Cho Yoon Shin, Go Min Jin, Kim Young Jin, Heo Jee Yeon, Oh Ji Hee, Ban Hyo-Jeong, Yoon Dankyu, Lee Mi Hee, Kim Dong-Joon, Park Miey, Cha Seung-Hun, Kim Jun-Woo, Han Bok-Ghee, Min Haesook, Ahn Younjhin, Park Man Suk, Han Hye Ree, Jang Hye-Yoon, Cho Eun Young, Lee Jong-Eun, Cho Nam H, Shin Chol, Park Taesung, Park Ji Wan, Lee Jong-Keuk, Cardon Lon, Clarke Geraldine, McCarthy Mark I, Lee Jong-Young, Lee Jong-Koo, Oh Bermseok, Kim Hyung-Lae
Center for Genome Science, National Institute of Health, Seoul, Korea.
Nat Genet. 2009 May;41(5):527-34. doi: 10.1038/ng.357. Epub 2009 Apr 26.
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.
为了识别影响具有生物医学重要性的数量性状的遗传因素,我们在来自韩国基于人群队列的8842个样本中进行了全基因组关联研究。对于身高和体重指数,检测到的大多数变异与欧洲样本中报道的变异重叠。对于所研究的其他性状,在7861个独立的韩国样本中对有前景的全基因组关联研究信号进行重复验证,确定了6个以前未知的基因座。对于脉搏率,达到全基因组显著性的信号定位于1号染色体q32区域(rs12731740,P = 2.9×10⁻⁹)和6号染色体q22区域(rs12110693,P = 1.6×10⁻⁹),后者距离GJA1编码序列约400 kb。对于收缩压,最显著的关联涉及12号染色体q21区域以及ATP2B1基因附近的变异(rs17249754,P = 1.3×10⁻⁷)。对于腰臀比,12号染色体q24区域的变异(rs2074356,P = 7.8×10⁻¹²)显示出令人信服的关联,尽管没有区域转录本具有很强的生物学候选资格。最后,我们确定了两个在多个部位影响骨密度的基因座。在7号染色体q31区域,rs7776725(位于FAM3C基因内)与桡骨(P = 1.0×10⁻¹¹)、胫骨(P = 1.6×10⁻⁶)和足跟(P = 1.9×10⁻¹⁰)的骨密度相关。在7号染色体p14区域,rs1721400(定位在靠近卷曲蛋白基因SFRP4处)在相同的三个部位显示出一致的关联(分别为P = 2.2×10⁻³、P = 1.4×10⁻⁷和P = 6.0×10⁻⁴)。这项对特征明确的韩国基于人群样本的大规模全基因组关联分析突出了以前未知的生物学途径。