A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits.
To identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples....
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
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Format: | Journal article |
Language: | English |
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2009
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author | Cho, Y Go, M Kim, Y Heo, J Oh, J Ban, H Yoon, D Lee, M Kim, D Park, M Cha, S Kim, J Han, BG Min, H Ahn, Y Park, MS Han, H Jang, H Cho, E Lee, J Cho, N Shin, C Park, T Park, J Lee, J |
author_facet | Cho, Y Go, M Kim, Y Heo, J Oh, J Ban, H Yoon, D Lee, M Kim, D Park, M Cha, S Kim, J Han, BG Min, H Ahn, Y Park, MS Han, H Jang, H Cho, E Lee, J Cho, N Shin, C Park, T Park, J Lee, J |
author_sort | Cho, Y |
collection | OXFORD |
description | To identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples. For the other traits examined, replication of promising GWAS signals in 7,861 independent Korean samples identified six previously unknown loci. For pulse rate, signals reaching genome-wide significance mapped to chromosomes 1q32 (rs12731740, P = 2.9 x 10(-9)) and 6q22 (rs12110693, P = 1.6 x 10(-9)), with the latter approximately 400 kb from the coding sequence of GJA1. For systolic blood pressure, the most compelling association involved chromosome 12q21 and variants near the ATP2B1 gene (rs17249754, P = 1.3 x 10(-7)). For waist-hip ratio, variants on chromosome 12q24 (rs2074356, P = 7.8 x 10(-12)) showed convincing associations, although no regional transcript has strong biological candidacy. Finally, we identified two loci influencing bone mineral density at multiple sites. On chromosome 7q31, rs7776725 (within the FAM3C gene) was associated with bone density at the radius (P = 1.0 x 10(-11)), tibia (P = 1.6 x 10(-6)) and heel (P = 1.9 x 10(-10)). On chromosome 7p14, rs1721400 (mapping close to SFRP4, a frizzled protein gene) showed consistent associations at the same three sites (P = 2.2 x 10(-3), P = 1.4 x 10(-7) and P = 6.0 x 10(-4), respectively). This large-scale GWA analysis of well-characterized Korean population-based samples highlights previously unknown biological pathways. |
first_indexed | 2024-03-07T06:46:34Z |
format | Journal article |
id | oxford-uuid:fb0c4ab7-2fbf-474b-98cb-a33ccad81168 |
institution | University of Oxford |
language | English |
last_indexed | 2024-03-07T06:46:34Z |
publishDate | 2009 |
record_format | dspace |
spelling | oxford-uuid:fb0c4ab7-2fbf-474b-98cb-a33ccad811682022-03-27T13:11:00ZA large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:fb0c4ab7-2fbf-474b-98cb-a33ccad81168EnglishSymplectic Elements at Oxford2009Cho, YGo, MKim, YHeo, JOh, JBan, HYoon, DLee, MKim, DPark, MCha, SKim, JHan, BGMin, HAhn, YPark, MSHan, HJang, HCho, ELee, JCho, NShin, CPark, TPark, JLee, JTo identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples. For the other traits examined, replication of promising GWAS signals in 7,861 independent Korean samples identified six previously unknown loci. For pulse rate, signals reaching genome-wide significance mapped to chromosomes 1q32 (rs12731740, P = 2.9 x 10(-9)) and 6q22 (rs12110693, P = 1.6 x 10(-9)), with the latter approximately 400 kb from the coding sequence of GJA1. For systolic blood pressure, the most compelling association involved chromosome 12q21 and variants near the ATP2B1 gene (rs17249754, P = 1.3 x 10(-7)). For waist-hip ratio, variants on chromosome 12q24 (rs2074356, P = 7.8 x 10(-12)) showed convincing associations, although no regional transcript has strong biological candidacy. Finally, we identified two loci influencing bone mineral density at multiple sites. On chromosome 7q31, rs7776725 (within the FAM3C gene) was associated with bone density at the radius (P = 1.0 x 10(-11)), tibia (P = 1.6 x 10(-6)) and heel (P = 1.9 x 10(-10)). On chromosome 7p14, rs1721400 (mapping close to SFRP4, a frizzled protein gene) showed consistent associations at the same three sites (P = 2.2 x 10(-3), P = 1.4 x 10(-7) and P = 6.0 x 10(-4), respectively). This large-scale GWA analysis of well-characterized Korean population-based samples highlights previously unknown biological pathways. |
spellingShingle | Cho, Y Go, M Kim, Y Heo, J Oh, J Ban, H Yoon, D Lee, M Kim, D Park, M Cha, S Kim, J Han, BG Min, H Ahn, Y Park, MS Han, H Jang, H Cho, E Lee, J Cho, N Shin, C Park, T Park, J Lee, J A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. |
title | A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. |
title_full | A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. |
title_fullStr | A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. |
title_full_unstemmed | A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. |
title_short | A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. |
title_sort | large scale genome wide association study of asian populations uncovers genetic factors influencing eight quantitative traits |
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