Understanding the genomic basis of post-traumatic stress disorder through integrative analysis of rare variants and other omics data

Virginia Commonwealth University, Richmond VA

Investigators

Abstract

ABSTRACT Posttraumatic stress disorder (PTSD) is a commonly occurring condition following exposure to traumatic events with significant clinical, quality of life, and economic impact. PTSD is moderately heritable. Significant advances have been made through efforts of consortia and large-scale genetic studies to shift PTSD from a disorder with low genetic discoverability to one with a growing number of identified, replicable common genetic variants and significant genetic correlations with other neuropsychiatric and substance use disorders. In addition, the integration of multi-omics approaches (i.e., information from the genome, epigenome, proteome, and transcriptome) has identified pathways and tissues associated with the disorder. Rare non-coding functional variants are also an important component of genetic risk. The integration of rare variants with common variants into these multi-omics approaches has not to date been done for PTSD. The proposed study seeks to fill this gap by building upon prior work by our group 1) observing rare-variant based genes and pathways associated with PTSD from a pilot study using a whole exome sequencing (WES) dataset, and 2) identifying additional genes associated with other neuropsychiatric and substance use disorders by integrating rare variants from WES datasets and other omics datasets. We aim to leverage existing large-scale WES and whole genome sequencing (WGS) datasets and biorepositories and use these integrative approaches to identify additional genetic signals for PTSD. To do so, we will develop analytic pipelines to analyze available datasets for PTSD phenotypes from the UK Biobank (500K WES/WGS) and the All of Us study (245K WGS). Our analyses will impute, harmonize, and integrate phenotypic information available from these select biobanks to increase sample sizes and in turn power to detect effects and prioritize genes associated with PTSD using rare variant information from WES/WGS data. We further propose to jointly analyze existing gene-sets associated with PTSD with rare variants from sequencing data to improve genetic detection. We will also leverage the genetic correlation among other conditions to increase statistical power by jointly analyzing sequencing datasets of PTSD and other comorbid disorders. The overarching goal of this work is to integrate rare variants from large scale sequencing biobank datasets and available omics information to capitalize on the full frequency spectrum of variants to identify additional, novel genetic signals associated with PTSD. The knowledge gained and pipelines developed from study goals will be critical for future R01-scale efforts to extend this approach to other datasets and phenotypes and identify targets for prevention and treatment of PTSD.