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Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population
Recent genome-wide association studies have identified various obesity or metabolic syndrome (MetS) susceptibility loci. However, most studies were conducted in a cross-sectional manner. To address this gap, we performed a longitudinal exome-wide association study to identify susceptibility loci for...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Physiological Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5899233/ https://www.ncbi.nlm.nih.gov/pubmed/29341862 http://dx.doi.org/10.1152/physiolgenomics.00117.2017 |
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author | Yasukochi, Yoshiki Sakuma, Jun Takeuchi, Ichiro Kato, Kimihiko Oguri, Mitsutoshi Fujimaki, Tetsuo Horibe, Hideki Yamada, Yoshiji |
author_facet | Yasukochi, Yoshiki Sakuma, Jun Takeuchi, Ichiro Kato, Kimihiko Oguri, Mitsutoshi Fujimaki, Tetsuo Horibe, Hideki Yamada, Yoshiji |
author_sort | Yasukochi, Yoshiki |
collection | PubMed |
description | Recent genome-wide association studies have identified various obesity or metabolic syndrome (MetS) susceptibility loci. However, most studies were conducted in a cross-sectional manner. To address this gap, we performed a longitudinal exome-wide association study to identify susceptibility loci for obesity and MetS in a Japanese population. We traced clinical data of 6,022 Japanese subjects who had annual health check-ups for several years (mean follow-up period, 5 yr) and genotyped ~244,000 genetic variants. The association of single nucleotide polymorphisms (SNPs) with body mass index (BMI) or the prevalence of obesity and MetS was examined in a generalized estimating equation model. Our longitudinal exome-wide association studies detected 21 BMI- and five MetS-associated SNPs (false discovery rate, FDR <0.01). Among these SNPs, 16 have not been previously implicated as determinants of BMI or MetS. Cross-sectional data for obesity- and MetS-related phenotypes in 7,285 Japanese subjects were examined in a replication study. Among the 16 SNPs, three (rs9491140, rs145848316, and rs7863248) were related to BMI in the replication cohort (P < 0.05). In conclusion, three SNPs [rs9491140 of NKAIN2 (FDR = 0.003, P = 1.9 × 10(−5)), rs145848316 of KMT2C (FDR = 0.007, P = 4.5 × 10(−5)), and rs7863248 of AGTPBP1 (FDR = 0.006, P = 4.2 × 10(−5))] were newly identified as susceptibility loci for BMI. |
format | Online Article Text |
id | pubmed-5899233 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Physiological Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-58992332018-04-17 Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population Yasukochi, Yoshiki Sakuma, Jun Takeuchi, Ichiro Kato, Kimihiko Oguri, Mitsutoshi Fujimaki, Tetsuo Horibe, Hideki Yamada, Yoshiji Physiol Genomics Research Article Recent genome-wide association studies have identified various obesity or metabolic syndrome (MetS) susceptibility loci. However, most studies were conducted in a cross-sectional manner. To address this gap, we performed a longitudinal exome-wide association study to identify susceptibility loci for obesity and MetS in a Japanese population. We traced clinical data of 6,022 Japanese subjects who had annual health check-ups for several years (mean follow-up period, 5 yr) and genotyped ~244,000 genetic variants. The association of single nucleotide polymorphisms (SNPs) with body mass index (BMI) or the prevalence of obesity and MetS was examined in a generalized estimating equation model. Our longitudinal exome-wide association studies detected 21 BMI- and five MetS-associated SNPs (false discovery rate, FDR <0.01). Among these SNPs, 16 have not been previously implicated as determinants of BMI or MetS. Cross-sectional data for obesity- and MetS-related phenotypes in 7,285 Japanese subjects were examined in a replication study. Among the 16 SNPs, three (rs9491140, rs145848316, and rs7863248) were related to BMI in the replication cohort (P < 0.05). In conclusion, three SNPs [rs9491140 of NKAIN2 (FDR = 0.003, P = 1.9 × 10(−5)), rs145848316 of KMT2C (FDR = 0.007, P = 4.5 × 10(−5)), and rs7863248 of AGTPBP1 (FDR = 0.006, P = 4.2 × 10(−5))] were newly identified as susceptibility loci for BMI. American Physiological Society 2018-03-01 2018-01-12 /pmc/articles/PMC5899233/ /pubmed/29341862 http://dx.doi.org/10.1152/physiolgenomics.00117.2017 Text en Copyright © 2018 the American Physiological Society http://creativecommons.org/licenses/by/4.0/deed.en_US Licensed under Creative Commons Attribution CC-BY 4.0 (http://creativecommons.org/licenses/by/4.0/deed.en_US) : © the American Physiological Society. |
spellingShingle | Research Article Yasukochi, Yoshiki Sakuma, Jun Takeuchi, Ichiro Kato, Kimihiko Oguri, Mitsutoshi Fujimaki, Tetsuo Horibe, Hideki Yamada, Yoshiji Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population |
title | Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population |
title_full | Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population |
title_fullStr | Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population |
title_full_unstemmed | Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population |
title_short | Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population |
title_sort | identification of three genetic variants as novel susceptibility loci for body mass index in a japanese population |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5899233/ https://www.ncbi.nlm.nih.gov/pubmed/29341862 http://dx.doi.org/10.1152/physiolgenomics.00117.2017 |
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