一种用于揭示慢性肾脏病进展的代谢物全基因组关联研究（mGWAS）方法。
A metabolite-GWAS (mGWAS) approach to unveil chronic kidney disease progression.
作者信息
Zhang Guanshi, Saito Rintaro, Sharma Kumar
机构信息
Center for Renal Translational Medicine, Division of Nephrology-Hypertension, Institute of Metabolomic Medicine, University of California-San Diego, La Jolla, California, USA.
Center for Renal Translational Medicine, Division of Nephrology-Hypertension, Institute of Metabolomic Medicine, University of California-San Diego, La Jolla, California, USA; Division of Nephrology-Hypertension, VA San Diego Healthcare System, La Jolla, California, USA.
出版信息
Kidney Int. 2017 Jun;91(6):1274-1276. doi: 10.1016/j.kint.2017.03.022.
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-monomethyl-l-arginine) with single-nucleotide polymorphisms of SLC7A9.
在本期杂志中，麦克马洪等人报告称，通过整合表型、代谢组学和基因数据，他们能够更好地在早期阶段检测出慢性肾病，并深入了解其病理生物学机制。该研究最重要的发现是，几种尿液代谢物（如甘氨酸和组氨酸）被确定为慢性肾病的早期风险因素，并且通过全基因组关联研究分析的代谢物确定了尿液代谢物（即赖氨酸和N-单甲基-L-精氨酸）与SLC7A9单核苷酸多态性之间的关联。
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