Particulate Matter Exposure and Default Mode Network Equilibrium During Early Adolescence

Abstract

Background: Air pollution exposure has been associated with adverse cognitive and mental health outcomes in children, adolescents, and adults, although youth may be particularly susceptible given ongoing brain development. However, the neurodevelopmental mechanisms underlying the associations among air pollution, cognition, and mental health remain unclear. We examined the impact of particulate matter (PM_2.5) on resting-state functional connectivity (rsFC) of the default mode network (DMN) and three key attention networks: dorsal attention, ventral attention, and cingulo-opercular. Methods: Longitudinal changes in rsFC within/between networks were assessed from baseline (9-10 years) to the 2-year follow-up (11-12 years) in 10,072 youth (M ± SD = 9.93 + 0.63 years; 49% female) from the Adolescent Brain Cognitive Development (ABCD^®) study. Annual ambient PM_2.5 concentrations from the 2016 calendar year were estimated using hybrid ensemble spatiotemporal models. RsFC was estimated using functional neuroimaging. Linear mixed models were used to test associations between PM_2.5 and change in rsFC over time while adjusting for relevant covariates (e.g., age, sex, race/ethnicity, parental education, and family income) and other air pollutants (O₃, NO₂). Results: A PM_2.5 × time interaction was significant for within-network rsFC of the DMN such that higher PM_2.5 concentrations were associated with a smaller increase in rsFC over time. Further, significant PM_2.5 × time interactions were observed for between-network rsFC of the DMN and all three attention networks, with varied directionality. Conclusion: PM_2.5 exposure was associated with alterations in the development and equilibrium of the DMN-a network implicated in self-referential processing-and anticorrelated attention networks, which may impact trajectories of cognitive and mental health symptoms across adolescence.

Keywords: Developmental biology; Psychiatry; Resting-state networks.

FIG. 1.

(A) Significant PM_{2.5 ×} time interaction on within-network resting-state functional connectivity (rsFC) of the default mode network (DMN). For ease of interpretation, PM_2.5 exposure is depicted as high/low groups, based on a median split. (B) Significant main effect of PM_2.5 on within-network rsFC of the cingulo-opercular network (CON). Both A and B display the predicted outcomes (i.e., Fischer z-transformed rsFC values), from the fully adjusted (i.e., covariates and other pollutants) linear mixed-effect models. The shaded area represents the confidence limits of the predicted outcomes.

FIG. 2.

Significant PM_2.5 × time interactions on between-network resting-state functional connectivity (rsFC) of the default mode network (DMN) with the three attention networks. (A) DAN: dorsal attention network. (B) VAN: ventral attention network. (C) CON: cingulo-opercular network. For ease of interpretation, graphs depict PM_2.5 exposure as high/low groups, based on a median split, and the predicted outcomes from the fully adjusted (i.e., covariates and other pollutants) linear mixed-effect models (i.e., Fischer z-transformed rsFC values). The shaded area represents the confidence limits of the predicted outcomes.

FIG. 3.

(A) Significant PM_2.5 × time interaction on between-network resting-state functional connectivity (rsFC) of the cingulo-opercular network (CON) and the ventral attention network (VAN). For ease of interpretation, the graph depicts PM_2.5 exposure as high/low groups, based on a median split. (B) Significant main effect of PM_2.5 on between-network rsFC of the CON and VAN. Both A and B display the predicted outcomes (i.e., Fischer z-transformed rsFC values), from the fully adjusted (i.e., covariates and other pollutants) linear mixed-effect models. The shaded area represents the confidence limits of the predicted outcomes.