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Meta-analysis of genome-wide association studies for height and body mass index in similar to 700 000 individuals of European ancestry

机译:Genome-宽协会的META分析,高度和体重指数与70万个欧洲祖先

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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.
机译:最近的全基因组关联研究(GWA)的高度和体重指数(BMI)类似于250000欧洲参与者导致类似于700的发现,类似于与这些特征相关的100个几乎独立的单一核苷酸多态性(SNP),分别。在这里,我们将这两项研究的汇总统计与高度和BMI相似,类似于欧洲祖先的450000英国Biobank参与者。总的来说,我们的GWAS META分析与70万个人相似,并且大大增加了与这些特征相关的GWAS信号的数量。我们分别识别了3290和941个与高度和BMI相关的近乎无关的SNP(以P <1×10(-8)的修正基因组 - 宽的显着性阈值),包括1185高度相关的SNP和751 BMI相关的SNP位于此前没有由这两个GWA识别的基因座内。近乎独立的基因组显着的显着性SNP与高度的24.6%的差异相似,并且类似于来自健康和退休研究(HRS)的独立样品中BMI方差的6​​.0%。基于这些SNP的多基因分数与HRS参与者中的BMI之间的多种子分谱之间的相关性分别与0.44类似,类似于0.22。通过分析通过基于摘要 - 基于数据的孟德尔随机化来集成GWAS和表达定量特征基因座(EQTL)数据,我们确定了铅高度和BMI信号之间的EQTL的富集,分别优先考虑610和138基因。我们的研究表明,如前所述,通过发现新的基因座,增加预测准确性并提供额外数据以实现更深入的洞察力,增加GWAS样本尺寸的增加仍在继续提供。所有汇总统计数据都可以用于后续研究。

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