Methods and compositions related to the assessment and treatment of kidney disease

Abstract

The embodiments described herein relate to methods and compositions for diagnosing, monitoring, classifying, staging, and determining treatment regimens in subjects with or at risk of kidney disease and / or all-cause mortality by determining amino acid or nucleic acid levels in biological fluids such as urine.In certain aspects, the subject is diagnosed with diabetes (or other underlying risk factors for kidney disease, such as hypertension) and has normal levels of urinary albumin.Additionally, methods of treating fibrotic conditions by inhibiting adenine production or function are disclosed herein. TIFF2025506412000022.tif81127

Description

[Technical field]

[0001] Priority paragraph This international application claims priority to U.S. Provisional Patent Application No. 63 / 306,943, filed February 4, 2022, which is incorporated by reference in its entirety.

[0002] Statement regarding federally funded research This invention was made with Government support under Grant Nos. DK094352, DK110541, and DK114920 awarded by the National Institutes of Health. The Government has certain rights in this invention.

[0003] FIELD OF THEINVENTION Aspects of the present invention are directed generally to the fields of medicine and nephrology, and specifically to the assessment of renal function. [Background technology]

[0004] background The diagnosis of patients at risk for progressive decline in renal function over time is currently based on an increase in urinary albumin levels above the normal range of 0-30 mg albumin / gram creatinine in random or scheduled urine collections, and a measurement of their glomerular filtration rate (GFR). Albumin is an abundant protein produced primarily by the liver and present in the blood circulation. Blood albumin is prevented from entering the final urine through barriers at the glomerular level and by reabsorption of albumin at the tubular level. In many patients with progressive renal failure, there is a disruption of glomerular or tubular function, and albumin "leaks" into the final urine. This is an important biomarker of progressive kidney disease, and approximately 70% of patients who progress to require renal replacement therapy have increasing levels of albumin in their urine (normalized by urinary creatinine to account for variations in urine concentration) before they require renal replacement therapy. The other main criterion for determining whether renal function is declining is a reduction in glomerular filtration rate, estimated based on blood creatinine values. A normal estimated GFR is usually 90 ml / min / 1.73 m 2 The National Kidney Foundation (URL kidney.org / professionals / explore-your-knowledge / how-to-classify-ckd) defines stage G1A1 kidney disease as an eGFR > 90 ml / min / 1.73 m 2 Stage G1A2 patients are defined as having an eGFR > 90 ml / min / 1.73 m 2 and moderately elevated levels of urinary albumin (30-300 mg / gram). These patients are said to have microalbuminuria. Stage G1A3 patients have an eGFR > 90 ml / min / 1.73 m 2 Patients who require renal replacement therapy typically have a urine output of 10 ml / min / 1.73 m2 have an eGFR value below TIFF2025506412000002.tif45170Abbreviations: CKD, chronic kidney disease; GFR, glomerular filtration rate. *Compared to young adult levels. In the absence of evidence of kidney damage, neither GFR category G1 nor G2 meets the criteria for CKD. TIFF2025506412000003.tif30161Abbreviations: ACR, albumin-to-creatinine ratio; CKD, chronic kidney disease. *Compared to young adult levels. **Includes nephrotic syndrome (albumin excretion ACR>2220 mg / g).

[0005] Over 120,000 patients develop end-stage renal disease requiring dialysis or transplantation each year. Typically, patients who have a progressive decline in eGFR and will require renal replacement therapy have increased levels of albuminuria. In epidemiological studies, 70% of patients who develop end-stage renal disease (ESRD) have high levels of urinary albumin during early CKD (stages 1-3). However, it is estimated that approximately 30% of patients who go on to develop stage 5 CKD do not have evidence of increased albuminuria during earlier CKD (stages 1-3). In patients with a level of urinary albumin / creatinine ratio below 30 mg / gram, the conclusion is that the patient is at low risk of developing kidney disease and therefore is not usually treated with medications that reduce the progression of kidney disease, such as renin-angiotensin-aldosterone inhibitors or sodium-glucose transporter 2-inhibitors. The subset of patients who have diabetes (or some underlying risk factors such as hypertension) and normoalbuminuria and progressively decline in kidney function is difficult to identify. In addition, these normoalbuminuric diabetes-associated kidney disease (NADKD) patients are often not included in clinical trials to determine whether new therapies will benefit them. As the 30% of patients who develop end-stage renal disease but do not have albuminuria, this is a large segment of the overall end-stage renal disease (ESKD) population that is currently not identified for interventional procedures, because it is very difficult to identify which patients will progress to develop ESKD based on traditional clinical risk markers.

[0006] Therefore, there is a great unmet need to develop non-invasive biomarker assays to diagnose and stratify patients for risk of progressive kidney disease. Summary of the Invention

[0007] overview In some aspects, the invention described herein relates to methods and compositions for diagnosing, monitoring, classifying, staging, and determining treatment regimens in subjects with or at risk of kidney disease by determining the levels of nucleic acid, amino acid, or both in biological fluids such as blood or urine.In some examples, the nucleic acid measured can be pyrimidine (e.g., cytosine, thymine), purine (e.g., adenine, guanine, or uric acid), or uracil.In some examples, the amino acid is asparagine, aspartic acid, betaine, homocysteine, isoleucine, L-α-aminobutyric acid, lysine, methionine, nicotinic acid, ornithine, phenylalanine, pipecolate, threonine, tryptophan, tyrosine, or valine.In some examples, the nucleic acid, nucleoside, or amino acid measured is a polyamine (e.g., adenine, ornithine, spermine, putrescine). In certain aspects, a subject is diagnosed with diabetes (or other underlying risk factors for kidney disease, such as hypertension) and has a normal level of urinary albumin. The level of adenine in a biological fluid, such as urine, is obtained from the patient and compared to the level of urinary adenine with a control reference range or threshold. An increase in the level of urinary adenine in the sample (e.g., represented by the urinary adenine / creatinine ratio) indicates that the patient is at high risk of decreased kidney function or at risk of kidney failure, independent of the albuminuria level. The urinary adenine assay can independently diagnose normoalbuminuric diabetes-associated kidney disease (NADKD) or microalbuminuric diabetes-associated kidney disease, and identify patients at high risk of decreased kidney function or who will require renal replacement therapy in the future. The urinary adenine / creatinine ratio can also identify patients at high risk of all-cause mortality and kidney failure, independent of the albuminuria level. Urinary adenine assays and or biofluid adenine measurements (e.g., in blood samples) may also identify patients with other causes of kidney disease (hypertension, ischemia-related acute kidney injury, etc.) who are at risk for decreased kidney function and who will require renal replacement therapy.

[0008] In some aspects, the present invention is directed to a method for prognosing or identifying patients with normal or elevated levels of urinary albumin, such as those with diabetes or other risk factors for kidney disease. The method can determine which patients are at risk for progressive kidney disease and the potential need for future renal replacement therapy. Based on untargeted metabolome analysis from spatial omics and urinary metabolomics, the metabolite adenine was found to be associated with glomerulosclerosis, tubular atrophy, tubulointerstitial fibrosis, and vascular arteriosclerosis, as well as reduced kidney function.

[0009] In some aspects, the present invention is directed to a method for prognosing or identifying patients with normal or elevated levels of urinary albumin, such as those with diabetes or other risk factors for kidney disease. The method can determine which patients are at risk for progressive kidney disease, potential future need for renal replacement therapy, and increased mortality. Based on untargeted and targeted metabolome analysis from spatial omics and urinary metabolomics, the metabolite adenine was found to be associated with glomerulosclerosis, tubular atrophy, tubulointerstitial fibrosis, and vascular arteriosclerosis, as well as reduced kidney function.

[0010] In some aspects, the present invention is directed to methods for the diagnosis of patients at risk for chronic kidney disease who have normal or elevated levels of albumin in the urine, and for predicting the need for renal replacement therapy based on the presence of adenine levels above a threshold in biological fluids such as urine or blood. The present invention is also directed to diagnostic assays that measure adenine levels in biological fluids, and are useful for identifying animal models of disease and identifying which drugs may be beneficial in certain conditions of kidney disease.

[0011] In some aspects, the present invention is directed to a method of treating a condition of progressive fibrosis or cellular senescence in a subject, comprising administering to the subject a therapeutically effective amount of a pharmaceutical composition, wherein the pharmaceutical composition inhibits the production or function of adenine. In some examples, the pharmaceutical composition inhibits the production of adenine by blocking a cell signaling pathway that leads to endogenous adenine production. In some examples, the pharmaceutical composition inhibits the production of endogenous adenine by inhibiting the expression or function of 5'-methylthioadenosine phosphorylase (MTAP). In some cases, inhibiting the expression of MTAP comprises using a short hairpin RNA that targets at least a portion of a polynucleotide sequence that encodes MTAP. In some cases, inhibiting the expression of MTAP comprises using a nuclease (e.g., Cas9 endonuclease) coupled to a guide RNA that targets at least a portion of a polynucleotide sequence that encodes MTAP. In some cases, inhibiting the expression of MTAP comprises inserting a silencer sequence near the polynucleotide sequence that encodes MTAP. In some cases, inhibiting the function of MTAP comprises using an MTAP neutralizing antibody. In some cases, inhibiting the function of MTAP includes using a small molecule inhibitor of MTAP. The small molecule inhibitor of MTAP can be MT-DADMe-ImmA (FIG. 17) or other small molecule inhibitors as described in U.S. Pat. Nos. US8916571 and US10918641 (both of which are incorporated herein by reference). In some aspects, MTAP can be inhibited by sodium hydrogen sulfide or analogs of hydrogen sulfide, or other molecules, including siRNA against MTAP, to affect the level or activity of MTAP. In some aspects, cell surface receptors for adenine can be inhibited by G protein-coupled receptor (GPCR) antagonists or siRNA. In some aspects, cell surface insulin receptors respond to adenine and can be inhibited by insulin receptor blockers.In some aspects, the siRNA targeting a portion of the insulin receptor inhibits the insulin receptor (IR). In some aspects, the pharmaceutical composition inhibits the function of endogenous adenine by inhibiting the expression or function of mTORCl. In some examples, the pharmaceutical composition is an mTORCl inhibitor selected from the group consisting of rapamycin, rapalogs, rapamycin derivatives, temsirolimus, everolimus, umirolimus, zotarolimus, torin-1, torin-2, and vistusertib. In some cases, the pharmaceutical composition comprises an siRNA that inhibits the function of endogenous adenine by inhibiting the expression or function of PI3K. In some examples, the pharmaceutical composition is a small molecule PI3K inhibitor. In some cases, the small molecule PI3K inhibitor is LY294002. In some examples, the pharmaceutical composition inhibits the function of endogenous adenine by inhibiting the expression or function of AKT. In some examples, the pharmaceutical composition is a small molecule AKT inhibitor. In some cases, the small molecule AKT inhibitor is MK2202. In some cases, the pharmaceutical composition inhibits the function of endogenous adenine by inhibiting the expression or function of the insulin receptor (IR). In certain embodiments, the IR-specific inhibitor includes nucleic acids, proteins, and small molecules. In certain embodiments, the IR-specific inhibitor is a nucleic acid. In certain embodiments, the nucleic acid is an antisense compound. In certain embodiments, the modified oligonucleotide can be single-stranded or double-stranded. In certain embodiments, the nucleobase sequence of the modified oligonucleotide comprises a nucleobase sequence that is at least 70%, 75%, 80%, 85%, 90%, 95%, or 100% identical to a nucleobase sequence listed in any one of SEQ ID NOs: 1-22. In certain embodiments, the nucleobase sequence of the modified oligonucleotide is at least 70%, 75%, 80%, 85%, 90%, 95%, or 100% complementary to a nucleobase sequence listed in any one of SEQ ID NOs: 23-31.In some cases, the insulin receptor inhibitor is a knockdown mechanism that includes at least one of RNA interference (RNAi), small interfering RNA (siRNA), short hairpin RNA (shRNA), or bacterial RNA-guided endonuclease against the insulin receptor. Examples of siRNAs targeting IR can include the nucleobase sequences (SEQ ID: 1-22) in Table 10A and Table 11A; however, it is contemplated that other IR siRNAs, including those that are commercially available, can also be used. General definitions and concepts regarding siRNAs are described in U.S. Patent Nos. 11,377,658 and 10,364,433, both of which are incorporated herein by reference. In some cases, the pharmaceutical composition inhibits the function of endogenous adenine by inhibiting the expression or function of Gi-coupled adenine receptor (AdeR).

[0012] In some aspects, the pharmaceutical composition inhibits the function of endogenous adenine by activating AMP-activated protein kinase (AMPK).In some examples, the pharmaceutical composition is an AMPK activator selected from the group of NaHS, metformin, AICAR, metformin hydrochloride, A769662, RSVA405, ZLN024 hydrochloride, PT1, and PF06409577.In some examples, the incorporation of small molecules or siRNA or modified siRNA or biologics can be incorporated into dendrimers or chitosan or other chemical entities to enhance distribution to target organs.In some examples, the progressive fibrosis condition is at least one of kidney disease, liver disease, lung disease, cardiac fibrosis, brain fibrosis, neurodegenerative disease, arthrofibrosis, skin fibrosis, bone marrow fibrosis, retroperitoneal fibrosis. In some cases, the kidney disease is at least one of chronic kidney disease, diabetes-related kidney disease, end-stage renal disease (renal failure), glomerulosclerosis, tubulointerstitial fibrosis, renal arteriosclerosis, renal arteriosclerosis, renal neoplasia, and renal tubular atrophy.In some cases, the lung disease is at least one of interstitial lung disease (ILD) and pulmonary fibrosis.It is further contemplated that the treatment of the disease described herein can be achieved by the combination of two or more methods disclosed herein.

[0013] Some aspects of the present disclosure provide a method for identifying a subject at risk of kidney disease, comprising: measuring the level of nucleic acid, nucleoside, or amino acid in a biological sample (e.g., urine or blood) from a subject; and evaluating the risk of kidney disease based on the level of nucleic acid, nucleoside, or amino acid compared with a standard or reference. In some examples, the standard is the average value measured in a population of healthy individuals with normal kidney function. In some examples, the standard is a previous measurement value of the same subject. In some examples, the nucleic acid, nucleoside, or amino acid measured is adenine, cytosine, guanine, thymine, uracil, asparagine, aspartic acid, betaine, homocysteine, isoleucine, L-α-aminobutyric acid, lysine, methionine, nicotinic acid, ornithine, phenylalanine, pipecolate, threonine, tryptophan, valine, or any combination thereof. In some examples, the kidney disease is at least one of chronic kidney disease, diabetes-related kidney disease, end-stage renal disease (renal failure), glomerulosclerosis, tubulointerstitial fibrosis, renal arteriosclerosis, renal arteriosclerosis, renal neoplasia, and renal tubular atrophy. In some examples, the kidney disease can include a progressive decrease in kidney function. In some cases, the risk of kidney disease includes a risk of disease progression. In some examples, the risk of kidney disease includes a risk of developing kidney disease in the future. In some cases, the method disclosed herein further includes processing the biological sample from the subject to separate or concentrate nucleic acids, nucleosides, or amino acids. In some examples, processing the biological sample includes performing capillary electrophoresis, liquid chromatography (HPLC), capillary electrophoresis, liquid chromatography, or any combination thereof. In some cases, measuring the nucleic acid, nucleoside, or amino acid is performed by diode array detection (e.g., wavelengths between 200-400 nm), ZipChip™, mass spectrometry, electromagnetic radiation absorption, or any combination thereof. In some instances, adenine levels above a threshold value indicate 1) a decrease in glomerular filtration rate (GFR), 2) CKD progression, and / or 3) renal failure.In some cases, adenine levels below a threshold of 2.92 nmol adenine / mmol creatinine indicate a low risk of developing a renal condition or disease described herein. In some cases, adenine levels above a threshold of 2.92 nmol adenine / mmol creatinine indicate an intermediate risk of developing a renal condition or disease described herein. In some cases, adenine levels above a threshold of 4.08 nmol adenine / mmol creatinine indicate a higher than average risk of developing a renal condition or disease described herein. In some cases, adenine levels above a threshold of 5.23 nmol adenine / mmol creatinine indicate a high risk of developing a renal condition or disease described herein. In some cases, adenine levels between 80-500 mg / g indicate ESKD. In some cases, the subject is diabetic. In some cases, the subject has normal albumin levels. In some examples, the subject is a mammal, for example, human, non-human primate, rodent, dog or cat.In some examples, the method disclosed herein further comprises administering treatment to the subject, and the treatment comprises surgery, chemotherapy, radiation therapy, dietary restriction, treatment of hypertension, treatment of diabetes, weight management, smoking cessation, treatment of high cholesterol and / or other lipid levels, kidney transplant, dialysis, administration of erythropoietin and / or calcitriol, diuretics, vitamin D, or phosphate binders, or any combination thereof.

[0014] Some aspects of the disclosure provide a method of treating or preventing kidney disease in a subject having or at risk of developing kidney disease, comprising: (a) determining the level of adenine in a biological sample (e.g., urine or blood) from the subject; and (b) administering a treatment for kidney disease if the adenine level is above a threshold (e.g., >2.92 nmol adenine / mmol creatinine or above the lowest tertile for a defined population). Tertiles found for low-risk patients are 0-2.92 nmol adenine / mmol creatinine, for intermediate risk 2.92-5.23 nmol adenine / mmol creatinine, and high risk above 5.23 nmol adenine / mmol creatinine. In some examples, the subject is diabetic. In some examples, the subject has normal urinary albumin levels. In some examples, the subject is a human or an animal model of CKD.

[0015] Some aspects of the present disclosure provide an assay for determining the level of adenine in a biological sample (e.g., urine or blood) from a subject, comprising: (a) separating analytes in the sample to form sample fractions; and (b) quantifying adenine in the appropriate fractions. In some examples, the subject is diabetic. In some examples, the subject has normal albumin levels. In some examples, the subject is a human or an animal model of CKD.

[0016] Some aspects of the present disclosure provide a method for identifying a subject at risk of progressive decline in kidney function, comprising: (a) processing a biological sample (e.g., urine or blood) from the subject to separate adenine, forming a processed sample; (b) measuring the adenine level in the processed sample; and (c) assessing the risk of progressive decline in kidney function based on the adenine level compared to a standard. In some cases, the processing step is selected from capillary electrophoresis, liquid chromatography (HPLC), or capillary electrophoresis and liquid chromatography. In some cases, the measuring of the adenine level is by mass spectrometry, electromagnetic radiation absorption, or by ZipChip™. In some cases, an adenine level higher than >2.92 nmol adenine / mmol creatinine indicates a subject at risk of progressive decline in kidney function and / or all-cause mortality. In some cases, adenine levels higher than 4.08 nmol adenine / mmol creatinine indicate subjects with a higher than average risk of progressive decline in kidney function and / or all-cause mortality. In some cases, adenine levels higher than 5.23 nmol adenine / mmol creatinine indicate subjects with a higher than average risk of progressive decline in kidney function and / or all-cause mortality. In some cases, the subject is diabetic. In some cases, the subject has normal urinary albumin levels, low levels of urinary albumin (microalbuminuria), or high levels of urinary albumin (macroalbuminuria). In some cases, the subject is a human or an animal model.

[0017] Some aspects of the present disclosure provide methods for assaying a therapy for the treatment of kidney disease, comprising: (a) exposing or contacting a subject with a test agent that is potentially a therapy for kidney disease; and (b) monitoring the subject by quantifying adenine levels, wherein a reduction in adenine levels indicates a therapeutic benefit of the test agent for the treatment of kidney disease.

[0018] Some aspects of the present disclosure provide methods for monitoring the progression of CKD in a subject, the methods including: (a) obtaining from the subject a first biological sample at a first time point and a second biological sample at a second time point; (b) measuring adenine levels in the first biological sample and the second biological sample; and (c) assessing CKD by comparing the difference in adenine levels between the first and second time points.

[0019] Some aspects of the present disclosure provide methods for identifying a subject at risk for kidney disease, the methods including: (a) measuring adenine and creatinine levels in a biological sample from the subject; and (b) assessing the risk of kidney disease based on the adenine / creatinine ratio compared to a standard.

[0020] Some aspects of the present disclosure provide a method for measuring a biological sample from a subject, comprising: (a) measuring nucleic acid, nucleoside, or amino acid in the biological sample from the subject; (b) calculating the ratio of nucleic acid, nucleoside, or amino acid to creatinine; and (c) comparing the ratio with a standard to determine whether the ratio is greater than a threshold value.In some cases, the threshold value is about 2.92 nmol nucleic acid, nucleoside, or amino acid / mmol creatinine.In some cases, the threshold value is about 4.08 nmol nucleic acid, nucleoside, or amino acid / mmol creatinine.In some cases, the threshold value is about 5.23 nmol nucleic acid, nucleoside, or amino acid / mmol creatinine. In some cases, the nucleic acid, nucleoside, or amino acid is a purine, polyamine, adenine, cytosine, guanine, thymine, uracil, asparagine, aspartic acid, betaine, homocysteine, isoleucine, L-α-aminobutyric acid, lysine, methionine, nicotinic acid, ornithine, phenylalanine, pipecolate, threonine, tryptophan, or valine, or any combination thereof. In some cases, an adenine level higher than 2.92 nmol nucleic acid, nucleoside, or amino acid / mmol creatinine indicates a subject at risk for developing a renal condition or disease. In some cases, an adenine level higher than 4.08 nmol nucleic acid, nucleoside, or amino acid / mmol creatinine indicates a subject at higher than average risk for developing a renal condition or disease. In some cases, an adenine level higher than 5.23 nmol nucleic acid, nucleoside, or amino acid / mmol creatinine indicates a subject at high risk for a renal condition or disease. In some examples, the subject is diabetic. In some examples, the subject has normal urinary albumin levels, low levels of urinary albumin (microalbuminuria), or high levels of urinary albumin (macroalbuminuria). In some examples, the subject is a human or an animal model.In some cases, the renal condition or disease is at least one of chronic kidney disease, diabetes-related kidney disease, hypertension-related kidney disease, glomerulonephritis-related kidney disease, end-stage renal disease (renal failure), glomerulosclerosis, tubulointerstitial fibrosis, renal arteriosclerosis, renal arteriosclerosis, renal neoplasia, or renal tubular atrophy.

[0021] Some aspects of the present disclosure provide a method for measuring a biological sample from a subject, comprising: (a) measuring the adenine and creatinine levels in the biological sample from a subject; (b) calculating the ratio of adenine / creatinine; and (c) comparing the ratio of adenine / creatinine with a standard to determine whether the ratio is greater than about 2.92 nmol adenine / mmol, or about 4.08 nmol adenine / mmol creatinine, or about 5.23 nmol adenine / mmol creatinine.In some cases, an adenine level higher than 2.92 nmol adenine / mmol creatinine indicates a subject at risk of developing renal conditions or diseases.In some cases, an adenine level higher than 4.08 nmol adenine / mmol creatinine indicates a subject at higher than average risk of developing renal conditions or diseases. In some cases, adenine level higher than 5.23 nmol adenine / mmol creatinine indicates that the subject is at high risk of renal condition or disease. In some cases, the subject is diabetic. In some cases, the subject has normal urinary albumin level, low level of urinary albumin (microalbuminuria), or high level of urinary albumin (macroalbuminuria). In some cases, the subject is a human or an animal model. In some cases, the renal condition or disease is at least one of chronic kidney disease, diabetes-related kidney disease, hypertension-related kidney disease, glomerulonephritis-related kidney disease, end-stage renal disease (renal failure), glomerulosclerosis, tubulointerstitial fibrosis, renal arteriosclerosis, renal arteriosclerosis, renal neoplasia, or renal tubular atrophy.

[0022] Certain embodiments are directed to methods for detecting urinary adenine levels in the top two tertiles of developing end stage renal disease (e.g., between 2.92 and 5.23 nmol adenine / mmol creatinine for intermediate risk, and above 5.23 nmol adenine / mmol creatinine for high risk).

[0023] Other embodiments are directed to methods for detecting levels of urinary adenine / creatinine ratio in the top two tertiles, which are indicative of increased risk of death and end stage renal disease.

[0024] Other embodiments are directed to methods for detecting urinary adenine levels in the top two tertiles of progressive decline in kidney function as measured by GFR (e.g., between 2.92 and 5.23 nmol adenine / mmol creatinine for intermediate risk, and above 5.23 nmol adenine / mmol creatinine for high risk).

[0025] Still other embodiments are directed to methods for detecting urinary adenine levels, e.g., >2.92 nmol adenine / mmol creatinine, >4.08 nmol adenine / mmol creatinine, or 5.23 nmol adenine / mmol creatinine, that indicate which patients should be selected for a particular class of drug therapy to reduce kidney disease progression.

[0026] Certain embodiments are directed to assays for use in patients with diabetes and no albuminuria as part of a screen to identify patients at risk for kidney disease.

[0027] In other embodiments, the assays are used to monitor patients to identify whether they are responding to new treatment regimens for renal protection.

[0028] In yet a further embodiment, the assay can identify animal models of kidney disease that are relevant to the human condition.

[0029] The term "biomarker" as used herein refers to any biological compound associated with the development of progressive chronic kidney disease.For example, the biomarker may include adenine, or any of its metabolites or derivatives.In certain aspects, the biomarker is adenine.

[0030] Adenine is one of the two purine nucleobases (the other being guanine) used to form nucleotides. It has the chemical structure TIFF2025506412000004.tif31128.

[0031] Creatinine is a breakdown product of creatine phosphate from muscle and protein metabolism. It is released by the body at a constant rate (depending on muscle mass). Creatinine is: It has the chemical structure TIFF2025506412000005.tif34128.

[0032] Some aspects of the present disclosure provide a method for treating a progressive fibrosis condition in a subject, comprising administering a therapeutically effective amount of a pharmaceutical composition to the subject, wherein the pharmaceutical composition is at least one of the following: an inhibitor of adenine accumulation, an inhibitor of adenine receptor, an inhibitor of adenine signaling, or any combination thereof.In some embodiments, the inhibitor of adenine accumulation is at least one of MTAP inhibitor (MTDIA) or hydrogen sulfide.In some embodiments, the inhibitor of adenine receptor is at least one of Gi-coupled adenine receptor (AdeR) or insulin receptor.In some embodiments, the inhibitor of adenine signaling is at least one of Akt inhibitor, PI3K inhibitor, or mTOR inhibitor.

[0033] As used herein, a "biological sample" is a sample of biological fluid. Examples of biological samples are blood, blood fraction, plasma, serum, or urine. In addition, pools or mixtures of the above-mentioned samples can also be used. Biological samples can be provided by collecting samples from subjects, but can also be provided by using previously collected samples. In a preferred embodiment, urine or blood samples are collected from subjects. In one embodiment, an initial sample is obtained from a subject before the start of therapeutic treatment.

[0034] A biological sample from a patient refers to a sample from a subject suspected of suffering from a disease. As used herein, the term "subject" refers to any mammal, including both humans and other mammals. Preferably, the method of the present invention is applied to a human subject.

[0035] The term "treating" or "treatment" refers to any success or indicator of success in attenuating or ameliorating an injury, pathology, or condition, including any objective or subjective parameter, such as remission, remission, diminishment of symptoms, or making the injury, pathology, or condition more tolerable to the patient, slowing the rate of degeneration or decline, making the end point of degeneration less debilitating, improving the physical or mental well-being of the subject, or prolonging survival. Treating or ameliorating symptoms can be based on objective or subjective parameters, including the results of a physical exam, a neurological exam, and / or a psychiatric evaluation.

[0036] "Effective amount" and "therapeutically effective amount" are used interchangeably herein and refer to an amount of an antibody or functional fragment thereof as described herein that is effective to achieve a particular biological or therapeutic result, such as, but not limited to, the biological or therapeutic results disclosed herein. The therapeutically effective amount of an antibody or antigen-binding fragment thereof may vary depending on factors such as the disease state, age, sex, and weight of the individual, and the ability of the antibody or functional fragment thereof to elicit a desired response in the individual. Such results may include, but are not limited to, the treatment of cancer, as determined by any means suitable in the art.

[0037] As used herein, the term "prognosis" refers to a medical conclusion based on the analysis of any biomarker that provides information regarding the progression of a medical condition, including but not limited to chronic kidney disease, including but not limited to determining the risk of developing end-stage renal disease or the risk of progressive decline in kidney function.

[0038] As used herein, the phrase "kidney disease" refers to any disease or condition affecting the kidneys, such as, for example, chronic kidney disease, acute kidney disease, congenital kidney disease, polycystic kidney disease, hypertensive kidney disease, inflammatory kidney disease, glomerulonephritis, tubulointerstitial disease, etc. Chronic kidney disease often manifests as having no detectable symptoms until there is irreversible damage to the kidneys.

[0039] As used herein, the term "chronic kidney disease (CKD)" refers to a condition in which exemplary symptoms include hyperphosphatemia (i.e., for example, >4.6 mg / dl) or low glomerular filtration rate (i.e., for example, >1.73 m 2The term "chronic kidney disease" refers to a medical condition that may include, but is not limited to, a chronic kidney disease (CKD) that is characterized by a persistent decrease in glomerular filtration rate (<90 ml / min per unit of body surface area) over a period of 3 months or more. However, many CKD patients may have normal serum phosphate levels with a persistent reduction in glomerular filtration rate for 3 months or more, or a normal GFR with persistent evidence of renal structural abnormalities. Alternatively, "chronic kidney disease" refers to a medical condition that may include, but is not limited to, a persistent decrease in glomerular filtration rate (<90 ml / min per unit of body surface area) over a period of 3 months or more ... However, many CKD patients may have normal serum phosphate levels with a persistent reduction in glomerular filtration rate for 3 months or more, or a normal GFR with persistent evidence of renal structural abnormalities. Alternatively, "chronic kidney disease" refers to a medical condition that is characterized by a persistent decrease in glomerular filtration rate (<1.73 ml / min per unit of body surface area) over a period of 3 months or more. 2 or (ii) a medical condition in which there is a structural or functional abnormality of the kidney for more than three months, even in the absence of a reduction in GFR. Renal structural or anatomical abnormalities may be defined as, but are not limited to, persistent microalbuminuria, proteinuria, or hematuria, or the presence of renal cysts.

[0040] The terms "patient", "individual", or "subject" are used interchangeably herein to refer to a mammalian subject, such as a human, to be treated. In some cases, the process of the present technology finds use in laboratory animals, including but not limited to rodents, including mice, rats, and hamsters; birds, fish, reptiles, and primates, in veterinary applications, and in the development of vertebrate models of disease.

[0041] The terms "normal subject" and "healthy subject" refer to a mammalian subject, e.g., a human, who is not or does not suffer from renal disease and has no past history of renal disease.

[0042] As used herein, the term "glomerular filtration rate (GFR)" refers to a measurement by which kidney function can be determined. Generally, a normal glomerular filtration rate is 1.73 m 2 The glomerular filtration rate is approximately 1.73 m 2 Impaired renal function is assumed when the glomerular filtration rate is less than 90 ml / min per cubic metre of body surface area. 2 If it falls below approximately 30 ml / min per body surface area, renal failure is likely.

[0043] "Estimated glomerular filtration rate (eGFR)" is a measure of how well your kidneys are working. eGFR is an estimate based on blood tests, as well as your age, sex, body type, and race.

[0044] Marker level can be compared with a reference level representing the same marker.In certain aspects, the reference level can be a reference level from a control or non-disease subject.Alternatively, the reference level can be a reference level from a different subject or a group of subjects.The reference level can be a single value or a range of values.In some embodiments, the reference level is the average level determined from a cohort of subjects.

[0045] Other aspects of the present invention are discussed throughout this application. Any aspect discussed with respect to one aspect of the present invention is equally applicable to other aspects of the present invention, and vice versa. It is understood that each embodiment described herein is an embodiment of the present invention that is applicable to all aspects of the present invention. It is contemplated that any embodiment discussed herein can be implemented with respect to any method or composition of the present invention, and vice versa. Furthermore, the compositions and kits of the present invention can be used to achieve the methods of the present invention.

[0046] The use of the words "a" or "an," when used in conjunction with the term "comprising" in the claims and / or specification, may mean "one," but is also consistent with the meanings of "one or more," "at least one," and "one or more."

[0047] As used herein, the phrases "at least one," "one or more," and "and / or" are open-ended expressions that are both conjunctive and disjunctive in nature. For example, each of the phrases "at least one of A, B, and C," "at least one of A, B, or C," "one or more of A, B, and C," "one or more of A, B, or C," and "A, B, and / or C" means A only, B only, C only, a combination of A and B, a combination of A and C, a combination of B and C, or a combination of A, B, and C.

[0048] As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. Furthermore, to the extent the terms "including," "includes," "having," "has," "with," or variations thereof are used in either the detailed description and / or claims, such terms are intended to be inclusive in a manner similar to the term "comprising."

[0049] The use of absolute or sequential terms, such as "will," "will not," "shall," "shall not," "must," "must not," "first," "firstly," "next," "then," "before," "after," "finally," and "finally," are not intended to limit the scope of the aspects of the invention disclosed herein, but are intended as illustrations.

[0050] As used herein, "or" may refer to "and," "or," or "and / or," and may be used in both the exclusive and inclusive sense. For example, the term "A or B" may refer to "A or B," "A but not B," "B but not A," and "A and B." In some cases, the context may dictate a particular meaning.

[0051] Any systems, methods, and platforms described herein are modular and not limited to sequential processes, and thus, terms such as "first" and "second" do not necessarily imply a priority, order of importance, or order of action.

[0052] As used herein, the term "about" when referring to a numerical value or numerical range means that the numerical value or numerical range referred to is an approximation within experimental variability (or within statistical experimental error), where the numerical value or numerical range may vary, for example, from 1% to 10% of the stated numerical value or numerical range. Unless otherwise indicated by context, the term "about" refers to ±10% of the stated numerical value or value.

[0053] As used herein, the term "approximately" means within an acceptable error range for a particular value as determined by one of ordinary skill in the art, which depends in part on how the value is measured or determined, e.g., the limitations of the measurement system. For example, "approximately" can mean within 1 or more than 1 standard deviation, according to convention for a given value. When a particular value is described in this application and claims, unless otherwise stated, the term "approximately" should be assumed to mean an acceptable error range for the particular value.

[0054] Where a range of values ​​is provided, unless the context clearly dictates otherwise, it is understood that each intervening value between the upper and lower limit of that range, to the tenth of the unit of the lower limit, and any other stated or intervening value in that stated range, is encompassed within the disclosure. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges, and are also encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where a stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure.

[0055] All ranges disclosed herein also encompass any and all possible subranges and combinations of subranges. Any recited range can be recognized as fully descriptive and allowing the same range to be broken down into at least equal halves, thirds, quarters, fifths, tenths, etc. As a non-limiting example, each range discussed herein can be easily broken down into a lower third, middle third, and upper third, etc. All phrases such as "up to," "at least," "greater than," "less than," etc., refer to ranges that include the recited numerical values ​​and can then be broken down into subranges as discussed above. Finally, ranges include each individual member. Thus, for example, a group having 1 to 3 items refers to a group having 1, 2, or 3 items. Similarly, a group having 1 to 5 items refers to a group having 1, 2, 3, 4, or 5 items, etc.

[0056] Whenever the term "at least," "greater than," "or greater than," or a similar phrase precedes the first number in a series of two or more numerical values, the term "at least," "greater than," "or greater than," or a similar phrase applies to each of the numerical values ​​in the series of numbers. For example, "at least 1, 2, or 3" is equivalent to "at least 1, at least 2, and / or at least 3."

[0057] As used herein, the symbol ">" means "greater than; the symbol "<" means "less than;" the symbol ">=" means "greater than or equal to;" the symbol "<=" means "less than or equal to."

[0058] Whenever the term "no more than," "less than," "less than or equal to," "no greater than," "at most," or a similar phrase precedes the first number in a series of two or more numerical values, the term "no more than," "less than," "less than or equal to," "no greater than," "at most," or a similar phrase applies to each of the numerical values ​​in the series of numerical values. For example, "less than 3, 2, or 1" is equivalent to "less than 3, less than 2, and / or less than 1."

[0059] As used herein, the following meanings apply unless otherwise specified: The word "may" is used in a permissive sense (i.e., meaning having the possibility) rather than a mandatory sense (i.e., meaning must). Words such as "include," "including," and "includes" mean including but not limited to. The singular forms "a," "an," and "the" include plural referents. Thus, for example, reference to "an element" includes a combination of two or more elements, regardless of the use of other terms and phrases for one or more elements, such as "one or more." The phrase "at least one" includes "one," "one or more," "one or a plurality," and "plural." The term "or" is non-exclusive, i.e., encompasses both "and" and "or," unless otherwise indicated. The term "any of" between a modifier and a sequence means that the modifier modifies every member of the sequence. Thus, for example, the phrase "at least 1, 2, or 3" means "at least 1, at least 2, or at least 3."

[0060] As used in the specification and claims, the words "comprising" (and any form of comprising, such as "comprise" and "comprises"), "having" (and any form of having, such as "have" and "has"), "including" (and any form of including, such as "includes" and "include"), or "containing" (and any form of containing, such as "contains" and "contain") are inclusive or open-ended and do not exclude additional, unrecited elements or method steps.

[0061] Other objects, features, and advantages of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and specific examples, while indicating specific embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.

[0062] The description and drawings are not intended to limit the invention to the particular forms disclosed; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims. Further modifications and alternative embodiments of various aspects of the invention will be apparent to those skilled in the art in view of this description. Thus, the description and drawings should be construed as illustrative only and are for the purpose of teaching those skilled in the art the general manner of carrying out the invention. It should be understood that the forms of the invention shown and described herein are to be taken as exemplary embodiments. Elements and materials may be substituted for those illustrated and described herein, parts and processes may be reversed or omitted, and certain features of the invention may be utilized independently, all as would be apparent to one skilled in the art after having the benefit of this description of the invention. Changes may be made in the elements described herein without departing from the spirit and scope of the invention as set forth in the appended claims. The headings used herein are for organizational purposes only and are not intended to be used to limit the scope of the description.

[0063] INCORPORATION BY REFERENCE All publications, patents, and patent applications mentioned in this specification are incorporated herein by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. To the extent that the publications and patents or patent applications incorporated by reference conflict with the disclosure contained in this specification, it is intended that the specification supersede and / or take precedence over any such conflicting material. [Brief description of the drawings]

[0064] The following drawings form part of the present specification and are included to further demonstrate certain aspects of the invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of embodiments of the specification presented herein.

[0065] [Figure 1] Figure 1A-1B. (A) Gene, protein, and metabolite marker enrichment analysis for proximal tubule predicts well-known functions. (B) Integration of tubulointerstitial metabolites into the KWEGG pathway purine metabolism (identified in A). Enzyme numbers were mapped to human gene products, and multiple gene products of the same family were collapsed into the family name. Selected reactions are shown. ACP3: acid phosphatase 3. ADP / AMP: adenosine diphosphate / monophosphate. AK3: nucleoside-triphosphate-adenylate kinase. APRT: adenine phosphoribosyltransferase. DR 1-P: D-ribose 1-phosphate. NDP / NTP: nucleoside 2 / 3-phosphate. NT: 5'-nucleotidase. Pi: orthophosphate. PP: diphosphate, reaction is reversible. PNP: purine-nucleoside phosphorylase. PRPP: 5-phospho-α-D-ribose 1-diphosphate. [Diagram 2] Figures 2A-2C. Endogenous adenine localized to areas of early glomerulosclerosis, atrophic tubules, and vascular arteriosclerosis in human kidney biopsies (A). MALDI-MSI was performed on a patient with CKD and the metabolite adenine was found to colocalize with glomeruli with early glomerulosclerosis lesions (B) and adjacent to areas of atrophic tubules. Adenine was also localized to peritubular regions and overlaid on the vascular wall of arteriosclerotic blood vessels (C). [Diagram 3] The ZipChip™ Urinary Adenine Assay Correlates Well with LC-MS / MS. The ZipChip™ Urinary Adenine Assay was developed and found to be highly correlated with urinary adenine measured by LC-MS / MS. N=23 samples, r=0.90, p<0.0001. [Figure 4]Flowchart of a biopsy study in the Pima Native American population (taken from PMID 30830355). [Diagram 5] Flow diagram of the analysis process and a brief summary of the results. [Figure 6] Forest plot of ESKD risk (hazard ratios with 95% CI) for 15 nontargeted and targeted metabolites. [Figure 7] Adenine dose-dependently reduced ATP production in human proximal tubule cells. At high doses, adenine exposure caused a complete reduction in ATP production in HK2 cells by Seahorse analysis. ****p<0.0001. [Figure 8] Urinary adenine correlates with glomerulosclerosis in Pima Indian populations. [Figure 9] Urinary adenine identifies patients with ESKD. [Figure 10] Forest plots showing subgroup analysis indicate that men and those with high urinary adenine / creatinine ratio (urinary AdCR) had a higher proportion of developing ESKD across the various albuminuria categories: HR men (1.11, 95% CI 1.05-1.17, p<0.001; women 0.99, 95% CI 0.92-1.06, p=0.8); macroalbuminuria HR 1.04, 0.98-1.10, p=0.2; microalbuminuria 1.13, CI 1.02-1.25, p=0.022; and normoalbuminuria HR 1.15, CI 1.00-1.33, p=0.048. [Figure 11] Figure 11A. Image of the ZipChip device. Figure 11B. Microfluidic chip in the ZipChip cartridge. [Figure 12] Plasma adenine identifies an animal model that can be used to model acute kidney injury. Plasma adenine was measured by Zipchip-QExactive in mice 24 hours after sham operation or 24 hours after ischemia-reperfusion injury. Plasma adenine was significantly increased in IRI mice, indicating that they would be a good model to mimic human kidney disease. [Figure 13] Adenine is toxic to kidney cells (causing disease). [Figure 14] Role of MTAP in adenine production. [Figure 15] The endogenous production of adenine and the effects of adenine are central to kidney disease progression. [Figure 16] MTAP is increased in IR-35 (acute) and MDM2 KO (chronic) kidney disease. [Figure 17] Structure of the MTAP inhibitor used in the experiments. [Figure 18] Protective Effects of MTAP Inhibitors. MT-DADMe-ImmA (also known as MTDIA; methylthio-DADMe-Immucillin), a small molecule inhibitor of MTAP, protects kidney cells from cell death and may therefore be protective against progressive kidney disease. [Figure 19] Effects of rapamycin and NaHS on adenine. Adenine-induced fibronectin accumulation was ameliorated by inhibition of mTORCl and activation of AMPK. A. Renal tubule (MCT) cells were preincubated with 10 nM rapamycin for 30 min, followed by incubation with 20 μM adenine for 15 min. B. MCT cells were incubated with 20 μM adenine and 250 μM NaHS for 15 min. Rapamycin-mediated inhibition of mTOR (Mammalian target of rapamycin) blocks adenine-induced fibronectin production in kidney cells, leading to renal cell scarring (Panel A). The compound sodium hydrosulfide (NaHS) can also inhibit adenine-induced fibronectin production by inhibiting mTOR and / or activating AMP-activated protein kinase (AMPK) (Panel B). [Figure 20]In patients with subclinical albuminuric diabetes, a higher urinary adenine / creatinine ratio at baseline (tertile 3 vs. tertile 1) is associated with ESKD. In a US cohort (n=551) including Caucasians, African Americans, and Hispanics with diabetes and subclinical albuminuria, higher urinary adenine / creatinine levels (tertile 3 vs. tertile 1) identify patients at increased risk of ESKD. [Figure 21] Risk of death and ESKD is highest in diabetic patients in the top tertile of urinary adenine / creatinine.A US cohort (n=904) including Caucasians, African Americans, and Hispanics demonstrates that the top two urinary adenine tertiles identify patients at higher risk of ESKD and death compared with the lowest tertile. [Figure 22] Urinary adenine / creatinine ratios are higher in type 1 diabetes (T1D) patients with hyperfiltration than in T1D patients with normofiltration. Differences in baseline euglycemic adenine between hyperfiltrated and normofiltrated participants. Significant p-values ​​stated. *p<0.05. [Figure 23] Empagliflozin reduces urinary adenine levels in patients with hyperfiltration. Hyperfilterers (red line and dots) and normofilterers (blue line and dots). The overall effect of treatment on least squares mean change in log-transformed adenine levels (Visits 3 and 4 vs. Visits 12 and 13) is reported. Significant p-values ​​stated. *p<0.05, **p<0.01. [Figure 24] Adenine rapidly stimulates type I collagen in renal tubular cells. [Diagram 25] The MTAP inhibitor DADMe-ImmA given once before ischemia-reperfusion injury prevents the increase in BUN levels in mice undergoing ischemia-reperfusion injury. Mice were subjected to 30 minutes of ischemia followed by reperfusion, and BUN was measured 24 hours later. There was no significant increase in BUN in mice treated with the MTAP inhibitor, whereas mice treated with vehicle had a marked increase in BUN. [Figure 26]MTAP levels, fibronectin, and urinary ACR are increased in db / db kidney disease and are reduced by NaHS. NaHS was administered to db / db and db / m mice for 4 weeks, and the levels of MTAP / -b-actin and fibronectin / b-actin were assessed by immunoblotting. Urinary ACR was measured at the end of 4 weeks of NaHS administration. NaHS administration significantly reduced MTAP (A), fibronectin (B), and urinary ACR (C) (n=8-10 / group, **p<0.01, ***p<0.001). [Figure 27] Specific siRNA against insulin receptor (IR) completely blocks adenine-induced stimulation of mTOR and fibronectin in renal tubular cells. siRNA against IR completely blocks IR levels in renal tubular cells (A) and prevents phosphorylation of S6K (B). siRNA against IR blocks adenine-induced fibronectin production in renal tubular cells (C). [Figure 28] Inhibition of PI3K with LY294002, or AKT with MK2202, or mTOR with rapamycin all blocked adenine-induced stimulation of the mTOR pathway.S6K phosphorylation (P-S6K), a sensitive indicator of mTOR stimulation, was increased within minutes of adenine challenge in tubular cells. [Figure 29] Spatial levels of adenine are increased in human diabetic kidneys. Quantitative assessment across healthy controls (n=5) and diabetic samples (n=8 T1D and n=8 T2D) with MALDI-MSI demonstrated a statistical increase in adenine in kidney tissue sections. [Diagram 30] Adenine administration to mice increases serum sTNFR1 (A) and plasma KIM-1 (B) (n=12 in control group and n=7 in adenine-treated group, *p<0.05, **p<0.01, ***p<0.001, ****p<0.001 vs. control by t-test or one-way ANOVA). [Diagram 31]Adenine administration to mice increases renal (A) and cardiac (B) hypertrophy and mTOR-mediated matrix molecules in the kidney (C). Quantitative assessment of phosphor-S6 kinase as a measure of mTOR (D), fibronectin / -b-actin (E), and collagen type 1 α2 chain (F). (n=12 in control group and n=7 in adenine-treated group, *p<0.05, **p<0.01, ***p<0.001, ****p<0.001 vs. control by t-test or one-way ANOVA). [Diagram 32] MTAP inhibitor DADMe-ImmA for 8 weeks reduces urinary ACR, urinary H2O2, and urinary collagen in db / db mice. Control (db / m) and diabetic (db / db) mice were treated with MTAP inhibitor (10 mg / kg / day in drinking water) from week 12 to week 20, and 24-h urine samples were collected to measure albumin / creatinine ratio (A), hydrogen peroxide / creatinine ratio (B), and collagen / creatinine ratio (C). (*p<0.05, ANOVA, n=5-6 / group). [Diagram 33] The MTAP inhibitor DADMe-ImmA has beneficial effects of reducing renal hypertrophy and inhibiting renal matrix accumulation in diabetic kidneys. Control (db / m) and diabetic (db / db) mice were treated with the MTAP inhibitor (10 mg / kg / day in drinking water) from week 12 to week 20, and kidney weights were normalized per tibia length (A). Kidney cortex was immunoblotted for fibronectin and laminin y1 and normalized for b-actin, and quantitative data are shown in (B) and (C), respectively. (*p<0.05, ANOVA, n=5-6 / group). [Diagram 34]Sequence-based siRNAs against insulin receptor (IR) in mouse and rat reduce IR in mouse kidney cells. Mouse cortical tubule (MCT) cells were reverse transfected with siRNAs targeting mouse and rat insulin receptor mRNA (m / r IR siRNA#1 and m / r IR siRNA#5) using RNAiMax (6 ul in optiMEM) and plated in 6-well plates. After 72 hours of incubation, total RNA was isolated and subjected to cDNA synthesis followed by qRTPCR (n=6 / group, ****p<0.0001). Both IR siRNA#1 and IR siRNA#5 significantly reduced mouse insulin receptor at the mRNA level. [Diagram 35] In vivo administration of IR siRNA#l specifically reduced IR in mouse kidney and prevented adenine-induced increase in BUN levels in mice. Mice were administered vehicle or kidney-targeted IR siRNA#1, and then challenged with adenine (5 mM) in drinking water for 4 days. On the fourth day, mouse kidneys showed reduced IR in mouse kidney cortex but not in liver compared to control samples, as demonstrated by immunoblotting with antibodies against IR and b-actin (representative immunoblot, upper panel). Mice given vehicle and adenine (n=2) had three-fold increased BUN levels relative to the non-adenine group (lower panel). Mice treated with siRNA against IR did not have any increase in BUN levels despite exposure to adenine (n=2) (lower panel). [Diagram 36]siRNAs against human and porcine insulin receptors are effective in reducing insulin receptor mRNA in human kidney cells. Human kidney (HK2) proximal tubule cells were transfected with siRNA (4 ul from 10 um stock) using RNAiMax (6 ul in optiMEM) and plated in 6-well plates. After 48 hours, the medium was replaced with fresh medium. 96 hours after transfection, total RNA was isolated and subjected to cDNA synthesis followed by qRTPCR. Human insulin receptor was significantly reduced in HK2 cells after transfection with H / P siRNA#2 and H / P IR siRNA#4 compared to control siRNA (n=6 / group, ****p<0.0001). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0066] explanation Methods and compositions are described for diagnosing, monitoring, classifying, staging, and determining treatment regimens in subjects by determining the level of adenine in biological fluids such as urine obtained from a patient, and comparing the level of urinary adenine to a control reference range or threshold. In certain aspects, the subject has diabetes (or other underlying risk factors for kidney disease, such as hypertension) and has normal levels of urinary albumin. An increase in the level of urinary adenine in the sample identifies the patient as at high risk of decreased kidney function, or at risk of kidney failure, or at risk of death. Urinary adenine assay can independently diagnose normoalbuminuric diabetes-associated kidney disease (NADKD) and identify patients at high risk of decreased kidney function, or who will require renal replacement therapy in the future. Urinary adenine assay and or biological fluid adenine measurement (e.g., in blood samples) can also identify patients with other causes of kidney disease (hypertension, ischemia-associated acute kidney injury, etc.) and at risk of decreased kidney function, and who will require renal replacement therapy, or at increased risk of death.

[0067] Described herein is an assay method for adenine that can measure adenine in biological fluids. The urine assay is performed in patients with diabetes and normal albuminuria and normal GFR (>90 ml / min / 1.73 m), who will have progression of kidney disease as measured by a decrease in GFR. 2 In addition, urine assays identify patients at increased risk of renal failure (eGFR < 15 ml / min / 1.73 m 2 , dialysis or other renal replacement therapy), normoalbuminuria and reduced eGFR (25–75 ml / min / 1.73 m 2 or stage G2A1 and stage G3A1 CKD).

[0068] I. Kidney Injury and / or Disease The kidneys are located on either side of the spine, at the back of the upper abdomen. They lie deep within the abdomen and are protected by the strong muscles of the spine, lower rib cage, and back. This location protects the kidneys from many external forces. The kidneys are highly vascular organs, which means that they have a large blood supply. If an injury occurs, severe bleeding can result.

[0069] The kidneys can be injured by damage to the blood vessels that supply or drain the kidney. This can be in the form of an aneurysm, arteriovenous fistula, arterial occlusion, or renal vein thrombosis. The amount of bleeding depends on the location and extent of the injury. The kidney can also bleed heavily if the center (inner) is injured, which is a life-threatening injury. Fortunately, most kidney injuries caused by blunt trauma occur peripherally and only cause kidney contusion, which is usually a self-limiting process.

[0070] Each kidney filters about 1700 liters of blood per day and concentrates fluids and waste products into about 1 liter of urine per day. This causes the kidney to be exposed to more toxic substances in the body than almost any other organ. Therefore, the kidney is highly susceptible to injury from toxic substances. Analgesic nephropathy is one of the most common types of toxic damage to the kidney. Exposure to lead, cleaning products, solvents, fuels, or other nephrotoxic chemicals (which can be toxic to the kidney) can damage the kidney. Excessive accumulation of body waste products such as uric acid (which can occur in gout or in the treatment of bone marrow, lymph nodes, or other disorders) can also damage the kidney.

[0071] Chronic renal failure (CKF) - Unlike acute renal failure, chronic renal failure slowly worsens. Chronic renal failure is most often due to any disease that causes a gradual loss of kidney function. It can range from mild dysfunction to severe kidney failure. The disease can lead to end-stage renal disease (ESRD).

[0072] Chronic kidney failure usually occurs over many years as the internal structure of the kidneys is slowly damaged. In the early stages, there may be no symptoms. In fact, it may progress so slowly that symptoms may not occur until kidney function is less than one-tenth of normal.

[0073] Chronic renal failure and ESRD affect more than 2 out of every 1,000 people in the United States. Diabetes and hypertension are the two most common causes and account for most cases. Other major causes include, but are not limited to, Alport syndrome, analgesic nephropathy, any type of glomerulonephritis (one of the most common causes), kidney stones and infections, obstructive uropathy, polycystic kidney disease, or reflux nephropathy. Chronic renal failure results in the accumulation of fluids and waste products in the body, leading to the accumulation of nitrogenous waste products in the blood (azotemia) and general poor health. Most body systems are affected by chronic renal failure.

[0074] Early symptoms may include, but are not limited to, fatigue, frequent hiccups, generalized malaise, generalized itching (pruritus), headache, nausea, vomiting, or unintentional weight loss.Furthermore, later symptoms may include, but are not limited to, blood in vomit or stool, drowsiness, confusion, delirium, or decreased alertness, including coma, decreased sensation in hands, feet, or other areas, easy bruising or bleeding, increased or decreased urine output, muscle twitching or spasms, seizures, or white crystals in and on the skin (uremic frost).

[0075] II. Adenine – a biomarker of kidney disease progression and mortality Certain patients present with normoalbuminuria and diabetes while having underlying renal pathology. Diagnosis of kidney disease in diabetic patients with normoalbuminuria and normal GFR is difficult. One approach is to demonstrate by kidney biopsy that the pathological features of kidney disease are present in patients with normoalbuminuria and normal levels of GFR. This was accomplished in a prior study of the Pima Native American population summarized below. Patients underwent a protocol involving collection of urine samples followed by a research kidney biopsy.

[0076] Pima Indian Study. All patients in this study were enrolled in a randomized clinical trial (Weil et al. 2013) testing the renal protective efficacy of losartan versus placebo in early diabetes-related kidney disease (ClinicalTrials.gov number, NCT00340678). Glomerular filtration rate (GFR) was measured annually throughout the study by urinary clearance of iothalamate. At the end of the 6-year clinical trial, participants underwent percutaneous kidney biopsy to determine whether the treatment was associated with preservation of kidney structure. Archived urine samples were available for 62 participants who had collected urine before the clinical trial-derived kidney biopsy for whom biopsy data were also available. The clinical trial was approved by the Institutional Review Board of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Each participant signed an informed consent document. As described herein, a follow-up biomarker study was conducted that was limited to the analysis of those participants randomized to placebo who were not taking any renin-angiotensin system blockers at the time of biopsy or at the time of collection of any of the urine specimens used to measure urinary adenine concentrations.

[0077] CRIC cohort. A metabolomic substudy of the Chronic Renal Insufficiency Cohort (CRIC) was also used. The parent CRIC study recruited (from 2003) an ethnically diverse group of subjects aged 21-74 years, approximately 50% with diabetes, and a wide range of renal function [Feldman et al. J Am Soc Nephrol. 2003, 14(7 Suppl 2):S148-53]. Informed consent was obtained from participants; the protocol was approved by the IRB and the Scientific and Data Coordinating Center (approval number 59 807882). The study included subjects with CKD stages 3a, 3b, and 4, eGFR 45-60, 30-45, and 20-30 ml / min / 1.73 m, respectively. 2Methods: We analyzed the urinary metabolome at study entry (baseline) of 995 randomly selected CRIC participants with diabetes mellitus across the lifespan.

[0078] Adenine has been identified as a biomarker for kidney disease progression. Various methods can be used to detect and / or measure adenine in a sample. In some embodiments, the processing of a sample or sample mixture can include separation. For example, a sample mixture containing the analyte to be detected can be prepared. To analyze the sample mixture, the components of the sample mixture can be separated and analysis can be performed only on a fraction of the sample mixture. In this way, the complexity of the analysis can be substantially reduced, since the separated analytes can be analyzed individually, thereby increasing the sensitivity of the analysis process. Of course, the analysis can be repeated one or more times on one or more additional fractions of the sample mixture, thereby allowing the analysis of all fractions of the sample mixture.

[0079] Adenine has been identified as a biomarker for all-cause mortality and renal failure in patients with diabetes and eGFR>20 ml / min / 1.73 m2. Various methods can be used to detect and / or measure adenine in a sample. In some embodiments, the processing of a sample or sample mixture can include separation. For example, a sample mixture containing the analyte to be detected can be prepared. To analyze the sample mixture, the components of the sample mixture can be separated and the analysis can be performed only on a fraction of the sample mixture. In this way, the complexity of the analysis can be substantially reduced, since the separated analytes can be analyzed individually, thereby increasing the sensitivity of the analytical process. Of course, the analysis can be repeated one or more times on one or more additional fractions of the sample mixture, thereby allowing the analysis of all fractions of the sample mixture.

[0080] The separation can be performed by chromatography. For example, liquid chromatography / mass spectrometry (LC / MS) can be used to perform such sample separation and mass spectrometry. Furthermore, any chromatographic separation process suitable for separating the analytes of interest can be used. For example, the chromatographic separation can be normal phase chromatography, reverse phase chromatography, ion exchange chromatography, size exclusion chromatography, or affinity chromatography.

[0081] Separation can be performed by electrophoresis. Non-limiting examples of electrophoretic separation techniques that can be used include, but are not limited to, 1D electrophoretic separation, 2D electrophoretic separation, and / or capillary electrophoretic separation.

[0082] Liquid chromatography (LC) is a well-established analytical technique for separating components of a fluid mixture for subsequent analysis and / or identification, in which a column, microfluidic chip-based channel, or tube is packed with a stationary phase material, typically a finely divided solid or gel, such as small particles with a diameter of a few microns. The small particle size provides a large surface area that can be modified with various chemistries to create the stationary phase. A liquid eluent is pumped through a liquid chromatography column ("LC column") at a desired flow rate based on the dimensions and particle size of the column. This liquid eluent is sometimes called the mobile phase. The sample to be analyzed is introduced (e.g., injected) in a small volume into the mobile phase stream in front of the LC column. Analytes in the sample are retarded by specific chemical and / or physical interactions with the stationary phase as they pass through the length of the column. The amount of retardation depends on the nature of the analyte and the composition of the stationary and mobile phases. The time at which a particular analyte elutes or comes out of the end of the column is called the retention time or elution time, and can be a characteristic that reasonably identifies a given analyte, especially when combined with other analytical characteristics such as the exact mass of the given analyte. Or in other words, analytes interact with the stationary phase based on the partition coefficient of each of the analytes. The partition coefficient is defined as the ratio of the time the analyte spends interacting with the stationary phase to the time it spends interacting with the mobile phase. The longer the analyte interacts with the stationary phase, the higher the partition coefficient and the longer the analyte is retained in the LC column. Isocratic flow in LC describes a mobile phase of constant composition. In contrast, the so-called "gradient elution" is a separation in which the composition of the mobile phase changes during the separation process. For example, a 20-minute gradient starts with 10% MeOH and ends with 30% MeOH within 20 minutes.

[0083] Detection of analytes separated in an LC or nano-LC column can be achieved by the use of a variety of different detectors. Spectroscopic detectors rely on changes in refractive index, absorption of ultraviolet and / or visible light, or fluorescence after excitation at suitable wavelengths to detect separated components. Additionally, separated components may be sent from the liquid chromatography column to other types of analytical instruments for further analysis, for example, liquid chromatography-mass spectrometry (LC / MS or LC-MS) separates compounds chromatographically before introducing them into the ion source of a mass spectrometer.

[0084] The purpose of an LC column is to separate analytes such that a unique response (e.g., a UV absorption peak) for each analyte from a selected detector can be obtained for quantitative or qualitative measurement. The ability of an LC column to produce a separation is determined by the dimensions of the column and the particle size supporting the stationary phase. Retention times of analytes can be adjusted by varying the composition of the mobile phase and the partition coefficients of the analytes. Increased chromatographic separation can be achieved through reduction of LC column diameter, increase of LC column length, and / or reduction of stationary phase particle size.

[0085] Mass spectrometry ("MS" or "mass-spec") is an analytical technique used to measure the mass-to-charge ratio of gas-phase ions. This is accomplished by ionizing a sample and separating ions of different masses and recording their relative abundance by measuring the intensity of the ion flux. A typical mass spectrometer includes three parts: an ion source, a mass analyzer, and a detector system. The ion source is the part of the mass spectrometer that ionizes the material under analysis (analyte). The ions are then transported by a magnetic or electric field to the mass analyzer, which separates the ions according to their mass-to-charge ratio (m / z). Many mass spectrometers use two or more mass analyzers for tandem mass spectrometry (MS / MS). The detector records the charge induced or the current generated when ions pass through or strike a surface. A mass spectrum is the result of measuring the signal generated at the detector when m / z ions are scanned through the mass analyzer.

[0086] Mass spectrometry has rapidly developed as an important emerging method for protein characterization. The two main methods for ionization of whole proteins are electrospray ionization (ESI) and matrix-assisted laser desorption / ionization (MALDI). Given the performance and mass range of available mass spectrometers, two approaches are used to characterize proteins. First, intact proteins are ionized by either of the two techniques mentioned above and then introduced into the mass analyzer. Second, proteins are enzymatically digested into smaller peptides using agents such as trypsin or pepsin. The collection of peptide products is then introduced into the mass analyzer. The latter is often referred to as the "bottom-up" approach of protein analysis.

[0087] Analytes of interest to biological researchers are usually part of a very complex mixture of other molecules that coexist in biological media. Due to the high complexity of biological mixtures, coupling separation techniques such as high performance liquid chromatography (HPLC) is often highly desirable or even necessary. In addition, HPLC connected online to ESI-MS offers the possibility of preconcentration of dilute samples, desalting, and detergent removal. In many applications, and especially when analyzing samples of relatively small volumes, improving the detection sensitivity can be particularly important. Improved detection sensitivity with concentration-sensitive detectors such as UV / Vis absorbance and ESI mass spectrometers can be achieved by using HPLC columns with smaller internal diameters (id). For example, increased sensitivity during analysis can result from the use of nano-LC (e.g., column id of 50-100 μm) and capillary LC (e.g., column id of 320 μm). The flow rate of the mobile phase through such columns is from a few nanoliters per minute (nL / min) to a few microliters per minute (μL / min), and the mobile phase can be sprayed directly without post-column splitting. The process of electrospray ionization at flow rates on the order of nanoliters per minute ("nL") has been called "nanoelectrospray ionization" (nanoESI).

[0088] Electrospray ionization (ESI) or nanoESI is a commonly applied ionization technique when dealing with biomolecules such as peptides and proteins. The electrospray process creates highly charged droplets that, under evaporation, create ions representative of the species contained in the solution. The ion sampling orifice of a mass spectrometer can be used to sample these gas-phase ions for mass analysis. When an electric potential or field is applied to the outlet of a conductive needle (often called a sprayer or emitter) against an extraction electrode such as that provided to the ion sampling orifice of a mass spectrometer, the resulting electric field at the needle causes the separation of positively and negatively charged ions in the solution, pushing ions of one polarity (e.g., positive or negative) to the solution surface. The higher the electric field, the greater the surface charge repulsion that counteracts the surface tension of the fluid. When the repulsive force of the solvated ions exceeds the surface tension of the fluid being electrosprayed, the volume of the fluid is pulled into the shape of a cone, known as a Taylor cone, extending from the tip of the needle. A jet of liquid extends from the tip of the Taylor cone and becomes unstable, producing electrically charged droplets. These small charged droplets are attracted towards an extraction electrode, e.g., the sampling electrode of a mass spectrometer. The small droplets are highly charged, and evaporation of the solvent from the droplets results in excess charge in the droplets that is present on the analyte molecules in the electrosprayed fluid. The charged molecules or ions are attracted through the ion sampling orifice of the mass spectrometer for mass analysis. The potential voltage ("V") required to initiate electrospray depends on the size of the sprayer, the surface tension of the solution, and the electric field is approximately 10 6 The physical size of the needle and the surface tension of the fluid determine the density of the electric field lines required to initiate electrospray.

[0089] In so-called nanoelectrospray, the sample is sprayed from a needle with a tip diameter of less than about 5 μm, for example, with a sample flow rate between 5 nL / min and 50 nL / min. Charged droplets with a diameter of less than 1 micron can be formed at flow rates of less than 40 nL / min. These small highly charged droplets can provide more efficient ionization of the analytes contained within the droplets compared to conventional ESI, due to their higher surface-to-volume ratio and the smaller radius that the analytes need to diffuse to reach the charged surface of the droplet. Thus, nanoESI-MS can be used to analyze small amounts of samples with low sample concentrations (e.g., femtomoles / microliter). Furthermore, in nanoESI, the ionic response of the analytes contained in the sample solution is proportional to their concentration, not their total amount. This means that the signal intensity measured using mass spectrometry is the same if the solution is sprayed at 200 nL / min or 50 nL / min or 20 nL / min. Thus, a 5-fold reduction in flow rate results in roughly a 5-fold increase in mass spectrometry scans acquired for the same amount of sample. As a result, averaging of the signals from an increased number of scans improves the signal-to-noise ratio and ion statistics, allowing multiple MS / MS experiments on an analyte and greater accuracy in identifying the analyte.

[0090] Tandem mass spectrometry (MS / MS) is a popular experimental method for identifying biomolecules such as proteins. Tandem MS usually involves multiple steps of mass selection or analysis, separated by some form of fragmentation. Tandem mass spectrometers are capable of multiple stages of mass analysis. For example, one mass analyzer can isolate one peptide from many other peptides that enter the mass analyzer. A second mass analyzer then stabilizes the peptide ion while it collides with a gas and causes it to fragment by collision-induced dissociation (CID). A third mass analyzer then characterizes the fragments generated from the peptide. Tandem MS can also be performed over time in a single mass analyzer, such as in a quadrupole ion trap. There are various methods for fragmenting molecules for tandem MS, including collision-induced dissociation (CID), electron capture dissociation (ECD), electron transfer dissociation (ETD), infrared multiphoton dissociation (IRMPD), and blackbody infrared radiation dissociation (BIRD).

[0091] Some specific, non-limiting examples for detecting and / or measuring adenine in a sample include the following:

[0092] A. ZipChip™-QExactive Assay for Urinary Adenine Adenine was assayed by using quantitative capillary electrophoresis (CE) coupled to mass spectrometry (ZipChip™-QExactive; Thermo Scientific, catalog numbers 00950-01-00492 and 0726030). The ZipChip™ device (Figure 11A) is a capillary electrophoretic separation method on a microfluidic device (Figure 11B). It allows rapid sample preparation, zone electrophoresis, is highly resistant to sample matrix effects, does not require labeling of analytes, can use small sample volumes (2-20 μl), and allows high throughput analysis (80-90 samples per day). The ZipChip™ platform was connected to a Thermo QC-Exactive for mass spectrometric detection of specific metabolites. The amino acid protocol was adapted to specifically measure urinary adenine.

[0093] Briefly, as a non-limiting example, for the ZipChip™ assay, 10 μL of urine sample or calibration standard mixture was mixed with 90 μL of extraction solution containing 80% methanol, 100 mM ammonium acetate, and 1 μM stable isotope-labeled internal standard (including adenine) in a 96-well plate. After mixing, the sample or calibration standard was stored in a -20°C freezer for at least 1 hour and then centrifuged at 5000 rpm for 5 minutes. 50 μL of the supernatant was transferred to a clean 96-well plate for analysis. Metabolite separation was achieved on a microfluidic chip that integrated capillary electrophoresis (CE) with nanoelectrospray ionization through the ZipChip™ interface (908 Devices, Boston, MA). For each sample, 20 μL of solution was placed in the sample well and then injected into the HS chip (Thermo Scientific, catalog number 00950-01-00498) using a 10-second load time. A field strength of 1000 V / cm was applied for separation for 4 min with a background electrolyte solution consisting of 2% formic acid in 50% methanol in water. Mass spectrometry acquisition was performed on a Q-Exactive™ mass spectrometer (Thermo, San Jose, CA). The resolving power was 17,500 and the AGC target was 3×10 6 The time was 20 ms, the maximum injection time was 20 ms, and the scan range was 75-500 m / z. Thermo Scientific software Xcalibur-Quan Browser was used for quantitative data processing. Calibration curves for all metabolites were included on each plate. Metabolite data for targeted assays were normalized to urinary creatinine measured at the CRIC Central Laboratory or by the ZipChip™-QExactive™ method if creatinine was not available.

[0094] ZipChip- QExactive Data: Intra- and Inter-assay Variability. Urinary adenine / creatinine ratios were measured in pooled human urine samples on two separate days with four replicates each day. Intra-assay CV was <5% for four replicate samples performed on the same day (%CV 4.5% on day 1 or 4.2% on day 2). Inter-day QC CV was 7.4%. Urine adenine mg / gram creatinine TIFF2025506412000006.tif60135

[0095] B. LC-MS / MS Method for Urinary Adenine Sample extraction: Calibration samples, urine samples were prepared in a 96-well plate in a mixed solvent of 80:20 MeOH:H2O. Internal standard was added at a concentration of 1 μM to a final volume of 200 μL. Multiple pipetting was performed in each well. The plate was covered with a cover sheet and placed at -20°C for at least 1 hour. The plate was then centrifuged at 4°C, speed 9 for 10 minutes. The plate was slowly removed. The cover was removed and 100 μl of the top solution was taken and transferred to an LCMS vial with an insert for LCMS analysis. The LC vial was centrifuged at 9000 rpm for 20 minutes at room temperature and then analyzed by LCMS using normal phase chromatography with a mobile phase of water (A) and methanol (B), both containing 0.5% formic acid.

[0096] LC-MS / MS method and calibration curve: The LC-MS / MS method was optimized for the detection of adenine using rat urine standard samples. A multipoint calibration curve was performed for both adenines at levels from 1 nM to 40 μM. A linear instrument response with a polynomial correlation coefficient of 0.99 was achieved in this range. Data were acquired simultaneously in PRM and SIM modes. A calibration curve of the area of ​​selected MS / MS fragments compared to the internal standard versus standard concentration was used for quantification of adenine in urine.

[0097] Assay correlation between Zipchip and LC / MSMS: The ZipChip™ method was compared to the LC-MS / MS method since LC-MS / MS is considered the gold standard for measuring non-protein chemical entities in biological fluids. Urinary adenine from urine samples of control and diabetic rats (n=23 samples) was acquired by Zipchip™ and LC / MSMS to evaluate the correlation between the methods. Pearson correlation and t-test were determined using all concentration data of control and ZDF samples. There was a very good correlation between the ZipChip™ and LC-MS / MS methods (r 2 =0.82 and p<0.00001).

[0098] C. HPLC Assay for Urinary Adenine To avoid the use of mass spectrometers, HPLC protocols can be developed that allow for the most cost-effective use of the instrument. The HPLC protocols were tested against the gold standard LC-MS / MS and ZipChip™ QExactive™ methods described herein. A simple protocol is described as follows:

[0099] Adenine and creatinine will be identified and quantified using HPLC / UPLC with DAD / UV detector. High performance liquid chromatography (HPLC) is an analytical chemistry technique used to separate, identify, and quantify each component in a mixture. It utilizes a pump to pass a pressurized liquid solvent containing the sample mixture through a column packed with a solid adsorbent material. Each chemical species in the sample will interact differently with the adsorbent material in the column, causing different flow rates for the different components, resulting in separation of the components as they exit the column. This HPLC protocol for measuring adenine and creatinine will offer an advantage over mass spectrometry-based protocols by requiring less expensive equipment and highly trained personnel to run the protocol.

[0100] As a non-limiting example, an efficient HPLC / UPLC method is established using a small volume of solution (5-20 μL) containing standards ranging from 1 μM to 100 μM. Metabolites are separated using a reversed-phase column such as a Hypersil™ C-18, 5-Am particle size, 250 mm×4.6 mm column (or any equivalent column) and a step gradient at a flow rate of 0.9 mL / min with two buffers and tetrabutylammonium hydroxide as pairing reagent. The starting HPLC / UPLC conditions may be considered as Buffer A (12 mM tetrabutylammonium hydroxide, 10 mM KH2PO4, 0.125% methanol, pH 7.00) and Buffer B (2.8 mM tetrabutylammonium hydroxide, 100 mM KH2PO4, 30% methanol, pH 5.50) in a step gradient starting from 100% Buffer A at 2 min and finally 0% Buffer A at 30 min. The separated analytes are detected by a highly sensitive UV / DAD detector at wavelengths from 200 nm and 400 nm. 7-(β-hydroxyethyl) theophylline is used as an internal standard and spiked into the biological samples to correct for analyte losses during sample preparation. To establish an efficient method, the buffer gradient and concentration may need to be adjusted to achieve reasonable separation of adenine and creatinine. The method is validated by recovery tests of the spiked standards in filtered and deproteinized urine and plasma samples (200 μL), as well as calibration curves ranging from 0, 10 nM to 500 μM for each metabolite and the linearity response of the method. An internal standard (10 μM) is used in solutions of the standards and biological samples. The linearity of the curves is assessed by plotting the area under the spectrum versus the concentration of each metabolite. Intra- / inter-assay precision is performed by analyzing three replicates of quality control samples at two different concentrations with the same method on the same day (for intra-assay) or on different days (for inter-assay). With adequate recovery and calibration linearity, the HPLC / UPLC method can be applied to biological samples.The biological samples are diluted 10-fold in DI water and then filtered through a membrane filter such as an MCE (mixed cellulose ester, 0.22 μm pore size) syringe filter or other efficient technique. An aliquot (100 μL) of the filtered biological sample is transferred to an HPLC vial with an insert. The samples are stored at -80°C if not analyzed immediately. The biological samples are analyzed using the HPLC / UPLC method in the proposed sequence of several blanks, the first series of calibration curve, the biological samples, and the second series of calibration curve samples. Data are obtained in terms of the area under the absorbance spectrum and the wavelength at the peak maximum. Multipoint calibration curves for each standard are constructed based on the relative area of ​​the standard above the internal standard versus the concentration of the standard. The equation for the calibration curve is used to estimate the unknown concentration of the metabolite of interest in urine and plasma. Any dilution factor is taken into account in the quantification.

[0101] III. Treatment of Kidney Disease Some treatment methods include (i) administering a drug to a subject in one or more doses (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 doses); (ii) determining the presence, absence, or amount of a biomarker in or from the subject after (i); (iii) providing instructions to increase, decrease, or maintain a subsequent dose of the drug for administration to the subject; and (iv) optionally administering the subsequent dose to the subject, where the subsequent dose is increased, decreased, or maintained compared to the earlier dose in (i). In some embodiments, the presence, absence, or amount of the biomarker is determined before, after, or before and after each dose of drug is administered to the subject, and sometimes the presence, absence, or amount of the biomarker is not determined after each dose of drug is administered (e.g., the biomarker is assessed after one or more of the first, second, third, fourth, fifth, sixth, seventh, eighth, ninth, or tenth dose, but not after every dose is administered).

[0102] The instruction to adjust the subsequent drug dose can be considered as the need to increase or decrease the subsequent drug dose. The instruction to adjust or maintain the subsequent drug dose can be considered by the clinician, who can act on the instruction in certain embodiments. In some embodiments, the clinician can choose not to act on the instruction. Thus, the clinician can choose to adjust or not adjust the subsequent drug dose based on the instruction provided.

[0103] The instructions for adjusting or maintaining the subsequent drug dose and / or the subsequent drug dosage can be provided in any convenient manner. The instructions can be provided in table form (e.g., physical or electronic media) in some embodiments. For example, biomarker thresholds can be provided in a table, and the clinician can compare the presence, absence, or amount of the biomarker determined for the subject with the threshold. The clinician can then identify the instructions for the subsequent drug dose from the table. In certain embodiments, the instructions can be presented (e.g., displayed) by the computer after the presence, absence, or amount of the biomarker is provided to the computer (e.g., entered into the computer's memory). For example, the presence, absence, or amount of the biomarker determined for the subject can be provided to the computer (e.g., entered into the computer's memory by a user or sent to the computer via a remote device in a computer network), and software in the computer can generate instructions for adjusting or maintaining the subsequent drug dose and / or provide the amount of the subsequent drug dose. Subsequent doses can be determined based on certain factors other than the presence, absence, or amount of a biomarker, such as, for example, the body weight of the subject, the level of one or more metabolites for the subject (e.g., a metabolite level related to liver function), etc.

[0104] Once the subsequent dose is determined based on the instruction, the clinician may administer the subsequent dose or provide instructions to another person or entity to adjust the dose. The term "clinician" as used herein refers to a decision maker, which in certain embodiments is a medical professional. In some embodiments, the decision maker can be a computer or a displayed computer program output, and the health care provider can act according to the instructions or subsequent drug dose displayed by the computer. The decision maker may administer the subsequent dose directly (e.g., the subsequent dose may be infused into the subject) or remotely (e.g., pump parameters may be changed remotely by the decision maker).

[0105] In one embodiment, the treatment includes surgery, chemotherapy, radiation therapy, dietary restrictions, treatment of hypertension (e.g., with angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor antagonists), treatment of diabetes (e.g., with sodium-glucose-coupled transporter 2-inhibitors (SGLT2-i)), weight control, smoking cessation, treatment of high cholesterol and / or other lipid levels, kidney transplant, dialysis, administration of erythropoietin and / or calcitriol, diuretics, vitamin D, or phosphate binders, or combinations thereof. In one embodiment, the subject is administered bardoxolone methyl, olmesartan medoxomil, sulodexide, and avosentan.

[0106] IV. Kits In another aspect, the present invention provides a kit for quantifying adenine and qualifying kidney disease state, the kit is used to detect and quantify adenine.In one embodiment, the kit includes a support such as a chip, a microtiter plate, or a bead or a resin.

[0107] In a further embodiment, such kits can include instructions for suitable operating parameters in the form of a label or separate insert. EXAMPLES

[0108] V. Working Examples The following examples and figures are included to demonstrate preferred embodiments of the invention. Those skilled in the art should recognize that the techniques disclosed in the examples or figures represent techniques discovered by the inventors to work well in the practice of the invention and therefore may be considered to constitute preferred modes for its practice. However, those skilled in the art should recognize in light of this disclosure that many changes can be made in the specific embodiments disclosed and still obtain the same or similar results without departing from the spirit and scope of the invention.

[0109] Example 1 High-throughput metabolomics and progression of diabetes-related kidney disease: evidence from the Chronic Renal Insufficiency (CRIC) study Metabolomics may provide novel prognostic biomarkers and elucidate mechanisms of diabetes-related kidney disease (DKD) progression. Using diverse CRIC samples from 995 CRIC participants with diabetes, high-throughput untargeted assays, followed by targeted analysis, and rigorous statistical analysis to reduce false discoveries, we identified several novel metabolites associated with DKD progression. These findings can inform risk stratification and treatment strategies for patients with DKD. Urine samples (N=995) were assayed for relative metabolite abundance by untargeted flow-injection mass spectrometry (MS) and rigorous statistical criteria were used to remove noise compounds, resulting in 698 annotated metabolite ions. Ion abundances of 698 metabolites, along with clinical data (demographics, blood pressure, HbA1c, eGFR, and albuminuria), were utilized to develop univariate and multivariate models for eGFR (estimated glomerular filtration rate) gradients using penalized (lasso) and random forest models. Final models were tested for time to ESKD (end-stage kidney disease) via cross-validated C-statistics. Pathway enrichment analysis and targeted analysis of a subset of metabolites were also performed. Six eGFR gradient models selected 9–30 variables. In the adjusted ESKD model with the highest C-statistics, valine (or betaine) and 3-(4-methyl-3-pentenyl)thiophene were associated with a 44% and 65% higher risk of ESKD per doubling of metabolite abundance, respectively (p<0.05). Additionally, 13 (out of 15) prognostic amino acids, including valine and betaine, were identified in the targeted analysis. Enrichment analysis revealed pathways implicated in kidney and cardiometabolic diseases.

[0110] A. Study Design and Methods Study cohort. We used the metabolomic substudy of the Chronic Renal Insufficiency Cohort (CRIC). The parent CRIC study recruited (from 2003) an ethnically diverse group of subjects aged 21-74 years, approximately 50% with diabetes, and a wide range of renal function [Feldman et al. J Am Soc Nephrol. 2003, 14(7 Suppl 2):S148-53]. Informed consent was obtained from participants; the protocol was approved by the IRB and the Scientific Data Coordinating Center (approval number 59 807882). The study included subjects with CKD stages 3a, 3b, and 4, eGFR 45-60, 30-45, and 20-30 ml / min / 1.73 m, respectively. 2 Methods: We analyzed the urinary metabolome at study entry (baseline) of 995 randomly selected CRIC participants with diabetes mellitus across the lifespan.

[0111] Disease outcomes. Two outcomes were assessed: percentage of annual eGFR change (eGFR slope) and time to ESKD. EGFR-slope was estimated via a mixed model using continuous eGFR measurements as previously described [Kwan et al. Am J Kidney Dis. 2020;76(4):511-20]. Time to ESKD was the time from entry into the CRIC study to incident renal failure requiring renal replacement therapy or kidney transplant; dropout or death prior to renal failure was considered a censored event.

[0112] eGFR was calculated using the CKD-EPI equation [Levey et al., Ann Intern Med. 2009;150(9):604-12]. Results were consistent when analyses were repeated using the CRIC-eGFR equation (data not shown) [Anderson et al. Am J Kidney Dis. 2012;60(2):250-61], therefore findings are reported using the widely used CKD-EPI equation.

[0113] Statistical analysis - Overview of analysis steps. (Figure 5) Stringent filtering was performed to exclude metabolite ions with high noise or low biological variability. Associations of single metabolites with DKD outcomes were tested with and without adjustment for clinical variables, corrected for multiple comparisons. Multivariate metabolite models were then developed using statistical and machine learning methods to identify marker signatures associated with eGFR slope, and these models were further tested for time to ESKD. A unique aspect of the approach is that we did not train the models on ESKD outcomes; thus, ESKD outcomes serve as an "internal replicate" for long-term clinical outcomes. Finally, pathway enrichment analysis was performed to investigate the biological basis of selected metabolites, and targeted analysis of a subset of metabolites was performed.

[0114] Metabolite ion filtering. Technical replicates were utilized and QC and CRIC samples were used to remove ions with insufficient confidence in the untargeted analysis. Of the 1899 annotated metabolite ions, 698 passed the filtering criteria and were the final metabolite ion set for all subsequent analyses. A single ion could annotate multiple metabolites; these resulting ambiguities were clarified as appropriate.

[0115] Associations of single metabolites with outcomes. Associations between 698 log2-transformed metabolite ions and outcomes were examined with and without adjustment for clinical variables: age, sex, race, smoking, baseline BMI, mean arterial pressure (MAP), HbA1c, eGFR, albuminuria [Kwan et al. Am J Kidney Dis. 2020;76(4):511-20]. For eGFR slope, Pearson correlations were calculated and fitted to linear models; for ESKD, Cox models were fitted. Benjamini-Hochberg false discovery rate (FDR) was used to correct for multiple comparisons [Benjamini and Hochberg J Royal Statist Soc, Series B. 1995;57:289-300].

[0116] Multivariate models for eGFR slope. Using eGFR slope as outcome, penalized regression models (via Lasso) and machine learning models (via Random Forest) were developed to derive multivariate prognostic metabolomic signatures. Lasso reduces overfitting by imposing a penalty (λ) [Hastie et al. The elements of statistical learning: data mining, inference, and prediction. 2nd ed. NYC: Springer; 2009]. Two λ values ​​selected by 10-fold cross-validation were considered: λ.min., the value that yielded the lowest prediction error; and λ.1se, the value within 1 SD of the lowest prediction error. Four Lasso models were fitted; each included 698 ions and 9 clinical variables as covariates. Two models utilized either λ.min or λ.1se to force inclusion of all 9 clinical variables. The other two models did not force inclusion of clinical variables. For random forests, the percentage increase in mean square error was used to rank the importance of variables [Hastie et al. The elements of statistical learning: data mining, inference, and prediction. 2nd ed. NYC: Springer; 2009]; for comparison, the same number of variables were selected as in the corresponding Lasso model (without forcing clinical variables). Thus, six multiple metabolite ion models were fitted, each of which selected the best set of predictors: four Lasso models and two Random Forest models. As a final sensitivity analysis, four elastic net models were fitted, which can select groups of correlated features and may better mimic biological pathways.

[0117] Internal replication for ESKD outcomes. To evaluate the models for time to ESKD, six Cox models were fitted, where the predictors were the variables selected in the six eGFR slope outcome analyses. Each Cox model was compared to its corresponding model of clinical variables only using likelihood ratio tests. To quantify the performance of the models, the mean and 95% CI of the C-statistic were estimated using 5-fold cross-validation repeated 100 times. The predictors used in these six Cox models were the predictors selected in the corresponding eGFR slope models; no tuning or variable selection was used in the Cox models. To evaluate whether the predictors of eGFR slope also predicted long-term outcomes (i.e., ESKD), further training on ESKD was intentionally avoided.

[0118] Enrichment analysis. The definition of known biological pathways with their respective involved metabolites was obtained from HMDB [Wishart et al., Nucleic Acids Res. 2018;46(D1):D608-d17]. 743 pathways were considered, A hypergeometric test was performed on each pathway definition via TIFF2025506412000007.tif13128. where M = number of measured metabolite ions, K = number of measured compounds in the pathway definition, N = number of "hits", i.e., selected / prognostic metabolite ions, and x = number of "hits" mapped to the pathway. p-values ​​were corrected for multiple testing using the Benjamini-Hochberg method.

[0119] Assay validation. The targeted assay was used to validate the selection and annotation of 15 metabolites detected by the untargeted analysis that were prognostic in the ESKD analysis. Again, Cox models were fitted, adjusting for nine clinical variables. Standardized hazard ratios (HRs) are presented to compare untargeted and targeted analyses.

[0120] B. Results Participant characteristics. At enrollment, participants (n=995) were on average 59.9 years old, 56% were male, 44% were white, and 42% were black; on average (mean (SD)) were obese (BMI 34.2 (7.9)), had poorly controlled diabetes (HbA1c 7.6 (1.5)%), and had moderate to poor renal function (eGFR 40.6 (11.2) ml / min / 1.73 m 2 The mean gradient of decline in eGFR was 1.8 (SD = 1.9) ml / min / 1.73 m 2 / year; 137 (N=360), or 36%, had ESKD during the 10-year study (range: 2-10 years). Subjects with missing clinical variables (<2%) were excluded.

[0121] Associations between single metabolites and disease outcomes. Of the 698 ions, 89 were significantly correlated with eGFR slope without adjustment for clinical variables (FDR corrected, p<0.05). In adjusted analyses, 6 ions remained significant with β coefficients between -0.45 and 0.3. Also, 123 (unadjusted) and 99 (adjusted) ions were significantly associated with ESKD in Cox regression. After adjustment, HRs ranged from 1.12 to 1.84. The prognostic ion set contained several amino acids (valine, isoleucine, tryptophan) and other compounds, such as hydroxybutanoic acid. Only one ion annotated as 3-(4-methyl-3-pentenyl)thiophene (ion index 1098) was associated with both eGFR slope and ESKD in the adjusted model, with a coefficient (95% CI) of -0.44 (-0.68, -0.21) for eGFR slope and an HR (95% CI) of 1.84 (1.45, 2.32), indicating that higher abundance of this compound may be associated with worse DKD progression. Hereafter, the 99 ESKD-151-associated metabolites are denoted as the 99-ESKD-associated set.

[0122] Multivariable prognostic metabolites for eGFR slope outcome. Each of the Lasso or Random Forest models selected 9–30 variables, resulting in 49 ions (out of 698) across the six prognostic models, denoted the 49-eGFR-associated set. Baseline albuminuria, blood pressure, and HbA1c were selected in all six models, and not surprisingly, higher levels of these clinical markers were associated with steeper eGFR declines; race was also selected in all six models; and 3,4-dicaffeoyl-1,5-quinolactone was selected in all models except model 1 (the clinical-only model). Nine ions (annotated as 3,4-dicaffeoyl-1,5-quinolactone, butynal, 3-(4-methyl-3-pentenyl)thiophene, C10:3, zalcitibine, asparaginyl-hydroxyproline, valine (or betaine), arginyl-glutamine, and pentose (or diisopropyl disulfide)) were selected in at least three models; an additional 13 ions were selected in at least two models. The elastic net model had a similar C-statistic, and therefore the more parsimonious Lasso model was retained.

[0123] Internal replication. The final selected features from each of the six eGFR slope models were tested for ESKD outcome in a Cox model. The p-values ​​of the likelihood ratio test were <0.0001 when comparing each of the six models with the corresponding model with only clinical features, i.e., adding metabolite ions significantly improved the fit of the model. Several ESKD models had similar median C-statistics, ranging from 0.82 to 0.85. The best (model 2), with 29 variables, had a cross-validated median C-statistic (95% CI) of 0.85 (0.85, 0.86). This model selected 20 metabolite ions via lasso; 14 were significantly associated with eGFR slope as evidenced by bootstrap 95% CIs excluding 0. Of more interest are the five ions significantly (at the 5% level) associated with time to ESKD. Higher abundance of valine (or betaine) and 3-(4-methyl-3-pentenyl)thiophene was each associated with increased risk of ESKD (HR 1.44 and 1.65, respectively); higher abundance of asparaginyl-hydroxyproline was associated with lower ESKD risk (HR=0.7). Two other significantly associated compounds were pipezethate and aminophylline. Importantly, our Lasso model was not trained on ESKD outcomes, so the results of the Cox model are expected to be valid and not influenced by model selection. Sensitivity analyses including ACE inhibitors or ARBs were performed and used in the Cox regression in model 2. For the 29 variables in model 2, there was a negligible change in the Cox model coefficients; the HR (95% CI) of ACE inhibitor or ARB use was 1.22 (0.92, 1.63, p=0.17), which was not statistically significant at the 5% significance level.

[0124] Enrichment analysis. Pathway enrichment was performed based on 49-eGFR-related set, 99-ESKD-related set, and the combination of 49-set and 99-set (=131 ions). Thus, in formula (1), M=698; N=49 or 99 or 131; K varies by pathway; and x=number of ions in pathway, and also in prognostic 49-set, 99-set, or 131-set.

[0125] Pathways that were consistently and significantly enriched across both eGFR slope and ESKD models were those related to enzyme deficiencies, aciduria, and acidemia, and amino acid metabolism. Interestingly, the valine-leucine-isoleucine degradation pathway, which is involved in insulin resistance, cardiometabolic risk, cardiomyopathy, and CKD [Manoli and Venditti, Transl Sci Rare Dis. 2016; 1(2):91-110;White and Newgard, Science. 2019;363(6427):582-3]; the 2-aminoadipic acid 2-oxoadipic aciduria and lysine degradation pathway, which is associated with diabetes and kidney disease [Sell et al., Ann NY Acad Sci. 2008;1126:205-9;Verzola et al, J Inherit Metab Dis. 2012;35(6):1011-9]; and the tryptophan pathway [Cheng et al., Sci Rep. 2020;10(1):12675;de Vries et al., Am J Physiol Renal Physiol. 2017;313(2):F475-f86; Debnath et al. Int J Tryptophan Res. 2017;10:1178646917694600] were enriched in the 99-ESKD and combined 131-ion sets.

[0126] Validation by targeted CE-MS approach. In the targeted validation analysis, 13 of 15 metabolites were significantly associated with ESKD. As shown in Figure 6, the HRs (95% CI) in the untargeted and targeted analyses were comparable.

[0127] Untargeted urinary metabolomics assay: sample processing and feature extraction. Frozen 24-h urine samples from 995 CRIC participants and healthy controls were thawed, centrifuged, and the sediment-free supernatants were diluted 1:50 with double-distilled water in 96-well polypropylene storage microplates (AB-1058, Abgene), sealed with easy-peel heat-sealing foil (AB-0745, Abgene), and stored frozen until analysis. Diluted urine was shipped on dry ice and stored at -80°C until 2 weeks prior to data acquisition by mass spectrometry. Samples were injected in duplicate (i.e., technical replicates) by untargeted flow injection analysis (Fuhrer et al., 2011) on an MPS 3 xt autosampler (Gerstel) coupled to an Agilent 6550 Q-TOF mass spectrometer (Agilent Technologies). Briefly, the flow rate was 150 μL / min of a mobile phase consisting of isopropanol / water (60:40, v / v) buffered with 5 mM ammonium fluoride, and homotaurine and hexakis(1H,1H,3H-tetrafluoropropoxy)phosphazine (HP-0921, Agilent Technologies) were added to the mobile phase for online mass axis correction. Profile mass spectra (MSI) were recorded in 4 GHz acquisition mode, from 50 to 1000 m / z, in negative ionization mode with the following source settings: temperature 225 °C, drying gas 11 L / min, nebulizer pressure 20 psig, sheath gas temperature 350 °C, sheath gas flow rate 10 L / min, Vcap voltage 3500 V, nozzle voltage 2000 V, fragmentor voltage 350 V, and Oct 1 RF Vpp voltage 750 V. All data processing and analysis steps were performed in Matlab R2017b (The Mathworks) using functions built into the bioinformatics, statistics, database, and parallel computing toolbox. Sample alignment and gap-filling were followed by correction for ion intensity drift over time and between plates, and recalibration of the common mass axis with known frequently occurring ions.Approximately 15k commonly observed ion masses were annotated based on exact mass comparison with a mass tolerance of 1 mDa to the Human Metabolome Database HMDBv4.0, resulting in 1899 annotated ion masses assuming a single deprotonation.

[0128] Targeted urinary metabolomics assay: sample processing and feature extraction. A subset of 15 candidate metabolites from the untargeted panel was assayed by using quantitative capillary electrophoresis (CE) coupled to mass spectrometry (ZipChip-Qexactive) to validate the identification and annotation of metabolite ions from the untargeted method.

[0129] For the ZipChip™ assay, 10 μL of urine sample or calibration standard mixture was mixed with 90 μL of extraction solution containing 80% methanol, 100 mM ammonium acetate, and 1 μM stable isotope-labeled internal standard in a 96-well plate. After mixing, the sample or calibration standard was stored in a -20°C freezer for at least 1 h and then centrifuged at 5000 rpm for 5 min. 50 μL of the supernatant was transferred to a clean 96-well plate for analysis. Metabolite separation was achieved on a microfluidic chip integrating capillary electrophoresis (CE) with nanoelectrospray ionization through the ZipChip™ interface (908 Devices, Boston, MA). For each sample, 20 μL of solution was placed in the sample well and then injected into the HS chip with a load time of 10 s. A field strength of 1000 V / cm was applied for separation for 4 min with a background electrolyte solution consisting of 2% formic acid in 50% methanol in water. Mass spectrometry acquisition was performed on a Q-Exactive mass spectrometer (Thermo, San Jose, CA). The resolving power was 17,500 and the AGC target was 3 × 10 6The time was 20 ms, the maximum injection time was 20 ms, and the scan range was 75-500 m / z. Thermo Scientific software Xcalibur-Quan Browser was used for quantitative data processing. Calibration curves for all metabolites were included on each plate. Metabolite data for the targeted assays were normalized to urinary creatinine measured at the CRIC central laboratory.

[0130] Untargeted metabolomics data: filtering of metabolic signatures. Leveraging technical replicate data for each sample, criteria were developed to filter out metabolite ions showing poor reproducibility. A total of 1899 annotated metabolite ions were measured for 995 CRIC subjects, together with pooled urine samples from healthy subjects as quality control (QC). All data were collected in duplicate. Three QC samples per plate were randomly performed in duplicate within each 96-well plate, resulting in six measurements per plate and a total of 198 measurements across 33 plates. The filtering process consisted of three steps. In step 1, only the QC data were used. Three reliability metrics were calculated for the abundance of each metabolite ion: correlation coefficients between technical replicates (Spearman and Pearson QC CC), intraclass correlation (QC ICC), and coefficient of variation (QC CV). The QC ICC for each metabolite ion abundance was calculated as the variance between technical duplicates divided by the total variation (including batch and replicate variations); the QC CV was calculated as the standard deviation between the abundances of the technical duplicates divided by the sample mean. A low correlation, high ICC, or high CV value would indicate poor confidence, i.e., high variability for the signal. We formalized these criteria as follows: QC_Spearman<0.85 or QC_Pearson<0.85 QC_CV≧0.05 QC_ICC≧0.05 Ions that met any of the above criteria were excluded. These cut-off values ​​are based on standard assay reliability metrics. Filtering step 2 was performed using CRIC samples, where the goal was to filter out metabolite ions that exhibited low biological variability. To this end, intraclass correlation (CRIC ICC) as the ratio of inter-subject variability to total sample variability was calculated; ions with ICC<=0.35 were further filtered out.

[0131] Thus, in summary, the final set of 698 retained metabolite ions met all criteria: QC Spearman >=0.85 and QC_Pearson >=0.85 and QC_CV<0.05 and QC_ICC<0.05 and CRIC_ICC>0.35. The metabolite ion abundances of the technical replicates (two per sample) were then averaged. In a final filtering step, low abundance metabolite ions were filtered out to exclude non-informative ions in the noise range. Ions that passed the filtering criteria and count thresholds constituted the final metabolite ion feature set for modeling.

[0132] Targeted metabolomic data: variability. QC CVs for metabolomic data are calculated in the same way as above. Interday CVs obtained from healthy human urine samples were calculated. Of the 15 metabolites included in the targeted analysis, 7 have a QC CV of <0.05 and 3 have a QC CV between 5% and 10%. Four of them, ornithine, isoleucine, asparagine, and betaine, have a QC CV greater than 10%.

[0133] High-throughput metabolomics offers great potential, but the scale and measurement error pose analytical and inferential challenges. To address these challenges, we perform two steps: (1) identify a sparse prognostic set of metabolites after adjusting for known clinical factors, and (2) use pathway analysis to derive biological meaning. First, we used untargeted assays to test the association of single metabolites with eGFR slope and ESKD.

[0134] As a next step, we performed quantitative targeted assays of 15 amino acid metabolism-metabolites from 99 (non-targeted) ions and validated the prognostic value of 13 (out of 15). The finding of prognostic value of urinary amino acids in a large CRIC cohort, even after adjustment for clinical factors, suggests that additional aminoaciduria may be a risk factor for DKD progression, independent of albuminuria.

[0135] Using multivariate analysis, asparaginyl-hydroxyproline and arginylglutamine are identified as novel findings in DKD research. In addition, valine, a glycogenic branched-chain amino acid, as well as C10:3 (acyl-carnitine) and 3-(4-methyl-3-pentenyl)thiophene were also identified. Importantly, in the multiply adjusted Cox model with the highest C-statistic, we identified several interesting prognostic (p<0.05) metabolite ions. Valine (or betaine) and 3-(4-methyl-3-pentenyl)thiophene were associated with 44% and 65% higher risk of ESKD per doubling of ion abundance, respectively. Importantly, the Cox model analysis does not include any training or variable selection, despite the same cohort, and therefore may be less biased in HR.

[0136] To systematically exploit the biological content of prognostic metabolite ions, we performed enrichment analysis using pathway, disease, and function definitions derived from HMDB. We focused on metabolic pathway enrichment because pathway definitions are less prone to curation abnormalities, more finite, and well-defined compared with disease and function definitions. We identified branched-chain amino acid pathways, namely, valine-leucine-isoleucine degradation, isovaleric acidemia / aciduria, propionic acidemia, and methylmalonic acidemia. Our study found that higher levels of tryptophan were associated with higher ESKD risk in both untargeted and targeted analyses, and that the tryptophan pathway was significantly enriched in our set of ESKD-related metabolites. To the best of our knowledge, these findings are novel and further investigation of urinary tryptophan is warranted.

[0137] In summary, large-scale untargeted and targeted metabolomics analyses were performed with diverse cohorts and identified several metabolites implicated in DKD. We used robust statistical models incorporating rigorous techniques to reduce overfitting: cross-validation for feature selection, replication of results to long-term clinical outcomes, and validation with targeted assays. Although we highlighted and validated several prognostic metabolites and associated pathways, the most important aspect of our study is that we identified 131 potential prognostic metabolites in untargeted analyses, some of which have not been addressed before. We hope that providing this list will encourage further investigation of these promising metabolites and enhance our understanding of DKD, ultimately leading to better treatment and disease management.

[0138] Example 2 The role of adenine in renal failure and mortality in diabetes mellitus The progression of diabetes-related kidney disease and CKD remains enigmatic. This example uses an unbiased multi-omics approach focused on spatial metabolomics on human kidney biopsies through the Kidney Precision Medicine Project. The major pathway associated with tubulointerstitial disease is the polyamine / purine pathway, and one potential key metabolite linked to both pathways is adenine. MALDI-mass spectrometry imaging with optical overlay identified adenine localized to areas of atrophied tubules, arteriosclerotic vessels, and sclerotic glomeruli in kidney biopsies from patients with diabetic and nondiabetic chronic kidney disease. In a rat model of diabetes-related kidney disease (ZDF rats), tissue adenine and urinary adenine / creatinine were correlated with glomerulosclerosis and tubulointerstitial fibrosis. In a cohort of Pima Native Americans with diabetes who underwent protocol kidney biopsy after urine measurement, urinary adenine / creatinine levels predicted glomerulosclerosis (r=0.57, p=0.03, n=15) better than urinary ACR (r=0.22, p=0.17). Furthermore, the upper tertile of urinary adenine / creatinine ratio was prognostic of measured GFR decline in Pima Native Americans with normoalbuminuria (HR 4.3, CI 1.14-16.21, p=0.03, n=32). This pattern was consistent in patients with diabetes in the Chronic Renal Insufficiency Cohort Study (CRIC), where the upper tertile of urinary adenine / creatinine ratio was found to be prognostic of renal failure in patients with diabetes and normoalbuminuria compared to the lowest tertile (n=301) (upper tertile HR 4.42, CI 1.56, 12.5, p=0.005, n=302, and middle tertile (HR 3.01, CI 1.09-8.32, p=0.034, n=301)). Thus, urinary adenine is a novel prognostic biomarker for ESKD in diabetes-related kidney disease with normoalbuminuria.

[0139] A. Results Data integration directed towards higher levels of bioinformatics across the KPMP TIS. It was demonstrated that integrated analysis of multiple omics layers from different TISs provides more robust, interpretable, and translatable data compared to any single omics layer alone. We developed an integrated approach centered on metabolic pathways by producing a map of all biochemical reactions and metabolic pathways that connect with other intracellular processes including transport systems, signaling pathways, and cytoskeleton systems. Secondly, we predicted overlapping, complementary, and interdependent pathways and reactions within these cellular and subcellular processes for six experimental techniques within the KPMP. Here, we considered spatial metabolomics, single-cell transcriptomics, single-nucleus transcriptomics, laser microdissection (LMD) transcriptomics, as well as LMD and near-single-cell proteomics applied to the KPMP samples and additional human kidney samples used to build the reference tissue atlas. Using pathway enrichment analysis, we documented consistent results resulting from the identification of overlapping genes, proteins, and metabolites, leading to the identification of biochemical pathway parts with the same higher level of function. Spatial metabolomics data served as an anchor for such biochemical pathway integration, since it provided the end products of metabolic pathways. The integrated functional relationships predicted interacting pathways such as β-oxidation, carnitine shuttle, and carnitine biosynthesis in the tubular compartment (Figure 1A), and helped to define new proximal tubule segments based on bioenergetic profiles. In addition, tubulointerstitial metabolites showed a strong functional relationship between purine metabolism and glycolysis. Furthermore, adenine, a nephrotoxic metabolite, was identified as a potential key metabolite in the tubulointerstitial compartment from the integrated bioinformatics analysis (Figure 1B). As in Example 1 above, urinary adenine was identified to be associated with ESKD in the untargeted urinary metabolome analysis of 995 patients with diabetes in the CRIC study. Therefore, a more detailed analysis of adenine was undertaken using spatial metabolomics.

[0140] Spatial metabolomics localizes adenine to glomerulosclerosis, arteriosclerosis, and tubular atrophy. Spatial metabolomics overlaid with histological studies of selected human kidney tissues with pathological features was examined for adenine. There was clear localization of adenine in the glomerular and tubulointerstitial compartments (Figure 2A and Figure 2B). Powerful resolution of adenine localized it adjacent to areas of atrophic tubules and tubulointerstitial fibrosis (Figure 2C). Adenine was also localized to the vascular compartment in the peritubular space, such as the vascular wall of small vessels with arteriosclerosis (Figure 2C). Given the role of adenine in tissue samples, we developed a targeted high-throughput urinary adenine assay and found excellent correlation with spatial adenine in tissue sections (r=0.73, p<0.001, Table 1) and with LC-MS / MS analysis of urinary adenine / creatinine (r=0.90, p<0.001, Figure 3).

[0141] Table 1: Baseline clinical characteristics of Pima Native Americans before kidney biopsy. Samples from patients not taking renin-angiotensin inhibitors were evaluated for urinary adenine levels at two time points before kidney biopsy. TIFF2025506412000008.tif94137

[0142] Urinary adenine correlates with renal pathology and clinical outcomes in the Pima Native American population. Given the colocalization of spatial adenine with pathological features, non-invasive urinary adenine levels measured before kidney biopsy were evaluated as a predictor for glomerular pathology. In collaboration with the Pima Native American Study (PMID 29305527) (described in Figure 4), urinary adenine was measured at two specified time intervals before study protocol biopsy in 15 patients not receiving renin-angiotensin inhibitor therapy. Baseline clinical characteristics are described in Table 1. By assessing the change in urinary adenine versus baseline and the pathology score, there was a statistically significant correlation between the change in urinary adenine and glomerulosclerosis (see Table 2). The correlation between urinary adenine and glomerulosclerosis % remained significant even after adjusting for urinary ACR (r=0.650, p=0.007). Surprisingly, the change in urinary ACR before renal biopsy was not statistically correlated with the degree of glomerulosclerosis (r=0.116, p=0.65, Table 2). There was a trend for a negative correlation between urinary adenine and the percentage of fenestrated endothelium, and a positive correlation with cortical interstitial volume.

[0143] (Table 2) Urinary Ad / Cr 6 months to 1 year prior to kidney biopsy predicts glomerulosclerosis in Pima Native Americans (n=15). TIFF2025506412000009.tif30170

[0144] Urinary adenine correlates with GFR decline. To determine whether urinary adenine levels have clinical predictive value, a cohort of 60 patients with measured urinary adenine levels were divided into tertiles (t1 3–67 nM adenine / mM creatinine (4–80 mg adenine / gram creatinine); t2 72–411 nM / mM (86–491 mg / gm); t3 429–2954 (512–3529 mg / gm)) and correlated with change in GFR measured on an iodine-based basis (Table 3). The outcome evaluated was a >=40% decline in GFR over a median follow-up of 7.6 years (IQR 3.8–11.8). Forty-seven of the 60 participants met this outcome criterion. Urinary adenine levels correlated with measured GFR decline in patients with normoalbuminuria when comparing tertile 3 (highest urinary adenine / creatinine group) versus tertile 1 (HR=4.3, 95% CI 1.14-16.21, p=0.03). In the normoalbuminuria group, there was a trend toward significance between tertile 2 versus tertile 1, but this did not reach statistical significance (HR=2.3, 95% CI 0.62-8.56, p=0.21). In the microalbuminuria group, there was a significant association between tertile 2 and tertile 1 (HR=4.96, 95% CI 1.10-22.34, p=0.04). The urinary adenine / creatinine ratio did not have a greater predictive value in the macroalbuminuria group.

[0145] (Table 3) Adjusted hazard ratios for a >=40% decrease in GFR among urinary adenine / creatinine tertiles in patients with normoalbuminuria, microalbuminuria, and overt macroalbuminuria in the Pima Native American Study. TIFF2025506412000010.tif53159

[0146] Urinary adenine identifies patients who will develop ESKD in the CRIC cohort. Because data from the Pima Indian population support the role of urinary adenine as a marker of renal pathology in patients and have shown a role in kidney disease progression, a large, well-characterized cohort of patients with diabetes-related kidney disease from the Chronic Renal Insufficiency Cohort (CRIC) was evaluated. Baseline urinary adenine was measured from samples at the time of entry into CRIC, and patients were followed annually for evaluation of ESKD outcomes (eGFR<15 ml / min / m2 or need for renal replacement therapy). Baseline clinical characteristics are shown in Table 4. Of the 995 evaluated subjects, 292 had normoalbuminuria (ACR≦30 mg / g creatinine). The group of subjects with the lowest tertile of urinary adenine / creatinine ratio was used as the reference group in the analysis of the association between ESKD outcomes and urinary adenine / creatinine ratio.

[0147] Table 4: Baseline characteristics of patients with diabetes in the CRIC study. BMI, body mass index; eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c; UACR, urinary albumin-to-creatinine ratio; *Continuous ACR was summarized using median (IQR, interquartile range) due to its skewed distribution. All other continuous variables were summarized using mean ± SD. TIFF2025506412000011.tif111128

[0148] After adjustment for differences in clinical variables, the top two tertiles of urinary adenine within the normoalbuminuric group had a strong effect size on ESKD outcomes (Table 5). The top tertile of urinary adenine had a hazard ratio of 4.42 (CI 1.56, 12.5, p=0.005) compared with the lowest tertile, and the middle tertile had a hazard ratio of 3.01 (CI 1.09-8.32, p=0.034) (Table 5). The top two tertiles did not have a significantly increased risk in the microalbuminuric group (Table 5).

[0149] Table 5. Adjusted hazard ratios for ESKD outcomes based on urinary adenine tertiles in normoalbuminuric and microalbuminuric groups from the CRIC study. Analyses were adjusted for baseline age, sex, eGFR, mean arterial blood pressure, hemoglobin A1C, and diabetes duration. TIFF2025506412000012.tif66164

[0150] Spatial adenine and urinary adenine correlate with renal pathology in the ZDF rat model of diabetic nephropathy. A time series assessment of markers and pathology is difficult to establish in patients, so a preclinical animal model was evaluated. Spatial metabolomics was performed in the ZDF rat model, and spatial adenine correlated with glomerulosclerosis (Table 6). Interestingly, in 6-month-old ZDF rats, glomerular adenine correlated poorly but significantly with glomerulosclerosis, whereas non-glomerular adenine and global whole slide image (WSI) adenine correlated much better with glomerulosclerosis.

[0151] Table 6. Correlation between spatial adenine and glomerulosclerosis TIFF2025506412000013.tif46161

[0152] A non-invasive urinary assay was developed using a high-throughput ZipChip-based, mass spectrometry-based approach and found to be highly correlated with LC-MS / MS measurements of urinary adenine (r2 = 0.82, p-value, n = 23 samples, Figure 3).

[0153] The urinary assay was also found to be highly correlated with glomerular, nonglomerular, and WSI adenine levels, indicating that urinary adenine reflects renal adenine levels (Table 7).

[0154] (Table 7) Spatial adenine correlated with urinary adenine in the ZDF rat model. TIFF2025506412000014.tif46161

[0155] Urinary adenine assays were then evaluated in a long-term 9-month model of diabetic nephropathy in ZDF rats. Urinary levels measured at 30 weeks of age predicted both glomerular sclerosis and tubulointerstitial disease assessed at 9 months of age. Surprisingly, urinary adenine performed better than urinary ACR to predict glomerular and tubulointerstitial pathology (Table 8).

[0156] (Table 8) Urinary adenine and albumin levels at 30 weeks of age were associated with glomerular sclerosis and tubulointerstitial disease at 36 weeks of age. TIFF2025506412000015.tif51161

[0157] Urinary adenine in Pima Indian populations demonstrates that urinary adenine correlates with kidney pathology and clinical outcomes. Given the strong correlation between urinary adenine and glomerulosclerosis in the ZDF model, we evaluated whether urinary adenine levels taken prior to kidney biopsy could predict glomerular pathology. In collaboration with the Pima Native American Study Group, urinary adenine was measured at two specified time intervals prior to study protocol biopsy in 15 patients not receiving renin-angiotensin inhibitor therapy (as part of a prior randomized study). By assessing the change in urinary adenine relative to baseline and the pathology score, there was a surprisingly strong correlation between the change in urinary adenine and glomerulosclerosis (see Figure 8 and Table 9).

[0158] The correlation between urinary adenine and % glomerulosclerosis remained significant even after adjusting for urinary ACR (r=0.650, p=0.007). Surprisingly, pre-kidney biopsy urinary ACR was not statistically correlated with the degree of glomerulosclerosis (r=0.116, p=0.65).

[0159] A cohort of 60 patients who had urinary adenine levels measured were divided into tertiles (t1 3-67; t2 72-411; t3 429-2954). The outcome was a >=40% reduction in GFR (using our standard imputation technique) at a median follow-up of 7.6 years (IQR 3.8-11.8). Forty-seven cases of the 60 participants were included in the analysis. Urinary adenine levels correlated with measured GFR reduction in patients with normoalbuminuria (HR=4.3, 95% CI 1.14-16.21, p=0.03, n=32). Of note, GFR was measured with an inulin-based assay and is therefore a measure of true GFR.

[0160] Table 9. Association of urinary adenine with renal pathology characteristics TIFF2025506412000016.tif126132

[0161] Recent analysis of urinary untargeted metabolomics identified urinary adenine and several other metabolites along the polyamine pathway (ornithine) to be associated with kidney disease progression (recent manuscript and new analysis), indicating that urinary adenine may be a risk factor for progression. Targeted assays identified urinary adenine to correlate with progression of kidney function decline and risk of ESKD. Indeed, high urinary adenine (top half of levels, giving absolute values) indicated a 60% higher risk of developing ESKD than those in the bottom half (Figure 9).

[0162] Further subgroup analysis identified that for risk of progression to ESKD, men with elevated urinary Ad / cr had a HR (1.11), and those with microalbuminuria (HR 1.13) or macroalbuminuria had the highest HR (1.15), even after adjustment for relevant clinical variables. See Figure 10.

[0163] B. Method Chemicals and Reagents. 1,5-Diaminonaphthalene (97%) was purchased from Sigma-Aldrich. Indium tin oxide (ITO) glass slides required for MALDI MSI were purchased from Bruker Daltonics (Bremen, Germany), and superfrost plus microscope slides essential for PAS and immunostaining were acquired from Fisher Scientific, PA, USA. Alcohol formalin, distilled, periodic acid, and Schiff's reagent are from Merck, Darmstadt, Germany. Mayer's hematoxylin is from NovaUltra™. TBS, ethanol, and xylene mounting media, as well as all other reagents, were sourced from Sigma-Aldrich (St. Louis, MO) unless otherwise stated.

[0164] Sample collection. Human samples were obtained from KPKP, and the Institutional Review Board of the University of Texas Health Science Center, San Antonio (UTHSCSA) approved all experimental procedures (IRB number: HSC2017035H). Written informed consent was obtained from all patients. Tissue specimens were obtained by surgical resection at the Department of Pathology, UTH San Antonio. Samples were immediately frozen in liquid nitrogen (without PBS prewetting) and stored in a biofreezer at -80°C until analysis.

[0165] Tissue sectioning. A Leica CM1950 cryomicrotome (Leica, Biffalo Grove, IL) was pre-equilibrated to chamber and blade temperatures of -15°C and -20°C, respectively. Tissues were embedded on ice with a few drops of Milli-Q water. All tissues were sectioned at 10 μm thickness and thaw-mounted onto indium tin oxide (ITO)-coated slides for MSI, and 4 μm thick sections were thaw-mounted onto microscope slides for PAS and immunofluorescence analysis. Slides to be analyzed for MALDI were placed in a vacuum desiccator for approximately 30 minutes before matrix application, and the remaining slides were stored in a biofreezer at -80°C until further analysis.

[0166] Optical Imaging. A multimodal imaging approach was used to investigate the regional localization of glomeruli, proximal tubules, and distal tubules in tissue sections. In this approach, optical microscopy is integrated with MSI. Brightfield microscopy visualized the shape of the glomeruli, autofluorescence microscopy outlined the location of the glomerular regions, and PAS staining revealed the localization of glomeruli in the tissue. MSI using MALDI-MSI visualized the distribution of intact small metabolite ions. All modalities were combined through the presence of fiducial markers visible in all imaging modalities.

[0167] Optical images (autofluorescence (AF), bright field (BF), and PAS images) are acquired with a confocal microscope (Leica TCS SP8) or Aperio ScanScopeXT (Leica Biosystems). For AF and BF images, images were captured before MALDI-MSI (pre-AF / BF). Briefly, pre-AF / BF images are captured with a Leica TSC SP8 confocal microscope using a 10x objective at wavelengths of 495 nm–720 nm, 404–488 nm, and the bright field channel is used for AF / BF imaging, before matrix application. Consecutive serial sections are obtained at 3–5 μM cryosections for PAS and immunofluorescence analysis. PAS-stained slides are scanned at 40x magnification with an Aperio CS2 image capture device. Optical images are uploaded to METASPACE and SCiLS Lab software for overlay with metabolite images. Extract data from regions of interest (ROIs) (e.g., glomerulus, proximal tubule, distal tubule, interstitium) for further analysis.

[0168] Matrix application for imaging of small metabolite molecules. The DAN-HCl matrix solution was sprayed onto an ITO glass slide using an HTX TM-Sprayer (HTX Technologies, Chapel Hill, NC) with the following settings: nozzle temperature 75°C, 16 passes, flow rate 0.060 mL / min, speed 1200 mm / min, track spacing 2 mm, pressure 10 psi, gas flow rate 3 L / min, drying time 20 s between passes, using the "CC" coverage pattern.

[0169] Mass spectrometry imaging. MSI images were obtained using a Thermo Scientific Q Exactive HF-X hybrid quadrupole-Orbitrap mass spectrometer (Thermo Scientific, USA) in combination with a novel high-pressure MALDI / ESI interface (Spectroglyph LLC, Kennewick, WA, USA) (Belov et al., 2017). This modified MALDI-Orbitrap mass spectrometer was equipped with a 349 nm, 120 uJ, 5 kHz Nd:YLF laser (Spectra Physics, Mountain View, CA). The 349 nm laser was operated at a laser repetition rate of 1000 Hz (was 500 Hz) with a laser pulse energy of 2.34 μJ (from 2.18 μJ) in a 5 ns pulse. In the IMS experiments, the sample was placed on the coordinate table 5 cm from the ion funnel to obtain negative ions. The generated ions were captured by the ion funnel and transferred to a Q Exactive Orbitrap mass spectrometer (Thermo). Mass spectra were acquired over a mass range of m / z 60-900. Spectroglyph MALDI Injector Software was used to control the raster step size of the tissue area imaged. To generate images, spectra were collected at intervals of 20-30 μm in both x and y dimensions across the surface of the sample. MSI data were recorded with the Orbitrap instrument operated at a nominal mass resolution of 120,000 (from 100,000), an ion injection time of 200 ms (there was an injection time of 180 ms), and with automatic gain control turned off. Ion images were generated from raw files (obtained from the Orbitrap tuning software) and position files (obtained from the MALDI Injector Software) by Image Insight software (Spectroglyph LLC).Centroid files and profile data were exported separately into imzML format using Image Insight and SCiLS Lab software version 2019c Pro (SCiLS, Bremen, Germany). Details of the general workflow are presented below in Figure 2.

[0170] PAS staining. Fresh frozen biopsy sections were stained with PAS and hematoxylin (Merck, Darmstadt, Germany) to show areas of sclerosis and histology of the glomeruli. Human kidney tissue sections of 4 μm thickness were mounted on pre-cleared superfrost plus microscope slides (Fisher Scientific, PA, USA) and stored at −80° C. using the following staining procedure from the UTHSCSA Department of Pathology and Laboratory Medicine, San Antonio (see section on tissue sectioning). Slides were removed from the biofreezer and dried in a desiccator for 30 min before the PAS staining procedure. Slides were immersed in 95% alcohol formalin for 10 min and the slides were rinsed four times with distilled water. Slides were placed in 0.5% aqueous periodic acid solution for 5 min followed by rinsing four times with tap water. Slides were immersed in Schiff's solution for 15 min and rinsed five times with warm tap water. Slides were then immersed in Mayer's hematoxylin for 3 min and rinsed four times with TBS and distilled water. Slides were dehydrated successively in 95% alcohol, 100% alcohol, and xylene for 5 s in each solution, then mounted and coverslipped. Slides were scanned with an Aperio VERSA 200 scanner (Leica Biosystems, IL, USA).

[0171] Statistical analysis. Multivariate analysis of the dataset was obtained from the MSI dataset of human kidney cortex tissue samples. First, as an unsupervised statistical method, principal component analysis (PCA) was used to detect outliers and find structure in the data. Second, as a supervised statistical method, orthogonal projection to latent structures-discriminant analysis (PLS-DA) was performed to describe the distinguishable metabolites between the two groups. The quality of the PLS-DA model was evaluated using R 2 X, R 2 Y, and Q 2 where R 2 and Q 2 are the goodness of fit and the goodness of prediction, respectively. Metabolite identification and pathway analysis were performed using MetaboAnalyst 4.0 (URL metaboanalyst.ca / ) against annotations extracted from the HMDB database in METESPACE and used for metabolic pathway analysis (MPA). The most relevant pathways were reported based on p-values ​​with a false discovery rate (FDR) of less than 0.05.

[0172] Urinary metabolomics (Zip-Chip™ analysis). Adenine in plasma samples was analyzed using ZipChip™ coupled to mass spectrometry. Briefly, 10 μL of sample or calibration standard mixture was mixed with 90 μL of extraction solution containing 80% methanol, 100 mM ammonium acetate, and 1.5 μM stable isotope-labeled internal standard in a 96-well plate. After mixing, the sample or calibration standard was stored in a −20° C. freezer for at least 1 h and then centrifuged at 5000 rpm for 10 min. 50 μL of the supernatant was transferred to a clean 96-well plate for analysis. Metabolite separation was achieved on a microfluidic chip integrating capillary electrophoresis (CE) with nanoelectrospray ionization through the ZipChip™ interface (908 Devices, Boston, MA). For each sample, 20 μL of solution was placed in the sample well and then injected into the HS chip using a 10 s load time. A field strength of 1000 V / cm was applied for separation for 4 min with a background electrolyte solution consisting of 2% formic acid in 50% methanol in water. Mass spectrometry acquisition was performed on a Q-Exactive™ mass spectrometer (Thermo, San Jose, CA). The resolving power was 17,500 and the AGC target was 3×10 6 The injection time was 20 ms, and the scan range was 75–500 m / z. Thermo Scientific software Xcalibur-Quan Browser was used for quantitative data processing.

[0173] Bioinformatics and Systems Medicine Analysis. Single cell, single nucleus, laser microdissection (LMD) transcriptomics, LMD proteomics, near single cell (NSC) proteomics, and spatial metabolomics datasets generated from non-diseased tissue in nephrectomy and biopsy samples were obtained from Hansen et al. (URL doi.org / 10.1101 / 2020.07.23.216507), Lake et al. (PMID: 31249312), and Menon et al. (PMID: 32107344). In these studies, marker genes and proteins were obtained by comparing gene expression in each cell type, subtype, and subsegment against all other cell types, subtypes, or subsegments. Marker genes and proteins that did not meet the significance criteria (maximum adjusted p-value of 0.05 for single cell and single nucleus transcriptomics, maximum p-value of 0.05 for LMD transcriptomics, LMD proteomics, and NSC proteomics) were removed, and the remaining genes and proteins were ranked by significance. The top 500 genes and proteins, as well as tubulointerstitial metabolites, were mapped to enzymes and regulatory proteins involved in polyamine metabolism (PMID: 30181570).

[0174] Pima Native American Study. All patients in this study were enrolled in a randomized clinical trial (Weil et al. 2013) testing the renal protective efficacy of losartan versus placebo in early diabetes-related kidney disease (ClinicalTrials.gov number, NCT00340678). Glomerular filtration rate (GFR) was measured annually throughout the study by urinary clearance of iothalamate. At the end of the 6-year clinical trial, participants underwent percutaneous kidney biopsy to determine whether the treatment was associated with preservation of kidney structure. Archived urine samples were available for 62 participants prior to kidney biopsy from the clinical trial for whom biopsy data were also available. The clinical trial was approved by the Institutional Review Board of the National Institute of Diabetes and Digestive and Kidney Diseases. Each participant signed an informed consent document. For this study, analyses were restricted to participants randomized to placebo who were not taking any renin-angiotensin system blockers at the time of biopsy or at the time of collection of any urine specimen used to measure urinary adenine concentrations.

[0175] Renal morphometry. Digital images from kidney biopsy tissue sections were collected and renal structural parameters were quantified by morphometry as previously described (Weil et al. 2013). Parameters measured using electron microscopy included glomerular basement membrane width, mesangial fractional volume per glomerulus, glomerular filtering surface density, number of podocytes per glomerulus, podocyte foot process width, percentage of surface-denuded endothelium, and percentage of fenestrated endothelium. Light microscopy was used to measure mean glomerular volume, total filtering surface per glomerulus, cortical interstitial fractional volume per glomerulus, and percentage of sclerotic glomeruli (Squarer et al. 1998).

[0176] Statistical analysis. Changes in urinary adenine were expressed as the ratio of urinary adenine concentrations measured closest to kidney biopsy to those measured one year before biopsy. The same approach was used for changes in urinary albumin:creatinine ratio. Variables with skewed distributions were log-transformed before analysis. Cross-sectional relationships between changes in urinary adenine and each morphometric variable were assessed by Pearson correlation and by linear regression and partial Pearson correlation after adjustment for age and sex.

[0177] Chronic Renal Insufficiency Cohort (CRIC). The parent CRIC study recruited (from 2003) an ethnically diverse group of participants aged 21-74 years, approximately 50% with diabetes, and with a wide range of renal function. Informed consent was obtained from participants; the protocol was approved by the IRB and the Scientific Data Coordinating Center (approval number 807882). The study included participants with CKD stages 3a, 3b, and 4, eGFR 45-60, 30-45, and 20-30 ml / min / 1.73 m, respectively. 2 Methods: We analyzed the urinary metabolome at study entry (baseline) of 995 randomly selected CRIC participants with diabetes mellitus across the lifespan.

[0178] Disease outcomes. Two outcomes were assessed: percentage of eGFR change per year (eGFR slope) and time to ESKD. EGFR-slope was estimated via a mixed model using continuous eGFR measurements as previously described. Time to ESKD was the time from entry into the CRIC study to incident renal failure requiring renal replacement therapy or kidney transplant; dropout or death prior to renal failure was considered a censored event.

[0179] Results of an unbiased multi-omics analysis using spatial metabolomics, untargeted urinary metabolomics, single-cell transcriptomics, and single-nucleus transcriptomics from kidney biopsy and urine samples identified the polyamine pathway as being involved in renal tubular function. A specific metabolite, adenine, is prognostic of kidney disease progression in patients with diabetes. Furthermore, urinary adenine is a robust prognostic biomarker, especially in patients with diabetes and normoalbuminuria, a large population of patients with diabetes.

[0180] Urine samples obtained 6 months to 1 year prior to renal biopsy were analyzed for urinary albumin / creatinine ratio and urinary adenine / creatinine (by ZipChip-QE method).Fifteen subjects with normal GFR and prior treatment with medications affecting the renin-angiotensin system were identified.

[0181] As mentioned, GFR was above the range for kidney disease (<90 ml / min). Urinary albumin / creatinine ratios (ACR) ranged from normal levels (<30 mg albumin / gram creatinine) to high (>300 mg albumin / gram creatinine). Urinary ACR and urinary adenine / creatinine ratios were measured on two separate occasions prior to kidney biopsy, and changes in urinary ACR or urinary adenine / creatinine ratios were statistically correlated with the degree of pathology in the kidney biopsy. Surprisingly, changes in urinary albumin / creatinine ratios did not correlate significantly with common markers of established kidney disease (glomerulosclerosis, r=0.22, p=0.17), but changes in urinary adenine / creatinine ratios correlated significantly with the degree of glomerulosclerosis (r=0.57, p=0.03).

[0182] Another marker of kidney disease is the expansion of interstitial volume (non-glomerular area). The correlation between the urinary albumin / creatinine ratio and the cortical interstitial fraction volume was poor and not significant (r=0.057, p=0.83), but there was a trend toward a correlation between the urinary adenine / creatinine ratio and the cortical interstitial fraction volume (r=0.38, p=0.16). Cumulative data indicate that changes in the urinary adenine / creatinine ratio identify which patients have normal levels of GFR and underlying renal pathology indicative of kidney disease.

[0183] Urinary adenine / creatinine ratios can identify which patients with diabetes and normoalbuminuria and normal GFR will experience a rapid decline in GFR. A Pima Native American cohort of 60 patients who had urinary adenine levels measured before kidney biopsy were divided into tertiles (t1 3–67; t2 72–411; t3 429–2954 nmole adenine / nmole creatinine ratio) based on their pre-kidney biopsy urinary adenine levels. Patients were divided into those with normoalbuminuria (n=32), microalbuminuria (n=16), or macroalbuminuria (n=12). Their GFR was measured annually throughout the study by urinary clearance of iodine-200-carboxylates. Statistical analysis was performed on the outcome of >=40% reduction in GFR (using our standard imputation techniques) at a median follow-up of 7.6 years (IQR 3.8-11.8). Forty-seven patients out of 60 participants met the criteria for reduced GFR, a >40% reduction in GFR being an accepted FDA criterion for clinical decline in renal function (PMID 25446026). Participants (n=62, mean age 45±10 years) had a baseline mean±standard deviation glomerular permeability of 137±50 ml / min and a median (interquartile range) urinary albumin:creatinine ratio of 34 (14-85) mg / g near the time of biopsy (PMID 30830355).

[0184] Urinary adenine levels based on the highest versus lowest tertile were highly predictive of measured GFR decline over a 7.6-year follow-up period in patients with normoalbuminuria (HR=4.3, 95% CI 1.14-16.21, p=0.03, n=32). Of note, GFR was measured with an inulin-based assay and is therefore a measure of true GFR. There was also a significant association comparing tertile 2 versus tertile 1 in the microalbuminuria group.

[0185] The data show that diabetic patients with normoalbuminuria and CKD in the G3 category have a 4.4-fold increased risk of renal failure if they are in the top tertile of urinary adenine compared to the lowest tertile. Diabetic patients with normoalbuminuria and CKD in the G3 category have a 3-fold increased risk of renal failure if they are in the second tertile of urinary adenine compared to the lowest tertile.

[0186] Urinary adenine can identify which diabetic patients need treatment at the G1A1 stage of kidney disease. When a patient at high risk of kidney disease progression is diagnosed for a GFR reduction of >40% while in the G1 stage, clinicians can easily select a treatment regimen that is compatible with the diagnosis, such as selecting certain antihypertensive drug therapies (renin-angiotensin inhibitors), mineralocorticoid receptor blockers, certain drug therapies that affect blood glucose levels (sodium-glucose transporter inhibitors (SGLT2i) or glucagon-like peptide agonists (GLP1 agonists)). All of these drug therapies may reduce the progression of kidney disease, but would be mainly justified in patients at high risk of developing a progressive decrease in kidney function. Additional dietary interventions such as altering sodium, protein, fat, and carbohydrates may be beneficial for high-risk patients. Lifestyle modifications such as smoking cessation or increased exercise may also be beneficial for this high-risk population that could not be identified otherwise.

[0187] Urinary adenine can identify which diabetic patients need treatment at the G3A1 stage of kidney disease. When a patient at high risk of kidney failure is diagnosed while at the G3A1 stage, clinicians can easily select a treatment regimen that is compatible with the diagnosis, such as selecting certain antihypertensive medications (renin-angiotensin inhibitors), mineralocorticoid receptor blockers, certain medications that affect blood glucose levels (sodium-glucose transporter inhibitors (SGLT2i) or glucagon-like peptide agonists (GLP1 agonists), etc.). All of these medications may reduce the progression of kidney disease, but would be mainly justified in patients at high risk of developing a progressive decline in kidney function. Additional dietary interventions, such as altering sodium, protein, fat, and carbohydrates, may be beneficial for high-risk patients. Lifestyle modifications, such as smoking cessation or increased exercise, may also be beneficial for this high-risk population that could not be otherwise identified.

[0188] Example 3 Use of the ZipChip assay to measure adenine in biological fluids In Figure 12, plasma adenine was measured by Zipchip-QExactive in mice 24 hours after sham operation or 24 hours after ischemia-reperfusion injury. Plasma adenine was significantly increased in IRI mice, indicating that they are a good model for mimicking human kidney disease. In the ischemia-reperfusion model, plasma adenine was found to be elevated in mice (n=5) 24 hours after ischemia-reperfusion compared to sham-operated mice (n=5).

[0189] Urinary adenine identifies animal models that can be used to model chronic kidney injury. Animal models can be useful to mimic human disease. By demonstrating that adenine is involved in human kidney disease, measurements of plasma or urinary adenine can be used to identify relevant models of progressive kidney disease. In the Zucker diabetic fatty rat model, urinary adenine / creatinine ratios were measured in n=9 ZDF rats and n=9 lean control rats. There was a four-fold increase in urinary adenine / creatinine ratio in ZDF rats (2603 nM / mM) compared to control rats (502 nM / mM).

[0190] Example 4 Protocol for using ZipChip™ to measure adenine levels A. All steps below should be performed in an ice bath.

[0191] B. A 1000 μM adenine stock solution and a 3000 μM creatinine stock solution are prepared in MS grade water and stored in a -80° C. freezer.

[0192] C. Preparation of calibration standards.

[0193] On the day of sample preparation, mix 20 µL of adenine stock with 20 µL of creatinine stock to obtain a mixture containing 500 µM adenine and 1500 µM creatinine.

[0194] Dilute as follows to obtain the desired concentrations (only adenine concentrations are shown): TIFF2025506412000017.tif88144

[0195] Dilute as follows to obtain the desired concentrations (only adenine concentrations are shown):

[0196] D. Preparation of extraction solution containing internal standards.

[0197] 80 mL MeOH + 10 mL 1M NH4Ac + 10 mL H2O + 25 μL of 25 mM creatinine d3 + 5 μL of 15 mM adenine-13C. Mix well, aliquot into 5 mL portions and store at -80 °C until use.

[0198] E. On the day of analysis, urine samples and pooled human urine as QC samples are thawed in an ice bath.

[0199] F. Prepare a 96-well plate (Thermo, AB-0800) with appropriate labeling and sample / QC location template.

[0200] G. Vortex each sample and transfer 10 μL to the desired wells. Transfer 10 μL of QC samples to wells A1, C3, E5, G7, and D9.

[0201] H. Transfer 10 μL of calibration standards to the appropriate wells (C11 through H12).

[0202] I. Using a multichannel pipette, transfer 90 μL of Extraction Solution (D above) to each of the sample, QC sample, calibration standard, and blank wells.

[0203] J. Cover the plate and store in a -20°C freezer for at least 30 minutes.

[0204] K. Centrifuge the plate at 9000 rpm, 4°C for 8-10 minutes.

[0205] L. Using a multichannel pipette, transfer the top 50 μL from each well to a new plate. Cover the plate with a "Zone free" (Sigma, Z721646-50EA) plate cover.

[0206] M. Instrumentation: Thermo Scientific Q Exactive HFX and 908 Devices ZipChip interface CE / MS.

[0207] N. Prepare BGE according to manufacturer's instructions (908 Devices). A full bottle of BGE is required for the entire 96-well plate of samples.

[0208] O. Check the operating conditions of the mass spectrometer. Perform mass calibration.

[0209] P. Prime the autosampler and HSX tips and check the tip spray.

[0210] Q. Set up the sequence so that both the MS and ZipChip systems start with a blank and then acquire data for the lowest concentration calibration standard.

[0211] ZipChip method: Electric field strength: 1000 V / cm Load volume: 5 nL Chip type: HS BGE: Metabolites Pressure Assis: None Run Time: 4 minutes

[0212] MS settings: m / z range: 70-500 Resolution: 15,000 AGC target: 1E6 Maximum ion implantation time: 20 ms Inlet capillary temperature: 200℃ S Lens RF: 40 Run Time: 4 minutes

[0213] R. To eliminate carryover, perform "Rinse Sample Well" 8 times after the highest calibration concentration and before the first sample injection.

[0214] S. Data is processed with Thermo Scientific software Xcalibur-Quan Browser to obtain adenine and creatinine concentrations for each urine sample and QC sample.

[0215] Example 5 Elevated urinary adenine identifies subclinical albuminuric patients at high risk for ESKD outcomes. Patients with diabetes are often classified as normoalbuminuric (0-30 mg albumin / gm creatinine), microalbuminuric (30-300 mg / g), or macroalbuminuric (>300 mg / g). Because patients with normoalbuminuric or microalbuminuric may fall back into either category, this group of patients can be considered subclinical albuminuric (<300 mg / g). In the new analysis, we also found that when patients are classified as subclinical albuminuric (i.e., <300 mg albumin / gram creatinine), they are at increased risk for ESKD, defined as a >50% decrease in eGFR, need for renal replacement therapy, or a sustained eGFR <15 ml / min / 1.73 m2 (Figure 20). This subclinical albuminuric classification encompasses >90% of patients with diabetes in the United States.

[0216] Example 6 Elevated urinary adenine identifies diabetic patients at risk for ESKD and all-cause mortality. Another finding was that in a US study with n=904 participants, high urinary adenine levels predicted ESKD and all-cause mortality, independent of albuminuria status (Figure 21). Patients who were in the top two tertiles have HRs of 1.6-1.8 vs. the lowest tertile for ESKD and all-cause mortality. This data indicates that measurement of urinary adenine / creatinine levels provides clinical value to all patients with diabetes, regardless of albuminuria status (Figure 21).

[0217] Example 7 Elevated urinary adenine is a noninvasive marker of hyperfiltration in diabetic patients. In patients with diabetes, the earliest risk factor for kidney disease is a physiological finding called hyperfiltration, but this measurement is difficult to perform without invasive protocols that require intravenous infusion. Normal kidney function is measured by glomerular filtration rate (GFR), which is accurately measured by intravenous infusion of certain molecules (iothalamate, inulin, etc.) that are completely filtered by the glomerulus and minimally reabsorbed or secreted at the tubular level. Normal GFR varies between 90-120 ml / min / 1.73 m2. In patients with early diagnosis of type 1 or type 2 diabetes who are at risk for progressive kidney disease, there are complex changes in blood flow regulation in the kidney that lead to an elevated GFR (called hyperfiltration, >135 ml / min / 1.73 m2). This is considered to be one of the earliest markers of diabetes-related kidney disease and occurs before increased albuminuria. However, measuring GFR is very difficult in patients, and therefore a noninvasive marker would be very useful. Another novel finding is that patients with type 1 diabetes and hyperfiltration have higher urinary adenine values ​​compared to patients with type 1 diabetes with normal GFR (Figure 22).

[0218] Example 8 Treatments that are protective for kidney and heart disease would reduce urinary adenine levels, and the urinary adenine / creatinine ratio can be used as a pharmacodynamic or surrogate biomarker. Since empagliflozin reduces urinary adenine / creatinine levels in high-risk patients with hyperfiltration after 8 weeks of treatment, the urinary adenine / creatinine ratio can be used to identify patients who will respond to SGLT2 inhibitors (Figure 23).

[0219] Example 9 Treatments that reduce adenine production protect against kidney disease. Adenine has been found to be toxic to kidney cells (FIG. 7 and FIG. 13) and stimulates the production of extracellular matrix molecules (type I collagen and fibronectin) in kidney tubular cells (FIG. 13 and FIG. 24). The production of extracellular matrix molecules is known to contribute to fibrosis, providing a rationale for why adenine correlates with glomerulosclerosis in patients (FIG. 8). The major source of endogenous adenine production is via the MTAP pathway (FIG. 14). Therefore, conditions in which MTAP is increased would indicate that these conditions would benefit from inhibition of MTAP (FIG. 15) and protect the kidney. MTAP gene expression was increased in an acute kidney injury (AKI) model of ischemia-reperfusion (FIG. 16 left panel) and an MDM2 tubular defect model of chronic kidney disease (FIG. 16 right panel). A small molecule specific inhibitor of MTAP (DADMe-ImmA) was administered for the first time in a model of AKI and found to protect kidney function as measured by BUN levels (Figure 25). DADMe-ImmA, a small molecule MTAP inhibitor, also protected kidney cells under conditions of cellular stress (by reducing MDM2) (Figure 18). Another novel approach to inhibiting MTAP is via the compound sodium hydrosulfide (NaHS). Administration of NaHS to kidney cells protects against adenine-induced matrix production and disease-causing pathways (mTOR) while improving healing pathways (AMPK) (Figure 19 right panel). Treatment of db / db mice (a model of diabetes-related kidney disease) with NaHS resulted in a reduction of MTAP in diabetic kidneys (Figure 24) and improved ACR and matrix accumulation in the kidney.

[0220] Example 10 Inhibition of the insulin receptor with novel siRNA blocks adenine-induced stimulation of mTOR and matrix production. The receptor through which adenine triggers intracellular signaling is via the insulin receptor, such that inhibition of the insulin receptor with novel siRNA completely blocks adenine signaling and matrix production (FIG. 27).

[0221] Example 11 Treatment that inhibits downstream pathways of adenine protects kidney cells. The downstream pathways stimulated by adenine are PI3 kinase, AKT, and mTOR (Figure 28). Inhibition of PI3K (LY294002), AKT (MK2202), or mTOR (rapamycin) with a small molecule inhibitor was all effective in reducing mTOR activation in renal tubular cells. Once mTOR was inhibited, the downstream effects of adenine to stimulate matrix accumulation were reduced (Figure 19).

[0222] Example 12 Inhibition of adenine production is protective against diabetes-related kidney disease. Patients with type 1 diabetes (n=8) or type 2 diabetes (n=8) have increased tissue levels of adenine in their kidney biopsies compared to healthy controls (n=5) (Figure 29). Adenine administration causes major manifestations of diabetes-associated kidney disease in mouse models, including serum soluble tumor necrosis factor receptor-1 (sTNFR1) and plasma kidney injury marker-1 (KIM1) (Figure 30). Adenine also stimulates renal and cardiac hypertrophy (Figure 31), as well as renal phosphor-S6-kinase (a marker of mTOR activity), renal fibronectin, and renal type 1 collagen α-2 chain (Figure 31). An inhibitor of MTAP (DADMe-ImmA at 10 mg / kg / d in drinking water for 8 weeks) reduces urinary ACR, urinary hydrogen peroxide (urinary H2O2), and urinary collagen in a mouse model of diabetes-associated kidney disease (db / db mice) (Figure 32). MTAP inhibitors also reduced renal hypertrophy, renal fibronectin, and renal laminin y1 (FIG. 33).

[0223] Example 13 siRNA against mouse and rat insulin receptors can reduce mouse insulin receptor in mouse tubular cells. Figure 34 shows that administration of siRNA against insulin receptor to mice treated with adenine reduced insulin receptor in kidney but not in liver and prevented the increase in blood urea nitrogen level (Figure 35). In Figure 34, siRNA against insulin receptor (IR) based on mouse and rat sequences reduces IR in mouse kidney cells. Mouse cortical tubule (MCT) cells were reverse transfected with siRNA targeting mouse and rat insulin receptor mRNA (m / r IR siRNA#1 and m / r IR siRNA#5) using RNAiMax (6 ul in optiMEM) and plated in 6-well plates. After 72 hours of incubation, total RNA was isolated and subjected to cDNA synthesis followed by qRTPCR (n=6 / group, ****p<0.0001). Both IR siRNA#1 and IR siRNA#5 significantly reduced mouse insulin receptor at the mRNA level.

[0224] In Figure 35, in vivo administration of IR siRNA#1 specifically reduced IR in mouse kidney and prevented adenine-induced increase in blood urea nitrogen (BUN) levels in mice. Mice were administered vehicle or IR siRNA#1 targeting the kidney, and then challenged with adenine (5 mM) in drinking water for 4 days. On the fourth day, mouse kidneys showed reduced IR in mouse kidney cortex but not in liver compared to control samples, as demonstrated by immunoblotting with antibodies against IR and b-actin (representative immunoblot, upper panel). Mice given vehicle and adenine (n=2) had three-fold increased BUN levels relative to the non-adenine group (lower panel). Mice treated with siRNA against IR did not have any increase in BUN levels despite exposure to adenine (n=2) (lower panel). Table 10A shows exemplary sequences of siRNAs that have been used and can be used to target mouse or rat IR mRNA; however, it is contemplated that other siRNAs targeting IR mRNA, including those that are commercially available, can also be used.

[0225] Table 10A. Exemplary siRNA sequences targeting mouse / rat IR mRNA TIFF2025506412000018.tif123161

[0226] Table 10B: Targeting sequences of siRNAs in Table 10A TIFF2025506412000019.tif60161

[0227] Example 14 siRNA targeting human / porcine insulin receptor In this non-limiting example, siRNA targeting human / porcine insulin receptor mRNA can reduce human insulin receptor in human tubular cells (Figure 36). In Figure 36, siRNA against human and porcine insulin receptors are effective in reducing insulin receptor mRNA in human kidney cells. Human kidney (HK2) proximal tubular cells were transfected with siRNA (4 ul from 10 um stock) using RNAiMax (6 ul in optiMEM) and plated in 6-well plates. After 48 hours, the medium was replaced with fresh medium. 96 hours after transfection, total RNA was isolated and subjected to cDNA synthesis followed by qRTPCR. Human insulin receptor was significantly reduced in HK2 cells after transfection with H / P siRNA#2 and H / P IR siRNA#4 compared to control siRNA (n=6 / group, ****p<0.0001). Table 11 shows exemplary sequences of siRNAs that have been used and can be used to target human or porcine IR mRNA; however, it is contemplated that other siRNAs targeting IR mRNA, including those that are commercially available, can also be used.

[0228] Table 11A. Exemplary siRNA sequences targeting human and porcine IR mRNA TIFF2025506412000020.tif164161

[0229] Table 11B: Targeting sequences of siRNAs in Table 11A TIFF2025506412000021.tif35170

Claims

1. 1. A method for identifying a subject at risk for kidney disease, comprising: (a) measuring the level of a nucleic acid, nucleoside, or amino acid in a biological sample from the subject; and (b) assessing the risk of kidney disease based on the level of the nucleic acid, nucleoside, or amino acid compared to a standard. The method comprising:

2. 2. The method of claim 1, wherein the nucleic acid, nucleoside, or amino acid is a purine, polyamine, adenine, cytosine, guanine, thymine, uracil, asparagine, aspartic acid, betaine, homocysteine, isoleucine, L-α-aminobutyric acid, lysine, methionine, nicotinic acid, ornithine, phenylalanine, pipecolate, threonine, tryptophan, or valine, or any combination thereof.

3. 3. The method of claim 1 or 2, wherein the kidney disease is at least one of chronic kidney disease, diabetes-related kidney disease, hypertension-related kidney disease, glomerulonephritis-related kidney disease, end-stage renal disease (renal failure), glomerulosclerosis, tubulointerstitial fibrosis, renal arteriosclerosis, renal arteriosclerosis, renal neoplasia, or renal tubular atrophy.

4. 4. The method of any one of claims 1 to 3, wherein the risk of kidney disease comprises risk of disease progression.

5. 4. The method of any one of claims 1 to 3, wherein the risk of kidney disease comprises the risk of developing kidney disease in the future.

6. 6. The method of any one of claims 1 to 5, further comprising processing the biological sample from the subject to separate or enrich the nucleic acids, nucleosides, or amino acids.

7. 7. The method of claim 6, wherein processing the biological sample comprises performing capillary electrophoresis, liquid chromatography (HPLC), capillary electrophoresis, or liquid chromatography, or any combination thereof.

8. 8. The method of any one of claims 1 to 7, wherein the step of measuring the levels of nucleic acids, nucleosides, or amino acids is by diode array detection, mass spectrometry, electromagnetic radiation absorption, or ZipChip™.

9. 9. The method of claim 8, wherein the diode array detection is performed using wavelengths between 200 and 400 nm.

10. 10. The method of any one of claims 1 to 9, wherein the nucleic acid being measured is adenine, and an adenine level higher than a threshold value indicates a decrease in glomerular filtration rate (GFR), CKD progression, and / or renal failure, the threshold value being about 2.92 nmol adenine / mmol creatinine, about 4.08 nmol adenine / mmol creatinine, or about 5.23 nmol adenine / mmol creatinine.

11. 10. The method of any one of claims 1-9, wherein the nucleic acid measured is adenine, and an adenine level greater than about 2.92 nmol adenine / mmol creatinine, about 4.08 nmol adenine / mmol creatinine, or about 5.23 nmol adenine / mmol creatinine is indicative of ESKD.

12. The method of any one of claims 1 to 11, wherein the subject has diabetes.

13. The method of any one of claims 1 to 12, wherein the subject has normal albumin levels.

14. The method of any one of claims 1 to 13, wherein the subject is a mammal.

15. 15. The method of claim 14, wherein the mammal is a human or an animal model.

16. 16. The method of any one of claims 1-15, further comprising administering to the subject a treatment, the treatment comprising surgery, chemotherapy, radiation therapy, dietary restriction, treatment of high blood pressure, treatment of diabetes, weight management, smoking cessation, treatment of high cholesterol and / or other lipid levels, kidney transplant, dialysis, administration of erythropoietin and / or calcitriol, diuretics, vitamin D, or phosphate binders, a pharmaceutical composition that inhibits adenine production or function, or any combination thereof.

17. The method of any one of claims 1 to 16, wherein the biological sample is urine or blood.

18. 1. A method of treating or preventing kidney disease in a subject having or at risk of developing kidney disease, comprising: (a) determining the level of adenine in a biological sample from the subject; and (b) administering a kidney disease treatment if the adenine level is above about 2.92 nmol adenine / mmol creatinine, about 4.08 nmol adenine / mmol creatinine, or about 5.23 nmol adenine / mmol creatinine. The method comprising:

19. 20. The method of claim 18, wherein the subject has diabetes.

20. 20. The method of claim 18 or 19, wherein the subject has normal albumin levels.

21. The method according to any one of claims 18 to 20, wherein the biological sample is urine.

22. The method of any one of claims 18 to 20, wherein the biological sample is blood.

23. The method of any one of claims 18 to 22, wherein the subject is a human or an animal model of CKD.

24. 24. The method of any one of claims 18-23, wherein said treatment comprises surgery, chemotherapy, radiation therapy, dietary restrictions, treatment of high blood pressure, treatment of diabetes, weight management, smoking cessation, treatment of high cholesterol and / or other lipid levels, kidney transplant, dialysis, administration of erythropoietin and / or calcitriol, diuretics, vitamin D, phosphate binders, pharmaceutical compositions that inhibit adenine production or function, or any combination thereof.

25. 1. An assay for determining the level of adenine in a biological sample from a subject, comprising: (a) separating analytes in a sample to form a sample fraction; and (b) Quantifying adenine in appropriate fractions The assay comprising:

26. 26. The assay of claim 25, wherein the biological sample is urine or blood.

27. 27. The assay of claim 25 or 26, wherein the subject has diabetes.

28. The assay of any one of claims 25 to 27, wherein the subject has normal albumin levels.

29. The assay of any one of claims 25 to 28, wherein the subject is a human or an animal model of CKD.

30. 1. A method for identifying a subject at risk for progressive decline in kidney function, comprising: (a) treating a biological sample from the subject to isolate adenine, forming a treated sample; (b) measuring adenine levels in the treated sample; and (c) assessing the risk of progressive decline in kidney function based on the adenine level compared to a standard. The method comprising:

31. 31. The method of claim 30, wherein the biological sample is urine.

32. 32. The method of claim 30 or 31, wherein the processing step is selected from capillary electrophoresis, liquid chromatography (HPLC), or capillary electrophoresis and liquid chromatography.

33. 33. The method of any one of claims 30 to 32, wherein the step of measuring adenine levels is by mass spectrometry or electromagnetic radiation absorption.

34. The method of any one of claims 30-33, wherein an adenine level greater than about 2.92 nmol adenine / mmol creatinine is indicative of a subject at risk of progressive decline in kidney function.

35. 35. The method of claim 34, wherein an adenine level greater than about 4.08 nmol adenine / mmol creatinine indicates a subject at higher risk of progressive decline in kidney function, and an adenine level greater than 5.23 nmol adenine / mmol creatinine indicates a subject at higher risk of progressive decline in kidney function.

36. The method of any one of claims 30 to 35, wherein the subject has diabetes.

37. The method of any one of claims 30 to 36, wherein the subject has normal albumin levels.

38. The method of any one of claims 30 to 37, wherein the subject is a human or an animal model.

39. 1. A method for assaying a therapeutic for the treatment of kidney disease, comprising: (a) exposing or contacting a subject to a test agent that is a potential treatment for kidney disease; and (b) monitoring the subject by quantifying adenine levels. Including, A decrease in adenine levels indicates a therapeutic benefit of the test agent for treating kidney disease. The method.

40. 1. A method for monitoring the progression of CKD in a subject, comprising: (a) obtaining a first biological sample at a first time point and a second biological sample at a second time point from a subject; (b) measuring adenine levels in said first biological sample and said second biological sample; and (c) assessing CKD by comparing the difference in adenine levels between the first and second time points. The method comprising:

41. 1. A method for treating a condition of progressive fibrosis or cellular senescence in a subject, comprising administering to the subject a therapeutically effective amount of a pharmaceutical composition, wherein the pharmaceutical composition inhibits the production or function of adenine.

42. 42. The method of claim 41, wherein the pharmaceutical composition inhibits the production of adenine by blocking a cell signaling pathway that leads to endogenous adenine production.

43. 43. The method of claim 42, wherein the pharmaceutical composition inhibits endogenous adenine production by inhibiting expression or function of 5'-methylthioadenosine phosphorylase (MTAP).

44. The method of claim 43, wherein inhibiting MTAP expression comprises using a short hairpin RNA that targets at least a portion of the polynucleotide sequence encoding MTAP.

45. The method of claim 43, wherein inhibiting MTAP expression comprises using a nuclease coupled to a guide RNA that targets at least a portion of a polynucleotide sequence encoding MTAP.

46. 46. ​​The method of claim 45, wherein said nuclease is a Cas9 endonuclease.

47. The method of claim 43, wherein inhibiting MTAP expression comprises inserting a silencer sequence near the polynucleotide sequence encoding MTAP.

48. The method of claim 43, wherein inhibiting MTAP function comprises using an MTAP neutralizing antibody.

49. The method of claim 43, wherein inhibiting MTAP function comprises using a small molecule inhibitor of MTAP.

50. The method of claim 49, wherein the small molecule inhibitor of MTAP is MT-DADMe-ImmA.

51. The method of claim 41, wherein the pharmaceutical composition inhibits the function of endogenous adenine by inhibiting the expression or function of mTORC1.

52. 52. The method of claim 51, wherein the pharmaceutical composition is an mTORC1 inhibitor selected from the group consisting of rapamycin, a rapalog, a rapamycin derivative, temsirolimus, everolimus, umirolimus, zotarolimus, torin-1, torin-2, and bistusertib.

53. The method of claim 41, wherein the pharmaceutical composition comprises an siRNA that inhibits the expression or function of PI3K and thereby inhibits the function of endogenous adenine.

54. 54. The method of claim 53, wherein the pharmaceutical composition is a small molecule PI3K inhibitor.

55. The method of claim 53, wherein the small molecule PI3K inhibitor is LY294002.

56. The method of claim 41, wherein the pharmaceutical composition inhibits the function of endogenous adenine by inhibiting the expression or function of AKT.

57. 57. The method of claim 56, wherein the pharmaceutical composition is a small molecule AKT inhibitor.

58. 58. The method of claim 57, wherein the small molecule AKT inhibitor is MK2202.

59. 42. The method of claim 41, wherein the pharmaceutical composition inhibits the function of endogenous adenine by inhibiting the expression or function of the insulin receptor.

60. 60. The method of claim 59, wherein the insulin receptor inhibitor is a knockdown mechanism comprising at least one of RNA interference (RNAi), small interfering RNA (siRNA), short hairpin RNA (shRNA), or bacterial RNA-guided endonuclease against the insulin receptor.

61. 42. The method of claim 41, wherein the pharmaceutical composition inhibits the function of endogenous adenine by inhibiting the expression or function of a Gi-coupled adenine receptor (AdeR).

62. 42. The method of claim 41, wherein the pharmaceutical composition inhibits the function of endogenous adenine by activating AMP-activated protein kinase (AMPK).

63. 64. The method of claim 63, wherein the pharmaceutical composition is an AMPK activator selected from the group consisting of NaHS, metformin, AICAR, metformin hydrochloride, A769662, RSVA405, ZLN024 hydrochloride, PT1, and PF06409577.

64. 64. The method of any one of claims 41-63, wherein the condition of progressive fibrosis or cellular senescence is at least one of kidney disease, liver disease, lung disease, cardiac fibrosis, brain fibrosis, neurodegenerative disease, arthrofibrosis, skin fibrosis, bone marrow fibrosis, or retroperitoneal fibrosis.

65. 65. The method of claim 64, wherein the kidney disease is at least one of chronic kidney disease, diabetes-related kidney disease, end-stage renal disease (renal failure), glomerulosclerosis, tubulointerstitial fibrosis, renal arteriosclerosis, renal arteriosclerosis, renal neoplasia, or renal tubular atrophy.

66. 65. The method of claim 64, wherein the pulmonary disease is at least one of interstitial lung disease (ILD) or pulmonary fibrosis.

67. A method for measuring a biological sample derived from a subject, comprising: (a) measuring adenine and creatinine levels in a biological sample from a subject; (b) calculating the adenine / creatinine ratio; and (c) comparing the adenine / creatinine ratio to a standard to determine whether the ratio is greater than a threshold value. The method comprising:

68. 68. The method of claim 67, wherein the threshold is about 2.92 nmol adenine / mmol creatinine.

69. 68. The method of claim 67, wherein the threshold is about 4.08 nmol adenine / mmol creatinine.

70. 68. The method of claim 67, wherein the threshold is about 5.23 nmol adenine / mmol creatinine.

71. A method for measuring a biological sample derived from a subject, comprising: (a) measuring levels of nucleic acids, nucleosides, or amino acids, and creatinine in a biological sample from a subject; (b) calculating the ratio of nucleic acid, nucleoside, or amino acid to creatinine; and (c) comparing the ratio of the nucleic acid, nucleoside, or amino acid to creatinine to a standard to determine whether the ratio is greater than a threshold value. The method comprising:

72. 72. The method of claim 71, wherein the nucleic acid, nucleoside, or amino acid is a purine, polyamine, adenine, cytosine, guanine, thymine, uracil, asparagine, aspartic acid, betaine, homocysteine, isoleucine, L-α-aminobutyric acid, lysine, methionine, nicotinic acid, ornithine, phenylalanine, pipecolate, threonine, tryptophan, or valine, or any combination thereof.

73. 73. The method of claim 71 or 72, wherein the threshold is about 2.92 nmol nucleic acid, nucleoside, or amino acid per mmol creatinine.

74. 73. The method of claim 71 or 72, wherein the threshold is about 4.08 nmol nucleic acid, nucleoside, or amino acid per mmol creatinine.

75. 73. The method of claim 71 or 72, wherein the threshold is about 5.23 nmol nucleic acid, nucleoside, or amino acid per mmol creatinine.

76. 76. The method of any one of claims 18-75, further comprising administering to the subject a treatment comprising surgery, chemotherapy, radiation therapy, dietary restriction, treatment of high blood pressure, treatment of diabetes, weight management, smoking cessation, treatment of high cholesterol and / or other lipid levels, kidney transplant, dialysis, administration of erythropoietin and / or calcitriol, diuretics, vitamin D, or phosphate binders, a pharmaceutical composition that inhibits adenine production or function, or any combination thereof.

77. A method for treating a progressive fibrotic condition in a subject, comprising administering to the subject a therapeutically effective amount of a pharmaceutical composition, wherein the pharmaceutical composition is at least one of an inhibitor of adenine accumulation, an inhibitor of an adenine receptor, an inhibitor of adenine signaling, or any combination thereof.

78. 78. The method of claim 77, wherein the inhibitor of adenine accumulation is at least one of an MTAP inhibitor (MTDIA) or hydrogen sulfide.

79. 78. The method of claim 77, wherein the inhibitor of an adenine receptor is at least one of a Gi-coupled adenine receptor (AdeR) or an insulin receptor.

80. The method of claim 79, wherein the inhibitor of the adenine receptor is an siRNA against the insulin receptor.

81. 78. The method of claim 77, wherein the inhibitor of adenine signaling is at least one of an Akt inhibitor, a PI3K inhibitor, or an mTOR inhibitor.

82. The method of claim 60 or 80, wherein said siRNA comprises a nucleobase sequence that is at least 70%, 75%, 80%, 85%, 90%, 95%, or 100% identical to a nucleobase sequence listed in any one of SEQ ID NOs: 1-22.

82. The method of claim 60 or 80, wherein said siRNA comprises a nucleobase sequence that is at least 70%, 75%, 80%, 85%, 90%, 95%, or 100% complementary to a nucleobase sequence listed in any one of SEQ ID NOs: 23-31.

83. The method of claim 60 or 80, wherein the siRNA is commercially available.

84. The method of claim 60 or 80, wherein the siRNA is customized.

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