With a few hundred twins, authors examined genetic & environmental influence on all pairwise functional connections between 264 brain regions (~35,000 functional connections) & found high non-shared environmental influence across the entire connectome, moderate heritability in roughly half of all connections, & weak-to-moderate shared environmental influences

Genetic and environmental influence on the human functional connectome. Andrew E. Reineberg, Alexander S. Hatoum, John K. Hewitt, Marie T. Banich, Naomi P. Friedman. bioRxiv, https://doi.org/10.1101/277996

Abstract: Detailed mapping of genetic and environmental influences on the functional connectome is a crucial step toward developing intermediate phenotypes between genes and clinical diagnoses or cognitive abilities. Historical attempts to estimate the genetic etiology of the connectome have focused on large-scale brain networks - obscuring possible heterogeneity among or novel communities of small network subcomponents. In the current study, we analyze resting-state data from two, adult twin samples - 198 twins from the Colorado Longitudinal Twin Sample and 422 twins from the Human Connectome Project - to examine genetic and environmental influence on all pairwise functional connections between 264 brain regions (~35,000 functional connections). We find high non-shared environmental influence across the entire connectome, moderate heritability in roughly half of all connections, and weak-to-moderate shared environmental influences. The pattern of genetic influence across the connectome is related to a priori notions of functional brain networks but also highly heterogeneous as confirmed by a hierarchical clustering analysis of the genetic profile of all 264 regions. Additionally, we confirm genetic influences on connections are independent of genetic influences shared with a global summary measure of brain connectivity - an important validation analysis for future, high-dimensionality genetic neuroimaging studies. Together, our analyses reveal a novel genetic taxonomy of brain regions and have implications for studies employing multivariate signals for prediction purposes. Variation across the population in those neurobiological signals is influenced by genes and the environment in different spatial locations and to different degrees suggesting genetic risk factors may be limited to a subset of the connectome.