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

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., gly...

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Podrobná bibliografie
Vydáno v:Kidney Int
Hlavní autoři: Zhang, Guanshi, Saito, Rintaro, Sharma, Kumar
Médium: Artigo
Jazyk:Inglês
Vydáno: 2017
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC5989707/
https://ncbi.nlm.nih.gov/pubmed/28501300
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.kint.2017.03.022
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