Amygdala functional connectivity, HPA axis genetic variation, and life stress in children and relations to anxiety and emotion regulation

Abstract

Internalizing pathology is related to alterations in amygdala resting state functional connectivity, potentially implicating altered emotional reactivity and/or emotion regulation in the etiological pathway. Importantly, there is accumulating evidence that stress exposure and genetic vulnerability impact amygdala structure/function and risk for internalizing pathology. The present study examined whether early life stress and genetic profile scores (10 single nucleotide polymorphisms within 4 hypothalamic-pituitary-adrenal axis genes: CRHR1, NR3C2, NR3C1, and FKBP5) predicted individual differences in amygdala functional connectivity in school-age children (9- to 14-year-olds; N = 120). Whole-brain regression analyses indicated that increasing genetic "risk" predicted alterations in amygdala connectivity to the caudate and postcentral gyrus. Experience of more stressful and traumatic life events predicted weakened amygdala-anterior cingulate cortex connectivity. Genetic "risk" and stress exposure interacted to predict weakened connectivity between the amygdala and the inferior and middle frontal gyri, caudate, and parahippocampal gyrus in those children with the greatest genetic and environmental risk load. Furthermore, amygdala connectivity longitudinally predicted anxiety symptoms and emotion regulation skills at a later follow-up. Amygdala connectivity mediated effects of life stress on anxiety and of genetic variants on emotion regulation. The current results suggest that considering the unique and interacting effects of biological vulnerability and environmental risk factors may be key to understanding the development of altered amygdala functional connectivity, a potential factor in the risk trajectory for internalizing pathology.

Figure 1. Normative Left Amygdala Connectivity and Regions Showing Significant Regression Effects

This figure presents a surface rendering of the normative resting state connectivity patterns found with the left amygdala. Specifically, colors on the surface indicate z-statistics for the whole-brain one-sample t-test indicating areas that show significant connectivity with the left amygdala. The normative connectivity results are also presented in axial slices in Figure S1. The center of the left amygdala seed is indicated by a green sphere. Other spheres indicate the peaks of regression effects: blue = main effects of genetic profile scores; yellow = main effects of life events; purple = genetic profile score x life events interactions. Axial slices through these regions showing altered connectivity are presented in Figure S3.

Figure 2. Simple Slope Plots for Interaction Effects

Simple slope effects of life events (top row) and genetic profile scores (bottom row) predicting two regions showing a genetic profile score x life events interaction on left amygdala connectivity are shown here, specifically a cluster in the caudate (left column) and the middle frontal gyrus (right column). These regions were chosen to exemplify the interaction patterns predicting regions showing typically positive connectivity, e.g. the caudate, or negative connectivity, e.g. the middle frontal gyrus. Simple slopes for each variable were presented at high (mean + 1 SD), mean, and low (mean − 1 SD) levels of the interacting variable and effects controlled for all other variables in the regressions (Table 5). * p<0.05, ** p<0.01, *** p<0.001

Figure 3. Mediation Models Predicting Outcomes at Follow-Up

This figure presents a schematic of the mediation results testing two model: (A) left amygdala-postcentral gyrus connectivity mediates the relations between genetic profile scores (GPS) and emotion regulation skills at follow-up and (B) left amygdala-anterior cingulate cortex (ACC) connectivity and concurrent anxiety symptoms act as serial mediators of the effects of life events (LE) on follow-up anxiety symptoms. Standardized regression coefficients (β) are presented for all effects. The path from the independent to dependent variable represents the total effect. * p<0.05, ** p<0.01, *** p<0.001