method for predicting the likelihood of renal recovery in a patient

专利摘要:
KIDNEY INJURY BIOMARKERS. This invention is related to the field of prevention and treatment of kidney disease. Treatment of kidney disease may be appropriate, depending on the need for, or the expectation of, long-term dialysis. For example, the long-term prediction of dialysis treatment can be determined by monitoring urine biomarkers related to the development of chronic kidney disease. For example, a standardized time course of approximately fourteen days of measuring hyaluronium acid, death receptor 5, and / or transforming growth factor <225> 1 can be used to establish the risk of recovery versus non-recovery in patient who has suffered an acute kidney injury.
公开号:BR112013006935B1
申请号:R112013006935-0
申请日:2011-09-19
公开日:2021-02-23
发明作者:Kai Singbartl；John A. Kellum
申请人:University Of Pittsburgh - Of The Commonwealth System Of Higher Education；
IPC主号:

专利说明:

Government support statement
[001] This invention was carried out with government support under concession number 5R01DK07091003 issued by the National Institute of Diabetes and Digestive and Renal Diseases. The government has certain rights in the invention. Field of the Invention
[002] This invention is related to the field of prevention and treatment of kidney disease. Treatment of kidney disease may be appropriate depending on the need for, or the expectation of, long-term dialysis. For example, the long-term prediction of dialysis treatment can be determined by monitoring urine biomarkers related to the development of chronic kidney disease. For example, a standardized time course of about fourteen days of measuring hyaluronic acid, death receptor 5, and / or transforming growth factor β1 can be used to establish the risk of recovery versus non-recovery in a patient having suffered an acute kidney injury. Background
[003] Chronic kidney disease (CKD) is believed to be one of the biggest health and rapidly growing issues facing the developed world. In the United States alone, 26 million people have CKD and another 20 million are at increased risk of developing the disease. CKD leads to dialysis and heart disease in such a way that the total associated medical costs are in the billions of dollars. One of the main causes of CKD is acute kidney injury (AKI), which is also associated with a substantial increase in healthcare costs, especially if dialysis (or a related kidney support technique) is needed.
[004] Chronic kidney disease can develop as a result of several factors, but mainly, genetic predisposition and / or acute kidney injury. The degree of kidney damage is also associated with an incremental increase in long-term mortality. For example, deaths that occur within a year after hospital discharge can be as high as 64% for patients with AKI requiring severe dialysis. In addition, renal function / injury markers currently used, such as serum creatinine levels, are ineffective in discriminating long-term renal disease outcomes. Regardless of the initial factor, chronic kidney disease has a high proportion of patients requiring long-term dialysis (ie, for example, renal replacement therapy or RRT). This treatment is expensive, time-consuming and can result in adverse side effects, including, but not limited to, stenosis and / or thrombosis of blood vessels.
[005] Thus, the development of a biomarker that allows the early identification and subsequent stratification of patients with AKI and also that can predict the recovery of renal function, is a clinical instrument that is in great need in the technique. Summary
[006] This invention is related to the field of prevention and treatment of kidney disease. Treatment of kidney disease may be appropriate depending on the need for, or the expectation of, long-term dialysis. For example, the long-term prediction of dialysis treatment can be determined by monitoring urine biomarkers related to the development of chronic kidney disease. For example, a normalized time course of approximately fourteen days of measurement of hyaluronic acid, receptor 5 of death, and / or the transforming growth factor β1 can be used to establish the risk of recovery versus non-recovery in a patient having suffered a acute kidney injury.
[007] In one embodiment, the present invention contemplates methods and compositions for diagnosis, differential diagnosis, risk stratification, monitoring, classification and determination of treatment regimes in subjects who suffer or are at risk of suffering kidney injury, reduced kidney function and / or acute kidney failure by measuring one or more reindeer injury markers of the present invention.
[008] In one embodiment, the present invention contemplates a method comprising: a) providing: i) a patient who exhibits at least one symptom of an acute kidney injury, and ii) a sample of biological fluid obtained from the patient, wherein the sample comprises at least one renal biomarker; b) measuring a patient value comprising at least one renal biomarker value in the sample; and c) predicting the likelihood of recovery for the renal patient based on the patient's value. In one embodiment, renal recovery is expected to occur within at least sixty days from the start of the acute kidney injury. In one embodiment, the sample is obtained within at least fourteen days from the onset of renal failure. In one embodiment, the sample is obtained within one day from the start of the kidney injury. In one embodiment, the forecast comprises correlating the patient's value with a threshold value. In one embodiment, the prediction of the threshold value comprises a value of urinary hyaluronic acid. In one embodiment, the prediction threshold value for urinary hyaluronic acid is approximately 12 μg / mg creatinine. In one embodiment, the prediction threshold value for urinary hyaluronic acid comprises a value of the area under the receiver operating characteristic curve (AUC ROC) of at least 0.70. In one embodiment, the prediction threshold value comprises a hyaluronic acid value and at least a clinical indication value. In one embodiment, the prediction threshold value for the urinary hyaluronic acid value and the at least one clinical evidence value comprises a value for the area under the receiver operating characteristic curve (AUC ROC) of at least 0.75 . In one embodiment, the forecast threshold value comprises a urinary β1 transformation growth factor value. In one embodiment, the prediction threshold value for the urinary β1 transforming growth factor value is approximately 274 pg / mg creatinine. In one embodiment, the forecast threshold value for the transformation growth factor β1 value comprises a value of the area under the receiver operating characteristic curve (AUC ROC) of at least 0.70. In one embodiment, the forecast threshold value comprises the urinary β1 transformation growth factor value and at least one clinical evidence value. In one embodiment, the forecast threshold value for the urinary β1 transforming growth factor and at least one clinical evidence value comprises a value of the area under the receiver operating characteristic curve (AUC ROC) of at least 0, 74. In one embodiment, the prediction threshold value comprises a death receptor value of 5 in the urine. In one embodiment, the prediction threshold value for the death receptor 5 value in urine is about 2.7 ng / mg creatinine. In one embodiment, the prediction threshold value for the death receptor value 5 in the urine comprises a value of the area under the receiver operating characteristic curve (AUC ROC) of at least 0.70. In one embodiment, the prediction threshold value comprises the value of death receptor 5 in the urine and a value for clinical evidence. In one embodiment, the prediction threshold value for the urine death receptor value 5 and the at least one clinical evidence value comprises a value for the area under the receiver operating characteristic curve (AUC ROC) of at least 0.76. In one embodiment, the forecast threshold value comprises at least one clinical evidence value. In one modality, the clinical evidence value is selected from the group comprising age, SOFA score, Charlson's comorbidity index, or APACHE II score. In one embodiment, the at least one clinical evidence value comprises a value of the area under the receiver operating characteristic curve (AUC ROC) of at least 0.71. In one embodiment, the patient's value comprises at least two values of clinical evidence. In one embodiment, the at least two values of clinical evidence comprise a combined area value under the receiver operating characteristic curve (AUC ROC) of at least 0.74. In one modality, at least two clinical indicator values include age and Charlson's comorbidity index.
[009] In one embodiment, the present invention contemplates a method for assessing renal status that identifies a subject's risk stratification comprising: a) providing: i) a patient who exhibits at least one symptom of an acute kidney injury; ii) a sample of biological fluid obtained from the patient, wherein said sample comprises at least one renal biomarker, b) measuring a patient value comprising at least one renal biomarker value in the sample; and c) correlate the patient's value with a threshold biomarker value at which risk stratification is identified. In one modality, the correlation also identifies a renal biomarker value becoming positive. In one modality, the correlation also identifies a renal biomarker value becoming negative. In one embodiment, the patient's value comprises a value for urinary hyaluronic acid and at least one value for clinical evidence. In one embodiment, the patient's value comprises a urinary β1 transforming growth factor value. In one embodiment, the patient's value comprises a death recipient value 5. In one embodiment, the patient's value additionally comprises at least one clinical evidence value. In one embodiment, the sample is obtained within at least fourteen days from the start of the acute kidney injury. In one modality, the risk stratification comprises a modified risk criterion, Injury, Insufficiency, Loss (RIFLE) selected from the group comprising Stage I, Stage II, or Stage III. In one modality, stage I comprises a risk category. In one embodiment, stage II comprises a category of injury. In one embodiment, stage III comprises a category of impairment. In one embodiment, risk stratification comprises assigning a likelihood of renal recovery. In one embodiment, the likelihood of renal recovery comprises the biomarker value having an area under the receiver operating characteristic curve (AUC ROC) above the threshold value of about 0.70. In one embodiment, risk stratification comprises assigning a likelihood of renal non-recovery. In one embodiment, the likelihood of non-renal recovery comprises the value of biomarkers having an area under the receiver operating characteristic curve (AUC ROC) below the threshold value of about 0.70. In one embodiment, risk stratification comprises determining a risk for the patient's clinical outcomes. In one embodiment, the risk of clinical outcomes comprises an improvement in renal function. In one embodiment, the risk of clinical outcomes comprises reduced renal function. In one embodiment, reduced kidney function comprises kidney damage. In one embodiment, kidney damage is progressive. In one modality, the risk of clinical outcomes comprises a category of Loss. In one modality, the risk of clinical outcomes comprises a category of Final Stage Renal Failure. In one embodiment, the likelihood of risk of clinical outcome is correlated with the patient's value in the area under the receiver operating characteristic curve (AUC ROC). In one embodiment, the likelihood of a loss category increases within an AUC ROC value ranging from approximately 0.5 - 0.3. In one embodiment, the probability of loss category decreases above an AUC ROC value of 0.5. In one modality, the probability of the Final Stage Renal Insufficiency category increased below an AUC ROC value of 0.3. In one modality, the probability of the Final Stage Renal Insufficiency category decreases above an AUC ROC value of approximately 0.3. In one embodiment, risk stratification comprises determining a risk in question for future reduced kidney function. In one embodiment, the risk in question for future reduced kidney function increases below an AUC ROC value of 0.5. In one embodiment, the risk in question for future reduced kidney function decreases above an AUC ROC value of 0.5. In one embodiment, future reduced renal function is likely to occur within 180 days of the time in which the body fluid sample is obtained from the subject. In one embodiment, future reduced renal function is likely to occur within a selected time period of the group comprising 18 months, 120 days, 90 days, 60 days, 45 days, 30 days, 21 days, 14 days, 7 days , 5 days, 96 hours, 72 hours, 48 hours, 36 hours, 24 hours, 12 hours, or less. In one modality, reduced renal function occurs within 0 hours after the moment when the sample of body fluid is obtained from the subject, thus providing a diagnosis of a current condition.
[010] In one embodiment, the present invention contemplates a method comprising: a) providing a subject that comprises at least one pre-existing risk factor for kidney disease, and b) selecting the subject for a risk stratification based on the factor pre-existing risk of kidney disease. In one embodiment, the pre-existing risk factor comprises a renal biomarker. In one embodiment, the renal biomarker is selected from the group comprising urinary hyaluronic acid, transforming growth factor β1 urinary, receptor 5 of urinary death. In one modality, the risk stratification comprises a modified risk criterion, Injury, Insufficiency, Loss (RIFLE) selected from the group comprising Stage I, Stage II, or Stage III. In one modality, Stage I comprises a risk category. In one modality, Stage II comprises a category of injury. In one modality, Stage III comprises a category of insufficiency. In one modality, risk stratification comprises a category of insufficiency. In one modality, risk stratification comprises a category of Final Stage Kidney Disease. In one modality, the risk category comprises an AUC ROC value ranging from approximately 0.6-0.7. In one embodiment, the injury category comprises an AUC ROC value ranging from approximately 0.5 - 0.6. In one embodiment, the injury category comprises an AUC ROC value ranging from about 0.4 - 0.5. In one embodiment, the Loss category comprises an AUC ROC value ranging from about 0.30.4. In one modality, the category of Final Stage Kidney Disease comprises an AUC ROC value below 0.3. In one embodiment, kidney disease is selected from the group comprising prenatal diseases, intrinsic kidney disease, or post-renal acute kidney disease. In one embodiment, the subject still comprises at least one medical condition selected from the group that comprises or has undergone major vascular surgery, coronary artery bypass, cardiac surgery or otherwise, a subject who has pre-existing, pre-existing congestive heart failure -eclampsia, eclampsia, diabetes mellitus, hypertension, coronary artery disease, proteinuria, renal failure, glomerular filtration below the normal range, cirrhosis, serum creatinine above the normal range, or septicemia. In one embodiment, the subject also understands exposure to at least one compound selected from the group comprising non-steroidal anti-inflammatory drugs, cyclosporins, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin. In one embodiment, the subject is selected for risk stratification based on a diagnosis of an existing injury selected from the group comprising renal function, reduced renal function, or acute renal failure.
[011] In one embodiment, the present invention contemplates a method for diagnosing a kidney injury in a subject. In one embodiment, the method further comprises assessing a kidney condition to assess whether a subject has suffered from kidney function injury, reduced kidney function, or AKI. In these modalities, the measurement assay, for example, a measured concentration of HA, DR5, and / or TGFβi, is / are correlated with the occurrence or non-occurrence of a change in renal status. In one embodiment, a diagnostic method comprises diagnosing the occurrence or non-occurrence of an impaired renal function. In one embodiment, the measurement of the assay is / are correlated with the occurrence or non-occurrence of such an injury. In one embodiment, the diagnostic method comprises the diagnosis of the occurrence or non-occurrence of reduced renal function. In one embodiment, the measurement of the assay is / are correlated with the occurrence or non-occurrence of an injury that causes reduced renal function. In one embodiment, the diagnostic method comprises the diagnosis of the occurrence or non-occurrence of AKI. In one embodiment, the measurement of the assay is / are correlated with the occurrence or non-occurrence of an injury that causes AKI. In one embodiment, the diagnostic method comprises diagnosing a subject as in need of renal replacement therapy. In one embodiment, the trial measurement is / are correlated with the need for renal replacement therapy. In one embodiment, the diagnostic method comprises diagnosing a subject as in need of kidney transplantation. In one embodiment, the measurement of the assay is / are correlated with a need for kidney transplantation.
[012] In one embodiment, each of the measured concentration (s) can be compared with a threshold value. In one embodiment, the measured concentration (s) can each be compared to a threshold value, in which either a "positive kidney injury marker" or a "negative kidney injury marker" is identified.
[013] In one embodiment, the present invention contemplates a method that comprises monitoring a kidney state in a subject. In one modality, control correlates with the occurrence or non-occurrence of an alteration in the renal state in the subject. In one embodiment, the kidney condition is reduced. In one embodiment, the subject is suffering from a kidney injury. In one embodiment, the subject is suffering from acute renal failure. In one embodiment, the subject is at risk of impaired renal function due to the pre-existence of one or more known risk factors for pre-renal, intrinsic, or post-renal AKI. In one embodiment, the measured concentration (s) can be compared with a threshold value. In one embodiment, the measured concentration (s) can each be compared to a threshold value, in which either a "positive kidney injury marker" or a "negative kidney injury marker" is identified.
[014] In one embodiment, the present invention contemplates a method of classifying a kidney injury in a subject. In one embodiment, the method comprises the assessment of a kidney condition in the subject. In one embodiment, the kidney condition determines a kidney injury selected from the group comprising pre-renal, intrinsic kidney, or post-renal disease. In one embodiment, the kidney condition determines the kidney injury selected from the group comprising acute tubular injury, acute glomerulonephritis, acute tubulointerstitial nephritis, acute vascular nephropathy, or infiltrative disease. In one embodiment, the kidney condition assigns a probability that the subject will progress to a particular RIFLE stage. In one embodiment, the measurement test, for example, at a measured concentration of HA, DR5 and / or TGFβ1. In one embodiment, the measured concentration is / are correlated with a particular injury classification and / or injury subclassification. In one embodiment, the measured concentration can be compared to a threshold value. In one modality, the measured concentration is above the threshold, in which a particular classification has been assigned. In one embodiment, the measured concentration is below the threshold, where a different rating can be assigned.
[015] In one embodiment, the present invention contemplates a method which comprises a) providing: i) a patient, in which the patient exhibits an acute kidney injury; ii) at least two urine samples obtained from the patient, b) detect persistently high hyaluronic acid in the urine samples, c) predict whether the patient needs long-term dialysis. In one embodiment, samples are collected on the first and fourteenth day after starting replacement therapy for severe kidney injury. In one embodiment, the method additionally comprises the diagnosis of the patient with chronic kidney disease. In one embodiment, the diagnosis occurs at least sixty days after the kidney injury. In one embodiment, the method additionally comprises the patient's entry into a chronic kidney disease prevention program.
[016] In one embodiment, the present invention contemplates a method which comprises a) providing: i) a patient, in which the patient exhibits an acute kidney injury, in which the patient is at risk of developing chronic kidney disease; ii) at least two urine samples obtained from the patient; b) detect persistently high hyaluronic acid in urine samples; c) treating the patient to avoid chronic kidney disease. In one embodiment, treatment is started on Day 14 after kidney disease.
[017] In one embodiment, the present invention contemplates a method which comprises: a) providing: i) a patient who has suffered an acute kidney injury; ii) obtaining a plurality of levels of hyaluronic acid and urinary creatinine from the patient, where the levels are obtained over time; b) construct a time course of the urinary hyaluronic acid level, in which the time course is normalized in relation to the urinary creatinine levels; and c) predict the development of chronic kidney disease. In one embodiment, the long-term forecast includes renal replacement therapy (ie, for example, dialysis). Definitions
[018] As used herein, a "kidney function injury" is a measurable abrupt reduction (i.e., for example, within 14 days, preferably within 7 days, more preferably within 72 hours, and even more preferably, within 48 hours) in a measure of renal function. Such damage to renal function can be identified, for example, by a decrease in the glomerular filtration rate (GFR) or estimated GFR (eGFR), a reduction in urine production, an increase in serum creatinine, an increase in cystatin C of serum, a requirement for renal replacement therapy (ie dialysis, for example), etc.
[019] As used herein, an "improvement in kidney function" is a measurable abrupt increase (i.e., within 14 days, preferably within 7 days, more preferably within 72 hours, and yet more preferably, within 48 hours) in a measure of kidney function. Preferred methods for measuring and / or estimating GFR are described below.
[020] As used herein, "reduced renal function" is an abrupt reduction (that is, for example, within 14 days, preferably within 7 days, more preferably within 72 hours, and even more preferably within 48 hours) in renal function identified by an absolute increase in serum creatinine greater than or equal to 0.1 mg / dL (> 8.8 μmol / L), an increase in the percentage of serum creatinine greater than or equal to 20% ( 1.2 times from baseline), or a reduction in urine output (documented oliguria of less than 0.5 ml / kg per hour).
[021] As used herein, "acute renal failure" or "AKI" is an abrupt reduction (that is, for example, within 14 days, preferably within 7 days, more preferably within 72 hours, and even more preferably, within 48 hours) of renal function identified by an absolute increase in serum creatinine greater than or equal to 0.3 mg / dL (> 26.4 μmol / L), an increase in the percentage of serum creatinine of greater or equal to 50% (1.5 times from baseline), or a reduction in urine output (documented oliguria of less than 0.5 ml / kg per hour for at least 6 hours). This term is synonymous with "acute kidney injury" or "AKI".
[022] As used herein, the term "relate a signal to the presence or quantity" of an analyte refers to test measurement using a standard curve calculated with known concentrations of the analyte of interest. The person skilled in the art will understand that the signals obtained from an assay are often a direct consequence of the complexes formed between, for example, one or more antibodies and a target biomolecule (i.e., for example, an analyte) and / or polypeptides containing an epitope (s) to which, for example, antibodies bind. Although these assays can detect a full-length biomarker and the test result can be expressed as the concentration of a biomarker of interest, the test signal is actually a result of all of these "immunoreactive" polypeptides present in the sample.
[023] As the term is used in this document, an assay is "configured to detect" an analyte if an assay can generate a detectable signal indicates the presence or amount of a physiologically relevant concentration of the analyte. For example, an antibody epitope is generally on the order of 8 amino acids, such that an immunoassay can be configured to detect a marker of interest that will also detect polypeptides related to the marker sequence, as long as the polypeptides contain the epitope (s) required to bind to the antibody or antibodies used in the assay.
[024] The "related marker" as used herein in relation to a biomarker as one of the renal biomarkers (i.e., for example, a kidney injury marker) described herein. A related marker can also refer to one or more fragments, variants, etc., of a particular marker or its original biosynthetic which can be detected as a substitute for the marker itself or as independent biomarkers. The term also refers to one or more polypeptides present in a biological sample, which are derived from the precursor of biomarkers complexed with additional species, such as binding proteins, receptors, heparin, lipids, sugars, etc.
[025] The term "subject" or "patient", as used herein, refers to a human or non-human organism. Thus, the methods and compositions described herein are equally applicable to human and veterinary disease. In addition, although a subject or patient is preferably a living organism, the invention described in this document can be used in postmortem analysis, as well. Preferred subjects are humans or patients, which as used herein refer to living humans who are receiving medical treatment for a disease or condition.
[026] The term "analyte", as used herein, refers to any compound or molecule measured. Preferably, an analyte is measured in a sample (i.e., for example, a sample of body fluid). A sample can be obtained from a subject or patient, or it can be obtained from biological materials intended to be provided to the subject or the patient. For example, a sample can be obtained from a kidney being evaluated for eventual transplantation in a subject, such that an analyte measurement can be used to assess the kidney for pre-existing damage.
[027] The term "body fluid sample", as used in this document, refers to any body fluid sample obtained for the purpose of diagnosis, prognosis, classification or evaluation of a subject of interest, such as a patient or blood donor. transplant. In certain embodiments, such a sample can be obtained for the purpose of determining the outcome of an ongoing medical condition or the effect of a treatment regime for a medical condition. Preferred body fluid samples include, but are not limited to, blood, serum, plasma, cerebrospinal fluid, urine, saliva, sputum, or pleural effusions. In addition, certain samples of body fluids can be more easily analyzed after a fractionation or purification process, for example, separation of whole blood into components of serum or plasma.
[028] The term "diagnosis" as used in this document refers to methods by which trained medical personnel can estimate and / or determine the likelihood (that is, for example, a possibility) of whether or not a patient is suffering from a particular disease or condition. In the case of the present invention, "diagnosis" includes correlating the results of an assay (i.e., for example, an immunoassay) to a renal biomarker of the present invention, optionally in conjunction with other clinical evidence, to determine the occurrence or non-occurrence of an acute kidney injury or acute kidney failure for a subject or patient from which a sample was obtained and analyzed. The fact that the diagnosis is "determined" does not mean that the diagnosis is 100% accurate. Thus, for example, a level of biomarkers measured below a predetermined diagnostic threshold may indicate a greater probability of the occurrence of a disease in the subject in relation to a level of biomarkers measured above the predetermined diagnostic threshold may indicate a lesser possibility for the occurrence of the same disease.
[029] The term "prognosis", as used in this document, refers to a probability (ie, for example, a possibility) that a specific clinical outcome will occur. For example, a level or a change in the level of a prognostic indicator, which in turn is associated with an increased likelihood of morbidity (for example, worsening kidney function, future AKI, or death) is referred to as "indicative of an increased likelihood "of an adverse event in a patient.
[030] The term "RIFLE" criterion, as used herein, refers to any quantitative clinical assessment of renal status used to establish the renal classification of Risk, Injury, Failure, Loss, & Final Stage Kidney Disease based on a uniform definition of acute kidney injury (AKI). Kellum, Crit. Care Med. 36: S14145 (2008); and Ricci et al, Kidney Int. 73, 538546 (2008), each of which is incorporated herein by reference in its entirety.
[031] The term, "modified RIFLE criterion", as used in this document, provides alternative classifications to stratify AKI patients, and may include, Stage I, Stage II, and / or Stage III. Mehta et al., Crit. Care 11: R31 (2007), incorporated herein by reference in its entirety.
[032] The term "Stage I", as used herein, refers to a risk stratification comprising a RIFLE risk category, characterized by an increase in serum creatinine greater than or equal to 0.3 mg / dL (> 26.4 μmol / L) and / or an increase of greater than or equal to 150% (1.5 times) from baseline. Alternatively, the category can be defined by a urine output of less than 0.5 ml / kg per hour for more than 6 hours.
[033] The term, "Stage II", as used herein, refers to risk stratification comprising a category of RIFLE injury, characterized by an increase in serum creatinine of more than 200% (> 2 times ) from baseline. Alternatively, the category can be defined by a urine output of less than 0.5 mL / kg per hour for more than 12 hours.
[034] The term, "Stage III", as used in this document, refers to a stratification comprising a category of RIFLE insufficiency, characterized by an increase in serum creatinine of more than 300% (> 3-fold) from baseline and / or serum creatinine> 354 μmol / L accompanied by an acute increase of at least 44 μmol / L. Alternatively, the category can be defined by a urine output of less than 0.3 ml / kg per hour for 24 hours or anuria for 12 hours.
[035] The term "risk category", as used in this document, refers to an RIFLE classification where, in terms of serum creatinine, it means any increase of at least 1.5 times over the baseline. base, or urine production of <0.5 ml / kg body weight / h for approximately 6 hours.
[036] The term "injury category", as used in this document, includes, or refers to, an RIFLE classification where, in terms of serum creatinine, it means any increase of at least 2.0 times in relation to the baseline. base or urine output <0.5 ml / kg / h for 12 h.
[037] The term "failure category", as used herein, includes, or refers to, an RIFLE classification where, in terms of serum creatinine, it means any increase of at least 3.0 times over at baseline or a urinary creatinine> 355 μmol / L (with an increase of> 44) or urine output below 0.3 ml / kg / h for 24 h, or anuria for at least 12 hours.
[038] The term "category of loss", as used in this document, refers to a risk of clinical outcomes and / or an RIFLE classification in which the risk of clinical outcomes is characterized by a constant need for the therapy of renal replacement for more than four weeks.
[039] The term "Final Stage Kidney Disease category" or "ESRD category" as used herein, refers to a risk of clinical outcomes and / or an RIFLE classification characterized by a need for dialysis during more than 3 months.
[040] The term "risk of clinical outcome", as used in this document, refers to a medical prognosis aimed at renal recovery or non-renal recovery.
[041] The term "renal biomarker", as used herein, refers to any biological compound related to the progressive development of chronic kidney disease. In particular, a renal biomarker can be a marker of kidney damage. For example, a renal biomarker may comprise hyaluronic acid, the death receptor 5, transforming growth factor β1, or any of its metabolites and / or derivatives.
[042] The term "positive biomarker" as used in this document, refers to any biomarker that is determined to be elevated in subjects who suffer from a disease or condition, compared to subjects who do not suffer from the disease or condition.
[043] The term "negative biomarker" as used in this document, refers to any biomarker that is determined to be reduced in subjects who suffer from a disease or condition, compared to subjects who do not suffer from disease or condition.
[044] The term "renal biomarker value becoming positive", as used in this document, refers to any increase in the possibility (ie, increased likelihood) of suffering a future injury to the assigned kidney function to a subject, when the measured biomarker concentration is above a specified threshold value, in relation to an assigned possibility when the measured biomarker concentration is below the specified threshold value. Alternatively, when the measured biomarker concentration is below a specified threshold value, an increase in the possibility of a non-occurrence of an injury to renal function can be attributed to the subject in relation to the possibility attributed when the measured biomarker concentration is above the specified threshold value. Alternatively, when the measured biomarker concentration is below the threshold value, an improvement in renal function can be attributed to the subject. A positive kidney injury marker may include, but is not limited to, an increased chance of one or more of the following: acute kidney failure, progression to the AKI worsening stage, mortality, a requirement for renal replacement therapy , a requirement for the removal of kidney toxins, end-stage kidney disease, heart failure, stroke, myocardial infarction, progression to chronic kidney disease, etc.
[045] The term "renal biomarker value becoming negative", as used in this document, refers to any increase in the possibility (i.e., for example, a greater likelihood) of suffering a future injury to the renal function attributed to the subject , when the measured biomarker concentration is below a specified threshold value, in relation to an assigned possibility when the measured biomarker concentration is above the threshold value. Alternatively, when the concentration of measured biomarkers is above the threshold value, a greater possibility of a non-occurrence of an injury to renal function can be attributed to the subject in relation to the possibility attributed when the measured biomarker concentration is below the value of threshold. Alternatively, when the concentration of measured biomarkers is above the threshold value, an improvement in renal function can be attributed to the subject. A negative kidney injury marker may include, but is not limited to, an increased chance of one or more of the following: acute kidney failure, progression to the AKI worsening stage, mortality, a need for renal replacement therapy , a need for the removal of kidney toxins, end-stage kidney disease, heart failure, stroke, myocardial infarction, progression to chronic kidney disease, etc.
[046] The term "pre-existing" and "pre-existence", as used herein, means any risk factor (ie, for example, a renal biomarker) existing at the time a sample of body fluid is obtained from from the subject.
[047] The term "forecast" as used in this document, refers to a method of forming a prognosis and / or a stratification risk assignment, in which a medically trained person analyzes the information of biomarkers and, optionally, with relevant clinical evidence and / or demographic information.
[048] The term "acute kidney disease / failure / injury", as used in this document, refers to any progressive worsening of kidney function, over hours to days, which results in the retention of nitrogenous waste (such as urea) and creatinine in the blood. The retention of these substances can also be referred to as, azotemia. In: Current Medical Diagnosis & Treatment 2008, 47 Ed., McGraw Hill, New York, pages 785815, hereby incorporated by reference in its entirety.
[049] The term "disease / failure / chronic injury", as used in this document, refers to a medical condition in which exemplary symptoms may include, but are not limited to, hyperphosphatemia (ie, for example,> 4.6 mg / dL) or low glomerular filtration rates (ie, <90 ml / minute for 1.73 m2 of body surface). However, many patients with CKD may have normal serum phosphate levels in conjunction with a sustained reduction in the glomerular filtration rate for 3 months or more, or a normal glomerular filtration rate, in conjunction with the sustained evidence of an abnormality structural damage of the kidney. In some cases, patients diagnosed with chronic kidney disease are placed on hemodialysis to maintain normal blood homeostasis (ie, for example, urea or phosphate levels). Alternatively, "chronic kidney disease" refers to a medical condition in which a patient has either i) a sustained reduction in GFR <60 ml / min per 1.73 m2 of body surface for 3 months or more; or ii) a structure or functional abnormality of renal function, for 3 months or more, even in the absence of a reduced glomerular filtration rate. Structural or anatomical abnormalities of the kidney could be defined as, but not limited to, microalbuminuria or proteinuria or persistent hematuria or the presence of renal cysts. Chronic kidney failure (chronic kidney disease) can also result from an abnormal loss of kidney function over months to years. In: Current Medical Diagnosis & Treatment 2008, 47 Ed., McGraw Hill, New York, pages 785815, hereby incorporated by reference in its entirety.
[050] The term "about" as used herein in the context of any of any test measurements refers to + / 5% of a given measurement.
[051] The term "asymptomatic", as used in this document, refers to a patient and / or subject who does not have a kidney disease and / or injury, where symptoms of a kidney disease and / or injury can include, but are not limited to, a reduced glomerular filtration rate (that is, for example, between about 7089 ml / min per 1.73 m2 of body surface) of less than three months.
[052] The term "glomerular filtration rate", as used herein, refers to any measure capable of determining renal function. In general, normal glomerular filtration varies between about 120-90 ml / minute per 1.73 m2 of body surface. Impaired renal function is assumed when glomerular filtration rates are less than 90 ml / minute per 1.73 m2 of body surface. Renal failure is likely when glomerular filtration rates are below approximately 30 ml / minute for 1.73 m2 of body surface. Dialysis is often initiated when the glomerular filtration rates are below approximately 15 ml / minute for 1.73 m2 of body surface.
[053] "Renal insufficiency", as used herein, refers to any acute, sudden and / or chronic loss of the kidneys' ability to eliminate waste and concentrate urine without loss of electrolytes.
[054] The term "biological sample", as used herein, refers to any substance derived from a living organism. For example, a sample can be derived from blood, such as a urine sample, a serum sample, a plasma sample, and or a whole blood sample. Alternatively, a sample can be derived from tissue collected, for example, by a biopsy. A tissue sample can comprise, for example, kidney tissue, vascular tissue and / or heart tissue. The biological sample may also comprise body fluids, including, but not limited to, urine, sweat or saliva.
[055] The "reagent", as used in this document, refers to any substance used to produce a chemical reaction, in order to detect, measure, produce, etc., other substances.
[056] The term "antibody" as used herein refers to any peptide or polypeptide derived from, modeled after, or substantially encoded by, an immunoglobulin gene or immunoglobulin genes, or fragments thereof, capable of binding specifically to an antigen or epitope. See, for example, In: Fundamental Immunology, 3rd edition, W.E. Paul, ed., Raven Press, NY (1993); Wilson et al, J. Immunol. Methods 175: 267273 (1994), and Yarmush et al., J. Biochem. Biophys. Methods 25: 8597 (1992). The term antibody includes, but is not limited to, antigen-binding portions, that is, "antigen-binding sites", exemplified by fragments, subsequences, and / or complementarity determining regions (CDRs)), which retain the ability to bind to the antigen, including, but not limited to: (i) a Fab fragment, a monovalent fragment comprising VL, VH, CL and CH1 domains, (ii) an F (ab ') 2 fragment, a fragment bivalent which comprises two Fab fragments linked by a disulfide bridge in the hinge region, (iii) an Fd fragment comprising the VH and CH1 domains, (iv) an Fv fragment comprising the VL and VH domains of a single arm of an antibody, (v) a dAb fragment (Ward et al., Nature 341: 544-546 (1989)), which comprises a VH domain, or (vi) an isolated complementarity determining region (CDR). Single chain antibodies are also included by reference in the term "antibody".
[057] The "epitope", as used herein, refers to any antigenic determinant capable of specifically binding to an antibody. Epitopes typically exhibit chemically active surface molecules such as amino acid or sugar side chains and generally have specific three-dimensional structural characteristics, as well as specific charge characteristics. Conformational and non-conformational epitopes can be distinguished by the fact that the connection to the anterior, but not so that the posterior can be lost, in the presence of denaturing solvents.
[058] The term "correlation", as used herein, in reference to the use of biological markers, refers to the comparison of the presence and / or quantity of any biomarker (s) in a patient with their presence and / or number of people known to suffer from, or known to be at risk for, a particular condition, or in people known to be free from a particular condition. This often takes the form of comparing a test result in the form of a concentration of biomarkers to a predetermined threshold selected to be indicative of the occurrence or non-occurrence of a disease or the possibility of some future result. Brief Description of the Figures
[059] Figure 1 presents exemplary data showing the excretion of hyaluronic acid from urine normalized to urinary creatinine in patients with acute renal failure. Samples were collected between one and fourteen days after starting replacement therapy for severe acute kidney injury (ie, D1, D7 and D14). The data presented represents data on patients who were recovered or not recovered within 28 days after kidney injury (R28 and NR28, respectively).
[060] Figure 2 shows exemplary data showing absolute differences between the urine samples collected in D1, D7 and / or D14 from patients who recover or do not recover within 28 days after kidney injury (R28 and NR28, respectively ).
[061] Figure 3 presents data showing examples of absolute differences between urine samples collected in D1, D7 and / or D14 from patients who recover or do not recover 60 days after kidney injury (R60 and NR60 , respectively).
[062] Figure 4 presents data showing examples of relative differences between urine samples collected in D1, D7 and / or D14 from patients who recover or do not recover within 28 days after kidney injury (R28 and NR28 , respectively).
[063] Figure 5 shows data showing examples of relative differences between urine samples collected in D1, D7 and / or D14 from patients who recover or do not recover within 60 days after kidney injury (R60 and NR60 , respectively).
[064] Figure 6 presents the exemplary data showing the high sensitivity of predicting dialysis in patients 60 days after kidney injury, when the excretion of AH was persistently high between D1 and D14.
[065] Figure 7 presents exemplary data showing data on the TGF-β1 / creatinine ratio during the first 21 days after the onset of an AKI. The reasons were significantly higher in patients who did not recover on either Day 7 or Day 14. Detailed Description of the Invention
[066] This invention is related to the field of prevention and treatment of kidney disease. The treatment of kidney disease may be appropriate depending on the need for, or the expectation of, long-term dialysis. For example, the long-term prediction of dialysis treatment can be determined by monitoring urine biomarkers related to the development of chronic kidney disease. For example, a standardized time course of about 14 days of measurement of hyaluronic acid, death receptor 5, and / or transforming growth factor β1 can be used to establish the risk of recovery versus non-recovery in the patient having suffered from an acute kidney injury.
[067] It has been highly desired in the art that if research efforts for the treatment of AKI and CKD prevention can be adequate according to the long-term prognosis, a more effective clinical strategy could be implemented. The use of such a method for patients predicted to not recover from kidney function may be the selectively provided aggressive treatment. On the other hand, patients with a favorable prognosis would be spared from more aggressive interventions and their potential adverse effects.
[068] Various modalities presented here have solved several problems in the technique that have hitherto hindered the doctors' ability to accurately predict which patients will recover, and which patients will not recover from kidney disease and / or failure. I. Kidney disease and / or injury
[069] The kidney is responsible for the excretion of water and solutes from the body. Its functions include maintaining acid-base balance, regulating electrolyte concentrations, controlling blood volume, and regulating blood pressure. As such, loss of kidney function due to injury and / or kidney disease results in morbidity and mortality. A detailed discussion of kidney injuries is provided in Harrison's Principies of Internai Medicine, 17th ed., McGraw Hill, New York, pages 1741-1830, which is incorporated herein by reference in its entirety. The kidneys are located on the flank (the back of the upper abdomen on either side of the spine). They are deep inside the abdomen, and are protected by the spine, lower rib cage, and strong muscles in the back. This location protects the kidneys from many external forces. They are well cushioned for a reason - the kidneys are highly vascular organs, which means that they have a large blood supply. If an injury occurs, it can result in severe bleeding.
[070] The kidneys can be damaged by damage to the blood vessels that supply or drain them. This can be in the form of an aneurysm, arteriovenous fistula, arterial obstruction, or renal vein thrombosis. The extent of bleeding depends on the location and degree of the injury. The kidneys can also bleed profusely if they are damaged centrally (inside) this is a fatal injury. Fortunately, most kidney injuries caused by blunt trauma occur peripherally, only causing bruising of the kidney (usually a self-limiting process).
[071] People with undiagnosed kidney diseases - such as angiomyolipoma (benign tumor), obstruction of the pyelocalyal junction (congenital or acquired UPJ obstruction), and other diseases - are more susceptible to kidney damage and are more likely to have serious complications, if they occur. Other causes of kidney damage and bleeding are medical procedures. Kidney biopsies, nephrostomy tube placement, or other surgery can cause an abnormal connection between an artery and a vein (arteriovenous fistula). This is usually a self-limiting problem, but close observation is usually necessary. Kidney damage can also disrupt the urinary tract, causing urine to leak out of the kidney.
[072] Each kidney filters about 1700 liters of blood per day and concentrates fluids and waste products in about 1 liter of urine per day. Because of this, the kidneys receive more exposure to toxic substances in the body than any other organ. Therefore, they are highly susceptible to injury from toxic substances. Analgesic nephropathy is one of the most common types of toxic damage to the kidney. Exposure to lead, cleaning products, solvents, fuels or other nephrotoxic chemicals (those that can be toxic to the kidneys) can damage the kidneys. Excessive formation of body products, such as uric acid residues (which can occur with gout or with bone marrow treatment, lymph nodes, or other disorders) can also damage the kidneys.
[073] Inflammation (irritation with swelling and the presence of additional immune cells) caused by immune responses to drugs, infection or other disorders can also damage kidney structures, usually causing various types of glomerulonephritis or acute tubular necrosis (tissue death) . Autoimmune disorders can also damage the kidneys. Kidney damage can result in short-term damage with minimal or no symptoms. Alternatively, it can be fatal because of bleeding and associated shock, or it can result in acute kidney failure or chronic kidney failure.
[074] Ureteral injuries (injuries to the tubes that carry urine from the kidneys to the bladder) can also be caused by trauma (blunt or penetrating), complications from medical procedures, and other diseases in the retroperitoneum, such as retroperitoneal fibrosis (RPF ), retroperitoneal sarcomas, or cancers positive for metastatic lymph nodes. Medical therapies (such as OB / GYN surgeries, chemotherapy or previous radiation and abdominopelvic surgeries) increase the risk of ureteral injuries. A. Acute Renal Failure
[075] Acute (sudden) kidney failure is the sudden loss of the kidneys' ability to eliminate waste and concentrate urine, without losing electrolytes. There are many causes of kidney damage, including, but not limited to, decreased blood flow, which can occur with extremely low blood pressure caused by trauma, surgery, serious illness, septic shock, bleeding, burns or dehydration, necrosis acute tubular (ATN), infections that directly damage the kidney, such as acute pyelonephritis or septicemia, urinary tract obstruction (obstructive uropathies), autoimmune kidney disease, such as interstitial nephritis or acute nephrotic syndrome, disorders that cause clotting in the inside of the kidney's thin blood vessels, idiopathic thrombocytopenic thrombotic purpura (ITTP), transfusion reaction, malignant hypertension, scleroderma, hemolyticouremic syndrome, delivery disorders, such as abrupt bleeding from the placenta or placenta previa.
[076] Symptoms of acute renal failure include, but are not limited to, decreased urine output (oliguria), urine stops (anuria), excessive urination at night, swelling of the ankle, foot and leg, generalized swelling, fluid retention, decreased sensitivity, especially in the hands and feet, decreased appetite, metallic taste in the mouth, persistent hiccups, changes in mental state or mood, agitation, drowsiness, lethargy, delirium or confusion, coma, mood swings, difficulty paying attention, hallucinations, sluggishness, laziness, movements, convulsions, hand tremors (agitation), nausea or vomiting, can last for days, bruising easily, prolonged bleeding, nosebleeds, bloody stools, flank pain (between the ribs and hips), fatigue, bad breath, or high blood pressure.
[077] Acute kidney failure (AKI) can also be referred to as an acute kidney injury (AKI) and can be characterized by an abrupt reduction (ie, for example, typically detected in about 48 hours to 1 week) in the rate glomerular filtration system (GFR). This loss of filtration capacity results in the retention of nitrogen (urea and creatinine) and non-nitrogenous waste products that are normally excreted by the kidneys, by a reduction in urine production, or both. AKI is reported to complicate about 5% of hospital admissions, 415% of cardiopulmonary bypass surgeries, and up to 30% of intensive care admissions. AKI can be classified as a pre-renal, intrinsic renal, or post-renal cause. Intrinsic kidney disease can be further divided into glomerular, tubular, interstitial and vascular abnormalities. The main causes of AKI are described in association with their respective risk factors and are summarized below. See, Table 1; In: Merck Manual, 17th ed, Chapter 222, which is incorporated by reference in its entirety. Table 1. Representative Risk Factors for Acute Renal Failure


[078] In the case of ischemic AKI, the course of the disease can be divided into four stages. During an initiation stage that lasts from hours to days, reduced kidney perfusion is progressing to injury. Glomerular ultrafiltration reduces, the flow of the filtrate is reduced due to debris inside the tubules, and again the leakage of the filtrate through the injured epithelium occurs. Kidney damage can be mediated during this stage of kidney reperfusion. Initiation is followed by an extension phase, which is characterized by ischemic injury and continuous inflammation and may involve endothelial damage and vascular congestion. During the maintenance phase, the duration of 1 to 2 weeks, kidney cell damage occurs, and glomerular filtration and urine production reaches a minimum. The recovery phase can continue when the renal epithelium is repaired and the GFR gradually recovers. Despite this, the survival rate of AKI patients can be as low as about 60%.
[079] Acute kidney damage caused by radiocontrast agents (also called contrast media) and other nephrotoxins such as antibiotics, including cyclosporine, aminoglycosides and anticancer drugs such as cisplatin, manifest over a period of days around one week. Contrast-induced nephropathy (CIN, which is AKI caused by radiocontrast agents) is believed to be caused by intrarenal vasoconstriction (leading to ischemic injury) and by the generation of reactive oxygen species, which are directly toxic to renal tubular epithelial cells . CIN classically presents itself as an acute elevation (beginning within 2448h), but reversible (peak 3-5 days, resolution within 1 week) that elevates blood urea nitrogen and serum creatinine.
[080] A commonly reported criterion for defining and detecting AKI is an abrupt elevation (usually about 2-7 days or within a hospital stay) of serum creatinine. Although the use of serum creatinine elevation to define and detect AKI is well established, the magnitude of serum creatinine elevation and the length of time it is measured to define AKI varies considerably between publications. Traditionally, relatively large increases in serum creatinine, such as 100%, 200%, an increase of at least 100% to a value greater than 2 mg / dL and other definitions have been used to define AKI. However, the recent trend has been to use lower elevations in serum creatinine to define AKI.
[081] For example, the relationships between elevated serum creatinine levels and AKI have been reported to be associated with health risks. Praught et al, Curr Opin Nephrol Hypertens 14: 265270 (2005) ;. and Chertow et al., J Am Soc Nephrol 16: 33653370 (2005); (both references are hereby incorporated by reference in their entirety). As described in these publications, acute worsening renal function (AKI) and increased risk of death and other negative results are now known to be associated with much smaller increases in serum creatinine. These increases in creatinine can be determined as a relative value (percentage) or a nominal value. Relative increases in serum creatinine as small as 20% relative to the pre-injury value have been reported to indicate acute worsening renal function (AKI) and increased health risk, but the value most commonly reported to define AKI and the increased health risk is a relative increase of at least 25%. Nominal increases as small as 0.3 mg / dL, 0.2 mg / dL or up to 0.1 mg / dL have been reported to indicate worsening kidney function and an increased risk of death. Various time periods for serum creatinine to rise to these threshold values have been used for the definition of AKI, for example, varying from 2 Days, 3 Days, 7 Days, or for a variable period defined as the time in which the patient is in the hospital or intensive care unit. These studies indicate that there is no specific threshold for serum creatinine increase (or time period for elevation) to worsen kidney function or AKI, but rather a continuous increase in the risk of increasing the magnitude of serum creatinine elevation.
[082] Another study correlated with serum creatinine levels, with post-surgical mortality rates. After cardiac surgery, patients with a slight drop in serum creatinine (ie, between about -0.1 to -0.3 mg / dL) had the lowest mortality rate, in which patients had a higher mortality rate associated with large falls in serum creatinine (ie, greater than or equal to -0.4 mg / dL), or an increase in serum creatinine. Lassnigg et al., J Am Soc Nephrol 15: 1597-1605 (2004), incorporated herein by reference in its entirety. These results suggest that the still very subtle changes in kidney function detected by small changes in creatinine within 48 hours of surgery, may be predictive of a patient outcome.
[083] A unified classification system that uses serum creatinine to define AKI in clinical trials and in clinical practice has been proposed to stratify patients with AKI. Bellomo et al, Crit Care 8 (4): R204-212 (2004), which is incorporated herein by reference in its entirety. For example, a 25% increase in serum creatinine can define contrast nephropathy. McCollough et al, Rev Med Cardiovasc. 7 (4): 177 - 197 (2006), hereby incorporated by reference in its entirety. Although several groups have proposed slightly different criteria for the use of serum creatinine for AKI detection, there is a consensus that small changes in serum creatinine, such as 0.3 mg / dL (ie, for example, approximately 25%) they are sufficient to detect AKI that characterizes worsening renal function and that the magnitude of the change in serum creatinine may be an indicator of AKI severity and risk of mortality.
[084] Although serial measurement of serum creatinine over a period of days is an acceptable method of detecting and diagnosing patients with AKI, serum creatinine is generally considered to have several limitations in the diagnosis, evaluation and monitoring of patients with AKI. The time period for serum creatinine to rise from about 0.3 mg / dL (25%) is considered to be the diagnosis for AKI and can be 48 hours or more, depending on the definition used.
[085] Since cell damage in AKI can occur over a period of hours, elevations in serum creatinine detected at 48 hours or longer can be an indicator of injury delay, and depend on serum creatinine and may thus delaying the diagnosis of AKI. In addition, serum creatinine is not a good indicator of accurate kidney status and needs treatment during the more acute phases of AKI, when kidney function is changing rapidly. Until defined by some modalities of the present invention, there were no methods for determining whether some patients with AKI would recover completely, or whether some would need dialysis (either in the short term or in the long term), or whether some would have other harmful consequences, including , but not limited to, death, adverse cardiac events or chronic kidney disease. Because serum creatinine is a marker of filtration rate, it makes no difference between the causes of AKI (pre-renal, intrinsic renal, post-renal obstruction, atheroembolic, etc.) or the category or location of the lesion in intrinsic kidney disease ( for example, tubular, glomerular or interstitial). The production of urine is likewise limited.
[086] These limitations underline the need for better methods to detect and evaluate AKI, particularly in the early and subclinical stages, but also in the later stages when kidney recovery and repair can occur. In addition, there is a need for better identification of patients who are at risk of having an AKI. B. Chronic Kidney Failure
[087] Unlike acute kidney failure, chronic kidney failure worsens slowly. Most of the time, it results from a disease that causes the gradual loss of kidney function. It can range from mild dysfunction to severe kidney failure. Chronic kidney failure can lead to end-stage kidney disease (ESRD).
[088] Chronic kidney failure usually occurs over a number of years in which the kidney's internal structures are slowly damaged. In the early stages, there may be no symptoms. In fact, progression can be so slow that symptoms do not occur until kidney function is less than a tenth of normal.
[089] Chronic kidney failure and ESRD, affect more than 2 out of 1,000 people in the United States. Diabetes and high blood pressure are the two most common causes and represent the majority of cases. Other major causes include, but are not limited to, Alport's syndrome, analgesic nephropathy, glomerulonephritis of any kind (one of the most common causes), kidney stones and infection, obstructive uropathy, polycystic kidney disease, or reflux nephropathy. Chronic kidney failure results in an accumulation of fluids and waste products in the body, leading to an accumulation of nitrogen waste products in the blood (azotemia) and general health problems. Most of the body's systems are affected by chronic kidney failure.
[090] Initial symptoms may include, but are not limited to, fatigue, frequent hiccups, general malaise, generalized itching (itching), headache, nausea, vomiting, or unintentional weight loss. In addition, late symptoms may include, but are not limited to, blood in the vomit or stool, decreased alertness, including drowsiness, confusion, delirium, orcoma, decreased sensitivity in the hands, feet, or other areas, injury or easy bleeding, increased or decreased urine output, muscle spasms or cramps, seizures, or white crystals inside the skin and on the skin (uremic frost).
[091] Circulating levels of cytokines and other inflammatory markers are markedly elevated in patients with chronic renal failure. This can be caused by increased generation, decreased removal, or both. However, it is not well established to what extent renal function per se contributes to the uremic proinflammatory medium. Relationships between the rate of inflammation and glomerular filtration (GFR) have been reported in 176 patients (age, 52 +/- 1 year; GFR, 6.5 +/- 0.1 ml / min) near the start of replacement therapy renal. Pecoits-Filho et al., "Associations between circulating inflammatory markers and residual renal function in CRF patients" Am J Kidney Dis. 41 (6): 1212-1218 (2003). For example, circulation levels of high-sensitivity Creative protein (hsCRP), tumor necrosis factoralpha (TNF-alpha), interleukin-6 (IL-6), hyaluronic acid, and neopterin were measured after an overnight fast. The patients were subsequently subdivided into two groups, according to the mean GFR (6.5 ml / min). Despite the narrow range of GFR (1.8 to 16.5 ml / min), the levels of hsCRP, hyaluronan, and neopterin were significantly higher in the subgroup with lower GFRs, and significant negative correlations were observed between GFR and IL-6 (rho -0.18; P <0.05), hyaluronic acid (rho = -0.25, P <0.001), and neopterin (rho = -0.32, P <0.0005). In a multivariate analysis, age and GFR were associated with inflammation, but cardiovascular disease and diabetes mellitus were not. These results show that a low glomerular filtration rate alone is associated with an inflammatory state, which suggests impaired renal elimination of pro-inflammatory cytokines, increased cytokine generation in uremia, or an adverse effect of inflammation on function renal. C. Dialysis
[092] Dialysis (ie, for example, renal replacement therapy) is a method of removing toxic substances (impurities or waste) from the blood when the kidneys are unable to do so and can be performed using several different methods . For example, peritoneal dialysis can filter waste, using the peritoneal membrane inside the abdomen. The abdomen is filled with special solutions that help remove toxins. The solutions remain in the abdomen for a while and then drain out. This form of dialysis can be performed at home, but it must be done every day. Alternatively, hemodialysis can be performed by circulating blood through special filters outside the body. Blood flows through a filter, along with solutions that help remove toxins.
[093] Dialysis uses special forms of access to blood in the blood vessels. Access can be temporary or permanent. Temporary access takes the form of dialysis catheters - hollow tubes placed in large veins that can withstand acceptable blood flows. Most catheters are used in emergency situations, for short periods of time. However, catheters called tunneled catheters can be used for long periods of time, often weeks or months. Permanent access is created by surgically connecting an artery to a vein. This allows the vein to receive blood at high pressure, leading to a thickening of the vein wall. This vein can handle repeated puncture and also provides excellent blood flow rates. The connection between an artery and a vein can be made using blood vessels (from an arteriovenous fistula, or AVF) or a synthetic bridge (arteriovenous graft, or AVG). The blood is diverted from the access point in the body to a dialysis machine. Here, blood flows countercurrently with a special solution called dialysate. The chemical imbalances and impurities in the blood are corrected and the blood is then returned to the body. Usually, most patients undergo hemodialysis for three sessions each week. Each session lasts 3-4 hours.
[094] The purpose of dialysis is to help kidney functions including, filters for the blood, removing waste, regulating the body's water, maintaining electrolyte balance, or maintaining the pH in the blood that remains between 7.35 and 7.45 . In addition, dialysis can replace some of the kidney functions that are not working properly, which could result in the death of a patient.
[095] Dialysis is most often used for patients suffering from kidney failure, but it can also quickly remove drugs or poisons in acute situations. This technique can save a life in people with acute or chronic kidney failure. II. Urinary Renal Biomarkers
[096] Currently, there are no effective treatments to improve kidney recovery, or to improve short- and long-term kidney outcomes after AKI. In addition, methods for predicting recovery are also lacking. The emerging role of biomarkers for the early detection of kidney disease and / or kidney injury may help to identify new prognostic tools for predicting clinical kidney outcomes. Potential candidates for renal recovery biomarkers include, but are not limited to, molecules expressed in pathways that lead to regeneration and proliferation, as well as markers of fibrosis and apoptosis. In addition, kidney injury biomarkers can also serve to distinguish early resolution and, therefore, increased chances of recovery.
[097] Acute kidney injury (AKI) has an estimated incidence rate of around 2000 per million inhabitants and this rate is increasing. Ali et al., "Incidence and outcomes in acute kidney injury: a comprehensive population-based study" J Am Soc Nephrol 18: 1292-1298 (2007). Approximately 5% of all people admitted to intensive care units worldwide develop severe AKI requiring dialysis. Uchino et al., "Acute renal failure in critically ill patients: a multinational, multicenter study" JAMA 294: 813-818 (2005). A recent multicenter study in the United States found that less than just about 60% of patients surviving severe AKI recovered kidney function for two months. Palevsky et al., "Intensity of renal support in critically ill patients with acute kidney injury" N Engl J Med 359: 7-20 (2008). Thus, a large number of AKI patients progress to end-stage kidney disease (ESRD).
[098] However, since only a fraction of AKI patients do not recover kidney function, interventions aimed at improving recovery or providing renal support (early dialysis, for example) cannot be selectively targeted appropriately without any means of determining which patients will recover and those who will not (ie, for example, the availability of non-invasive biomarkers). Currently, the clinical risk prediction for recovery after AKI is extremely limited. Thus, the development of a non-invasive biomarker that allows the initial prediction of renal function recovery is a need that has long been felt in the technique of treating kidney disease.
[099] The identification of such non-invasive biomarkers (ie, for example, a urinary biomarker) would significantly improve the long-term prognosis, thereby adapting research efforts for the treatment of AKI and ESRD prevention. In other words, having the ability to predict which patients will not recover kidney function allows a clinician to focus limited resources on developing and implementing aggressive treatment interventions on these predicted risk patients. On the other hand, patients with a favorable prognosis would be spared from more aggressive interventions and their potential adverse effects, thereby freeing up medical resources for those in need and reducing general medical costs.
[0100] In one embodiment, the present invention contemplates methods and compositions for assessing renal function in a subject. As described herein, the measurement of various kidney injury markers described herein can be used for diagnosis, prognosis, risk stratification, preparation, monitoring, categorization and a determination of diagnosis and additional treatment regimens, in subjects who are suffering or running the risk of suffering from impaired kidney function, reduced kidney function and / or acute kidney failure (also called acute kidney injury).
[0101] Renal biomarkers, as described herein, can be used individually, or on panels, comprising a plurality of renal biomarkers, for risk stratification. In one modality, the risk stratification identifies subjects at risk for a future: i) kidney injury; ii) progression to reduced kidney function, and iii) progression to AKI, or iv) improvement of kidney function, etc. In one modality, risk stratification diagnoses an existing disease, comprising the identification of subjects who have: i) suffered an injury to kidney function; ii) progressed to reduced kidney function; or iii) progressed to ARF, etc. In one embodiment, risk stratification monitors deterioration and / or improvement in renal function. In one embodiment, risk stratification predicts a future medical outcome, including, but not limited to, an improvement or worsening of kidney function, a risk of decreased or increased mortality, a decrease or increased risk that a subject will require initiation or continuation of renal replacement therapy (ie, hemodialysis, peritoneal dialysis, hemofiltration and / or kidney transplantation), a decreased or increased risk that a subject will recover from impaired renal function, a decrease or increase in risk that the subject will recover from ARF, a decrease or increase in the risk that a subject will progress to end-stage reindeer disease, a decrease or increase in the risk that a subject will progress to chronic renal failure, a decrease or increased risk that a subject will suffer from rejection of a transplanted kidney, etc.
[0102] In one embodiment, the present invention contemplates methods for assessing renal status in a subject. In one embodiment, the method provides a sample of body fluid obtained from the subject. In one embodiment, the method comprises performing an assay with the body fluid sample to detect one or more renal biomarkers selected from the group including, but not limited to, hyaluronic acid (HA), death receptor 5 (DR5), or transformation growth factor β1 (TGFβ1). The test measurement, for example, a measured concentration of HA, DR5, and / or TGFβ1, is / are then related to a threshold value to determine the subject's renal condition.
[0103] Correlations to establish a patient's renal condition may include, but are not limited to, correlation of assay measurement to one or more risk stratification, diagnosis, prognosis, preparation, classification and monitoring of the subject as described herein. Thus, the present invention uses one or more renal biomarkers of the present invention for the assessment of kidney disease and / or impairment.
[0104] A variety of methods can be used to achieve a desired threshold value for use in these methods. For example, a threshold value can be determined from a population of normal subjects, selecting a concentration of renal biomarkers representing the 75 °, 85 °, 90 °, 95 °, or 99 ° percentile of the biomarker as measured in such subjects normal. Alternatively, a threshold value can be determined from a population of "sick" subjects, for example, those who suffer from an injury or who are predisposed to an injury (for example, progression to AKI or some other clinical outcome, such as death, dialysis, kidney transplant, etc.), selecting a concentration of renal biomarker representing the 75 °, 85 °, 90 °, 95 ° or 99 ° percentile of the biomarker as measured in such sick subjects. In another alternative, the threshold value can be determined from a previous measurement of a renal biomarker on the same subject; that is, a temporal change in the level of the biomarker in the subject can be used to assign risk to the subject.
[0105] The discussion that follows is not intended to imply, however, that the renal biomarkers contemplated here are limited to a comparison with corresponding individual thresholds. Other methods for combining test results may include the use of multivariate logistic regression, loglinear modeling, neural network analysis, n-of-m analysis, decision tree analysis, calculation of marker ratios, etc. This list does not is meant to be limiting. In these methods, a composite results, which is determined by the combination of individual biomarkers, can be treated as if it were a biomarker itself; that is, a threshold value can be determined for the resulting composite as described herein for the individual biomarkers, and the resulting composite for an individual patient in comparison to this threshold value.
[0106] In one embodiment, the present invention contemplates a biomarker of urinary hyaluronic acid (HA) to predict the recovery of renal function after injury and / or kidney disease. In one embodiment, the identification of biomarkers provides the stratification of the patient to adjust the intensity of the treatment, thus avoiding unnecessary complications in the long run.
[0107] In one embodiment, the present invention contemplates a method which comprises predicting the long-term prognosis of an injury and / or kidney disease early after the onset of the injury and / or kidney disease. In one embodiment, the method provides for long-term dialysis when urinary AH is persistently elevated between D1 - D14 after the start of replacement therapy for severe acute kidney injury. In one embodiment, the method provides for long-term dialysis when urinary AH is persistently elevated between D1 - D14 after the start of replacement therapy for severe acute kidney injury. In one embodiment, long-term dialysis comprises at least sixty (60) days after kidney injury. In one embodiment, long-term dialysis comprises at least sixty (60) days after the diagnosis of kidney disease.
[0108] Some data provided here was collected from forty-three (43) patients enrolled in a large randomized controlled multicenter trial studying the effect of different doses of RRT on AKI survival. In one embodiment, AKI survival was correlated with a urinary hyaluronic acid (HA) biomarker. Although it is not necessary to understand the mechanism of the invention, it is believed that HA (i.e., for example, hyaluronic acid or hyaluronate) comprises an unsulfated glycosaminoglycan, and it is believed that it is widely distributed throughout the connective tissue , epithelial and neural. It is also believed that HA is one of several components within the extracellular matrix and that it may be involved in tissue repair and remodeling through the mediation of cell proliferation and migration, synthesis and degradation of the extracellular matrix. For example, fragmented HA has been observed to accumulate during tissue injury and can stimulate the expression of inflammatory genes by a variety of immune cells at the injury site. In addition, decreased HA clearance was seen to result in persistent inflammation.
[0109] In one embodiment, the biomarker provides for non-recovery of renal function, in which dependence on dialysis is greater than sixty (60) days. In one modality, non-recovery of renal function comprises the elevation of the biomarker above its initial value for at least fourteen (14) days. In one embodiment, the biomarker prediction is supported by an analysis of the receiver's operating characteristics (ROC). In one embodiment, the ROC analysis provides calculations, including, but not limited to, area under the fitted curve and / or trapezoidal area (Wilcoxon). In one embodiment, the area under the fitted curve = 0.9686 with an estimated standard error = 0.0518. In one embodiment, the trapezoidal area (Wilcoxon) = 0.9692 having an estimated standard error = 0.0568. See, Figure 5. A. Hyaluronic Acid
[0110] Hyaluronic acid (HA) is believed to be a ubiquitous glycosaminoglycan connective tissue that in vivo is present as a high molecular mass component of most extracellular matrices. HA has not been identified as one of the main constituents of normal renal corticosteroids. Hansell et al., "Hyaluronan content in the kidney in different states of body hydration" Kidney Int 58: 2061-2068 (2000). However, HA is expressed around proximal renal tubular epithelial cells (PTC), after acute and chronic kidney damage that is caused by numerous diseases. Sibalic et al., "Upregulated renal tubular CD44, hyaluronan, and osteopontin in kdkd mice with interstitial nephritis" Nephrol Dial Transplant 12: 1344-1353 (1997); and Lewington et al., "Expression of CD44 in kidney after acute ischemic injury in rats" Am J Physiol Regul Integr Comp Physiol 278: R247-254 (2000). In addition, the increased deposition of interstitial AH correlates with kidney function and proteinuria in progressive kidney disease. Sano et al., "Localization and roles of CD44, hyaluronic acid and osteopontin in IgA nephropathy" Nephron 89: 416421 (2001).
[0111] The binding of HA to its principle receptor, CD44, promotes inflammation through the interaction between HA and CD44, expressed in inflammatory cells. Melin et al., "Ischemia induced renal expression of hyaluronan and CD44 in diabetic rats" Nephron Exp Nephrol 103: e86-94 (2006). HA / CD44 activates the mitogen-activated protein kinase pathway (MAPK) and improves PTC migration, a process that is implicated in the transdifferentiation of fibroblast-epithelial cells and progressive renal fibrosis. Yang et al., "Dissection of key events in tubular epithelial to myofibroblast transition and its implications in renal interstitial fibrosis" Am J Pathol 159: 1465-1475 (2001). In ischemic kidneys of diabetic subjects, the renal HA content started to increase after 24 hours and significantly 18 weeks after ischemia / reperfusion (I / R). Okajima K: "Regulation of inflammatory responses by natural anticoagulants" Immunol Rev 184: 258-274 (2001).
[0112] Hyaluronic acid (also known in the art as hyaluronate and hyaluronan, and abbreviated as HA) is a glycosaminoglycan that comprises a linear unbranched polysaccharide chain with alternating units of N-acetyl-D-glucosamine and D-glucuronic acid. Laurent et al, "Hyaluronan" FASEB J 6: 2397-2404 (1992); and Delpech et al, "Hyaluronan: fundamental principles and applications in cancer" J Intern Med 242: 41-48 (1997). HA is ubiquitously present in several types of biological materials, including both bacteria and animals. In humans, HA is found in high concentrations in umbilical cords, vitreous humor of the eyes, cartilage and synovial fluid. Small amounts of HA are present in CSF, lymph, blood, serum and urine. HA levels have been associated with diseases such as rheumatoid arthritis, liver cirrhosis, and Wilms' tumor. HA is associated with non-specific tumors in general, but its use has not been applied until now for the discovery, therapy, and control of certain clinical tumors. HA has been known to play a role in several pathophysiological conditions including cancer.
[0113] For example, HA levels have been shown to be elevated in certain tumor models in animals (eg, rabbit V2 carcinoma) and in human cancers (eg, lung, Wilms' tumor, breast, etc.) Knudson et al., "The role and regulation of tumor associated hyaluronan" In: The Biology of Hyaluronan (J. Whelan, ed.), pp. 150-169, New York, Wiley Chichister (Ciba Foundation Symposium 143), 1989). In tumor tissues, HA supports the adhesion and migration of tumor cells and also offers some protection against immune surveillance.
[0114] Small fragments of HA have also been observed to stimulate angiogenesis, and such fragments are found in the urine of patients with carcinoma of the bladder and tumor tissues. Sattar et al., "Does hyaluronan have a role in endothelial cell proliferation of the synovium " Semin Arthritis Rheum 22: 3713 (1992); Lokeshwar VB, Selzer MG. Differences in hyaluronic acid mediated functions and signaling in arterial, microvessel, and veinderived human endothelial cells. J Biol Chem 2000; 275: 27641-27649. Fragments of hyaluronic acid are generated when HAase, an endoglycosidase, degrades the HA polymer. Csoka TB, Frost GI, Stern R. Hyaluronidases in tissue invasion. Invasion Metastasis 1997; 17: 297-311; and 55. Roden L, Campbell P, Fraser JR, Laurent TC, Petroff H, Thompson JN. Enzymatic pathways of hyaluronan catabolism. In: Whelan J, editor. The Biology of Hyaluronan. New York: Wiley Chichister 1989: 60-86. A HA test has been suggested to detect bladder carcinoma, regardless of the tumor grade. Lokeshwar VB, Obek C, Pham HT, Wei D, Young MJ, Duncan RC. Urinary hyaluronic acid and hyaluronidase: markers for bladder cancer detection and evaluation of grade. J Urol 2000; 163: 348-356. An HA test has been suggested for the detection of bladder carcinoma, regardless of the degree of the tumor. Lokeshwar VB, Obek C, Pham HT, Wei D, Young MJ, Duncan RC. Urinary hyaluronic acid and hyaluronidase: markers for bladder cancer detection and evaluation of grade. J Urol 2000; 163: 348-356.
[0115] The effectiveness of the HA-HAase test to monitor bladder tumor recurrence, compared to the BTA-Stat standard has recently been reported. Lokeshwar et al., Bladder Tumor Markers for Monitoring Recurrence and Screening Comparison of Hyaluronic Acid-Hyaluronidase and BTA-Stat Tests Cancer 95: 61-72 (2002). This study suggests that a biochemical test, such as the HA-HAase test, can detect recurrence of bladder carcinoma before cystoscopy. If early detection of this type can provide a clinical advantage in terms of outcome, cystoscopy may not remain the supreme gold standard for deciding the sensitivity, specificity and accuracy of a test for monitoring recurrence. An interesting corollary to this problem would be the treatment of patients with prostate carcinoma and enlarged prostate specific antigen after radical prostectomy or radiation therapy, the HA-HAase test can be an effective aid for cystoscopy for monitoring the recurrence of carcinoma of the bladder. With over 90% sensitivity and 86% accuracy, the HA-HAase test can be an effective aid for cystoscopy for monitoring recurrence of bladder carcinoma. A false-positive HA-HAase test carries a significant risk of recurrence within five months. Thus, it is possible that a combination of biochemical tests could effectively control the recurrence of bladder carcinoma, which can allow a minimum reduction of 50% in the number of surveillance cystoscopy procedures.
[0116] Hyaluronidase (HAase) is an endoglycoside enzyme that degrades HA by hydrolyzing N-acetylglucosamine bonds in HA. The limited degradation of HA by hyaluronidase results in the generation of HA fragments of specific lengths (~ 3-25 disaccharide units), which are angiogenic ((West et al., Angiogenesis induced by degradation products of hyaluronic acid. Science, 228: 1324-1326, 1985)). In vertebrates, hyaluronidases can be classified into two classes, those that are active at neutral pH (optimal pH is 5.0), and those that are active at acid pH (pH 3.5-4.0) (Roden et al., Enzymatic pathways of hyaluronan catabolism, In: The Biology of hyaluronan, (J. Whelan, ed.), pp. 60-86, New York, Wiley Chichister (Ciba Foundation Symposium 143), 1989; West et al., ibid .; Gold, Purification and properties of hyaluronidase from human liver. Biochem. J., 205: 69-74, 1982; Fraser and Laurent, Turnover and metabolism of Hyaluronan. In: Biology of Hyaluronan, (J. Whelan, ed.), Pp. 41 -59, New York, Wiley Chichister (Ciba Foundation Symposium 143), 1989; Zhu et al., Molecular cloning of a mammalian hyaluronidase reveals identity with hemopexin, a serum hemebinding protein. J. Biol. Chem., 269: 3209232097, 1994 ; Lin et al., A hyaluronidase activity of the sperm plasma membrane protein PH-20 enables sperm to penetrate the cumulus layer surrounding the egg. J. Cell Biol., 125: 1157-1163, 1995). For example, testicular hyaluronidase is of the neutral type, whereas liver hyaluronidase has an optimal acidic pH. The concerted actions of HA and hyaluronidase are known to play an important role during embryonic development, vasculogenesis, vascular remodeling, immune surveillance and tumor progression ((McCormick and Zetter, Adhesive interactions in angiogenesis and metastasis. Pharmac. Ther., 53: 239260, 1992; Hobarth et al., Topical chemo-prophylaxis of superficial bladder cancer by mitomycin C and adjuvant hyaluronidase, Eur. Urol., 21: 206-210, 1992; Knudson et al., The role and regulation of tumorassociated hyaluronan. In: The Biology of Hyaluronan (J. Whelan, ed.) Pp. 150-169, New York, Wiley, Chichester (Ciba Foundation Symposium 143), 1989; Lin et al., Urinary hyaluronic acid is a Wilms' tumor marker. J. Ped. Surg., 30: 304-308, 1995; Stern et al., Hyaluronidase levels in urine from Wilms' tumor patients. J. Natl. Cane. Inst., 83: 1569-1574, 1991). B. Death receiver 5
[0117] Death receptor 5 (DR5) is believed to be a proapoptotic receptor that is activated by the tumor necrosis factor (TRAIL) -related apoptosis ligand. TRAIL is believed to be a soluble form of an endogenous apoptosis-inducing ligand that induces apoptosis in a wide variety of cells and contributes to inflammation and subsequent fibrosis. TRAIL or DR5-deficient mice have been reported to be relatively resistant to the occurrence of inflammation and subsequent fibrosis. Wang et al., "Overexpression of C / EBP-alpha induces apoptosis in cultured rat hepatic stellate cells depending on p53 and peroxisome proliferator-activated receptorgamma" Biochem Biophys Res Commun 380: 2862-91 (2009); and Takeda et al., "Death receptor 5 mediated-apoptosis contributes to cholestatic liver disease" Proc Natl Acad Sci USA 105: 10895-10900 (2008).
[0118] The data presented here exemplify a screening method for a number of urinary proteins that are relevant for inflammation, septicemia, acute kidney injury and acute kidney failure. From this panel, the urine death receptor 5 (DR5) was identified as a potential biomarker for recovery after severe AKI. The death receptor 5 (also known as TRAILR2) is part of the Tumor Necrosis Factor (TNF) superfamily, and is a receptor for Tumor Necrosis Factor-Related Apoptosis (TRAIL). After the binding of TRAIL to its receptors (DR4 and DR5), a cascade of events begins that leads to NFkB activation and apoptosis. Shetty et al., "Tumor necrosis factorrelated apoptosis inducing ligand (TRAIL) up-regulates death receptor 5 (DR5) mediated by NFkB activation in epithelial cell lines" Apoptosis 7: 413-420 (2002).
[0119] In one embodiment, the present invention contemplates a urinary biomarker comprising DR5 capable of predicting the recovery of post-AKI renal function. In one embodiment, the present invention contemplates a urinary biomarker comprising DR5 capable of providing patient stratification for the intensity of post-AKI treatment and prevention of long-term complications. C. Transformation growth factor β1
[0120] Transformational growth factor β1 (TGFβ1) is believed to be a secreted protein that performs many cellular functions, including, but not limited to, proliferation, differentiation and apoptosis. TGFβ1 can act directly, stimulating the synthesis of extracellular matrix components and reducing collagenase production, or indirectly through other pro-fibrogenic factors, such as connective tissue growth factor (CTGF), which can play a role in glomerulosclerosis , interstitial fibrosis and tubular atrophy that occur with end-stage renal failure, regardless of primary etiology. Wolf G., "Renal injury due to renin-angiotensin-aldosterone system activation of the transforming growth facto-rbeta pathway" Kidney Int 70: 1914-1919 (2006). TGFβ1 is also highly expressed after ischemia / reperfusion (I / R) and promotes the loss of blood vessels through the induction of phenotypic transition of endothelial cells to a transdifferentiation in fibroblast / myofibroblast phenotype.
[0121] The data presented here trace a series of urinary proteins related to renal physiology. From this panel, the Urinary Transformation Growth Factor β1 (TGF-β1) was identified as a potential biomarker for recovery after severe renal AKI. TGF-β1 is the growth factor involved in embryonic development and tissue healing and repair. TGF-β1 is known to be involved in signaling the epithelial cells of the renal tubules. Sakurai et al., "An in vitro tubulogenesis system using cell lines derived from the embryonic kidney shows dependence on multiple soluble growth factors" Proc Natl Acad Sci USA 94: 6279-6284 (1997).
[0122] In one embodiment, the present invention contemplates a urinary biomarker comprising TGF-β1 capable of predicting the recovery of renal function post-AKI. In one embodiment, the present invention contemplates a urinary biomarker comprising TGF-β1 capable of providing patient stratification for the intensity of post-AKI treatment and prevention of long-term complications. D. Clinical Test Results 1. Experimental Project
[0123] A recent renal recovery study (BioMARK) was an observational cohort study conducted as part of the Veterans Affairs / National Institutes of Health (VA / NIH) Acute Renal Failure Test Network Study (hereinafter referred to as the ATN study) ). The ATN study comprised a multicenter, prospective test of two strategies for renal replacement therapy in critically ill patients with acute kidney injury. The ATN study was conducted between November 2003 and July 2007 at 27 medical centers affiliated with the University and Veterans Administration. All adult patients (18 years or older) had AKI clinically consistent with acute tubular necrosis (defined as a clinical setting of ischemic or nephrotoxic injury and increased serum oliguria or creatinine) and requiring renal replacement therapy (RRT), as well as insufficiency of one or more non-renal organ systems or septicemia.
[0124] The exclusion criteria were: i) baseline serum creatinine of more than 2 mg / dl in men or more than 1.5 mg / dL in women; ii) AKI clinically considered to be due to a different etiology of acute tubular necrosis; iii) previous kidney transplantation; iv) pregnancy, v) incarceration; vi) weight of more than 120 kg; vii) not applying for RRT; viii) dying state; or ix) patient with no expectation to survive 28 days because of an irreversible medical condition. Eligible patients could not have undergone more than one intermittent hemodialysis session or sustained low-efficiency dialysis or more than 24 hours of continuous renal replacement therapy prior to randomization.
[0125] As a sub-study of the ATN Test, some patients enrolled in the medical centers of the University of Pittsburgh Medical Center, Pittsburgh VA Medical Center, Cleveland Clinical Foundation, University of Texas Health Science Center in Houston, and Washington University Medical Center perform series measurements of selected potential biomarkers (ie, for example, hyaluronic acid, transforming growth factor β1, or death receptor 5). This particular study required an additional consent form for the determination of biomarkers, and a total of 76 cases from these 5 centers were available for analysis and included in the study. Approval was obtained from the Institutional Review Boards of the University of Pittsburgh and all participating locations. 2. Analysis and Data Collection
[0126] Medical records of study participants were prospectively reviewed to recover hospitalization data, including baseline demographic characteristics, serial renal function, and / or the presence of oliguria (as defined by urinary output <400 ml / day). The presence of septicemia was defined using the systemic inflammatory response syndrome criteria. The definition of renal recovery was modified from the 2nd International Consensus Conference of the acute dialysis quality initiative group (ADQI). Recovery of renal function was defined by long-term survival or independence from dialysis. Non-recovery was defined by non-survival or independence from dialysis.
[0127] Fresh urine samples were obtained at the following times: Day 1, Day 7, and Day 14 after enrollment. After centrifuging the urine for 5 minutes at 1000 xg, at 4 ° C, the urine samples were aliquoted and stored at -80 ° C. None of the samples were thawed and frozen again before the study. Urinary creatinine concentrations were measured using a commercially available enzyme assay (DZ072B, Diazyme labs, California, USA); Urinary HA was measured using a commercially available assay (Echelon Biosciences, Salt Lake City, USA); and TGFβ1 was measured using a commercially available assay (R&D, Minneapolis, USA). All were measured according to the respective manufacturer's instructions. DR5 was measured by a chemiluminescent immunoassay using an automated analyzer (IMMULITE®; Diagnostic Products Corp, Los Angeles, California).
[0128] The outcome of recovery as independence from dialysis was defined as occurring on day 60. Baseline characteristics were compared between patients who recovered from acute kidney injury for 60 days after enrollment and those who failed to recover. Continuous data were expressed as mean ± SD and compared using Student's t test or Wilcoxon ranksum test. Categorical data were expressed as proportions and compared using the chi-square test or Fisher's exact test. The levels of renal biomarkers were normalized by the urinary creatinine concentration and analyzed at each time point. The analysis was then performed using the largest relative change within the first 14 days, compared to day 1 and the last available measurement for each patient. Logistic regression was then adjusted for the data set to assess the association between each potential biomarker and AKI recovery. Consequently, the area under the receiver operating characteristic curve (AUC ROC) was generated to assess the prediction accuracy of each renal biomarker. The best cutoff points were determined by the highest sum of sensitivity and specificity. To assess the additive predictability of each renal biomarker for traditional clinical predictors, a clinical prediction model was identified from the AUC ROC analysis and then added to each renal biomarker individually for this clinical model. The AUC ROCs from the combined models were compared with the AUC ROCs from the clinical model. All analyzes were performed using SAS 9.0 (SAS Institute, Cary, NC) with a significance level of 0.05. 3. Results
[0129] The clinical characteristics of the 76 patients are summarized in Table 2.Table 2: Demographic and Clinical Evidence

The. Summary of Day 1
[0130] There was an equal number of patients in the recovery and non-recovery group. No significant differences were found between the recovery and non-recovery groups which are, in terms of sex, race, baseline renal function, or clinical assessment scores on Day 1 (ie, for example, APACHE II scores and / or scores Cleveland Clinic ARF IUC Renal Insufficiency). Mean age, length of stay in IUC before randomization, Charlson's comorbidity index, total SOFA score on Day 1 were all significantly higher in the non-recovery group when compared to the recovery group. Ischemia was observed to have the highest percentage (97.4%) for AKI causes in the non-recovery group when compared to 76.3% in the recovery group. Septicemia was also seen to be responsible for AKI more often in the non-recovery group than in the recovery group (71.05% vs 60.53%, respectively). B. Day 60 Recovery Forecast
[0131] Five (5) different models of combinations of individual biomarkers were selected for the best area under the ROC curve (AUC ROC) for the recovery forecast for Day 60. See, Table 3.Table 3: Model Correlations of Urinary Biomarker Predicting Recovery by Day 60

[0132] The data shows that the HA on Day 14, TGFβ1 on Day 14, and the last available DR5 values were the best indicators of AKI recovery with AUC ROCs ranging from 0.70 to 0.89. The optimized clinical model was a combination of age and Charlson's comorbidity index, which indicated a significant AUC ROC of 0.74 for AKI recovery. Major improvements in AUC were seen when renal urinary biomarkers of ROCs were added to the clinical model. AUC ROCs of clinical model evidence combined with relative changes in HA, DR5, and TGFβ1 were 0.83, 0.86, 0.84 and 0.91, respectively, where the AUC ROC reaches 0.97 when HA from Day 14 is combined with age (P <0.001 for all previous models, Table 4). Table 4: Improved Prediction using Clinical Model Combinations

[0133] The significant time points for each urine marker were decided by choosing the maximum AUC ROC values. A clinical threshold was determined by identifying the maximum sum of sensitivity and specificity of the five models above. See, Table 3. Day 14 HA was observed to have the highest sensitivity value of 0.93 and specificity of 0.83 to 12 mcg / mg.Cr. Although lower in sensitivity, the last available DR5, and TGFβ1 values for Day 14 were also determined to be predictable. See, Table 5.Table 5: Thresholds of Urinary Biomarkers

[0134] No significant differences were found in relation to baseline renal function, the combination of septicemia, APACHE II score or RRT intensity between the recovery and non-recovery groups. However, patients in the non-recovery group were found to be the oldest, most likely to have renal ischemia, incurred in the ICU for long periods before RRT, plus comorbidities and higher SOFA potencies. The data suggest that a combination of age, total SOFA score for Day 1 and Charlson's comorbidity index comprises a preferred predictive clinical model.
[0135] These data also demonstrate that the relative change in urinary biomarkers HA, DR5, and TGFβ1 is significantly correlated with adverse AKI results. These three (3) renal biomarkers represent biological processes of deposition of extracellular matrix in renal course, cell apoptosis, transdifferentiation of intrinsic cell phenotype and tubular epithelial cell injury, respectively. Although it is not necessary to understand the mechanism of the invention, it is believed that since Day 1 the values represent the intensity of insults and internal cellular responses, the relative change of these renal biomarkers can represent the degree of recovery, regardless of the individual baseline characteristics. In addition, a strong association between HA on Day 14 with the results suggests that deposition of extracellular matrix may play a role in the kidney recovery process. III. Renal State Test Measurements
[0136] The ability of a particular renal biomarker assay measurement to distinguish between the two populations can be established using ROC analysis. For example, the ROC curves were established from a "first" subpopulation (that is, for example, a population predisposed to one or more future changes in kidney condition) and a "second" subpopulation (that is, for example, a population not predisposed to one or more future changes in kidney status). The calculation of the ROC curves and the establishment of the area under these ROC curves quantify the predictive power of the measurement of the specific test. In some embodiments, the predictive power established by the test measurements described here comprises an AUC ROC greater than 0.5, preferably at least 0.6, more preferably 0.7, even more preferably at least 0.8, even more preferably, at least 0.9, and most preferably, at least 0.95. A. Immunoassays
[0137] In general, immunoassays involve contacting a sample containing, or suspected to contain, a biomarker of interest with at least one antibody that specifically binds to the biomarker. A detectable signal is then generated indicative of the presence or quantity of complexes formed by the binding of polypeptides in the sample with the antibody. The detectable signal is then related to the presence or quantity of the marker in the sample. Numerous methods and devices have been reported in relation to the detection and analysis of biological biomarkers. See, for example, US patents 6,143,576; 6,113,855; 6,019,944; 5,985,579; 5,947,124; 5,939,272; 5,922,615; 5,885,527; 5,851,776; 5,824,799; 5,679,526; 5,525,524, and 5,480,792, and The immunoassay Handbook, David Wild, ed. Stockton Press, New York, 1994, each of which is incorporated herein by reference in its entirety, including all tables, figures and claims.
[0138] Numerous immunoassay devices and methods can use labeled molecules in various sandwich assay formats, competitive or non-competitive, to generate a signal that is related to the presence or quantity of the marker of interest. Suitable assay formats also include spectrographic methods, mass chromatography, and protein blotting. In addition, certain methods and devices, such as biosensors and optical immunoassays, can be employed to determine the presence or quantity of analytes, without the need for a labeled molecule. See, for example, US Patents 5,631,171 and 5,955,377, each of which is incorporated herein by reference in its entirety, including all tables, figures and claims. Robotic instrumentation to perform these immunoassays is commercially available, including, but not limited to, Beckman ACCESS®, Abbott AXSYM®, Roche ELECSYS®, Dade Behring STRATUS® systems. But any suitable immunoassay can be used, for example, enzyme linked immunoassays (ELISA), radioimmunoassay (RIA), competitive binding assays, and the like.
[0139] Antibodies or other polypeptides can be immobilized on a variety of solid supports for use in immunoassays. The solid phases that can be used to immobilize specific binding members include, but are not limited to those that have been developed and / or used as solid phases, in solid phase binding assays. Examples of suitable solid phases include, but are not limited to, membrane filters, cellulose-based papers, granules (including polymeric particles, latex and paramagnetic), glass, silicone wafers, microparticles, nanoparticles, TentaGels, AgroGels, PEGA gels , SPOCC gels, and multi-well plates. For example, a dosing strip can be prepared by coating the antibody or a plurality of antibodies on a solid support matrix. This strip can then be dipped in the test sample and then quickly processed through washing and detection steps to generate a measurable signal, such as a color stain. Antibodies or other polypeptides can be attached to specific zones of test devices, either by conjugation directly to a surface of the test device, or by indirect attachment. In an example of the latter case, antibodies or other polypeptides can be immobilized on particles or other solid supports, and the solid support immobilized on the surface of the device.
[0140] In certain embodiments, a urinary renal biomarker assay method comprises an immunoassay. For example, antibodies for use in such assays can specifically bind to an epitope of a renal biomarker of interest, and can also bind to one or more polypeptides that are "related" to them, as the term is defined further up. In one embodiment, the renal biomarker of interest is a full-length marker (i.e., for example, a protein). In one embodiment, the renal biomarker of interest is a protein fragment marker (i.e., for example, a peptide). Numerous immunoassay formats are available that are compatible with body fluid samples, including, but not limited to, blood, urine, serum, saliva, tears and plasma.
[0141] In this respect, the detectable signals obtained from an immunoassay can be a direct result of complexes formed between one or more antibodies and the target biomolecule (i.e., an analyte) and polypeptides containing the (s) necessary epitope (s) to which antibodies bind. Although these assays can detect the full-length biomarker and the test result is expressed as the concentration of a biomarker of interest, the test signal may actually be the result of all of these "immunoreactive" polypeptides present in the sample. Expression of biomarkers can also be determined by means other than immunoassays, including proteins (i.e., dot blots, Western blots, chromatographic methods, mass spectrometry, etc.) and nucleic acid measurements (mRNA quantification) ). This list is not intended to be limiting.
[0142] The steps of the method above should not be interpreted as meaning that the renal biomarkers assay measurement (s) is / are used alone in the methods described herein. Instead, additional variables or other clinical evidence can be included in the methods described here. For example, risk stratification, diagnosis, classification, control, etc., methods as described herein, can be combined with one or more clinical evidence relevant to the patient population, including, but not limited to, demographic information (eg , weight, sex, age, race), medical history (eg, family history, type of surgery, pre-existing diseases such as aneurysm, congestive heart failure, pre-eclampsia, eclampsia, diabetes mellitus, arterial hypertension, arterial disease coronary disease, proteinuria, kidney failure or septicemia, type of exposure to a toxin, such as NSAIDs, cyclosporins, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin , clinical variables (for example, blood pressure, temperature, respiration rate), risk scores (APACHE score, PREDICT score, TIMI risk for UA / NSTEMI, Framingham Risk score), a glomerular filtration rate, an estimated glomerular filtration rate, a urine production rate, a concentration of serum or plasma creatinine, a concentration of urinary creatinine, an excretion fractionated sodium, a concentration of sodium in the urine, ratio of urine creatinine to serum or plasma creatinine, a specific urine severity, a urine osmolality, a ratio of urine urea to plasma urea nitrogen, a ratio of plasma BUN to creatnine, a renal failure index calculated as urine sodium / (urine creatinine / plasma creatinine), a concentration of neutrophil gelatinase (NGAL) in serum or plasma, a concentration of urine NGAL, a serum or plasma cystatin C concentration, a serum or plasma cardiac troponin concentration, a serum or plasma BNP concentration, a serum or plasma NTproBNP concentration, and a concentration tration of proBNP in serum or plasma. Other measures of renal function that can be combined with one or more measurements of renal biomarkers assays are described below. In: Harrison's Principles of Internal Medicine, 17th Ed., McGraw Hill, New York, pages 1741-1830; and In: Current Medical Diagnosis & Treatment 2008, 47th Ed, McGraw Hill, New York, pages 785815, each of which is incorporated herein by reference in its entirety.
[0143] When more than one biomarker is measured, individual biomarkers can be measured on samples obtained at the same time, or they can be determined from samples obtained at different times (for example, an anterior or posterior). Individual biomarkers can also be measured on the same body fluid samples or different body fluid samples. For example, a renal biomarker can be measured in a serum or plasma sample and another renal biomarker can be measured in a urine sample. In addition, the assignment of a possibility may combine a renal biomarker assay measurement with time variations in one or more additional variables. B. Detectable Markers
[0144] The generation of a detectable signal from the detectable marker can be performed using various optical, acoustic and electrochemical methods. Examples of detection modes include, but are not limited to, fluorescence, radiochemical detection, reflectance, absorbance, amperometry, conductance, impedance, interferometry, ellipsometry, etc. In some of these methods, the solid phase antibody can be coupled to a transducer (for example, a diffraction grid, electrochemical sensor, etc.) for generating a signal, while in others, a signal is generated by a transducer that is spatially separated from the solid phase antibody (for example, a fluorimeter which employs an excitation light source and an optical detector). This list is not intended to be limiting. Antibody-based biosensors can also be used to determine the presence or amount of analytes that optionally eliminate the need for a labeled molecule.
[0145] Biological assays require detection methods, and one of the most common methods for quantifying assay measurements is to conjugate a detectable marker for a nucleic acid or protein that has an affinity for one of the components of the biological system being studied. The detectable markers used in the immunoassays described above may include, but are not limited to, molecules which are themselves detectable (e.g., fluorescent fractions, electrochemical markers, ecl (electrochemical luminescence) markers, metal chelates, colloidal metallic particles, etc. .), as well as molecules that can be detected indirectly through the production of a detectable reaction product (for example, enzymes such as horseradish peroxidase, alkaline phosphatase, etc.), or through the use of a specific binding molecule that can be detectable in itself (for example, a labeled antibody that binds to the second antibody, biotin, digoxigenin, maltose, oligohistidine, 2,4-dintrobenzene, phenylarsenate, ssDNA, dsDNA, etc.).
[0146] The preparation of solid phases and detectable marker conjugates often includes the use of chemical cross-linking agents. Crosslinking reagents can involve at least two reactive groups, and are generally divided into homofunctional crosslinkers (containing identical reactive groups) and heterofunctional crosslinkers (containing non-identical reactive groups). Homobifunctional crosslinkers that are coupled through amines, sulfhydryls or react non-specifically are available from many commercial sources. Maleimides, alkyl and aryl halides, alpha-haloacyls and pyridyl disulfides are reactive thiol groups and are believed to react with sulfhydryl to form thiol ether bonds, while pyridyl disulfide reacts with sulfhydryl to produce disulfide mixed. The cleavable disulfide product is pyridyl. Imidoesters are also very useful for protein-protein cross-linking. A variety of heterobifunctional crosslinkers, each combining different attributes for successful conjugation, is commercially available. C. Hyaluronic Acid Tests
[0147] Urinary hyaluronic acid can be determined first by collecting the null urine specimens (clean collection) that are stored at - 20 ° C until testing. The HA assay can be based on an ELISA plate-based assay for hyaluronic acid using the G1 domain region of biotinylated proteoglycans (HA binding). Fosang et al. Matrix, 10: 306-313 (1990). In one embodiment, the assay can be modified using 96-well microtiter plates coated with HA of human umbilical cord (25 μg / ml) which are incubated with serial dilutions of urine samples in phosphate buffered saline (PBS) + Tween 20 to 0.05% (PBS + Tween), and a biotinylated bovine nasal cartilage HA binding protein (1 μg / ml). After incubation at room temperature for 16 h, the wells were washed with PBS + Tween. The HA binding protein bound to these wells was quantified using an avidinabiotin detection system and ABTS substrate (2,2 'azino-bis (3-ethyl-benzthiazolin-6-sulfonic acid)) (Vector Laboratories, Burlingame, California). A standard plot can be prepared by plotting absorbance (405 nm) versus HA concentrations of human umbilical cord (ng / ml). Using this graph, the HA concentration of each dilution of the urine sample can be calculated. From several of these determinations, the average concentration of HA in each sample was determined and then normalized to the concentration of creatinine (mg / ml) in the urine sample.
[0148] The HA test described above of the invention has been shown to detect bladder cancer with a sensitivity of about 88% using a cutoff of approximately 500 ng / ml. Lokeshwar et al. Methods for the detection and evaluation of bladder cancer of United States Patent 6,350,571 (incorporated herein by reference). Although it is not necessary to understand the mechanism of the invention, it is believed that the cutoff limits for the concentration of HA may vary, and the spread of the population should be taken into account. Setting the cut-off limit for HA concentration to achieve adequate predictors for long-term dialysis may include factors to consider, including, but not limited to, age, diet, protein concentration in the sample, influence of the environment, genetic predisposition, hydration status, medical history, physical condition, sex, weight or similar.
[0149] In one embodiment, the HA test comprises the adsorption of HA on the surface of a solid phase. Although it is not necessary to understand the mechanism of the invention, it is believed that HA can be derived from any convenient source, such as human umbilical cord. The solid phase can be any conventional solid phase, including nitrocellulose and the like, and preferably microtiter wells. After adsorption of HA in the solid phase, the surface of the solid phase is preferably washed with conventional buffers. Because the solid phase still has sites left on its surface that are capable of coupling with HA or other molecules, it is preferable that, before adding the sample, and a blocking substance is added in order to cover a part of the solid phase on which HA has not been adsorbed. Examples of suitable blocking substances include Y-globulin and albumin derived from cows or other animals. Bovine serum albumin is preferred. After blocking free sites of the solid phase, the surface of the solid phase is preferably washed with conventional buffers.
[0150] Then, the HA binding protein (HABP) is added to the coated solid support in the presence of a sample of biological fluid collected from a person suspected of having a kidney injury and incubated under conditions such that the HABP is allowed to bind to the coated HA on the solid support and urinary HA (if any is present). The incubation time and conditions can vary within wide limits, but an incubation time of about 4 to about 16 hours, and an incubation temperature of about 4 ° C to about 37 ° C is satisfactory. However, longer or shorter incubation times and higher or lower incubation temperatures are also possible.
[0151] The HABP suitable for use with the assays of the present invention can be easily purified from a number of sources, such as bovine nasal cartilage (Ten-gblad, Biochim Biophys Acta, 578: 281-289, 1979), cartilage of the pig larynx (Fosang et al., Matrix, 10: 306-313, 1990). After binding HABP to the coated HA and / or to the HA sample, the surface of the solid phase is preferably washed with conventional buffer (s). Then, the amount of HABP bound to the HA coated on the solid support is determined. Preferably, HABP is biotinylated and bound HABP is visualized after incubation with an avidin-enzyme conjugate and any substrate for the enzyme that generates a colored product. This detection system does not use radioactivity since one marker, or multiple markers (that is, enzyme molecules) are immobilized for each HABP attached to the solid support, and the signal (that is, the color product) is amplified through rotation. (turnover) of the enzyme. However, any conventional marker system can be used in conjunction with HABP.
[0152] Examples of suitable marker systems include enzymes, fluorescence, chemiluminescence, enzyme-substrate, isotope markers, radiolabels and the like. Preferably, the determination of the amount of HABP bound to the HA coated on the solid support is done through an avidin-biotin detection system. Another useful marker system employs keratin sulfate and antibodies reactive to keratin sulfate. Urinary HA levels can usefully be determined using a microtiter plate reader, and can be extrapolated from a standard plot. The amount of HABP coupled with the coated HA can then be correlated with the existence of bladder cancer in the patient from whom the biological fluid sample was taken.
[0153] For the HA assay, purified hyaluronic acid is preferably used as a standard.
[0154] The HA binding fragments used in the above assay can be isolated from human umbilical cord HA (about 500 mg) by digestion with 20,000 testicular hyaluronidase units (Sigma Chemical Co., St. Louis, MO) at 37 ° C for different time intervals. The generated HA fragments were separated on a Sephadex G-50 column (1.5 x 120 cm). Fractions of ten ml were collected and tested for the content of uronic acid (Bitter and Muir, The reaction of modifying uronic acid carbazole. Anal. Bio-chem., 4: 330-334, 1962). The fractions were combined to generate three preparations, F1, F2 and F3. The number of reduction ends in each fraction was determined using the Dygert assay (Dygert et al, Determination of reducing sugars with improved accuracy Anal Biochem, 13: 367-374, 1965). Since each linear HA polysaccharide or fragment thereof contains a single reduction end, the chain length of each fragment was calculated from the number of reduction ends per mole of uronic acid. The size range of oligosaccharides in each fraction was determined by incorporating 3H-labeled HA (prepared as described in Lokeshwar et al., Ankyrin CD44 binding domain (gp85) is required for the expression of the hyaluronic acid-mediated adhesion function J. Cell Biol., 126 1099-1 109, 1994) during the digestion of HA and analysis of fragments by gel electrophoresis and fluorography.
[0155] Thus, in an embodiment of the present invention, long-term dialysis can be predicted by a quantitative measure of HA in a sample of biological fluid (such as, for example, a urine sample) collected from a patient suspected of having have an injury and / or kidney disease. Any conventional assay methodology can be used to determine the presence and measurement of HA, including radioassays, sandwich assays, inhibition assays and the like. However, HA is preferably measured from a competitive binding assay. More preferably, the assay of the present invention works in the same way as an ELISA assay, but does not make use of antibody completion mechanisms.
[0156] In one embodiment, long-term dialysis can be predicted through a method that comprises: (a) coating a solid support (preferably microtiter wells) with HA; (b) contacting and incubating the HA binding protein (HABP) with the coated solid support in the presence of a biological fluid sample (for example, as a urine sample) collected from a person suspected of having an injury and / or kidney disease, in conditions such that HABP is allowed to bind to the coated HA on the solid support and the HA of the sample (if any is present); (c) determine the amount of HABP bound to the HA coated on the solid support and determine, from there, the amount of HA present in the sample.
[0157] Although it is not necessary to understand the mechanism of the invention, it is believed that when HA is present in the sample, less HABP will bind to the coated HA, as determined by, for example, comparison with a standard. In other words, a reduction in the amount of HABP bound to the coated HA (that is, in comparison with the controls) would mean high HA present in the sample. In one embodiment, elevated urinary AH is predictive of long-term dialysis.
[0158] In one embodiment, the method may further comprise detecting a signal associated with, or produced by, HABP on. While it is not necessary to understand the mechanism of the invention, it is believed that the amount of HABP bound to HA coated on the solid support can be used to determine, from there, the amount of HA present in the sample. For example, a microtiter plate reader can be used to measure the absorbance of the colored product, as an indirect measure of biotinylated HABP attached to the solid support (for example, an avidin-enzyme conjugate and labeled substrate are used to generate the product. colorful). Maximum absorbance can be obtained by incubating wells coated with HA with buffer individually, in the absence of any HA or sample containing HA. A standard graph can then be prepared by plotting the absorbance against ng / well or 0.2 ml HA. Using this standard graph, the HA concentration (ng / ml) in each of the sample dilutions can be calculated. From several of these determinations, the average HA concentration in each sample can be determined. The concentration of creatinine can be determined in such a way that the concentrations of HA can be normalized.
[0159] In one embodiment, the prediction of whether a patient will need long-term dialysis can be determined by the following calculations derived from the level of normalized urinary HA: HA (ng / ml) extrapolated from a stroke chart time x dilution factor / mg / ml of protein in urine. For example, a low absorbance reading would be indicative of a significant amount of HA in the urine sample, which in itself would be indicative of the need for long-term dialysis in the patient. 1. Isolation of HA and HA Fragments from Patients' Urine
[0160] Urine specimens from normal subjects and patients can be concentrated 10 times and dialyzed extensively against PBS. Approximately 2 ml of each of the dialysed specimens (about 20 mg of protein) was applied to a Sepharose 6-CL-B (1.5 x 120 cm) column (Pharmacia, Piscataway, N.J.) equilibrated with PBS. The column was run in PBS at 7 ml / h and fractions of 3.5 ml were collected. Fractions were assayed for HA by the ELISA-like assay as described above. Since the standard globular protein markers and linear polysaccharides, such as HA and HA fragments have different shapes, the column was calibrated using HA from the human umbilical vein (about 2 x 106 D) and HA fragments, F1, F2 and F3.
[0161] The ELISA assay may involve the use of a bio-tinylated HA-binding protein to determine the concentration of HA in urine specimens. Because levels of urinary HA (ie, normally, in amounts of ng) were found to be influenced by the state of hydration and urine production, the levels were normalized to the urinary creatinine content. D. Test Correlations
[0162] In some embodiments, the renal biomarkers assay measurement is / are correlated (s) with one or more future changes in renal function. In one embodiment, risk stratification comprises determining a subject's possibility (that is, for example, the probability) for an improvement in future kidney function.
[0163] In one embodiment, the renal biomarkers assay measurement is / are correlated (s) with a possibility of future improvement in renal function. In one embodiment, the method correlates with a possibility of such a future injury to kidney function. In one embodiment, risk stratification comprises determining a subject's risk for progression to acute renal failure (ARF).
[0164] In one embodiment, the renal biomarkers measurement assay is / are correlated (s) with a possibility of progression to acute renal failure (ARF). In one embodiment, the risk stratification method comprises the determination of a subject's outcome risk.
[0165] In one embodiment, the measurement of the trial is / are correlated (s) with the possibility of the occurrence of a clinical result related to a kidney injury suffered by the subject.
[0166] Consequently, the measured concentration value (s) can each be compared to a threshold value, where either a "positive kidney injury marker" or a "negative kidney injury marker" is identified. In one embodiment, risk stratification comprises determining a subject's risk for future reduced kidney function. In some modalities, the method assigns a possibility, risk, or probability in such a way that an event of interest is more or less likely to occur within 180 days of the time in which the body fluid sample is obtained from the subject. In some embodiments, the assigned possibility, risk, or probability refers to an event of interest that occurs within a period of time including, but not limited to, 18 months, 120 days, 90 days, 60 days, 45 days , 30 days, 21 days, 14 days, 7 days, 5 days, 96 hours, 72 hours, 48 hours, 36 hours, 24 hours, 12 hours, or less. Alternatively, assigning a risk to 0 hours of the time in which the sample of body fluid is obtained from the subject is equivalent to diagnosing a current condition.
[0167] The selection of a diagnostic threshold involves, among other things, the consideration that the likelihood of illness, distribution of true and false diagnoses at different test thresholds, and estimates of the consequences of treatment (or lack of treatment) based on the diagnosis. For example, when considering the administration of a specific therapy, which is highly effective and has a low level of risk, few tests are necessary because doctors can accept substantial diagnostic uncertainty. On the other hand, in situations where treatment options are less effective and at greater risk, doctors often need a greater degree of diagnostic certainty. Thus, a cost / benefit analysis is involved in choosing a diagnostic threshold. 1. Thresholds
[0168] The appropriate thresholds can be determined in a variety of ways. For example, a recommended diagnostic threshold for the diagnosis of acute myocardial infarction uses cardiac troponin, where the diagnostic threshold is defined at the 97.5th percentile of the cardiac troponin concentration measured in a normal population. Another method for determining a diagnostic threshold is to measure serial samples from the same patient, where the previous "baseline" result is used to monitor temporal changes at a level of biomarkers.
[0169] Population studies can also be used to select thresholds. For example, the Receiver Operation Characteristic ("ROC") emerged from the detection signal field developed during World War II for the analysis of radar images and ROC analysis is often used to select a threshold to distinguish a "sick" subpopulation from a "non-sick" subpopulation. Predictive power balances the occurrences of false positives (that is, for example, when the person has positive tests, but does not actually have the disease) and false negatives (that is, for example, when the person has a negative test, which suggests that they are healthy, when they actually have the disease). To draw a ROC curve, the true positive rate (TPR) and false positive rate (FPR) are determined as the decision threshold is varied continuously. Since TPR is equivalent with sensitivity and FPR is equal to (1 - specificity), the ROC plot is sometimes called sensitivity versus plotting (1 - specificity). A perfect test will have an area under the ROC curve of 1.0; a random test will have an area of 0.5. A threshold value is selected to provide an acceptable level of sensitivity and specificity generally determined by adding the specificity values with the sensitivity values. Consequently, the higher the calculated threshold value, the greater the predictive power of the specific test measurement under analysis.
[0170] In this context, "sick" is used to refer to a population with a characteristic (that is, for example, the presence of a disease or condition or occurrence of some result) and "non-sick" population without the same characteristic . Although a single decision threshold is the simple application of this method, multiple decision thresholds can be used. For example, below a first threshold, the absence of disease can be attributed with relatively high confidence, and above a second threshold of the presence of disease can also be attributed with relatively high confidence. Between two thresholds it can be considered indeterminate. This is meant to be exemplary only in nature.
[0171] In addition to value threshold comparisons, other methods for correlating test measurements to the patient's classification (ie, for example, the occurrence or non-occurrence of the disease, the possibility of a result, etc.), include , but are not limited to, decision trees, rule sets, Bayesian methods, and neural network methods. These methods can produce probability values that represent the degree to which a subject or patient belongs to a classification out of a plurality of classifications.
[0172] Multiple thresholds can also be used to assess kidney status in a subject and / or a patient. For example, a multiple threshold method may combine a "first" subpopulation, which is predisposed to one or more future changes in kidney status, the occurrence of an injury, a classification, etc., with a "second" subpopulation which is not so predisposed in a single group. This combination group is then subdivided into three or more equal parts (that is, for example, tertiles, quartiles, quintiles, etc., depending on the number of subdivisions). An odds ratio is assigned to subjects based on which subdivision they fall into. If a tertile modality is considered, the lowest or highest tertile can be used as a reference for comparing the other subdivisions. This reference subdivision is assigned an odds ratio of 1. The second tertile is assigned to an odds ratio that is relative to the first tertile. That is, someone in the second tertile may be 3 times more likely to experience one or more future changes in kidney status compared to someone in the first tertile. The third tertile is also assigned a odds ratio that is relative to the first tertile. 2. Specificity and Sensitivity
[0173] In some modalities, the measured concentration of one or more renal biomarkers, or a composition of such biomarkers, can be treated as continuous variables. For example, any particular concentration of biomarkers can be converted into a corresponding probability of reduced future kidney function for the subject, the occurrence of an injury, a classification, etc. Alternatively, a threshold value can provide an acceptable level. of sensitivity and specificity in separating a population of subjects in "boxes", such as a "first" subpopulation (for example, that is predisposed to one or more future changes in kidney status, the occurrence of an injury, classification, etc. ) and a "second" subpopulation that is not so predisposed.
[0174] In one embodiment, a threshold value is selected to separate a first and a second population with one or more of the following test accuracy measures: i) an odds ratio greater than 1, preferably at least about 2 or more, or about 0.5 or less, more preferably, at least about 3 or more, or about 0.33 or less, even more preferably, at least about 4 or more, or about 0.25 or less, even more preferably, at least about 5 or more or about 0.2 or less, and most preferably, at least about 10 or more, or about 0.1 or less; ii) a specificity greater than 0.5, preferably at least about 0.6, more preferably, at least about 0.7, even more preferably, at least about 0.8, even more preferably, at least about 0.9 and even more preferably, at least about 0.95, with a corresponding sensitivity greater than 0.2, preferably greater than about 0.3, more preferably greater than about 0.4, even more preferably, at least about 0.5, even more preferably, about 0.6, even more preferably, greater than about 0.7, even more preferably, greater than about 0.8, more preferably, greater than about 0.9, and more preferably, greater than about 0.95; iii) a sensitivity greater than 0.5, preferably at least about 0.6, more preferably at least about 0.7, even more preferably, at least about 0.8, even more preferably, at least about 0.9 and even more preferably, at least about 0.95, with a corresponding specificity greater than 0.2, preferably greater than about 0.3, more preferably greater than about 0.4, even more preferably, at least about 0.5, even more preferably, about 0.6, even more preferably, greater than about 0.7, even more preferably, greater than about 0.8, more preferably, greater than about 0.9, and more preferably, greater than about 0.95; iv) at least about 75% sensitivity, combined with at least about 75% specificity, with a positive odds ratio (calculated as sensitivity / (1 - specificity)) greater than 1, at least about 2 , more preferably, at least about 3, even more preferably, at least about 5, and most preferably, at least about 10; or v) a negative chance ratio (calculated as (1 - sensitivity) / specificity) of less than 1, less than or equal to about 0.5, more preferably less than or equal to about 0.3, and more preferably , less than or equal to about 0.1.
[0175] Various measures of test accuracy have been reported and used to determine the effectiveness of a given biomarker. Fischer et al., Intensive Care Med. 29: 1043-1051 (2003). These precision measures include, but are not limited to, sensitivity and specificity, predictive values, odds ratios, odds ratios for diagnosis, and AUC ROC values. For example, the AUC ROC values are equal to the probability that a classifier will classify a randomly chosen positive example greater than a randomly chosen negative. Consequently, an AUC ROC value can be considered as equivalent to the Mann-Whitney U test, whose tests for the mean difference between the scores obtained in the two groups are considered if the groups are continuous data, or for the test of classifications of Wilcoxon.
[0176] As discussed above, suitable tests can present one or more of the following results on these various measures: a specificity greater than 0.5, preferably at least 0.6, more preferably at least 0.7, even more preferably, at least 0.8, even more preferably, at least 0.9 and even more preferably, at least 0.95, with a corresponding sensitivity greater than 0.2, preferably greater than 0.3, more preferably, greater than 0.4, even more preferably, at least 0.5, even more preferably, 0.6, even more preferably, greater than 0.7, even more preferably, greater than 0.8, more preferably, greater than 0, 9, and more preferably, greater than 0.95; a sensitivity greater than 0.5, preferably at least 0.6, more preferably at least 0.7, even more preferably at least 0.8, even more preferably at least 0.9 and most preferably at least 0 .95, with a corresponding specificity greater than 0.2, preferably greater than 0.3, more preferably greater than 0.4, even more preferably at least 0.5, even more preferably 0.6, even more preferably, greater that 0.7, even more preferably, greater than 0.8, more preferably, greater than 0.9, and more preferably, greater than 0.95; at least 75% sensitivity, combined with at least 75% specificity, an ROC curve area greater than 0.5, preferably at least 0.6, more preferably 0.7, even more preferably at least 0 , 8, even more preferably, at least 0.9, and most preferably, at least 0.95; a different odds ratio of 1, preferably at least about 2 or more, or about 0.5 or less, more preferably, at least about 3 or more, or about 0.33 or less, even more preferably , at least about 4 or more, or about 0.25 or less, even more preferably, at least about 5 or more or about 0.2 or less, and most preferably, at least about 10 or more, or about 0.1 or less, with a positive probability ratio (calculated as the sensitivity / (1 specificity)) greater than 1, at least 2, more preferably, at least 3, even more preferably, at least 5, and more preferably, at least 10, and / or a negative probability ratio (calculated as (1 - sensitivity) / specificity) less than 1, less than or equal to 0.5, more preferably, less than or equal to 0.3, and more preferably, less than or equal to 0.1. E. Clinical Evidence Tests
[0177] Additional clinical evidence can be combined with the renal biomarker assay measurement of the present invention, to improve the sensitivity and specificity of correlations for risk stratification, classification, diagnosis and / or prognosis of an injury and / or kidney disease . These include, but are not limited to, other biomarkers related to the kidney condition.
[0178] Examples that recite the name of the common biomarker, followed by the Swiss-Prot entry number for the biomarker or its origin, include but are not limited to: Actin (P68133), adenosine deaminase binding protein (DPP4, P27487); glycoprotein 1 alpha-1-acid (P02763); alpha-1-microglobulin (P02760); Albumin (P02768); An-giotensinogenase (renin, P00797); annexin A2 (P07355); beta-glucuronidase (P08236), B-2-microglobulin (P61679); Beta-galactosidase (P16278); BMP-7 (P18075); brain natretic-peptide (proBNP, BNP-32, NTproBNP; P16860); beta calcium-binding protein (S100-beta, P04271); carbonic anhydrase (Q16790); casein kinase 2 (P68400); Cadherin-3 (P07858); Ceruloplasmin (P00450); Clusterin (P10909); Complement C3 (P01024); cysteine-rich protein (CYR61, 000622); Cytochrome C (P99999), epidermal growth factor (EGF, P01133); endothelin-1 (P05305); Exosomal Fetuin-A (P02765); fatty acid binding protein, heart (FABP3, P05413); fatty acid binding protein, liver (P07148); Ferritin (light chain, P02793, heavy chain P02794); fructose-1,6-bisphosphatase (P09467); GRO-alpha (CXCL1, (P09341); Growth Hormone (P01241), hepatocyte growth factor (P14210); insulin-like growth factor I (P01343); Immunoglobulin G; Immunoglobulin Light Chains (Kappa and Lambda); interferon gamma (P01308); Lysozyme (P61626); Interleukin-1 alpha (P01583); Interleukin-2 (P60568); Interleukin-4 (P60568); Interleukin-9 (P15248); interleukin-12p40 (P29460); Interleukin- 13 (P35225); Interleukin-16 (Q14005); L1 cell adhesion molecule (P32004); Lactate dehydrogenase (P00338); Leucine Aminopeptidase (P28838); Meprin A alpha subunit (Q16819); Meprin A beta subunit (( Q16820); Midkin (P21741); MIP2-alpha (CXCL2, P19875); MMP-2 (P08253); MMP-9 (P14780); netrin-1 (095,631); Neutral endopeptidase (P08473); Osteopontin (P10451); Aantigen renal papillary 1 (RPA1); renal papillary antigen 2 (RPA2); retinol-binding protein (P09455); ribonuclease; calcium-binding A6 proteins S100 (P06703); serum amyloid P component (P02743); Sodium / Hydrogen exchanger isoform (NHE3, P48764), Spermidine / spermine N1-acetyltransferase (P21673); TGF-Beta1 (P01137); Transferrin (P02787); Trefoil Factor 3 (TFF3, Q07654); Toll-like protein 4 (O00206); Total protein; Túbulointerstitial nephritis antigen (Q9UJW2); Uromodu-lina (Tamm-Horsfall protein, P07911). 1. Risk stratification improvements
[0179] For risk stratification purposes, biomarkers of clinical evidence that improve the determination of renal condition include, but are not limited to: Adiponecin A (Q 15848), Alkaline phosphatase (P05186); Aminopeptidase N (P15144); Calbindin D28k (P05937); Cystatin C (P01034), ATPase FIFO subunit 8 (P03928); Gamma-glutamyltransferase (P19440); GSTa (alpha-glutathione-S-transferase, P08263); GSTpi (Glutati-one-S-transferase P; GST-pi class; P09211); IGFBP-1 (P08833); IGFBP-2 (P18065); IGFBP-6 (P24592), integral membrane protein 1 (Itml, P46977); Interleukin-6 (P05231); Interleukin-8 (P10145); Interleukin-18 (Q14116), IP-10 (10 kDa of the interferon-gamma protein induced by, P02778); IRPR (IFRD1, 000458); Isovaleryl-CoA dehydrogenase (IVD, P26440); I-TAC / CXCL11 (O14,625); Keratin 19 (P08727); Kim-1 (hepatitis A virus cell receptor 1, 043656), L-arginine: glycine amidinotransferase (P50440); Leptin (P41159); Lipocalin2 (NGAL, P80188); MCP-1 (P13500); MIG (monocyte Q07325 induced by gamma-interferon); MIP-1a (P10147); MIP-3a (P78556); MIP-1beta (P13236); MIP-1d (Q16663); NAG (N-acetyl-beta-D-glucosaminidase, P54802); organic ion transporter (OCT2, 015244); Osteoprotegerin (O14,788); P8 protein (060356); Plasminogen activator inhibitor 1 (PAI-1, P05121); proANP (1-98) (P01160); Protein phosphatase 1-beta (PPI-beta, P62140); Rab GDI-beta (P50395); Renal Kallikrein (Q86U61); chain of RT1.B-1 (al-fa) of the integral membrane protein (Q5Y7A8); Member of the soluble tumor necrosis factor 1-A receptor superfamily (sTNFR-I, P 19438); superfamily of member 1B of the soluble tumor necrosis receptor factor (sTNFR-II, P20333); tissue inhibitor of metalloprotein ses 3 (TIMP-3, P35625); uPAR (Q03405) can be combined with the kidney injury marker assay measurement of the present invention. F. Evidence of Demographic Information
[0180] Other clinical evidence that can be combined with the measurements of renal biomarkers of the present invention includes demographic information, including but not limited to, weight, race, age, sex, medical history, family history, type of surgery , pre-existing diseases such as aneurysm, congestive heart failure, pre-eclampsia, eclampsia, diabetes mellitus, hypertension, coronary artery disease, proteinuria, kidney failure, or septicemia, type of exposure to a toxin, such as NSAIDs, cyclosporins , tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin), variable clinical aspects (eg blood pressure, temperature, respiration rate), risk score (APACHE score, PREDICT score, TIMI Risk score for UA / NSTEMI, Framingham risk and score), a measure of total protein urine, a glomerular filtration rate, an estimated glomerular filtration rate, a urine production rate, a concentration of creatinine in serum or plasma from, a measurement of papillary renal antigen 1 (RPA1); a measurement of renal papillary antigen 2 (RPA2), a concentration of urinary creatinine, fractional sodium excretion, a concentration of sodium in the urine, a ratio of urine creatinine to serum or plasma creatinine, specific urine severity, a urine osmolality, a ratio of urine nitrogen to plasma urea nitrogen, a plasma BUN to creatnine ratio, and / or a renal failure index calculated as urine sodium / (urine creatinine / plasma creatinine) ). Other measures of renal function that can be combined with the kidney injury marker assay measurement are described below. In: Harrison's Principles of Internal Medicine, 17th Ed., McGraw Hill, New York, pages 1741 1830; and In: Current Medical Diagnosis & Treatment 2008, 47th Ed, McGraw Hill, New York, pages 785815, each of which is incorporated herein by reference in its entirety.
[0181] The combination of measurements of renal biomarkers with measurements of clinical evidence in this way can comprise the use of multivariate logistic regression, loglinear modeling, neural network analysis, n-of-m analysis, decision tree analysis, etc. This list is not intended to be limiting. G. Conventional Kidney Diagnostics
[0182] As noted above, the terms "acute kidney (or kidney) injury" and "acute kidney (or kidney) failure" as used herein are generally defined, in part, in terms of creatinine changes serum from a baseline value. More conventional definitions of ARF have elements in common, including but not limited to, the use of serum creatinine and, often, urine production. Patients may present with renal dysfunction without an available baseline measure of renal function for use in this comparison. In such a case, a baseline serum creatinine value can be estimated, assuming that the patient had a normal GFR. 1. Glomerular Filtration Rate and Creatinine
[0183] Glomerular filtration rate (GFR) is generally defined as the volume of fluid filtered from renal glomerular capillaries (from the kidney) to the Bowman capsule per unit time. The glomerular filtration rate (GFR) can be calculated by measuring any chemical that has a constant level in the blood, and is freely filtered, but is neither reabsorbed nor secreted by the kidneys. GFR is typically expressed in units of ml / min:
[0184] The normalization of GFR for the body surface area, a GFR of approximately 75-100 ml / min per 1.73 m2 can be assumed. The rate, therefore, measured is the amount of substance present in the urine, which originated from a calculated volume of blood.
[0185] There are several different techniques used to calculate or estimate the glomerular filtration rate (GFR or eGFR). In clinical practice, however, creatinine clearance is used to measure the glomerular filtration rate. Creatinine is produced naturally by the body (creatinine is a metabolite of creatine, which is found in muscles). It is filtered freely by the glomeruli, but also actively secreted by the renal tubules in very small amounts such that the creatinine clearance overestimates the actual GFR by 10-20%. This margin of error is acceptable in view of the ease with which creatinine clearance is measured.
[0186] Creatinine clearance (CCr) can be calculated if values for urine creatinine concentration (UCr), urine flow rate (V), and plasma creatinine concentration (PCr) are known. Since the product of the urine concentration and urine flow rate produces the creatinine excretion rate, creatinine clearance is also considered to be your excretion rate (UCrxV) divided by its plasma concentration. This is commonly represented mathematically as:

[0187] Usually a 24-hour urine collection is performed, from an empty bladder one morning to the contents of the bladder the next morning, with a comparative blood test then taken:

[0188] To allow comparison of results between people of different sizes, CCr is often corrected for the body surface area (BSA) and expressed in comparison to the average man as ml / min / 1.73 m2. While most adults have a BSA that approaches 1.7 (1.61.9), extremely obese or thin patients should have their CCr corrected to their actual BSA:

[0189] The accuracy of a measurement of creatinine clearance (even when collection is complete) is limited because as the glomerular filtration rate (GFR) falls, creatinine secretion is increased and therefore the elevation of serum creatinine is lower. Thus, the excretion of creatinine is much greater than the filtered load, resulting in a potentially large overestimation of GFR (as much as a two-fold difference). However, for clinical purposes, it is important to determine whether kidney function is stable or worsening or better. This is often determined by monitoring serum creatinine alone. Like creatinine clearance, serum creatinine will not be an accurate reflection of GFR in the non-steady state condition of ARF. However, the degree to which changes in serum creatinine from baseline will reflect the change in GFR. Serum creatinine is quickly and easily measurable and is specific for kidney function.
[0190] For the purpose of determining urine production, on a ml / kg / h basis, the collection and measurement of urine per hour is adequate. In the event that, for example, only a cumulative 24-h production was available and no patient weight is provided, minor changes to the RIFLE urine production criteria have been described. For example, some have assumed an average patient weight of 70 kg, in which patients are assigned an RIFLE rating based on the following: <35 mL / h (Risk), <21 mL / h (injury) or < 4 mL / h (Insufficiency). Bagshaw et al., Nephrol. Dial. Transplant. 23: 1203-1210 (2008). 2. Selection of Treatment Regime
[0191] Once a renal diagnosis is obtained, the doctor can easily select a treatment regimen that is compatible with the diagnosis, such as initiating renal replacement therapy, removing the distribution of compounds that are known to be harmful to the kidney, kidney transplantation, delaying or avoiding procedures that are known to be harmful to the kidneys, modifying the administration of diuretics, initiating targeted targeted therapy, etc. Several appropriate treatments for numerous diseases have been previously discussed in relation to the diagnostic methods described here. See, for example, the Merck Manual os Diagnosis and Therapy, Ed. 17. Merck Research Laboratories, Whitehouse Station, NJ, 1999. In addition, since the methods and compositions described here provide prognostic information, the renal biomarkers of the present invention can be used to monitor the course of treatment. For example, an improved prognosis state or an aggravated prognosis state may indicate that a particular treatment is or is not effective. IV. Antibodies.
[0192] The antibodies used in the immunoassays described herein, preferably, specifically bind to a kidney injury marker of the present invention. The term "specifically binds" is not intended to indicate that an antibody binds exclusively to its intended target since, as mentioned above, an antibody binds to any polypeptide exhibiting the epitope (s) to which the antibody binds. In contrast, an antibody "specifically binds" if its affinity for the intended target is about 5 times greater when compared to its affinity for the non-target molecule that does not have the appropriate epitope (s) ). Preferably, the affinity of the antibody will be at least about 5 times, preferably, 10 times, more preferably, 25 times, even more preferably, 50 times, and most preferably, 100 times or more, greater for a target molecule than that its affinity for a non-target molecule. In some embodiments, antibodies bind with affinities of at least about 107 M1, and preferably, between about 108 M-1 to about 109 M-1, about 109 M-1 to about 1010 M-1 , or about 1010 M-1 to about 1012 M-1.
[0193] Affinity can be calculated as Kd = koff / kon (koff is the dissociation rate constant, Kon is the association rate constant and Kd is the equilibrium constant). Affinity can be determined at equilibrium by measuring the bound fraction (r) of the labeled ligand in various concentrations (c). The data are plotted using the Scatchard equation: r / c = K (nr): where r = moles of bound ligand / mole of receptor at steady state, c = concentration of free ligand at steady state, K = equilibrium association constant, and n = number of ligand binding sites per receptor molecule. By graphical analysis, r / c is plotted on the Y axis against r on the X axis, producing a Scatchard plot. The measurement of antibody affinity by Scatchard analysis is well known in the art. See, for example, van Erp et al., J. Immunoassay 12: 425-443 (1991); and Nelson et al., Comput. Biomed Methods Programs. 27: 65-68 (1988).
[0194] Numerous publications discuss the use of phage display technology to produce and search polypeptide libraries for binding to a selected analyte. See, for example, Cwirla et al., Proc. Natl. Acad. Sci. USA 87: 6378-6382 (1990); Devlin et al., Science 249: 404-406 (1990); Scott et al, Science 249: 386-388 (1990), and Ladner et al., US Patent No. 5,571,698 (all references hereby incorporated by reference). A basic concept of phage display methods is the establishment of a physical association between the DNA that encodes a polypeptide to be screened and the polypeptide. This physical association is provided by the phage particle, which exhibits a polypeptide as part of a capsid surrounding the phage genome that encodes the polypeptide. The establishment of a physical association between the polypeptides and their genetic material allows the simultaneous mass screening of a large number of phages that carry different polypeptides. The phage exhibiting a polypeptide with affinity for a target binding to the target and these phages are enriched by screening for affinity for the target. The identity of the polypeptides displayed from these phages can be determined from their respective genomes. Using these methods, a polypeptide identified as having a binding affinity for a desired target can then be synthesized in large quantities by conventional means. See, for example, US Patent No. 6,057,098, which is incorporated herein in its entirety, including all tables, figures and claims.
[0195] The antibodies generated by these methods can then be selected first by screening for affinity and specificity with the purified polypeptide of interest and, if necessary, comparing the results with the affinity and specificity of the antibodies with the desired polypeptides. be excluded from the connection. The screening process may involve immobilizing the purified polypeptides in separate wells of microtiter plates. The solution containing a potential antibody or groups of antibodies is then placed in the respective microtiter wells and incubated for about 30 min to 2 h. The wells are then washed and a labeled secondary antibody (for example, an anti-mouse antibody conjugated to alkaline phosphatase, if the induced antibodies are mouse antibodies) is added to the wells and incubated for about 30 min and then washed. The substrate is added to the wells and the color of the reaction will appear where the antibody to the immobilized polypeptide (s) is present.
[0196] The antibodies thus identified can then be further analyzed for affinity and specificity in the selected test project. In the development of immunoassays for the target protein, the purified target protein acts as a standard against which the sensitivity and specificity of the immunoassay is judged using the antibodies that have been selected. Because the binding affinity of various antibodies may be different; certain pairs of antibodies (for example, in sandwich assays) may interfere with each other sterically, etc., the performance of an antibody assay may be a more important measure than the absolute affinity and specificity of an antibody. V. Kits
[0197] In some embodiments, the present invention also contemplates devices and kits for carrying out the methods described herein. Suitable kits comprise sufficient reagents to perform an assay for at least one of the kidney injury markers described, along with instructions for making the described threshold comparisons.
[0198] In certain embodiments, the reagents for carrying out such tests are provided in a test device, and such test devices can be included in such a kit. Preferred reagents can comprise one or more solid phase antibodies, the solid phase antibody comprising the antibody that detects the desired target biomarker (s) attached to a solid support. In the case of sandwich immunoassays, such reagents may also include one or more detectably labeled antibodies, the detectably labeled antibody comprising the antibody that detects the desired target biomarker (s) attached to a detectable marker. Additional optional elements that can be supplied as part of a test device are described below.
[0199] In some embodiments, the present invention provides kits for the analysis of the kidney injury markers described. The kit comprises reagents for the analysis of at least one test sample that comprises at least one kidney injury marker antibody. The kit may also include devices and instructions for performing one or more of the diagnostic and / or prognostic correlations described here. The preferred kits will comprise a pair of antibodies for performing a sandwich assay, or a species labeled for conducting a competitive assay, for the analyte. Preferably, a pair of antibodies comprises a first antibody conjugated to a solid phase and a second antibody conjugated to a detectable marker, wherein each of the first and second antibodies binds to a kidney injury marker. Most preferably, each of the antibodies are monoclonal antibodies. Instructions for using the kit and carrying out correlations may be in the form of a label, which refers to any written or registered material that is attached to, or otherwise accompanies a kit at any time during its manufacture, transportation, sale or use. For example, the term labeling covers advertising leaflets and brochures, packaging materials, instructions, audio or video cassettes, computer discs, as well as writing printed directly on kits.
[0200] In one embodiment, the invention includes diagnostic kits for predicting long-term dialysis. In one embodiment, the kit comprises HA and / or HAase, HABP and a marker or HABP conjugated to a marker, and auxiliary reagents suitable for use in detecting the presence of HA and / or HAase in a biological sample (i.e., for example , a urine sample). An example of a diagnostic kit contemplated by the present invention is a conventional probe-type test device.
[0201] In one embodiment, a probe-like test device can withstand an HA test to predict long-term dialysis. For example, the use of conventional solid-phase methodology in the form of a probe can be used for HA testing, as described above. In one embodiment, the probe can be coated or impregnated with HA, where the probe can be used to test any biological fluid, including, but not limited to, urine. Experimental
[0202] In some embodiments, the present invention is well suited to achieve the objectives and obtain the mentioned purposes and advantages, as well as those inherent to it. The examples presented here are representative of preferred embodiments, are exemplary, and are not intended to be limitations on the scope of the invention. Example 1 Normalized Hyaluronic Acid in Human Urine Samples
[0203] Hyaluronic acid has been determined in human urine, as described above. A time course was generated by the collection and analysis of HA in the urine for two weeks (ie, fourteen days; D1-D14). The data presented shows patients who recover and patients who do not recover within twenty-eight (28) days after having suffered a kidney injury, (ie, for example, R28 = patients who recover, and NR28 = patients who do not recover). During the collection period of fourteen (14) days, the samples were analyzed on day 1 (D1), Day 7 (D7), and Day 14 (D14). See, Figure 1.
[0204] The data shows that for patients who recover, hyaluronic acid was higher in D1 and progressively decreased in D7 and D14. In contrast, for patients who do not recover, hyaluronic acid increased regularly over the same period of time. Clearly, the data suggest that hyaluronic acid is correlated with recovery from kidney injury. Example 2 Absolute Normalized Hyaluronic Acid Levels in Human Urine Samples
[0205] The data in this example examines the differences between the normalized absolute levels of hyaluronic acid above with samples collected in D1, D7, and / or D14 after kidney injury, collected according to Example 1, for patients showing recovery both in 28 days (R28) and in 60 days (R60) after kidney injury, and patients who do not recover (NR28 and NR60).
[0206] Data show that between Day 1 & Day 7, as well as between Day 1 & Day 14, recovering patients demonstrated clear reductions in normalized hyaluronic acid excretion (ie, excretion of acid absolute hyaluronic decreased during this period of time). The difference between Day 7 & Day 14 was, however, negligible meaning that the rate of excretion has not changed. In contrast, in patients who do not recover the difference between Day 1 & Day 7, as well as between Day 1 & Day 14 shows clear increases in the excretion of normalized hyaluronic acid (that is, for example, the excretion of absolute hyaluronic acid increased over this period of time). In addition, the excretion rate did not change between Day 7 & 14. See, Figures 2 and 3. Example 3 Relative Normalized Hyaluronic Acid Levels in Human Urine Samples
[0207] This example redraws the data according to Example 2, to further illustrate the magnitude of the differences between patients who recover and patients who do not recover. In particular, the data are expressed as a percentage (that is, D7 / D1, D14 / D1, D7 / D14, or D14 / D7).
[0208] The data show that in recovering patients, the relative excretion of hyaluronic acid decreases progressively between Day 1 and Day 14, where the relative difference between Day 14 and Day 7 is almost insignificant. This is consistent with the interpretation of the above data which suggests that hyaluronic acid decreases in patients recovering from kidney injury over time. In contrast, the data show that in patients who do not recover, the relative excretion of hyaluronic acid remained high throughout the period of time. This is consistent with the interpretation of the above data which suggests that hyaluronic acid is elevated in patients who do not recover from kidney damage over time. See, Figures, 4 and 5. Example 4 Long-Term Dialysis Forecast at D14 After Kidney Injury
[0209] The data presented in accordance with Example 2 were analyzed and plotted again to assess the relationship between true positives and false positives. In particular, in conditions where there was a persistent elevation of urinary AH / creatinine (that is, the difference between the D1 and D14 measurements), there was a high sensitivity to the prediction that the patient would be on long-term dialysis at D60 after the kidney injury. See, Figure 6. In conclusion, the data suggest that, in patients who demonstrate persistently elevated urinary hypertension between D1-D14 after kidney injury, they will be on dialysis at D60 (and most likely after). Example V TGF-β1 Predicts Post-AKI Renal Recovery
[0210] This study was an aid to a larger multicenter randomized controlled trial that studies the effect of different doses of renal replacement therapy on AKI survival, which included 24 patients.
[0211] Urinary TGF-β1 was significantly higher on Day 14 after AKI initiation in patients who failed to recover renal function by Day 60, compared with those who recovered (p <0.01). See, Figure 7.
[0212] Urinary TGF-β1 values predicted renal recovery on Day 60, using samples collected on Day 14 after AKI initiation and with an area under the Receptor Operator Characteristic (AUC ROC) curve of 0.81 (estimated standard error = 0.09). In addition, if the change in urinary TGFβ1 is considered, from Day 1 to Day 14, the area under the AUC ROC curve increases to 0.84 (p <0.01). TGF-β1 was measured using a commercially available ELISA kit (R&D Systems, Minneapolis, MN). Example VI Death Receiver 5 (DR5) Predicts Post-AKI Renal Recovery
[0213] This study was an aid to a larger multicenter randomized controlled trial that studies the effect of different doses of renal replacement therapy on AKI survival that included 25 subjects.
[0214] Urinary DR5 was significantly higher on Day 14 after the onset of AKI in subjects who were unable to recover renal function by Day 60, compared to those who recovered. See, Table 6.Table 6. DR5 values for recovered and non-recovered renal function by Day 60. (A) Average DR5 values presented for Days 1 and 14, not recovered and recovered. (B) Average values of log DR5 presented for Days 1 and 14, not recovered and recovered.

[0215] Urinary DR5 values predicted renal recovery by Day 60, using samples collected on Day 14 after AKI initiation and having an area under the Receptor Operation Characteristic Curve (AUC ROC) of 0.90 (p <0.02). DR5 was measured using a commercially available test kit (Invitrogen, Carlsbad, CA). The assay system is based on a Luminex® extracellular granule platform that has been multiplexed with 5-plex, + IL-10, TNF-R1 and TNF-R2 inflammatory cytokines.
[0216] Although the invention has been described and exemplified in sufficient detail for those skilled in the art to make and use it, several alternatives, modifications and improvements must be evident without departing from the spirit and scope of the invention. The examples provided here are representative of preferred embodiments, are exemplary, and are not intended to be limitations on the scope of the invention. Modifications to it and other uses will occur to those skilled in the art. These modifications are included within the spirit of the invention and are defined by the scope of the claims.
[0217] It will be readily apparent to one skilled in the art that various substitutions and modifications can be made to the invention described herein without departing from the scope and spirit of the invention.
[0218] All patents and publications mentioned in the specification are indicative of the levels of those skilled in the technique to which the invention belongs. All patents and publications are hereby incorporated by reference to the same extent as if each individual publication were specifically and individually designated to be incorporated by reference.
[0219] The invention described here by way of illustration can be properly practiced in the absence of any element or elements, limitations or limitations that are not specifically described here. Thus, for example, in each case here any of the terms "comprising", "consisting essentially of" and "consisting of" can be replaced by either of the other two terms. The terms and expressions that have been used are used as terms of description and not of limitation, and there is no intention that, in the use of such terms and expressions, any equivalents of the characteristics shown and described or their portions are excluded, but it is recognized that various modifications are possible within the scope of the claimed invention. Thus, it should be understood that, although the present invention has been specifically described by preferred modalities and optional features, the modification and variation of the concepts described herein can be invoked by those skilled in the art, and that such modifications and variations are considered to be part of the scope of the present invention as defined by the appended claims.
[0220] Other modalities are defined in the scope of the following claims.

权利要求:
Claims (8)
[0001]
1. Method for predicting the likelihood of a patient's renal recovery, CHARACTERIZED by the fact that it comprises: a) providing a sample of biological fluid obtained from the patient exhibiting at least one symptom of an acute kidney injury, in which said sample comprises at least one renal biomarker; b) measure a patient's value comprising a urinary hyaluronic acid value in said sample and at least two values of clinical evidence, in which said values of clinical evidence include age and Charlson's comorbidity index; and c) predicting said renal recovery probability for said patient based on said patient value.
[0002]
2. Method, according to claim 1, CHARACTERIZED by the fact that said predicted probability of renal recovery occurs within at least sixty days from the beginning of said acute kidney injury.
[0003]
3. Method, according to claim 1, CHARACTERIZED by the fact that said sample is obtained within at least fourteen days from the beginning of said kidney injury.
[0004]
4. Method, according to claim 1, CHARACTERIZED by the fact that said sample is obtained within one day from the beginning of the said kidney injury.
[0005]
5. Method, according to claim 1, CHARACTERIZED by the fact that said forecast comprises correlating said patient value with a threshold value.
[0006]
6. Method according to claim 5, CHARACTERIZED by the fact that said threshold value comprises a threshold value of urinary hyaluronic acid, for example in which said threshold value of urinary hyaluronic acid is approximately 12 μg / mg of creatinine or where the said urinary hyaluronic acid threshold value comprises an area value under the receiver operating characteristic curve (AUC ROC) of at least 0.70.
[0007]
7. Method according to claim 5, CHARACTERIZED by the fact that said threshold value comprises a threshold value of hyaluronic acid and at least a threshold value of clinical indications, for example in which said threshold value of urinary hyaluronic acid and said at least one threshold value of clinical evidence comprises an area value under the receiver operating characteristic curve (AUC ROC) of at least 0.75.
[0008]
8. Method, according to claim 5, CHARACTERIZED by the fact that said at least two clinical indication values comprise an area value under the receiver operating characteristic curve (AUC ROC) of at least 0.74.

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引用文献:

---

公开号 | 申请日 | 公开日 | 申请人 | 专利标题

---

---

US5223409A|1988-09-02|1993-06-29|Protein Engineering Corp.|Directed evolution of novel binding proteins|

---

US5939272A|1989-01-10|1999-08-17|Biosite Diagnostics Incorporated|Non-competitive threshold ligand-receptor assays|

---

US5028535A|1989-01-10|1991-07-02|Biosite Diagnostics, Inc.|Threshold ligand-receptor assay|

---

US5922615A|1990-03-12|1999-07-13|Biosite Diagnostics Incorporated|Assay devices comprising a porous capture membrane in fluid-withdrawing contact with a nonabsorbent capillary network|

---

WO1992005282A1|1990-09-14|1992-04-02|Biosite Diagnostics, Inc.|Antibodies to complexes of ligand receptors and ligands and their utility in ligand-receptor assays|

---

US5955377A|1991-02-11|1999-09-21|Biostar, Inc.|Methods and kits for the amplification of thin film based assays|

---

WO1992018868A1|1991-04-10|1992-10-29|Biosite Diagnostics Incorporated|Crosstalk inhibitors and their uses|

---

AU1911592A|1991-04-10|1992-11-17|Biosite Diagnostics Incorporated|Novel conjugates and assays for simultaneous detection of multiple ligands|

---

US6019944A|1992-05-21|2000-02-01|Biosite Diagnostics, Inc.|Diagnostic devices and apparatus for the controlled movement of reagents without membranes|

---

US6143576A|1992-05-21|2000-11-07|Biosite Diagnostics, Inc.|Non-porous diagnostic devices for the controlled movement of reagents|

---

US5494829A|1992-07-31|1996-02-27|Biostar, Inc.|Devices and methods for detection of an analyte based upon light interference|

---

US5824799A|1993-09-24|1998-10-20|Biosite Diagnostics Incorporated|Hybrid phthalocyanine derivatives and their uses|

---

US6350571B1|1996-02-01|2002-02-26|Vinata B. Lokeshwar|Methods for detection and evaluation of bladder cancer|

---

US6113855A|1996-11-15|2000-09-05|Biosite Diagnostics, Inc.|Devices comprising multiple capillarity inducing surfaces|

---

US5947124A|1997-03-11|1999-09-07|Biosite Diagnostics Incorporated|Diagnostic for determining the time of a heart attack|

---

US6057098A|1997-04-04|2000-05-02|Biosite Diagnostics, Inc.|Polyvalent display libraries|

---

CN101393165A|2007-09-20|2009-03-25|复旦大学附属华山医院|Method for detecting discrepancy expressed protein spectrum in blood serum sample of diabetes and kidney disease patient|

---

JP4423375B2|2008-02-29|2010-03-03|国立大学法人名古屋大学|Biomarker for estimating acute kidney injury and prognosis and its use|

---

US20090239242A1|2008-03-18|2009-09-24|Biotrin Intellectual Properties Limited|Method for the early identification and prediction of kidney injury|

---

EP3273246A1|2008-08-28|2018-01-24|Astute Medical, Inc.|Methods and compositions for diagnosis and prognosis of renal injury and renal failure|

---

CA2735590A1|2008-08-29|2010-03-04|Astute Medical, Inc.|Methods and compositions for diagnosis and prognosis of renal injury and renal failure|

---

US8501489B2|2008-09-26|2013-08-06|University of Pittsburgh—of the Commonwealth System of Higher Education|Urinary biomarkers to predict long-term dialysis|

---

US20110207161A1|2008-10-21|2011-08-25|Astute Medical, Inc.|Methods and compositions for diagnosis and prognosis of renal injury and renal failure|

---

CA2743253A1|2008-11-22|2010-05-27|Astute Medical, Inc.|Methods and compositions for diagnosis and prognosis of renal injury and renal failure|

---

CN104483488A|2009-08-28|2015-04-01|阿斯图特医药公司|Methods and compositions for diagnosis and prognosis of renal injury and renal failure|

---

CA2784889C|2009-12-20|2018-06-19|Astute Medical, Inc.|Methods and compositions for diagnosis and prognosis of renal injury and renal failure|EP3797591A1|2009-04-29|2021-03-31|Amarin Pharmaceuticals Ireland Limited|Stable pharmaceutical composition and methods of using same|

---

KR101357438B1|2009-04-29|2014-02-06|아마린 코포레이션 피엘씨|Pharmaceutical compositions comprising epa and a cardiovascular agent and methods of using the same|

---

EP2480248B1|2009-09-23|2015-09-02|Amarin Pharmaceuticals Ireland Limited|Pharmaceutical composition comprising omega-3 fatty acid and hydroxy-derivative of a statin and methods of using same|

---

US20130282390A1|2012-04-20|2013-10-24|International Business Machines Corporation|Combining knowledge and data driven insights for identifying risk factors in healthcare|

---

WO2013184868A1|2012-06-06|2013-12-12|The Cleveland Clinic Foundation|Prediction of acute kidney injury from a post-surgical metabolic blood panel|

---

KR20210005314A|2012-10-08|2021-01-13|리립사, 인크.|Potassium-binding agents for treating hypertension and hyperkalemia|

---

WO2014074552A2|2012-11-06|2014-05-15|Amarin Pharmaceuticals Ireland Limited|Compositions and methods for lowering triglycerides without raising ldl-c levels in a subject on concomitant statin therapy|

---

US20140187633A1|2012-12-31|2014-07-03|Amarin Pharmaceuticals Ireland Limited|Methods of treating or preventing nonalcoholic steatohepatitis and/or primary biliary cirrhosis|

---

US9452151B2|2013-02-06|2016-09-27|Amarin Pharmaceuticals Ireland Limited|Methods of reducing apolipoprotein C-III|

---

BR112015023706A2|2013-03-15|2017-07-18|Sera Prognostics Inc|panel of isolated biomarkers, method of determining the likelihood of preterm birth, method of predicting gab, method of predicting time of delivery and method of determining probability for normal birth.|

---

US10966968B2|2013-06-06|2021-04-06|Amarin Pharmaceuticals Ireland Limited|Co-administration of rosiglitazone and eicosapentaenoic acid or a derivative thereof|

---

WO2014210031A1|2013-06-25|2014-12-31|University Of Pittsburgh - Of The Commonwealth System Of Higher Education|Proteomic biomarkers of sepsis in elderly patients|

---

GB201317621D0|2013-10-04|2013-11-20|Randox Teoranta|Kidney disease biomarker|

---

US10561631B2|2014-06-11|2020-02-18|Amarin Pharmaceuticals Ireland Limited|Methods of reducing RLP-C|

---

US20180038873A1|2015-02-05|2018-02-08|University Of Florida Research Foundation, Inc.|Use of nhe3 as a biomarker for radiation biodosimetry|

---

KR20200013721A|2017-05-31|2020-02-07|마아즈, 인코오포레이티드|How to diagnose and treat chronic kidney disease|

---

CN111936859A|2018-01-19|2020-11-13|马斯公司|Biomarkers and classification algorithms for chronic kidney disease in cats|

---

US11058661B2|2018-03-02|2021-07-13|Amarin Pharmaceuticals Ireland Limited|Compositions and methods for lowering triglycerides in a subject on concomitant statin therapy and having hsCRP levels of at least about 2 mg/L|

---

WO2020006571A1|2018-06-29|2020-01-02|pulseData Inc.|Machine learning systems and methods for predicting risk of renal function decline|

---

JP2021532344A|2018-07-14|2021-11-25|マース インコーポレーテッドMars Incorporated|Biomarkers and test models for chronic kidney disease|

---

CN112218630A|2018-09-24|2021-01-12|阿马里纳药物爱尔兰有限公司|Method of reducing the risk of a cardiovascular event in a subject|

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CN109738931A|2018-12-18|2019-05-10|浙江瑞派医疗科技有限公司|A kind of glomerular filtration rate detection device|

---

WO2021247550A1|2020-06-01|2021-12-09|Mars, Incorporated|System and method for chronic kidney disease of a dog|

---

RU2761738C1|2021-06-07|2021-12-13|Алина Владимировна Еремеева|Method for selection of children with onset of acute pyelonephritis for the course of anti-relapse therapy of pyelonephritis|

法律状态:
2018-04-03| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|

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2019-07-23| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|

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2021-01-12| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|

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2021-02-23| B16A| Patent or certificate of addition of invention granted|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 19/09/2011, OBSERVADAS AS CONDICOES LEGAIS. |

优先权:

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申请号 | 申请日 | 专利标题

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US38623010P| true| 2010-09-24|2010-09-24|

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US61/386,230|2010-09-24|

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US13/235,005|US10557856B2|2010-09-24|2011-09-16|Biomarkers of renal injury|

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US13/235,005|2011-09-16|

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PCT/US2011/052082|WO2012040073A2|2010-09-24|2011-09-19|Biomarkers of renal injury|

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