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Köttgen, A.* ; Raffler, J. ; Sekula, P.* ; Kastenmüller, G.

Genome-wide association studies of metabolite concentrations (mGWAS): Relevance for nephrology.

Semin. Nephrol. 38, 151-174 (2018)

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Metabolites are small molecules that are intermediates or products of metabolism, many of which are freely filtered by the kidneys. In addition, the kidneys have a central role in metabolite anabolism and catabolism, as well as in active metabolite reabsorption and/or secretion during tubular passage. This review article illustrates how the coupling of genomics and metabolomics in genome-wide association analyses of metabolites can be used to illuminate mechanisms underlying human metabolism, with a special focus on insights relevant to nephrology. First, genetic susceptibility loci for reduced kidney function and chronic kidney disease (CKD) were reviewed systematically for their associations with metabolite concentrations in metabolomics studies of blood and urine. Second, kidney function and CKD-associated metabolites reported from observational studies were interrogated for metabolite-associated genetic variants to generate and discuss complementary insights. Finally, insights originating from the simultaneous study of both blood and urine or by modeling intermetabolite relationships are summarized. We also discuss methodologic questions related to the study of metabolite concentrations in urine as well as among CKD patients. In summary, genome-wide association analyses of metabolites using metabolite concentrations quantified from blood and/or urine are a promising avenue of research to illuminate physiological and pathophysiological functions of the kidney.

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Publication type Article: Journal article

Document type Review

Corresponding Author

Keywords Genome-wide Association Studies ; Kidney ; Filtration ; Ckd ; Metabolomics

ISSN (print) / ISBN 0270-9295

Journal Seminars in Nephrology

Quellenangaben Volume: 38, Issue: 2, Pages: 151-174

Publisher Elsevier

Publishing Place Philadelphia

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Institute of Bioinformatics and Systems Biology (IBIS)