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Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment

机译:110万人口的受教育程度的GWAS中的基因发现和多基因预测

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摘要

We conduct a large-scale genetic association analysis of educational attainment in a sample of ~1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of ~0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
机译:我们在约110万个人的样本中进行了教育程度的大规模遗传关联分析,确定了1,271个独立的全基因组重要SNP。对于一起使用的SNP,我们发现了跨环境异质效应的证据。 SNP牵涉参与大脑发育过程和神经元至神经元通讯的基因。在X染色体的单独分析中,我们确定了10个独立的全基因组有意义的SNP,并估计男女的SNP遗传力均为〜0.3%,与部分剂量补偿一致。对教育程度和三种相关的认知表型的联合(多表型)分析产生了多基因评分,可以解释教育程度差异的11–13%和认知表现差异的7–10%。这种预测准确性大大提高了多基因评分作为研究工具的效用。

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