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Article

A metabolite-GWAS (mGWAS) approach to unveil chronic kidney disease progression.

Kidney international - 1 Jun 2017

Zhang Guanshi, Saito Rintaro, Sharma Kumar

Abstract excerpt

In this issue, McMahon et al. report that, by combining phenotypic, metabolomic, and genetic data, they could better detect chronic kidney disease at the early stages and provide insight into its pathobiology. The most significant findings of the study are that several urinary metabolites (e.g., glycine and histidine) were identified as early risk factors for chronic kidney disease, and metabolites with...

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Identifiers

PMID: 28501300
DOI: 10.1016/j.kint.2017.03.022
PMCID: PMC5989707

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

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