Metabolomics and renal disease

Abstract

Purpose of review: This review summarizes recent metabolomics studies of renal disease, outlining some of the limitations of the literature to date.

Recent findings: The application of metabolomics in nephrology research has expanded from the initial analyses of uremia to include both cross-sectional and longitudinal studies of earlier stages of kidney disease. Although these studies have nominated several potential markers of incident chronic kidney disease (CKD) and CKD progression, a lack of overlap in metabolite coverage has limited the ability to synthesize results across groups. Furthermore, direct examination of renal metabolite handling has underscored the substantial impact kidney function has on these potential markers (and many other circulating metabolites). In experimental studies, metabolomics has been used to identify a signature of decreased mitochondrial function in diabetic nephropathy and a preference for aerobic glucose metabolism in polycystic kidney disease. In each case, these studies have outlined novel therapeutic opportunities. Finally, as a complement to the longstanding interest in renal metabolite clearance, the microbiome has been increasingly recognized as the source of many plasma metabolites, including some with potential functional relevance to CKD and its complications.

Summary: The high-throughput, high-resolution phenotyping enabled by metabolomics technologies has begun to provide insight on renal disease in clinical, physiologic, and experimental contexts.

Figures

Figure 1. Overview of Metabolomics Technologies

NMR is robust, requiring relatively little sample preparation and no chromatographic separation. However, because of limited sensitivity and high data complexity, unambiguous identification is typically limited to targeted analyses, where ~100s of metabolites of known identity are measured, whereas time-of-flight and ion trap instruments are often used for nontargeted analyses of ~1000s of metabolite peaks (only a subset of which have assigned identities). Relative advantages (+) and disadvantages (−) of the different approaches are detailed in the figure.

Figure 2. Different Axes of Renal Health and Prognosis

Although kidney function is defined clinically by the excretion of select nitrogenous waste products, profiling of plasma from the aorta and renal vein has demonstrated the breadth and heterogeneity of renal metabolite handling [24]. Select markers of tubular secretion (kynurenic acid) and renal metabolism (citrulline and choline), which decreased more than creatinine across the renal circulation, were found to predict incident CKD in a community-based cohort, even after adjusting for eGFR, proteinuria, and other CKD risk factors. Metabolite structures were downloaded from www.hmdb.ca.