Background Post-Traumatic Stress Disorder (PTSD) is a debilitating psychiatric disorder occurring in individuals exposed to trauma. To date, little is known about the genetic aetiology of the disorder, although the latest GWAS (carried out by the PGC-PTSD working group) demonstrates that genetic heritability is in line with other psychiatric disorders. PTSD development involves multi-systemic dysregulation in multiple brain regions and diverse peripheral tissues. Some peripheral systems are particularly interesting since epidemiologic evidence suggests that PTSD patients commonly have cardiovascular, metabolic and immune dysregulation. Methods Transcriptomic Imputation approaches use machine-learning methods to impute gene expression from large genotype data using curated eQTL reference panels. These offer an exciting opportunity to compare gene associations across neurological and peripheral tissues. Here, we apply CommonMind Consortium (CMC) and Genotype-Tissue Expression (GTEx) derived gene expression prediction models to the PGC-PTSD data (9,245 cases/ 24,285 controls). Models included 12 brain regions, five cardiovascular tissues, 2 endocrine tissues, the tibial nerve, adipose tissue and whole blood. Results We identified 24 significant gene-tissue associations, of which 5 were in peripheral tissues (adrenal gland, heart atrial appendage, tibial artery, tibial nerve). We stratified analyses according to trauma type (civilian vs. combat trauma), sex, and self-defined ancestry. Our three strongest associations were identified in military cohorts only, which supports the hypothesis that there is substantial genetic heterogeneity between civilian and combat PTSD risk. We used the PsychENCODE neuronal and non-neuronal reference map for two histone marks associated with transcription and open chromatin (3-trimethyl-lysine 4 (H3K4me3) and H3-acetyl-lysine 27 (H3K27ac) to understand patterns of histone modification among our PTSD-associated genes. Preliminary analyses indicate a significant correlation between PTSD-association statistics and the presence of both histone marks (correlation with neuronal H3K4me3, Pearson R=0.87, p=3.99×10-5). We intend to expand this analysis to include a wider range of histone modification marks. Discussion We will further expand these analyses to identify tissue specific gene clusters and enriched pathways across tissues or in specific tissues. Finally, we will use neuroimaging data and physiological cardiovascular data to functionally validate our results.