Sections

Sections Novel Biomarkers of Kidney Function
Introduction and Overview
Characteristics of an Ideal Marker for Kidney Disease
Biomarkers of Acute Kidney Injury
Biomarkers of Chronic Kidney Disease
Biomarkers of Nephrotoxicity
Biomarkers of Glomerular Diseases
Biomarkers of ADPKD
Conclusion
Show All
References

Introduction and Overview

A biomarker (biologic marker) is a measurable indicator of a specific biological state, particularly one relevant to the risk for, presence of, or stage of a disease. Although historically the term often referred to a physical trait or physiological metric, it now typically refers to products of genomic, metabolomic, and proteomic research.^[1] Clinically, biomarkers can be used to screen for, diagnose, or monitor the activity of diseases as well as guide molecularly targeted therapy or assess therapeutic response.^[2]

The National Institutes of Health (NIH) Biomarkers Definitions Working Group has defined a biomarker as, “a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention."^[3]

Biomarker discovery is complex and involves many phases. The biomarker discovery process has been described as having the following six stages, each of which has its own challenges^[1]:

Discovery
Qualification
Verification
Research assay optimization
Clinical validation
Commercialization

Ideal biomarkers have the following general characteristics^[4]:

Noninvasive, easily measured, inexpensive, and produce rapid results
Readily available sources, such as blood or urine
High sensitivity to allow early detection, and no overlap in values between diseased patients and healthy controls
High specificity, being greatly upregulated (or downregulated) specifically in diseased samples, and unaffected by comorbid conditions
Levels that vary rapidly to reflect disease severity and in response to treatment
Levels that aid in risk stratification and possess prognostic value in terms of hard clinical outcomes
Are biologically plausible and provide insight into the underlying disease mechanism

Biomarkers of kidney function can be used to estimate the severity and nature of kidney injury. Conventional biomarkers for kidney function include serum creatinine (SCr), urine output (changes in which may precede biochemical changes), and urine microscopy. Serum creatinine remains the most commonly used biomarker of kidney function despite its known limitations:

Serum creatinine level is influenced by multiple factors extrinsic to the kidney (ie, age, sex, muscle mass, muscle metabolism, diet, medications, amputations, hydration status).
Serum creatinine is reflective of glomerular filtration rate (GFR) under steady-state conditions but has less utility in the context of decreasing kidney function. In acute kidney injury (AKI), the serum creatinine level can take several hours or days to reach a new steady state and does not reflect the true decrease in GFR. An increase in the serum creatinine level represents a delayed indication of a functional change in GFR that lags behind structural changes that occur early in AKI.
Serum creatinine may not become elevated before substantial kidney function has been lost due to renal reserve.
Serum creatinine measurement is not reliably indicative of underlying pathophysiology (ie, it does not allow differentiation of hemodynamically mediated changes in kidney function, such as prerenal azotemia from intrinsic renal failure or obstructive uropathy from structural kidney damage).
Creatinine production is decreased in sepsis. ^[5]
Hypervolemia, which is common in critically ill patients, can lead to spuriously low creatinine levels. ^[6]

Given the limitations of serum creatinine as a biomarker of kidney function, different urinary and serum proteins, molecules, and, most recently, microRNAs have been rigorously investigated over the past decade as possible biomarkers for kidney disease.

Although a comprehensive discussion of individual biomarkers is beyond the scope of this review, we will briefly describe select biomarkers under investigation in various renal conditions, including:

AKI
Chronic kidney disease (CKD)
Various forms of glomerulonephritis (GN)
Autosomal dominant polycystic kidney disease (ADPKD)

Characteristics of an Ideal Marker for Kidney Disease

An ideal biomarker for acute kidney injury (AKI) or chronic kidney disease (CKD) should have the following characteristics^[7]:

Changes rapidly and reliably in response to kidney disease
Highly sensitive and specific for AKI and/or CKD
Adequately correlates with degree of kidney injury
Provides risk stratification and prognostic information (severity of kidney disease, need for dialysis, length of hospital stay, and mortality)
Is site-specific (proximal, distal, interstitium, or vasculature) to detect early injury and pathologic changes in specific segments of renal tubules
Relevant among different races and age groups
Indicates the cause of kidney injury or disease (eg, ischemia, toxins, sepsis, cardiovascular disease, diabetic nephropathy, lupus, combined factors)
Is organ-specific and allows differentiation among intrarenal, prerenal, and extrarenal causes of kidney injury
Identifies the duration of kidney failure (AKI versus CKD)
Is amenable to repeated measurement to allow monitoring of response to therapeutic intervention
Provides information on the risk of complications from comorbid conditions (especially in CKD)
Is stable over time across different temperature and pH conditions, with clinically relevant storage conditions
Is noninvasively, rapidly, and easily measurable
Is not affected by drugs or endogenous substances

Biomarkers of Acute Kidney Injury

Because of the significant morbidity associated with AKI in hospitalized patients, the development of novel biomarkers to improve early detection, diagnosis and prognostication is of significant clinical interest. Novel biomarkers of AKI include the following^[8]:

Neutrophil gelatinase-associated lipocalin (NGAL)
Interleukin-18 (IL-18)
Kidney injury molecule 1 (KIM-1)
Liver-type fatty acid–binding protein (L-FABP)
Insulin like growth factor–binding protein 7 (IGFBP7) x tissue inhibitor of metalloproteinases–2 (TIMP-2)
Calprotectin
Urinary angiotensinogen
Urinary microRNA
Cystatin C

Neutrophil Gelatinase-associated Lipocalin

NGAL is a 25-kD protein of the lipocalin family that is widely expressed and functions as a growth and differentiation factor in multiple cell types and also has a role in iron trafficking in renal epithelium.^[9] Up-regulation of NGAL transcription and protein expression occurs as a result of ischemic or nephrotoxic kidney injury, which can be detected by elevations in both urine and plasma NGAL.^[10]The thick ascending limb of the loop of Henle and the intercalated cells of the collecting duct are the primary sites of NGAL production in the kidney.^{[11, 12, 9]} NGAL elevation can be detected as early as 3 hours after injury, peaks in 6-12 hours, and persists for up to 5 days, depending on the severity of injury. ^[13]

In human studies, increased NGAL expression is significantly associated with the development of AKI in the following settings:

Ischemic ^{[14, 10]}, septic, ^{[15, 16]} or post-transplantation AKI ^{[17, 18]}
As an early marker of AKI in pediatric patients undergoing cardiopulmonary bypass surgery ^{[19, 20]}
ST elevation myocardial infarction (STEMI) patients undergoing percutaneous coronary intervention ^{[21, 22]}
Decompensated cirrhosis ^{[23, 24]}

NGAL may reduce injury by inhibiting apoptosis and increasing the normal proliferation of kidney tubule cells. More specifically, NGAL upregulates heme oxygenase-1, which preserves proximal tubule N-cadherin, and subsequently inhibits cell death.^[25]

The functional utility of NGAL as a biomarker for AKI has been evaluated mainly in the following contexts:

Early prediction
Differentiation of underlying pathophysiology
Prediction of progression

Early prediction

NGAL may be a useful biomarker for the early prediction of AKI. Using samples from the Translational Research Investigating Biomarker Endpoints in AKI (TRIBE-AKI) study, researchers tried to determine whether biomarkers measured at the time of first clinical diagnosis of early AKI after cardiac surgery predicted AKI severity. Urinary IL-18, urinary albumin-to-creatinine ratio (ACR), and urinary and plasma NGAL all improved risk classification compared with the clinical model alone, with plasma NGAL performing the best (category-free net reclassification improvement of 0.69, P < 0.0001). The authors concluded that biomarkers measured on the day of AKI diagnosis improve risk stratification and identify patients at higher risk for AKI progression and worse outcomes.^[26]

In a study of 157 adults treated in an emergency department with in 24 hours of poisoning, baseline NGAL levels enabled a more accurate assessment of AKI risk relative to initial creatinine levels; patients with AKI had higher plasma NGAL levels than in those without (median, 310 vs 86 ng/mL; P < 0.001). The researchers concluded that plasma NGAL may serve as a good predictor of AKI in cases of adult poisoning.^[27] Notably, though plasma NGAL may serve as an early biomarker for AKI in high-risk patients, urine NGAL more accurately predicts AKI in patients with underlying CKD.^[28]

Differentiation of underlying pathology

NGAL may aid in the diagnosis of early acute tubular necrosis (ATN) and help differentiate it from other types of AKI. Paragas et al found that following ischemia-reperfusion in a mouse strain containing an NGAL promoter gene linked to sequences encoding a bioluminescent and fluorescence protein, specific cells of the distal nephron were illuminated on imaging, indicating NGAL production at the site of injury. However, no NGAL illumination was seen in the presence of significant prerenal disease. Thus, NGAL may be useful in differentiating prerenal disease from ATN.^[29]

This finding was further studied in post-surgical patients. When urinary NGAL was sampled 2-3 h after general surgery in a prospective study, NGAL levels were elevated only in patients with sustained AKI (mostly likely ATN), while remaining normal in patients with transient AKI (hemodynamic, prerenal).^[30]

NGAL appears to be useful in the differential diagnosis of AKI in cirrhosis, particularly for differentiating ATN from other kidney injuries, such as hepatorenal syndrome (HRS). In a prospective study of 320 patients hospitalized with decompensated cirrhosis with concurrent AKI, urinary NGAL measured at day 3 differentiated ATN from other types of AKI with the greatest accuracy relative to other elevated biomarkers (area under the curve [AUC] 0.87, 95% confidence index [CI]: 0.78-0.95).^[24] Subsequent data has supported the utility of urinary NGAL as an early marker for AKI differentiation and 30-day mortality prediction in decompensated cirrhosis. ^[23]

Prediction of progression

Both plasma and urinary NGAL have been evaluated as a predictor for AKI progression. In a prospective observational study of 361 intensive care unit (ICU) patients, plasma NGAL levels at admission were significantly higher in patients with early (first 48 h of admission) AKI progression. However, when this value was added to a multi-variate model predicting AKI progression, test characteristics were not significantly improved.^[31]

As one of the most promising biomarkers currently under investigation, NGAL has been studied in various populations. However, its utility is limited by nonspecific increases in the setting of systemic inflammation (common in critically ill patients) as well as unpredictable increases in the setting of kidney injury progression.^[32]

A meta-analysis of 52 observational studies (involving 13,040 acutely ill adult patients) demonstrated that both urinary and plasma NGAL concentrations may aid the identification of patients at high risk for AKI, though appropriate cut-off values in different clinical situations remain undefined.^[33] This step will be crucial for validating NGAL as a biomarker.

Interleukin-18

The pro-inflammatory cytokine IL-18 is a candidate biomarker for renal parenchymal injury. IL-18 is formed in the proximal tubules and can be detected in the urine.^[34] In mouse models, IL-18 has been shown to exacerbate tubular necrosis; neutralizing antibodies formed against IL-18 were found to reduce kidney injury.

Parikh et al demonstrated that patients with ATN have significantly higher urine IL-18 levels than control subje–cts or patients with other forms of kidney disease.^[34]In kidney transplant recipients, those patients with delayed graft function in the immediate post-transplantation period had higher urinary IL-18 levels than patients with immediate graft function. Furthermore, patients with ischemia-reperfusion injury, glycerol injection, or cisplatin-induced kidney injury have demonstrated similarly elevated levels of this pro-inflammatory cytokine.^{[35, 36, 37]}

Urinary NGAL and IL-18 have both been evaluated as potential markers in AKI (post–cardiopulmonary bypass) and may have utility as sequential markers: NGAL levels peak within the first 2-4 hours following AKI, while IL-18 peaks at the 12th hour.^[38]

A potential limitation of IL-18 is that it can act as a more generalized marker of inflammation rather than a specific marker of AKI. This is particularly true in elderly populations, who may have baseline decreased kidney function at baseline. A meta-analysis of 7 studies including 2315 patients found urinary NGAL was a more specific marker for AKI prediction relative to IL-18.^[39]

A meta-analysis of 11 studies with 2796 patients showed reasonable results in post–cardiac surgery AKI in pediatric patients, while other studies failed to demonstrate a strong predictive accuracy. Disagreement regarding an appropriate cut-off level of IL-18 may contribute to these conflicting findings.^[40]

Kidney Injury Molecule 1

KIM-1 is a type 1 transmembrane protein containing extracellular mucin and immunoglobulin domains.^[41] This protein has low basal expression in the normal kidney but is up-regulated in the proximal tubule in post–ischemic injury. The extracellular domain of KIM-1 appears in the urine shortly after ischemic injury and can be readily detected using a urinary dipstick, rendering KIM-1 a convenient and readily measurable marker for AKI.^{[42, 43]}

Apart from its potential as a biomarker for ATN, KIM-1 may have a role in determining risk for the development of AKI. In a prospective study that included 123 patients undergoing cardiac surgery, preoperative KIM-1 levels, along with alpha-glutathione-s-transferase (GST), were able to predict future development of stages 1 and 3 AKI.^[44] In a study by Liangos et al., elevated urinary KIM-1 in patients with established AKI was significantly associated with the composite end point of mortality or dialysis, even when adjusted for comorbidities and disease severity.^[45]

Ichimura et al demonstrated that KIM-1 can specifically recognize apoptotic cell surface–specific epitopes expressed by apoptotic tubular epithelial cells and subsequently phagocytose apoptotic bodies and necrotic debris.^[46] Therefore, KIM-1 may play a role in renal remodeling after AKI and offer a target for pharmacological intervention.

In cardiac studies, KIM-1 elevation correlated with increased risk of death or hospitalization independent of estimated glomerular filtration rate (eGFR). After cardiac surgery, both KIM-1 and IL-18 had an AUC of 0.92, though the combination of both biomarkers together was a better predictor among 32 urinary biomarkers.^{[47, 48]}

Liver-type Fatty Acid–Binding Protein

L-FABP is a 14-kD protein that is localized predominantly in the proximal tubule.^[49]Its level in the urine has been noted to be elevated in patients who sustained AKI following cardiac surgery. The L-FABP gene is expressed in the renal cortex and is induced by hypoxia.^[25]In kidney transplant recipients, urinary L-FABP has been noted to strongly correlate with ischemic time and has thus been proposed to be a marker of kidney hypoxia.^[25]

Several studies have shown that L-FABP can predict patient susceptibility to AKI and determine the implications of the injury. A study in critically ill patients with early AKI found that L-FABP improved the prediction model for AKI progression, dialysis, and death within seven days.^[50] More recent data from prospective studies in a cohort of critically ill cardiac patients further support the role of urinary L-FABP as an independent predictor of AKI as well as an independent predictor of long-term adverse outcomes (a composite endpoint of all-cause death, progression to end-stage kidney disease requiring initiation of maintenance dialysis, or kidney transplant).^{[51, 52]}

In a meta-analysis of seven prospective cohort studies, L-FABP detected AKI and predicted the need for renal replacement therapy and in-hospital mortality in hospital-based cohorts of patients at risk of AKI.^[53]In a subsequent systematic review of 1700 patients, the AUC of L-FABP for predicting AKI was 0.72,^[54] suggesting a possible role for urinary L-FABP in improving long-term risk stratification in critically ill patients.

In addition to early AKI prediction, urinary L-FABP may also serve as a biomarker to predict renal recovery. A prospective cohort study of 114 patients with stage 3 AKI (as determined by Acute Kidney Injury Network [AKIN] criteria) found that patients who had renal recovery showed lower initial urinary L-FABP, with an AUC–receiver operating characteristic (ROC) of 0.906 (95% CI: 0.837-0.953). In this study, urinary L-FABP more accurately predicted failure of recovery when compared with a clinical model using APACHE II score combined with ATN severity scoring index (ATN-ISS).^[55]

Urinary Insulin-like Growth Factor–Binding Protein 7 and Tissue Inhibitor of Metalloproteinases–2

After sepsis or ischemic injury, renal tubular cells enter a brief period of cell cycle arrest, a key mechanism implicated in AKI.^[56]In the Sapphire validation study of more than 700 critically ill patients identified in multicenter cohorts, insulin-like growth factor–binding protein 7 (IGFBP-7) and tissue inhibitor of metalloproteinases–2 (TIMP-2), both of which are inducers of G1 cell cycle arrest, were shown to be predictive of AKI, with AUCs of 0.76 and 0.79, respectively.^[57]

The Opal study validated the role of urinary TIMP-2 × IGFBP-7 and found that a cut-off of 0.3 had 89% sensitivity and a cut-off of 2 had 90% specificity in identifying patients at risk for developing stage 2 or 3 AKI within 12 h.^[58]Similarly, the Topaz study found there was a seven-fold higher risk of AKI in critically ill patients with urinary TIMP-2 × IGFBP-7 levels greater than 0.3.^[59]

In the long-term follow-up of the SAPPHIRE validation study, the authors showed that TIMP-2 × IGFBP-7 levels at the time of ICU admission were predictive of a composite of death or receipt of renal replacement therapy during the next 9 months in patients who developed AKI.^[60]

In a study of 50 patients at high risk for AKI who were undergoing cardiac surgery with cardiopulmonary bypass, urinary TIMP-2 and IGFBP7 were sensitive and specific biomarkers to predict AKI early after surgery and predict renal recovery.^[61] Similar test characteristics have been confirmed to predict AKI after severe trauma in a prospective observational study of 88 trauma surgery patients.^[62]

In 2014, the US Food and Drug Administration (FDA) allowed the marketing of a commercial test, NephroCheck, which detects the presence of IGFBP-7 and TIMP-2, to help determine whether certain critically ill hospitalized patients are at risk of developing moderate to severe acute AKI in the 12 hours after testing.^[63]

The clinical utility of urinary TIMP-2 × IGFBP-7 was demonstrated in the PrevAKI trial, which implemented the Kidney Disease Improving Global Outcomes (KDIGO) guidelines in patients undergoing cardiac surgery who were identified as being high risk for AKI based on urinary TIMP-2 × IGFBP-7 levels exceeding 0.3. In those patients, the use of a so-called KDIGO bundle (ie, optimization of volume status and hemodynamic parameters, avoidance of nephrotoxins, and prevention of hyperglycemia) was associated with significantly reduced rates of moderate to severe AKI compared with controls.^[64] A follow-up study found a significant increase in the application of the KDIGO bundle in patients at high risk for AKI progression as determined by a TIMP-2 × IGFBP-7 value of > 0.3, which supports the utility of this test as a risk screening tool in a real-world setting.^[65]

To date, published literature surrounding urinary TIMP-2 × IGFBP-7 focuses predominantly on its role in predicting AKI in ICU and perioperative settings. Validation in other demographics and further studies to evaluate the predictive value of this test for adverse outcomes are needed.^[66]

Calprotectin

Calprotectin is a 24-kDa heterodimer that associates with the cytoskeleton. It is secreted by immune cells as a danger-associated molecular pattern protein.^[67]

In a study of nephron-sparing surgery for kidney tumors using transient clamping of the renal artery, calprotectin levels rose significantly within 2 h and reached a peak in 48 h, and remained elevated for 5 days post-op.^[68]

Several studies have shown a promising role for calprotectin in differentiating prerenal from intrinsic AKI. A multicenter study demonstrated an AUC of 0.94 differentiating patients from prerenal allograft AKI vs intrinsic AKI.^[69] A meta-analysis of 6 studies evaluating urinary calprotectin as a diagnostic tool for differentiation of intrinsic and prerenal AKI included 502 patients and revealed a pooled sensitivity and specificity of 0.09 and 0.93, respectively.^[70]

Although urinary calprotectin shows promise as a good diagnostic tool, results should be interpreted with caution, as calprotectin is increased in several conditions, including rheumatoid arthritis, inflammatory bowel disease, urogenital malignancies, and urinary tract infections. The role of calprotectin in AKI remains poorly defined.^[71]

Urine Angiotensinogen

AGT is a 453 amino acid–long protein cleaved by renin to form angiotensin 1. Increased urine AGT is a promising biomarker for AKI progression in acute decompensated heart failure.^[72]Chen et al reported that AGT outperformed other biomarkers (NGAL, KIM-1, IL-18), with an AUC 0.78 for AKI progression and 0.85 for progression with death.^[73]Further studies investigating the role of AGT in AKI are warranted.

Urine microRNA

MicroRNA are endogenous noncoding RNA molecules containing 18-22 nucleotides. A study of microRNA 21 (miR-21) found that urine and serum miR-21 can predict AKI progression with an AUC of 0.81-0.83; urine miR-21 was a better outcome predictor than plasma miR-21.^[74]Various sets of microRNA have been evaluated and their levels were demonstrably altered several days prior to serum creatinine increase, suggesting they may have utility for predicting AKI in ICU patients.^[75]Indeed, other microRNAs are independent predictors of mortality in AKI patients requiring renal replacement therapy.^[76]

Cystatin C

Cystatin C is a small non-glycosylated protein produced by all human nucleated cells, filtered freely at the glomerulus, and almost completely reabsorbed and metabolized, but not secreted, in the proximal tubule. Cystatin C has a superior correlation with GFR compared with serum creatinine as measured by iohexol clearance.^[77] Given that the half-life of cystatin C is three times less than that of serum creatinine, its serum level will change more rapidly with a decrease in GFR.^[78] However, cystatin C has not been reliably demonstrated to perform better than serum creatinine in early detection of AKI or persistence/progression of kidney injury in the acutely ill population.^[79]

A major advantage of cystatin C is that its levels are independent of muscle mass, which is important in patients with prolonged hospitalizations and associated myopathy. In addition, a study in critically ill patients reported significantly improved achievement of goal vancomycin trough levels using an algorithm based on eGFR calculated from creatinine and cystatin C levels compared with an algorithm based on estimated creatinine clearance.^[80]

Biomarkers of Chronic Kidney Disease

Serum creatinine and albuminuria form the core of most CKD prediction and progression risk models. However, both biomarkers only show alterations relatively late in the disease process and thus, are not suitable for early CKD diagnosis.^[81]

Biomarkers of chronic kidney disease (CKD) include the following:

Cystatin C
β-trace protein (BTP)
Neutrophil gelatinase-associated lipocalin (NGAL)
Kidney injury molecule 1 (KIM-1)
Liver-type fatty acid–binding protein (L-FABP)
Asymmetric dimethylarginine (ADMA)
Uromodulin
MicroRNA

Cystatin C

Cystatin C is a 13-kD cysteine protease inhibitor that has gained popularity for measuring kidney function and determining eGFR. As with serum creatinine, higher cystatin C levels are associated with male sex, greater height and weight, and higher lean body mass.^[82]

Evidence supports the addition of cystatin C measurements to creatinine measurements to calculate eGFR as a confirmatory test for CKD. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) reported that using both creatinine and cystatin C to calculate eGFR provided greater precision and accuracy and resulted in more accurate classification of measured GFR at less than 60 mL/min/1.73 m²—the threshold for the diagnosis of CKD.^[83]

Shlipak et al reported that adding cystatin C levels to calculations of eGFR in CKD provides a more accurate estimate of the risk of death from any cause and, to a lesser extent, the risks of death from cardiovascular causes and kidney failure.^[84]

Notably, when eGFR is calculated using both creatinine and cystatin C, investigators found a consistent linear association with increased risks of death from any cause and from cardiovascular causes for all eGFR levels below approximately 85 mL/min/1.73 m², which is well above the threshold of 60 mL/min/1.73 m²for the detection of CKD with a creatinine-based eGFR.^[84] Subsequent studies in elderly cohorts have found serum cystatin C to be a stronger predictor of all-cause mortality when compared with creatinine.^{[85, 86]}

Equations combining cystatin C and serum creatinine perform better than either measurement alone in diagnosis of CKD. Combining serum creatinine, cystatin C, and urine albumin-to-creatinine ratio also improves risk stratification and assessment of CKD progression and mortality.^[87]

β-Trace Protein

BTP, also known as lipocalin-type prostaglandin D2 synthase, is a lipocalin glycoprotein used to evaluate kidney function. In a report from the mild to moderate kidney disease (MMKD) study group, BTP provided reliable risk prediction for CKD progression.^[88]In a study of more than 800 African Americans with hypertensive CKD, higher BPT level was strongly associated with progression to kidney failure, compared with traditional markers of kidney function such as measured GFR.^[89]Although promising, BTP requires validation in large CKD populations.

Inker et al studied BTP in a pooled database of three populations with CKD and concluded that BTP is less influenced by age, sex, and race than creatinine and is less influenced by race than cystatin C. However, BTP provides less accurate GFR estimates than the CKD-EPI creatinine and cystatin C equations.^[90]

A follow-up study evaluated both a three-marker panel (BTP, b-₂microglobulin (B2M), and cystatin C) as well as a four-marker panel (+ serum creatinine) in a pooled population of seven studies to estimate GFR. The three-marker panel was more accurate than eGFR as determined by cystatin C, with the four-marker panel being as accurate as eGFR via combination of cystatin C and creatinine.^[91] Importantly, these panels did not specify race.

Neutrophil Gelatinase-associated Lipocalin

In addition to its potential role in AKI diagnosis, NGAL may also be a useful biomarker in CKD patients. Studies in a strain of mice that develop severe renal lesions upon nephron reduction have revealed NGAL as an active player in kidney disease progression.^[92]

A cohort study of 160 elderly patients with CKD demonstrated an AUC > 0.8 with a sensitivity of > 70%, suggesting that serum NGAL accurately reflects renal impairment.^[93]

In a cross-sectional study of 80 non-diabetic patients with CKD stages 2–4, serum NGAL was elevated in those with the most advanced CKD.^[43] A recent meta-analysis of the diagnostic value of NGAL in diabetic kidney disease included 19 studies and found favorable test characteristics for both urinary and serum NGAL (serum NGAL pooled sensitivity of 79%, specificity 87%, and urine NGAL pooled sensitivity of 85%, specificity 74%). ^[94]

Moreover, an elevation of urinary and serum NGAL levels has been noted in a wide range of kidney diseases, including IgA nephropathy, autosomal polycystic kidney disease, and diabetic nephropathy.^{[95, 96]}

NGAL is also a promising biomarker for identifying CKD of uncertain etiology, which is becoming epidemic in agricultural communities in Sri Lanka.^[97]

Kidney Injury Molecule 1

When KIM-1 is expressed in renal epithelial cells, mice develop spontaneous and progressive interstitial kidney inflammation with fibrosis leading to renal failure with anemia, proteinuria, hyperphosphatemia, hypertension, cardiac hypertrophy, and death. These findings are comparable to progressive kidney disease in humans.^[98]Consequently, sustained KIM-1 expression may promote kidney fibrosis and provide a mechanistic link between acute and recurrent injury with progressive CKD.

In a retrospective study of patients with non-diabetic proteinuric kidney disease, KIM-1 levels in urine were elevated but subsequently decreased once patients received treatment with angiotensin-converting enzyme inhibitors or a low-sodium diet. These findings suggest a potential role for KIM-1 as a measure of therapeutic efficacy.^[99]

In a study of patients with type 1 diabetes and proteinuria, serum KIM-1 levels at baseline strongly predicted the rate of estimated GFR loss and risk of ESRD during 5-15 years of follow up, identifying KIM-1 as a marker for CKD and predictor of CKD progression.^[100]

Like urinary NGAL, KIM-1 has shown some promise as a potential biomarker in identifying CKD of uncertain etiology in agricultural communities in Sri Lanka.^[97]

In a cohort of 4739 patients, fasting plasma KIM-1 levels were significantly associated with greater eGFR decline (as measured by creatinine or cystatin) over a median follow up of 19.2 years.^[101]

The predictive value of KIM-1 was further demonstrated in the CRIC study, a case-control study of 894 patients with CKD and diabetes, which demonstrated that higher plasma levels of KIM-1 are associated with an increased risk of diabetic kidney disease progression over a median follow up of 8.7 years.^[102]

In addition to KIM-1, the CRIC study found that TNFR-1, TNFR-2, monocyte chemotactic peptide-1 (MCP-1), soluble urokinase receptor (suPAR), and YKL-40 are significantly associated with increased risk of progression of diabetic kidney disease, providing insight into other potential CKD biomarkers.

Liver-type Fatty Acid–Binding Protein

In a study of 50 patients with CKD, the level of L-FABP in urine correlated with the degree of tubulointerstitial damage and urinary protein excretion.^[103]In a prospective study, urinary L-FABP was found to be more sensitive than proteinuria in predicting the progression of CKD.^[104]In 165 patients without albuminuria from a cohort of 227 patients with type 1 diabetes, baseline urinary L-FABP levels predicted the development of micro- and macro-albuminuria, suggesting a potential role in distinguishing patients who may benefit from early preventive therapies.^[105]

Asymmetric Dimethylarginine

ADMA is an endogenously generated methylated arginine that reversibly inhibits nitric oxide synthase. When present in increased quantities, ADMA results in decreased nitric oxide production, which in turn is associated with endothelial dysfunction and kidney damage.^[106]

ADMA has been investigated as a biomarker in CKD and its progression. In a study of early CKD in type 2 diabetics, Hanai et al found that increased plasma levels of ADMA were predictive of nephropathy development and progression.^[107]A prospective study by Ravani et al in patients with CKD found that plasma ADMA levels were inversely correlated with GFR and predicted progression to kidney failure.^[108]

ADMA holds promise as a relevant biomarker for CKD.^[87] ADMA has also been shown to be a significant predictor of cardiovascular outcome and mortality in pre-dialysis and dialysis-dependent patients with CKD.^{[109, 110]}

Uromodulin

Uromodulin (also known as the Tamm–Horsfall protein) is a glycoprotein produced in the tubular cells of the thick ascending limb and early distal tubule that is released into the tubular lumen. CKD patients with interstitial fibrosis and tubular atrophy have lower levels of uromodulin. Thus, uromodulin may represent intact renal mass rather than kidney function.^[111]

Steubl et al showed that plasma uromodulin concentration was a robust marker for intact renal mass and allowed for identification of early stages of CKD.^[112] Further, urinary uromodulin independently predicts rapid kidney function decline (progression to kidney failure or 25% decline of eGFR).^[113]

MicroRNA

There is increasing interest in the role of microRNA in the pathogenesis and progression of CKD. MicroRNA may be a marker of impaired filtration (as microRNAs are cleared renally) and also indicate tubular function (levels change with tubular dysfunction).^[114]

Khurana et al analyzed several other noncoding RNA classes, such as transfer RNAs (tRNAs), tRNA fragments (tRFs), mitochondrial tRNAs, and long intergenic noncoding RNAs (lincRNAs), and identified nearly 30 differentially expressed noncoding RNAs in CKD patients as suitable biomarkers for early diagnosis. Of those, miRNA-181a was the most robust biomarker for CKD.^[115]

Biomarkers of Nephrotoxicity

Novel biomarkers of nephrotoxicity include the following:

N-acetyl-glucosaminidase (NAG)
Glutathione-s-transferase (GST)
Gamma-glutamyl transpeptidase (GGT)
Alanine aminopeptidase (AAP)
Lactate dehydrogenase (LDH)
Kidney injury molecule 1 (KIM-1)

N-acetyl-glucosaminidase (NAG)

NAG is an enzyme found predominantly in lysosomes of the proximal tubular cells and has reemerged as an important nephrotoxicity biomarker.^[116]NAG is a sensitive marker of acute ischemic and oxidative stress within the kidney. Specifically, elevations in urinary concentration of NAG have been demonstrated in mice exposed to gentamicin^[117]and in rats exposed to cisplatin^[118]or lithium^[119]; in the lithium study, antioxidant treatment attenuated the nephrotoxicity.^[119]

Glutathione-s-transferase (GST)

GST represents a family of cytosolic, microsomal, and membrane-bound enzymes. The GST alpha isoform is localized in the proximal tubular cells, while the pi isoform is confined to distal tubular cells. Increased levels of GST in the urine after nephrotoxic injury are attributed to leakage from the tubular epithelial cells into the tubular lumen secondary to cell damage.^[120]

In two strains of rats, GST alpha successfully detected proximal tubular necrosis as early as 48 h after cisplatin-induced injury.^[121]In patients with rheumatoid arthritis, acute tubular injury from methotrexate and disease-modifying anti-rheumatic drugs were excluded by normal GST alpha activity.^[122]KIM-1 and GST alpha proved the most sensitive means of predicting polymyxin-induced nephrotoxicity, outperforming conventional biomarkers such as serum creatinine and blood urea nitrogen.^[123]

Gamma-glutamyl Transpeptidase, Alanine Aminopeptidase, and Lactate Dehydrogenase

GGT, AAP, and LDH are brush border enzymes that are present in the proximal renal tubule and are normally present in urine as a consequence of tubular cell shedding. Following gentamicin treatment in rats, increased levels of AAP and GGT were noted at all time points tested: days 4, 7, 10, and 14. The results suggest that increased levels of AAP and GGT in urine reflect loss of brush border integrity while an increased urinary NAG level is consistent with the autophagic response of the kidney to acute injury.^[124]

Vancomycin-induced acute tubular necrosis in rats was associated with dose-dependent renal injury by pathological assessment and increased urinary excretion of AAP, GGT, and LDH. However, of these, LDH was the most sensitive indicator of AKI and correlated most closely with the extent of acute tubular injury.^[125]

Kidney Injury Molecule 1

In a dose-response study in rats, KIM-1 and the KIM-1/hepatitis A viral cellular receptor-1 (KIM-1/Havcr1) were found to be more sensitive markers of AKI from nephrotoxic chemicals and drugs than were serum urea and creatinine concentrations. In a time course study, urinary KIM-1 was elevated within 24 hours after exposure to gentamicin, mercury, and chromium and remained elevated through 72 hours.^[126]In cases where acute drug exposure caused necrosis of around half of all proximal tubules, urinary KIM-1 levels increased, while serum urea and creatinine and urinary NAG activity did not differ from controls, indicating that these were too insensitive to detect tubular injury.^[73]

Biomarkers of Glomerular Diseases

Novel biomarkers may have a role in the following glomerular disorders:

IgA nephropathy (IgAN)
Membranous nephropathy (MN)
Focal segmental glomerulosclerosis (FSGS)
Lupus nephritis (LN)

IgA Nephropathy

Serum levels of galactose-deficient (Gd)-IgA1 and glycan-specific antibodies directed against the hinge region of Gd-IgA1 represent the most promising candidate biomarkers for IgA nephropathy.^[127]These immune complexes deposit in the glomerular mesangium and induce the mesangioproliferative glomerulonephritis characteristic of IgA nephropathy.

A lectin-based enzyme-linked immunosorbent assay for circulating Gd-IgA1 has 90% specificity and 76% sensitivity for the diagnosis of IgA nephropathy and thus, is one of the best candidates for a new, noninvasive biomarker.^[127]In a study from China, higher levels of Gd-IgA1 were independently associated with a greater risk of deterioration in kidney function and thus with a poor prognosis in IgAN.^[128]

These results were supported by a study assessing the relationship between plasma Gd-IgA1 and complement component C3 in a large cohort of patients (n=1210) with IgAN. This study demonstrated an independent association between Gd-IgA1/C3 ratio and CKD progression independent of clinical characteristics or biopsy results. ^[129]

The combination of serum creatinine and normalized fractional excretion of IgG can be used to stratify patients with IgAN into high and low risk for progression.^[130]The presence of granule membrane protein of 17 kDa (GMP-17)–positive T-lymphocytes is predictive of progression of IgAN.^[131]

Torres et al reported that the ratio of epidermal growth factor (EGF) to monocyte chemotactic peptide-1 (MCP-1) in the urine can be used to predict renal prognosis in IgAN. Patients were divided into tertiles based on the ratio of EGF to MCP-1. Patients in the lowest tertile had a significant decline in kidney function while those in the highest tertile had a 100% renal survival at 48 and 84 months of follow-up.^[132]

Membranous Nephropathy

In 2009, Beck and colleagues identified the M-type phospholipase A2 receptor (PLA2R), a transmembrane receptor that is highly expressed in glomerular podocytes, as a target podocyte antigen that triggers an antibody response in membranous nephropathy. In this study, the levels of anti-PLA2R antibodies, primarily of the IgG4 subclass, were elevated in approximately 60% to 70% of patients with primary membranous nephropathy, and a clear correlation between the antibody titers, clinical disease activity, and response to treatment was demonstrated. In contrast, PLA2R antibodies were not found in serum from patients with membranous nephropathy secondary to lupus or hepatitis B, those with proteinuric conditions other than membranous nephropathy, or in healthy controls.^[133]

Seropositivity develops after clinical membranous nephropathy. Spontaneous or treatment-induced decline or disappearance of circulating anti-PLA₂R antibodies precedes clinical remission by months. In kidney transplant recipients, anti-PLA2R antibodies could be used to diagnose relapsing membranous nephropathy.^[134]Treatment with rituximab reduces antibody titers and proteinuria.^[135]

A second podocyte antigen, the thrombospondin type-1 domain-containing 7A (THSD7A) has gained prominence in recent years. THSD7A is also deposited in the subepithelial region and accounts for up to 5% of cases of idiopathic membranous nephropathy in Western countries.^[136]

Both PLA2R and THSD7A are currently being used to guide diagnosis and treatment of membranous nephropathy.^[137]

Focal Segmental Glomerulosclerosis

Mice exposed to certain forms of suPAR developed foot process effacement, proteinuria, and FSGS-like glomerulopathy. Experimental data indicate that suPAR acts through binding to the podocyte β3 integrin, one of the principal proteins anchoring podocytes to the glomerular basement membrane. The interaction of suPAR and β3 integrin produces structural changes in podocytes, altering the permeability of the glomerular filtration membrane^[138]

In addition, plasmapheresis, which is commonly used to treat recurrent FSGS following kidney transplantation, induced remission and decreased both serum suPAR levels and beta3 integrin activity in a subset of patients with recurrent FSGS.^[139]

Notably, subsequent studies cast doubts on the usefulness of serum suPAR as a diagnostic biomarker for FSGS and its ability to distinguish FSGS from other nephrotic syndromes (eg, minimal change disease) or primary FSGS from secondary FSGS.^{[138, 140, 141, 142, 143]}

Lupus Nephritis

Traditional biomarkers, including elevated serum creatinine, hematuria, and proteinuria remain important biomarkers in the initial diagnostic evaluation of LN. Proteinuria, in particular, is a strong predictor of long-term renal outcomes.^[144] Although multiple novel biomarkers have been proposed to guide therapy for LN, none are routinely used in clinical settings.

Avihingsanon and colleagues reported that urinary messenger RNA (mRNA) levels of chemokine and growth factor genes could identify active class IV LN more accurately than currently available clinical markers, and be used to monitor therapeutic response. In their evaluation of urinary mRNA levels of interferon gamma–induced protein 10 (IP-10), its receptor (CXCR3), transforming growth factor–β (TGF-β), and vascular endothelial growth factor (VEGF), an ROC curve analysis showed that IP-10 had the best discriminative power, with an AUC of 0.89.^[145]

β1-integrin has also been studied as a highly specific marker for class IV LN. Initial studies have shown some correlation.^[146]

Several other biomarkers have been studied for LN, including the following:

Urinary FOXP3 mRNA
Urinary tumor necrosis factor–like weak inducer of apoptosis (TWEAK)
Urinary neutrophil gelatinase-associated lipocalin (NGAL)
Urinary MCP-1
Annexin A1 and A2
Alpha Actinin
Alpha-enolase
Interleukin-6 (IL-6)
Vascular cell adhesion molecule 1 (VCAM-1)
Osteoprotegerin

Of those, urinary NGAL appears most promising. However, multiple biomarker panels may have better predictive value for LN than measurement of individual biomarkers.^{[147, 148]}

Biomarkers of ADPKD

The identification of biomarkers for autosomal dominant polycystic kidney disease (ADPKD) is still in its infancy. In an exploratory study in 2009, Kistler et al identified 197 proteins and peptides whose urinary excretion was significantly different in ADPKD subjects than in healthy controls and patients with other kidney diseases.^[149]Using those findings, they derived a score that could identify patients with ADPKD with good sensitivity and specificity; this score was subsequently validated in a separate cohort.

In a more recent study, Hogan et al examined differential protein abundance on urinary exosome-like vesicles (ELVs) from subjects with ADPKD compared with controls. Of over 2000 ELV proteins studied, 8 showed reduced levels in ADPKD patients (among them, polycystin-1 and polycystin-2). In contrast, the levels of one (transmembrane protein 2 [TMEM2]), were consistently increased. These authors also determined that the ratio of polycystin-1 (PC1) or polycystin-2 (PC2) to MEM2 have utility in diagnosis and monitoring of polycystic kidney disease.^[150]

Beta2 microglobulin (b2MG) and MCP-1 may be useful for detecting rapidly progressive disease. In a cohort of 302 patients with ADPKD, b2MG and MCP-1 showed the strongest association with rapidly progressive disease as assessed by eGFR, with a predictive value comparable to or better than height-adjusted total kidney volume or PKD mutation.^[151]

The following proteins are also under investigation^{[152, 153]}:

Fetuin-A
Plasma copeptin
Secreted frizzled-related protein 4 ^[154]

Conclusion

Biomarker discovery in nephrology is increasingly being revitalized, as advances in the fields of proteomics, genomics, and metabolomics improve the ability of researchers to study various proteins, and these techniques become widely available. Given the significant limitations of current established biomarkers (eg, creatinine and urinary albumin), the results from biomarker discovery studies are much anticipated.

Rifai N, Gillette MA, Carr SA. Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nat Biotechnol. 2006 Aug. 24 (8):971-83. [QxMD MEDLINE Link].
Etzioni R, Urban N, Ramsey S, McIntosh M, Schwartz S, Reid B, et al. The case for early detection. Nat Rev Cancer. 2003 Apr. 3 (4):243-52. [QxMD MEDLINE Link].
Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001 Mar. 69 (3):89-95. [QxMD MEDLINE Link].
Bennett MR, Devarajan P. Characteristics of an Ideal Biomarker of Kidney Diseases. Edelstein CL. Biomarkers of Kidney Disease. 2nd ed. Academic Press; 2017. 1–20.
Doi K, Yuen PS, Eisner C, Hu X, Leelahavanichkul A, Schnermann J, et al. Reduced production of creatinine limits its use as marker of kidney injury in sepsis. J Am Soc Nephrol. 2009 Jun. 20 (6):1217-21. [QxMD MEDLINE Link].
Pickering JW, Ralib AM, Endre ZH. Combining creatinine and volume kinetics identifies missed cases of acute kidney injury following cardiac arrest. Crit Care. 2013 Jan 17. 17 (1):R7. [QxMD MEDLINE Link].
Parikh CR, Koyner JL. Biomarkers in Acute and Chronic Kidney Diseases. Karl Skorecki, Chertow GM, Marsden PA, Taal MW, Yu ASL. Brenner & Rector’s the kidney. 10th ed. Philadelphia: Elsevier, Inc.; 2016. 1: 926.
Kashani K, Cheungpasitporn W, Ronco C. Biomarkers of acute kidney injury: the pathway from discovery to clinical adoption. Clin Chem Lab Med. 2017 Jul 26. 55 (8):1074-1089. [QxMD MEDLINE Link].
Schmidt-Ott KM, Mori K, Li JY, Kalandadze A, Cohen DJ, Devarajan P, et al. Dual action of neutrophil gelatinase-associated lipocalin. J Am Soc Nephrol. 2007 Feb. 18 (2):407-13. [QxMD MEDLINE Link].
Mishra J, Ma Q, Prada A, Mitsnefes M, Zahedi K, Yang J, et al. Identification of neutrophil gelatinase-associated lipocalin as a novel early urinary biomarker for ischemic renal injury. J Am Soc Nephrol. 2003 Oct. 14 (10):2534-43. [QxMD MEDLINE Link].
Paragas N, Kulkarni R, et al. α-Intercalated cells defend the urinary system from bacterial infection. J Clin Invest. 2014 Jul. 124 (7):2963-76. [QxMD MEDLINE Link].
Charlton JR, Portilla D, Okusa MD. A basic science view of acute kidney injury biomarkers. Nephrol Dial Transplant. 2014 Jul. 29 (7):1301-11. [QxMD MEDLINE Link].
Nickolas TL, O'Rourke MJ, Yang J, Sise ME, Canetta PA, Barasch N, et al. Sensitivity and specificity of a single emergency department measurement of urinary neutrophil gelatinase-associated lipocalin for diagnosing acute kidney injury. Ann Intern Med. 2008 Jun 3. 148 (11):810-9. [QxMD MEDLINE Link].
Savran Karadeniz M, Alp Enişte I, Şentürk Çiftçi H, Usta S, Tefik T, Şanlı Ö, et al. Neutrophil Gelatinase-associated Lipocalin Significantly Correlates with Ischemic Damage in Patients Undergoing Laparoscopic Partial Nephrectomy. Balkan Med J. 2019 Feb 28. 36 (2):121-128. [QxMD MEDLINE Link].
Zhang A, Cai Y, Wang PF, Qu JN, Luo ZC, Chen XD, et al. Diagnosis and prognosis of neutrophil gelatinase-associated lipocalin for acute kidney injury with sepsis: a systematic review and meta-analysis. Crit Care. 2016 Feb 16. 20:41. [QxMD MEDLINE Link].
Park HS, Kim JW, Lee KR, Hong DY, Park SO, Kim SY, et al. Urinary neutrophil gelatinase-associated lipocalin as a biomarker of acute kidney injury in sepsis patients in the emergency department. Clin Chim Acta. 2019 Aug. 495:552-555. [QxMD MEDLINE Link].
Liu Y, Li HX, Ying ZW, Guo JJ, Cao CY, Jia W, et al. Serum Neutrophil Gelatinase-Associated Lipocalin and Cystatin C for Assessing Recovery of Graft Function in Patients Undergoing Living-Donor Kidney Transplantation. Clin Lab. 2016. 62 (1-2):155-63. [QxMD MEDLINE Link].
Yeung ACY, Morozov A, Robertson FP, Fuller BJ, Davidson BR. Neutrophil Gelatinase-Associated Lipocalin (NGAL) in predicting acute kidney injury following orthotopic liver transplantation: A systematic review. Int J Surg. 2018 Nov. 59:48-54. [QxMD MEDLINE Link].
Schroeder LW, Buckley JR, Stroud RE, Martin RH, Nadeau EK, Barrs R, et al. Plasma Neutrophil Gelatinase-Associated Lipocalin Is Associated With Acute Kidney Injury and Clinical Outcomes in Neonates Undergoing Cardiopulmonary Bypass. Pediatr Crit Care Med. 2019 Oct. 20 (10):957-962. [QxMD MEDLINE Link].
Zhou F, Luo Q, Wang L, Han L. Diagnostic value of neutrophil gelatinase-associated lipocalin for early diagnosis of cardiac surgery-associated acute kidney injury: a meta-analysis. Eur J Cardiothorac Surg. 2016 Mar. 49 (3):746-55. [QxMD MEDLINE Link].
Merdler I, Rozenfeld KL, Zahler D, Shtark M, Goldiner I, Loewenstein IS, et al. Neutrophil Gelatinase-Associated Lipocalin for the Early Prediction of Acute Kidney Injury in ST-Segment Elevation Myocardial Infarction Patients Treated with Primary Percutaneous Coronary Intervention. Cardiorenal Med. 2020. 10 (3):154-161. [QxMD MEDLINE Link].
Banai A, Rozenfeld KL, Lewit D, Merdler I, Loewenstein I, Banai S, et al. Neutrophil gelatinase-associated lipocalin (NGAL) for the prediction of acute kidney injury in chronic kidney disease patients treated with primary percutaneous coronary intervention. Int J Cardiol Heart Vasc. 2021 Feb. 32:100695. [QxMD MEDLINE Link].
Udgirkar S, Rathi P, Sonthalia N, Chandnani S, Contractor Q, Thanage R, et al. Urinary neutrophil gelatinase-associated lipocalin determines short-term mortality and type of acute kidney injury in cirrhosis. JGH Open. 2020 Oct. 4 (5):970-977. [QxMD MEDLINE Link].
Huelin P, Solà E, Elia C et al. Neutrophil Gelatinase-Associated Lipocalin for Assessment of Acute Kidney Injury in Cirrhosis: A Prospective Study. Hepatology. 2019 Jul. 70 (1):319-333. [QxMD MEDLINE Link].
Yamamoto T, Noiri E, Ono Y, Doi K, Negishi K, Kamijo A, et al. Renal L-type fatty acid--binding protein in acute ischemic injury. J Am Soc Nephrol. 2007 Nov. 18(11):2894-902. [QxMD MEDLINE Link].
Koyner JL, Garg AX, Coca SG, Sint K, Thiessen-Philbrook H, Patel UD, et al. Biomarkers predict progression of acute kidney injury after cardiac surgery. J Am Soc Nephrol. 2012 May. 23(5):905-14. [QxMD MEDLINE Link]. [Full Text].
Ahn JY, Lee MJ, Seo JS, Choi D, Park JB. Plasma neutrophil gelatinase-associated lipocalin as a predictive biomarker for the detection of acute kidney injury in adult poisoning. Clin Toxicol (Phila). 2016. 54 (2):127-33. [QxMD MEDLINE Link].
Yi A, Lee CH, Yun YM, Kim H, Moon HW, Hur M. Effectiveness of Plasma and Urine Neutrophil Gelatinase-Associated Lipocalin for Predicting Acute Kidney Injury in High-Risk Patients. Ann Lab Med. 2021 Jan. 41 (1):60-67. [QxMD MEDLINE Link].
Paragas N, Qiu A, Zhang Q, Samstein B, Deng SX, Schmidt-Ott KM, et al. The Ngal reporter mouse detects the response of the kidney to injury in real time. Nat Med. 2011 Feb. 17(2):216-22. [QxMD MEDLINE Link]. [Full Text].
Au V, Feit J, Barasch J, Sladen RN, Wagener G. Urinary neutrophil gelatinase-associated lipocalin (NGAL) distinguishes sustained from transient acute kidney injury after general surgery. Kidney Int Rep. 2016 May. 1 (1):3-9. [QxMD MEDLINE Link].
Koeze J, van der Horst ICC, Keus F, Wiersema R, Dieperink W, Kootstra-Ros JE, et al. Plasma neutrophil gelatinase-associated lipocalin at intensive care unit admission as a predictor of acute kidney injury progression. Clin Kidney J. 2020 Dec. 13 (6):994-1002. [QxMD MEDLINE Link].
Mårtensson J, Bellomo R. The rise and fall of NGAL in acute kidney injury. Blood Purif. 2014. 37 (4):304-10. [QxMD MEDLINE Link].
Albert C, Zapf A, Haase M et al. Neutrophil Gelatinase-Associated Lipocalin Measured on Clinical Laboratory Platforms for the Prediction of Acute Kidney Injury and the Associated Need for Dialysis Therapy: A Systematic Review and Meta-analysis. Am J Kidney Dis. 2020 Dec. 76 (6):826-841.e1. [QxMD MEDLINE Link].
Parikh CR, Jani A, Melnikov VY, Faubel S, Edelstein CL. Urinary interleukin-18 is a marker of human acute tubular necrosis. Am J Kidney Dis. 2004 Mar. 43(3):405-14. [QxMD MEDLINE Link].
Wu H, Craft ML, Wang P, Wyburn KR, Chen G, Ma J, et al. IL-18 contributes to renal damage after ischemia-reperfusion. J Am Soc Nephrol. 2008 Dec. 19(12):2331-41. [QxMD MEDLINE Link]. [Full Text].
Homsi E, Janino P, de Faria JB. Role of caspases on cell death, inflammation, and cell cycle in glycerol-induced acute renal failure. Kidney Int. 2006 Apr. 69(8):1385-92. [QxMD MEDLINE Link].
Melnikov VY, Ecder T, Fantuzzi G, Siegmund B, Lucia MS, Dinarello CA, et al. Impaired IL-18 processing protects caspase-1-deficient mice from ischemic acute renal failure. J Clin Invest. 2001 May. 107(9):1145-52. [QxMD MEDLINE Link]. [Full Text].
Gonzalez F, Vincent F. Biomarkers for acute kidney injury in critically ill patients. Minerva Anestesiol. 2012 Dec. 78 (12):1394-403. [QxMD MEDLINE Link].
Gan J, Zhou X. Comparison of urine neutrophil gelatinase-associated lipocalin and interleukin-18 in prediction of acute kidney injury in adults. Medicine (Baltimore). 2018 Sep. 97 (39):e12570. [QxMD MEDLINE Link].
Lin X, Yuan J, Zhao Y, Zha Y. Urine interleukin-18 in prediction of acute kidney injury: a systemic review and meta-analysis. J Nephrol. 2015 Feb. 28 (1):7-16. [QxMD MEDLINE Link].
Ichimura T, Bonventre JV, Bailly V, Wei H, Hession CA, Cate RL, et al. Kidney injury molecule-1 (KIM-1), a putative epithelial cell adhesion molecule containing a novel immunoglobulin domain, is up-regulated in renal cells after injury. J Biol Chem. 1998 Feb 13. 273(7):4135-42. [QxMD MEDLINE Link].
Han WK, Bailly V, Abichandani R, Thadhani R, Bonventre JV. Kidney Injury Molecule-1 (KIM-1): a novel biomarker for human renal proximal tubule injury. Kidney Int. 2002 Jul. 62(1):237-44. [QxMD MEDLINE Link].
Vaidya VS, Ford GM, Waikar SS, Wang Y, Clement MB, Ramirez V, et al. A rapid urine test for early detection of kidney injury. Kidney Int. 2009 Jul. 76(1):108-14. [QxMD MEDLINE Link]. [Full Text].
Koyner JL, Vaidya VS, Bennett MR, Ma Q, Worcester E, Akhter SA, et al. Urinary biomarkers in the clinical prognosis and early detection of acute kidney injury. Clin J Am Soc Nephrol. 2010 Dec. 5(12):2154-65. [QxMD MEDLINE Link]. [Full Text].
Liangos O, Perianayagam MC, Vaidya VS, Han WK, Wald R, Tighiouart H, et al. Urinary N-acetyl-beta-(D)-glucosaminidase activity and kidney injury molecule-1 level are associated with adverse outcomes in acute renal failure. J Am Soc Nephrol. 2007 Mar. 18 (3):904-12. [QxMD MEDLINE Link].
Ichimura T, Asseldonk EJ, Humphreys BD, Gunaratnam L, Duffield JS, Bonventre JV. Kidney injury molecule-1 is a phosphatidylserine receptor that confers a phagocytic phenotype on epithelial cells. J Clin Invest. 2008 May. 118(5):1657-68. [QxMD MEDLINE Link]. [Full Text].
Ghatanatti R, Teli A, Tirkey SS, Bhattacharya S, Sengupta G, Mondal A. Role of renal biomarkers as predictors of acute kidney injury in cardiac surgery. Asian Cardiovasc Thorac Ann. 2014 Feb. 22 (2):234-41. [QxMD MEDLINE Link].
Arthur JM, Hill EG, Alge JL, Lewis EC, Neely BA, Janech MG, et al. Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery. Kidney Int. 2014 Feb. 85 (2):431-8. [QxMD MEDLINE Link].
Maatman RG, van de Westerlo EM, van Kuppevelt TH, Veerkamp JH. Molecular identification of the liver- and the heart-type fatty acid-binding proteins in human and rat kidney. Use of the reverse transcriptase polymerase chain reaction. Biochem J. 1992 Nov 15. 288 ( Pt 1):285-90. [QxMD MEDLINE Link]. [Full Text].
Parr SK, Clark AJ, Bian A, Shintani AK, Wickersham NE, Ware LB, et al. Urinary L-FABP predicts poor outcomes in critically ill patients with early acute kidney injury. Kidney Int. 2015 Mar. 87 (3):640-8. [QxMD MEDLINE Link].
Naruse H, Ishii J, Takahashi H, Kitagawa F, Nishimura H, Kawai H, et al. Predicting acute kidney injury using urinary liver-type fatty-acid binding protein and serum N-terminal pro-B-type natriuretic peptide levels in patients treated at medical cardiac intensive care units. Crit Care. 2018 Aug 18. 22 (1):197. [QxMD MEDLINE Link].
Naruse H, Ishii J, Takahashi H, Kitagawa F, Nishimura H, Kawai H, et al. Urinary Liver-Type Fatty-Acid-Binding Protein Predicts Long-Term Adverse Outcomes in Medical Cardiac Intensive Care Units. J Clin Med. 2020 Feb 10. 9 (2):[QxMD MEDLINE Link].
Susantitaphong P, Siribamrungwong M, Doi K, Noiri E, Terrin N, Jaber BL. Performance of urinary liver-type fatty acid-binding protein in acute kidney injury: a meta-analysis. Am J Kidney Dis. 2013 Mar. 61(3):430-9. [QxMD MEDLINE Link]. [Full Text].
Ho J, Tangri N, Komenda P, Kaushal A, Sood M, Brar R, et al. Urinary, Plasma, and Serum Biomarkers' Utility for Predicting Acute Kidney Injury Associated With Cardiac Surgery in Adults: A Meta-analysis. Am J Kidney Dis. 2015 Dec. 66 (6):993-1005. [QxMD MEDLINE Link].
Wang L, Xue J, Chen C, Zhang Z, Deng Z, Sun Z, et al. Urinary liver-type fatty acid-binding protein predicts recovery from acute kidney injury. Clin Nephrol. 2015 Nov. 84 (5):255-61. [QxMD MEDLINE Link].
Mori K, Lee HT, Rapoport D, Drexler IR, Foster K, Yang J, et al. Endocytic delivery of lipocalin-siderophore-iron complex rescues the kidney from ischemia-reperfusion injury. J Clin Invest. 2005 Mar. 115(3):610-21. [QxMD MEDLINE Link]. [Full Text].
Kashani K, Al-Khafaji A, Ardiles T, Artigas A, Bagshaw SM, et al. Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit Care. 2013 Feb 6. 17 (1):R25. [QxMD MEDLINE Link]. [Full Text].
Hoste EA, McCullough PA, Kashani K, Chawla LS, Joannidis M, Shaw AD, et al. Derivation and validation of cutoffs for clinical use of cell cycle arrest biomarkers. Nephrol Dial Transplant. 2014 Nov. 29 (11):2054-61. [QxMD MEDLINE Link].
Bihorac A, Chawla LS, Shaw AD, et al. Validation of cell-cycle arrest biomarkers for acute kidney injury using clinical adjudication. Am J Respir Crit Care Med. 2014 Apr 15. 189 (8):932-9. [QxMD MEDLINE Link].
Koyner JL, Shaw AD, Chawla LS, Hoste EA, Bihorac A, Kashani K, et al. Tissue Inhibitor Metalloproteinase-2 (TIMP-2)⋅IGF-Binding Protein-7 (IGFBP7) Levels Are Associated with Adverse Long-Term Outcomes in Patients with AKI. J Am Soc Nephrol. 2015 Jul. 26 (7):1747-54. [QxMD MEDLINE Link].
Meersch M, Schmidt C, Van Aken H, Martens S, Rossaint J, Singbartl K, et al. Urinary TIMP-2 and IGFBP7 as early biomarkers of acute kidney injury and renal recovery following cardiac surgery. PLoS One. 2014. 9(3):e93460. [QxMD MEDLINE Link]. [Full Text].
Hatton GE, Wang YW, Isbell KD, Finkel KW, Kao LS, Wade CE. Urinary cell cycle arrest proteins urinary tissue inhibitor of metalloprotease 2 and insulin-like growth factor binding protein 7 predict acute kidney injury after severe trauma: A prospective observational study. J Trauma Acute Care Surg. 2020 Oct. 89 (4):761-767. [QxMD MEDLINE Link].
Lowes R. FDA OKs NephroCheck to Assess Risk for Acute Kidney Injury. Medscape Medical News. Available at https://www.medscape.com/viewarticle/831212. September 5, 2014; Accessed: June 3, 2019.
Meersch M, Schmidt C, Hoffmeier A, Van Aken H, Wempe C, Gerss J, et al. Prevention of cardiac surgery-associated AKI by implementing the KDIGO guidelines in high risk patients identified by biomarkers: the PrevAKI randomized controlled trial. Intensive Care Med. 2017 Nov. 43 (11):1551-1561. [QxMD MEDLINE Link].
Kane-Gill SL, Peerapornratana S, Wong A, Murugan R, Groetzinger LM, Kim C, et al. Use of tissue inhibitor of metalloproteinase 2 and insulin-like growth factor binding protein 7 [TIMP2]•[IGFBP7] as an AKI risk screening tool to manage patients in the real-world setting. J Crit Care. 2020 Jun. 57:97-101. [QxMD MEDLINE Link].
Fan W, Ankawi G, Zhang J, Digvijay K, Giavarina D, Yin Y, et al. Current understanding and future directions in the application of TIMP-2 and IGFBP7 in AKI clinical practice. Clin Chem Lab Med. 2019 Apr 24. 57 (5):567-576. [QxMD MEDLINE Link].
Ehrchen JM, Sunderkötter C, Foell D, Vogl T, Roth J. The endogenous Toll-like receptor 4 agonist S100A8/S100A9 (calprotectin) as innate amplifier of infection, autoimmunity, and cancer. J Leukoc Biol. 2009 Sep. 86 (3):557-66. [QxMD MEDLINE Link].
Ebbing J, Mathia S, Seibert FS, Pagonas N, Bauer F, Erber B, et al. Urinary calprotectin: a new diagnostic marker in urothelial carcinoma of the bladder. World J Urol. 2014 Dec. 32 (6):1485-92. [QxMD MEDLINE Link].
Seibert FS, Rosenberger C, Mathia S, Arndt R, Arns W, Andrea H, et al. Urinary Calprotectin Differentiates Between Prerenal and Intrinsic Acute Renal Allograft Failure. Transplantation. 2017 Feb. 101 (2):387-394. [QxMD MEDLINE Link].
Chen JJ, Fan PC, Kou G, Chang SW, Chen YT, Lee CC, et al. Meta-Analysis: Urinary Calprotectin for Discrimination of Intrinsic and Prerenal Acute Kidney Injury. J Clin Med. 2019 Jan 10. 8 (1):[QxMD MEDLINE Link].
Schrezenmeier EV, Barasch J, Budde K, Westhoff T, Schmidt-Ott KM. Biomarkers in acute kidney injury - pathophysiological basis and clinical performance. Acta Physiol (Oxf). 2017 Mar. 219 (3):554-572. [QxMD MEDLINE Link].
Yang X, Chen C, Tian J, Zha Y, Xiong Y, Sun Z, et al. Urinary Angiotensinogen Level Predicts AKI in Acute Decompensated Heart Failure: A Prospective, Two-Stage Study. J Am Soc Nephrol. 2015 Aug. 26 (8):2032-41. [QxMD MEDLINE Link].
Chen C, Yang X, Lei Y, Zha Y, Liu H, Ma C, et al. Urinary Biomarkers at the Time of AKI Diagnosis as Predictors of Progression of AKI among Patients with Acute Cardiorenal Syndrome. Clin J Am Soc Nephrol. 2016 Sep 7. 11 (9):1536-44. [QxMD MEDLINE Link].
Du J, Cao X, Zou L, Chen Y, Guo J, Chen Z, et al. MicroRNA-21 and risk of severe acute kidney injury and poor outcomes after adult cardiac surgery. PLoS One. 2013. 8 (5):e63390. [QxMD MEDLINE Link].
Aguado-Fraile E, Ramos E, Conde E, Rodríguez M, Martín-Gómez L, Lietor A, et al. A Pilot Study Identifying a Set of microRNAs As Precise Diagnostic Biomarkers of Acute Kidney Injury. PLoS One. 2015. 10 (6):e0127175. [QxMD MEDLINE Link].
Lorenzen JM, Kielstein JT, Hafer C, Gupta SK, Kümpers P, Faulhaber-Walter R, et al. Circulating miR-210 predicts survival in critically ill patients with acute kidney injury. Clin J Am Soc Nephrol. 2011 Jul. 6 (7):1540-6. [QxMD MEDLINE Link].
Delanaye P, Cavalier E, Morel J, Mehdi M, Maillard N, Claisse G, et al. Detection of decreased glomerular filtration rate in intensive care units: serum cystatin C versus serum creatinine. BMC Nephrol. 2014 Jan 13. 15:9. [QxMD MEDLINE Link].
Lima RM, Navarro LH, Nakamura G, Solanki DR, Castiglia YM, Vianna PT, et al. Serum cystatin C is a sensitive early marker for changes in the glomerular filtration rate in patients undergoing laparoscopic surgery. Clinics (Sao Paulo). 2014 Jun. 69 (6):378-83. [QxMD MEDLINE Link].
Hoste E, Bihorac A, Al-Khafaji A, Ortega LM, Ostermann M, Haase M, et al. Identification and validation of biomarkers of persistent acute kidney injury: the RUBY study. Intensive Care Med. 2020 May. 46 (5):943-953. [QxMD MEDLINE Link].
Frazee E, Rule AD, Lieske JC, Kashani KB, Barreto JN, Virk A, et al. Cystatin C-Guided Vancomycin Dosing in Critically Ill Patients: A Quality Improvement Project. Am J Kidney Dis. 2017 May. 69 (5):658-666. [QxMD MEDLINE Link].
Levey AS, Cattran D, Friedman A, Miller WG, Sedor J, Tuttle K, et al. Proteinuria as a surrogate outcome in CKD: report of a scientific workshop sponsored by the National Kidney Foundation and the US Food and Drug Administration. Am J Kidney Dis. 2009 Aug. 54 (2):205-26. [QxMD MEDLINE Link].
Knight EL, Verhave JC, Spiegelman D, Hillege HL, de Zeeuw D, Curhan GC, et al. Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement. Kidney Int. 2004 Apr. 65(4):1416-21. [QxMD MEDLINE Link].
Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med. 2012 Jul 5. 367 (1):20-9. [QxMD MEDLINE Link]. [Full Text].
Shlipak MG, Matsushita K, Ärnlöv J, Inker LA, Katz R, Polkinghorne KR, et al. Cystatin C versus creatinine in determining risk based on kidney function. N Engl J Med. 2013 Sep 5. 369 (10):932-43. [QxMD MEDLINE Link]. [Full Text].
Shlipak MG, Sarnak MJ, Katz R, Fried LF, Seliger SL, Newman AB, et al. Cystatin C and the risk of death and cardiovascular events among elderly persons. N Engl J Med. 2005 May 19. 352 (20):2049-60. [QxMD MEDLINE Link].
Willey JZ, Moon YP, Husain SA, Elkind MSV, Sacco RL, Wolf M, et al. Creatinine versus cystatin C for renal function-based mortality prediction in an elderly cohort: The Northern Manhattan Study. PLoS One. 2020. 15 (1):e0226509. [QxMD MEDLINE Link].
Wasung ME, Chawla LS, Madero M. Biomarkers of renal function, which and when?. Clin Chim Acta. 2015 Jan 1. 438:350-7. [QxMD MEDLINE Link].
Spanaus KS, Kollerits B, Ritz E, Hersberger M, Kronenberg F, von Eckardstein A. Serum creatinine, cystatin C, and beta-trace protein in diagnostic staging and predicting progression of primary nondiabetic chronic kidney disease. Clin Chem. 2010 May. 56(5):740-9. [QxMD MEDLINE Link].
Bhavsar NA, Appel LJ, Kusek JW, Contreras G, Bakris G, Coresh J, et al. Comparison of measured GFR, serum creatinine, cystatin C, and beta-trace protein to predict ESRD in African Americans with hypertensive CKD. Am J Kidney Dis. 2011 Dec. 58(6):886-93. [QxMD MEDLINE Link]. [Full Text].
Inker LA, Tighiouart H, Coresh J, Foster MC, Anderson AH, Beck GJ, et al. GFR Estimation Using β-Trace Protein and β2-Microglobulin in CKD. Am J Kidney Dis. 2016 Jan. 67 (1):40-8. [QxMD MEDLINE Link]. [Full Text].
Inker LA, Couture SJ, Tighiouart H, Abraham AG, Beck GJ, Feldman HI, et al. A New Panel-Estimated GFR, Including β₂-Microglobulin and β-Trace Protein and Not Including Race, Developed in a Diverse Population. Am J Kidney Dis. 2020 Dec 7. [QxMD MEDLINE Link].
Viau A, El Karoui K, Laouari D, Burtin M, Nguyen C, Mori K, et al. Lipocalin 2 is essential for chronic kidney disease progression in mice and humans. J Clin Invest. 2010 Nov. 120(11):4065-76. [QxMD MEDLINE Link]. [Full Text].
Guo L, Zhu B, Yuan H, Zhao W. Evaluation of serum neutrophil gelatinase-associated lipocalin in older patients with chronic kidney disease. Aging Med (Milton). 2020 Mar. 3 (1):32-39. [QxMD MEDLINE Link].
He P, Bai M, Hu JP, Dong C, Sun S, Huang C. Significance of Neutrophil Gelatinase-Associated Lipocalin as a Biomarker for the Diagnosis of Diabetic Kidney Disease: A Systematic Review and Meta-Analysis. Kidney Blood Press Res. 2020. 45 (4):497-509. [QxMD MEDLINE Link].
Ding H, He Y, Li K, Yang J, Li X, Lu R, et al. Urinary neutrophil gelatinase-associated lipocalin (NGAL) is an early biomarker for renal tubulointerstitial injury in IgA nephropathy. Clin Immunol. 2007 May. 123(2):227-34. [QxMD MEDLINE Link].
Bolignano D, Coppolino G, Campo S, Aloisi C, Nicocia G, Frisina N, et al. Neutrophil gelatinase-associated lipocalin in patients with autosomal-dominant polycystic kidney disease. Am J Nephrol. 2007. 27(4):373-8. [QxMD MEDLINE Link].
De Silva PM, Mohammed Abdul KS, Eakanayake EM, Jayasinghe SS, Jayasumana C, Asanthi HB, et al. Urinary Biomarkers KIM-1 and NGAL for Detection of Chronic Kidney Disease of Uncertain Etiology (CKDu) among Agricultural Communities in Sri Lanka. PLoS Negl Trop Dis. 2016 Sep. 10 (9):e0004979. [QxMD MEDLINE Link].
Humphreys BD, Xu F, Sabbisetti V, Grgic I, Naini SM, Wang N, et al. Chronic epithelial kidney injury molecule-1 expression causes murine kidney fibrosis. J Clin Invest. 2013 Sep 3. 123(9):4023-35. [QxMD MEDLINE Link]. [Full Text].
Waanders F, Vaidya VS, van Goor H, Leuvenink H, Damman K, Hamming I, et al. Effect of renin-angiotensin-aldosterone system inhibition, dietary sodium restriction, and/or diuretics on urinary kidney injury molecule 1 excretion in nondiabetic proteinuric kidney disease: a post hoc analysis of a randomized controlled trial. Am J Kidney Dis. 2009 Jan. 53(1):16-25. [QxMD MEDLINE Link]. [Full Text].
Sabbisetti VS, Waikar SS, Antoine DJ, Smiles A, Wang C, Ravisankar A, et al. Blood kidney injury molecule-1 is a biomarker of acute and chronic kidney injury and predicts progression to ESRD in type I diabetes. J Am Soc Nephrol. 2014 Oct. 25(10):2177-86. [QxMD MEDLINE Link]. [Full Text].
Schulz CA, Engström G, Nilsson J, Almgren P, Petkovic M, Christensson A, et al. Plasma kidney injury molecule-1 (p-KIM-1) levels and deterioration of kidney function over 16 years. Nephrol Dial Transplant. 2020 Feb 1. 35 (2):265-273. [QxMD MEDLINE Link].
Schrauben SJ, Shou H, Zhang X et al. Association of Multiple Plasma Biomarker Concentrations with Progression of Prevalent Diabetic Kidney Disease: Findings from the Chronic Renal Insufficiency Cohort (CRIC) Study. J Am Soc Nephrol. 2021 Jan. 32 (1):115-126. [QxMD MEDLINE Link].
Kamijo A, Sugaya T, Hikawa A, Okada M, Okumura F, Yamanouchi M, et al. Urinary excretion of fatty acid-binding protein reflects stress overload on the proximal tubules. Am J Pathol. 2004 Oct. 165(4):1243-55. [QxMD MEDLINE Link]. [Full Text].
Kamijo A, Sugaya T, Hikawa A, Yamanouchi M, Hirata Y, Ishimitsu T, et al. Clinical evaluation of urinary excretion of liver-type fatty acid-binding protein as a marker for the monitoring of chronic kidney disease: a multicenter trial. J Lab Clin Med. 2005 Mar. 145(3):125-33. [QxMD MEDLINE Link].
Nielsen SE, Sugaya T, Hovind P, Baba T, Parving HH, Rossing P. Urinary liver-type fatty acid-binding protein predicts progression to nephropathy in type 1 diabetic patients. Diabetes Care. 2010 Jun. 33(6):1320-4. [QxMD MEDLINE Link]. [Full Text].
Fliser D, Kronenberg F, Kielstein JT, Morath C, Bode-Böger SM, Haller H, et al. Asymmetric dimethylarginine and progression of chronic kidney disease: the mild to moderate kidney disease study. J Am Soc Nephrol. 2005 Aug. 16 (8):2456-61. [QxMD MEDLINE Link].
Hanai K, Babazono T, Nyumura I, Toya K, Tanaka N, Tanaka M, et al. Asymmetric dimethylarginine is closely associated with the development and progression of nephropathy in patients with type 2 diabetes. Nephrol Dial Transplant. 2009 Jun. 24(6):1884-8. [QxMD MEDLINE Link].
Ravani P, Tripepi G, Malberti F, Testa S, Mallamaci F, Zoccali C. Asymmetrical dimethylarginine predicts progression to dialysis and death in patients with chronic kidney disease: a competing risks modeling approach. J Am Soc Nephrol. 2005 Aug. 16(8):2449-55. [QxMD MEDLINE Link].
Oliva-Damaso E, Oliva-Damaso N, Rodriguez-Esparragon F, Payan J, Baamonde-Laborda E, Gonzalez-Cabrera F, et al. Asymmetric (ADMA) and Symmetric (SDMA) Dimethylarginines in Chronic Kidney Disease: A Clinical Approach. Int J Mol Sci. 2019 Jul 26. 20 (15):[QxMD MEDLINE Link].
Ashokachakkaravarthy K, Rajappa M, Parameswaran S, Satheesh S, Priyadarshini G, Mohan Raj PS, et al. Asymmetric dimethylarginine and angiopoietin-like protein-2 are independent predictors of cardiovascular risk in pre-dialysis non-diabetic chronic kidney disease patients. Int Urol Nephrol. 2020 Jul. 52 (7):1321-1328. [QxMD MEDLINE Link].
Prajczer S, Heidenreich U, Pfaller W, Kotanko P, Lhotta K, Jennings P. Evidence for a role of uromodulin in chronic kidney disease progression. Nephrol Dial Transplant. 2010 Jun. 25 (6):1896-903. [QxMD MEDLINE Link].
Steubl D, Block M, Herbst V, Nockher WA, Schlumberger W, Satanovskij R, et al. Plasma Uromodulin Correlates With Kidney Function and Identifies Early Stages in Chronic Kidney Disease Patients. Medicine (Baltimore). 2016 Mar. 95 (10):e3011. [QxMD MEDLINE Link].
Steubl D, Block M, Herbst V, Nockher WA, Schlumberger W, Kemmner S, et al. Urinary uromodulin independently predicts end-stage renal disease and rapid kidney function decline in a cohort of chronic kidney disease patients. Medicine (Baltimore). 2019 May. 98 (21):e15808. [QxMD MEDLINE Link].
Nassirpour R, Raj D, Townsend R, Argyropoulos C. MicroRNA biomarkers in clinical renal disease: from diabetic nephropathy renal transplantation and beyond. Food Chem Toxicol. 2016 Dec. 98 (Pt A):73-88. [QxMD MEDLINE Link].
Khurana R, Ranches G, Schafferer S, Lukasser M, Rudnicki M, Mayer G, et al. Identification of urinary exosomal noncoding RNAs as novel biomarkers in chronic kidney disease. RNA. 2017 Feb. 23 (2):142-152. [QxMD MEDLINE Link].
Ali BH, Al-Moundhri M, Eldin MT, Nemmar A, Al-Siyabi S, Annamalai K. Amelioration of cisplatin-induced nephrotoxicity in rats by tetramethylpyrazine, a major constituent of the Chinese herb Ligusticum wallichi. Exp Biol Med (Maywood). 2008 Jul. 233(7):891-6. [QxMD MEDLINE Link].
Li J, Li QX, Xie XF, Ao Y, Tie CR, Song RJ. Differential roles of dihydropyridine calcium antagonist nifedipine, nitrendipine and amlodipine on gentamicin-induced renal tubular toxicity in rats. Eur J Pharmacol. 2009 Oct 12. 620(1-3):97-104. [QxMD MEDLINE Link].
Ali BH, Al Moundhri MS, Tag Eldin M, Nemmar A, Tanira MO. The ameliorative effect of cysteine prodrug L-2-oxothiazolidine-4-carboxylic acid on cisplatin-induced nephrotoxicity in rats. Fundam Clin Pharmacol. 2007 Oct. 21(5):547-53. [QxMD MEDLINE Link].
Oktem F, Ozguner F, Sulak O, Olgar S, Akturk O, Yilmaz HR, et al. Lithium-induced renal toxicity in rats: protection by a novel antioxidant caffeic acid phenethyl ester. Mol Cell Biochem. 2005 Sep. 277(1-2):109-15. [QxMD MEDLINE Link].
Harrison DJ, Kharbanda R, Cunningham DS, McLellan LI, Hayes JD. Distribution of glutathione S-transferase isoenzymes in human kidney: basis for possible markers of renal injury. J Clin Pathol. 1989 Jun. 42(6):624-8. [QxMD MEDLINE Link]. [Full Text].
Gautier JC, Riefke B, Walter J, Kurth P, Mylecraine L, Guilpin V, et al. Evaluation of novel biomarkers of nephrotoxicity in two strains of rat treated with Cisplatin. Toxicol Pathol. 2010 Oct. 38(6):943-56. [QxMD MEDLINE Link].
Svendsen KB, Ellingsen T, Bech JN, Pfeiffer-Jensen M, Stengaard-Pedersen K, Pedersen EB. Urinary excretion of alpha-GST and albumin in rheumatoid arthritis patients treated with methotrexate or other DMARDs alone or in combination with NSAIDs. Scand J Rheumatol. 2005. 34(1):34-9. [QxMD MEDLINE Link].
Keirstead ND, Wagoner MP, Bentley P, Blais M, Brown C, Cheatham L, et al. Early prediction of polymyxin-induced nephrotoxicity with next-generation urinary kidney injury biomarkers. Toxicol Sci. 2014 Feb. 137(2):278-91. [QxMD MEDLINE Link].
Whiting PH, Brown PA. The relationship between enzymuria and kidney enzyme activities in experimental gentamicin nephrotoxicity. Ren Fail. 1996 Nov. 18(6):899-909. [QxMD MEDLINE Link].
Naghibi B, Ghafghazi T, Hajhashemi V, Talebi A. Vancomycin-induced nephrotoxicity in rats: is enzyme elevation a consistent finding in tubular injury?. J Nephrol. 2007 Jul-Aug. 20(4):482-8. [QxMD MEDLINE Link].
Zhou Y, Vaidya VS, Brown RP, Zhang J, Rosenzweig BA, Thompson KL, et al. Comparison of kidney injury molecule-1 and other nephrotoxicity biomarkers in urine and kidney following acute exposure to gentamicin, mercury, and chromium. Toxicol Sci. 2008 Jan. 101 (1):159-70. [QxMD MEDLINE Link]. [Full Text].
Moldoveanu Z, Wyatt RJ, Lee JY, Tomana M, Julian BA, Mestecky J, et al. Patients with IgA nephropathy have increased serum galactose-deficient IgA1 levels. Kidney Int. 2007 Jun. 71(11):1148-54. [QxMD MEDLINE Link].
Zhao N, Hou P, Lv J, Moldoveanu Z, Li Y, Kiryluk K, et al. The level of galactose-deficient IgA1 in the sera of patients with IgA nephropathy is associated with disease progression. Kidney Int. 2012 Oct. 82(7):790-6. [QxMD MEDLINE Link]. [Full Text].
Chen P, Yu G, Zhang X, Xie X, Wang J, Shi S, et al. Plasma Galactose-Deficient IgA1 and C3 and CKD Progression in IgA Nephropathy. Clin J Am Soc Nephrol. 2019 Oct 7. 14 (10):1458-1465. [QxMD MEDLINE Link].
Bazzi C, Rizza V, Raimondi S, Casellato D, Napodano P, D'Amico G. In crescentic IgA nephropathy, fractional excretion of IgG in combination with nephron loss is the best predictor of progression and responsiveness to immunosuppression. Clin J Am Soc Nephrol. 2009 May. 4 (5):929-35. [QxMD MEDLINE Link].
van Es LA, de Heer E, Vleming LJ, van der Wal A, Mallat M, Bajema I, et al. GMP-17-positive T-lymphocytes in renal tubules predict progression in early stages of IgA nephropathy. Kidney Int. 2008 Jun. 73 (12):1426-33. [QxMD MEDLINE Link].
Torres DD, Rossini M, Manno C, Mattace-Raso F, D'Altri C, Ranieri E, et al. The ratio of epidermal growth factor to monocyte chemotactic peptide-1 in the urine predicts renal prognosis in IgA nephropathy. Kidney Int. 2008 Feb. 73 (3):327-33. [QxMD MEDLINE Link].
Beck LH Jr, Bonegio RG, Lambeau G, Beck DM, Powell DW, Cummins TD, et al. M-type phospholipase A2 receptor as target antigen in idiopathic membranous nephropathy. N Engl J Med. 2009 Jul 2. 361(1):11-21. [QxMD MEDLINE Link]. [Full Text].
Debiec H, Martin L, Jouanneau C, Dautin G, Mesnard L, Rondeau E, et al. Autoantibodies specific for the phospholipase A2 receptor in recurrent and De Novo membranous nephropathy. Am J Transplant. 2011 Oct. 11(10):2144-52. [QxMD MEDLINE Link].
Beck LH Jr, Fervenza FC, Beck DM, Bonegio RG, Malik FA, Erickson SB, et al. Rituximab-induced depletion of anti-PLA2R autoantibodies predicts response in membranous nephropathy. J Am Soc Nephrol. 2011 Aug. 22(8):1543-50. [QxMD MEDLINE Link]. [Full Text].
Tomas NM, Beck LH Jr, Meyer-Schwesinger C, Seitz-Polski B, Ma H, Zahner G, et al. Thrombospondin type-1 domain-containing 7A in idiopathic membranous nephropathy. N Engl J Med. 2014 Dec 11. 371 (24):2277-2287. [QxMD MEDLINE Link].
Ruggenenti P, Fervenza FC, Remuzzi G. Treatment of membranous nephropathy: time for a paradigm shift. Nat Rev Nephrol. 2017 Sep. 13 (9):563-579. [QxMD MEDLINE Link].
Wei C, Trachtman H, Li J, Dong C, Friedman AL, Gassman JJ, et al. Circulating suPAR in two cohorts of primary FSGS. J Am Soc Nephrol. 2012 Dec. 23(12):2051-9. [QxMD MEDLINE Link]. [Full Text].
Staeck O, Slowinski T, Lieker I, Wu K, Rudolph B, Schmidt D, et al. Recurrent Primary Focal Segmental Glomerulosclerosis Managed With Intensified Plasma Exchange and Concomitant Monitoring of Soluble Urokinase-Type Plasminogen Activator Receptor-Mediated Podocyte β3-integrin Activation. Transplantation. 2015 Dec. 99 (12):2593-7. [QxMD MEDLINE Link]. [Full Text].
Meijers B, Maas RJ, Sprangers B, Claes K, Poesen R, Bammens B, et al. The soluble urokinase receptor is not a clinical marker for focal segmental glomerulosclerosis. Kidney Int. 2014 Mar. 85 (3):636-40. [QxMD MEDLINE Link].
Wada T, Nangaku M, Maruyama S, Imai E, Shoji K, Kato S, et al. A multicenter cross-sectional study of circulating soluble urokinase receptor in Japanese patients with glomerular disease. Kidney Int. 2014 Mar. 85 (3):641-8. [QxMD MEDLINE Link].
Sinha A, Bajpai J, Saini S, Bhatia D, Gupta A, Puraswani M, et al. Serum-soluble urokinase receptor levels do not distinguish focal segmental glomerulosclerosis from other causes of nephrotic syndrome in children. Kidney Int. 2014 Mar. 85 (3):649-58. [QxMD MEDLINE Link].
Huang J, Liu G, Zhang YM, Cui Z, Wang F, Liu XJ, et al. Plasma soluble urokinase receptor levels are increased but do not distinguish primary from secondary focal segmental glomerulosclerosis. Kidney Int. 2013 Aug. 84 (2):366-72. [QxMD MEDLINE Link].
Tamirou F, D'Cruz D, Sangle S, Remy P, Vasconcelos C, Fiehn C, et al. Long-term follow-up of the MAINTAIN Nephritis Trial, comparing azathioprine and mycophenolate mofetil as maintenance therapy of lupus nephritis. Ann Rheum Dis. 2016 Mar. 75 (3):526-31. [QxMD MEDLINE Link].
Avihingsanon Y, Phumesin P, Benjachat T, Akkasilpa S, Kittikowit V, Praditpornsilpa K, et al. Measurement of urinary chemokine and growth factor messenger RNAs: a noninvasive monitoring in lupus nephritis. Kidney Int. 2006 Feb. 69 (4):747-53. [QxMD MEDLINE Link].
Nakayamada S, Saito K, Nakano K, Tanaka Y. Activation signal transduction by beta1 integrin in T cells from patients with systemic lupus erythematosus. Arthritis Rheum. 2007 May. 56 (5):1559-68. [QxMD MEDLINE Link].
Abulaban KM, Song H, Zhang X, Kimmel PL, Kusek JW, Nelson RG, et al. Predicting decline of kidney function in lupus nephritis using urine biomarkers. Lupus. 2016 Aug. 25 (9):1012-8. [QxMD MEDLINE Link].
Wolf BJ, Spainhour JC, Arthur JM, Janech MG, Petri M, Oates JC. Development of Biomarker Models to Predict Outcomes in Lupus Nephritis. Arthritis Rheumatol. 2016 Aug. 68 (8):1955-63. [QxMD MEDLINE Link].
Kistler AD, Mischak H, Poster D, Dakna M, Wüthrich RP, Serra AL. Identification of a unique urinary biomarker profile in patients with autosomal dominant polycystic kidney disease. Kidney Int. 2009 Jul. 76 (1):89-96. [QxMD MEDLINE Link].
Hogan MC, Bakeberg JL, Gainullin VG, Irazabal MV, Harmon AJ, Lieske JC, et al. Identification of Biomarkers for PKD1 Using Urinary Exosomes. J Am Soc Nephrol. 2015 Jul. 26 (7):1661-70. [QxMD MEDLINE Link].
Messchendorp AL, Meijer E, Visser FW, Engels GE, Kappert P, Losekoot M, et al. Rapid Progression of Autosomal Dominant Polycystic Kidney Disease: Urinary Biomarkers as Predictors. Am J Nephrol. 2019. 50 (5):375-385. [QxMD MEDLINE Link].
Kawano H, Muto S, Ohmoto Y, Iwata F, Fujiki H, Mori T, et al. Exploring urinary biomarkers in autosomal dominant polycystic kidney disease. Clin Exp Nephrol. 2015 Oct. 19 (5):968-73. [QxMD MEDLINE Link].
Petzold K, Poster D, Krauer F, Spanaus K, Andreisek G, Nguyen-Kim TD, et al. Urinary biomarkers at early ADPKD disease stage. PLoS One. 2015. 10 (4):e0123555. [QxMD MEDLINE Link].
Zschiedrich S, Budde K, Nürnberger J, Wanner C, Sommerer C, Kunzendorf U, et al. Secreted frizzled-related protein 4 predicts progression of autosomal dominant polycystic kidney disease. Nephrol Dial Transplant. 2016 Feb. 31 (2):284-9. [QxMD MEDLINE Link].

Media Gallery

of 0

Author

Ankit Sakhuja, MBBS, FACP, FASN, FCCP Assistant Professor of Medicine, Division of Cardiovascular Critical Care, Department of Cardiovascular and Thoracic Surgery, Heart and Vascular Institute, West Virginia University School of Medicine

Ankit Sakhuja, MBBS, FACP, FASN, FCCP is a member of the following medical societies: American College of Chest Physicians, American College of Physicians, American Society of Nephrology, Society of Critical Care Medicine

Disclosure: Nothing to disclose.

Coauthor(s)

Megan Chalupsky, MD Resident Physician, Department of Internal Medicine, UC Davis Health

Disclosure: Nothing to disclose.

Edgar V Lerma, MD, FACP, FASN, FAHA, FASH, FNLA, FNKF Clinical Professor of Medicine, Section of Nephrology, Department of Medicine, University of Illinois at Chicago College of Medicine; Research Director, Internal Medicine Training Program, Advocate Christ Medical Center; Consulting Staff, Associates in Nephrology, SC

Edgar V Lerma, MD, FACP, FASN, FAHA, FASH, FNLA, FNKF is a member of the following medical societies: American Heart Association, American Medical Association, American Society of Hypertension, American Society of Nephrology, Chicago Medical Society, Illinois State Medical Society, National Kidney Foundation, Society of General Internal Medicine

Disclosure: Serve(d) as a speaker or a member of a speakers bureau for: Astra Zeneca<br/>Author for: UpToDate, ACP Smart Medicine, Elsevier, McGraw-Hill, Wolters Kluwer.

Chief Editor

Vecihi Batuman, MD, FASN Professor of Medicine, Section of Nephrology-Hypertension, Deming Department of Medicine, Tulane University School of Medicine

Vecihi Batuman, MD, FASN is a member of the following medical societies: American College of Physicians, American Society of Hypertension, American Society of Nephrology, Southern Society for Clinical Investigation

Disclosure: Nothing to disclose.

Additional Contributors

Mahendra Agraharkar, MD, MBBS, FACP, FASN Clinical Associate Professor of Medicine, Baylor College of Medicine; President and CEO, Space City Associates of Nephrology

Mahendra Agraharkar, MD, MBBS, FACP, FASN is a member of the following medical societies: American College of Physicians, American Society of Nephrology, National Kidney Foundation

Disclosure: Nothing to disclose.

Brent Kelly, MD Assistant Professor, Department of Dermatology, University of Texas Medical Branch, Galveston, Texas

Brent Kelly, MD is a member of the following medical societies: Alpha Omega Alpha, American Medical Association

Disclosure: Nothing to disclose.

Judy Ann K Tan, MD Fellow, Department of Nephrology, Mount Sinai Hospital

Judy Ann K Tan, MD is a member of the following medical societies: American College of Physicians, International Society of Nephrology, Renal Physicians Association, Philippine Medical Association, American Telemedicine Association

Disclosure: Nothing to disclose.

Nikhil A Shah, MBBS, DNB(Neph) Clinical Research Fellow in Home Dialysis, Nephrologist, University of Alberta Faculty of Medicine and Dentistry, Canada

Nikhil A Shah, MBBS, DNB(Neph) is a member of the following medical societies: American Society of Nephrology, American Society of Transplantation, Canadian Medical Protective Association, Canadian Society of Nephrology, Indian Society of Nephrology, International Society of Nephrology

Disclosure: Nothing to disclose.

Acknowledgements

George R Aronoff, MD Director, Professor, Departments of Internal Medicine and Pharmacology, Section of Nephrology, Kidney Disease Program, University of Louisville School of Medicine

George R Aronoff, MD is a member of the following medical societies: American Federation for Medical Research, American Society of Nephrology, Kentucky Medical Association, and National Kidney Foundation

Disclosure: Nothing to disclose.

F John Gennari, MD Associate Chair for Academic Affairs, Robert F and Genevieve B Patrick Professor, Department of Medicine, University of Vermont College of Medicine

F John Gennari, MD is a member of the following medical societies: Alpha Omega Alpha, American College of Physicians-American Society of Internal Medicine, American Federation for Medical Research, American Heart Association, American Physiological Society, American Society for Clinical Investigation, American Society of Nephrology, and International Society of Nephrology

Disclosure: Nothing to disclose.

Francisco Talavera, PharmD, PhD Adjunct Assistant Professor, University of Nebraska Medical Center College of Pharmacy; Editor-in-Chief, Medscape Drug Reference

Disclosure: Medscape Salary Employment

Sections Novel Biomarkers of Kidney Function
Introduction and Overview
Characteristics of an Ideal Marker for Kidney Disease
Biomarkers of Acute Kidney Injury
Biomarkers of Chronic Kidney Disease
Biomarkers of Nephrotoxicity
Biomarkers of Glomerular Diseases
Biomarkers of ADPKD
Conclusion
Show All
References

Novel Biomarkers of Kidney Function Introduction and Overview

Introduction and Overview

Characteristics of an Ideal Marker for Kidney Disease

Biomarkers of Acute Kidney Injury

Neutrophil Gelatinase-associated Lipocalin

Interleukin-18

Kidney Injury Molecule 1

Liver-type Fatty Acid–Binding Protein

Urinary Insulin-like Growth Factor–Binding Protein 7 and Tissue Inhibitor of Metalloproteinases–2

Calprotectin

Urine Angiotensinogen

Urine microRNA

Cystatin C

Biomarkers of Chronic Kidney Disease

Cystatin C

β-Trace Protein

Neutrophil Gelatinase-associated Lipocalin

Kidney Injury Molecule 1

Liver-type Fatty Acid–Binding Protein

Asymmetric Dimethylarginine

Uromodulin

MicroRNA

Biomarkers of Nephrotoxicity

N-acetyl-glucosaminidase (NAG)

Glutathione-s-transferase (GST)

Gamma-glutamyl Transpeptidase, Alanine Aminopeptidase, and Lactate Dehydrogenase

Kidney Injury Molecule 1

Biomarkers of Glomerular Diseases

IgA Nephropathy

Membranous Nephropathy

Focal Segmental Glomerulosclerosis

Lupus Nephritis

Biomarkers of ADPKD

Conclusion

References

Tables

Contributor Information and Disclosures

What would you like to print?