Meta-analysis of genome-wide association studies for height and body mass index in ∼700 000 individuals of European ancestry
Meta-analysis of genome-wide association studies for height and body mass index in ∼700 000 individuals of European ancestry
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DOI：
10.1093/hmg/ddy271
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发表时间：
2018-10-15
影响因子：
3.5
通讯作者：
Visscher, Peter M.
中科院分区：
文献类型：
--
作者：
Yengo, Loic;Sidorenko, Julia;Visscher, Peter M.
最近对大约 250000 名欧洲参与者进行的身高和体重指数 (BMI) 的全基因组关联研究 (GWAS) 分别发现了大约 700 个和大约 100 个与这些性状相关的几乎独立的单核苷酸多态性 (SNP)。在这里，我们将这两项研究的汇总统计数据与对 450000 名欧洲血统的英国生物银行参与者进行的身高和体重指数 GWAS 结合起来。总体而言，我们的综合 GWAS 荟萃分析覆盖了大约 700000 个人，并大幅增加了与这些性状相关的 GWAS 信号数量。我们分别鉴定了 3290 个和 941 个与身高和 BMI 相关的近乎独立的 SNP（修正后的全基因组显着性阈值 P < 1 x 10(-8)），其中包括位于这两个 GWAS 先前未识别的基因座内的 1185 个与身高相关的 SNP 和 751 个与 BMI 相关的 SNP。在健康与退休研究 (HRS) 的独立样本中，近乎独立的全基因组显着 SNP 解释了类似于 24.6% 的身高方差和 6.0% 的 BMI 方差。基于这些 SNP 的多基因评分与 HRS 参与者的实际身高和 BMI 之间的相关性分别类似于 0.44 和 0.22。通过基于汇总数据的孟德尔随机化对 GWAS 和表达数量性状位点 (eQTL) 数据进行整合分析，我们确定了前导身高和 BMI 信号中 eQTL 的富集，分别优先考虑 610 和 138 个基因。我们的研究表明，正如之前预测的那样，通过发现新基因座，增加 GWAS 样本量将继续提高预测准确性并提供更多数据，以更深入地了解复杂性状生物学。所有汇总统计数据均可用于后续研究。
Recent genome-wide association studies (GWAS) of height and body mass index (BMI) in similar to 250000 European participants have led to the discovery of similar to 700 and similar to 100 nearly independent single nucleotide polymorphisms (SNPs) associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in similar to 450000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N similar to 700000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3290 and 941 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of P < 1 x 10(-8)), including 1185 height-associated SNPs and 751 BMI-associated SNPs located within loci not previously identified by these two GWAS. The near-independent genome-wide significant SNPs explain similar to 24.6% of the variance of height and similar to 6.0% of the variance of BMI in an independent sample from the Health and Retirement Study (HRS). Correlations between polygenic scores based upon these SNPs with actual height and BMI in HRS participants were similar to 0.44 and similar to 0.22, respectively. From analyses of integrating GWAS and expression quantitative trait loci (eQTL) data by summary-data-based Mendelian randomization, we identified an enrichment of eQTLs among lead height and BMI signals, prioritizing 610 and 138 genes, respectively. Our study demonstrates that, as previously predicted, increasing GWAS sample sizes continues to deliver, by the discovery of new loci, increasing prediction accuracy and providing additional data to achieve deeper insight into complex trait biology. All summary statistics are made available for follow-up studies.