NON-INVASIVE METHOD FOR QUANTIFICATION OF KIDNEY FUNCTION AND FUNCTIONAL DECLINE

Description

BACKGROUND

[0001] Fourteen percent of the United States population is afflicted with chronic kidney disease (CKD). Approximately 661,000 Americans have renal failure, of which, approximately 468,000 are on dialysis. The high incidence of CKD contributes to health care costs of approximately $80,000 US dollars, per patient, per year. Further, approximately 193,000 Americans have a functioning kidney transplant and 30,000 patients receive new kidney transplants every year - incurring health care costs of approximately $100,000 - $200,000 US dollars yearly for each transplant, and $20,000 US dollars, per patient, per year for immunosuppression. In 2015, Medicare alone spent 64 Billion USD for treatment of chronic kidney disease alone (11% of total covered patients).

[0002] Accurate assessment of renal function is imperative to allow for proper tracking of kidney function or injury. In the case of renal transplantation, renal dysfunction can be associated with 15% - 30% of cases that require treatment with augmented immunosuppression. Usually, 130,000 transplants are rejected after the first 10 years of graft transplantation, making it very important to have accurate and non-invasive tests for kidney function or kidney injury. Nonetheless, the current standard of care does not allow for proper distinction between various underlying causes of either kidney function or injury, such as acute insult / recovery, chronic damage / progression of injury, time assessment for renal replacement therapy, or assessment of dialysis / transplantation needs.

[0003] Consider for instance the severe limitations of a widely used test for measuring renal function, namely the serum creatinine (SCr) blood test. First, the SCr test is a blood test, and the requirement for a blood draw limits its utility in a non-invasive manner. Second, serum creatinine is a late marker of advanced kidney injury and is not specific for the diagnosis of acute rejection (AR). In fact, SCr blood test is confounded by multiple variables as serum creatinine can rise with multiple causes unrelated to kidney function, such as volume depletion, infection, and obstruction. Furthermore, SCr measurements are further confounded by variables such as gender, hydration status, diet and muscle mass. As a result, while the cost of a SCr test is low, the lack of specificity of the SCr test and the influence of confounding variables limit the clinical utility of the test.

[0004] Additionally, the current standard of care for measuring kidney function - the glomerular filtration rate (GFR; also referred to as estimated glomerular filtration rate eGFR) - is perhaps even more limited than the SCr test. In chronic kidney disease, the kidneys lose their ability to effectively filter waste products in the blood because of damage to the glomeruli of nephrons. The standard glomerular filtration rate tests evaluate some level of kidney function by measuring the volume of plasma that the kidneys filter through the glomeruli per unit time. However, there are numerous limitations with the current eGFR tests. First, eGFR requires a blood sample and thus cannot readily be used in a non-invasive setting. Second, eGFR measurements are limited by demographic data collection. eGFR tests provide a measure of how well the kidneys are removing wastes and excess fluid from the blood by inputting a detected serum creatinine level in an equation, along with parameters for age and gender adjustments, and in some instances additional adjustments for those of African American descent. However, there is a lack of a consensus about what formula should be used to estimate glomerular function, where some prefer the Modification of Diet in Renal Disease (MDRD) equation and others the Cockcroft-Gault (CG) equation, as some believe the MDRD equation significantly underestimates the measured GFR when compared with the CG formula. Recently, calculation of the eGFR is done by the chronic kidney disease epidemiology collaboration formula (CKD-EPI).

[0005] Lastly, more sensitive measurements of eGFR are available through the use of inulin, a molecule that is not endogenous in humans. When inulin is used to measure eGFR, a specified mass comprising inulin is injected into a person's bloodstream and the amount of inulin cleared through the urine is indicative of the amount of plasma filtered by the body's glomeruli. Unfortunately, inulin eGFR not only requires a blood draw, but it also typically requires a patient to stay in an outpatient setting, further limiting its utility. Moreover, the inulin GFR test is quite costly relative to SCr or non-inulin eGFR tests, making this test something that is rarely used in an actual clinical setting.

[0006] There currently do not exist any urine-based methods for eGFR prediction or estimation of kidney function. Current methods for kidney function assessment largely consist of semi-quantitative measures of leukocytes, nitrite, urobilinogen, protein, pH, blood, specific gravity, ketone, bilirubin, and glucose. These tests merely identify the presence of late-stage kidney disease and functional decline and do not provide a quantitative estimate of kidney function.

[0007] Eiselt J, et al,. Asymmetric dimethylarginine and progression of chronic kidney disease: a one-year follow-up study. Kidney Blood Press Res. 2014;39(1):50-7 describes that asymmetric dimethylarginine (ADMA) is a prognostic factor in patients with CKD.

[0008] WO 2004 / 046314 describes methods for detecting ADMA in a biological sample.

[0009] CN 105988001 describes a test kit and methods for measuring dimethyl-L-arginine concentrations.

[0010] US 2010 / 029013 describes methods for detecting ADMA in a biological sample.

[0011] US 2016 / 187348 describes methods and apparatus for determination, diagnosis, progression and prognosis of kidney disease and mortality associated with kidney disease.BRIEF SUMMARY OF THE INVENTION

[0012] The invention provides a method for determining kidney function of a subject from a urine sample, the method comprising: detecting an amount of asymmetric dimethylarginine (ADMA) from a urine sample of a subject; assaying the urine sample to determine a hydration status of the subject; generating a value indicative of the kidney function of the subject based on the amount of ADMA from the urine sample and the hydration status of the subject; determining the kidney function of the subject based on the value, wherein the amount of urine ADMA from the urine sample of the subject positively correlates with glomerular filtration rate (GFR) estimated from plasma; further comprising coupling a reagent to ADMA prior to detecting the amount of ADMA from the urine sample, wherein the coupling reagent is a compound that comprises a NHS ester moiety; wherein the step of detecting the amount of ADMA from the urine sample of the subject comprises: contacting the urine sample with an antibody that specifically binds to ADMA; and detecting an amount of the antibody that is in a bound state; wherein the antibody that specifically binds ADMA has a reactivity for symmetric dimethylarginine (SDMA) that is less than 1 % of the antibody's reactivity for ADMA.

[0013] In some embodiments, the coupling agent is selected from N-hydroxysuccinimido carbonic acid; (2,5-dioxopyrrolidin-1-yl) hydrogen carbonate (also known as succinimidocarbonate); N,N'-Disuccinimidyl carbonate; carbonic acid (chloromethyl ester) (N-hydroxysuccinimide ester); or (2,5-dioxopyrrolidin-1-yl) prop-2-enyl carbonate.

[0014] The antibody that specifically binds ADMA has a reactivity for symmetric dimethylarginine (SDMA) that less than 1% of its reactivity for ADMA. In some cases, the method further comprises contacting the urine sample with the probe to determine an amount of the urinary biomarker that is indicative of the subject's hydration level, and the urinary biomarker that is indicative of the subject's hydration level may be urine creatinine.

[0015] The method comprises contacting the urine sample with a reagent that reacts with free ADMA to form an ADMA conjugate prior to contacting the urine sample with the antibody that specifically binds to ADMA. ADMA may be bound to the antibody as either free ADMA or the conjugate that results after the aforementioned coupling. The reagents may be selected from N-hydrosuccinimido carbonic acid; (2,5-dioxopyrrolidin-1yl)hydrogen carbonate (also known as succinimidocarbonate); N,N'-disuccinimidyl carbonate; carbonic acid (choloromethyl ester) (N-hydroxysuccinimide ester); or (2,5-dioxopyrrolidin-1-yl)prop-2-enyl carbonate. In some instances, the amount of ADMA is determined via an enzyme-linked immunosorbent assay (ELISA), such as a competitive ELISA. In some instances, the amount of ADMA is determined via a lateral flow assay.

[0016] In some instances, the urine sample is a diluted urine sample. In some cases the subject is a mammal, such as human, a domesticated cat or a dog.

[0017] In some aspects provided herein is a method for determining kidney function of a subject from a urine sample, the method comprising: detecting an amount of asymmetric dimethylarginine (ADMA) from a urine sample of a subject; assaying the urine sample to determine a hydration status of the subject; and generating a value indicative of the kidney function of the subject based on the amount of ADMA from the urine sample and the hydration status of the subject; determining the kidney function of subject based on the value. In some instances, generating a value indicative of the kidney function of the subject comprises inputting the amount of ADMA and the hydration status of the subject into an algorithm to produce the value. In such instances, the algorithm may be implemented via a computer system. In some instances, determining the kidney function of the subject comprises comparing the value to a threshold and determining the kidney function of the subject based on the comparison. In some instances, generating the value indicative of the kidney function of the subject comprises inputting a determined amount of a hydration marker from the urine sample into the algorithm to produce the value, the hydration marker can be creatinine.. In some cases, the amount of urine ADMA from the urine sample of the subject positively correlates with glomerular filtration rate (GFR). In some instances, the hydration status of the subject is an amount of a urinary marker that is indicative of a hydration level in the subject, and the hydration mark can be urine creatinine.

[0018] The method may further comprise coupling a reagent to ADMA prior to detecting the amount of ADMA from the urine sample, and the reagent can be selected from N-hydrosuccinimido carbonic acid; (2,5-dioxopyrrolidin-1yl)hydrogen carbonate (also known as succinimidocarbonate); N,N'-disuccinimidyl carbonate; carbonic acid (choloromethyl ester) (N-hydroxysuccinimide ester); or (2,5-dioxopyrrolidin-1-yl)prop-2-enyl carbonate. The step of detecting the amount of ADMA from the urine sample of the subject comprises: contacting the urine sample with an antibody that specifically binds to ADMA; and detecting an amount of the antibody that is in a bound state. The antibody that specifically binds ADMA has a reactivity for symmetric dimethylarginine (SDMA) that is less 1% of its reactivity for ADMA. In some aspects, the subject is identified as having impaired kidney function when the ADMA is in the urine sample at a concentration of less than 19.4 µM. In some instances, the subject is identified as having impaired kidney function when the ADMA / creatinine ratio is less than 0.3 µM / mg / dL or 0.7 µM / mg / dL, respectively.BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Fig. 1A shows an example fit for ADMA using the analysis methods described herein. Fig. 1B shows an example fit for SDMA using the analysis methods described herein. Fig. 2A shows that the kidney health of an individual can be determined by comparing the quantity of ADMA in the urine sample to a cutoff value indicative of kidney injury status, which may be a pre-determined clinical threshold or relative to a patient's baseline ADMA value. Fig. 2B shows that the kidney health of an individual can be determined by comparing the ratio of the ADMA / SDMA in the urine sample to a cutoff value indicative of kidney injury status, which may be a pre- determined clinical threshold or relative to a patient's baseline ADMA / SDMA ratio value. Fig. 2C shows that the ratio of ADMA / SDMA in the urine sample can be used to calculate an approximation of a known clinical parameter, the estimated glomerular filtration rate (eGFR). Fig. 2D shows that a representative functional score can be used to determine CKD in a subject. Fig. 2E shows that a representative multiple linear regression can be used to determine kidney function in a patient. The data in Figs. 1A-2E are from a dataset of 80 urine samples. Fig. 3 shows data from a larger data set of 300 urine samples. Based on these data. KIT Function (also referred to as KIT GFR ) was calculated using a formula that incorporates SDMA, ADMA, urine creatinine, urine protein and age of patient. The upper row of panels shows eGFR plotted against ADMA concentration, the ratio of ADMA / SDMA, and the ratio of ADMA to creatinine. The lower row of panels shows eGFR plotted against KIT Function , CKD stage plotted against KIT Function , specificity and sensitivity of the assay for KIT Function and proteinuria, and mean of actual eGFR and KIT Function versus actual eGFR minus KIT Function . Fig. 4 shows a representative study design and patient disposition. (Left) In the original trial, 34 patients met inclusion criteria and were randomized into rituximab and standard of care treatment groups. At least one urine sample was available from 28 of the 34 patients, with 14 having urine samples at all three designated time-points. (Right) Pictorial depiction of patients, treatment, and sample availability. Patients were segregated based on treatment, either with standard of care (turquoise) or rituximab (coral), with individual patients as rows. A yellow square indicates a urine sample was available at the indicated time-point, while gray indicates that no urine sample was available. Figs. 5A and 5B show that the urinary KIT biomarkers could segregate healthy controls from those with IgA nephropathy. Fig. 5A. An IgA Risk Score ranging from 0 to 100 segregated healthy control patients from those with IgA nephropathy. Urine samples were collected from healthy controls (n = 64) who had no evidence of kidney disease or injury as assessed by both absence of proteinuria and eGFR greater than 120 mL / min per 1.73 m 2< . All urine samples from IgA patients (n = 67) were used, as none of these patients had remission of IgA during the treatment duration. Fig. 5B. Receiver-operator characteristic (ROC) curves of the IgA Risk Score with AUC of 0.994 (P < 0.0001) and proteinuria. For the IgA Risk Score, at a threshold of 57.4, the sensitivity and specificity were 95.5% and 98.4% respectively. **** P < 0.0001. Fig. 6 shows a representative example of biomarker modeling of disease progression status after one year of treatment. Modeling was performed on endpoint, midpoint, and baseline biomarker data. The y-axis shows the probability of progression as determined by a nominal logistic regression model. Fig. 7 is a schematic illustrating that SDMA is renally cleared regardless of the degree of kidney functional impairment, in contrast ADMA is degraded. Fig. 8 shows that urinary ADMA was inversely correlated with blood SDMA in canine samples, suggesting its utility in noninvasively determining kidney function. Fig. 9 shows a linear relationship between the ratio of urinary ADMA / SDMA and blood SDMA, suggesting that SDMA may be used as a normalization factor. Fig. 10 shows a linear relationship between the ratio of urinary ADMA / creatinine and blood SDMA, suggesting that creatine may be used as a normalization factor. Fig. 11 shows a linear relationship between SDMA and creatinine measurements of feline and canine kidney function. Fig. 12 is a graph illustrating the development of a one-biomarker formula only considering urinary ADMA and predicting blood SDMA. Fig. 13 is a graph illustrating the development of a formula for kidney function considering urinary SDMA, ADMA, and creatine together. Fig. 14 illustrates results obtained for the detection of SDMA and ADMA in mammalian urine samples with the protocols described herein. Fig. 15 illustrates a comparison of the performance of the method described herein in urine sample versus serum samples in five different stages of chronic kidney disease. DEFINITIONS

[0020] The terms "a," "an," or "the" as used herein not only include aspects with one member, but also include aspects with more than one member. For instance, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a cell" includes a plurality of such cells and reference to "the agent" includes reference to one or more agents known to those skilled in the art, and so forth.

[0021] The terms "subject", "patient" or "individual" are used herein interchangeably to refer to a human or animal. For example, the animal subject may be a mammal, a primate (e.g., a monkey), a livestock animal (e.g., a horse, a cow, a sheep, a pig, or a goat), a companion animal (e.g., a dog, a cat), a laboratory test animal (e.g., a mouse, a rat, a guinea pig, a bird), an animal of veterinary significance, or an animal of economic significance.

[0022] The term "biofluid" or "biofluidic sample" refers to a fluidic composition that is obtained or derived from an individual that is to be characterized and / or identified, for example based on physical, biochemical, chemical and / or physiological characteristics. Examples of biofluid include blood, serum, plasma, saliva, phlegm, gastric juices, semen, tears, and sweat. The method of the present invention is carried out using a urine sample.

[0023] As used herein, the term "AUC" refers to "area under the curve" or C-statistic, which is examined within the scope of ROC (receiver-operating characteristic) curve analysis. AUC is an indicator that allows representation of the sensitivity and specificity of a test, assay, or method over the entire range of test (or assay) cut points with just a single value. An AUC of an assay is determined from a diagram in which the sensitivity of the assay on the ordinate is plotted against 1-specificity on the abscissa. A higher AUC indicates a higher accuracy of the test; an AUC value of 1 means that all samples have been assigned correctly (specificity and sensitivity of 1), an AUC value of 50% means that the samples have been assigned with guesswork probability and the parameter thus has no significance.

[0024] Using AUCs through the ROC curve analysis to evaluate the accuracy of a diagnostic or prognostic test are well known in the art, for example, as described in, Pepe et al., "Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic, Prognostic, or Screening Marker," Am. J. Epidemiol 2004, 159 (9): 882-890, and "ROC Curve Analysis: An Example Showing The Relationships Among Serum Lipid And Apolipoprotein levels In Identifying Subjects With Coronary Artery Disease," Clin. Chem., 1992, 38(8): 1425-1428. See also, CLSI Document EP24-A2: Assessment of the Diagnostic Accuracy of Laboratory Tests Using Receiver Operating Characteristic Curves; Approved Guideline - Second Edition. Clinical and Laboratory Standards Institute; 2011; CLSI Document I / LA21-A2: Clinical Evaluation of Immunoassays; Approved Guideline - Second Edition. Clinical and Laboratory Standards Institute; 2008.

[0025] As used herein, the term "diagnose" means assigning symptoms or phenomena to a disease or injury. For the purpose of this invention, diagnosis means determining the presence of organ injury in a subject.

[0026] As used herein, the term "predict" refers to predicting as to whether organ injury is likely to develop in a subject.

[0027] As used herein, the terms "glomerular filtration rate" ("GFR"), "estimated glomerular filtration rate" ("eGFR"), and "actual glomerular filtration rate" ("actual GFR"), refer to a measure of kidney function that uses a person's age, gender, and blood creatinine level.

[0028] As used herein, the terms "KIT Function ", "KIT GFR ", is a measurement of kidney function that incorporates measurements of SDMA, ADMA, urine creatinine, urine protein, and age of patient as inputs into a suitable formula, such as the formula below. eGFR = SDMA + 277 + 140 × ADMA Gender F + SDMA + 83.321 ∗ min greaterorequal 37 × ADMA , Protein , SDMA 2 × min 0.288 Citrate Age × ADMA − min Protein , min 48.065 + ADMA , Creatinine Alternative suitable formulas are further described in the specifications.

[0029] As used herein, a urinary biomarker that is indicative of the subject's hydration level, or a "hydration marker", or "a marker of hydration status", refers to creatinine and SDMA, either used jointly or individually.

[0030] As used herein, the abbreviation SDMA refers to symmetric dimethylarginine.

[0031] As used herein, the abbreviation ADMA refers to asymmetric dimethylarginine.

[0032] As used herein, the abbreviation "KIT biomarkers" refers to a composite of six biomarkers, namely cell-free DNA (cfDNA), methylated cfDNA, clusterin, creatinine, protein, and CXCL10 biomarkers used in kidney injury test (KIT) assay urinary biomarkers to detect kidney injury.

[0033] As used herein, the term "probe" refers to an agent that binds to a biomarker in urine. The term "probe" includes antibodies that bind to biomarkers, including biomarkers that indicate a subject's hydration level.

[0034] As used herein, and as generally used in the art, "urine specific gravity" (USG) is a measure of the concentration of particles in urine and the density of urine compared with the density of water.DETAILED DESCRIPTION

[0035] The present invention provides a method for determining kidney function comprising the quantitative measurement of ADMA in a urine sample. The method of the invention in its general sense is defined by independent claim 1. Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of NO-synthase. It is formed during proteolysis of methylated proteins and removed by renal excretion or metabolic degradation by the enzyme dimethylarginine dimethylaminohydrolase (DDAH). Several cell types, including human endothelial and tubular cells are capable of synthesizing and metabolizing ADMA. The disclosure demonstrates that SDMA and ADMA can be detected in urine samples from a subject using a simple and inexpensive assay which can be easily performed in most clinical laboratories. Notably, the instant disclosure demonstrates that urinary ADMA is both positively and strongly correlated with kidney function, and thus can be used as a biomarker for kidney function, an unexpected result in view of the characterization in the art of serum ADMA as being negatively and weakly correlated with GFR. Consider for example, that SDMA is almost entirely renally cleared (see Fig. 7). Meanwhile, the majority of ADMA is instead degraded. When the kidney is injured the enzymes that degrade ADMA may be upregulated, providing different patterns of ADMA and SDMA for kidney function and injury.

[0036] The methods described herein provide the following advantages. The methods are fully noninvasive and only require urine samples for the prediction of kidney function. No blood draws are required and thus skilled technicians / phlebotomists are not required. Minimal sample processing is required prior to quantification, as the metabolic biomarkers of interest do not degrade rapidly, or they are amenable to being treated with a stabilizing solution.

[0037] In one aspect, the method comprises a microwell assay format and analysis methods that integrates the ADMA biomarkers, additional biomarkers, and clinical / demographic parameters of the subject to provide a functional kidney score and / or predicted eGFR measurement. In one aspect, the method is a urinary ELISA assay for detecting dimethylarginine (ADMA) in a urine sample from a subject. In some embodiments, the method is a competitive enzyme-linked immunoassay. The steps of the method are recited in claim 1.

[0038] In the method of the present invention, urinary ADMA is derivatized by contacting the urine sample with a coupling agent. The coupling agent is a compound that comprises an NHS ester moiety. In some embodiments, the compound is based on amine-reactive crosslinker chemistry whereby primary amines (- NH 2 ) are reacted with various chemical groups that enable subsequent conjugation of other chemicals of interest and typically conjugate based on acylation or alkylation. The conjugation chemistry is described below:

[0039] In some embodiments, the coupling agent is selected from the group consisting of N-hydroxysuccinimido carbonic acid; (2,5-dioxopyrrolidin-1-yl) hydrogen carbonate (also known as succinimidocarbonate); N,N'-Disuccinimidyl carbonate; carbonic acid (chloromethyl ester) (N-hydroxysuccinimide ester); and (2,5-dioxopyrrolidin-1-yl) prop-2-enyl carbonate.

[0040] The coupling agent provides the following advantages. First, without being bound by theory, ADMA is a small molecule, and antibodies may bind to the derivatized ADMA with higher affinity than the non-derivatized ADMA because this class of antibodies are generated against ADMA conjugated to either KLH or BSA. As such, while the antibody binds ADMA, it actually has higher binding affinity for a region consisting of ADMA and the derivatization linker. Furthermore, ADMA can occur internally within a protein sequence, as they are derivatives of arginine, a common amino acid. By using a derivatization agent, the likelihood of cross-reactivity towards internal ADMA moieties (i.e., within a protein sequence) versus free ADMA is reduced as the antibodies can bind to the derivatization linker in addition to the ADMA molecule in the free-form, but cannot bind ADMA within the amino acid sequence of a protein as the derivatization agent does not chemically react with internal ADMA. The urinary biomarker that is indicative of the subject's hydration level can be urine creatinine and it may be detected with suitable methods described in the art, including ELISA. In some instances, the antibody that specifically binds ADMA has a reactivity for symmetric dimethylarginine (SDMA) that is less 1% of its reactivity for ADMA.

[0041] Second, while it is possible to create competitive immunoassays that do not use a derivatization agent (e.g. by direct conjugation of the small molecule to the adsorbent component, such as BSA), this creates significant steric hindrance that reduces the ability of the antibody to bind the molecule of interest, thus reducing overall affinity. Thus, derivatization allows detecting the small molecule ADMA in a competitive immunoassay with high sensitivity.

[0042] In some embodiments, ELISA wells are coated with ADMA, and an antibody against ADMA is mixed with the diluted urine sample of interest and is added to these wells. The endogenous ADMA in the sample that has been derivatized competes with the well-bound ADMA for antibody binding. In some embodiments, the sample is washed, and antibody binding is detected using a detectable label. In some embodiments, the detectable label is a peroxidase-conjugated antibody that can added to each microtiter well to detect the anti-ADMA antibodies. In some embodiments, the detectable label is detected contacting the sample with tetramethylbenzidine (TMB) or a chemiluminescent substrate solution such as SuperSignal FEMTO ELISA (Thermo Fisher), which is a substrate for peroxidase. In embodiments where the substrate is TMB, the enzymatic reaction can be terminated by an acidic stop solution. In some embodiments, the absorbance is measured by a spectrophotometer at 450 nm or the luminescence by a luminometer. In a competitive enzyme-linked immunoassay, the intensity of the signal is inversely proportional to the ADMA concentration in the urine sample, as a high ADMA concentration in the sample reduces the urine specific gravity of well-bound antibodies and lowers the signal.

[0043] In some instances, a lateral flow assay LFA dipstick is configured for the detection ADMA, creatinine or both. These markers are indicative of various different kidney failure modes. The results of the test may be read using a benchtop lateral flow assay reader such as the Qiagen LR3, Axxin readers, or another suitable reader. The output of these tests may be plugged into an injury test of the disclosure.

[0044] In some embodiments, the urine sample is diluted to ensure that interference from other urinary components do not interfere with the assay and to ensure that the concentration of ADMA falls within the linear and / or quantifiable range of the assay. Dilution of the urine sample can be done with 1X PBS, bovine serum albumin (BSA) in 1X PBS (where the concentration can range from 1% to 5%), or human serum albumin (HSA) in the range of 3.5 to 5.5 g / dL in 1X PBS.

[0045] In some embodiments, unknown samples are interpolated to the values from a known standard of ADMA values via curve-fitting such as that done by a 4-parameter or 5-parameter logistic, or a log-linear fit. An example fit for ADMA is shown in Fig. 1A. An example fit for SDMA is shown in Fig. 1B. The fits from these curves can be used to create a score for the quantitation of kidney function based on ADMA / SDMA measurements. In some instances, generating the value indicative of the kidney function of the subject comprises inputting an age and a gender of the subject into the algorithm, but do not require an input of the race of a subject.

[0046] A non-limiting example of how ADMA / SDMA measurements can be computed and transformed into a score that is representative of kidney function is as follows: eGFR = SDMA + 277 + 140 × ADMA Gender F + SDMA + 83.321 ∗ min greaterorequal 37 × ADMA , Protein , SDMA 2 × min 0.288 Citrate Age × ADMA − min Protein , min 48.065 + ADMA , Creatinine .

[0047] In some aspects, the sensitivity of the test can be increased by detecting an amount of at least one, at least two, at least three, at least four, or at least five biomarkers in the urine sample, wherein the biomarkers are selected from creatinine, total protein, 5-methylcytosine, cell-free DNA, methylated cell-free DNA, CXCL10, and clusterin.DATA ANALYTICS

[0048] The method of the present invention is for determining kidney function of a subject. In some embodiments, determination of kidney function of an individual comprises comparing the quantity of ADMA in the urine sample to a cutoff value indicative of kidney injury status, which can be a pre-determined clinical threshold or is relative to a patient's baseline ADMA value (See Fig. 2A).

[0049] In some instances, a cut off value that is indicative of kidney injury status can be an ADMA value less than 30 µM, less than 29 µM, less than 28 µM, less than 27 µM, less than 26 µM, less than 25 µM, less than 24 µM, less than 23 µM, less than 22 µM, less than 21 µM, less than 20 µM, less than 19 µM, less than 18 µM, less than 17 µM, less than 16 µM, less than 15 µM, less than 14 µM, less than 13 µM, less than 12 µM, less than 11 µM, less than 10 µM, less than 9 µM, less than 8 µM, less than 7 µM, less than 6 µM, or less than 5 µM. In some embodiments, an ADMA value less than 19.421 µM indicates the subject has reduced kidney function or kidney disease.

[0050] In some embodiments, kidney function is determined by a ratio of ADMA to a biomarker of a subject's hydration level. In some embodiments, the biomarker of the subject's hydration level is creatinine, and kidney function is determined by the ADMA / creatinine ratio. In some instances, an ADMA / creatinine ratio that is indicative of kidney injury status is a ratio of less than 2.0 (µM / mg / dL), less than 1.9 (µM / mg / dL), less than 1.8 (µM / mg / dL), less than 1.7 (µM / mg / dL), less than 1.6 (µM / mg / dL), less than 1.5 (µM / mg / dL), less than 1.4 (µM / mg / dL), less than 1.3 (µM / mg / dL), less than 1.2 (µM / mg / dL), less than 1.1 (µM / mg / dL), less than 1.0 (µM / mg / dL), less than 0.9 (µM / mg / dL), less than 0.8 (µM / mg / dL), less than 0.7 (µM / mg / dL), less than 0.6 (µM / mg / dL), less than 0.5 (µM / mg / dL), less than 0.4 (µM / mg / dL), less than 0.3 (µM / mg / dL), less than 0.2 (µM / mg / dL), or less than 0.1 (µM / mg / dL). In some embodiments, an ADMA / creatinine ratio of less than 0.312 (µM / mg / dL) indicates the subject has reduced kidney function or kidney disease.

[0051] In some embodiments, a functional score is used to determine kidney function in a subject. In some embodiments, the functional score is estimated GFR (eGFR). In some embodiments, the functional score is a composite value that is calculated based on the quantity of ADMA detected in the urine samples. The functional score can be, for example, calculated from the mathematical relationships described in Figs. 1-3, along with the input of other relevant data, such as age and gender. In some embodiments, additional biomarkers, such as citrate, can be used to calculate the composite value. In some embodiments, additional biomarkers present in the urine sample, including but not limited to creatinine, total protein, 5-methylcytosine, cell-free DNA, methylated cell-free DNA, CXCL10, and clusterin, can be used to calculate the composite value. In some embodiments, clinicodemographic features are included to refine the functional score, including age and gender. In a specific case, the score may take the form of c * ADMA / (d * SDMA + age * creatinine), where c and d are specific constants, ADMA and SDMA are measured in µM, age is measured in years, and creatinine is measured in mg / dL. In some embodiments, the constants c and d are 3.932 * 10 4< and 149.3 respectively, in which case the score approximates the eGFR. In some embodiments, an eGFR less than 120 mL / min per 1.73 m 2< , less than 110 mL / min per 1.73 m 2< , less than 100 mL / min per 1.73 m 2< , less than 95 mL / min per 1.73 m 2< , less than 90 mL / min per 1.73 m 2< , less than 85 mL / min per 1.73 m 2< , less than 80 mL / min per 1.73 m 2< , less than 75 mL / min per 1.73 m 2< , less than 70 mL / min per 1.73 m 2< , less than 65 mL / min per 1.73 m 2< , less than 60 mL / min per 1.73 m 2< , less than 55 mL / min per 1.73 m 2< , less than 50 mL / min per 1.73 m 2< , less than 45 mL / min per 1.73 m 2< , less than 40 mL / min per 1.73 m 2< , less than 35 mL / min per 1.73 m 2< , or less than 30 mL / min per 1.73 m 2< is indicative of kidney injury status. In some embodiments, an eGFR less than 90 mL / min per 1.73 m 2< indicates the subject has reduced kidney function or kidney disease.

[0052] In some embodiments, the functional score is calculated based on the following equation: SDMA + 83.321 * A - D + E, where A is the minimum of B or (SDMA 2< * C / (age * ADMA)) where B is 1 if (37 * ADMA) >= total protein and 0 otherwise, where C is minimum of 0.288 or citrate, where D is the minimum of total protein or 48.065 + ADMA or creatinine, and where E is (277 + 140 * ADMA)(Gender F + SDMA), where Gender F = 1 if the Gender is female. In this case, ADMA, SDMA, and citrate are measured in µM, age is measured in years, total protein is measured in ug / mL, and creatinine is measured in mg / dL. (See Fig. 2D).

[0053] In some embodiments, a multiple linear regression of the above parameters can be used in order to create a functional score. In some embodiments, an intercept is included. In some embodiments, two-way interactions, three-way interactions, and transforms such as logarithm, square, cube, and square root are included (Fig. 2E). In some embodiments, logistic regression or bootstrap random forest ensemble models are used to determine a functional score. The present disclosure contemplates variations of the analysis that can be similarly used to transform the data into a functional score.

[0054] In some embodiments, kidney function (KIT Function or KIT GFR ) is calculated using a formula that incorporates ADMA, and a marker of hydration that can be urine creatinine. The formula can further incorporate the biological gender and age of patient. The formula can also incorporate the total amount of protein. Additional model development can also include gender and race (Fig. 3). In some instances a race of the subject is not inputed into the algorithm. In some embodiments, the following formula is used to calculate KIT GFR : KIT GFR = 141.922734943398 + 44.1991850006697*ADMA / Creatinine - max(Age, min(150.839900231942 + -200.429015237454*ADMA / Creatinine - ADMA, Age*Protein - 1403.95919636272 - Creatinine*ADMA)).

[0055] Kidney function and injury are related, but injury can occur at severely low function or at normal function. Acute kidney injury (AKI), formerly called acute kidney failure, for example can be associated with a sudden decline in glomerular filtration rate (GFR). The assays and biomarkers described herein can also be used to discriminate healthy control subjects from patients with IgA nephropathy. As shown in the Fig. 5A and 5B, an IgA risk score was developed using the biomarkers using a Bootstrap Forest ensemble model, as described in the Examples. For the IgA Risk Score, at a threshold of 57.4, the sensitivity and specificity were 95.5% and 98.4% respectively.

[0056] The assays and biomarkers described herein can also be used discriminate kidney disease progressors from non-progressors. As shown in Fig. 6, urinary biomarkers alone could be used to classify progressor status. In some embodiments, progressor status was classified using nominal logistic regression with 100% accuracy based on urinary measurements alone (P = 0.0154).EXAMPLES

[0057] Only the sections relating to a method for determining kidney function of a subject from a urine sample fall within the invention.Example 1

[0058] This example describes a representative assay of the methods described herein. The assay was performed based on the following protocol: 1. Raw urine samples received by the lab are collected in standard urine collection containers (100 mL maximum volume). 2. The urine specimen is equally aliquoted into 50 mL conical tubes. 3. The urine is centrifuged for 20 minutes at 2,000 x g at 4 C. 4. The urine is pooled into a separate container and the pellet discarded. This removes contaminating debris and cells. Alternatively, a 5 micron (µM) cell strainer may be employed to similar effect. 5. Tris 1M pH 7.0 is added to the pooled urine at 1 / 10th volume of the urine. This ensures that all samples will behave similarly in the downstream analysis procedures and ensures similar stability of urine components. 6. For long-term storage (>1 month), the sample is stored at -80C. For short-term storage prior to analysis, the sample is stored at -20C. 7. For the ADMA ELISA, the urine is diluted 1:20 in 1X PBS to ensure proper osmolality for downstream derivatization and antibody binding. 8. 1X PBS with 0.05% Tween-20 is used as the wash buffer (PBST). 9. For each sample, 50 µL of the pre-diluted urine is mixed with 150 µL of 1 M Tris-HCl, pH 9.1. To this, 50 µL of the derivatization solution (0.833 mg of N-hydroxysuccinimido carbonic acid in 50 µL of DMSO) is mixed on a horizontal shaker at 400 RPM for 45 minutes at room temperature. Standards (diluted from stock solution in 1X PBS) are treated similarly. 10. 250 µL of 1X PBS is added to the mixture and mixed on a horizontal shaker at 400 RPM for 45 minutes at room temperature. 11. Onto a clear-bottom, functionalized ELISA microplate which has been coated with BSA conjugated to ADMA, 50 µL of the derivatized samples are added. 12. 50 µL of mouse monoclonal ADMA IgM antibody is added to each of the wells and allowed to incubate overnight at 4 C. 13. The wells are washed 5X with PBST. 14. 100 µL of biotinylated rabbit anti-mouse IgM is added to each of the wells and allowed to incubate for 1 hour at RT at 400 RPM on a horizontal shaker. 15. The wells are washed 5X with PBST. 16. 100 µL of 1-Step Ultra TMB-ELISA Substrate Solution is added and covered with a foil plate cover. 17. The plate is allowed to incubate for ~15 minutes at RT at 400 RPM on a horizontal shaker. 18. 100 µL of 2N sulfuric acid is added to each well. 19. Absorption is determined by using a colorimetric plate reader at 450 nm with 620 nm as a reference wavelength. 20. A 4-parameter logarithmic fit is used to interpolate the unknown values against the standard curve values. Example 2

[0059] This example describes a representative study design and patient disposition.

[0060] From 34 total patients, 69 urine samples were collected from 28 patients (Fig. 4). Two time-points or more was available from 25 patients, and a complete set of three time-points collected at baseline, ½ year, and 1 year was available from 14 patients. The baseline characteristics and disposition of the 14 patients are listed in Table 1. Table 1. Baseline characteristics of IgA nephropathy patients with urine collected at all designated three time-points.Baseline Characteristics IgA Cohort (N = 14) 1< Age, year39.5 (29 - 59)Sex• Female4• Male10Race• Caucasian7• Asian / Pacific Islander5• Hispanic / Latino2BMI, kg / m 2< 27.9 (20.5 - 37.4)eGFR, mL / min per 1.73 m 2< 44.7 (30.6 - 69.3)Treatment• Rituximab7• Standard of Care7 1< Data are reported as median (range) or count.

[0061] There was no statistically significant difference between the change in eGFR over the course of the study by treatment with rituximab over standard of care (data not shown). However, while some patients maintained or even recovered kidney function (corresponding to an increase in eGFR), some patients had IgAN progression with functional decline. We therefore investigated whether the KIT Assay biomarkers could be used to not only detect IgA nephropathy through urine alone, but also monitor kidney function changes longitudinally.Example 3

[0062] This example shows that the biomarkers described herein can discriminate healthy controls from patients with IgA Nephropathy.

[0063] Urine samples from healthy control patients were assessed and compared to those collected from the IgA nephropathy patients for the KIT biomarkers. An IgA Risk Score, ranging from 0 to 100, was developed on these biomarkers using a Bootstrap Forest ensemble model. The scores for each of the patients in the two groups are depicted in Fig. 4A. This Score could distinguish between healthy control (median 14.03, 95% CI 8.94 - 18.52) and IgA patients (median 87.76, 95% CI 83.39 - 90.32) (P < 0.0001). Receive-operator characteristic curves (Fig. 4B) comparing the discrimination abilities of the IgA Risk Score and proteinuria identifies the IgA Risk Score (AUC 0.9935, 95% CI 0.985 - 1.000) as performing better than proteinuria (AUC 0.9100, 95% CI 0.855 - 0.965), even in this comparison against healthy control patients. For the IgA Risk Score, at a threshold of 57.4, the sensitivity and specificity were 95.5% and 98.4% respectively.Example 4

[0064] This example shows that the biomarkers described herein can discriminate disease progressors versus non-progressors and predict disease progression.

[0065] Progression was defined as a composite clinical evaluation of changes in proteinuria and eGFR from baseline and, as such, was dependent on both urine and serum biomarker values. We first sought to investigate whether urinary biomarkers alone could be used to classify progressor status. Looking at the 1-year endpoint biomarkers (Fig. 6), progressor status could be classified using nominal logistic regression with 100% accuracy based on urinary measurements alone (P = 0.0154). We then investigated whether midpoint (1 / 2 year prior to progression determination) and baseline (1 year prior) urinary biomarkers could predict progression status. We found that the KIT Assay biomarkers could predict progressor status with 100% accuracy at both time-points (midpoint P = 0.0269, baseline P = 0.0383). For both the baseline and midpoint predictions, the cfDNA values were the most important predictors, with chi square likelihood ratios of 25.92 and 141.98, and with P < 0.0001 for both.Example 5

[0066] This example describes a representative method for selecting a subject for treatment using the methods described herein.

[0067] The disclosed assay, alongside blood glucose and HbA1c testing, can be performed in a community clinic as part of a screening program targeting low resource individuals. The results of the assay may show that a patient has a KIT Function (a measure of kidney function which approximates eGFR) of 22 mL / min / 1.73m 2< . Confirmatory serum creatinine results confirm that the eGFR is in the range of 15 - 30 mL / min / 1.73m 2< , which is clinically recognized as Stage 4 CKD. The patient's blood glucose and HbA1c testing may also reveal that the patient has longstanding, untreated Type II diabetes. The patient will thus be diagnosed with diabetic kidney disease. The patient can be treated with a DKD-targeted drug, such as the SGLT-2 receptor inhibitor empaglifozin at the usually prescribed levels. The patient's kidney function can stabilize and the disclosed assay can be used as a monitoring tool to ensure maintenance of this kidney function over time.Example 6

[0068] This example describes another representative method for selecting a subject for treatment using the methods described herein.

[0069] The disclosed assay can be performed as part of a nationwide screening program in primary school age children targeted towards early detection of IgA / Non-IgA mesangial proliferative glomerulonephritis as well as membrano-proliferative glomerulonephritis. In one scenario, a child is referred with a low KIT Function for kidney biopsy, which has confirmatory findings of IgA nephropathy as based on the Oxford classification with concurrent nephrotic syndrome. The patient is prescribed and receives pulse steroid therapy consisting of i.v. methylprednisone 500 mg / m 2< for 3 consecutive days. Continued oral steroid therapy consists of prednisolone of 30 mg / m 2< daily. Additionally, this patient could receive supportive care of a renin angiotensin system blockade. Recovery of kidney function in the patient can assessed by both an increase in eGFR / serum creatinine and the KIT Function .Example 7

[0070] This example describes another representative method for selecting a subject for treatment using the methods described herein.

[0071] The disclosed assay can be performed on a patient presenting with extreme fatigue, loss of appetite, vomiting, nausea, and changes in urination volume. The results of the assay may show that the patient has a KIT Function of 8 mL / min / 1.73m 2< , indicating Stage 5 CKD. The patient will start renal replacement therapy, involving dialysis at an in-center dialysis clinic, where the patient receives nocturnal dialysis three times a week. The patient will continue this therapy while being placed on the kidney transplant waiting list.Example 8

[0072] This example describes a LFA dipstick prototype for the reliable and accurate detection of ADMA / SDMA in addition to one, two, three, or four additional markers in human urine that have been associated with kidney injury and disease. The markers include cell-free DNA (cfDNA), 5-methylcytosine, CXCL10, and albumin. These four markers are indicative of various different kidney failure modes.

[0073] Normal ranges of cfDNA in urine range from 0 to 5000 GE / ml (where 1 GE = 6.6 pg). Normal ranges of CXCL10 typically are from 0 to 50 pg / mL. Normal ranges of 5-mC typically range from ~0.7 to ~4 ng / ul. Normal ranges of albumin typically range from 0 to 8 mg / dL (i.e. 0 to 80 ug / mL).

[0074] The LFA dipstick prototype described herein is designed to detect the following minimum amounts of the four analytes combined with a threshold of ADMA: Analyte Minimum concentrations cfDNA3000 GE / mLCXCL107.8 pg / mL5-mC0.5 ngalbumin1.5 ug / mL

[0075] The results of the test are read using a benchtop lateral flow assay reader such as the Qiagen LR3 or the Axxin readers.Example 9

[0076] This example describes a representative assay of the methods described herein conducted in ten (10) veterinary subjects. The assay was performed based on the general protocols described in examples above.

[0077] Urine samples from felines and canines with matched blood-based kidney function biomarkers were characterized for urinary ADMA, SDMA, total protein, and creatinine. Ten canines were included in this preliminary analysis for further validation of the markers in other mammalian models. Briefly, the standard-of-care test for veterinary applications, namely IDEXX test, was used to measure performance of kidney function in 10 canines. The kidney function of the canines as measured by the IDEXX SMDA test is described below: Animal IDSample DateIDEXX SDMA [ug / dL]CANINE-10037 / 1 / 202015CANINE-10047 / 1 / 202014CANINE-10057 / 1 / 202019CANINE-10067 / 1 / 202072CANINE-10075 / 29 / 202017CANINE-10097 / 10 / 202014CANINE-10107 / 14 / 202043CANINE-10137 / 17 / 202012CANINE-10157 / 17 / 202020CANINE-10167 / 17 / 202012

[0078] The analysis indicated that urinary ADMA was inversely correlated (exponential relationship) with blood SDMA in these canine samples, suggesting its utility in noninvasively determining kidney function. See Fig. 8. The analysis also identified a linear relationship between the ratio of ADMA / SDMA and the ratio of ADMA / SDMA with blood SDMA, demonstrating the utility of SDMA or creatinine as normalization factors. See Fig. 9 and Fig. 10. Further, SDMA and creatinine correlated strongly with one another. See Fig. 11.

[0079] Based on this analysis a one-biomarker formula was developed for predicting the levels of blood SDMA. See Fig. 12. eGFR = 4.457 + 1.290 0.183 − 0.154 × ADMA

[0080] Further, a composite analysis of SDMA, ADMA, and creatine together provided the following equation for predicting the levels of blood SDMA. See Fig. 13. eGFR = 12.831 + 176.293 × SDMA + 50.745 × ADMA + 180.145 × ADMA 2 × SDMA 2 − 0.137 × CR − 0.434 × SDMA × CR − 230.623 × ADMA × SDMA − 121.514 × SDMA 2 Example 10

[0081] This example describes a representative ELISA assay for the detection of SDMA. The assay is performed with antibodies purchased from Immundiagnostik AG, Stubenwald-Allee 8a, 64625 Bensheim, Germany, and resold by various suppliers, including Enzo Life Sciences. In some embodiments, detection of SDMA was performed as described below: The assay is based on the method of competitive enzyme linked immunoassays.

[0082] The sample preparation includes the addition of a derivatisation reagent for SDMA derivatisation. Afterwards, the treated samples and the polyclonal SDMA antiserum are incubated in wells of a microtiter plate coated with SDMA derivative (tracer). During the incubation period, the target SDMA in the sample competes with the tracer, immobilised on the wall of the microtiter wells, for the binding of the polyclonal antibodies.

[0083] During the second incubation step, a peroxidase conjugated antibody is added to detect the anti-SDMA antibodies. After washing away the unbound components, tetramethylbenzidine (TMB) is added as a peroxidase substrate. Finally, the enzymatic reaction is terminated by an acidic stop solution. The colour changes from blue to yellow and the absorbance is measured in a photometer at 450 nm. The intensity of the yellow colour is inverse proportional to the SDMA concentration in the sample; this means high SDMA concentration in the sample reduces the concentration of tracer-bound antibodies and lowers the photometric signal. A dose response curve of absorbance unit (optical density, OD at 450 nm) vs. concentration is generated using the values obtained from the standards. SDMA, present in the patient samples, is determined directly from this curve.Urine and SDMA detection sample preparation procedure

[0084] Bring all reagents and samples to room temperature (15-30 °C) and mix well. Derivatisation of standards, controls and samples is carried out in single analysis in vials (e.g. 1.5 ml polypropylene vials). 1Add 200 µl standard (STD), 200 µl control (CTRL) and 50 µl of urine sample in the corresponding vials.2Add 150 µl reaction buffer (DERBUF) only to the samples.3Add 50 µl derivatisation reagent (DER) into each vial (STD, CTRL, sample), mix thoroughly by repeated inversion or several seconds on a vortex mixer. Incubate for 45 min at room temperature (15-30 °C) on a horizontal shaker.

[0085] 2 x 50 µl of the derivatised standards, controls and samples are used in the ELISA as duplicates.Test procedure

[0086] Mark the positions of standards / controls / samples in duplicate on a protocol sheet. Take as many microtiter strips as needed from the kit. Store unused strips covered with foil at 2-8 °C. Strips are stable until expiry date stated on the label. 4For the analysis in duplicate, take 2 x 50 µl of the derivatised standards / controls / samples out of the vials and add into the respective wells of the microtiter plate.5Add 50 µl SDMA antibody (AB) into each well of the microtiter plate.6Cover the strips and incubate for 2 hours at room temperature (15-30 °C) on a horizontal shaker.7Discard the content of each well and wash 5 times with 250 µl wash buffer. After the final washing step, remove residual wash buffer by firmly tapping the plate on absorbent paper.8Add 100 µl conjugate (CONJ) into each well.9Cover the strips and incubate for 1 hour at room temperature (15-30 °C) on a horizontal shaker.10Discard the content of each well and wash 5 times with 250 µl wash buffer. After the final washing step, remove residual wash buffer by firmly tapping the plate on absorbent paper.11Add 100 µl substrate (SUB) into each well.12Incubate for 10-15 min* at room temperature (15-30 °C) in the dark.13Add 100 µl stop solution (STOP) into each well and mix well.14Determine absorption immediately with an ELISA reader at 450 nm against 620 nm (or 690 nm) as a reference. If no reference wavelength is available, read only at 450 nm. If the extinction of the highest standard exceeds the range of the photometer, absorption must be measured immediately at 405 nm against 620 nm (690 nm) as a reference. Example 11

[0087] This example describes a representative ELISA assay for the detection of ADMA. The assay is performed with antibodies purchased from Immundiagnostik AG, Stubenwald-Allee 8a, 64625 Bensheim, Germany. In some embodiments, detection of ADMA was performed as described below: The assay is based on the method of competitive enzyme linked immunoassays. The sample preparation includes the addition of a derivatisation-reagent for ADMA derivatisation. Afterwards, the treated samples and the polyclonal ADMA-antiserum are incubated in the wells of a microtiter plate coated with ADMA-derivative (tracer). During the incubation period, the target ADMA in the sample competes with the tracer immobilised on the wall of the microtiter wells for the binding of the polyclonal antibodies.

[0088] During the second incubation step, a peroxidase-conjugated antibody is added to detect the anti-ADMA antibodies. After washing away the unbound components, tetramethylbenzidine (TMB) is added as a peroxidase substrate. Finally, the enzymatic reaction is terminated by an acidic stop solution. The colour changes from blue to yellow, and the absorbance is measured in the photometer at 450 nm. The intensity of the yellow colour is inverse proportional to the ADMA concentration in the sample; this means, high ADMA concentration in the sample reduces the concentration of tracer-bound antibodies and lowers the photometric signal. A dose response curve of the absorbance unit (optical density, OD at 450 nm) vs. concentration is generated, using the values obtained from the standard. ADMA, present in the patient samples, is determined directly from this curve.Sample preparation procedure

[0089] Bring all reagents and samples to room temperature (15-30 °C) and mix well.

[0090] Derivatisation of standards, controls and samples is carried out in single analysis in vials (e.g. 1.5 ml polypropylene vials). We recommend preparing one derivatisation per standard, control and sample and transferring it in duplicate determinations into the wells of the microtiter plate. 1Add 200 µl standard (STD), 200 µl control (CTRL) and 50 µl urine sample in the corresponding vials.2Add 150 µl reaction buffer (DERBUF) only to the urine samples.3Add 50 µl derivatisation reagent into each vial (STD, CTRL, sample) and mix thoroughly by repeated inversion or several seconds on a vortex mixer. Incubate for 45 min at room temperature (15-30 °C) on a horizontal shaker.4Add 250 µl dilution buffer (CODIL) into each vial, mix well and incubate for 45 min at room temperature (15-30 °C) on a horizontal shaker.

[0091] 2 x 50 µl of the derivatised standards, controls and samples are used in the ELISA as duplicates.Test procedure

[0092] Mark the positions of standards / controls / samples in duplicate on a protocol sheet. Take as many microtiter strips as needed from the kit. Store unused strips covered with foil at 2-8 °C. Strips are stable until expiry date stated on the label. 5For the analysis in duplicate take 2 x 50 µl of the derivatised standards / controls / samples out of the vials and add into the respective wells of the microtiter plate.6Add 50 µl ADMA antibody into each well of the microtiter plate.7Cover the strips tightly with foil and incubate overnight at 2-8°C.8Discard the content of each well and wash 5 times with 250 µl wash buffer. After the final washing step, remove residual wash buffer by firmly tapping the plate on absorbent paper.9Add 100 µl conjugate (CONJ) into each well.10Cover the strips and incubate for 1 hour at room temperature (15-30 °C) on a horizontal shaker.11Discard the content of each well and wash 5 times with 250 µl wash buffer. After the final washing step, remove residual wash buffer by firmly tapping the plate on absorbent paper.12Add 100 µl substrate (SUB) into each well.13Incubate for 10-14 min* at room temperature (15-30 °C) in the dark.14Add 100 µl stop solution (STOP) into each well and mix well.15Determine absorption immediately with an ELISA reader at 450 nm against 620 nm (or 690 nm) as a reference. If no reference wavelength is available, read only at 450 nm. If the extinction of the highest standard exceeds the range of the photometer, absorption must be measured immediately at 405 nm against 620 nm (690 nm) as a reference.

[0093] For automated ELISA processors, the given protocol may need to be adjusted according to the specific features of the respective automated platform.Example 12

[0094] This example describes a representative ELISA assay for the parallel detection of ADMA and SDMA. The assay is performed with antibodies purchased from Immundiagnostik AG, Stubenwald-Allee 8a, 64625 Bensheim, Germany. In some embodiments, detection of ADMA and SDMA was performed as described below: In these ELISAs, standards and controls are provided by the manufacturer as ready-to-use vials. The ADMA antibody and derivatization reagents come lyophilized and must be reconstituted. The SDMA antibody does not come lyophilized and is ready-to-use.Pre-Prep

[0095] The SDMA standards are stored at -20°C. These should be removed prior to the start of the experiment to thaw.

[0096] The ADMA DMSO and the SDMA DER derivatization reagents are frozen at 4°C. These should be thawed prior to use by thawing or on a heat block.

[0097] The ADMA DER derivatization reagent is lyophilized and must be reconstituted in 6 mL of DMSO 10 minutes prior to use.

[0098] The ADMA antibody is lyophilized and must be reconstitute in 6 mL of 1X wash buffer.Sample Preparation

[0099] Bring all reagents from both ADMA and SDMA kits and samples to room temperature (20 - 30 °C) and mix well. Make wash buffer by diluting wash buffer concentrate (WASHBUF A) 1:10 with ultrapure water.

[0100] Depending on how many replicates are to be run, dilute the urine sample 1:20 in 1X PBS in a 96-well plate. All proceeding steps will describe how to run this set of assays in duplicate with controls and standards also run in duplicate. Modifications to the plate plan and amount of sample can be made to run this in singlicate or triplicate.

[0101] Derivatization of standards, controls and samples is carried out in 2 mL deep 96-well plates, with one plate per assay.

[0102] Add 200 uL of standard (STD), 200 uL of control (CTRL), and 50 uL of diluted sample in the corresponding wells.

[0103] Add 150 uL of reaction buffer (DERBUF) only to the sample wells.

[0104] Add 50 uL derivatization reagent into the sample, STD, and CTRL wells.

[0105] Incubate for 1 hour at room temperature on a circular, horizontal shaker. This time may require modification. This is a chemical reaction step, as it is a chemical reaction that may come to completion faster in a hotter environment.

[0106] ADMA only: Add 250 uL dilution buffer (CODIL) into the sample, STD, and CTRL wells.

[0107] For SDMA, continue incubating during this period.

[0108] Incubate for 45 minutes at room temperature on a circular, horizontal shaker.Assay Procedure

[0109] Take out the microtiter strips from the kit matching the number of CTRL / STD / sample wells needed for the ADMA and SDMA assays.

[0110] For ADMA and SDMA plates respectively: Take 2 x 50 uL from the sample, STD, and CTRL wells into the appropriate wells in the microtiter strips for duplicates.

[0111] Add 50 uL ADMA or SDMA antibody into each well for the ADMA or SDMA plate respectively.

[0112] Cover the microtiter plates tightly with foil and incubate overnight at 4°C.

[0113] Discard the content of each well and wash 5 times with 250 uL wash buffer on an automated plate washer.

[0114] Add 100 uL conjugate (CONJ) into each well.

[0115] Cover the microtiter plate tightly with foil and incubate for 1 hour at room temperature on a circular, horizontal shaker.

[0116] Discard the content of each well and wash 5 times with 250 uL wash buffer on an automated plate washer.

[0117] Add 100 uL substrate (SUB) into each well.

[0118] Incubate for 10-15 minutes at room temperature covered by a foil plate sealer.

[0119] Add 100 uL stop solution (STOP) into each well and mix on a plate shaker.

[0120] Determine absorption immediately with an ELISA reader at 450 nm and at 620 nm.Standard Curve Generation and Interpolation

[0121] Using a 4-parameter logistic fit, create a curve correlating the concentration of the standards with the difference in absorption at 450 nm and 620 nm.

[0122] Interpolate sample unknown values to the curve. Although there is no sample concentration between 0 and 0.1 µM, the manufacturer sets the 0 value as 0.001 µM in generating the standard curve. This can be done if sample values are expected to fall below 0.1 µM.

[0123] Multiply the interpolated value by 20 to get the actual urine concentrations for SDMA and ADMA in the samples.Expected Results

[0124] Fig. 14 illustrates expected results for the SDMA and ADMA assay. Squares indicate the interpolation of the urine samples. All urine samples were within the range of the assay.

[0125] The quantitative numbers detected by this assay can be inputted into one or more of the algorithms described above and the kidney function of the subject can be estimated.Example 13

[0126] On 346 unique urine samples from 346 human patients, the KIT Function / eGFR score was determined by measuring ADMA and using the equation:

[0127] KIT_GFR = 141.922734943398 + 44.1991850006697*ADMA / Creatinine - max(Age, min(150.839900231942 + -200.429015237454*ADMA / Creatinine - ADMA, Age*Protein - 1403.95919636272 - Creatinine*ADMA)). Detection of six biomarkers (CXCL10, cfDNA, m-cfDNA, creatinine, total protein, clusterin) had previously been measured on the same urine samples as described by PCT / US2017 / 047372. This KIT Function / eGFR score was inputted into the KIT Score algorithm, thus providing a substitute for other blood-based eGFR tests described in the art.

[0128] Fig. 15 illustrates a comparison of the performance of the method described herein in urine sample versus serum samples in five different stages of chronic kidney disease.

Claims

1. A method for determining kidney function of a subject from a urine sample, the method comprising: detecting an amount of asymmetric dimethylarginine (ADMA) from a urine sample of a subject; assaying the urine sample to determine a hydration status of the subject; generating a value indicative of the kidney function of the subject based on the amount of ADMA from the urine sample and the hydration status of the subject; determining the kidney function of the subject based on the value, wherein the amount of urine ADMA from the urine sample of the subject positively correlates with glomerular filtration rate (GFR) estimated from plasma; further comprising coupling a reagent to ADMA prior to detecting the amount of ADMA from the urine sample, wherein the coupling reagent is a compound that comprises a NHS ester moiety; wherein the step of detecting the amount of ADMA from the urine sample of the subject comprises: contacting the urine sample with an antibody that specifically binds to ADMA; and detecting an amount of the antibody that is in a bound state; wherein the antibody that specifically binds ADMA has a reactivity for symmetric dimethylarginine (SDMA) that is less than 1 % of the antibody's reactivity for ADMA.

2. The method of claim 1, wherein the hydration status of the subject is an amount of a urinary marker that is indicative of a hydration level in the subject.

3. The method of claim 2, wherein the urinary marker that is indicative of a hydration level in the subject is urine creatinine.

4. The method of any one of claims 1-3, wherein generating a value indicative of the kidney function of the subject comprises inputting the amount of ADMA and the hydration status of the subject into an algorithm to produce the value.

5. The method of claim 4, wherein the algorithm is implemented via a computer system.

6. The method of any one of claims 1-5, wherein determining the kidney function of the subject comprises comparing the value to a threshold and determining the kidney function of the subject based on the comparison.

7. The method of any one of claims 1-6, wherein generating the value indicative of the kidney function of the subject comprises inputting an age, a gender, or both of the subject into an algorithm.

8. The method of any one of claims 1-7, wherein the reagent is selected from N-hydrosuccinimido carbonic acid; (2,5-dioxopyrrolidin-1-yl)hydrogen carbonate; N,N'-disuccinimidyl carbonate; carbonic acid, chloromethyl ester, N-hydroxysuccinimide ester; or (2,5-dioxopyrrolidin-1-yl)prop-2-enyl carbonate.