General dimensions of human brain morphometry inferred from genome-wide association data

主成分分析 全基因组关联研究 生物 遗传建筑学 遗传关联 人类连接体项目 神经影像学 生命银行 连锁不平衡 认知 人口 遗传学 神经科学 数量性状位点 单核苷酸多态性 基因型 医学 计算机科学 人工智能 基因 环境卫生 功能连接
作者
Anna E. Fürtjes,Ryan Arathimos,Jonathan R. I. Coleman,James H. Cole,Simon R. Cox,Ian J. Deary,Javier de la Fuente,James W. Madole,Elliot M. Tucker‐Drob,Stuart J. Ritchie
标识
DOI:10.1101/2021.10.22.465437
摘要

Abstract Background Understanding the neurodegenerative mechanisms underlying cognitive declines in the general population may facilitate early detection of adverse health outcomes in late life. This study investigates biological pathways shared between brain morphometry, ageing, and cognitive ability. Methods We develop Genomic Principal Components Analysis (genomic PCA) to model general dimensions of variance in brain morphometry within brain networks at the level of their underlying genetic architecture. With genomic PCA we extract genetic principal components (PCs) that index global dimensions of genetic variance across phenotypes (unlike ancestral PCs that index genetic similarity between participants). Genomic PCA is applied to genome-wide association data for 83 brain regions which we calculated in 36,778 participants of the UK Biobank cohort. Using linkage disequilibrium score regression, we estimate genetic overlap between brain networks and indices of cognitive ability and brain ageing. Results A genomic principal component (PC) representing brain-wide dimensions of shared genetic architecture accounted for 40% of the genetic variance across 83 individual brain regions. Genomic PCs corresponding to canonical brain networks accounted for 47-65% of the genetic variance in the corresponding brain regions. These genomic PCs were negatively associated with brain age ( r g = −0.34). Loadings of individual brain regions on the whole-brain genomic PC corresponded to sensitivity of a corresponding region to age ( r = - 0.27). We identified positive genetic associations between genomic PCs of brain morphometry and general cognitive ability ( r g = 0.17-0.21). Conclusion These results demonstrate substantial shared genetic etiology between connectome-wide dimensions of brain morphometry, ageing, and cognitive ability, which will help guide investigations into risk factors and potential interventions of ageing-related cognitive decline.
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