Correlation between cortical gene expression and resting-state functional network centrality in healthy young adults

Resting-state functional connectivity in the human brain is heritable, and previous studies have investigated the genetic basis underlying functional connectivity. However, at present, the molecular mechanisms associated with functional network centrality are still largely unknown. In this study, functional networks were constructed, and the graph-theory method was employed to calculate network centrality in 100 healthy young adults from the Human Connectome Project. Specifically, functional connectivity strength (FCS), also known as the degree centrality of weighted networks, is calculated to measure functional network centrality. A multivariate technique of partial least squares regression (PLSR) was then conducted to identify genes whose spatial expression profiles best predicted the FCS distribution. We found that FCS spatial distribution was significantly positively correlated with the expression of genes defined by the first PLSR component. The FCS-related genes we identified were significantly enriched for ion channels, axon guidance, and synaptic transmission. Moreover, FCS-related genes were preferentially expressed in cortical neurons and young adulthood and were enriched in numerous neurodegenerative and neuropsychiatric disorders. Furthermore, a series of validation and robustness analyses demonstrated the reliability of the results. Overall, our results suggest that the spatial distribution of FCS is modulated by the expression of a set of genes associated with ion channels, axon guidance, and synaptic transmission.

Automated summary

This study investigated the relationship between functional network centrality and gene expression, finding that the spatial distribution of FCS is modulated by a set of genes associated with ion channels, axon guidance, and synaptic transmission. The identified FCS-related genes are preferentially expressed in cortical neurons and young adulthood, and enriched in various neurodegenerative and neuropsychiatric disorders. Validation and robustness analyses support the reliability of the results.