Shared neural basis and genetic architecture of psychiatric disorders - Project Summary/Abstract Psychiatric disorders carry a significant public health burden and are among the most debilitating health conditions that individuals can face. Despite tremendous efforts to collect and analyze genetic and clinical data from millions of participants across various psychiatric disorders, understanding the intricate pathophysiological pathways and identifying objective biomarkers for psychiatric risk management and patient treatment remain formidable tasks. The rapid evolution of large- scale imaging genetic data resources unlocks new possibilities to uncover shared neural foundations and genomic pathways pertinent to psychiatric disorders. Nevertheless, current research on imaging biomarkers in psychiatric genetics predominantly centers on mapping genetic effects of common variants within a single imaging modality, such as brain structural magnetic resonance imaging (MRI). These approaches often miss more extensive biological mechanisms that span across multiple imaging modalities and organs, and neglecting rare variants, which may have larger biological effects. In response to NOT-MH-21-175 (further analysis of human connectome data), we aim to is to conduct thorough secondary data analyses to enhance the integration of multi-organ imaging data of the brain and body, psychiatric genetic studies, and functional genomic data resources. These novel approaches will incorporate multi-organ multi-modal imaging data resources and will encompass a comprehensive range of genetic variants, from common to rare, across the full allele frequency spectrum. Our specific goals are as follows. Aim 1 involves integrating common and rare variations to understand the genetic co-architecture of psychiatric disorders and multi-organ imaging phenotypes of the brain and body. Leveraging our expertise in medical imaging data analysis, we will harness the latest open-access imaging genetic datasets from 9 studies involving more than 100,000 subjects, linked to extensive brain MRI, cardiac MRI, abdominal MRI, and retinal imaging data. In Aim 2, we will link imaging data to the tissue and cell type-specific functional landscape of psychiatric disorders and identify involved imaging traits within gnomically supported brain and body regions and cell types. By the convergence of evidence from genomic and imaging data integration, we aim to decode the complex genetic underpinnings of psychiatric disorders, leading to improved biological targets. Aim 3 will evaluate the putative causal mechanisms between imaging phenotypes and psychiatric disorders. This research project aims to substantially advance the integration of both population-scale imaging resources and curated functional genomic databases into psychiatric genetic studies, providing a novel multi-organ perspective that broadens the scope for identifying biomarkers and understanding the etiology of psychiatric diseases.
