Journal of Epidemiology
Online ISSN : 1349-9092
Print ISSN : 0917-5040
ISSN-L : 0917-5040
GWAS meta-analysis of kidney function traits in Japanese populations
Asahi HishidaMasahiro NakatochiYoichi SutohShiori NakanoYukihide MomozawaAkira NaritaKozo TannoAtsushi ShimizuAtsushi HozawaKengo KinoshitaTaiki YamajiAtsushi GotoMitsuhiko NodaNorie SawadaHiroaki IkezakiMako NagayoshiMegumi HaraSadao SuzukiTeruhide KoyamaChihaya KoriyamaSakurako Katsuura-KamanoAya KadotaKiyonori KurikiMasayuki YamamotoMakoto SasakiMotoki IwasakiKeitaro MatsuoKenji Wakai
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JOURNAL OPEN ACCESS Advance online publication
Supplementary material

Article ID: JE20230281

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Abstract

Background: Genetic epidemiological evidence for the kidney function traits in East Asian population including Japanese remain still relatively unclarified. Especially, the number of GWASs for kidney traits reported still remains limited, and the sample size of each independent study is relatively small. Given the genetic variability between ancestries/ethnicities, implementation of GWAS with sufficiently large sample sizes in specific population of Japanese is considered meaningful.

Methods: We conducted the GWAS meta-analyses of kidney traits by leveraging the GWAS summary data of the representative large genome cohort studies with about 200,000 Japanese participants (n = 202,406 for estimated glomerular filtration rate [eGFR] and n = 200,845 for serum creatinine [SCr]).

Results: In the present GWAS meta-analysis, we identified 110 loci with 169 variants significantly associated with eGFR (on chromosomes 1-13 and 15-22; p < 5×10-8), whereas we also identified 112 loci with 176 variants significantly associated with SCr (on chromosomes 1-22; p < 5×10-8), of which one locus (more than 1Mb distant from known loci) with one variant (CD36 rs146148222 on chromosome 7) for SCr was considered as the truly novel finding.

Conclusions: The present GWAS meta-analysis of largest genome cohort studies in Japanese provided some original genomic loci associated with kidney function in Japanese, which may contribute to the possible development of personalized prevention of kidney diseases based on genomic information in the near future.

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© 2024 Asahi Hishida et al.

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