A metabolite-GWAS (mGWAS) approach to unveil chronic kidney disease progression.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 28501300.
- Also identified by DOI 10.1016/j.kint.2017.03.022 and PMC identifier 5989707.
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Abstract
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 genomewide association study analysis identified associations of urinary metabolites (i.e., lysine and N<sup>G</sup>-monomethyl-l-arginine) with single-nucleotide polymorphisms of SLC7A9.
Medical subject headings
- Genome-Wide Association Study
- Renal Insufficiency, Chronic