Air pollution interacts with genetic risk to influence cortical networks implicated in depression

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 118; no. 46; pp. 1 - 9
• Main Authors: Li, Zhi, Yan, Hao, Zhang, Xiao, Shah, Shefali, Yang, Guang, Chen, Qiang, Han, Shizhong, Zhang, Dai, Weinberger, Daniel R., Yue, Weihua, Tan, Hao Yang
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 16.11.2021
• Subjects: Adult; Air Pollutants - adverse effects; Air pollution; Air Pollution - adverse effects; Anxiety - chemically induced; Biological Sciences; Brain; Brain - drug effects; Cognition; Depression - chemically induced; Environmental Exposure - adverse effects; Epidemiology; Exposure; Humans; Information transfer; Mental depression; Mental disorders; Morbidity; Neural networks; Particulate matter; Particulate Matter - adverse effects; Pollution control; Polygenic inheritance; Problem solving; Risk; Risk Factors; Short term memory; Social Sciences; gene–environment interaction; fine particulate matter; major depressive disorder; PM2.5; polygenic risk
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.2109310118

Air pollution is a reversible cause of significant global mortality and morbidity. Epidemiological evidence suggests associations between air pollution exposure and impaired cognition and increased risk for major depressive disorders. However, the neural bases of these associations have been unclear. Here, in healthy human subjects exposed to relatively high air pollution and controlling for socioeconomic, genomic, and other confounders, we examine across multiple levels of brain network function the extent to which particulate matter (PM2.5) exposure influences putative genetic risk mechanisms associated with depression. Increased ambient PM2.5 exposure was associated with poorer reasoning and problem solving and higher-trait anxiety/depression. Working memory and stress-related information transfer (effective connectivity) across cortical and subcortical brain networks were influenced by PM2.5 exposure to differing extents depending on the polygenic risk for depression in gene-by-environment interactions. Effective connectivity patterns from individuals with higher polygenic risk for depression and higher exposures with PM2.5, but not from those with lower genetic risk or lower exposures, correlated spatially with the coexpression of depression-associated genes across corresponding brain regions in the Allen Brain Atlas. These converging data suggest that PM2.5 exposure affects brain network functions implicated in the genetic mechanisms of depression.