Metabolite markers of incident CKD risk

Metabolomics of Chronic Kidney Disease Progression: A Case-Control Analysis in the Chronic Renal Insufficiency Cohort Study

BACKGROUND

Whereas several longitudinal metabolomics studies have been conducted in individuals with normal estimated glomerular filtration rate (eGFR) at baseline, disease progression among individuals with established chronic kidney disease (CKD) has not been rigorously examined.

METHODS

We performed a nested case-control study of rapid CKD progression in the Chronic Renal Insufficiency Cohort Study, profiling baseline plasma from 200 individuals each with eGFR slope <-3 ml/min/1.73 m2/year (cases) or between -1 and +1 ml/min/1.73 m2/year (controls), matched on baseline eGFR and proteinuria. To directly assess how the kidney modulates circulating metabolites, we profiled plasma from the aorta and renal vein of 25 hospital-based individuals.

RESULTS

At baseline, cases and controls had a mean eGFR of 41.7 ± 13.3 and 45.0 ± 14.5 ml/min/1.73 m2, respectively. Ten plasma metabolites were nominally associated with CKD progression in logistic regression models adjusted for age, sex, race/ethnicity, hypertension, systolic and diastolic blood pressure, diabetes, eGFR and proteinuria; no metabolite achieved the Bonferroni-adjusted significance threshold (p < 0.0003). In a cross-sectional analysis, all 6 of the metabolites that were higher in cases than controls were significantly associated with eGFR at baseline. By contrast, threonine, methionine and arginine were lower in cases than in controls and had no association with baseline eGFR. Furthermore, in the hospital-based cohort that underwent renal arteriovenous sampling, these 3 metabolites were net released from the kidney. Combining these metabolites into a panel of markers further strengthened their association with CKD progression.

CONCLUSION

Our results motivate interest in arginine, methionine and threonine as potential indicators of renal metabolic function and markers of renal prognosis.

Metabolomics and renal disease

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.