2018
DOI: 10.1681/asn.2018030291
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Insights into CKD from Metabolite GWAS

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Cited by 3 publications
(4 citation statements)
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References 10 publications
(14 reference statements)
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“…20 Participants 18-74 years of age at their baseline examination were recruited through a stratified multistage area probability sample design from four communities (San Diego, California; Chicago, Illinois; The Bronx, New York, New York; and Miami, Florida). Overall, 16,415 participants, representing major self-reported US Hispanic/Latino background groups (Mexicans, Puerto Ricans, Cubans, Central Americans, Dominicans, and South Americans), took part in baseline examinations that occurred in June 2008-July 2011. Second visits were performed in 2014-2017, and the completion of third visits began in 2020 and is ongoing.…”
Section: Hchs/solmentioning
confidence: 99%
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“…20 Participants 18-74 years of age at their baseline examination were recruited through a stratified multistage area probability sample design from four communities (San Diego, California; Chicago, Illinois; The Bronx, New York, New York; and Miami, Florida). Overall, 16,415 participants, representing major self-reported US Hispanic/Latino background groups (Mexicans, Puerto Ricans, Cubans, Central Americans, Dominicans, and South Americans), took part in baseline examinations that occurred in June 2008-July 2011. Second visits were performed in 2014-2017, and the completion of third visits began in 2020 and is ongoing.…”
Section: Hchs/solmentioning
confidence: 99%
“…We conducted a network-based analysis to identify modules of genes whose combined effect was overrepresented in GWASs by using the previously developed dense module searching for GWASs (dmGWAS, version 2.7). 43 Specifically, we performed our analysis by using two protein-protein interaction networks: one from PathwayCommons (PC) 44 (16,332 genes and 369,895 interactions) and the other from in-house curation with 21,137 genes and 413,492 interactions. In brief, dmGWAS implements a dense module searching algorithm to search for modules in the reference network with a goal of achieving a maximum module score.…”
Section: Pathway Analysismentioning
confidence: 99%
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“…Although genome-wide association study (GWAS) may indicate risk for disease, it does not clearly explain the underlying cause. Thus, other research groups have performed an integrated analysis of GWAS with other fields such as metabolomics, proteomics, and transcriptomics to overcome the limitations of GWAS [ 26 , 27 ]. To the best of our knowledge, metabolite GWAS (mGWAS) for IDO activity associated with CKD has not been reported yet.…”
Section: Introductionmentioning
confidence: 99%