WO2015077676A1 - Serum biomarkers in human kidney disease patients - Google Patents

Abstract

Methods for determining CKD or CHF severity, risk and progression using Kidney Injury Marker 1 (KIM-1) in biological samples from a subject.

Description

SERUM BIOMARKERS IN HUMAN KIDNEY DISEASE PATIENTS

BACKGROUND

[0001] Acute kidney disorders often result in the development of chronic kidney disease (CKD). CKD can also develop slowly and result in acute episodes.

Elevations in Kidney Injury Molecule (KIM-1) in human or animal urine specimens have been noted (Zhang et al. 2013, Nan Fang Yi Ke Da Xue Xue Bao 33(8): 1 146-50; Alter et al. 2012, Clin. Lab 58(7-8): 659-71). Furthermore, endothelin-1 (ET-1) and interleukin- 18 (IL-18) elevations in plasma have been shown to be associated with CKD (Yong et al. 2013, Cytokine 64(l):39-42; Cottone et al. 2009, Nephrol. Dial. Tranplant 24:497-503). No studies have shown that KIM-1 is measurable in human plasma or serum, and no studies have shown that KIM-1 in plasma or serum or blood is diagnostic or associated with CKD or Acute kidney disease. There is currently great interest in the field of CKD to identify biomarkers that provide a method for earlier diagnosis and identify patients at higher risk for CKD progression.

[0002] Also, patients with CKD are known to also have a higher risk of cardiovascular disease.

[0003] Accordingly, the inventors have identified a need in the art to detect biomarkers in serum or plasma that are related to CKD so that CKD can be more readily or effectively diagnosed and staged, risk for developing CKD can be more readily or effectively assessed, and patients who are responders and non-responders to CKD therapy can be more readily or effectively identified.

[0004] The inventors have also identified in a need in the art for a better predictor of congestive heart failure (CHF).

SUMMARY

[0005] Broadly stated, the disclosure relates to the use of KIM-1 in the diagnosis, prognosis, and treatment of CKD and CHF. In some aspects, KIM-1 is combined with Endothelin- 1 in the diagnosis, prognosis and treatment. The biomarkers are measured in plasma and the results are used in various statistical analyses for diagnosis, prognosis and treatment. [0006] In one aspect, the disclosure is directed to a method for detecting Kidney Injury Molecule- 1 (KIM-1) protein in a sample of human blood, serum or plasma. The method includes contacting the sample with an antibody specific for KIM-1 and detecting the binding between the antibody and KIM- 1 in the sample.

[0007] In another aspect the disclosure is directed to a method for diagnosing CKD in a subject. The method includes determining an amount of KIM-1 in a blood, serum or plasma sample from the subject, comparing the amount of KIM-1 in the sample to a threshold concentration representing a concentration of KIM-1 in a the blood, serum or plasma of a population of healthy patients, and determining that the subject has CKD when the concentration of a KIM-1 in the sample is above the threshold concentration. The threshold concentration may be, for example, a mean amount of KIM-1 in the population samples.

[0008] A further aspect of the disclosure is directed to a method of determining the progression of CKD in a subject. The method includes determining an amount of KIM-1 in a first blood, serum or plasma sample from a subject at a first time point, determining an amount of KIM-1 in a second blood, serum or plasma sample from a subject at a second time point, comparing the amount of KIM-1 in first sample to the amount of KIM- 1 in the second sample; and determining that CKD has progressed in the patient by determining that the amount of KIM- 1 in the second sample is greater than the amount of KIM- 1 in the first sample.

[0009] In yet another aspect, the disclosure is directed to a method for detecting CKD in a subject. The method includes detecting the concentration of Kidney Injury Molecule-1 (KIM-1) and Endothelin-1 (ET-1) in a blood, serum or plasma sample from the subject, creating a CKD score based upon the concentration of KIM-1 and ET-1; determining CKD in the subject when the score is greater than a predetermined CKD score. In one embodiment, the score is determined using an area under receiver operator characteristic analysis. In other embodiments, the score comprises an odds ratio, which may be determined by predicting the presence of CKD by the coded risk categories in a logistic regression model.

[0010] Still further, the disclosure is directed to a method for diagnosing congestive heart failure (CHF) in a subject. The method includes determining an amount of KIM-1 in a blood, plasma or serum sample from a subject a subject, and correlating the amount of KIM- 1 in the sample to the presence of CHF in the subject. The method may also include comparing the amount of KIM- 1 in the sample to a threshold concentration representing the concentration in a non-CHF population, and determining that the subject has CHF when the concentration of a KIM- 1 in the sample is above the threshold concentration.

BRIEF DESCRIPTION OF THE FIGURES

[0011] Figure 1 shows KIM-1 levels in normal human plasma donors. All 7 EDTA plasma samples tested quantified above the assay LLoQ.

[0012] Figure 2 shows IL-18 levels in normal human plasma and serum donors. IL-18 levels in 2 human EDTA plasma samples (samples 1-2) and 8 human serum samples (samples 3-10). All IL-18 samples quantified above the assay LLoQ.

[0013] Figure 3 shows ET-1 correlation with age, and demonstrates that ET-1 does not significantly correlate with age in this panel of 300 normal human donors.

[0014] Figure 4 shows AuROC of biomarkers independently and combined. ROC analysis of KIM-1, ET-1, and IL-18 predicting CKD. Individual area under the curves were 0.8856, 0.9753, and 0.8092 respectively, however when combined the AUC was 0.9862.

[0015] Figure 5 shows KIM-1 levels between congestive heart failure (CHF) plasma versus age/gender matched plasma.

[0016] Figure 6 shows AuROC of KIM-1 and ET-1 biomarkers independently and combined. ROC analysis of KIM-1 and ET-1 used to predict CKD. Individual area under the curves were 0.8533 and 0.8639 respectively, however when combined, the AUC was 0.9222.

[0017] Figure 7 shows a linearity of standardization, spike recovery and dilutional linearity of the plasma KIM-1 assay. FIG 7A shows the back- fit of standard curve across the reportable range. FIG 7B shows the linearity of signal at the low-end assay range. FIG7C shows the spike recovery and dilutional linearity of samples

[0018] Figure 8 shows the provisional reference range of plasma KIM-1 in healthy volunteers.

[0019] Figure 9 shows the weekly biological variability of KIM-1 over 6 weeks [0020] Figure 10 shows the plasma KIM-1 elevations in Kidney disease (CKD) and congestive heart failure (CHF) compared to controls

[0021] Figure 1 1 shows the plasma KIM-1 concentrations (pg/mL) as a function of eGFR (mL/minute) quartiles in the heart failure validation cohort

DESCRIPTION

[0022] Unless otherwise defined, the technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. Expansion and clarification of some terms are provided herein. All publications, patent applications, patents and other references mentioned herein, if not otherwise indicated, are explicitly incorporated by reference.

[0023] As used herein, the singular forms "a," "an", and "the" include plural referents unless the context clearly dictates otherwise.

[0024] As used herein, the term "subject" refers to a mammal that can be afflicted by a osteoarthritis, but may or may not have such a disease. Typically, the terms "subject" and "patient" are used herein interchangeably. In various embodiments, the subject is a human.

[0025] As used herein, the term "sample" is taken broadly to include any sample suitable for the methods described herein. Typically, the sample blood, serum, or plasma.

[0026] As used herein, the term "healthy volunteer average concentrations" refers to the average concentration of the various biomarkers described herein for at least two subjects who do not have CKD (i.e., "healthy patients"). Preferably, average concentration values are calculated from biomarker concentrations measured in larger groups of patients without CKD or free of any symptoms of CKD. Healthy volunteer ("HV") average concentrations are provided herein, but one of skill in the art may also measure biomarker concentrations in one or more populations of subjects lacking CKD or any symptoms of CKD utilizing an apparatus capable of sensitively measuring the concentrations of biomarkers described herein and calculating the average values for each biomarker in such HV populations. [0027] As used herein, the term "therapy" refers to the administration of any medical treatment (e.g., pharmaceuticals) or interventional treatment (e.g., surgery) to affect CKD or the biomarkers relevant to CKD described herein.

[0028] As used herein, the term "CV" refers to the coefficient of variance.

[0029] As used herein, the term "average CV" refers to average of the coefficient of variance obtained for all samples tested in triplicate.

[0030] The terms "diagnosis" and "diagnostics" also encompass the terms "prognosis" and "prognostics", respectively, as well as the applications of such procedures over two or more time points to monitor the diagnosis and/or prognosis over time, and statistical modeling based thereupon. Furthermore the term diagnosis includes: a. prediction (determining if a patient will likely develop a

hyperproliferative disease), b. prognosis (predicting whether a patient will likely have a better or worse outcome at a pre-selected time in the future), c. therapy selection, and d. therapeutic drug monitoring e. relapse monitoring.

[0031] The term "score" or "scoring" refers to calculating a probability likelihood for a parameter in a sample. In one example, values closer to 1.0 are used to represent the likelihood that a sample is from a patient suffering from a condition, such as CKD or CHF; values closer to 0.0 represent the likelihood that the patient does not have a condition. The logistic regression classification method may be used to combine a panel of biomarkers to calculate the probability score between, for example, 0 and 1 for each sample.

[0032] The term "coefficients" refers to the weight assigned to each protein used to in the logistic regression equation to score a sample.

[0033] The term "condition" as used herein refers generally to a disease, event, or change in health status.

[0034] "Accuracy" refers to the degree of conformity of a measured or calculated quantity (a test reported value) to its actual (or true) value. Clinical accuracy relates to the proportion of true outcomes (true positives (TP) or true negatives (TN) versus misclassified outcomes (false positives (FP) or false negatives (FN)), and may be stated as a sensitivity, specificity, positive predictive values (PPV) or negative predictive values (NPV), or as a likelihood, odds ratio, among other measures. [0035] The term "biological sample" as used herein refers to any sample of biological origin potentially containing one or more biomarker proteins. Examples of biological samples include tissue, organs, or bodily fluids such as whole blood, plasma, serum, tissue, lavage or any other specimen used for detection of disease.

[0036] The terms "subject" or "patient" as used herein refers to a mammal, preferably a human.

[0037] The term "biomarker" as used herein refers to a polypeptide in a biological sample from a subject with. A biomarker protein includes not only the polypeptide itself, but also minor variations thereof, including for example one or more amino acid substitutions or modifications such as glycosylation or phosphorylation.

Biomarker levels may change due to treatment of the disease. The changes in biomarker levels may be measured in accordance with the present disclosure.

Changes in biomarker levels may be used to monitor the progression of disease or therapy.

[0038] The terms "panel" or "biomarker panel" as used herein refers to a plurality of biomarkers, for example, 1, 2, 3 or more biomarkers. In certain embodiments, the levels of the proteins in the panels can be correlated with the existence of a condition in a subject.

[0039] "Treating" or "treatment" as used herein with regard to a condition may refer to preventing the condition, slowing the onset or rate of development of the condition, reducing the risk of developing the condition, preventing or delaying the development of symptoms associated with the condition, reducing or ending symptoms associated with the condition, generating a complete or partial regression of the condition, or some combination thereof.

[0040] The term "providing" as used herein with regard to a biological sample refers to directly or indirectly obtaining the biological sample from a subject. For example, "providing" may refer to the act of directly obtaining the biological sample from a subject (e.g., by a blood draw, tissue biopsy, lavage and the like). Likewise, "providing" may refer to the act of indirectly obtaining the biological sample. For example, providing may refer to the act of a laboratory receiving the sample from the party that directly obtained the sample, or to the act of obtaining the sample from an archive. [0041] The term "sensitivity" refers to a characteristic of a diagnostic test relating to the probability that a patient with the disease will have a positive test result. This is derived from the number of patients with the disease who have a positive test result (true positive) divided by the total number of patients with the disease, including those with true positive results and those patients with the disease who have a negative result, i.e. false negative.

[0042] The term "specificity" refers to a characteristic of a diagnostic test relating the probability that a patient without the disease will have a negative test result. This is derived from the number of patients without the disease who have a negative test result (true negative) divided by all patients without the disease, including those with a true negative result and those patients without the disease who have a positive test result, e.g. false positive. While the sensitivity, specificity, true or false positive rate, and true or false negative rate of a test provide an indication of a test's performance, e.g. relative to other tests, to make a clinical decision for an individual patient based on the test's result, the clinician requires performance parameters of the test with respect to a given population.

[0043] In one aspect, the disclosure relates to a method for detecting Kidney Injury Molecule- 1 (KIM-1) protein in a sample of human serum or plasma comprising contacting the sample with an antibody specific for KIM- 1 and detecting the binding between the antibody and KIM-1 in the sample. In various embodiments, the disclosure is directed to a highly sensitive assay that can be used to measure plasma levels of KIM-1 and ET-1 for predicting CKD and CKD severity and progression, and CHF and CHF severity and progression.

[0044] Further, differences in KIM- 1 and ET- 1 concentrations can be used to determine between various stages of CKD and CHF progression.

[0045] In another aspect, the disclosure relates to a method for diagnosing CKD and CHF in a subject comprising determining an amount of KIM-1 in a blood, serum or plasma sample from the subject, comparing the amount of KIM-1 in the sample to a threshold concentration representing a concentration of KIM-1 in a the blood, serum or plasma of a population of healthy patients, and determining that the subject has CKD when the concentration of a KIM- 1 in the sample is above the threshold concentration. In some embodiments, the amount of KIM-1 in the sample from the subject is determined by contacting the sample with an antibody specific for KIM-1 and detecting the binding between the antibody and KIM- 1 in the sample. In another embodiment, the threshold concentration represents an amount equivalent to, for example, the mean amount of KIM-1 in the population samples. In another example, the threshold concentration represents the mean KIM-1 concentration in a healthy population plus one or two standard deviations from the mean.

[0046] In another aspect, the disclosure relates to a method of determining the progression of CKD or CHF in a subject comprising: (a) determining an amount of KIM-1 in a first biological sample from a subject at a first time point; (b) determining an amount of KIM-1 in a second biological sample from a subject at a second time point; (c) comparing the amount of KIM- 1 in first sample to the amount of KIM- 1 in the second sample; and (d) determining that CKD or CHF has progressed in the patient by determining that the amount of KIM-1 in the second sample is greater than the amount of KIM-1 in the first sample. In some embodiments, the methods above determine the amount of KIM- 1 by contacting the biological sample with an antibody specific for KIM-1 and determining the amount of specific binding between the antibody and KIM-1 in the sample.

[0047] In another aspect, the disclosure relates to a method for detecting CKD in a subject, comprising detecting the concentration of Kidney Injury Molecule-1 (KIM-1) and Endothelin-1 (ET-1) in a blood, serum or plasma sample from the subject, creating a CKD score based upon the concentration of KIM- 1 and ET- 1 ; determining CKD in the subject when the score is greater than a predetermined CKD score. In some embodiments, the score comprises an odds ratio. In another embodiment, the odds ratio is determined by predicting the presence of CKD by the coded risk categories in a logistic regression model. The coded risk categories may be, for example, age and gender. In another example, the CKD score is determined using an area under receiver operator characteristic (AuROC) analysis.

[0048] In one embodiment, to evaluate the diagnostic performance of a particular set of biomarkers, a ROC curve is generated for each biomarker. An "ROC curve" as used herein refers to a plot of the true positive rate (sensitivity) against the false positive rate (specificity) for a binary classifier system as its discrimination threshold is varied. A ROC curve can be represented equivalently by plotting the fraction of true positives out of the positives (TPR=true positive rate) versus the fraction of false positives out of the negatives (FPR=false positive rate). Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold.

[0049] FIGS. 4, 5 and 6 provide a graphical representation of the functional relationship between the distribution of biomarker or biomarker panel sensitivity and specificity values in a cohort of diseased subjects and in a cohort of non-diseased subjects.

[0050] AUC or AuROC represents the area under the Receiver Operator Characteristic curve. The AUC is an overall indication of the diagnostic accuracy of 1) a biomarker or a panel of biomarkers and 2) a ROC curve. AUC is determined by the "trapezoidal rule." For a given curve, the data points are connected by straight line segments, perpendiculars are erected from the abscissa to each data point, and the sum of the areas of the triangles and trapezoids so constructed is computed. In certain embodiments of the methods provided herein, a biomarker protein has an AUC in the range of about 0.75 to 1.0. In certain of these embodiments, the AUC is in the range of about 0.8 to 0.9, 0.9 to 0.95, or 0.95 to 1.0.

[0051 ] The disclosure provides for the use of a highly sensitive immunoassay system to measure KIM- 1 and ET- 1 protein levels in blood plasma obtained from CKD patients and healthy volunteer subjects, and describes the differences in biomarker concentrations between these two study groups.

[0052] In an embodiment, the measurement of differences in the biomarker concentrations, either up- or down-regulated, singly or in combination, in CKD patients at a particular time point, for example 24 months, versus baseline provides opportunities for better (e.g., simpler, earlier, faster) disease diagnosis, disease staging, risk classification, disease progression, disease severity and/or identification of therapy responders/non-responders.

[0053] In one embodiment, the disclosure is directed to the determination and monitoring of tubulointerstitial injury, in which the proximal tubular epithelial cells (PTEC) are instrumental. The expression and release of KIM- 1 are induced in PTEC upon injury. KIM-1 appears to be implicated in the process of kidney injury and healing. Expression of KIM-1 is also associated with tubulointerstitial inflammation and fibrosis. In addition, KIM-1 expressing PTEC appears to play the role as the residential phagocytes, contribute to the removal of apoptotic cells and facilitate the regeneration of injured tubules. The precise mechanism of KIM- 1 on restoration of tubular integrity after injury is not fully understood. Better understanding of all of the characteristics resulting in dedifferentiation and proliferation of the proximal tubule epithelial cell and cell-cell and cell-matrix interactions important for this repair function will lead to novel approaches to therapies designed to facilitate the processes of recovery in humans. Accordingly, the determination of KIM- 1 in blood samples can be used an indicator of epithelial integrity and repair.

[0054] CKD Biomarkers

[0055] The use of a biomarker that can predict CKD or rapid disease progression in CKD will facilitate the identification of patients that will have a worsening of disease. This is important for both patient management as well as drug development. There is currently great interest in the field of CKD to identify biomarkers that provide a method for earlier diagnosis and identify patients at higher risk for disease progression.

[0056] In some embodiments, the disclosure is directed to methods for detecting an amount of KIM- 1 and ET-1, in a biological sample from a patient. In one embodiment, the amount of KIM- 1 and ET-1 in a patient's biological sample is compared to the progression or stage of CKD in the patient.

[0057] In other embodiments, the disclosure is also directed to methods for predicting the progression of CKD in a patient comprising determining an amount of a KIM- 1 and ET- 1 in a biological sample from the patient, comparing the amount of the KIM-1 and ET-1 in the sample to a threshold concentration, and predicting the progression of CKD when the concentration of the KIM-1 and ET-1 in the sample is above the threshold concentration. In some embodiments, the threshold

concentration is predetermined. In other embodiments, the threshold concentration is calculated from the concentration of KIM- 1 and ET- 1 in biological samples taken from the same patient at earlier time points.

[0058] KIM-1 is a biomarker for CHF

KIM- 1 is elevated in plasma from human patients diagnosed with congestive heart failure (CHF). Figure 5 shows that KIM-1 is elevated in the CHF panel compared to the age/gender matched panel and demonstrates that KIM-1, a known urine kidney disease biomarker, is elevated in plasma from patients diagnosed with congestive heart failure. All sample tested (CHF and age/gender normal donors) were quantifiable. A logistic regression model controlled for age and gender demonstrated that patients with elevated KIM-1 have a 3.6 (1.1 to 1 1.6 95% confidence interval) higher likelihood of having CHF.

Instruments and Systems Suitable for Highly Sensitive Analysis of Biomarkers

[0059] In another embodiment of the analyzer system, an automatic sampling system may be included in the analyzer system for introducing the sample into the analyzer system. In another embodiment of the analyzer system, a sample preparation system may be included in the analyzer system for preparing a sample. In a further embodiment, the analyzer system may contain a sample recovery system for recovering at least a portion of the sample after analysis is complete.

[0060] In one aspect, the analyzer system consists of an electromagnetic radiation source for exciting a single particle labelled with a fluorescent label. In one embodiment, the electromagnetic radiation source of the analyzer system is a laser. In a further embodiment, the electromagnetic radiation source is a continuous wave laser.

[0061] In an exemplary embodiment, the electromagnetic radiation source excites a fluorescent moiety attached to a label as the label passes through the interrogation space of the capillary flow cell. In some embodiments, the fluorescent label moiety includes one or more fluorescent dye molecules. In some embodiments, the fluorescent label moiety is a quantum dot.

[0062] When the interrogation space is a capillary flow cell, a label is exposed to electromagnetic radiation when the label passes through an interrogation space. The interrogation space is typically fluidly connected to a sampling system. In some embodiments the label passes through the interrogation space of the capillary flow cell due to a motive force to advance the label through the analyzer system. The interrogation space is positioned such that it receives electromagnetic radiation emitted from the radiation source. In some embodiments, the sampling system is an automated sampling system capable of sampling a plurality of samples without intervention from a human operator. [0063] The label passes through the interrogation space and emits a detectable amount of energy when excited by the electromagnetic radiation source. In one embodiment, an electromagnetic radiation detector is operably connected to the interrogation space. The electromagnetic radiation detector is capable of detecting the energy emitted by the label, e.g., by the fluorescent moiety of the label.

[0064] In a further embodiment of the analyzer system, the system further includes a sample preparation mechanism where a sample may be partially or completely prepared for analysis by the analyzer system. In some embodiments of the analyzer system, the sample is discarded after it is analyzed by the system. In other embodiments, the analyzer system further includes a sample recovery mechanism whereby at least a portion, or alternatively all or substantially all, of the sample may be recovered after analysis. In such an embodiment, the sample can be returned to the origin of the sample. In some embodiments, the sample can be returned to microtiter wells on a sample microtiter plate. The analyzer system typically further consists of a data acquisition system for collecting and reporting the detected signal.

Sample Preparation

[0065] In certain embodiments, the patient sample must be prepared for analysis according to the methods of the disclosure.

[0066] In general, any method of sample preparation may be used that produces a label corresponding to a biomarker to be measured, where the label is detectable in the instruments described herein. As is known in the art, sample preparation in which a label is added to one or more particles may be performed in a homogeneous or heterogeneous format. In some embodiments, the sample preparation is formed in a homogenous format. In analyzer system employing a homogenous format, unbound label is not removed from the sample. See, e.g., U.S. Patent Nos. 7,838,250,

7,572,640, and 7,914,734, each of which is incorporated by reference herein in their entirety. In some embodiments, the particle or particles of interest are labelled by addition of labelled antibody or antibodies that bind to the particle or particles of interest. Antibodies

[0067] In one aspect of the disclosure, the biomarker to be measured, such as KIM-1, ET-1 and/or IL-18, can be joined with a binding partner. In certain embodiments, the binding partner is an antibody.

[0068] Any suitable binding partner with the requisite specificity for the form of molecule, e.g., a marker, to be detected can be used. If the molecule, e.g., a marker, has several different forms, various specificities of binding partners are possible. Suitable binding partners are known in the art and include antibodies, aptamers, lectins, and receptors. A useful and versatile type of binding partner is an antibody.

[0069] In one aspect of the disclosure, the amount of KIM-1 and ET-1 is determined by contacting the biological sample with an antibody specific for KIM-1 and ET- 1 and determining the amount of specific binding between the antibody and KIM-1 and ET-1 in the sample.

[0070] In some embodiments, the binding partner is an antibody specific for a molecule to be detected. The term "antibody," as used herein, is a broad term and is used in its ordinary sense, including, without limitation, to refer to naturally occurring antibodies as well as non-naturally occurring antibodies, including, for example, single chain antibodies, chimeric, bifunctional and humanized antibodies, as well as antigen-binding fragments thereof. It will be appreciated that the choice of epitope or region of the molecule to which the antibody is raised will determine its specificity, e.g., for various forms of the molecule, if present, or for total (e.g., all, or substantially all, of the molecule).

[0071] Methods for producing antibodies are well-established. One skilled in the art will recognize that many procedures are available for the production of antibodies, for example, as described in Antibodies, A Laboratory Manual, Ed Harlow and David Lane, Cold Spring Harbor Laboratory (1988), Cold Spring Harbor, N.Y. One skilled in the art will also appreciate that binding fragments or Fab fragments that mimic antibodies can be prepared from genetic information by various procedures (Antibody Engineering: A Practical Approach (Borrebaeck, C, ed.), 1995, Oxford University Press, Oxford; J. Immunol. 149, 3914-3920 (1992)). Monoclonal and polyclonal antibodies to molecules, e.g., proteins, and markers also commercially available (R and D Systems, Minneapolis, Minn. USA; HyTest Ltd., Turku Finland; Abeam Inc., Cambridge, Mass., USA, Life Diagnostics, Inc., West Chester, Pa., USA; Fitzgerald Industries International, Inc., Concord, Mass. USA; BiosPacific, Emeryville, Calif. USA).

[0072] In some embodiments, the antibody is a polyclonal antibody. In other embodiments, the antibody is a monoclonal antibody.

[0073] Capture binding partners and detection binding partner pairs, e.g., capture and detection antibody pairs, can be used in embodiments of the disclosure. Thus, in some embodiments, a heterogeneous assay protocol is used in which, typically, two binding partners, e.g., two antibodies, are used. One binding partner is a capture partner, usually immobilized on a solid support, and the other binding partner is a detection binding partner, typically with a detectable label attached. Such antibody pairs are available from several commercial sources, such as BiosPacific, Emeryville, Calif. Antibody pairs can also be designed and prepared by methods well-known in the art. Compositions of the disclosure include antibody pairs wherein one member of the antibody pair is a label as described herein, and the other member is a capture antibody.

[0074] Antibodies to KIM-1 and ET-1 are well characterized in the field of the disclosure. Antibodies to KIM- 1 and ET- 1 are available from a variety of commercial and non-commercial sources. The disclosure is not limited to any of the particular antibodies provided for exemplary purposes.

Systems for Detection

[0075] As noted above, the diagnostic/prognostic methods described herein generally involve the determination of the amount of biomarker related to CKD from one or a set of samples from a subject. Determination of concentrations of biomarker related to CKD in the practice of the methods can be performed using any suitable apparatus or system that allow for the detection levels described herein. See, e.g., U.S. Patent Nos. 7,838,250, 7,572,640, and 7,914,734. These patents describe instruments, reagents and methods for measuring analytes at levels to carry out the methods of the disclosure and thus identify those patients with biomarker levels related to CKD or CKD progression. Characterization of CKD

[0076] Chronic kidney disease (CKD) is a condition characterized by a gradual loss of kidney function over time. Complications resulting from CKD may include high blood pressure, anaemia (low blood count), weak bones, poor nutritional health and nerve damage. Also, CKD increases a patient's risk of having heart and blood vessel disease. Chronic kidney disease may be caused by diabetes, high blood pressure and other disorders. Importantly, early detection and treatment of CKD can often keep chronic kidney disease from getting worse.

[0077] Symptoms of CKD may include feeling more tired and having less energy, having trouble concentrating, having headaches, nausea, weight loss, having a poor appetite, having trouble sleeping, having muscle cramping at night, having swollen feet and ankles, having puffiness around your eyes, especially in the morning, having dry, itchy skin, needing to urinate more often, especially at night. Furthermore, anyone can get chronic kidney disease at any age. However, some people are more likely than others to develop kidney disease. A patient may have an increased risk for kidney disease if they have diabetes, have high blood pressure, have a family history of kidney failure, are older, or belong to a population group that has a high rate of diabetes or high blood pressure, such as African Americans, Hispanic Americans, Asian, Pacific Islanders, and American Indians.

[0078] CKD may be diagnosed by calculating a patient's Glomerular Filtration Rate (GFR), which can be calculated from the patient's blood creatinine, age, race, gender and other factors. GFR can help stage CKD. A patient may also undergo an ultrasound or CT scan to get a picture of the patient's kidneys and urinary tract. A doctor may also perform a kidney biopsy, which is done in some cases to check for a specific type of kidney disease, or see how much kidney damage has occurred.

[0079] Recent professional guidelines classify the severity of chronic kidney disease in five stages, with stage 1 being the mildest and usually causing few symptoms and stage 5 being a severe illness with poor life expectancy if untreated. Stage 5 CKD is often called end stage renal disease (ESRD), end stage renal failure (ESRF), or end-stage kidney disease (ESKD) and is synonymous with the terms chronic kidney failure (CKF) or chronic renal failure (CRF). Stage 1 : Slightly diminished function; kidney damage with normal or relatively high GFR (>90 niL/min/1.73 m2). Kidney damage is defined as pathological abnormalities or markers of damage, including abnormalities in blood or urine test or imaging studies. Stage 2: Mild reduction in GFR (60-89 mL/min/1.73 m2) with kidney damage. Kidney damage is defined as pathological abnormalities or markers of damage, including abnormalities in blood or urine test or imaging studies. Stage 3 : Moderate reduction in GFR (30-59 mL/min/1.73 m2). British guidelines distinguish between stage 3 A (GFR 45-59) and stage 3B (GFR 30^14) for purposes of screening and referral. Stage 4: Severe reduction in GFR (15-29 mL/min/1.73 m2). Preparation for renal replacement therapy. Stage 5: Established kidney failure (GFR <15 mL/min/1.73 m2, permanent renal replacement therapy (RRT), or end stage renal disease (ESRD).

[0080] Treatment of CKD

[0081 ] Depending on the underlying cause, some types of chronic kidney disease can be treated; however; in most cases chronic kidney disease has no cure. Treatment typically consists of measures to help control signs and symptoms of chronic kidney disease, reduce complications, and slow the progress of the disease. If a patient's kidneys become severely damaged, the patient may need treatments for end-stage kidney disease.

[0082] Treating CKD usually involves therapies to slow or control the disease or condition that is causing your kidney failure. The goal of therapy is to slow down or halt the progression of CKD to stage 5. Treatment options vary, depending on the cause, but kidney damage can continue to worsen even when an underlying condition, such as high blood pressure, has been controlled. Treatments may include: (1) High blood pressure medications. People with chronic kidney disease may experience worsening high blood pressure, and medications to lower blood pressure may be used (i.e., angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers). (2) Medications to lower cholesterol levels (i.e., statins, to lower your cholesterol. (3) Medications to relieve anemia (i.e., erythropoietin, typically with iron). (4) Medications to relieve swelling (i.e., diuretics). (5) Medications to protect your bones (i.e., calcium and vitamin D supplements). (6) A lower protein diet to minimize waste products in the patient's blood and reduce the amount of work on the kidneys. Treatment for end-stage kidney disease requires dialysis or a kidney transplant. [0083] In another aspect, the patient is treated according to the Kidney Disease Outcomes Quality Initiative (KDOQI) Clinical Practice Guideline for Diabetes and Chronic Kidney Disease (CKD) (2012 update) (Am J Kidney Dis. 2012; 60(5):850- 886), which is incorporated by reference herein in its entirety.

[0084] In another aspect, the disclosure is directed to a method for optimizing of a treatment protocol for a patient suffering from CKD. The method includes determining one or more biomarkers for CKD including KIM-1 and ET-1 in a patient suffering from CKD before and/or or during a treatment regimen for CKD. The levels of the biomarkers may be monitored over the course of the treatment, and the treatment may be maintained, adjusted, enhanced, removed, or changed based upon the levels of the biomarkers over the course of the treatment. For example, the biomarkers may be measured at intervals such as daily, weekly, monthly, quarterly, semi-annually, or annually, in order to identify the usefulness of a treatment for CKD, and the treatment may be maintained, adjusted, removed or changed based upon level of the biomarkers or the state of CKD in the patient.

[0085] Treatment of CHF

[0086] After congestive heart failure is diagnosed, treatment should be started immediately. Perhaps the most important and yet most neglected aspect of treatment involves lifestyle modifications, such as reduction of sodium intake, regulation of fluid consumption, maintaining an appropriate body weight, and exercise.

[0087] In addition, CHF patients can be treated with several medications. For example, anticoagulants (e.g., Dalteparin (Fragmin), Danaparoid (Orgaran)

Enoxaparin (Lovenox) Heparin (various) Tinzaparin (Innohep) and

Warfarin (Coumadin)); antiplatelet agents (e.g., Aspirin, Ticlopidine, Clopidogrel (Plavix®), and Dipyridamole), Angiotensin-Converting Enzyme (ACE) Inhibitors (e.g„ Benazepril (Lotensin), Captopril (Capoten), Enalapril (Vasotec), Fosinopril (Monopril), Lisinopril, (Prinivil, Zestril), Moexipril (Univasc), Perindopril (Aceon), Quinapril (Accupril), Ramipril (Altace), Trandolapril (Mavik); Angiotensin II Receptor Blockers (or inhibitors) (e.g., Candesartan (Atacand), Eprosartan (Teveten), Irbesartan (Avapro), Losartan (Cozaar), Telmisartan (Micardis), and Valsartan (Diovan); Beta Blockers (e.g., Acebutolol (Sectral), Atenolol (Tenormin), Betaxolol (Kerlone), Bisoprolol/hydrochlorothiazide (Ziac), Bisoprolol (Zebeta), Carteolol (Cartrol), Metoprolol (Lopressor, Toprol XL), Nadolol (Corgard), Propranolol (Inderal), Sotalol (Betapace), Timolol (Blocadren); Calcium Channel Blockers (e.g., Amlodipine (Norvasc, Lotrel), Bepridil (Vascor), Diltiazem (Cardizem, Tiazac), Felodipine (Plendil), Nifedipine (Adalat, Procardia), Nimodipine , (Nimotop), Nisoldipine (Sular), Verapamil (Calan, Isoptin, Verelan); Diuretics (e.g., Amiloride (Midamor), Bumetanide (Bumex), Chlorothiazide (Diuril), Chlorthalidone

(Hygroton), Furosemide (Lasix), Hydro-chlorothiazide (Esidrix, Hydrodiuril), Indapamide (Lozol) and Spironolactone Aldactone); Vasodialators (e.g., Isosorbide dinitrate (Isordil), Nesiritide (Natrecor), Hydralazine (Apresoline), Nitrates,

Minoxidil); Digitalis Preparations (Digoxin and Digitoxin, e.g., Lanoxin); and Statins (e.g., statins, resins, nicotinic acid (niacin), gemfibrozil, clofibrate etc.).

[0088] Diagnosis of Disease using KIM-1 and ET-1.

[0089] In the following examples, median biomarker levels were compared between diseased panels and normal panels using the Wilcoxon Rank Sum test.

Continuous variable correlations were performed using Spearman Correlation.

Individual or multi-marker odds ratio and AuRoc models were determined using logistic regression. Median biomarker levels were compared between the KD & CHF panels and their matched control panel using the Wilcoxon Rank Sum test.

Continuous variable correlations were performed using Spearman Correlation or multivariate linear regression of log transformed biomarker concentrations. Individual or multi-marker odds ratio and area under the receiver-operating characteristic curve AUROC models were determined using logistic regression. All statistics were performed using SAS version 9.3.

Examples

[0090] Example 1: KIM-1 and ET-1 in normal human serum or plasma

[0091 ] KIM- 1 and ET- 1 levels in human serum and plasma samples were quantified using the methods described below (informed consent was given by all study participants and studies were approved by the Institutional Review Board (IRB), and all samples were stored at -70C prior to thawing for the current study). The KIM- 1 and ET-1 assays had analytical Lower Limits of Quantification (LLoQs) of 2.0 pg/mL, 0.5 pg/mL, and 0.6 pg/mL respectively. Human KIM-1 levels from 7 normal EDTA plasma donors are shown in Figure 1. Human IL-18 levels were also determined in 2 normal EDTA plasma donors and 8 normal serum donors. (See Figure 2). KIM-1, ET-1 and IL-18 levels were quantifiable in plasma/serum from all normal human donors tested. Polypeptide sequences for each of the markers are shown in Table 12 at the end of the specification.

[0092] KIM-1 Human Sample Testing

[0093] KIM-1 levels in human serum and plasma samples were quantified using a plate based sandwich immunoassay. Capture antibody (Human TIM-l/KIM- 1/HAVCR Affinity Purified Polyclonal Ab, Catalog #AF1750, R&D Systems) was passively coated to a 96-well polystyrene assay plate in a carbonate buffer. The plate was incubated overnight at 4°C then washed (3x, BioTek plate washer) and blocked with 3% BSA/TBS for 1 hour at room temperature. After blocking, the plate was frozen at -80°C until use. On the day of testing the 96-well plate was thawed and washed (3x). The standard curve was prepared by diluting recombinant human KIM- 1 analyte (Catalog #1750-TM, R&D Systems) in assay buffer (1.6% BSA, heterophilic blockers, 0.25% Triton X-100, 600 mM NaCl, 15 mM EDTA, lOOmM TRIS, 0.1% NaN3, pH 8.0). 50 of each standard was added to the plate in duplicate. Samples were diluted 1 :2.5 in assay buffer and 50 was added to the plate in duplicate. The plate was incubated at room temperature for 1 hour, not shaking, and then washed (6x). Alexa-fluor 647 labeled detection antibody (Catalog #AF1750, R&D Systems) was diluted to 100 ng/mL and 50 was added to each well. The plate was incubated at room temperature for 1 hour, not shaking, and then washed (6x). Detection antibody was eluted by adding 50 μΐ_^ of low pH glycine buffer and incubated for 5 minutes at room temperature. A polypropylene 384-well plate was prepared with 10 μϊ_^ of 1 M neutralizing Tris buffer. Then 30 μϊ_^ of the eluent from the 96-well plate was added to 384-well plate containing Tris.

Neutralized detection antibody was analyzed on the SINGULEX^® Single Molecule Counting ERENNA^® System.

[0094] Analytical assay methods and sample preparation.

[0095] The reporting range of the assay and linearity of curve fit was determined by back fitting signal (Detected Events signal) obtained from the standard curve. The assay limit of detection (LoD) was determined through the method of two times the standard deviation of the blank signal divided by the slope of the standard curve. The assay lower limit of quantification (LLoQ) was determined across 6 independent assay runs using the lowest standard point where the back interpolated value provided a CV < 20% and a recovery between 80-120%. Precision studies used human plasma with values of approximately 20-120pg/mL run in triplicates per plate for six independent assay runs to determine intra-assay precision and over twenty six independent assay runs to evaluate inter-assay precision. Precision samples were diluted 1 :6 in assay buffer. Spike recovery was performed by spiking four neat plasma samples with 3 levels of KIM-1 (600, 120, and 24pg/ml) and then diluting the samples 1 :5 in assay buffer before testing. Dilutional linearity was performed by spiking four independent plasma samples with KIM- 1 analyte to an anticipated final concentration of 400 pg/mL. This neat sample was then diluted serially 1 :2 to 1 : 16 with assay buffer. These neat and diluted samples were added directly to the assay well without further dilution. KIM-1 assay testing on the KD and CHF discovery panels used a 1 :2.5 dilution in assay buffer and the 200 sample- Vanderbilt Registry HF cohort was tested as a 1 :4 dilution in assay buffer. The final concentrations of KIM- 1 were back calculated using the appropriate dilution factor.

[0096] Representative graphs and a table showing typical assay performance results are presented in Figure 7A-C and Table A. Figure 7A depicts the reporting range of the assay, from 2 pg/mL to 1,000 pg/mL. The linearity of curve fitting was determined by back fitting the signal obtained from the standard curve resulted in an R2 of 0.98. Figure 7B depicts the low-end reporting linearity (R2=0.99) of the assay as Detected Event signal vs. KIM-1 input. Regarding assay sensitivity, the assay LoD was calculated at 1.4 pg/mL and the assay LLoQ was 2 pg/mL. Assay precision reported in Table A showed acceptable performance with both intra- and inter- assay coefficients of variance (CVs) <20% Spike recovery and dilutional linearity results are shown in Figure 7C. A linear response was found with plasma diluted 1 :2 to 1 : 16 serially with recovery generally between 90-110%. Of note, neat spiked samples significantly under recovered indicating that a minimal dilution of 1 :2 in assay buffer was required. Hence plasma clinical samples from the KD and CHF discovery panels and validation panel were tested with at least a 1 :2 dilution in assay buffer, as described in Methods. The four human spiked plasma spiked with 600, 120 and 24pg/mL KIM-1, all provided recovery between 80-102%. TABLE 1. KIM-1 Assay Performance

[0097] A preliminary assessment of the appropriate dilution factor for KIM-1 measurement in plasma was determined. A 1 : 10 dilution in assay buffer resulted in KIM- 1 quantification in all 7 plasma samples tested with the resulting values being 4- 10- fold higher than the assay LLoQ (data not shown). These results led to the conclusion that dilution of plasma in the discovery and validation panels (as described in Methods) would yield accurate quantification of KIM- 1.

[0098] ET-1 Human Sample Testing

[0099] The endothelin-1 assay targeted the final active form of the molecule (amino acids 1-21). Endothelin-1 levels in serum samples were quantified using a microparticle based sandwich immunoassay. Biotin labelled capture antibody (Catalog #MAB3440, R&D Systems) was bound to streptavidin coated microparticles (Catalog# 65002, Invitrogen). The standard curve was prepared by diluting ET-1 analyte (Catalog #22859, Anaspec) in standard diluent (3% BSA/TBS). 100 of each standard was added to assay plate in duplicate. Samples were diluted 1 :3 in standard diluent and 100 was added to plate in duplicate. Then 100 of diluted microparticles and diluted detection antibody (Catalog #CBL85, Millipore) were added to assay plate. The plate was incubated for 30 minutes then washed (6x, Tecan HydroFlex). The detection antibody was eluted by adding 10 μΐ_^ of low pH glycine and incubated for 5 minutes at room temperature. Eluent was transferred a 384-well plate already containing 10 μϊ_^ of 0.5 M neutralizing Tris. Neutralized detection antibody was analyzed on the STNGULEX® Single Molecule Counting ERENNA® System. [00100] IL-18 Human Sample Testing

[00101] IL-18 levels in serum samples were quantified using a plate based sandwich immunoassay. Capture antibody for IL-18 (Catalog #D045-3, Medical and Biological Laboratories) was passively coated to a 96-well polystyrene assay plate in a carbonate buffer. The plate was incubated overnight at 4°C then washed (3x, BioTek plate washer) and blocked with 3% BSA/TBS for 1 hour at room temperature. After blocking, the plate was frozen at -80°C until use. On the day of the testing the 96-well plate was thawed and washed (3x). Standard curve was prepared by diluting IL-18 analyte (Catalog #B001-5, Medical and Biological Laboratories) in 50% assay buffer/50% standard diluent. 50 of each standard was added to assay plate in duplicate. Samples were diluted 1 :20 in 50% assay buffer/50% standard diluent and 50 was added to plate in duplicate. The plate was incubated at room temperature for 1 hour, not shaking. Plate was washed (6x). Alexa-fluor 647 labelled detection antibody (Catalog #D044-3, Medical and Biological Laboratories) was diluted to 200 ng/mL and 50 was added to each well. The plate was incubated at room temperature for 1 hour, not shaking. Plate was washed (6x). Detection antibody was eluted by adding 50 μΐ_^ of low pH glycine buffer and incubated for 5 minutes at room temperature. A polypropylene 384-well plate was prepared with 10 μΐ_^ of 1 M neutralizing Tris buffer. Then 30 μϊ_^ of the eluent from the 96-well plate was added to 384-well plate containing Tris. Neutralized detection antibody was analyzed on the SINGULEX® Single Molecule Counting ERENNA® System.

[00102] Example 2: CKD and Corresponding Control Panels

[00103] Serum from 30 human patients diagnosed with CKD was procured from ProMedDx (Norton, MA). The sample IDs, estimated glomerular filtration (eGFR), and renal disease state are displayed in Table 1. A first control serum panel of 30 normal donors was procured from Golden West Biologicals, Inc.® (Temecula, CA). The first normal donor panel was intended to be age/gender matched to the CDK panel. Both the CKD panel and normal donor panel contained 20 males and 10 females. However the CKD panel consisted of mostly older patients (min=51, median=79, and max=89 years), while the first normal donor panel was poorly age- matched (min=50, median=56, and max=79 years; Control Panel 1). A closer age- matched panel of older normal donors was procured for testing. The median eGFR of the panel was 29 mL/min/1.73 m2m (range of 23-88 mL/min/1.73m2).

Table 2: CKD Panel Sourced from ProMedDx

[00104] In order to have a more closely age-matched panel of older normal donors, a second control serum panel of 30 normal donors containing 19 males and 11 females was procured from Bioreclamation (Westbury, NY; Control Panel 2). The second control panel had a median age of 74 years (range 55 to 87 years), and was therefore closer age-matched to the CKD panel than the first control panel. The age and gender distributions between the CKD and second control panel were not significantly different.

[00105] Example 3: CHF and Corresponding Age/Gender Matched Panel Analysis of ET-1 Panel of Normal Donors

[00106] To determine whether ET-1 correlates with age, plasma from a total of 300 normal donors were sourced from Golden West Biologicals, Inc. and Bioreclamation. The median age was 31, range 17 to 79. The 300 samples were evenly split between males and females. Figure 3 shows the results of analysis of this population for ET-1, which shows that ET-1 concentrations do not correlate with age (n=300, R=0.02, p- value=0.71).

[00107] Example 4: KIM-1 and ET-1 are elevated in humans diagnosed with Chronic Kidney Disease

[00108] KIM-1, ET-1, and IL-18 levels in human serum and plasma CKD samples were quantified using the methods described above. KIM-1, ET-1, and IL-18 levels were all elevated in the CKD panel compared to the Control Panel 1. The results in Table 3 demonstrate that the CKD patients had median elevations of 215 pg/mL, 2.9 pg/mL, and 199 pg/mL compared to KIM-1, ET-1, and IL-18, respectively of Control Panel 1. KIM-1, ET-1, and IL-18 levels are elevated in humans diagnosed with CKD, and these elevations were all statistically significant (p-value <0.0001, Wilcoxon Rank Sum Test).

Table 3

Median Differences Between CKD Panel and Control Panel 1

[00109] KIM-1 and ET-1 were both elevated in the CKD panel compared to the age/gender matched Control Panel 2. The results in Table 4 demonstrate that the CKD patients had median KIM-1 and ET-1 elevations of 159 pg/mL and 2.1 pg/mL, respectively, compared to Control Panel 2. These elevations were both significantly significant (p-value <0.0001, Wilcoxon Rank Sum Test). IL-18, a known kidney biomarker in urine, was not significantly elevated in human serum.

Table 4

Median Differences between CKD Panel Age/Gender Matched Control Panel (Control Panel 2)

[00110] The elevation in patients diagnosed with CKD is unlikely to be due to the age difference between the CKD panel and the Control Panel 2. Table 5 shows that biomarker correlations with age were not significant within each panel. The only exception is a negative correlation between IL- 18 and age in the control panel. The negative correlation is in opposition to the hypothesis that increased age is related to increased biomarker concentrations. Additionally, studies demonstrated that ET-1 concentrations were not correlated with age (Figure 3).

Table 5: Biomarker Correlations with Age

[0011 1] The odds ratio (OR) and AuROC were determined for each biomarker individually using logistical regression. To determine the odds ratio, the median value across all patients was used as the cut-point for each biomarker. Each patient's biomarker result was compared to the cut-point. If the patient result was less than the cut point then the patient was coded as 'Low Risk' and if the patient result was equal to or greater than the cut point then the patient was coded as 'High Risk'. The univariate odds ratio was determined by predicting the presence of CKD by the coded risk categories in a logistic regression model. For the AuROC's, the biomarkers were used as a continuous variable to predict the presence of CKD. The OR's and AuROC's for each unadjusted biomarker are shown in Tables 6 and 7. In Table 8 the OR for each individual biomarker adjusted for age is shown and Table 9 contains the OR for each individual biomarker adjusted for age and gender.

Table 6. Unadjusted Individual Biomarker Odds Ratios and AuROC's

[00112] The OR and AuROC for each unadjusted individual biomarker. All three biomarkers significantly predicted the presence of CKD using OR or AuROC analysis.

[00113] The high odds ratios for KIM-1 and ET-1 denotes that elevated levels of these biomarkers significantly increases the likelihood of having CKD. The high AuROCs for KIM-1 and ET-1 demonstrates that these biomarkers predict CKD. IL- 18 does not predict CKD.

Table 8. Individual Biomarker Odds Ratios and AuROCs, Adjusted for Age

[00114] The OR for each biomarker individually, adjusted for age. All three biomarkers significantly predicted the presence of CKD using an OR analysis. The upper bound of the 95% CI for IL-18 could not be determined in this model. Table 9. Adjusted Individual Biomarker Odds Ratios and AuROCs

[00115] The AuROC for each individually biomarker adjusted for age and the OR for each individually biomarker adjusted for age and gender. AuROC models cannot be adjusted for gender because gender is a categorical variable. Again, KIM-1 and ET-1 significantly predict the presence of CKD, while IL-18 not predictive of CKD in serum.

Table 10: Individual Biomarker Odds Ratios, Adjusted for Age and Gender

[00116] In Table 10, the OR for each biomarker individually, adjusted for age and gender. All three biomarkers significantly predicted the presence of CKD using an OR analysis. The upper bound of the 95% CI for IL-18 could not be determined in this model. AuROC cannot be estimated for models including gender because gender is a categorical variable.

[00117] A multi-marker odds ratio model along with a multi-marker AuROC model was built using logistic regression. Table 11 shows that when KIM-1, ET-1, and IL-18 are controlled for each other and gender, only KIM-1 and ET-1 biomarker serum levels can independently predict the presence of CKD. Figure 4 demonstrates that KIM-1, ET-1, and IL-18 can be used together in a AuROC model to improve the predictive power.

Table 11: Multi-marker Odds Ratio Model, Adjusted for Gender

[00118] In Table 1 1, all three biomarkers were adjusted for each other and gender. Only KIM-1 and ET-1 significantly predicted CKD independently. An age adjustment could not be included in the model due to incomplete data separation.

[00119] Multi-marker logistic regression models were built to determine the fully adjusted odds ratios AuROCs. Table 12 shows that when KIM-1, ET-1, and IL-18 are controlled for each other, age, and gender only KIM- 1 and ET- 1 independently predict the presence of CKD. Figure 6 demonstrates that KIM-1 and ET-1 can be used together in a AuROC model to improve the predictive power.

Table 12. Multi-marker Odds Ratio Model, Adjusted for Age and Gender

[00120] In Table 8, all three biomarkers were adjusted for each other, age, and gender. KIM-1 and ET-1 were independently predictive of CKD. When IL-18 was removed, similar results were obtained.

Example 5. KIM-1 elevation in human CKD and CHF patients

[00121] Finally, it was demonstrated that KIM-1 was elevated in plasma from human patients diagnosed with congestive heart failure (CHF). EDTA plasma from 29 (n=9, 10, and 10 from in NYHA classes I, II, and III respectively) human patients diagnosed with congestive heart failure (CHF) was procured from ProMedDx. A control plasma panel of 30 normal donors was also procured from ProMedDx. The normal donor panel was age/gender matched to the CHF panel. Both panels consisted of 17 females and 13 males. The median ages were 63.0 years (CHF panel) vs 63.5 years (age/gender matched panel).

[00122] Figure 5 shows that KIM-1 is elevated in the CHF panel compared to the age/gender matched panel and demonstrates that KIM-1, a known urine kidney disease biomarker, is elevated in plasma from patients diagnosed with congestive heart failure. All samples tested (CHF and age/gender normal donors) were quantifiable. A logistic regression model controlled for age and gender demonstrated that patients with elevated KIM-1 have a 3.6 (1.1 to 11.6 95% confidence interval) higher likelihood of having CHF. [00123] Compared to controls, plasma KIM-1 concentrations were significantly elevated in both CKD and CHF samples (Figure 10). In CKD the median

concentration was 264 pg/mL vs. 105 for controls (p<0.0001). For differentiating the CKD panel from controls, the adjusted odds ratio (OR, adjusted for age and sex) was 15.6 (95% CI 4.3-56.6; cutpoint based on median values). AUROC analysis provided an area under the curve of 0.89. KIM-1 values did not correlate with age (R = 0.151, p=0.43). KIM-1 values did not correlate with eGFR across the entire CKD discovery panel (R=0.02, p=0.92); however, analysis of a subset of the panel focusing on patients with only mild to moderate renal dysfunction with eGFR > 30 mL/min (n=9), revealed a strong inverse correlation between KIM- 1 concentration and eGFR (R= - 0.72, p = 0.03). This paradox may reflect the destruction of proximal tubules in late stage renal disease and hence their inability to release KIM-1 into circulation. In contrast, IL-18 was not elevated in CKD vs. controls, (432 pg/mL and 415 pg/mL, respectively). The IL-18 findings support the specificity of KIM-1 elevation with renal dysfunction, and the implications are discussed below. In CHF, the median KIM-1 concentration was 248 pg/mL vs. 166 pg/mL for controls (p=0.0274; FIG5). For differentiating CHF from controls the odds ratio was 3.6 (95% CI 1.1-1 1.6).

Example 6. Validation of KIM-1 elevation in human CHF patients

[00124] A cross-sectional study was also performed using EDTA plasma from a validation panel of 200 heart failure (HF) patients (CHF validation panel) distributed across ACC/AHA heart failure stages A-D (n= 26, 43, 66, and 65, respectively). This well characterized panel was a subset of the Vanderbilt University Heart Registry. The median age of this set was 55 years with 58% males. The preliminary reference range for the KIM-1 assay was determined with plasma samples from 120 healthy subjects (50% male, median age 38, age range 20-67 years; Bioreclamation,

Westbury, NY). The biological variability panel consisted of plasma collected each Wednesday between 9-1 1AM over 6 weeks from 25 volunteers (40% male, median age 30) self-reported to be free of kidney disease. The concentrations of plasma KIM-1 in 120 healthy subjects is depicted in Figure 8. KIM-1 was detectable in all subjects with median, 95th percentile and 99th percentile concentrations of 1 19 pg/mL, 292 pg/mL and 823 pg/mL, respectively. There was no difference in KIM-1 concentration between males and females (p = 0.304). [00125] KIM-1 was quantifiable in all 200 plasma of the CHF validation panel. The median KIM-1 concentration from the validation panel was 242 pg/mL compared to 264 pg/mL from the discovery panel. KIM-1 values were not correlated with CHF severity using either ACC/AHA or NYHFA criteria but were significantly inversely correlated with eGFR (spearman R = -.32, p<0.0001). In a subset analysis of patients with eGFR < 30 mL/min, KIM-1 did not correlate with eGFR (R= -0.03, p=0.91), confirming the preliminary finding with the KD discovery panel. In a fully adjusted linear regression model (adjusted for age, sex, HF classification, plasma BNP) the beta regression coefficient for every one unit Log transformed KIM-1 incremental increase, eGFR decreased by 1 1.9 mL/min (p= 0.0006).

[00126] The examples given above are merely illustrative and are not meant to be an exhaustive list of all possible embodiments, applications or modifications of the disclosure. Thus, various modifications and variations of the described methods and systems of the disclosure will be apparent to those skilled in the art without departing from the scope and spirit of the disclosure. Although the disclosure has been described in connection with specific embodiments, it should be understood that the disclosure as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the disclosure which are obvious to those skilled in molecular biology, immunology, chemistry, biochemistry or in the relevant fields are intended to be within the scope of the appended claims.

[00127] Any numerical values recited herein include all values from the lower value to the upper value in increments of one unit provided that there is a separation of at least two units between any lower value and any higher value. As an example, if it is stated that the concentration of a component or value of a process variable such as, for example, size, angle size, pressure, time and the like, is, for example, from 1 to 90, specifically from 20 to 80, more specifically from 30 to 70, it is intended that values such as 15 to 85, 22 to 68, 43 to 51, 30 to 32, etc. are expressly enumerated in this specification. For values which are less than one, one unit is considered to be 0.0001, 0.001, 0.01 or 0.1 as appropriate. These are only examples of what is specifically intended and all possible combinations of numerical values between the lowest value and the highest value enumerated are to be considered to be expressly stated in this application in a similar manner. [00128] Particular methods, devices, and materials are described, although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the disclosure. The disclosures of all references and publications cited herein are expressly incorporated by reference in their entireties to the same extent as if each were incorporated by reference individually.

Table 12. Protein Se uences of Select Biomarkers

Claims

WHAT IS CLAIMED IS:

1. A method for detecting Kidney Injury Molecule- 1 (KIM-1) protein in a sample of human blood, serum or plasma comprising contacting the sample with an antibody specific for KIM-1 and detecting the binding between the antibody and KIM-1 in the sample.

2. A method for diagnosing CKD in a subject comprising determining an amount of KIM-1 in a blood, serum or plasma sample from the subject, comparing the amount of KIM-1 in the sample to a threshold concentration representing a concentration of KIM-1 in a the blood, serum or plasma of a population of healthy patients, and determining that the subject has CKD when the concentration of a KIM-1 in the sample is above the threshold concentration.

3. The method of claim 3, wherein the amount of KIM-1 in the sample from the subject is determined by contacting the sample with an antibody specific for KIM-1 and detecting the binding between the antibody and KIM-1 in the sample.

4. The method of claim 3, wherein the threshold concentration represents an amount equivalent to a mean amount of KIM-1 in the population samples.

5. A method of determining the progression of CKD in a subject comprising:

(a) determining an amount of KIM-1 in a first blood, serum or plasma sample from a subject at a first time point;

(b) determining an amount of KIM-1 in a second blood, serum or plasma sample from a subject at a second time point;

(c) comparing the amount of KIM-1 in first sample to the amount of KIM-1 in the second sample; and

(d) determining that CKD has progressed in the patient by determining that the amount of KIM-1 in the second sample is greater than the amount of KIM-1 in the first sample.

6. The method of any of claims 2-3, wherein the determining the amount of KIM-1 comprises contacting the sample with an antibody specific for KIM-1 and determining the amount of specific binding between the antibody and KIM-1 in the sample.

7. A method for detecting CKD in a subject, comprising detecting the concentration of Kidney Injury Molecule- 1 (KIM-1) and Endothelin-1 (ET-1) in a blood, serum or plasma sample from the subject, creating a CKD score based upon the concentration of KIM-1 and ET-1; determining CKD in the subject when the score is greater than a predetermined CKD score.

8. The method of claim 7, wherein the score is determined using an area under receiver operator characteristic analysis.

9. The method of claim 7, wherein the score comprises an odds ratio.

10. The method of claim 8, wherein the odds ratio is determined by predicting the presence of CKD by the coded risk categories in a logistic regression model.

11. The method of claim 8, wherein the coded risk categories include age and gender.

12. The method of any of claims 7, wherein the determining the amount of KIM-1 comprises contacting the biological sample with an antibody specific for KIM-1 and determining the amount of specific binding between the antibody and KIM-1 in the sample.

13. A method of treating CKD comprising determining that a patient is suffering from CKD using a method according to any of claim 1-12, and administering a treatment to the patient in accordance with the guideline of the National Kidney Foundation Kidney Disease Outcomes Quality Initiative (NKF KDOQI) for CKD care.

14. A method for diagnosing congestive heart failure (CHF) in a subject comprising determining an amount of KIM-1 in a blood, plasma or serum sample from a subject a subject, and correlating the amount of KIM-1 in the sample to the presence of CHF in the subject.

15. The method of claim 14, further comprising comparing the amount of KIM- 1 in the sample to a threshold concentration representing the concentration in a non-CHF population, and determining that the subject has CHF when the concentration of a KIM-1 in the sample is above the threshold concentration.

16. A method of treating CHF comprising determining that a patient is suffering from CHF using a method according to any of claims 14-15, and administering a treatment to the patient comprising regulating the subjects diet, fluid intake, sodium intake and exercise, or treating the patient with one or more of the following compounds:

anticoagulants (e.g., Dalteparin (Fragmin), Danaparoid (Orgaran) Enoxaparin

(Lovenox) Heparin (various) Tinzaparin (Innohep) and Warfarin (Coumadin));

antiplatelet agents (e.g., Aspirin, Ticlopidine, Clopidogrel (Plavix®), and

Dipyridamole), Angiotensin-Converting Enzyme (ACE) Inhibitors (e.g„ Benazepril (Lotensin), Captopril (Capoten), Enalapril (Vasotec), Fosinopril (Monopril),

Lisinopril, (Prinivil, Zestril), Moexipril (Univasc), Perindopril (Aceon), Quinapril (Accupril), Ramipril (Altace), Trandolapril (Mavik); Angiotensin II Receptor Blockers (or inhibitors) (e.g., Candesartan (Atacand), Eprosartan (Teveten), Irbesartan

(Avapro), Losartan (Cozaar), Telmisartan (Micardis), and Valsartan (Diovan); Beta Blockers (e.g., Acebutolol (Sectral), Atenolol (Tenormin), Betaxolol (Kerlone), Bisoprolol/hydrochlorothiazide (Ziac), Bisoprolol (Zebeta), Carteolol (Cartrol), Metoprolol (Lopressor, Toprol XL), Nadolol (Corgard), Propranolol (Inderal), Sotalol (Betapace), Timolol (Blocadren); Calcium Channel Blockers (e.g., Amlodipine (Norvasc, Lotrel), Bepridil (Vascor), Diltiazem (Cardizem, Tiazac), Felodipine (Plendil), Nifedipine (Adalat, Procardia), Nimodipine , (Nimotop), Nisoldipine (Sular), Verapamil (Calan, Isoptin, Verelan); Diuretics (e.g., Amiloride (Midamor), Bumetanide (Bumex), Chlorothiazide (Diuril), Chlorthalidone (Hygroton), Furosemide (Lasix), Hydro-chlorothiazide (Esidrix, Hydrodiuril), Indapamide (Lozol) and

Spironolactone Aldactone); Vasodialators (e.g., Isosorbide dinitrate (Isordil),

Nesiritide (Natrecor), Hydralazine (Apresoline), Nitrates, Minoxidil); Digitalis Preparations (Digoxin and Digitoxin, e.g., Lanoxin); and Statins (e.g., statins, resins, nicotinic acid (niacin), gemfibrozil, clofibrate etc.).