The Promise of Tubule Biomarkers in Kidney Disease: A Review

Abstract

For over 70 years, serum creatinine has remained the primary index for detection and monitoring of kidney disease. Tubulointerstitial damage and fibrosis are highly prognostic for subsequent kidney failure in biopsy studies, yet this pathology is invisible to the clinician in the absence of a biopsy. Recent discovery of biomarkers that reflect distinct aspects of kidney tubule disease have led to investigations of whether these markers can provide additional information on risk of chronic kidney disease (CKD) progression and associated adverse clinical end points, above and beyond estimated glomerular filtration rate and albuminuria. These biomarkers can be loosely grouped into those that mark tubule cell injury (eg, kidney injury molecule 1, monocyte chemoattractant protein 1) and those that mark tubule cell dysfunction (eg, α₁-microglobulin, uromodulin). These kidney tubule biomarkers provide new opportunities to monitor response to therapeutics used to treat CKD patients. In this review, we describe results from some unique contributions in this area and discuss the current challenges and requirements in the field to bring these markers to clinical practice. We advocate for a broader assessment of kidney health that moves beyond a focus on the glomerulus, and we highlight how such tools can improve diagnostic accuracy and earlier assessment of therapeutic efficacy or harm in CKD patients.

Keywords: Acute interstitial nephritis (AIN); acute tubule necrosis (ATN); biomarker; epidermal growth factor (EGF); interleukin 18 (IL-18); kidney damage; kidney function; kidney injury marker 1 (KIM-1); monocyte chemoattractant protein 1 (MCP-1); renal tubule; review; tubular atrophy; tubular disease; tubule dysfunction; tubule injury; tubulointerstitial fibrosis; uromodulin (UMOD); α1-microglobulin (A1M).

Figure 1.

A comprehensive kidney health biomarker panel would capture not only glomerular function (eGFR) and injury (albuminuria), but also kidney tubule function and injury concurrently. An example list of biomarkers marking each category is provided. Abbreviations: *α1M for alpha 1 microglobulin, UMOD for uromodulin, EGF for epidermal growth factor. Endogenous secretion markers reflects a panel of 13 biomarkers measured in paired blood and urine that mark the kidney tubule secretory capacity.(40) † KIM-1 for kidney injury molecule 1, IL-18 for interleukin-18, NGAL for neutrophil gelatinase-associated lipocalin, MCP-1 for monocyte chemoattractant protein-1, and PIIINP for procollagen type 3 amino terminal pro-peptide.

Figure 2.

The figure provides examples of potential use cases for kidney tubule injury and dysfunction biomarkers in clinical practice. Examples in the literature of each are provided here for the purposes of prognosis,(20,27,37) treatment selection,(36) monitoring for treatment effectiveness,(41,42) monitoring for medication safety,(29,43) and distinguishing injury from hemodynamic causes of declining eGFR.(–35)

Figure 3.

The figure compares the highest to the lowest tertile of each biomarker, to provide an even reference for comparison. Models are adjusted for age, race, HTN, DM, HCV coinfection, smoking, LDL, triglycerides, BMI, HIV viral load, CD4 count, anti-retroviral use, and all biomarkers shown concurrently. Reproduced from Jotwani et al¹³ with permission of the American Society of Nephrology; original graphic © 2015 American Society of Nephrology.

Figure 4.

Figure depicts changes in biomarkers over 1 year in the intensive vs. the standard arm among 978 SPRINT participants with CKD at baseline. Biomarkers that are small molecules that are filtered at the glomerulus were all decreased in the intensive vs. the standard arm (red box). In contrast, biomarkers that are produced within kidney tissue and found in higher concentrations in the urine in response to kidney tubule injury, repair, or inflammation were all similar in the intensive vs. the standard arm (blue box). Collectively, the data suggest that changes in eGFR in response to intensive SBP lowering are predominantly driven by hemodynamic changes. Adapted from Malhotra et al³³.