercially available immunoassay kit Quikread go®, following the standard protocol provided by the manufacturer (Aidian Oy, Estonia). Data Analysis Data was analyzed using MedCalc™ software (MedCalc Software Ltd.). Key measures included sensitivity and specificity and area under the curve (AUC). Results This study aims to establish performance parameters to distinguish between patients with non-infectious inflammation and those with infection by comparing levels of the isoform SAA2 to CRP levels, which is a conventional marker for infection (considered by many as a gold standard for confirming infection). The results demonstrated that SAA2 exhibited significantly higher specificity and sensitivity for differentiating inflammation from infection compared to CRP (see Table 4). SAA2 showed superior diagnostic performance with a higher AUC. CRP, while traditionally considered the gold standard, had lower sensitivity and specificity overall. Table 4: Diagnostic performance metrics of SAA2 compared to conventional marker CRP when differentiating non-infectious inflammation from infection. SAA2 CRP AUC 0.928 0.808 Cut-off (ug / ml) >13.8 >31.6 Sensitivity (%) 82.9 74.3 Specificity (%) 100 90 This study investigates the diagnostic efficacy of SAA2 and CRP in distinguishing between inflammation and infection. SAA2 demonstrated higher specificity and sensitivity in differentiating inflammation from infectious conditions compared to CRP. These findings suggest that SAA2 could enhance diagnostic accuracy and improve clinical outcomes. Despite CRP being the traditional gold standard, its lower sensitivity and specificity, and AUC compared to SAA2, underscore the need for integrating more reliable biomarkers like SAA2 into diagnostic protocols. The enhanced performance of SAA2 can lead to more accurate diagnoses, better patient stratification, and ultimately improved clinical outcomes. When differentiating between inflammation and infection, the choice between a highly sensitive or highly specific test depends on the clinical objectives. While sensitivity is important to ensure cases are not missed, high specificity is particularly valuable in symptomatic patients to avoid false positives, reduce unnecessary treatments, and improve overall patient care. By prioritizing specificity, clinicians can better differentiate between infection and inflammation, leading to more accurate diagnoses and better health outcomes. Reducing unnecessary interventions using a highly specific test helps avoid unnecessary follow-up tests, treatments, and the anxiety that might come from a false positive result. Symptomatic patients often present with overlapping symptoms for both infections and inflammation, adding to the complexity of accurate diagnosis. High specificity tests provide clearer diagnostic outcomes, aiding clinicians in making more informed decisions in these complex cases. Reducing diagnostic ambiguity is crucial for effective patient management. Sensitivity reflects a test's ability to correctly identify patients who do have the disease, thereby minimizing false negatives. However, in the clinical setting of distinguishing between infection and inflammation, the implications of false positives are particularly significant. Unnecessary antibiotic use resulting from misdiagnosing inflammation as an infection can have serious consequences. This not only contributes to the global challenge of antibiotic resistance but also exposes patients to unnecessary medication, leading to potential side effects and complications. Additionally, a false positive diagnosis for infection can cause undue stress for patients and may lead to further unnecessary diagnostic procedures and treatments. Prioritizing high specificity in symptomatic patients helps to avoid false positives, reduce unnecessary treatments, and improve overall patient care. By focusing on specificity, clinicians can better differentiate between infection and inflammation, leading to more accurate diagnoses and better health outcomes. The findings from this study highlight the superior performance of SAA2 as a diagnostic biomarker compared to CRP. SAA2’s higher specificity for differentiating inflammation from infection makes it an invaluable tool in clinical settings, where accurate diagnosis is crucial for effective patient management. The higher AUC of SAA2 indicates better diagnostic accuracy, which is essential for ruling out inflammation and confirming infection diagnoses. Accurate differentiation between inflammation and infection plays a crucial role in enhancing patient outcomes. By reducing the risk of complications arising from misdiagnosis, patients receive the correct treatment promptly, which is essential for effective disease management. Additionally, accurate diagnosis allows for optimized follow-up care. Patients correctly differentiated can be monitored and managed appropriately, thus improving their long-term health outcomes. EXAMPLE 3: ASSESSMENT OF SAA ISOFORMS FOR GENERAL SCREENING This study evaluates the effectiveness of SAA isoforms, specifically SAA1 and SAA2, in general health screening, and in particular to determine their efficacy in detecting non- healthy patients, including those with infection or inflammation. The study aimed to determine which isoform better identifies non-healthy patients, encompassing those with either infection or inflammation. In the context of general health screening, the primary objective is to identify individuals with potential health issues, ensuring early diagnosis and treatment. Sensitivity is a critical factor in this process. Materials and Methods This study involved the analysis of 95 biobanked patient samples, consisting of 30 healthy individuals and 65 non-healthy patients, selected based on comprehensive clinical notes associated with the samples. The healthy group was confirmed to be free of any signs of infection or inflammation, while the non-healthy group included patients diagnosed with either infection or inflammation. The selection criteria ensured that only well-documented cases were included. Levels of SAA1 and SAA2 were measured using ELISA immunoassays and statistical analyses were performed using MedCalc™ software to evaluate and compare the sensitivity, specificity, and Area Under the Curve (AUC) of the two isoforms as potential biomarkers for distinguishing between healthy and diseased states. Results The evaluation of SAA isoforms for general screening purposes yielded significant findings. The AUC for SAA1 was 0.907, indicating a high level of diagnostic accuracy (see Table 5). In contrast, the AUC for SAA2 was 0.815, suggesting lower diagnostic performance compared to SAA1. The cut-off values for the isoforms were set at >5 for SAA1 and >7 for SAA2. SAA1 demonstrated a sensitivity of 82.8%, effectively identifying the majority of non- healthy patients (see Table 5). This high sensitivity underscores SAA1's capability in capturing a wide range of disease states, which is critical for general screening where early detection is paramount and symptoms may not be present. In comparison, SAA2 exhibited a much lower sensitivity. This correlates with previous findings where SAA2 was more closely associated with differentiation of infection from inflammation. Specificity was also assessed, with SAA1 showing a specificity of 90%, indicating a relatively low rate of false positives. SAA2, on the other hand, achieved a perfect specificity of 100%, ensuring that all identified positive cases were indeed non-healthy, but at the cost of significantly lower sensitivity. These results highlight the superior performance of SAA1 in terms of sensitivity, making it a more suitable biomarker for general screening where the primary goal is to identify as many non-healthy individuals as possible. Table 5: Comparison of diagnostic performance metrics of SAA1 and SAA2 in general health screening SAA1 SAA2 AUC 0.907 0.815 Cut-off (ug / ml) >5 >7 Sensitivity (%) 82.8 48.4 Specificity (%) 90 100 The results of this study demonstrate that SAA1 has a higher sensitivity compared to SAA2 in detecting non-healthy patients. In the context of general screening, high sensitivity is crucial because it ensures that the majority of individuals with potential health issues are identified. This reduces the risk of false negatives, which could lead to the progression of undiagnosed conditions and subsequent health complications. By utilizing a highly sensitive biomarker like SAA1, healthcare providers can ensure early intervention, which is crucial for effective disease management and improving patient outcomes. Although specificity is important for reducing false positives, in a general screening scenario where there are not necessarily symptoms present, the priority is to capture as many cases as possible. This broad detection capability is particularly valuable in public health, where the aim is to monitor and control disease prevalence within a population. High sensitivity in screening helps in timely identification and management of diseases, thereby enhancing overall public health outcomes. The results indicate that SAA1 exhibits higher sensitivity compared to SAA2, making it a more suitable biomarker for general screening purposes. This study considers in screening protocols, highlighting the benefits of early detection and intervention. This study highlights the benefits of SAA1 as part of a screening protocol which would support early detection and intervention, in particular, when screening non-symptomatic patients. EXAMPLE 4 DECISION TREE AND CLINICAL PROTOCOL FOR CATEGORIZING PATIENT HEALTH STATUS BASED ON SAA ISOFORMS The applicants have developed a decision tree and clinical protocol for categorizing patient health-status based on SAA1 and SAA2 isoform levels (see Figure 3). 1. Patient Health Status: o Healthy: Characterized by low SAA1 levels (below a certain threshold, denoted as "1A"). o Inflammation: Characterized by high SAA1 levels (above the threshold "1A"). 2. Inflammation Further Classification (when SAA1 levels are high): o Infection: Indicated further by high SAA2 levels (above a second threshold level “2A”). 3. Infection Further Classification (When SAA1 levels and SAA2 levels are high): o Viral Infection: Indicated further by SAA2 levels between the second “2A” and a third threshold “2B”. o Bacterial Infection: Indicated further by SAA2 levels above the third threshold “2B”. Clinical Protocol for Categorizing Patient Health Status Using SAA Isoform Protein Levels This clinical protocol outlines the procedure for categorizing patient health status using SAA isoform protein levels, specifically focusing on SAA1 and SAA2. This protocol helps differentiate between healthy individuals, those with inflammation, and those with bacterial or viral infections. Objectives ^ To accurately categorize patient health status based on SAA1 and SAA2 levels. ^ To distinguish between inflammation and infection in patients with elevated SAA levels. ^ To further differentiate between bacterial and viral infections using specific cut- off criteria. 1. Patient Sample Assessment: ^ Measure SAA1 and SAA2 levels in the patient's blood sample. 2. Decision Tree for Health Status Categorization: 1. Healthy: o If SAA1 levels are below the first threshold "1A," categorize the patient as healthy. 2. Not Healthy: o If SAA1 levels are above the first threshold "1A", categorize the patient as unhealthy and proceed with further assessment. 3. Classification of Not Healthy Patients: o Inflammation: ^ Indicated by elevated SAA1 above the first threshold “1A”. o Infection: ^ Indicated by elevated SAA2 above the second threshold “2A”, categorise the patient as having an infection and proceed with further assessment. 4. Infection Classification: o Viral Infection: ^ If the SAA2 concentration falls within a specific range (the first threshold “2A” to a third threshold “2B”) categorize the patient as having a viral infection. o Bacterial Infection: ^ If the SAA2 concentration exceeds a defined third threshold (“2B”), categorize the patient as having a bacterial infection. 3. Interpretation of Results: ^ Review the patient's SAA1 and SAA2 levels ^ Refer to the decision tree to categorize the patient's health status accurately. 4. Documentation and Reporting: ^ Record the SAA1 and SAA2 levels and the final health status categorization in the patient's medical record. 5. Follow-up: ^ Patients categorized as "Not Healthy" should undergo further clinical evaluation and appropriate treatment based on the underlying cause ( inflammation, bacterial infection, or viral infection). Accurate differentiation between viral and bacterial infections is crucial in clinical practice for several reasons. Proper identification of the underlying cause of an infection not only guides the appropriate treatment plan but also helps in the fight against antibiotic resistance, improves patient outcomes, and optimizes healthcare resource utilization. One of the primary benefits of correctly identifying the type of infection is the ability to provide targeted treatment. Antibiotics, for instance, are effective against bacterial infections but not viral ones. Misuse of antibiotics for viral infections can lead to antibiotic resistance, a growing global health threat. By ensuring that antibiotics are prescribed only when necessary, we can preserve their effectiveness for future bacterial infections. In addition to antibiotic stewardship, accurate differentiation allows for the appropriate use of antiviral therapies. Certain viral infections can be treated with specific antiviral medications, which can significantly improve patient recovery times. Without proper identification, patients may miss out on these beneficial treatments, potentially prolonging illness and increasing the risk of complications. Moreover, understanding whether an infection is viral or bacterial can impact overall patient management and healthcare resource allocation. Viral infections may require different isolation protocols to prevent the spread within healthcare settings, while bacterial infections might necessitate more intensive monitoring and supportive care. The ability to distinguish between viral and bacterial infections is essential for providing effective, targeted treatment, preventing the misuse of antibiotics, and improving overall patient care. This protocol outlines a systematic approach using SAA isoform levels to aid in this critical differentiation. Case Study 1: A Diagnostic Algorithm for Differentiating Healthy, Inflammatory, Viral, and Bacterial Conditions This case study presents a novel diagnostic algorithm designed to sequentially rule out healthy individuals, identify inflammation, and differentiate between viral and bacterial infections using specific biomarker thresholds. Inclusion criteria were healthy individuals, patients with confirmed inflammatory conditions, and patients with confirmed viral and bacterial infections. The algorithm utilizes a three-step process involving serial biomarker measurements and thresholds. Methodology A cohort of biobanked patient samples, was included, including healthy individuals, patients with confirmed inflammatory conditions, and patients with confirmed viral and bacterial infections. The study involved the following steps: 1. Initial Measurement (Step 1): The first biomarker measurement aimed to rule out healthy individuals. 2. Second Measurement (Step 2): For those not ruled out as healthy, a second measurement was used to rule out inflammation. 3. Third Measurement (Step 3): For patients identified with infection, a third measurement applied specific thresholds to determine the probability of a viral infection (range A to B) or a bacterial infection (over B). Results The diagnostic algorithm with applied thresholds demonstrated the following outcomes: ^ Step 1: The initial measurement accurately ruled out healthy individuals in 93% of cases. ^ Step 2: Among those not ruled out as healthy, the second measurement accurately ruled out non-infectious inflammation in 100% of cases. ^ Step 3: For patients with confirmed infectious inflammation, the third measurement successfully differentiated between viral and bacterial infections using the predefined thresholds, achieving a 83% probability rate for bacterial infections when levels of SAA2 were over 260ug / ml. The thresholds used were with samples with SAA1 (eliminate healthy) and SAA2 (eliminate inflammation). A summary of the results are provide in Tables 6 below. Table 6: SAA2 Range between threshold “2A” and “2B” have High Probability of a Viral Infection and SAA2 Range above threshold “2B” have High Probability of a Bacterial Infection Isoform Isoform Condition Diagnostic Probability Clinical Levels Statistics Interpretation (ug / ml) <6 SAA1 Healthy 93% Healthy, no specificity inflammation or infection <13.8 SAA2 Inflammation 100% Non-infectious specificity inflammation 13.8- SAA2 Bacterial Infection –higher 260 65.8% Viral probability of viral or Viral >260 SAA2 Bacterial 82.8% Strongly suggests Infection Bacterial bacterial infection The algorithm's stepwise approach provides a robust framework for diagnosing infectious and inflammatory conditions. By sequentially ruling out healthy individuals and identifying inflammation, the algorithm minimizes the risk of false positives and ensures that only patients with potential infections undergo further testing. In the first step, the use of a specific biomarker effectively distinguished healthy individuals from those with any form of inflammation or infection, streamlining the diagnostic process. The second step focused on detecting inflammation, which is a common response to both infectious and non-infectious conditions. This step was crucial for ensuring that patients with underlying inflammatory diseases were appropriately identified. The third step applied precise thresholds to differentiate between viral and bacterial infections. This differentiation is vital for guiding treatment decisions, particularly the use of antibiotics. The algorithm's ability to assign a probability range for viral infections (for example, 18-260ug / ml) and identify bacterial infections (for example, >260ug / ml)) allows for nuanced clinical decisions, reducing the likelihood of unnecessary antibiotic use. EXAMPLE 5: MONITORING TREATMENT CASE STUDIES:A SERIES OF CASE STUDIES WERE UNDERTAKEN TO DETERMINE THE CLINICAL UTILITY OF SAA2 IN MONITORING RESPONSE TO TREATMENT Case Study 1: SAA2 Measurements and Survivability in Sepsis Patients Sepsis is a life-threatening condition triggered by an infection, leading to systemic inflammation and potential organ failure. Timely and accurate biomarkers are critical for predicting patient outcomes and guiding treatment decisions in the intensive care unit (ICU). SAA2 is an acute-phase protein that responds rapidly to inflammation, making it a potential candidate for monitoring sepsis progression and patient prognosis. The objective of this case study was to evaluate the prognostic value of SAA2 levels in predicting the survivability of sepsis patients in an ICU setting. Methodology Eleven patients diagnosed with sepsis and admitted to the ICU were included in this study. Serial measurements of SAA2 concentrations were taken to monitor changes over time. Specifically, the study aimed to identify whether a decrease in SAA2 levels within a critical time window could predict short-term survival. ^ Inclusion Criteria: Patients diagnosed with sepsis and admitted to the ICU. ^ Measurement Intervals: SAA2 levels were measured at multiple time points, with a focus on identifying peak levels and subsequent changes in concentration. ^ Outcome Assessment: Patient survivability within 2 days following the peak SAA2 measurement was recorded. Results The study found a significant correlation between the change in SAA2 levels and patient outcomes: ^ Peak Measurement: All 11 patients reached a peak SAA2 concentration. ^ Critical Decline: For patients whose SAA2 levels dropped by at least 10% within 6 hours of reaching the peak, the survivability rate within the next 2 days was 100%. ^ Non-responders: Patients whose SAA2 levels did not show at least a 10% decline within 6 hours had varied outcomes, with a lower overall survival rate. Table 7: Changes in SAA2 levels associated with survival duration Sample SAA2 Peak SAA2 Drop % in x Min. Hours ID (ug / ml) (ug / ml) Drop hours survived 1 419.5 293.5 0.7 24.0 73.5 2 174.9 152.4 0.9 27.0 47.0 3 215.9 133.0 0.6 48.0 240.0 4 1392.0 1109.9 0.8 20.0 76.0 5 370.3 276.0 0.7 6.0 42.5 6 610.2 52.0 0.1 24.0 72.0 7 568.0 510.5 0.9 6.0 144.0 8 1732.5 1058.9 0.6 16.0 144.0 9 1353.4 1164.6 0.9 92.0 203.0 10 1223.1 119.0 0.1 44.5 60.0 11 941.2 337.9 0.4 46.0 62.0 The findings suggest that a rapid decrease in SAA2 levels following the peak concentration is a strong predictor of short-term survival in sepsis patients. This 10% decline within 6 hours could serve as a critical marker for clinicians to identify patients with a better prognosis and potentially adjust treatment strategies for those not exhibiting this pattern. Case Study 2: Monitoring Response to Infection Treatment Using SAA2 Accurate and timely monitoring of response to treatment in sepsis patients is crucial for improving outcomes. This case study investigates the efficacy of two biomarkers, SAA2 and CRP, in monitoring the response to antibiotic treatment in an ICU setting. Methodology Three patients diagnosed with sepsis and confirmed infections were included in this study. All patients were undergoing antibiotic treatment in the ICU. Serial measurements of SAA2 and CRP biomarkers were taken to assess their levels over time. ^ Inclusion Criteria: Patients with confirmed infection and receiving antibiotic treatment in the ICU. ^ Measurement Intervals: Both SAA2 and CRP levels were measured at regular intervals. ^ Outcome Assessment: The time to peak concentration for both biomarkers was determined and analysed. Results The study revealed distinct differences in the response times of the two biomarkers: ^ SAA2 Biomarker: o Reached peak levels within 10 to 48 hours in all patients. o Provided an earlier indication of response to treatment, with the earliest peak observed at 10 hours. ^ CRP Biomarker: o Reached peak levels between 19 and 48 hours. o Indicated response to treatment later than SAA2 in all cases. Table 8: Time to peak levels for SAA and CRP in patients with infection after ICU admission Peak SAA2 (ug / ml) Peak CRP (ug / ml) Peak SAA2 Hours After ICU Peak CRP Hours After ICU Sample ID Level Admission of Peak Levels Admission of Peak 1 419.5 20 35.0 92 2 159.7 48 50.0 96 3 1392.0 22 113.0 42 4 568.0 24 114.0 0 5 941.2 19 136.0 19 The findings demonstrate that SAA2 is a superior biomarker compared to CRP for monitoring response to treatment in patients with infection. SAA2 consistently reached peak levels faster than CRP, with the earliest peaks observed within 10 hours. This rapid response allows for quicker assessment of treatment effectiveness, enabling timely adjustments to the therapeutic regimen if needed. The ability to detect peak levels as early as 10 hours post-treatment initiation provides a significant advantage in critical care settings, where early intervention is crucial for patient survival. SAA2 showed a more consistent time-frame to peak levels (10-48 hours) across all patients compared to the broader range observed with CRP (19-48 hours). Using SAA2 as a biomarker can lead to more proactive and responsive patient management, reducing the time to recognize the effectiveness of antibiotic therapy. Early detection of treatment response or failure can enhance decision-making processes, potentially leading to better patient outcomes and reduced ICU stays. Case Study 3: Efficacy of SAA2 as a Biomarker for Monitoring Response to Treatment Biomarkers are crucial in evaluating patient responses to treatment, offering valuable insights into the effectiveness of therapeutic interventions. This case study investigates the efficacy of SAA2 as a biomarker for monitoring by analysing levels over time in patients undergoing treatment. The dataset comprises SAA2 measurements from three patients, with samples taken at various intervals following their peak levels n=10. Results Table 9: Decrease of SAA2 Levels from Peak over Time Hours Since Sample ID Peak (hrs) SAA2 Concentration (ug / ml) % Change (Reduction) 1A 0 215.9 - 1B 32 133 38 1C 224 41 81 2A 0 610.2 - 2B 24 52.2 91 2C 48 42.2 80 2D 72 27.4 95 3A 0 941.2 - 3B 46 337.9 64 3C 65 5 99 The dataset in Table 9 shows a significant decrease in SAA2 levels over time for all three samples indicating a response to treatment. The data demonstrates that SAA2 levels consistently decrease over time following treatment in all samples. This trend suggests that SAA2 is highly responsive to treatment and is a reliable indicator of treatment efficacy. A consistent decline across samples is observed whereby SAA2 levels show an uniform pattern of decrease across different samples making it a reliable indicator. Significant drops in SAA2 levels are observed within a short timeframe indicating effectiveness in monitoring early response to treatment. The substantial decrease in SAA2 from initial peak values to much lower levels provides a clear marker for assessing treatment progress. The data demonstrates that SAA2 levels decrease significantly within the first 24-48 hours across all patients. As an example, Sample 2 shows a 91% reduction in SAA2 concentration within 24 hours indicating a rapid initial response to treatment and early indicator of treatment efficacy. The data shows significant reductions in SAA2 levels over time for example in Sample 2 and 3. Despite variations in peak concentrations, reduction is consistent across all patients supporting reliability across a wide range baseline / peak values and applicable in diverse clinical scenarios. The data shows sharp contrasts in peak SAA2 levels and subsequent measurements allowing for differentiation of treatment response. For example, the dramatic reduction from 941.2 µg / ml to 5 µg / ml in Sample 3 clearly indicates a strong positive response to treatment. The study indicates that a reduction of at least 38% within the first 48 hours is indicative of successful treatment. All patients in the dataset meet or exceed this threshold. EXAMPLE 6: ENHANCED SPECIFICITY IN DIFFERENTIATING INFLAMMATION FROM INFECTION BY CALCULATING THE DIFFERENCE BETWEEN THE EXPRESSION OF THE ISOFORMS SAA1 AND SAA2 Differentiating between inflammation and infection in clinical practice is important, particularly when guiding treatment decisions. This case study explores the benefits of calculating the absolute difference between SAA1 and SAA2 to determine improvements in specificity to rule out non-infectious inflammation. Materials and Methods This study involved the analysis of 122 samples consisting of 63 samples with confirmed non-infectious inflammation and 59 samples with clinical notes confirming infection. Levels of SAA1 and SAA2 were measured using ELISA immunoassays and the absolute difference between SAA1 and SAA2 was calculated. The absolute difference between two levels considers how far from each other they are without considering which one is bigger. Statistical analyses were performed on the two groups, infection and inflammation using MedCalc™ software to evaluate and compare sensitivity, specificity, and Area Under the Curve (AUC). Results Table 10: Diagnostic Performance of Absolute Difference Between Isoforms SAA1 and SAA2 in Differentiating Infection from Inflammation Infection vs Inflammation AUC 0.85 P-value >0.001 Cut-off (ug / ml) >33 Sensitivity (%) 66.10 Specificity (%) 95.24 Calculating the absolute difference between SAA1 and SAA2 offers good specificity in distinguishing between inflammation and infection. This method provides a reliable metric for clinicians. Using the difference between SAA1 and SAA2, particularly when values are low can help to improve specificity when differentiating between inflammation and infection. EXAMPLE 7: BENEFITS OF COMBINING SAA1 AND SAA2 EXPRESSION VALUES IN ASSESSING OVERALL DISEASE BURDEN Accurately assessing disease burden and stratifying risk are critical components of clinical decision-making. This study investigates the potential benefits of combining SAA1 and SAA2 values to enhance diagnostic accuracy and their use as an effective metric for assessing overall disease burden. When the values of SAA1 and SAA2 are both relatively low, their combined sum might exceed a critical threshold (control expression level), potentially aiding in the early detection of conditions that might not be evident when considered separately. Materials & Methods This study involved the analysis of 122 samples consisting of 63 samples with confirmed non-infectious inflammation and 59 samples with clinical notes confirming infection. Levels of SAA1 and SAA2 were measured using ELISA immunoassays and statistical analyses were performed using MedCalc™ software to evaluate and compare sensitivity, specificity, and Area Under the Curve (AUC) of when combining the Isoforms. SAA1 and SAA2 are measured separately and the results combined to give a value. This combination method was assessed across 2 groups, inflammation and infection. The combined parameter from each patient was categorized into the appropriate group (inflammation vs infection) and an ROC analysis was undertaken. If the combined number exceeded a threshold, or a combined expression value from a control sample, inflammation was ruled out. Results: Table 11: Diagnostic Performance of Combining Isoforms SAA1 and SAA2 in Differentiating Infection from Inflammation Infection vs Inflammation AUC 0.9 P-value <0.001 Cut-off (ug / ml) >18 Sensitivity (%) 79.66 Specificity (%) 96.83 Conclusion: Combining the SAA1 and SAA2 expression values can enhance the assessment of overall disease burden. This approach can be used to capture the cumulative effects of disease processes and facilitate effective interventions and is also useful in providing a larger dynamic range for assessing disease severity. EXAMPLE 8: USING SAA2 CONCENTRATIONS TO DIFFERENTIATE BETWEEN INFECTION, INFLAMMATION IN EQUINE SAMPLES As in human medicine, it is also important in veterinary medicine to accurately distinguish between infection, and inflammation. This study investigates the use of SAA2 levels to distinguish equine samples from horses with inflammatory airway disease, a non- infectious condition and those exhibiting signs of infection or inflammation. The samples n=42 were obtained from a biobank along with clinical notes. Methods The samples were categorized into three groups based on their clinical background: 1. Infection: Samples representing equines diagnosed with infections (EHV4 and S. Equi). 2. Inflammation: Samples, representing equines with a diagnosed inflammatory airway disease (IAD), a non-infectious inflammation condition. SAA2 in each sample was measured using an ELISA method. Results Table 12: SAA2 levels in Equines according to Condition (Infection, Inflammation) Sample ID SAA2 Concentration (ug / ml) Equine Infection 1 86 Equine Infection 2 283 Equine Infection 3 1680 Equine Infection 4 52 Equine Infection 5 1597 Equine Infection 6 3025 Equine Infection 7 2197 Equine Infection 8 2196 Equine Infection 9 787 Equine Infection 10 1242 Equine Inflammation 1 0 Equine Inflammation 2 35 Equine Inflammation 3 0 Equine Inflammation 4 0 Equine Inflammation 5 0 Equine Inflammation 6 0 Equine Inflammation 7 0 Equine Inflammation 8 0 Equine Inflammation 9 0 Equine Inflammation 10 0 Equine Inflammation 11 0 Equine Inflammation 12 0 Equine Inflammation 13 0 Equine Inflammation 14 0 Equine Inflammation 15 0 Equine Inflammation 16 0 Equine Inflammation 17 0 Equine Inflammation 18 0 Equine Inflammation 19 0 Equine Inflammation 20 0 Table 13: Performance parameters of SAA2 when used to distinguish between infection and inflammation Cut Off (ug / ml) Sensitivity(%) Specificity(%) > 43.35 100 100 The study shows elevated SAA2 levels are associated with infections and that there is no elevation of SAA2 in inflammation or in healthy individuals. The results of the study summarised in Table 12 show that SAA2 concentrations can differentiate between inflammation and infection making it a highly valuable biomarker in a clinical setting in equines. High SAA2 levels are strongly indicative of infection, and a lack of detectable SAA2 is consistent with the presence of an inflammatory conditions, especially in the presence of symptoms and likely indicates wellness in the absence of symptoms. The sensitivity and specificity to infectious processes make it a valuable biomarker which supports timely and targeted interventions. The findings from this study suggest that routine measurement of SAA2 in equine clinical practice enhances diagnostic accuracy, particularly in distinguishing between infections and inflammatory conditions. Discussion Figures 1 and 2 depict lateral flow test strips of varying formats. The test strip can be presented as a laminated dipstick or as being assembled into a housing with suitable internal structures to ensure contact between overlapping materials, a port for sample application at the sample pad, and a result window for viewing the test and control lines. Test strips are run by preparing a sample by dilution and applying a set volume of diluted sample to the sample pad region of the test strip. The test strip is left to run for a set amount of time during which the sample containing analyte SAA1 and / or SAA2 mixes with the conjugate (colloidal gold bound to antibody) and binds to form an analyte- conjugate complex. Analyte, analyte-conjugate complex, and free conjugate flow up the membrane towards the test and control line regions, where the test line binds to analyte- conjugate complexes and accumulates to create a visible signal that can be interpreted by an electronic reader. Free conjugate binds to the control line and the remainder of the sample continues to flow towards the wick, which absorbs the sample and enables continued flow through the test strip until test completion. SAA1-specific and SAA2-specific test strip (see Figure 1) can both be assembled in a single housing, where SAA1 and SAA2 are detected on separate test strips, but the results of which can be combined using an electronic reader. This study in Example 1 demonstrates that SAA1 and SAA2 isoforms can significantly enhance diagnostic accuracy in differentiating between clinically healthy individuals and those with non-infectious inflammation. SAA1’s high specificity for inflammation and SAA2's association with infection provides a nuanced diagnostic approach, representing a considerable improvement over existing methods. The use of SAA1 and SAA2 as diagnostic markers can streamline the diagnostic process for patients presenting with symptoms of inflammation and infection. SAA1’s ability to specifically rule out healthy cases allows for quick identification of inflammatory conditions, while SAA2 aids in discerning infections. This specificity is particularly valuable in clinical settings, reducing the likelihood of misdiagnosis and enabling more precise and effective treatment strategies. The study in Example 2 demonstrates that SAA2 outperforms CRP in differentiating between inflammation and infection. SAA2’s higher specificity and sensitivity suggest it should be integrated into diagnostic protocols to improve patient outcomes through more accurate diagnoses. The study in Example 3 highlights the sensitivity of SAA1 in general health screening. By prioritizing sensitivity, healthcare systems can effectively identify non-healthy individuals, facilitating early diagnosis and intervention. The use of SAA1 as a screening biomarker can significantly improve disease detection rates, contributing to better patient outcomes and enhanced public health management. The study in Example 4, the diagnostic algorithm presented in this study offers a comprehensive and accurate method for distinguishing between healthy individuals, inflammatory conditions, and viral versus bacterial infections. Its stepwise approach ensures that only patients requiring further investigation are tested, enhancing diagnostic efficiency and accuracy. Implementing this diagnostic algorithm in clinical practice could improve patient outcomes by ensuring timely and appropriate treatment. By accurately differentiating between viral and bacterial infections, the algorithm can help reduce the misuse of antibiotics and combat antibiotic resistance. This case study demonstrates the potential of a stepwise diagnostic algorithm to enhance the accuracy and efficiency of diagnosing infectious and inflammatory conditions, ultimately improving patient care and treatment outcomes. The case study 1 in Example 5 shows that monitoring SAA2 levels in sepsis patients provides valuable prognostic information. A decline of at least 10% within 6 hours of peak concentration is associated with a 100% survival rate over the following 2 days, highlighting the potential of SAA2 as a biomarker for early intervention and treatment adjustment in the ICU. This case study demonstrates the potential of SAA2 as a reliable biomarker for predicting survivability in sepsis patients. The implementation of serial SAA2 measurements in clinical practice could enhance the ability of healthcare providers to predict outcomes and tailor treatments for sepsis patients. The case study 2 in Example 5 concludes that SAA2 is a more effective biomarker for monitoring the response to antibiotic treatment in patients compared to CRP. Its rapid and more consistent peak levels provide an earlier and more reliable indication of treatment efficacy, which is critical in all settings but particularly in the ICU setting for timely and appropriate patient management. The integration of SAA2 measurements in clinical practice could significantly improve the monitoring and management of infection treatment. This case study highlights the advantages of SAA2 over CRP as a biomarker for monitoring treatment response emphasizing the importance of rapid and reliable indicators in improving patient outcomes in critical care environments. The case study 3 in Example 5 indicates that SAA2 is an excellent biomarker for monitoring response to treatment due to its consistent and rapid decline across different patient samples. Utilizing SAA2 levels would enhance the accuracy and efficiency of treatment monitoring, leading to better patient outcomes. In the specification the terms "comprise, comprises, comprised and comprising" or any variation thereof and the terms “include, includes, included and including" or any variation thereof are considered to be totally interchangeable and they should all be afforded the widest possible interpretation and vice versa. The invention is not limited to the embodiments hereinbefore described but may be varied in both construction and detail.

Claims

Claims 1. A method of determining a health status of an individual, the method comprising the steps of assaying a biological sample from the individual for the positive expression of SAA1 and / or SAA2, and wherein the positive expression of the SAA1 and / or SAA2 above or below an expression threshold level of SAA1 and / or SAA2 in a control sample correlates with the health status of the individual.

2. A method of determining the progression of treatment of an individual with an inflammatory disease, the method comprising the step of assaying a biological sample from the individual with the inflammatory disease for the positive expression of SAA1, wherein the positive expression of SAA1 above or below a threshold level of SAA1 in a control sample, correlates with the effectiveness of treatment of the inflammatory disease or disorder in the individual.

3. The method of Claim 2, wherein when the positive expression of SAA1 is below a threshold level of SAA1 in a control sample, the treatment is effective in treating the inflammatory disease or disorder in the individual.

4. The method according to Claim 2 or Claim 3, wherein when the expression levels of SAA1 is below the expression threshold level in the control sample, the individual is responding to treatment; and wherein when the expression levels of SAA1 is above the expression levels of SAA1 in the control sample, the individual is experiencing an inflammatory response and is not responding to treatment.

5. The method according to Claim 1 or Claim 2, wherein when the expression levels of SAA1 are above the expression threshold level in the control sample, the individual is at risk of onset of an autoimmune condition and / or an autoinflammatory condition.

6. A method of monitoring the effectiveness of treatment of an infection or an infectious disease in an individual with an infection or an infectious disease, the method comprising the step of assaying a biological sample from the individual with an infection or an infectious disease for the positive expression of SAA1 and / or SAA2, wherein when the positive expression of SAA1 is below a threshold level of SAA1 in a control sample and the positive expression of SAA2 is below a threshold expression level of SAA2 in the control sample correlates with the effectiveness of treatment of the infection or the infectious disease in the individual.

7. A method of determining the progression of treatment of an individual with an infection, the method comprising the step of assaying a biological sample from the individual with the infection for the positive expression of SAA2, wherein the positive expression of SAA2 above or below a threshold level of SAA2 in a control sample, correlates with the effectiveness of treatment of the infection in the individual.

8. The method of Claim 6 or Claim 7, wherein when the positive expression of SAA2 is below a threshold expression level of SAA2 in the control sample, the treatment is effective in treating the infection in the individual.

9. A method of identifying an individual with an infection or an infectious disease that is suitable for treatment with a therapy for treating the infectious disease, the method comprising the steps of assaying a biological sample from the individual with the infection or infectious disease for the positive expression SAA2, wherein the positive expression of SAA2 above or below a threshold expression level of SAA2 in a control sample correlates with identifying that the individual has an infection or an infectious disease.

10. The method according to any one of the preceding Claims, wherein when the expression levels of SAA1 and / or SAA2 are below the threshold expression level in the control sample, the individual is not suffering from an infection, an infectious disease, an inflammatory event, or an inflammatory condition.

11. The method according to any one of Claims 1 to 10, wherein when the expression levels of SAA1 are above the expression threshold level in the control sample, the individual is experiencing an inflammatory event or is suffering from an inflammatory condition, and wherein when the protein expression levels of SAA2 are above the expression threshold level in the control sample, the individual is suffering from an infection or an infectious disease.

12. The method according to any one of Claims 1 and 6 to 11, wherein when the expression levels of SAA2 are above the expression threshold level in the control sample, the individual is experiencing an infection.

13. The method according to Claim 6 or Claim 7, wherein when the expression levels of SAA2 are above the expression threshold level in the control sample, the individual has an infection and is not responding to treatment.

14. The method according to Claim 6 or Claim 7, wherein when the expression levels of SAA2 is below the expression threshold level in the control sample, the individual is responding to treatment; and wherein when the expression levels of SAA2 is above the expression threshold level in the control sample, the individual is experiencing an infection and is not responding to treatment.

15. The method according to any one of Claims 1 to 14, wherein a combination of the expression levels of SAA1 and SAA2 in the biological sample from the individual greater than the combined threshold expression levels of SAA1 and SAA2 in the control sample correlates with differentiating between inflammation and infection.

16. The method according to any one of Claims 1 to 14, wherein determining a difference in the expression levels of SAA1 and SAA2 differentiates between inflammation and infection, wherein a negative expression value of SAA1 following subtraction of SAA2 expression levels from the SAA1 expression levels in the biological sample indicates an infection, while a positive expression value of SAA1 following subtraction of the SAA2 expression levels in the biological sample indicates an inflammation event.

17. The method according to any one of the preceding claims, in which the individual is a mammal.

18. The method according to Claim 17, wherein the mammal is a human.

19. The method of any one of the preceding claims, wherein the infection or infectious disease is selected from septicaemia, meningitis, an eye infection, an ear infection, tuberculosis, an upper respiratory tract infection, pneumonia, gastritis, a nail infection, a soft tissue infection, a skin infection, a central nervous system infection, a sexually transmitted infection, a bone infection, a joint infection, and a general post-surgical infection.

20. The method of any one of the preceding claims, wherein the inflammatory condition is selected from allergies, asthma, colitis, ulcerative colitis, and Crohn’s disease, lupus, rheumatoid arthritis, multiple sclerosis, endocrine disorders, chronic inflammatory demyelinating polyneuropathy, Guillain-Barre syndrome, psoriasis, vasculitis, Grave’s disease, myasthenia gravis, Hashimoto’s thyroiditis, celiac disease, glomerulonephritis, hepatitis, cryopyrinopathies or cryopyrin-associated periodic syndromes (CAPS), hives,skin rash, bronchitis, tissue injury, bone and skin non-infectious inflammation, kidney and urinary tract inflammatory conditions, acne, chronic prostatitis, diverticulitis, chronic obstructive pulmonary disease (COPD), cystic fibrosis, atherosclerosis, Alzheimer’s disease, cancer, and heart disease.

21. A method of treating an infection, an infectious disease, an inflammatory condition, or an autoinflammatory condition in a subject, the method comprising: receiving the results of an assay that indicates that the level of SAA1 and / or SAA2 in a sample obtained from the subject is above or below an expression threshold level in a control sample; and administering a treatment for the disease or condition.

22. A method of treating an inflammatory disease in a subject in need thereof, the method comprising: a) determining the expression level of SAA1 in a sample obtained from a subject; and b) administering an anti-inflammatory drug to the subject if the expression level of SAA1 is above a threshold expression level in a control sample.

23. The method according to any one of Claims 21 to 22 further comprising administering a suitable treatment as set out in Table 1 to a subject previously determined to have an expression level of SAA1 and / or SAA2 that is above or below the expression threshold level in the control sample.

24. A method of treating an infectious disease in a subject in need thereof, the method comprising administering an antibiotic to a subject determined to have an expression level of SAA2 above an expression threshold level of SAA2 in a control sample.

25. The method according to any one of Claims 21 to 24, wherein the infection, the infectious disease, the inflammatory condition, or the autoinflammatory condition is selected from the disease or condition set out in Table 1.

26. A method for differentiating whether an individual is healthy, has an inflammatory condition or has a viral or bacterial infection, the method comprising the steps of assaying a biological sample from the individual for the positive expression of SAA1 and / or SAA2 and wherein the positive expression of SAA1 and / or SAA2 above or below an expression threshold level in a control sample correlates with the health status of the individual, wherein if the concentration of SAA2 is above the expression threshold level in the control sample the individual is determined to have a bacterial or viral infection; wherein if the concentration of SAA1 is above the expression threshold level in the control samplethe individual is determined to have an inflammatory condition; and wherein if the concentration of SAA1 and / or SAA2 is below the expression threshold level in the control sample, the individual is determined to be healthy.

27. A method according to any one of Claims 1 to 26, wherein when a negative expression of SAA1 and / or SAA2, or when the expression levels of SAA1 and / or SAA2 are below the expression threshold level in the control sample, the result indicates a healthy status in the subject, and the treatment, if being administered, can be stopped.

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