Limited efforts have been paid to evaluate the potential relationships between structural and functional brain imaging and intelligence until now. We performed a two-stage analysis to systematically explore the relationships between 3144 brain image-derived phenotypes (IDPs) and intelligence. First, by integrating genome-wide association studies (GWAS) summaries data of brain IDPs and two GWAS summary datasets of intelligence, we systematically scanned the relationship between each of the 3144 brain IDPs and intelligence through linkage disequilibrium score regression (LDSC) analysis. Second, using the individual-level genotype and intelligence data of 160 124 subjects derived from UK Biobank datasets, polygenetic risk scoring (PRS) analysis was performed to replicate the common significant associations of the first stage. In the first stage, LDSC identified 6 and 2 significant brain IDPs significantly associated with intelligence dataset1 and dataset2, respectively. It is interesting that NET100_0624 showed genetic correlations with intelligence in the two datasets of intelligence. After adjusted for age and sex as the covariates, NET100_0624 (P = 5.26 × 10⁻²⁰, Pearson correlation coefficients = −0.02) appeared to be associated with intelligence by PRS analysis of UK Biobank samples. Our findings may help to understand the genetic mechanisms of the effects of brain structure and function on the development of intelligence.

中文翻译：

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智力和脑成像表型之间的大规模遗传相关扫描。

到目前为止，为评估结构和功能性大脑成像与智能之间的潜在关系，人们付出了有限的努力。我们进行了两个阶段的分析，以系统地探索3144个脑图像衍生表型（IDP）与智力之间的关系。首先，通过整合大脑IDP的全基因组关联研究（GWAS）汇总数据和两个GWAS智力的摘要数据集，我们通过连锁不平衡得分回归（LDSC）分析系统地扫描了3144个大脑IDP中的每一个与智力之间的关系。其次，使用来自UK Biobank数据集的160124名受试者的个体水平基因型和情报数据，进行了多基因风险评分（PRS）分析，以复制第一阶段的常见显着关联。在第一阶段 LDSC分别确定了与情报数据集1和数据集2显着相关的6个和2个重要的大脑IDP。有趣的是，NET100_0624在两个智能数据集中显示出与智能的遗传相关性。调整年龄和性别作为协变量后，NET100_0624（P = 5.26×10⁻²⁰（Pearson相关系数= −0.02）通过UK Biobank样本的PRS分析似乎与智力相关。我们的发现可能有助于了解大脑结构和功能对智力发展的影响的遗传机制。