Detection of cell damage

Abstract

Epigenetic modifications play an important role in regulating cell-specific expression patterns. For example, different DNA methylation signatures can be found in different tissues and even between different cell types within a particular tissue. In the research leading to the present invention, the inventors have found that these methylation signatures can be used to identify the tissue of origin of cfDNA. Furthermore, these novel methylation markers can be used to detect cell, tissue or organ damage, including self-derived cell, tissue or organ damage.

Description

Technical Field

[0001] Field of Disclosure The present disclosure relates to methods and compositions for detecting cell, tissue, and organ damage using cell-free DNA.

Background Art

[0002] Background of the Disclosure Any discussion of prior art throughout this specification should in no way be construed as an admission that such prior art is widely known or forms part of the common general knowledge in the art.

[0003] Cell-free DNA (cfDNA) in the blood of healthy individuals is mainly derived from white blood cells, and 20-30% is occupied by normal cell turnover of organs throughout the body. During injury and disease, organ or tissue-specific cell death results in an increase in DNA contribution from that organ or tissue to the cfDNA population. Detection of these changes in cfDNA levels has been applied to monitor graft rejection in organ transplantation by measuring donor-derived cell-free DNA (dd-cfDNA) found in transplant recipients.

[0004] Organ-specific cfDNA detection has been achieved using Y chromosome markers in female patients receiving organs from male donors. More recently, next-generation sequencing has been used to identify donor-specific alleles or single nucleotide polymorphisms (SNPs). However, dd-cfDNA assays are only applicable in situations where chimerism exists, such as in organ transplant recipients.

[0005] There is a need for methods and compositions for detecting and monitoring tissue or organ-specific cfDNA derived from native / self-organs.

Summary of the Invention

Means for Solving the Problems

[0006] Summary of the Disclosure Epigenetic modifications play an important role in regulating cell-specific expression patterns. For example, different DNA methylation signatures can be found in different tissues and even between different cell types within a particular tissue. In the research leading to the present invention, the inventors have found that these epigenetic signatures can be used to identify the tissue of origin of cfDNA. Furthermore, these novel epigenetic markers can be used to detect cell, tissue or organ damage including self-derived cells, tissues or organs.

[0007] In one aspect, the present disclosure provides a method for diagnosing organ damage in a subject, the method comprising detecting an organ-specific epigenetic marker in cfDNA obtained from a biological sample of the subject, wherein the presence of the epigenetic marker in the cfDNA indicates organ damage.

[0008] In another aspect, the present disclosure provides a method for detecting organ damage in a subject, the method comprising: a) obtaining a biological sample containing cfDNA from the subject; and b) detecting an organ-specific epigenetic marker in the cfDNA of the sample, wherein the presence of the epigenetic marker in the cfDNA of the sample indicates organ damage.

[0009] In yet another aspect, the present disclosure provides a method for identifying at least one methylated region in cfDNA, the method comprising: (i) obtaining cfDNA from a subject; (ii) treating the cfDNA with bisulfite to obtain bisulfite-converted cfDNA; (iii) identifying at least one methylated region by PCR amplification of the bisulfite-converted cfDNA using primers that selectively amplify at least one methylated region; and the at least one methylated region is a differentially methylated region that occurs in kidney cells.

[0010] In some examples, the method includes monitoring kidney injury during renal replacement therapy.

[0011] In some examples, the method includes detecting an increase in the level of an epigenetic marker as compared to a reference level. In some examples, the method includes detecting an increase in the level of an epigenetic marker over time.

[0012] The epigenetic marker is preferably the DNA methylation state in the differential methylation region of cfDNA.

[0013] In some examples, the method includes detecting the cfDNA methylation state in more than one differential methylation region. In some examples, the methylation state can be determined in more than one differential methylation region using a multiplex assay.

[0014] In some examples, the methylation state is determined by a method that does not involve genomic DNA sequencing. The methylation state is preferably determined by a method that does not involve DNA sequencing. The methylation state can be determined, for example, by treating cfDNA with bisulfite and amplifying the differential methylation region using polymerase chain reaction (PCR). The PCR can be digital PCR (dPCR), droplet digital PCR (ddPCR) or quantitative PCR (qPCR).

[0015] In some examples, the organ is the kidney. The organ injury can be associated with acute kidney injury (AKI), chronic kidney disease (CKD) or kidney transplant rejection after organ donation. In some examples, the organ injury is associated with chemotherapy or radiotherapy. The biological sample can be saliva, blood or serum or plasma, urine, semen, vitreous humor, lymph, synovial fluid, follicular fluid, gastric juice, intestinal juice, bile, tumor fluid, interstitial fluid, amniotic fluid, mucus, breast milk, pleural effusion, sweat, tears, feces, serum or cerebrospinal fluid.

[0016] In a further aspect, the present disclosure provides a method for diagnosing kidney injury in a subject, the method comprising detecting at least one differential methylation region of the kidney in cfDNA, wherein the cfDNA is obtained from a biological sample of the subject, and the presence of at least one differential methylation region of the kidney in the cfDNA indicates kidney injury.

[0017] In yet a further aspect, the present disclosure provides a method for detecting kidney injury in a subject, the method comprising a) obtaining a biological sample containing cfDNA from the subject; and b) detecting at least one differential methylation region of the kidney in the cfDNA; wherein the presence of at least one kidney-specific methylation site in the cfDNA indicates organ injury.

[0018] In some examples, the method comprises detecting an increase in the level of at least one differential methylation region of the kidney compared to a reference level. In a further example, the method comprises detecting an increase in the level of at least one differential methylation region of the kidney over time. In yet a further example, the method comprises detecting the cfDNA methylation state in more than one differential methylation region of the kidney. In yet a further example of the method, the methylation state is determined in more than one differential methylation region of the kidney using a multiplex assay. In a particular example of the method, the methylation state is determined by a method that does not involve DNA sequencing. In a particular example of the method, the methylation state is determined by treating the cfDNA with bisulfite and amplifying at least one differential methylation region of the kidney using polymerase chain reaction (PCR), where the PCR is, for example, digital PCR (dPCR), digital droplet PCR (ddPCR) or quantitative PCR (qPCR).

[0019] In certain examples of the method, the subject and the kidney are autologous. In further examples of the method, the kidney injury is associated with acute kidney injury, chronic kidney disease, or kidney transplant rejection or renal replacement therapy. In further examples of the method, the kidney injury is associated with chemotherapy or radiation therapy. In still further examples of the method, the biological sample is urine.

[0020] In certain examples of the method, the method specifically detects damage to defined tissues or cell types of the kidney. For example, damage to renal proximal tubular epithelial cells, or damage to podocytes.

[0021] In certain examples, the subject is human. In other examples, the subject is non-human. For example, in certain examples, the non-human subject is, for example, a farm animal or a companion animal, and the farm animal can be selected from the group consisting of, for example, sheep, cows, horses, cats, dogs, pigs, and chickens, and the companion animal can be selected from, for example, cats and dogs.

[0022] In certain examples, the method further includes treating the subject for kidney injury.

[0023] In some examples, the differential methylation region is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5. In some examples, the differential methylation region is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. In some examples, the differential methylation region is located at two loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. For example, the differentially methylated region can be located at GRAMD1B and DDC; GRAMD1B and MAST4; GRAMD1B and MCF2L; GRAMD1B and PAX2; DDC and MAST4; DDC and MCF2L; DDC and PAX2; MAST4 and MCF2L; MAST4 and PAX2; or MCF2L and PAX2. In some examples, the differential methylation region is located at three loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. For example, the differentially methylated region can be located at GRAMD1B, DDC, and MAST4; GRAMD1B, DDC, and MCF2L; GRAMD1B, DDC, and PAX2; GRAMD1B, MAST4, and MCF2L; GRAMD1B, MAST4, and PAX2; GRAMD1B, MCF2L, and PAX2; DDC, MAST4, and MCF2L; DDC, MAST4, and PAX2; DDC, MCF2L, and PAX2; or MAST4, MCF2L, and PAX2. In some examples, the differential methylation region is located at four loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. For example, the differentially methylated region can be located at GRAMD1B, DDC, MAST4, and MCF2L; GRAMD1B, DDC, MAST4, and PAX2; GRAMD1B, MAST4, MCF2L, and PAX2; GRAMD1B, DDC, MCF2L, and PAX2; or DDC, MAST4, MCF2L, and PAX2.In some examples, the differentially methylated regions are located in GRAMD1B, DDC, MAST4, MCF2L, and PAX2. The differentially methylated regions can include a sequence having at least 90% identity with any one or more of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 29, or SEQ ID NO: 30.

[0024] It will be appreciated that tissue damage can include damage to specific cells or tissue types within the tissue. In some examples, the method specifically detects damage to a defined tissue or cell type of an organ. The defined cell type can be renal proximal tubular epithelial cells. The differentially methylated regions can be located in at least one of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5.

[0025] In some examples, the method further includes treating the subject for organ damage. For example, the present disclosure also provides a method of treating an organ injury in a subject, the method comprising: i) detecting an organ-specific epigenetic marker in cfDNA obtained from a biological sample of the subject, wherein the presence of the epigenetic marker in the cfDNA indicates organ injury; and ii) treating the subject for organ injury.

[0026] In another aspect, the present disclosure provides a method of indicating to a user whether a subject has organ damage, the method comprising a) generating sample epigenetic data by determining the level of an organ-specific epigenetic marker in cell-free DNA obtained from a biological sample of the subject; b) the processor receiving the sample epigenetic data, wherein the processor also receives reference epigenetic data corresponding to the epigenetic marker; c) the processor generates differential epigenetic data by comparing the sample epigenetic data with reference epigenetic data; d) the processor processes the differential epigenetic data to generate a damage index value; e) the processor determines the damage state of the subject based on the damage index value, the damage state indicating whether the subject has organ damage; f) transferring an indicator of the disease state of the subject to the user via a communication network; including.

[0027] In certain embodiments, the methods of the invention relate to companion diagnostics used in conjunction with other diagnostic markers and / or reference data or details of the subject to determine or predict kidney damage in a subject. Other diagnostic markers can include, but are not limited to, elevated blood and / or urine creatinine levels, elevated blood urea nitrogen (BUN), glomerular filtration levels, urine albumin:creatinine ratio, and hyperlipidemia. Reference data or details of the subject can include, but are not limited to, the subject's age, weight, alcohol intake, smoking status, drug intake or dosing regimen, physical fitness or lack thereof, blood pressure, disease, stress or mental illness, cardiovascular disease, and existing or susceptibility to stroke.

[0028] An epigenetic marker is preferably the DNA methylation state in differentially methylated regions within cfDNA. In some examples, the differentially methylated regions are located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5. In some examples, the differentially methylated regions are located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. In some examples, the differentially methylated regions are located at two loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. For example, the differentially methylated regions can be located at GRAMD1B and DDC; GRAMD1B and MAST4; GRAMD1B and MCF2L; GRAMD1B and PAX2; DDC and MAST4; DDC and MCF2L; DDC and PAX2; MAST4 and MCF2L; MAST4 and PAX2; or MCF2L and PAX2. In some examples, the differentially methylated regions are located at three loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. For example, the differentially methylated regions can be located at GRAMD1B, DDC, and MAST4; GRAMD1B, DDC, and MCF2L; GRAMD1B, DDC, and PAX2; GRAMD1B, MAST4, and MCF2L; GRAMD1B, MAST4, and PAX2; GRAMD1B, MCF2L, and PAX2; DDC, MAST4, and MCF2L; DDC, MAST4, and PAX2; DDC, MCF2L, and PAX2; or MAST4, MCF2L, and PAX2. In some examples, the differentially methylated regions are located at four loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2.For example, differentially methylated regions may be located in GRAMD1B, DDC, MAST4 and MCF2L; GRAMD1B, DDC, MAST4 and PAX2; GRAMD1B, MAST4, MCF2L and PAX2; GRAMD1B, DDC, MCF2L and PAX2; or DDC, MAST4, MCF2L and PAX2. In some examples, the differentially methylated regions are located in GRAMD1B, DDC, MAST4, MCF2L and PAX2. The differentially methylated regions may include a sequence having at least 90% identity with any one or more of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 29 or SEQ ID NO: 30.

[0029] The present invention relates to a method of using differential methylation specifically in kidney cells. In one embodiment, one important advantage relates to the ability to selectively amplify methylated target sequences and exclude the unmethylated version of the gene. Thus, only kidney cfDNA is amplified and identified. This approach not only enables PCR-based assays, but also provides alternative low-cost sequencing-based embodiments. Thus, the possibility of incorporating sequencing into one embodiment of the method of the present invention provides a useful alternative route to overcome the limitations associated with PCR alone. Nevertheless, the PCR assay of the present invention remains commercially viable due to its wide use and relatively low cost required for setup.

[0030] It will be apparent to those skilled in the art that the present invention is not limited to any particular differentially methylated region within the described locus. For example, the present invention can be practiced using at least one of several differentially methylated regions present within the described locus.

[0031] In some examples, the sample epigenetic data and the reference epigenetic data are based on more than one epigenetic marker.

[0032] In some examples, the processor processes differential epigenetic data using univariate and / or multivariate analysis.

[0033] The subject can be a human or non-human subject, and the non-human subject can be, for example, a farm animal or a companion animal, the farm animal can be selected from the group consisting of, for example, sheep, cows, horses, cats, dogs, pigs and chickens, and the companion animal can be selected from, for example, cats and dogs.

[0034] In some examples, the subject is human.

[0035] In yet another aspect, the disclosure provides at least one nucleotide primer or nucleotide probe sequence when used in the method of the invention to detect at least one differential methylation region of the kidney of cfDNA. In certain examples, the at least one nucleotide primer or probe is two nucleotide primers when used in PCR to detect a differential methylation region of the kidney in cfDNA.

[0036] In still a further aspect, the disclosure provides a kit for use in diagnosing kidney injury of a subject, comprising at least one reagent for detecting at least one differential methylation region of the kidney in cfDNA, wherein the cfDNA is derived from a biological sample of the subject that includes instructions for use in the method of the invention. In certain examples, the at least one reagent for detecting at least one differential methylation region of the kidney in cfDNA is at least one nucleotide primer or nucleotide probe, and in certain examples, two nucleotide primers configured to detect at least one differential methylation region of the kidney in cfDNA.

[0037] In a further aspect, the present disclosure provides the use of at least one kidney differential methylation region in cfDNA in the manufacture of a reagent for diagnosing a target kidney injury. In a specific example, the reagent is at least one nucleotide primer or nucleotide probe, and in a specific example, two nucleotide primers configured to detect at least one kidney differential methylation region in cfDNA.

Brief Description of the Drawings

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Mode for Carrying Out the Invention

[0064] Detailed Description Definitions In the context of this specification, the terms "a" and "an" are used herein to refer to one or more than one (i.e., at least one) of the grammatical objects of the article. By way of example, "an element" means one element or more than one element.

[0065] The term "about" is understood to refer to a range of + / - 10%, preferably + / - 5% or + / - 1%, or more preferably + / - 0.1%.

[0066] As used in this specification and the claims, the terms "comprise", "comprises", "comprised", "comprising", "including", "having", etc. are used in an inclusive sense, i.e., they identify the presence of the stated features but do not preclude the presence of additional or further features.

[0067] As used herein, "CpG dinucleotide", "CpG methylation site" or the like should be construed to refer to a cytosine linked to a guanine by a phosphodiester bond. CpG dinucleotides are targets for methylation of cytosine residues and can be present within coding or non-coding nucleic acids.

[0068] The term "identity" refers to the relationship between the sequences of two or more polypeptide molecules or two or more nucleic acid molecules, determined by aligning the sequences for comparison. The percent identity between two sequences is determined in an optimal alignment of the sequences, taking into account the number of gaps that need to be introduced for the optimal alignment of the two sequences and the length of each gap, such that (i.e., % homology = number of identical positions / total number of positions × 100) it is a function of the number of identical positions shared by the sequences. Comparison of sequences and determination of the percent identity between two sequences can be accomplished using mathematical algorithms.

[0069] The percent identity between two nucleotide sequences can be determined using the GAP program of the GCG software package, using NWSgapdna, the CMP matrix, and gap weights of 40, 50, 60, 70, or 80 and length weights of 1, 2, 3, 4, 5, or 6. The percent identity between two nucleotide or amino acid sequences can also be determined using the algorithm of E. Meyers and W. Miller (CABIOS, 4:11-17 (1989)) incorporated into the ALIGN program, using the PAM120 weight residue table, a gap length penalty of 12, and a gap penalty of 4. Further, the percent identity between two amino acid sequences can be determined using either the Blossum 62 matrix or the PAM250 matrix, and gap weights of 16, 14, 12, 10, 8, 6, or 4 and length weights of 1, 2, 3, 4, 5, or 6, using the Needleman and Wunsch (J. Mol. Biol. 48:444-453 (1970)) algorithm incorporated into the GAP program of the GCG software package.

[0070] As used herein, the term "DNA methylation" is understood to mean the presence of methyl groups added to cytosine bases or bases in a region of a nucleic acid, such as genomic DNA, by the action of a DNA methyltransferase enzyme. Thus, as used herein, the term "methylation state" refers to the presence or absence of methylation at a particular locus.

[0071] The term "substantially complementary", when used to describe a first nucleotide sequence in relation to a second nucleotide sequence, refers to the ability of an oligonucleotide or polynucleotide containing the first nucleotide sequence to hybridize to an oligonucleotide or polynucleotide containing the second nucleotide sequence and form a double-stranded structure with the oligonucleotide or polynucleotide containing the second nucleotide sequence. It will be understood that the sequence of a nucleic acid need not be 100% complementary to the sequence of its target. The conditions under which hybridization occurs can be stringent, such as 400 mM NaCl, 40 mM PIPES pH 6.4, 1 mM EDTA, 50 °C or 70 °C for 12 - 16 hours, followed by washing. Other conditions such as physiologically relevant conditions that may be encountered inside an organism can also be applied. Substantial complementarity enables the progression of related functions of nucleic acids, such as guide RNA hybridization and CRISPR-mediated gene activation. One of ordinary skill in the art can determine the set of conditions most suitable for testing the complementarity of two sequences according to the ultimate application of the hybridized nucleotides.

[0072] The term "subject" refers to an animal, preferably a mammal, such as a human or non-human, including, but not limited to, members of the classifications of sheep, cattle, horses, pigs, cats, dogs, primates, and rodents, and particularly, but not limited to, domesticated members of these classifications such as cats, sheep, cattle, horses, cats, dogs, pigs, chickens, rats, and mice.

[0073] The term "reference level" in the context of the methods of the present invention refers to the level of differentially methylated regions in a subject having no organ injury or having slight organ injury, particularly kidney injury, or having no kidney injury or having slight kidney injury.

[0074] In a preferred embodiment, the present invention relates to the methods described herein for use in connection with a human subject. In particular, for example, the present invention relates to the use of the methods described herein for detecting kidney injury in a human. In another embodiment, the present invention relates to the methods described herein for use in connection with, for example, a non-human subject. In particular, the use of the methods described herein for detecting kidney injury in a domesticated animal (including, but not limited to) such as a cat, sheep, cow, horse, cat, dog, pig, chicken, rat, and mouse, including companion animals. In a particular embodiment, the present invention relates to the methods described herein for detecting kidney injury in, for example, a cat and / or a dog.

[0075] One of ordinary skill in the art will understand that it is routine to perform multiple alignments of nucleotide sequences using publicly available software such as, but not limited to, ClustalW. One of ordinary skill in the art will also readily understand that common primers and probes can be designed to detect regions of high nucleotide sequence identity in two or more different species. Alternatively, it will be apparent to one of ordinary skill in the art that species-specific oligonucleotides can be designed to target, in particular, DMRs from one species. Differential methylation status can be determined in each target species for use in the methods of the present invention as described in this application. Specifically, differential methylation status can be determined using the methodology as detailed herein.

[0076] More specifically, those skilled in the art will understand that primers and probes suitable for use in the methods described herein can be readily designed to detect DMRs at at least one locus selected from the group consisting of, for example, GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17 35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5. In particular, those skilled in the art will understand the relevant locus sequences, such as GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17 35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5 from different target species, and such humans and non-humans will exhibit a high level of sequence identity. Thus, based on the specific DMR sequences disclosed and exemplified herein in relation to, for example, human and feline kidney-specific DMR sequences, those skilled in the art can readily identify kidney DMRs within the range of non-human animals including, but not limited to, cats, dogs, sheep, cows, horses, mice, rats, pigs, and chickens. The relevant sequence information regarding loci containing kidney-specific DMRs from humans and non-human animals (such as breeding animals) is shown in Tables 1-11 below.

[0077] Exemplary support for the identification of kidney-specific DMRs in non-human animals is provided in FIG. 19, which shows an increase in the level of the PAX2 methylation biomarker in urine samples obtained from cats with CKD compared to urine obtained from healthy cats.

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[0078] When numerical ranges are used to describe specific embodiments of the present disclosure, it should be understood that each range should be considered to include sub-ranges therein. For example, a description of a range such as 1 to 6 should be considered to include sub-ranges such as 1 to 5, 2 to 4, 2 to 6, etc. Similarly, a description of a range between 1 and 6 should be considered to include sub-ranges between 2 and 5, between 1 and 3, between 3 and 6, etc.

[0079] Cell damage and related conditions Damage to organs and tissues that results in organ- or tissue-specific cell death leads to an increase in the concentration of organ- or tissue-specific DNA in the cfDNA population. The inventors have found epigenetic signatures within various organs, tissues, and even cell types that can be used as markers to detect damage to organs, tissues, or cells from a sample of cfDNA. For example, an increase in the concentration of kidney-specific epigenetic markers within cfDNA can indicate kidney damage resulting from cell death within the kidney. The methods described herein can be used to diagnose diseases or conditions or disorders associated with cell death. The methods may also be used to predict the likelihood of an event occurring. For example, the methods described herein can be used to prognose renal failure in a subject.

[0080] The methods described herein are not limited to any particular organ or tissue. For example, the methods can be used to detect damage to the kidney, liver, spleen, prostate, heart, muscle, lung, brain, small intestine, large intestine, bladder, pancreas, adrenal gland, breast, colon, pancreas, bone, placenta, or skin, or their tissues or cell types. The damage can be caused by disease, infection, or trauma.

[0081] In some examples, the methods described herein detect epigenetic markers in cfDNA from dead neurons (indicating traumatic brain injury, amyotrophic lateral sclerosis, stroke, Alzheimer's disease, Parkinson's disease, or brain tumor), dead pancreatic acinar cells (indicating pancreatic cancer or pancreatitis), dead lung cells (indicating lung disease states including lung cancer), dead adipocytes (indicating changes in lipid metabolism), dead hepatocytes (indicating liver failure, liver disease, or hepatotoxicity), dead cardiomyocytes (indicating heart disease or graft failure in the case of a heart transplant), dead skeletal muscle cells (indicating muscle injury and myopathy), dead oligodendrocytes (indicating white matter damage in relapsing-remitting multiple sclerosis, amyotrophic lateral sclerosis, or glioblastoma), dead placental cells (indicating preeclampsia or placental abruption), or dead colon cells (indicating colorectal cancer).

[0082] In some examples, the methods described herein are used to detect kidney injury. Injury to the kidney can result from, for example, acute kidney injury (AKI) or chronic kidney disease (CKD). Risk groups for which regular screening can be particularly beneficial include patients with diabetes, subjects with hypertension, subjects with polycystic kidney disease, transplant recipients, and the like.

[0083] Kidney diseases are major health problems representing the interrelated spectrum of AKI and CKD. AKI is associated with high morbidity, mortality, long-term hospitalization, and progression to CKD. Patients with CKD can progress to end-stage renal disease (ESRD) requiring dialysis or kidney transplantation. Kidney diseases impose a significant cost on the health system and are disproportionately prevalent among Indigenous Australians, low socioeconomic groups, the elderly, and people in rural / remote locations. Kidney diseases are underdiagnosed, and most people are unaware of their existence until symptoms appear. In the United States, it is estimated that approximately 200,000 people (0.06% of the US population) are living with a kidney transplant, approximately 4 million people (1.2%) develop AKI each year, and approximately 37 million people (11.2%) are living with CKD. Since 90% are unaware of their diagnosis, CKD patients are 20 times more likely to die of cardiovascular disease due to having CKD than to receive renal function replacement. Early and accurate detection of kidney diseases delays and reduces the loss of kidney function. The use of serum creatinine as a surrogate for detecting AKI / CKD takes up to 48 hours to produce a measurable change. In the case of CKD, it can be degraded before a change in creatinine in up to 50% of the kidney and before symptoms appear in up to 90%. The ability to detect these conditions earlier in higher-risk populations and in patients without obvious clinical symptoms enables more rapid intervention to reduce further kidney injury and the morbidity and mortality associated with AKI / CKD. The present disclosure provides methods useful for the early detection of AKI and CKD.

[0084] The methods described herein can also be used to detect tissue or organ damage after transplantation of a tissue or organ. For example, the methods can be used to detect kidney damage after kidney transplantation. The methods can identify early signs of organ rejection. The methods can also be used to detect tissue or organ damage after a particular treatment. For example, the methods can be used to detect kidney damage after cardiothoracic surgery or renal replacement therapy.

[0085] The methods described herein do not rely on detecting unique DNA sequences and thus are not limited to situations where one subject's genome is to be distinguished from another's (e.g., after transplantation of an organ or tissue). In other words, the methods of the present disclosure can be used to detect an individual subject's own organ damage. In that regard, in the methods of the present disclosure, the subject and the organ are preferably autologous.

[0086] The epigenetic markers described herein can be organ-specific, tissue-specific, or cell-specific, and in that regard, the methods of the present disclosure can be used to detect damage to an organ, tissue, or cell. For example, in the kidney, the inventors have identified epigenetic markers (e.g., methylation in MAST4 and DDC) that are enriched in renal proximal tubule epithelial cells compared to other cells of the kidney and other organs of the body. These markers can be used to diagnose conditions associated with or caused by damage to renal proximal tubule epithelial cells, such as ischemia-reperfusion injury. Renal proximal tubule epithelial cells (RPTEC) have abundant mitochondria that are highly dependent on oxidative phosphorylation, which renders RPTEC vulnerable to injury and serves as an early marker of ischemia-reperfusion injury by cell death. Injury to RPTEC also results in the formation of tubuloglomerular feedback and can lead to CKD. The ability to detect RPTEC-specific cell death improves early detection and location-specific injury associated with surgical and disease-induced damage.

[0087] In some examples, the present disclosure provides a method for detecting renal proximal tubular epithelial cell injury in a subject, the method comprising detecting a methylation state in MAST4 or DDC in cfDNA obtained from a biological sample of the subject, wherein the presence of methylated MAST4 or DDC in the cfDNA indicates renal proximal tubular epithelial cell injury. It is understood that an increase in the level of methylated MAST4 and / or DDC DNA in cfDNA obtained from a subject may indicate that the subject is suffering from renal proximal tubular epithelial cell injury. In some examples, the present disclosure provides a method for diagnosing ischemia-reperfusion injury in a subject, the method comprising detecting a methylation state in MAST4 or DDC in cfDNA obtained from a biological sample of the subject.

[0088] In one embodiment, the method of the invention uses a combination of differential methylation regions of the kidney to obtain a measure of kidney injury. In this regard, the present invention provides differential methylation regions of the kidney that correlate with specific kidney cells. For example, PAX2 in urine serves as a useful marker for general kidney injury. However, Pax2 is not an optimal classification metric for stage 2 samples in CKD. In contrast, GRAMD1B and DDC, which correlate with renal podocytes and renal proximal tubular cells, provide a more effective option for detecting kidney injury problems. Additionally, PAX2 may be susceptible to fluctuations due to inflammation caused by, for example, infections. In the case of kidney transplantation, it is known that BK virus can cause an increase in kidney cfDNA in urine when measuring dd-cfDNA, as infections are expected to be kidney-based. As a result, the measurement of tubular markers may provide a more robust assessment as they are less likely to be affected by infections. Thus, the measurement of PAX2 enables a general determination of problems in the kidney, and other kidney DMRs provide more specific indicators of kidney cell injury. For example, detection of elevated levels of GRAMD1B indicates renal podocyte injury, and detection of elevated levels of DDC indicates renal proximal tubular cell injury.

[0089] The methods described herein may also be useful for detecting proliferative diseases such as cancer. Such diseases may be associated with not only an increase in cell proliferation but also an increase in cell damage or cell death. For example, proliferating cells themselves (e.g., tumor cells) may die over time and release DNA that can be detected in cfDNA using the methods described herein. In other examples, proliferating cells may cause damage or death to proximal or distal cells and thus release DNA that can be detected in cfDNA using the methods described herein.

[0090] The present disclosure also contemplates treating a subject who has been found to be suffering from or at risk of organ or tissue damage. The treatment may include, for example, administration of a pharmaceutical, surgery, chemotherapy, lifestyle modification, dietary modification, or physical therapy. In some examples, the present disclosure provides a method of detecting an organ injury in a subject, the method comprising detecting an organ-specific epigenetic marker in cfDNA obtained from a biological sample of the subject, wherein the presence of the epigenetic marker in the cfDNA indicates organ injury, and administering a treatment for the organ injury to the subject when the organ injury is detected. In some examples, the present disclosure provides a method of treating a subject who has or is at risk of having an organ injury, the organ injury having been detected by a method comprising detecting an organ-specific epigenetic marker in cfDNA obtained from a biological sample of the subject, wherein the presence of the epigenetic marker in the cfDNA indicates organ injury.

[0091] Epigenetic marker The epigenetic markers of the present disclosure are cell-specific, tissue-specific, or organ-specific in the sense that they are enriched in that cell, tissue, or organ compared to other cells, tissues, or organs of the body. In some examples, the epigenetic marker is at least about 5% more abundant, such as at least about 10% more abundant, or at least about 15% more abundant, at least about 20% more abundant, at least about 25% more abundant, at least about 30% more abundant, at least about 35% more abundant, at least about 40% more abundant, at least about 45% more abundant, at least about 50% more abundant, at least about 55% more abundant, at least about 60% more abundant, at least about 65% more abundant, at least about 70% more abundant, at least about 75% more abundant, at least about 80% more abundant, at least about 85% more abundant, at least about 90% more abundant, at least about 95% more abundant, or at least about 100% more abundant in the cell, tissue, or organ of interest compared to other cells, tissues, or organs of the body. In some examples, the epigenetic marker is at least 2-fold more abundant, at least 3-fold more abundant, at least 4-fold more abundant, at least 5-fold more abundant, at least 6-fold more abundant, at least 7-fold more abundant, at least 8-fold more abundant, at least 9-fold more abundant, at least 10-fold more abundant, at least 11-fold more abundant, at least 12-fold more abundant, at least 13-fold more abundant, at least 14-fold more abundant, or at least 15-fold more abundant in the cell, tissue, or organ of interest compared to other cells, tissues, or organs of the body. In some examples, the epigenetic marker is detectable only in the cell, tissue, or organ of interest.

[0092] One of ordinary skill in the art will understand that different types of epigenetic markers can be used to identify specific cell, tissue, or organ types. Suitable epigenetic markers can include the acetylation state of DNA or histones, or the methylation state of DNA or histones. In some examples, epigenetic markers are selected from the group consisting of DNA modifications, histone modifications, and nucleosome arrangements.

[0093] In some examples, nucleosome arrangement is determined by a nucleosome arrangement assay. Histone modifications can be detected by a pull-down assay using an antibody specific for the histone modification. The antibody can be specific for histone methylation, acetylation, phosphorylation, ubiquitination, GlcNAcylation, citrullination, crotonylation, or isomerization. In some examples, histone methylation-specific antibodies include antibodies against H3K4Me1, H3K4Me2, H3K4Me3, or H3K36Me3 modifications.

[0094] Preferably, the epigenetic marker used in the methods of the present disclosure is the DNA methylation state at one or more DMRs within cfDNA. For example, a DMR may be unmethylated in the heart but methylated in other parts of the body. In some examples, a DMR is methylated in the kidney but not in other parts of the body. The amount of methylated DNA at a DMR present in a subject's cfDNA can be proportional to the level of organ damage experienced by the subject.

[0095] The methylation status can be detected at one or more CpG dinucleotides. For example, one epigenetic marker can have methylation at one CpG dinucleotide, two CpG dinucleotides, three CpG dinucleotides, four CpG dinucleotides, five CpG dinucleotides, six CpG dinucleotides, seven CpG dinucleotides, eight CpG dinucleotides, nine CpG dinucleotides, ten CpG dinucleotides, eleven CpG dinucleotides, twelve CpG dinucleotides, thirteen CpG dinucleotides, fourteen CpG dinucleotides, fifteen CpG dinucleotides, sixteen CpG dinucleotides, seventeen CpG dinucleotides, eighteen CpG dinucleotides, nineteen CpG dinucleotides, or at least twenty CpG dinucleotides. In situations where a DMR contains differentially methylated CpG dinucleotides that exceed one, those CpG dinucleotides may or may not be contiguous (i.e., adjacent) within the DMR.

[0096] Various techniques can be used to detect DNA methylation status. For example, cfDNA can be treated with bisulfite and sequenced or assayed using PCR techniques. Bisulfite conversion typically involves treating DNA with a bisulfite such as sodium bisulfite, which results in the deamination of unmethylated cytosine to uracil, while methylated cytosine (both 5-methylcytosine and 5-hydroxymethylcytosine) remains unchanged. This is shown in Figure 20. The DNA can then be amplified by PCR, where uracil is converted to thymine. Bisulfite-converted DNA can be analyzed for methylation status using primers that distinguish methylated and unmethylated sequences. The primers can be designed such that amplification occurs (or is substantially more efficient) only when the template is derived from either methylated DNA or unmethylated DNA. In addition to, or instead of, this, probes can be designed that specifically hybridize to bisulfite-converted DNA derived from either methylated DNA or unmethylated DNA. After bisulfite conversion of DNA, the two strands are often no longer complementary to each other, which means that primers and probes can be designed for either strand. In some examples, the methylation status is detected using quantitative PCR (qPCR), digital PCR (dPCR), or digital droplet PCR (ddPCR). These techniques are described in Shemer, R. et al., Current Protocols in Molecular Biology, 127.1 (2019): e90, and Zemmour, Hai et al., Nature Communications, 9.1 (2018): 1-9. Unmethylated cytosine nucleotides can also be enzymatically converted to uracil nucleotides, for example using NEBNext's Enzymatic Methyl-seq Kit. The Methyl-seq Kit uses TET2 to oxidize 5-methylcytosine and 5-hydroxymethylcytosine, thereby protecting them from deamination by apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC).In some cases, the methylation status can be detected using nanopore sequencing technology. Nanopore sequencing technology can detect native CpG methylation in cfDNA without prior bisulfite treatment.

[0097] Alternatively, the amplification products of bisulfite-converted DNA can be sequenced to determine the methylation status of the template, and comparing the sequence of the converted DNA with the untreated DNA creates a methylation profile of the amplified region. The presence of mutant or non-mutant nucleotides in the bisulfite-treated sample can also be detected using, for example, pyrosequencing as described in Uhlmann et al., Electrophoresis, 23:4072-4079, 2002. In essence, this method is a form of real-time sequencing that uses primers that hybridize to sites adjacent to or very close to the sites of methylated cytosine. After hybridization of the primer to the template in the presence of DNA polymerase, each of the four modified deoxynucleotide triphosphates is added separately in a predetermined dispensing order. Only the additional nucleotides complementary to the bisulfite-treated sample are incorporated, releasing inorganic pyrophosphate (PPi). PPi then drives a reaction that results in the production of a detectable level of light. Such a method allows determination of the identity of specific nucleotides adjacent to the primer hybridization site.

[0098] The presence of non-mutant nucleic acid sequences can be detected using, essentially, combined bisulfite restriction analysis (COBRA) as described in Xiong and Laird, Nucl Acids Res., 25:2532-2534, 2001. This method takes advantage of the difference in restriction enzyme recognition sites between methylated and unmethylated nucleic acids after bisulfite treatment. Methylation-specific microarrays (MSOs) are also useful for distinguishing mutant and non-mutant sequences. Suitable methods are described, for example, in Adorjin et al., Nucl.Acids Res., 30:e21, 2002.

[0099] In other examples, cfDNA can be used directly as a template in a methylation-sensitive PCR assay. Methylation-sensitive PCR can rely on the use of methylation-sensitive restriction enzymes that cut either methylated DNA or unmethylated DNA, but not both. Exemplary methylation-sensitive restriction enzymes include AatII, AvaI, CfoI, Eco47III, HpaI, HpaII, MluI, NaeI, NarI, NotI, NruI, PvuI, SacII, SmaI, SnaBI, and XhoI. For example, HpaI recognizes and cuts the GTT|AAC site when it is unmethylated. HpaII does not cut its CCGG recognition site if it is methylated. The DNA is treated with a methylation-sensitive restriction enzyme and then used as a template for PCR amplification using primers adjacent to the recognition and cleavage sites of the methylation-sensitive restriction enzyme. The PCR assay can be quantitative or semi-quantitative.

[0100] U.S. Patent No. 7,229,759 also describes techniques (sometimes referred to as "methylight") that can be used to detect methylation status.

[0101] In some examples, methods for detecting methylation status do not include genome sequencing. In some examples, the methods do not include DNA sequencing. PCR-based assays can be less expensive and faster than sequencing-based methods. Additionally, certain biological samples, such as urine, may be more suitable for PCR-based methods than sequencing-based methods due to problems such as cfDNA fragmentation.

[0102] For example, methods for designing probes and / or primers for use in PCR or hybridization are known in the art and are described, for example, in Dieffenbach and Dveksler (Eds) (In: PCR Primer: A Laboratory Manual, Cold Spring Harbor Laboratories, NY, 1995). Furthermore, several software packages for designing probes and / or primers for various assays have been published. In some examples, the primers and / or probes include a fluorescent label. The fluorescent signal from the probe can be measured as a readout, and the tissue composition of cfDNA can be inferred from the readout.

[0103] Preferably, the epigenetic marker used in the method of the present disclosure is the DNA methylation state within one or more DMRs of cfDNA. In some examples, the epigenetic marker is kidney-specific. Kidney-specific epigenetic markers can include methylated DMRs at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5. In some examples, the DMR is located at one locus selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5. In some examples, the DMR is located at more than one locus selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5.

[0104] In some examples, the DMR is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. Sequences from these loci are shown in Table 12, and one of ordinary skill in the art will understand that natural polymorphisms and allelic variations exist among individuals. In some examples, the DMR is located at one locus selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. In some examples, at least one DMR is located at PAX2. In some examples, at least one DMR comprises the sequence shown in SEQ ID NO: 1 or SEQ ID NO: 2, or a sequence having at least 90% identity to SEQ ID NO: 1 or SEQ ID NO: 2. In some examples, at least one DMR is located at GRAMD1B. In some examples, at least one DMR comprises the sequence shown in SEQ ID NO: 8 or SEQ ID NO: 9, or a sequence having at least 90% identity to SEQ ID NO: 8 or SEQ ID NO: 9. In some examples, at least one DMR is located at DDC. In some examples, at least one DMR comprises the sequence shown in SEQ ID NO: 15 or SEQ ID NO: 16, or a sequence having at least 90% identity to SEQ ID NO: 15 or SEQ ID NO: 16. In some examples, at least one DMR is located at MAST4. In some examples, at least one DMR comprises the sequence shown in SEQ ID NO: 22 or SEQ ID NO: 23, or a sequence having at least 90% identity to SEQ ID NO: 22 or SEQ ID NO: 23. In some examples, at least one DMR is located at MCF2L. In some examples, at least one DMR comprises the sequence shown in SEQ ID NO: 29 or SEQ ID NO: 30, or a sequence having at least 90% identity to SEQ ID NO: 29 or SEQ ID NO: 30.

[0105] In some examples, the DMR is located at two loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. For example, the DMR can be located at GRAMD1B and DDC; GRAMD1B and MAST4; GRAMD1B and MCF2L; GRAMD1B and PAX2; DDC and MAST4; DDC and MCF2L; DDC and PAX2; MAST4 and MCF2L; MAST4 and PAX2; or MCF2L and PAX2. In some examples, the DMR is located at three loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. For example, the DMR can be located at GRAMD1B, DDC, and MAST4; GRAMD1B, DDC, and MCF2L; GRAMD1B, DDC, and PAX2; GRAMD1B, MAST4, and MCF2L; GRAMD1B, MAST4, and PAX2; GRAMD1B, MCF2L, and PAX2; DDC, MAST4, and MCF2L; DDC, MAST4, and PAX2; DDC, MCF2L, and PAX2; or MAST4, MCF2L, and PAX2. In some examples, the DMR is located at four loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2. For example, the DMR can be located at GRAMD1B, DDC, MAST4, and MCF2L; GRAMD1B, DDC, MAST4, and PAX2; GRAMD1B, MAST4, MCF2L, and PAX2; GRAMD1B, DDC, MCF2L, and PAX2; or DDC, MAST4, MCF2L, and PAX2. In some examples, the DMR is located at GRAMD1B, DDC, MAST4, MCF2L, and PAX2.

[0106] In the example where the DMR is located at more than one locus, the methylation status at each locus can be detected by separate singleplex assays, or the methylation status at all loci can be detected by a single multiplex assay. For example, the DMR may be located at two loci and can be detected using a methylation status duplex assay. In another example, the DMR is located at three loci and the methylation status can be detected using a triplex assay. This method may include, for example, using a triplex assay to detect the methylation status in GRAMD1B, DDC, and PAX2. In another example, the DMR is located at four loci and the methylation status can be detected using a quadruplex assay. In another example, the DMR is located at five loci and the methylation status can be detected using a pentaplex assay.

[0107] The DMR may contain one methylation site or multiple methylation sites. The DMRs may be adjacent to each other on the same chromosome or may be distantly located on the same or different chromosomes.

[0108] The present disclosure also provides isolated nucleic acids corresponding to tissue- or organ-specific DMRs, and optionally, the nucleic acids are bisulfite-treated. In one example, the present disclosure provides an isolated nucleic acid having a sequence derived from or corresponding to GRAMD1B, DDC, MAST4, MCF2L or PAX2, or a part of GRAMD1B, DDC, MAST4, MCF2L or PAX2. The part is preferably at least 30 nucleotides in length, for example, between about 30 nucleotides and 600 nucleotides, or between about 30 nucleotides and 500 nucleotides, or between about 30 nucleotides and 400 nucleotides, or between about 30 nucleotides and 350 nucleotides, or between about 30 nucleotides and 300 nucleotides, or between about 30 nucleotides and 250 nucleotides, or between about 30 nucleotides and 200 nucleotides, or between about 30 nucleotides and 150 nucleotides, or between about 40 nucleotides and 150 nucleotides, or between about 40 nucleotides and 100 nucleotides, or between about 50 nucleotides and 100 nucleotides. In some examples, the present disclosure provides an isolated nucleic acid having a sequence that is at least 80% identical, or at least 85% identical, or at least 90% identical, or at least 95% identical or 100% identical to the sequence set forth in any one of SEQ ID NOs: 1 to 35. In some examples, the present disclosure provides an isolated nucleic acid generated by bisulfite treatment of a nucleic acid molecule having a sequence that is at least 80% identical, or at least 85% identical, or at least 90% identical, or at least 95% identical or 100% identical to the sequence shown in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 29 or SEQ ID NO: 30.

[0109] In some examples, the nucleic acid is bisulfite-treated. In some examples, the present disclosure provides a bisulfite-treated nucleic acid having a sequence that is at least 80% identical, or at least 85% identical, or at least 90% identical, or at least 95% identical or 100% identical to the sequence shown in SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34 or SEQ ID NO: 35. In some examples, the bisulfite-treated nucleic acid is at least 30 nucleotides in length, for example, between about 30 nucleotides and 600 nucleotides, or between about 30 nucleotides and 500 nucleotides, or between about 30 nucleotides and 400 nucleotides, or between about 30 nucleotides and 350 nucleotides, or between about 30 nucleotides and 300 nucleotides, or between about 30 nucleotides and 250 nucleotides, or between about 30 nucleotides and 200 nucleotides, or between about 30 nucleotides and 150 nucleotides, or between about 40 nucleotides and 150 nucleotides, or between about 40 nucleotides and 100 nucleotides, or between about 50 nucleotides and 100 nucleotides in length. Sequence

[0110] The sequences related to the present disclosure, including those mentioned in the examples, are listed in Table 12. [Table 12-1] [Table 12-2] [Table 12-3] [Table 12-4] [Table 12-5]

Table 12-6

Table 12-7

[0111] Indicators of cell damage An assessment of whether a subject is suffering from or at risk of tissue or organ damage can be made by comparing the level of an epigenetic marker to a reference level or by monitoring the level of an epigenetic marker over time. The reference level of an epigenetic marker in cfDNA can be used as a baseline against which the level of the epigenetic marker in a cfDNA sample is compared. The reference level can represent the concentration of an epigenetic marker expected in the cfDNA of a healthy individual or group or population of healthy individuals. A higher or lower concentration of an epigenetic marker in the sample cfDNA compared to the reference level can indicate that the subject is suffering from or at risk of tissue or organ damage. The reference level may be based on studies conducted on cfDNA taken from healthy individuals or on the concentration of an epigenetic marker in cfDNA from a subject at a defined point in time (e.g., before a particular treatment). The reference level may be based on a dataset that includes the levels of epigenetic markers in a population of healthy subjects or individuals.

[0112] A difference of at least about 5% in the level of an epigenetic marker in a sample cfDNA compared to a reference level can indicate tissue or organ damage. For example, a difference of at least about 10%, such as at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95% or at least about 100% can indicate tissue or organ damage. In some examples, if the amount of an epigenetic marker present in the cfDNA of a sample is about 5% higher than the amount present in the reference cfDNA, damage to an organ or tissue can be indicated. In some examples, if the amount of an epigenetic marker present in the cfDNA of a sample is at least about 10% higher, such as at least about 15% higher, at least about 20% higher, at least about 25% higher, at least about 30% higher, at least about 35% higher, at least about 40% higher, at least about 45% higher, at least about 50% higher, at least about 55% higher, at least about 60% higher, at least about 65% higher, at least about 70% higher, at least about 75% higher, at least about 80% higher, at least about 85% higher, at least about 90% higher, at least about 95% higher, or at least about 100% higher than the amount present in the reference cfDNA, damage to an organ or tissue can be indicated. In some examples, if the amount of an epigenetic marker present in the cfDNA of a sample is at least about 2-fold higher, such as at least about 3-fold higher, at least about 4-fold higher, at least about 5-fold higher, at least about 6-fold higher, at least about 7-fold higher, at least about 8-fold higher, at least about 9-fold higher, or at least about 10-fold higher than the amount present in the reference cfDNA, damage to an organ or tissue can be indicated.

[0113] In some examples, the reference level of an epigenetic marker can be 0 (undetectable), and the detectable presence of an epigenetic marker in cfDNA of a sample can indicate tissue or organ damage. In other examples, the level of an epigenetic marker is measured over time. A subject can be monitored, for example, by collecting a biological sample from the subject over time and measuring the level of an epigenetic marker in cfDNA from each biological sample. An increase in the concentration of an epigenetic marker in cfDNA over time can indicate that the subject has or is at risk of having tissue or organ damage.

[0114] The methods described herein can be performed on subjects of any age, although cellular damage may be more common in older subjects compared to younger subjects. Correspondingly, cell-specific, tissue-specific, or organ-specific epigenetic markers can be present at higher concentrations in older subjects compared to younger subjects. In some examples, the present disclosure provides a method of detecting organ damage in a subject, wherein the subject is at least 5 years old. In some examples, the subject is at least 10 years old, or at least 15 years old, or at least 20 years old, or at least 25 years old, or at least 30 years old, or at least 35 years old, or at least 40 years old, or at least 45 years old, or at least 50 years old, or at least 55 years old, or at least 60 years old, or at least 65 years old.

[0115] Epigenetic data can be combined and made more clinically useful by using various formulas, including statistical classification algorithms, etc., that combine beyond the performance characteristics of any individual data point and often extend the performance characteristics of that combination. These particular combinations exhibit an acceptable level of diagnostic / prognostic accuracy and can reliably achieve a high level of diagnostic / prognostic accuracy that is transportable from one population to another when sufficient information from one or more markers is combined in a trained formula.

[0116] Some statistical and modeling algorithms known in the art can be used to assist in marker selection and optimize algorithms that combine these selections. Statistical tools such as factor and cross-marker correlation / covariance analysis can enable a more rational approach to panel construction. Mathematical clustering and classification trees showing Euclidean standardized distances between markers can be advantageously used. Pathway informed seeding based on such statistical classification techniques can also be used so that a rational approach is possible based on the selection of individual markers and their involvement in specific pathways or physiological functions or individual performance.

[0117] Equations such as statistical classification algorithms can be directly used to select epigenetic markers and generate and train equations for combining results from multiple epigenetic markers into a single index. Techniques such as forward selection (from 0 potential explanatory parameters) and backward selection (from all available potential explanatory parameters) are often used, and information criteria are used to quantify the trade-off between panel performance and diagnostic / prognostic accuracy and the number of epigenetic markers used. The position of individual epigenetic markers on the forward or backward selected panel can be closely related to providing the incremental information content of the algorithm, so the order of contribution can depend on other constituent markers within the panel.

[0118] Any suitable equation can be used to combine the results of epigenetic markers into an indicator or indicators useful in the methods of the present disclosure. As shown herein, but not limited to, such indicators can indicate probability, likelihood, absolute or relative risk, time or rate to organ damage, conversion from one disease state to another among various other indications, or predict future epigenetic marker measurements of organ or tissue damage. This can be for a specific period or periods, or for residual life risk, or simply provided as an indicator relative to another reference population.

[0119] The actual model type or the equation itself used may be selected from the field of potential models based on its resulting performance and diagnostic accuracy characteristics in the training population. The details of the equation itself can generally be obtained from the marker results in the relevant training population. In particular, such an equation is intended to map a feature space obtained from one or more marker inputs to a set of target classes (e.g., useful for predicting whether a subject is normal, at risk of organ injury, or belongs to a class of subjects that respond / do not respond to treatment), to obtain an estimate of a probability function of a risk (e.g., the risk of organ injury or a recurrence event) using Bayesian methods, or to estimate class-conditional probabilities and then generate a class probability function using Bayes' rule.

[0120] Following the analysis and determination of an indicator of the presence or absence of organ injury or the probability of response to treatment, the indicator can be transmitted or provided to a third party, such as a physician for evaluation. The indicator can be used by the physician to evaluate whether additional diagnostic methods, such as biopsy and histological analysis and / or other assays, or a change in treatment or initiation of treatment is necessary.

[0121] The knowledge-based computer software and hardware for implementing the algorithms of the present disclosure also form part of the present disclosure. Accordingly, the present disclosure also provides software or hardware programmed to implement an algorithm that processes data obtained by performing the methods of the present disclosure via univariate or multivariate analysis to provide an injury indicator value and provide or permit the diagnosis of organ or tissue injury.

[0122] In one example, the method of the present disclosure can be used in an existing knowledge-based architecture or platform related to pathology services. For example, the results from the methods described herein are transmitted to a processing system via a communication network (e.g., the Internet), where algorithms are stored and used to generate a predicted posterior probability value that is converted into an indicator of the probability of damage, and then transferred to an end user in the form of a diagnostic or predictive report. Accordingly, the method of the present disclosure can be in the form of a kit or computer-based system that includes reagents necessary to detect the level of epigenetic marker(s) and computer hardware and / or software to facilitate the determination and transmission of reports to clinicians.

[0123] In some examples, the present disclosure enables the integration of assays into existing or specifically developed pathological structures or platform systems. For example, the present disclosure contemplates a method that enables a user to determine the state of a subject with respect to organ damage, the method comprising: (a) receiving sample epigenetic data in the form of the level of organ-specific epigenetic markers in cfDNA obtained from a biological sample of the subject compared to reference epigenetic data, optionally in combination with another marker of organ damage; (b) processing the sample epigenetic data via univariate and / or multivariate analysis to provide a damage indicator value; (c) comparing and determining the state of the subject according to the damage indicator value with a predetermined value; and (d) transferring an indicator of the state of the subject to the user via a communication network.

[0124] In some examples, the method further includes (i) using a remote end station to have a user determine data, and (ii) transferring data from the end station to a base station via a communication network. The base station may include first and second processing systems, in which case the method may include (a) transferring data to the first processing system, (b) transferring the data to the second processing system, and (c) causing the first processing system to perform univariate or multivariate analysis to generate a damage index value.

[0125] This method may also include (a) transferring the result of the univariate or multivariate analysis function to the first processing system, and (b) having the first processing system determine the state of the object.

[0126] Biological samples from which cfDNA can be obtained may include saliva, blood or serum or plasma, urine, semen, vitreous humor, lymph fluid, synovial fluid, follicular fluid, gastric juice, intestinal juice, bile, tumor fluid, interstitial fluid, amniotic fluid, mucus, breast milk, pleural effusion, sweat, tears, feces, serum or cerebrospinal fluid. Those skilled in the art will understand that other biological samples can be employed as a source of cfDNA. Methods for obtaining biological samples from a subject are known in the art and include, for example, surgery, biopsy, or collection of body fluids by, for example, puncture or thoracentesis, or collection of blood or a portion thereof. In some examples, the method of the present disclosure includes obtaining a biological sample containing cfDNA from a subject and, optionally, isolating cfDNA from the biological sample.

[0127] Preferably, the biological sample is liquid. Some biological samples may be more suitable than others for detecting damage to an organ or tissue depending on the particular organ or tissue in question. In some examples, urine is used as the biological sample for detecting kidney damage. In other examples, blood or plasma is used as the biological sample to detect heart damage.

[0128] DMR can be present in a biological sample of a healthy subject at a concentration of at least about 3.3 pg of single-stranded DNA / mL, such as at least about 4 pg / mL, or at least about 5 pg / mL, or at least about 10 pg / mL, or at least about 20 pg / mL, or at least about 30 pg / mL, or at least about 40 pg / mL, or at least about 50 pg / mL, or at least 75 pg / mL, or at least about 100 pg / mL, or at least about 125 pg / mL, or at least about 150 pg / mL, or at least about 175 pg / mL, or at least about 200 pg / mL, or at least about 225 pg / mL, or at least about 250 pg / mL, or at least about 275 pg / mL, or at least about 300 pg / mL, or at least about 325 pg / mL, or at least about 350 pg / mL, or at least about 375 pg / mL, or at least about 400 pg / mL, or at least about 425 pg / mL, or at least about 450 pg / mL, or at least about 475 pg / mL, or at least about 500 pg / mL, or at least about 525 pg / mL, or at least about 550 pg / mL, or at least about 575 pg / mL, or at least about 600 pg / mL, or at least about 625 pg / mL, or at least about 650 pg / mL.DMR can be present in a biological sample of a healthy subject at a concentration of at least about 1 copy / mL, such as at least about 5 copies / mL, or at least about 10 copies / mL, or at least about 15 copies / mL, or at least about 20 copies / mL, or at least about 25 copies / mL, or at least about 50 copies / mL, or at least about 75 copies / mL, or at least about 100 copies / mL, or at least about 150 copies / mL, or at least about 200 copies / mL, or at least about 250 copies / mL, or at least about 300 copies / mL, or at least about 350 copies / mL, or at least about 400 copies / mL, or at least about 450 copies / mL, or at least about 500 copies / mL, or at least about 600 copies / mL, or at least about 700 copies / mL, or at least about 800 copies / mL, or at least about 900 copies / mL, or at least about 1000 copies / mL.

[0129] In some examples, the proportion of cfDNA in a biological sample of a healthy subject corresponding to an epigenetic marker is 1%. For example, in the situation where the epigenetic marker is methylated DNA at locus A, about 1% of the DNA molecules at locus A in cfDNA are methylated. In some examples, the proportion of cfDNA in a biological sample of a healthy subject corresponding to a tissue- or organ-specific epigenetic marker is less than about 75%, such as less than about 70%, or less than about 65%, or less than about 60%, or less than about 55%, or less than about 50%, or less than about 45%, or less than about 40%, or less than about 35%, or less than about 30%, or less than about 25%, or less than about 20%, or less than about 15%, or less than about 10%, or less than about 5%, or less than about 1%, or less than about 0.1%. It is understood that the proportion of cfDNA corresponding to an epigenetic marker can be lower when the marker is cell-type specific or tissue-specific, and higher when the marker is organ-specific. It is also understood that the proportion of cfDNA corresponding to an epigenetic marker can increase in the presence of tissue or organ damage.

[0130] The method of the present disclosure Method 1. A method for diagnosing organ damage in a subject, the method comprising detecting an organ-specific epigenetic marker in cfDNA obtained from a biological sample of the subject, wherein the presence of the epigenetic marker in the cfDNA indicates organ damage.

[0131] Method 2. A method for detecting organ damage in a subject, the method comprising: a) obtaining a biological sample containing cfDNA from the subject; and b) detecting an organ-specific epigenetic marker in the cfDNA, wherein the presence of the epigenetic marker in the cfDNA indicates organ damage.

[0132] Method 3. The method according to Method 1 or Method 2, wherein the method comprises detecting an increase in the level of an epigenetic marker as compared to a reference level.

[0133] Method 4. The method according to Method 1 or Method 2, wherein the method comprises detecting an increase in the level of an epigenetic marker over time.

[0134] Method 5. The method according to any one of Methods 1 to 4, wherein the epigenetic marker is a DNA methylation state in a differential methylation region of the cfDNA.

[0135] Method 6. The method according to any one of Methods 1 to 5, wherein the method comprises detecting the cfDNA methylation state in more than one differential methylation region.

[0136] Method 7. The method according to Method 6, wherein the methylation state is determined in more than one differential methylation region using a multiplex assay.

[0137] Method 8. The method according to any one of Methods 5 to 7, wherein the methylation state is determined by a method that does not involve DNA sequencing.

[0138] Method 9. The method according to any one of Methods 5 to 8, wherein the methylation state is determined by treating the cfDNA with bisulfite and amplifying the differentially methylated region using polymerase chain reaction (PCR).

[0139] Method 10. The method according to Method 9, wherein the PCR is digital PCR (dPCR), digital droplet PCR (ddPCR) or quantitative PCR (qPCR).

[0140] Method 11. The method according to any one of Methods 1 to 10, wherein the subject and the organ are autologous.

[0141] Method 12. The method according to any one of Methods 1 to 11, wherein the organ is a kidney.

[0142] Method 13. The method according to any one of Methods 1 to 12, wherein the organ injury is associated with acute kidney injury, chronic kidney disease or kidney transplant rejection.

[0143] Method 20. The method according to any one of Methods 1 to 12, wherein the organ injury is associated with chemotherapy or radiotherapy.

[0144] Method 15. The method according to any one of Methods 1 to 14, wherein the biological sample is urine.

[0145] Method 16. The method according to any one of Methods 5 to 15, wherein the differentially methylated region is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D and SPAG5.

[0146] Method 17. The method according to any one of Methods 5 to 16, wherein the differentially methylated region is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L and PAX2.

[0147] Method 18. The method according to any one of Methods 5 to 17, wherein the differential methylation region comprises a sequence having at least 90% identity with any one or more of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 29 or SEQ ID NO: 30.

[0148] Method 19. The method according to any one of Methods 1 to 18, wherein the method specifically detects damage to a defined tissue or cell type of the organ.

[0149] Method 20. The method according to Method 19, wherein the defined cell type is a renal proximal tubular epithelial cell.

[0150] Method 21. The method according to Method 19 or Method 20, wherein the differential methylation region is located in at least one of MAST4 and DDC.

[0151] Method 22. The method according to any one of Methods 1 to 21, further comprising treating the subject for the organ damage.

[0152] Method 23. A method for diagnosing kidney damage in a subject, the method comprising detecting at least one differential methylation region of the kidney in cfDNA, the cfDNA being obtained from a biological sample of the subject, wherein the presence of the at least one differential methylation region of the kidney in the cfDNA indicates kidney damage.

[0153] Method 24. A method for detecting kidney damage in a subject, the method comprising: a) obtaining a biological sample containing cfDNA from the subject; and b) detecting at least one differential methylation region of the kidney in the cfDNA; wherein the presence of the at least one kidney-specific methylation site in the cfDNA indicates organ damage.

[0154] ​ Method 25. The method according to method 23 or method 24, wherein the method comprises detecting an increase in the level of the differential methylation region of the at least one kidney as compared to a reference level.

[0155] Method 26. The method according to method 23 or method 24, wherein the method comprises detecting an increase in the level of the differential methylation region of the at least one kidney over time.

[0156] Method 27. The method according to any one of methods 23 to 26, wherein the method comprises detecting the cfDNA methylation state in differential methylation regions of more than one kidney.

[0157] Method 28. The method according to method 27, wherein the methylation state is determined in differential methylation regions of more than one kidney using a multiplex assay.

[0158] Method 29. The method according to any one of methods 23 to 28, wherein the methylation state is determined by a method that does not involve DNA sequencing.

[0159] Method 30. The method according to any one of methods 23 to 29, wherein the methylation state is determined by treating the cfDNA with bisulfite and amplifying the differential methylation region of the at least one kidney using polymerase chain reaction (PCR).

[0160] Method 31. The method according to method 30, wherein the PCR is digital PCR (dPCR), digital droplet PCR (ddPCR) or quantitative PCR (qPCR).

[0161] Method 32. The method according to any one of methods 23 to 31, wherein the subject and the organ are autologous.

[0162] Method 33. The method according to any one of methods 23 to 32, wherein the kidney injury is associated with acute kidney injury, chronic kidney disease or kidney transplant rejection.

[0163] Method 34. The method according to any one of Methods 23 to 33, wherein the kidney injury is related to chemotherapy or radiotherapy.

[0164] Method 35. The method according to any one of Methods 23 to 34, wherein the biological sample is urine.

[0165] Method 36. The method according to any one of Methods 23 to 35, wherein the differential methylation region of the at least one kidney is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5.

[0166] Method 37. The method according to any one of Methods 23 to 36, wherein the differential methylation region of the at least one kidney is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2.

[0167] Method 38. The method according to any one of Methods 23 to 37, wherein the differential methylation region of the at least one kidney comprises a sequence having at least 90% identity with any one or more of SEQ ID NO: 1, SEQ ID NO: 8, SEQ ID NO: 15, SEQ ID NO: 22, or SEQ ID NO: 29.

[0168] Method 39. The method according to any one of Methods 23 to 38, wherein the method specifically detects damage to the defined tissue or cell type of the kidney.

[0169] Method 40. The method according to Method 39, wherein the defined cell type is renal proximal tubular epithelial cells.

[0170] Method 41. The method according to Method 39 or Method 40, wherein the differential methylation region of the at least one kidney is located at least in part in MAST4 and / or DDC.

[0171] Method 42. The method according to method 39 or method 40, wherein the differential methylation region of the at least one kidney is located in at least one of GRAMD1B and DDC.

[0172] Method 43. The method according to method 39 or method 40, wherein the differential methylation region of the at least one kidney is located in at least one of GRAMD1B, DDC, and PAX2.

[0173] Method 44. The method according to any one of methods 23 to 43, wherein the subject is a human.

[0174] Method 45. The method according to any one of methods 23 to 43, wherein the subject is a non-human.

[0175] Method 46. The method according to method 45, wherein the subject is a breeding animal.

[0176] Method 47. The method according to method 46, wherein the breeding animal is a companion animal.

[0177] Method 48. The method according to method 47, wherein the breeding animal is selected from the group consisting of sheep, cattle, horses, cats, dogs, pigs, and chickens.

[0178] Method 49. The method according to method 47, wherein the companion animal is selected from cats and dogs.

[0179] Method 50. The method according to any one of methods 23 to 43, wherein the method further comprises treating the subject for the kidney injury.

[0180] The present invention also includes the following method embodiments.

[0181] Method 51. A method for identifying at least one methylation region in cfDNA, the method comprising: (i) obtaining cfDNA from a subject; and (ii) treating the cfDNA with bisulfite to obtain bisulfite-converted cfDNA; (iii) identifying the at least one methylated region by PCR amplification of the bisulfite-converted cfDNA using primers that selectively amplify the at least one methylated region; comprising the method, wherein the at least one methylated region is a differentially methylated region that occurs in kidney cells.

[0182] The method according to method 51, identifying differentially methylated regions exceeding method 52.1.

[0183] The method according to method 51, identifying differentially methylated regions exceeding 1 using a multiplex assay.

[0184] The method according to any one of methods 51 to 53, wherein identifying at least one methylated region in the cfDNA is confirmed by DNA sequencing.

[0185] The method according to any one of methods 51 to 53, wherein the PCR is digital PCR (dPCR), digital droplet PCR (ddPCR) or quantitative PCR (qPCR).

[0186] The method according to any one of methods 51 to 55, wherein the at least one differentially methylated region is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360, chr17-35303285, DEF6, EMX1, HPD, PDE4D and SPAG5.

[0187] The method according to any one of methods 51 to 56, wherein the at least one differentially methylated region is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L and PAX2.

[0188] Method 58. The method according to any one of Methods 51 to 57, wherein the at least one differential methylation region comprises a sequence having at least 90% identity with any one or more of SEQ ID NO: 1, SEQ ID NO: 8, SEQ ID NO: 15, SEQ ID NO: 22, or SEQ ID NO: 29.

[0189] Method 59. The method according to any one of Methods 51 to 58, wherein the at least one differential methylation region is differentially methylated in renal proximal tubular epithelial cells.

[0190] Method 60. The method according to Method 59, wherein the at least one differential methylation region of the kidney is located in at least one of MAST4 and DDC.

[0191] Method 61. The method according to any one of Methods 51 to 60, wherein the at least one differential methylation region of the kidney is located in at least one of GRAMD1B and DDC.

[0192] Method 62. The method according to any one of Methods 51 to 60, wherein the at least one differential methylation region of the kidney is located in at least one of GRAMD1B, DDC, and PAX2.

[0193] Method 63. The method according to any one of Methods 51 to 62, wherein the subject is a human.

[0194] Method 64. The method according to any one of Methods 51 to 62, wherein the subject is a non-human.

[0195] Method 65. The method according to Method 64, wherein the subject is a domestic animal.

[0196] Method 66. The method according to Method 65, wherein the domestic animal is a companion animal.

[0197] Method 67. The method according to method 65, wherein the breeding animal is selected from the group consisting of sheep, cattle, horses, cats, dogs, pigs, and chickens.

[0198] Method 68. The method according to method 47, wherein the companion animal is selected from cats and dogs.

[0199] Method 69. The method according to any one of methods 23 to 43, wherein the method further comprises treating the subject for the kidney injury.

[0200] Method 70. A method for indicating to a user whether a subject has organ injury, the method comprising: a) generating sample epigenetic data by determining the level of an organ-specific epigenetic marker in cell-free DNA (cfDNA) obtained from a biological sample of the subject; b) the processor receiving the sample epigenetic data, the processor also receiving reference epigenetic data corresponding to the epigenetic marker; c) the processor generating differential epigenetic data by comparing the epigenetic data of the sample with the reference epigenetic data; d) the processor processing the differential epigenetic data to generate an injury index value; e) the processor determining the injury status of the subject based on the injury index value, the injury status indicating whether the subject has organ injury; f) transferring an indicator of the organ injury of the subject to the user via a communication network. The method comprising.

[0201] Method 71. The method according to method 70, wherein the organ injury is kidney injury, the organ-specific epigenetic marker is at least one differential methylation region of the kidney, the sample epigenetic data is sample methylation data, and the reference epigenetic data is reference methylation data.

[0202] Method 72. The method according to method 70 or method 71, wherein the sample methylation data is increased as compared with the reference methylation data.

[0203] Method 73. The method according to any one of methods 70 to 72, wherein the method includes detecting a temporal increase in the level of methylation data of the sample.

[0204] Method 74. The method according to any one of methods 70 to 73, wherein the methylation data of the sample includes the methylation state of cfDNA in differential methylation regions of more than one kidney.

[0205] Method 75. The method according to any one of method 74, wherein the methylation state is determined in differential methylation regions of more than one kidney using a multiplex assay.

[0206] Method 76. The method according to any one of methods 70 to 75, wherein the methylation data is determined by treating the cfDNA with bisulfite and amplifying the differential methylation region of the at least one kidney using polymerase chain reaction (PCR).

[0207] Method 77. The method according to method 76, wherein the PCR is digital PCR (dPCR), digital droplet PCR (ddPCR) or quantitative PCR (qPCR).

[0208] Method 78. The method according to any one of methods 70 to 77, wherein the subject and the kidney are autologous.

[0209] Method 79. The method according to any one of Methods 70 to 78, wherein the kidney injury is related to acute kidney injury, chronic kidney disease, or kidney transplant rejection or renal function replacement therapy.

[0210] Method 80. The method according to any one of Methods 70 to 79, wherein the kidney injury is related to chemotherapy or radiotherapy.

[0211] Method 81. The method according to any one of Methods 70 to 80, wherein the biological sample is urine.

[0212] Method 82. The method according to any one of Methods 71 to 81, wherein the differential methylation region of the at least one kidney is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5.

[0213] Method 82. The method according to any one of Methods 71 to 81, wherein the differential methylation region of the at least one kidney is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2.

[0214] Method 83. The method according to any one of Methods 71 to 81, wherein the differential methylation region of the at least one kidney comprises a sequence having at least 90% identity with any one or more of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 29, or SEQ ID NO: 30.

[0215] Method 84. The method according to any one of Methods 71 to 83, wherein the method specifically detects damage to a defined tissue or cell type of the kidney.

[0216] Method 84. The method according to any one of Methods 71 to 83, wherein the differential methylation region of the at least one kidney is located in at least one of MAST4 and DDC.

[0217] Method 85. The method according to any one of Methods 71 to 83, wherein the differential methylation region of the at least one kidney is located in at least one of GRAMD1B and DDC.

[0218] Method 86. The method according to any one of Methods 71 to 83, wherein the differential methylation region of the at least one kidney is located in at least one of GRAMD1B, DDC, and PAX2.

[0219] Method 87. The method according to any one of Methods 71 to 86, wherein the subject is a human.

[0220] Method 88. The method according to any one of Methods 71 to 87, wherein the subject is a non-human.

[0221] Method 89. The method according to Method 88, wherein the subject is a breeding animal.

[0222] Method 90. The method according to Method 89, wherein the breeding animal is a companion animal.

[0223] Method 91. The method according to Method 89, wherein the breeding animal is selected from the group consisting of sheep, cattle, horses, cats, dogs, pigs, and chickens.

[0224] Method 92. The method according to Method 91, wherein the companion animal is selected from cats and dogs.

[0225] Method 93. At least one nucleotide primer sequence or nucleotide probe sequence when used in any one of Methods 1 to 92 for detecting the differential methylation region of cfDNA in at least one kidney.

[0226] Method 94. The method of method 93, wherein the at least one nucleotide primer is two nucleotide primers when used in PCR to detect at least one differential methylation region of the kidney in cfDNA.

[0227] Use 1. Use of at least one differential methylation region of the kidney in cfDNA in the manufacture of a reagent for diagnosing kidney damage in a subject.

[0228] Use 2. The use according to use 1, wherein the reagent is at least one nucleotide primer or nucleotide probe, and in certain examples, two nucleotide primers configured to detect at least one differential methylation region of the kidney in cfDNA.

Example

[0229] Example Identification of epigenetic markers DNA methylation data from normal tissues and kidney cell types generated using Illumina's Infinium Human Methylation 450K or EPIC arrays were sourced from publicly available data including The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. A total of 1,643 samples were downloaded, processed, and collated. The details of the cohort are shown in Tables 13 and 14.

Table 13

Table 14

[0230] Using the TCGABiolinks function TCGAanalyze_DMC, DMRs were identified for hypermethylated regions. The average methylation difference between the whole kidney tissue and the whole of other tissue sources was determined. The p-value was estimated using the Wilcoxon test with Benjamini-Hochberg adjustment. Hypermethylated probes were identified using differential methylation differences greater than 0.25 with a false discovery rate (FDR)-adjusted Wilcoxon rank sum P-value of less than 0.01. The threshold for differential methylation was selected to enable the detection of DMRs driven by high methylation levels within a specific cell type. -0.5 For candidate CpG probes, methylation levels were plotted over a region within 5,000 base pairs (Figure 1). These plots included different renal cell types, including human renal proximal tubular epithelial cells (RPTECs), human cultured podocytes, and human renal cortical epithelial cells. These plots were individually scrutinized to create a shortlist based on separation between tissue types and large methylation differences between RPTECs and other tissues (Table 15).

[0231]

Table 15-1

Table 15-2

[0232] From the probes remaining on these final candidate lists, five of DDC, MAST4, PAX2, MCF2L, and GRAMD1B were used to design methylation-specific PCR assays.

[0233] Detection of DNA methylation status According to the manufacturer's instructions, cfDNA was extracted from biological samples (plasma, urine, tissue, etc.) using the QIAamp Circulating Nucleic Acid Kit (Qiagen, catalog number 55114). The eluted DNA was then bisulfite-converted using the EZ DNA Methylation-Lightning Kit (Zymo, catalog number D5030) or the EpiTect Fast DNA Bisulfite Kit (Qiagen, catalog number 59824) according to the manufacturer's instructions. The resulting bisulfite-converted DNA was analyzed using a qPCR or dPCR assay designed to amplify one or more target strands of the following targets: PAX2 (SEQ ID NOs: 5-7), GRAMD1B (SEQ ID NOs: 12-14), DDC (SEQ ID NOs: 19-21), MAST4 (SEQ ID NOs: 26-28), or MCF2L (SEQ ID NOs: 33-35). ACTB amplification was also used as a control to ensure that extraction (SEQ ID NOs: 38-40 for detection of the native ACTB sequence) or bisulfite conversion and PCR (SEQ ID NOs: 43-45 for detection of the bisulfite-converted ACTB sequence) functioned. The qPCR reaction was composed to a final volume of 15 μL containing 7.5 μL of GoTaq Hot Start Colourless master mix, 2 mM MgCl2, 200 nM of each forward and reverse primer, 100 nM of a fluorescently labeled hydrolysis probe, and template DNA, and this was cycled on a QuantStudio7 real-time PCR system (ThermoFisher) as follows: 95°C for 2 minutes; [95°C for 15 seconds; 62°C for 30 seconds, 72°C for 30 seconds (for acquisition)] × 50; 40°C for 10 seconds. For digital PCR, the reaction was composed to a final volume of 40 μL containing 10 μL of QIAcuity probe PCR mix (Qiagen, catalog number 250103), 800 nM of each forward and reverse primer, 400 nM of a fluorescently labeled hydrolysis probe, and template DNA, and this was cycled on a QIAcuity 4 plate digital PCR system (Qiagen) as follows: 95°C for 2 minutes [95°C for 15 seconds; 61°C for 30 seconds (for acquisition)] × 40.

[0234] The following sections show the DMRs, as well as the sequences of the primers and probes, used to determine the methylation status in these DMRs (based on hg19).

[0235] Human Chr10(+): 102,505,468 - 102,590,402 - Paired box 2 (PAX2) gene; NM_000278.5 Chr10(+): 102,586,126 - 102,588,109 - CpG island where the PAX2 amplicon target is present.

[0236] Chr10(+): 102,587,777 - 102,587,835 - Native sequence (59bp) of the PAX2 PCR assay region. The sequences of the top strand (SEQ ID NO: 1) and bottom strand (SEQ ID NO: 2) of the PCR assay region are shown in Figure 2A.

[0237] The sequences of the bisulfite - converted methylation top strand (SEQ ID NO: 3) and PCR - generated complementary strand (SEQ ID NO: 4) are shown in Figure 2B. The forward and reverse primers, as well as the oligonucleotide probes, used to detect the bisulfite - converted methylated DNA are listed in Table 16.

Table 16

[0238] Human Chr11(+): 123,229,130 - 123,498,475 - GRAM domain - containing 1B (GRAMD1B) gene; NM_001367420 Chr11(+): 123,301,050 - 123,302,149 - CpG island where the GRAMD1B amplicon target is present.

[0239] Chr11(+): 123,301,149 - 123,301,216 - Native sequence (67bp) of the GRAMD1B PCR assay region. The sequences of the top strand (SEQ ID NO: 8) and bottom strand (SEQ ID NO: 9) of the PCR assay region are shown in Figure 3A.

[0240] The sequences of the bisulfite-converted methylated top strand (SEQ ID NO: 10) and the PCR-generated complementary strand (SEQ ID NO: 11) are shown in Figure 3B. The forward primer, reverse primer, and oligonucleotide probe used to detect bisulfite-converted methylated DNA are listed in Table 17. [Table 17]

[0241] Human Chr7(+): 50,526,140 - 50,633,102 - dopa decarboxylase (DDC) gene; NM_001082971.2 CpG island where the Chr7(+): 50,535,741 - 50,535,953 - DDC amplicon is present.

[0242] Chr7(+): 50,535,754 - 50,535,837 - natural sequence (84bp) of the DDC PCR assay region. The sequences of the top strand (SEQ ID NO: 15) and the bottom strand (SEQ ID NO: 16) of the PCR assay region are shown in Figure 4A.

[0243] The sequences of the bisulfite-converted methylated top strand (SEQ ID NO: 17) and the PCR-generated complementary strand (SEQ ID NO: 18) are shown in Figure 4B. The forward primer, reverse primer, and oligonucleotide probe used to detect bisulfite-converted methylated DNA are listed in Table 18. [Table 18]

[0244] Human Chr5(+): 65,892,221 - 66,465,421 - member 4 of the microtubule-associated serine / threonine kinase family (MAST4) gene; NM_001164664.2 CpG island where the Chr5(+): 66,299,769 - 66,300,083 - MAST4 amplicon target is present.

[0245] Chr5(+): 66,299,953 - 66,300,019 - Natural sequence of the MAST4 PCR assay region (67 bp). The sequences of the top strand (SEQ ID NO: 22) and the bottom strand (SEQ ID NO: 23) of the PCR assay region are shown in Figure 5A.

[0246] The sequences of the bisulfite - converted methylated top strand (SEQ ID NO: 24) and the PCR - generated complementary strand (SEQ ID NO: 25) are shown in Figure 5B. The forward primer, reverse primer, and oligonucleotide probe used to detect bisulfite - converted methylated DNA are listed in Table 19.

Table 19

[0247] Human Chr13(+): 113,623,528 - 113,754,056 - Transformed sequence - like (MCF2L) gene derived from the MCF.2 cell line; NM_001112732.3 Chr13(+): 113,622,738 - 113,623,660 - CpG island where the MCF2L amplicon target is present.

[0248] Chr13(+): 113,623,573 - 113,623,646 - Natural sequence of the MCF2L PCR assay region (74 bp). The sequences of the top strand (SEQ ID NO: 29) and the bottom strand (SEQ ID NO: 30) of the PCR assay region are shown in Figure 6A.

[0249] The sequences of the bisulfite - converted methylated top strand (SEQ ID NO: 31) and the PCR - generated complementary strand (SEQ ID NO: 32) are shown in Figure 6B. The forward primer, reverse primer, and oligonucleotide probe used to detect bisulfite - converted methylated DNA are listed in Table 20.

Table 20

[0250] Human Chr7(-): 5,566,779 - 5,570,232 (+2kb upstream region → 5,566,779 - 5,572,232) - ACTB gene; NM_001101 Chr7(-): 5,571,726 - 5,571,859 - Target region (134bp) of the PCR assay used to quantify the yield of genomic DNA. The amplicon is located in the promoter region +2kb upstream. The sequences of the top strand (SEQ ID NO: 36) and the bottom strand (SEQ ID NO: 37) of the PCR assay region are shown in Figure 7A. The forward primer, reverse primer, and oligonucleotide probe used to detect the ACTB sequence are listed in Table 21.

Table 21

[0251] Bottom strand bisulfite conversion sequence of the genomic region located at Chr7(+): 5,572,176 - 5,572,265 (89bp). The sequences of the top strand (SEQ ID NO: 41) and the bisulfite-converted bottom strand (SEQ ID NO: 42) generated by PCR are shown in Figure 7B. The forward primer, reverse primer, and oligonucleotide probe used to detect the bisulfite-converted methylated DNA are listed in Table 22.

Table 22

[0252] Tissue specificity Loci that are differentially methylated in kidney cells / tissues compared to blood and other tissues were identified by bioinformatics, and specific primers and probes were designed for these regions as described above. Several different assays were designed for each of the 5 DMRs and these were tested analytically to identify the assay with the best performance for each DMR (SEQ ID NOs: 1 - 35).

[0253] To confirm the specificity of these assays, DNA from 14 different tissue types including fat, adrenal gland, brain, breast, colon, heart, kidney, liver, lung, pancreas, skeleton, skin and spleen, as well as commercially supplied completely unmethylated DNA (CpGenome universal unmethylated DNA, Sigma, catalog number S7822) and human genomic DNA from buffy coat (PBMC, Sigma, catalog number 11691112001) were bisulfite converted using the EZ DNA Methylation-Lightning kit (Zymo, catalog number D5030) or the EpiTect Fast DNA Bisulfite kit (Qiagen, catalog number 59824) according to the manufacturer's instructions. Five nanograms each of bisulfite-converted DNA from each tissue type, bisulfite-converted unmethylated DNA, bisulfite-converted PBMC DNA and native PBMC DNA were amplified in quadruplicate by qPCR using primers and probes specific for PAX2 (SEQ ID NOs: 5-7), GRAMD1B (SEQ ID NOs: 12-14), DDC (SEQ ID NOs: 19-21), MAST4 (SEQ ID NOs: 26-28) or MCF2L (SEQ ID NOs: 33-35). ACTB amplification was also used as a control for quantifying native total DNA (SEQ ID NOs: 38-40) or bisulfite-converted total DNA (SEQ ID NOs: 43-45). Standard curves for each assay were prepared by amplifying quadruplicate 2.5-fold serial dilutions of bisulfite-converted fully methylated DNA (Zymo, catalog number D5011) from 5000 pg / reaction to 8.2 pg / reaction, or from 500 copies / reaction to 0.82 copies / reaction, and these were used to calculate the amount of DNA amplified for each gene.The qPCR reaction consisted of 7.5 μL of GoTaq Hot Start Colourless master mix, 2 mM MgCl2, 200 nM of each forward and reverse primer, 100 nM of a fluorescently labeled hydrolysis probe, and template DNA, made up to a final volume of 15 μL, which was cycled on a QuantStudio 7 real-time PCR system (ThermoFisher) as follows: 95°C for 2 min; [95°C for 15 s; 62°C for 30 s, 72°C for 30 s (for acquisition)] × 50; 40°C for 10 s.

[0254] Figure 8 shows the results of a representative assay designed for each of the five DMR genes assayed. Each assay was found to strongly detect kidney DNA as well as some low-level positives in several other tissues. Typically, this off-target amplification is less than 1% of the target amplification, and occasional samples are higher than this, but with a typical yield of approximately 10 ng / mL plasma or 5 ng / mL urine for total cfDNA, and this low-level positivity is generally not important when applied to this cfDNA scenario where only a portion of this is derived from these organs / tissues excluding the liver.

[0255] Sensitivity of differential methylation assays in plasma from putative healthy donors Next, to determine whether there is a background signal, five selected assays were tested in plasma obtained from presumptively healthy individuals under 30 years of age. cfDNA from two aliquots of 3 mL plasma was extracted using the QIAamp Circulating Nucleic Acid Kit (Qiagen, catalog number 55114) according to the manufacturer's instructions. DNA eluted from two aliquots of each sample was combined and then bisulfite-converted using the EZ DNA Methylation-Lightning Kit (Zymo, catalog number D5030) or the EpiTect Fast DNA Bisulfite Kit (Qiagen, catalog number 59824) according to the manufacturer's instructions. The amount of bisulfite-converted DNA corresponding to 1 mL of plasma was analyzed in triplicate by qPCR for each assay targeting PAX2 (SEQ ID NOs: 5-7), GRAMD1B (SEQ ID NOs: 12-14), DDC (SEQ ID NOs: 19-21), MAST4 (SEQ ID NOs: 26-28), or MCF2L (SEQ ID NOs: 33-35). To demonstrate that extraction, bisulfite conversion, and PCR were functional, and also to determine the total amount of amplifiable DNA regardless of methylation status, ACTB (SEQ ID NOs: 43-45) was also amplified as a control. Standard curves for each assay were prepared by amplifying quadruplicates of 2.5-fold serial dilutions of bisulfite-converted fully methylated DNA (Zymo, catalog number D5011) from 5000 pg / reaction to 8.2 pg / reaction, or from 500 copies / reaction to 0.82 copies / reaction, and these were used to calculate the amount of DNA amplified for each gene. The qPCR reaction mixture consisted of 7.5 μL of GoTaq Hot Start Colourless master mix, 2 mM MgCl2, 200 nM of each forward and reverse primer, 100 nM of a fluorescently labeled hydrolysis probe, and template DNA, made up to a final volume of 15 μL, and this was cycled on a QuantStudio7 real-time PCR system (ThermoFisher) as follows: 95°C for 2 minutes; [95°C for 15 seconds; 62°C for 30 seconds, 72°C for 30 seconds (for acquisition)] × 50; 40°C for 10 seconds.

[0256] Figure 9 shows that for any of the kidney-specific assays in plasma, little signal was obtained, and when signal was detected, the % of total kidney cfDNA was typically 0.1% or less. Only GRAMD1B gave a higher signal than this in only one sample (1.26% of total kidney cfDNA). Since these samples were from putative healthy donors rather than individuals confirmed to have no kidney disease, donor HMN569764 may have had a kidney condition underlying the low-level positivity seen in 3 out of the 5 markers tested.

[0257] Sensitivity of differential methylation assays in urine from putative healthy donors Next, the five selected assays were tested with urine obtained from 20 apparently healthy individuals aged 26 to 61 years to determine whether there was a background signal. cfDNA from two aliquots of 3 mL of urine was extracted using the QIAamp Circulating Nucleic Acid Kit (Qiagen, catalog number 55114) according to the manufacturer's instructions. DNA eluted from two aliquots of each sample was combined and then bisulfite converted using the EZ DNA Methylation-Lightning Kit (Zymo, catalog number D5030) or the EpiTect Fast DNA Bisulfite Kit (Qiagen, catalog number 59824) according to the manufacturer's instructions. The amount of bisulfite-converted DNA corresponding to 1 mL of urine was analyzed by dPCR for each assay targeting PAX2 (SEQ ID NOs: 5-7), GRAMD1B (SEQ ID NOs: 12-14), DDC (SEQ ID NOs: 19-21), MAST4 (SEQ ID NOs: 26-28), or MCF2L (SEQ ID NOs: 33-35). To demonstrate that extraction, bisulfite conversion, and PCR were functional and also to determine the total amount of amplifiable DNA regardless of methylation status, ACTB (SEQ ID NOs: 43-45) was also amplified as a control. The dPCR reaction mixture consisted of 10 μL of QIAcuity probe PCR mix (Qiagen, catalog number 250103), 800 nM of each forward and reverse primer, 400 nM of a fluorescently labeled hydrolysis probe, and template DNA, made up to a final volume of 40 μL, which was cycled on a QIAcuity 4 plate digital PCR system (Qiagen) as follows: 95°C for 2 minutes [95°C for 15 seconds; 61°C for 30 seconds (for acquisition)] × 40.

[0258] Figure 10 shows that the situation is completely different in urine compared to plasma. All differentially methylated loci are strongly amplified and contribute a significant amount of signal (mostly about 1 - 20%) compared to total kidney cfDNA. Since these samples were obtained from patients of various ages, the inventors investigated whether there is a correlation with age and the increasing signal and found that this is indeed the case, especially when considering the signal as a percentage of total cfDNA. An increase in the amount or proportion of kidney-specific cfDNA may indicate acute kidney injury or chronic kidney disease and may indicate a decline in renal function associated with aging.

[0259] Sensitivity of kidney-specific PCR with low DNA input The sensitivity of each of the five kidney-specific assays was evaluated with a devised sample containing very low concentrations of fully methylated bisulfite-converted DNA (Zymo, catalog number D5011). The fully methylated DNA was bisulfite-converted using the EZ DNA Methylation-Lightning Kit (Zymo, catalog number D5030) or the EpiTect Fast DNA Bisulfite Kit (Qiagen, catalog number 59824) according to the manufacturer's instructions. The eluted DNA was quantified by dPCR using the ACTB assay (SEQ ID NOs: 43-45) and subsequently diluted in 1 ng / mL cRNA as a stabilizer such that each PCR well contained amplifiable DNA at 0.17 copies. For each kidney-specific assay containing 320 or 343 wells of low-concentration bisulfite-converted methylated DNA, 384-well qPCR plates were set up, and a standard curve for each assay was prepared by amplifying four replicates of 2.5-fold serial dilutions of bisulfite-converted fully methylated DNA (Zymo, catalog number D5011) from 5000 pg / reaction to 8.2 pg / reaction, or from 500 copies / reaction to 0.82 copies / reaction. The qPCR reactions for each assay targeting PAX2 (SEQ ID NOs: 5-7), GRAMD1B (SEQ ID NOs: 12-14), DDC (SEQ ID NOs: 19-21), MAST4 (SEQ ID NOs: 26-28), or MCF2L (SEQ ID NOs: 33-35) consisted of 7.5 μL of GoTaq Hot Start Colourless master mix, 2 mM MgCl2, 200 nM of each forward and reverse primer, 100 nM of a fluorescently labeled hydrolysis probe, and template DNA, and were assembled to a final volume of 15 μL, which was cycled on a QuantStudio7 real-time PCR system (ThermoFisher) as follows: 95°C for 2 minutes; [95°C for 15 seconds; 62°C for 30 seconds, 72°C for 30 seconds (for acquisition)] × 50; 40°C for 10 seconds. Three consecutive wells were combined to emulate a triplicate-tested sample. Thus, when the assay is performed optimally, individual replicate positives are expected to be 17% and sample positives to be approximately 50%. Table 23 shows that all of these assays are functioning almost completely.

Table 23

[0260] Detection of kidney-specific cfDNA in kidney transplant patients DNA was extracted from 57 clinical specimens collected from 25 kidney transplant patients at various time points before and after kidney transplantation. When available, DNA from an amount corresponding to 1 mL of plasma for each time point was extracted using the QIAamp Circulating Nucleic Acid Kit (Qiagen, catalog number 55114) according to the manufacturer's instructions. The eluted DNA was then bisulfite-converted using the EZ DNA Methylation-Lightning Kit (Zymo, catalog number D5030) or the EpiTect Fast DNA Bisulfite Kit (Qiagen, catalog number 59824) according to the manufacturer's instructions. The resulting bisulfite-converted DNA was analyzed using qPCR or dPCR assays designed to amplify the target strands of the following targets: PAX2 (SEQ ID NOs: 5-7), GRAMD1B (SEQ ID NOs: 12-14), and DDC (SEQ ID NOs: 19-21). To ensure that extraction, bisulfite conversion, and PCR functioned, ACTB (SEQ ID NOs: 43-45) amplification was also used as a control. The qPCR reaction consisted of 7.5 μL of GoTaq Hot Start Colourless master mix, 2 mM MgCl2, 200 nM of each forward and reverse primer, 100 nM of a fluorescently labeled hydrolysis probe, and template DNA, made up to a final volume of 15 μL, which was cycled on a QuantStudio 7 real-time PCR system (ThermoFisher) as follows: 95°C for 2 minutes; [95°C for 15 seconds; 62°C for 30 seconds, 72°C for 30 seconds (for acquisition)] × 50; 40°C for 10 seconds. For digital PCR, the reaction consisted of 10 μL of QIAcuity probe PCR mix (Qiagen, catalog number 250103), 800 nM of each forward and reverse primer, 400 nM of a fluorescently labeled hydrolysis probe, and template DNA, made up to a final volume of 40 μL, which was cycled on a QIAcuity 4 plate digital PCR system (Qiagen) as follows: 95°C for 2 minutes [95°C for 15 seconds; 61°C for 30 seconds (for acquisition)] × 40.

[0261] When the copy number per mL of plasma per sample at each time point was examined, the results showed that there was significantly more total cfDNA present in the samples collected after transplantation compared to ACTB at 437.5 c / mL before transplantation (mean = 1190 c ACTB / mL at 24 hours and 3849 c / mL at 168 hours after transplantation) (Figure 11). This difference is more pronounced when comparing kidney-specific cfDNA concentrations. PAX2 had mean concentrations of 0.34 c / mL before transplantation, 12.08 c / mL at 24 hours, and 0 c / mL at 168 hours, GRAMD1B had mean concentrations of 0.51 c / mL before transplantation, 8.47 c / mL at 24 hours, and 0 c / mL at 168 hours, and DDC had mean concentrations of 0.88 c / mL before transplantation, 3.67 c / mL at 24 hours, and 6.51 c / mL at 168 hours. In relation to the low levels of kidney-specific cfDNA detectable before transplantation, these patients were generally in renal failure and had no functional kidneys remaining before transplantation. The levels of cfDNA detected are typically highest within 24 hours after transplantation and begin to return to baseline levels by day 7. These results are consistent with those using donor-derived cfDNA to monitor transplantation. PAX2 provides the highest level of signal, at 1 - 1.2% of total cfDNA, within 24 hours after transplantation.

[0262] Identification of the Specificity of Biomarkers Derived from Different Renal Cell Types Cell-specific biomarkers: Cell-specific data is not very abundant in the public domain. To identify differentially methylated regions in cells within the kidney, a 0.25 methylation difference cutoff was used to identify low-level differentially methylated regions across the kidney tissue, which were then further evaluated in cell-specific data to determine the methylation rates in these specific cell types. Data was obtained for renal proximal tubule epithelial cells (31 samples from human subjects GSE115227, GSE145745, and GSE126441), human cultured podocytes (2 samples from human subject GSE41689), and human renal cortical epithelial cells (1 sample from human subject GSE126441). These cell types were selected to evaluate the methylation status of the identified probes that showed low-level methylation as shown in Figure 12.

[0263] As shown in Figure 12, PAX2 (cg23206032) was found to be highly methylated in all cell types and was the only region developed for positive PCR in renal cortical epithelial cells. Both DDC and MAST4 were specific to renal proximal tubule epithelial cells (RPTEC). Considering the important role of RPTEC in kidney function, including the reabsorption of water, electrolytes, and nutrients, this could be advantageous for the early detection of injury and prognostic diagnosis. MCF2L and GRAMD1B had a similar profile to DDC and MAST4 but showed methylation in podocytes.

[0264] Development of PCR assays For all five regions, namely GRAMD1B, DDC, MAST4, MCF2L, PAX2 (Panel A, Figures 23 - 27), several methylation - specific PCR primers and probes were designed. Each assay was evaluated by repeating it more than 4 times with 2.5 - fold serial dilutions of bisulfite - converted methylated DNA (Zymo D5011) from 500 cps / rxn to 0.82 cps / rxn. Ct = 50 indicates a failed amplification (Panel B, Figures 23 - 27). Specificity was evaluated using bisulfite - converted unmethylated DNA (hypomethylated placental DNA; bis UM)) and bisulfite - converted (bis PBMC) or native peripheral blood mononuclear cell DNA (WT PBMC) (Panel C, Figures 23 - 27). Assay designs with amplification up to at least 12.8 cps / rxn with no or minimal detection of bisulfite - converted unmethylated DNA or PBMC DNA were selected for further evaluation. Next, the assay designs were tested in a panel of 15 normal tissues (Panel C, Figures 23 - 27). DNA obtained from these tissue types was added at 5 ng / rxn and evaluated by digital PCR with at least 4 repeats. ND indicates not done, and the blank well indicates no amplification in any of the replicates. As shown in Figure 14, the observed profiles were similar to the array data with exceptional specificity for DNA extracted from whole kidney tissue. Triplex assays were prepared for PAX2, DDC, and GRAMD1B. Preferred PCR designs for detecting differentially methylated regions in the human kidney are included in Figures 23 - 27 and Tables 12, 16 - 20.

[0265] Comparison of kidney - specific methylation biomarkers in urine samples from subjects with various stages of CKD. The kidney-specific methylation biomarkers PAX2, GRAMD1B, and DDC were detected in urine samples using the above dPCR methodology (Figure 15), and all of PAX2, GRAMD1B, and DDC showed statistically significant differences (p-values = 0.0409, 0.0020, and 0.0033, respectively). Patients were classified based on eGFR determined using the CKD-EPI 2021 formula. The results from PAX2 were significantly different from those of GRAMD1B and DDC, with the latter being better representations of renal proximal tubule epithelial cells (RPTEC), offering the potential for early detection of CKD and prediction of renal function decline. In particular, lower levels of DNA were detected for DDC and GRAMD1B compared to PAX2.

[0266] Comparison of kidney-specific methylation biomarkers in urine samples from healthy patients and subjects before and after heart transplantation surgery Urine samples were collected from a presumed healthy adult cohort with no known kidney disease and patients before and after heart transplantation surgery. Post-transplant samples were divided into two groups: a group with severe AKI within 48 hours after surgery and a group without postoperative AKI or with moderate AKI. Classification was determined based on the RIFLE criteria of the fold change in creatinine from baseline. ACTB is a measure of total cfDNA and shows increased levels in heart transplant patients after severe AKI surgery (see Figure 16). Thus, renal cfDNA release as a result of injury increased total cfDNA in urine. However, the levels of total cfDNA measurements lack specificity and do not distinguish between increases in cfDNA due to other biological variabilities, including exercise, inflammation, and infection.

[0267] The first postoperative sample had a marked increase in PAX2, which was evident before any detectable change in creatinine (see Figures 18 and 19). Tubule-specific markers (GRAMD1B and DDC) provided a different profile, with a slight increase in marker concentration in samples postoperatively (within 24 hours), but large variability in preoperative samples. These markers also increased in patients with CKD, consistent with Figure 15. This suggests that GRAMD1B and DDC markers provide insight into renal frailty and may predict patient outcomes such as postoperative AKI or CKD-related renal function decline.

[0268] Comparison of kidney-specific methylation biomarkers in plasma from healthy patients and subjects before and after heart transplantation surgery As shown in Figure 17, only a very small number of samples from the healthy cohort and pre-operative samples had detectable kidney DNA in plasma. After heart transplantation, 3 out of 10 patients had detectable plasma kidney differential methylation cfDNA at multiple time points (see Figures 18 and 19 for example). In these examples, using only 1 mL of plasma, increasing the sample input volume while further optimizing assay performance may improve sensitivity. Furthermore, the discrepancy between plasma and urine suggests the potential utility of plasma in the identification of diverse injuries and disease types via the release of kidney cfDNA from various pathophysiologies. This has promising implications for improving patient selection and stratification in therapeutic applications.

[0269] Serial hourly testing of methylation biomarker comparison in urine from patients 1 and 10 after heart transplantation Biomarker values were generated using dPCR as described above. Figures 18A - D show total cfDNA (A) and kidney-specific cfDNA (B - D) in both urine (left y-axis) and plasma (right y-axis). Figure E shows creatinine (μmol / mL), eGFR (ml / min / 1.73m using a rolling 6-hour average based on hourly readings 2Provide standard treatment markers for patients including creatinine (mg / dL) and urine output (mL). The time on the x-axis for all plots is the time since surgery. As shown in Figure E, the patient had a rapid increase in creatinine with an increase more than 3-fold above the postoperative baseline, accompanied by a decrease in urine output. The urine output returned to normal levels within 24 hours, but the high creatinine persisted until 9 days postoperatively (data not shown). Total cfDNA (Figure 18A) increased dramatically in both urine and plasma (from 815 cps / mL and 813 cps / mL at baseline to 5,928 cps / mL and 225,884 cps / mL in urine and plasma respectively), but decreased rapidly within 24 hours, providing little insight into the damage within the kidney. The kidney-wide cfDNA marker PAX2 increased in urine immediately after surgery (5,928 cps / mL urine) 10 hours before the baseline (226 cps / mL urine), after which creatinine increased to 2.14 times the baseline and more than tripled after 33 hours. The corresponding matched blood samples for PAX2 were low for the first sample but very elevated for the second sample when urinary PAX2 cfDNA was decreasing. This indicates that urine is the primary sample for early detection and that the release of kidney cfDNA into plasma is delayed. This also indicates that although total cfDNA increases dramatically in plasma after surgery, this does not contain kidney cfDNA and thus total cfDNA is an inadequate marker for the assessment of kidney damage. Tubule-specific (DDC) and tubule / podocyte-specific (GRAMD1B) markers in cfDNA were low until the second sample (about 24 hours after surgery), indicating a delay in the release of tubule DNA after injury and may represent acute tubular necrosis. From this sample, the tubule-specific cfDNA concentration remained elevated and irregular and could be a predictor of long-term kidney damage. The levels seen in Patient 1 are only repeated in patients receiving dialysis in the ICU. Before surgery, this patient was classified as stage 2 CKD (eGFR = 79.1 ml / min / 1.73m 2 ) but had elevated kidney cfDNA in the preoperative urine sample (226, 154, 50 cps / mL for PAX2, GRAMD1B, and DDC respectively).

[0270] The same assay conditions described for Patient 1 were also performed for Patient 10 (there is no urinary excretion data for Patient 10 shown in Figure 19). Patient 10 received hemodiafiltration while in the ICU. Patient 10 also showed an increase in PAX2 post - operatively (1,904 cps / mL urine) compared to the pre - operative sample (1,245 cps / mL urine). During hemodiafiltration, when low urinary output is expected, renal - specific cfDNA increases rapidly. This has been observed in all patients who received hemodiafiltration while in the ICU and is independent of urinary output. This indicates that renal cell death is occurring during hemodiafiltration and that tubular cell death is also occurring. Without cell - specific markers, it is impossible to determine whether this damage was occurring within the tubular cells, but it is clear that the damage is clinically significant. The identification of kidney injury occurring within RPTECs is clinically significant for several reasons. RPTECs play an important role in renal function, including the reabsorption of essential substances and the maintenance of electrolyte balance. Damage to RPTECs can disrupt these important functions, leading to renal dysfunction and potentially contributing to the development or progression of kidney disease.

[0271] By determining whether the observed damage is occurring specifically within RPTECs, clinicians can gain insights into the underlying mechanisms and pathophysiology of kidney injury. This knowledge can help guide treatment strategies and interventions aimed at maintaining RPTEC function and promoting renal recovery. The identification of RPTEC damage also provides important diagnostic and prognostic information. It serves as an indicator of the severity and extent of kidney injury and can help predict the likelihood of adverse outcomes or complications. This information is extremely important for patient management, including making appropriate treatment decisions, monitoring disease progression, and evaluating the effectiveness of interventions aimed at maintaining renal function.

[0272] PAX2 amplification in cats. Oligonucleotides were designed for feline PAX2 in two different regions having substantial sequence identity with the sequences of the human PAX2 marker. These oligonucleotides are shown in Table 12 as SEQ ID NO:50, SEQ ID NO:51, and SEQ ID NO:52 (assay PAX2-A), and SEQ ID NO:57, SEQ ID NO:58, and SEQ ID NO:59 (assay PAX2-B).

[0273] An alignment of the relevant sequences is shown in FIG. 22. The subsequent dPCR assay was tested on bisulfite-converted cfDNA extracted from 1 mL of urine from 5 cats, namely 2 healthy cats, and 3 cats with known CKD. The dPCR reaction consisted of 10 μL of QIAcuity probe PCR mix (Qiagen, catalog number 250103), 800 nM of each forward and reverse primer, 400 nM of a fluorescently labeled hydrolysis probe, and template DNA, made up to a final volume of 40 μL, which was cycled on a QIAcuity 4 plate digital PCR system (Qiagen) as follows: 95° C., 2 minutes [95° C., 15 seconds; 60° C., 30 seconds (for acquisition)]×40.

[0274] The results demonstrate that for both PAX2 assays, there is a significant increase in the amount of PAX2 detected in the urine of those cats with CKD compared to healthy cats (see FIG. 20). The results of this experiment show the usefulness of using differentially methylated regions to detect kidney-specific cfDNA in different animal species.

[0275] It will be understood by those skilled in the art that the present disclosure may be embodied in many other forms.

Claims

1. A method for detecting at least one differential methylation region of the kidney in cfDNA as an indicator of kidney damage in a subject, wherein the method comprises detecting the at least one differential methylation region of the kidney in the cfDNA, the cfDNA is obtained from a biological sample of the subject, and the presence of the at least one differential methylation region of the kidney in the cfDNA indicates kidney damage.

2. A method for detecting at least one differential methylation region of the kidney in cfDNA as an indicator of kidney damage in a subject, wherein the method is To detect at least one differential methylation region of the kidney in the cfDNA. The cfDNA is obtained from a biological sample containing the cfDNA from the subject, A method in which the presence of at least one kidney-specific methylation site in the cfDNA indicates organ damage.

3. The method according to claim 1, wherein the method includes detecting an increase in the level of the differential methylation region of at least one kidney compared to a reference level.

4. The method according to claim 1, wherein the method includes detecting a time-dependent increase in the level of differential methylation regions in at least one kidney.

5. The method according to claim 1, wherein the method includes detecting the cfDNA methylation status in one or more differential methylation regions of the kidney.

6. The method according to claim 5, wherein the methylation state is determined by a multiplex assay using one or more differentially methylated regions of the kidney.

7. The method according to claim 1, wherein the methylation state is determined by a method that does not involve DNA sequencing.

8. The method according to claim 1, wherein the methylation state is determined by treating the cfDNA with a bisulfite and amplifying the differential methylation region of at least one kidney using polymerase chain reaction (PCR).

9. The method according to claim 8, wherein the PCR is digital PCR (dPCR), digital droplet PCR (ddPCR), or quantitative PCR (qPCR).

10. The method according to claim 1, wherein the subject and the kidney are of autologous origin.

11. The method according to claim 1, wherein the kidney injury is related to acute kidney injury, chronic kidney disease, or kidney transplant refusal or renal function replacement therapy.

12. The method according to claim 1, wherein the kidney injury is related to chemotherapy or radiotherapy.

13. The method according to claim 1, wherein the biological sample is urine.

14. The method according to claim 1, wherein the at least one differential methylation region of the kidney is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, PAX2, chr12-122277360 (CLIP1), chr17-35303285, DEF6, EMX1, HPD, PDE4D, and SPAG5.

15. The method according to claim 5, wherein the at least one differential methylation region of the kidney is located at one or more loci selected from the group consisting of GRAMD1B, DDC, MAST4, MCF2L, and PAX2.

16. The method according to claim 1, wherein the differential methylation region of at least one kidney includes a sequence having at least 90% identity with one or more of SEQ ID NOs: 1, SEQ ID NOs: 2, SEQ ID NOs: 8, SEQ ID NOs: 9, SEQ ID NOs: 15, SEQ ID NOs: 16, SEQ ID NOs: 22, SEQ ID NOs: 23, SEQ ID NOs: 29, or SEQ ID NOs:

30.

17. The method according to claim 1, wherein the method specifically detects damage to a defined tissue or cell type of the kidney.

18. The method according to claim 17, wherein the defined cell type is renal proximal tubular epithelial cell.

19. The method according to claim 17, wherein the differential methylation region of the at least one kidney is located in at least one of MAST4 and DDC.

20. The method according to claim 1, wherein the presence of at least one differential methylation region of the kidney in the cfDNA indicates that the subject should be treated for the kidney injury.

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