NGAL for the Detection of AKI: More Questions Than Answers

In cardiovascular disease, acute kidney injury (AKI) is associated with increased morbidity and mortality.1,2 Creatinine's shortcomings for diagnosing AKI have prompted research for new biomarkers. Neutrophil gelatinase-associated lipocalin (NGAL) is one that has shown promise. With over a decade of research, results are mixed on NGAL's ability to predict AKI. Yet, with a poor gold standard for diagnosing AKI (creatinine), a new paradigm for evaluating AKI, and NGAL's complex physiology, further research is needed to define NGAL's role for diagnosing AKI, if any.

Predictive Ability of NGAL

In 2005, a landmark study of 71 children undergoing cardiac surgery showed that urine NGAL (uNGAL) and plasma NGAL (pNGAL), assessed 2 hours after cardiopulmonary bypass, had a high diagnostic accuracy for AKI (defined as a ≥50% increase in creatinine from baseline).3 uNGAL's sensitivity was 100% with an area under the receiver-operating characteristic curve (AUC) of 0.998, and pNGAL's sensitivity was 70% with an AUC of 0.906. These promising results led to further studies of NGAL in cardiogenic shock, contrast-induced nephropathy (CIN), heart failure (HF), sepsis, and critical illness.

In adults undergoing cardiac surgery, studies have been unable to reproduce the same predictive value of NGAL for AKI. Large trials have failed to produce an AUC >0.64 for uNGAL or pNGAL.4,5 In the largest multicenter study evaluating AKI biomarkers after cardiac surgery, the TRIBE-AKI (Translational Research Investigating Biomarker Endpoints in Acute Kidney Injury) study, both uNGAL and pNGAL were evaluated in 1,219 adults at high risk for post-operative AKI.6 Subjects in the highest quintile of pNGAL had 6.8 increased odds of AKI compared with the lowest quintile. No significant difference was found between quintiles of uNGAL. The AUCs were fair at 0.70 for pNGAL and 0.67 for uNGAL. Notably, when added to a multivariate model, pNGAL improved the AUC from 0.70 to 0.75. The net reclassification improvement and integrated discrimination improvement were also examined, showing that pNGAL improved the net reclassification improvement (0.18) and integrated discrimination improvement (0.02), but uNGAL did not.6 This study suggests the potential utility of pNGAL for AKI in cardiac surgery; however, it used a high-risk population for post-operative AKI, and the results may not be referable to other populations. A recent meta-analysis found an AUC of 0.72 for uNGAL and 0.71 for pNGAL for AKI after cardiac surgery, but there was significant study heterogeneity with I2 of 81.1% for uNGAL and 32.6% for pNGAL.7 Findings suggest NGAL has prognostic ability for AKI or refining risk in cardiac surgery but not to the degree hoped based on the initial study.

Compared with cardiac surgery, NGAL has been less extensively studied in other clinical settings. Large studies have examined NGAL's utility for diagnosing AKI in critical illness, with most finding fair or even poor predictive value. Siew et al. described uNGAL as having an AUC of 0.71 for diagnosing AKI at 24 hours from study enrollment, which declined to 0.64 at 48 hours.8 uNGAL did not significantly improve a prediction model or net reclassification improvement but did strongly predict AKI in subjects with an estimated glomerular filtration rate (eGFR) >60 ml/min/1.73 m2 (AUC of 0.77) and was prognostic for the need for renal replacement therapy. In another study, Endre et al. found uNGAL's AUC was 0.66 for AKI.9 When controlling for timing of insult and eGFR, the AUC remained ≤0.71 except when uNGAL was measured 12-36 hours after renal insult in subjects with an eGFR <60 ml/min/1.73 m2; then the AUC improved to 0.85.9 Additionally, uNGAL predicted need of renal replacement therapy with AUC of 0.78. In comparison, de Geus et al. evaluated uNGAL and pNGAL for predicting AKI and found AUCs of 0.80 and 0.77, respectively; however, this was no better than eGFR, which had an AUC of 0.84.10 uNGAL and pNGAL did predict more severe AKI (AUCs of 0.79 and 0.75, respectively) better than eGFR and strongly predicted need for renal replacement therapy (AUCs of 0.89 and 0.88, respectively). Similar to cardiac surgery, findings are mixed and inconclusive for NGAL's prognostic utility for AKI. However, there is a signal that NGAL can predict more severe AKI and need of renal replacement therapy, which could have therapeutic implications.

Within critical illness, septic patients are at significantly increased risk of AKI. In a multicenter study of patients presenting to the emergency department with suspected sepsis, pNGAL strongly predicted AKI with an AUC of 0.82 versus 0.73 for creatinine.11 However, only 1.7% of subjects developed AKI based on the study definition, and serum creatinine was higher (1.9 mg/dL) in those with AKI compared with those without (1.1 mg/dL). pNGAL did have an excellent sensitivity of 96% at a cut-off of 150 ng/mL and strongly predicted mortality with an AUC of 0.75. A meta-analysis similarly found that pNGAL has a high sensitivity of 88.1% for AKI, and uNGAL is not predictive.12 This suggests that a strength of pNGAL in sepsis is its ability to exclude AKI. However, pNGAL has a poor specificity and positive predictive value because it arises from neutrophils in sepsis and reflects inflammation.12

NGAL has shown promise in predicting AKI upon presentation to the emergency department. Two large single-center studies have shown uNGAL and pNGAL to strongly predict sustained AKI, defined as a persistent rise in creatinine for more than 3 days, with an AUC ≥0.77.13,14 Also, NGAL was relatively sensitive for AKI, with the AUC and sensitivity improving with more severe forms of AKI.13,14 Multicenter trials have similarly shown uNGAL and pNGAL to predict sustained AKI. Di Somma et al. found an AUC of 0.80 for pNGAL for sustained AKI, although this was not significantly different than eGFR.15 They also found that serial NGALs (assessed on presentation and 6 hours later) had a 98% negative predictive value for sustained AKI.15 Among multiple urine biomarkers, Nickolas et al. found uNGAL to have the best AUC at 0.81 for sustained AKI, though creatinine alone performed the best with an AUC of 0.90.16 uNGAL improved the net reclassification improvement by 26.1% and had a positive integrated discrimination improvement when added to a model containing creatinine.16 A common trend in these studies is NGAL's ability to differentiate sustained AKI from normal renal function, chronic kidney disease, and transient AKI (creatinine elevated from baseline but resolving within 3 days). Being able to differentiate sustained injury from pre-existing or transient injury could be useful in determining therapy and resource utilization; however, this has yet to be shown prospectively.

Less-studied areas of NGAL utilization include HF and CIN. In the largest multicenter trial of NGAL in HF, AKINESIS (Acute Kidney Injury Neutrophil Gelatinase-Associated Lipocalin Evaluation of Symptomatic Heart Failure Study), demonstrated pNGAL to have an AUC <0.66 for AKI, which was similar to creatinine.17 pNGAL was no more prognostic than creatinine for in-hospital adverse events, though there was suggestion that a low pNGAL in patients with an eGFR <60 ml/min/1.73 m2 predicted a low likelihood of adverse events.17 In CIN, 2 recent meta-analyses have shown that NGAL has excellent predictive utility for AKI with AUCs of 0.87 and 0.93.18,19 However, the included studies were often small and were performed both in children and adults, and the AUCs did not differentiate between uNGAL and pNGAL. A large multicenter study is needed to confirm these findings.

The Spectrum of NGAL

Complicating interpretation of these studies are NGAL's physiology and methods of measurement. NGAL is made in multiple tissues, including the kidney, neutrophils, intestines, airways, and epithelia.20 Within the kidney, NGAL is made in the loop of Henle and collecting ducts during injury and released predominately in the urine and not systemic circulation.20 Systemically produced NGAL is taken up by the proximal renal tubule, but it may appear in urine with injury to the proximal tubule. So assessment of uNGAL versus pNGAL likely reflects different pathophysiologic processes, and these processes could vary substantially with the clinical scenario. Whether uNGAL or pNGAL is better for a specific clinical scenario is unclear.

Furthermore, studies have measured NGAL using different methods including western blot, enzyme-linked immunosorbent assay, immunoblot, and immunoassays.21 Early studies often used research-based assays; only recently have standardized commercial assays been used. NGAL is not a single molecule either but is found as a 25-kiloDalton (kDa) monomer, 45-kDa homodimer, and 135-kDa heterodimer with different forms arising from different cell types.21 Which isoforms were measured in studies is not always clear. Additionally, NGAL has significant biologic variability and reference values in normal subjects, and different disease states have yet to be clearly defined.20 These factors complicate synthesizing the results of prior NGAL studies given the variability in assessment of levels and disease states.

The Paradigm of AKI

Another consideration is how exactly AKI should be defined given the recent changes in the paradigm of AKI. Various criteria exist to define AKI including the Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease criteria; Acute Kidney Injury Network criteria; and Kidney Disease Improving Global Outcomes criteria. Additionally, certain conditions use their own definition for AKI, such as CIN. Prior NGAL studies have not used one specific definition for AKI. This has contributed to the variability in reported predictive ability of NGAL and complicates comparing study results.

Confounding assessment of NGAL as a marker of AKI is the reliance of current definitions on a poor gold standard: creatinine. Creatinine levels vary based on age, race, sex, muscle mass, comorbidities, hydration status, and medications, and levels have a delayed rise over days after over 50% of kidney function is lost in AKI.13,20 Additionally, creatinine assesses only glomerular filtration and functional changes; a new paradigm of AKI recognizes that kidney damage can occur without functional change (Figure 1).22 Thus, NGAL may diagnose AKI without a change in creatinine. This has been shown and termed "subclinical AKI." An elevated NGAL without a rise in creatinine is associated with worse outcomes including mortality, need of renal replacement therapy, and length of stay.16,23 However, these findings may not be related to actual kidney injury but to other factors, such as inflammation, that lead to an elevation in NGAL. Long-term studies showing that an elevated NGAL without a rise in creatinine leads to deterioration of renal function would be helpful.

Figure 1: New Paradigm for AKI22

Figure 1


The complexities of NGAL and AKI have led to more questions than answers on the utility of using NGAL for diagnosing AKI. At this time, it does not appear that NGAL is ready for clinical use, though a recent study used NGAL for clinical decision-making with a reduction in mortality.24 NGAL's inability to predict creatinine-based AKI definitions alone should not discount NGAL as a potential biomarker. Its prognostic utility for subclinical AKI highlights the complex pathophysiology of AKI, which is unlikely to be captured by a single biomarker. This may explain why NGAL is not always predictive of AKI. A possible paradigm for AKI pathophysiology involving injury biomarkers is proposed in Figure 2. Likely, a panel of biomarkers will be needed to help detect different pathophysiologic processes in AKI, of which NGAL may be one. Thus, it is still too early to determine whether NGAL will be useful for AKI.

Figure 2: Proposed Paradigm of Kidney Injury With Subclinical Damage Detected by Novel Biomarkers Prior to Progressing to Functional Change

Figure 2


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Clinical Topics: Acute Coronary Syndromes, Heart Failure and Cardiomyopathies, ACS and Cardiac Biomarkers, Acute Heart Failure, Heart Failure and Cardiac Biomarkers

Keywords: Acute Coronary Syndrome, Acute Kidney Injury, Biological Markers, Cardiopulmonary Bypass, Comorbidity, Creatinine, Enzyme-Linked Immunosorbent Assay, Glomerular Filtration Rate, Heart Failure, Kidney Failure, Chronic, Kidney Tubules, Proximal, Loop of Henle, Protein Isoforms, Renal Replacement Therapy, Sepsis, Shock, Cardiogenic

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