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GWAS meta-analysis of kidney function traits in Japanese populations.
Hishida, Asahi; Nakatochi, Masahiro; Sutoh, Yoichi; Nakano, Shiori; Momozawa, Yukihide; Narita, Akira; Tanno, Kozo; Shimizu, Atsushi; Hozawa, Atsushi; Kinoshita, Kengo; Yamaji, Taiki; Goto, Atsushi; Noda, Mitsuhiko; Sawada, Norie; Ikezaki, Hiroaki; Nagayoshi, Mako; Hara, Megumi; Suzuki, Sadao; Koyama, Teruhide; Koriyama, Chihaya; Katsuura-Kamano, Sakurako; Kadota, Aya; Kuriki, Kiyonori; Yamamoto, Masayuki; Sasaki, Makoto; Iwasaki, Motoki; Matsuo, Keitaro; Wakai, Kenji.
Afiliação
  • Hishida A; Department of Preventive Medicine, Nagoya University Graduate School of Medicine.
  • Nakatochi M; Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine.
  • Sutoh Y; Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization.
  • Nakano S; Division of Biomedical Information Analysis, Iwate Medical University.
  • Momozawa Y; Division of Epidemiology, National Cancer Center Institute for Cancer Control.
  • Narita A; Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN.
  • Tanno K; Tohoku Medical Megabank Organization, Tohoku University.
  • Shimizu A; Division of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization.
  • Hozawa A; Department of Hygiene and Preventive Medicine, Iwate Medical University.
  • Kinoshita K; Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization.
  • Yamaji T; Division of Biomedical Information Analysis, Iwate Medical University.
  • Goto A; Tohoku Medical Megabank Organization, Tohoku University.
  • Noda M; Tohoku Medical Megabank Organization, Tohoku University.
  • Sawada N; Division of Epidemiology, National Cancer Center Institute for Cancer Control.
  • Ikezaki H; Department of Public Health, School of Medicine, Yokohama City University.
  • Nagayoshi M; Department of Diabetes, Metabolism and Endocrinology, Ichikawa Hospital, International University of Health and Welfare.
  • Hara M; Department of Endocrinology and Diabetes, Saitama Medical University.
  • Suzuki S; Division of Cohort Research, National Cancer Center Institute for Cancer Control.
  • Koyama T; Department of Comprehensive General Internal Medicine, Graduate School of Medical Sciences, Kyushu University.
  • Koriyama C; Department of General Internal Medicine, Kyushu University Hospital.
  • Katsuura-Kamano S; Department of Preventive Medicine, Nagoya University Graduate School of Medicine.
  • Kadota A; Department of Preventive Medicine, Faculty of Medicine, Saga University.
  • Kuriki K; Department of Public Health, Nagoya City University Graduate School of Medical Sciences.
  • Yamamoto M; Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine.
  • Sasaki M; Department of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences.
  • Iwasaki M; Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences.
  • Matsuo K; Center for Epidemiologic Research in Asia, Shiga University of Medical Science.
  • Wakai K; Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka.
J Epidemiol ; 2024 Apr 06.
Article em En | MEDLINE | ID: mdl-38583947
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article