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

Abstract

SummaryUnderstanding the neurodegenerative mechanisms underlying cognitive declines in the general population may facilitate early detection of adverse health outcomes in late life. We develop Genomic Principal Components Analysis (genomic PCA) to elucidate the complex biological connections between macroscopic brain organisation, ageing, and cognitive ability. A genetic principal component (PC) representing dimensions of shared genetic architecture in brain morphometry across the whole brain accounted for 40% of the genetic variance across 83 individual brain regions. Genomic PCs corresponding to more specific canonical brain networks of interest accounted for 47-65% of the genetic variance in the corresponding brain regions. These genomic PCs were negatively associated with a measure of brain age (rg = -0.34) and the loadings of individual brain regions on the whole brain genomic PC corresponded to sensitivity of the corresponding region to age (r = -0.27). We identified positive genetic associations between the genomic PCs of brain morphometry and a general factor of cognitive ability (rg = 0.17-0.21 for different networks). Genomic PCA allowed us to model structural covariance within brain networks at the level of their underlying genetic architecture. We identified substantial genetic overlap between brain morphometry, ageing, and cognitive ability.