Towards Scalable Biomarker Discovery in Posttraumatic Stress Disorder: Triangulating Genomic and Phenotypic Evidence from a Health System Biobank

Abstract

Importance: Biomarkers can potentially improve the diagnosis, monitoring, and treatment of posttraumatic stress disorder (PTSD). However, PTSD biomarkers that are scalable and easily integrated into real-world clinical settings have not been identified.

Objective: To triangulate phenotypic and genomic evidence from a health system biobank with a goal of identifying scalable and clinically relevant biomarkers for PTSD.

Design setting and participants: The analysis was conducted between June to November 2024 using genomic samples and laboratory test results recorded in the Mass General Brigham (MGB) Health System. The analysis included 23,743 European ancestry participants from the nested MGB Biobank study.

Exposures: The first exposure was polygenic risk score (PRS) for PTSD, calculated using the largest available European ancestry genome-wide association study (GWAS), employing a Bayesian polygenic scoring method. The second exposure was a clinical diagnosis of PTSD, determined by the presence of two or more qualifying PTSD phecodes in the longitudinal electronic health records (EHR).

Main outcomes and measures: The primary outcomes were the inverse normal quantile transformed, median lab values of 241 laboratory traits with non-zero h ² _SNP estimates.

Results: Sixteen unique laboratory traits across the cardiometabolic, hematologic, hepatic, and immune systems were implicated in both genomic and phenotypic lab-wide association scans (LabWAS). Two-sample Mendelian randomization analyses provided evidence of potential unidirectional causal effects of PTSD liability on five laboratory traits.

Conclusion and relevance: These findings demonstrate the potential of a triangulation approach to uncover scalable and clinically relevant biomarkers for PTSD.

Figure 1.

Manhattan plots of lab-wide association scans (LabWAS) using (a) polygenic risk score for posttraumatic stress disorder (PRS_PTSD) as a predictor (left), and (b) PTSD diagnosis (Dx_PTSD) as a predictor (right). Lymphocytes* refers to automated lymphocyte count.

Figure 2.

Triangulation of results across PRS_PTSD and Dx_PTSD LabWAS, grouped by physiological systems. Statistical significance after Bonferroni correction from the genomic LabWAS (shown in triangles) and phenotypic LabWAS (shown in circles), grouped by physiological systems. Physiological systems are sorted alphabetically (top to bottom). Within each system, results are sorted alphabetically (left to right). Number of outcomes per system is listed in parentheses on the y-axis. All sixteen unique markers that are statistically significant in both analyses are concordant in the direction of association. Numeric estimates from the genomic and phenotypic LabWAS can be found in eTables 2 and 3, respectively.