TY - JOUR
T1 - A metabolite-GWAS (mGWAS) approach to unveil chronic kidney disease progression
AU - Zhang, Guanshi
AU - Saito, Rintaro
AU - Sharma, Kumar
N1 - Publisher Copyright:
© 2017
PY - 2017/6
Y1 - 2017/6
N2 - 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 NG-monomethyl-L-arginine) with single-nucleotide polymorphisms of SLC7A9.
AB - 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 NG-monomethyl-L-arginine) with single-nucleotide polymorphisms of SLC7A9.
UR - https://www.scopus.com/pages/publications/85019154702
UR - https://www.scopus.com/pages/publications/85019154702#tab=citedBy
U2 - 10.1016/j.kint.2017.03.022
DO - 10.1016/j.kint.2017.03.022
M3 - Comment/debate
C2 - 28501300
AN - SCOPUS:85019154702
SN - 0085-2538
VL - 91
SP - 1274
EP - 1276
JO - Kidney international
JF - Kidney international
IS - 6
ER -