Shared genetic influences on resting-state functional networks of the brain

Abstract

The amplitude of activation in brain resting state networks (RSNs), measured with resting-state functional MRI, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome-wide association studies (GWAS) explored the genetic underpinnings of RSNs, but do not describe their pleiotropic nature. In this study, we used multivariate genomic structural equation modelling to model latent factors that capture shared genomic influences. Using summary statistics from GWAS of 21 RSNs in the UK Biobank (N = 21,081) sample, we show that their genetic organization can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. We identify single-nucleotide polymorphisms and genes associated with the joint architecture of resting-state networks. We conclude that multivariate models of genetic structures can help us to learn more about the biological mechanisms involved in brain function.