Organization of the social cognition network predicts future depression and interpersonal impairment: a prospective family-based study

Abstract

Deficits in social cognition and functioning are common in major depressive disorder (MDD). Still, no study into the pathophysiology of MDD has examined the social cognition-related neural pathways through which familial risk for MDD leads to depression and interpersonal impairments. Using resting-state fMRI, we applied a graph theoretical analysis to quantify the influence of nodes within the fronto-temporo-parietal cortical social cognition network in 108 generation 2 and generation 3 offspring at high and low-risk for MDD, defined by the presence or absence, respectively, of moderate to severe MDD in generation 1. New MDD episodes, future depressive symptoms, and interpersonal impairments were tested for associations with social cognition nodal influence, using regression analyses applied in a generalized estimating equations approach. Increased familial risk was associated with reduced nodal influence within the network, and this predicted new depressive episodes, worsening depressive symptomatology, and interpersonal impairments, 5-8 years later. Findings remained significant after controlling for current depressive/anxiety symptoms and current/lifetime MDD and anxiety disorders. Path-analysis models indicate that increased familial risk impacted offspring's brain function in two ways. First, high familial risk was indirectly associated with future depression, both new MDD episodes and symptomatology, via reduced nodal influence of the right posterior superior temporal gyrus (pSTG). Second, high familial risk was indirectly associated with future interpersonal impairments via reduced nodal influence of right inferior frontal gyrus (IFG). Finally, reduced nodal influence was associated with high familial risk in (1) those who had never had MDD at the time of scanning and (2) a subsample (n = 52) rescanned 8 years later. Together, findings reveal a potential pathway for the intergenerational transmission of vulnerability via the aberrant social cognition network organization and suggest using the connectome of neural network related to social cognition to identify intervention and prevention targets for those particularly at risk.