Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
Department of Psychology, University of Edinburgh, Edinburgh, UK.
Mol Psychiatry. 2019 Feb;24(2):169-181. doi: 10.1038/s41380-017-0001-5. Epub 2018 Jan 11.
Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (r = 0.70). We used these findings as foundations for our use of a novel approach-multi-trait analysis of genome-wide association studies (MTAG; Turley et al. 2017)-to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination-as well as genes expressed in the synapse, and those involved in the regulation of the nervous system-may explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.
智力，或一般认知功能，与许多特征在表型和遗传上相关，包括广泛的身体和心理健康变量。教育与智力在遗传上密切相关（r=0.70）。我们利用这些发现作为基础，采用了一种新的方法——全基因组关联研究的多性状分析（MTAG；Turley 等人，2017 年）——将两项关于教育和智力的大型全基因组关联研究结合起来，增加了统计效力，从而产生了迄今为止报道的最大规模的智力全基因组关联研究。我们的研究有四个目标：第一，促进发现与智力相关的新遗传位点；第二，增进我们对智力差异生物学的理解；第三，研究以这种方式结合遗传上相关的性状是否会产生与智力的主要表型一致的结果；最后，测试这种新的智力元分析数据样本在独立样本中预测表型智力的效果如何。通过使用 MTAG 合并数据集，我们的功能样本量从 199242 名参与者增加到 248482 名。我们使用 SNP 基和基因基全基因组关联研究发现了 187 个与智力相关的独立位点，涉及 538 个基因。我们发现神经发生和髓鞘形成的证据，以及突触中表达的基因和参与神经系统调节的基因，可能解释了智力的一些生物学差异。我们的综合分析结果表明，遗传相关性与以前的智力全基因组关联研究结果相同，为这些遗传相关表型的荟萃分析提供了支持。
