Human blood metabolites and risk of post-traumatic stress disorder: A Mendelian randomization study.

Abstract

Background: Post-traumatic stress disorder (PTSD) is a debilitating chronic mental disorder that leads to reduced quality of life and increased economic burden. Observational studies have found an association between human blood metabolites and PTSD. Nonetheless, these studies have limitations and are subject to confounding factors as well as reverse causation. Herein, we employed a two-sample Mendelian randomization (MR) approach for the systematic analysis of the blood metabolites and PTSD causal link.

Methods: Data for the human blood metabolome, cerebrospinal fluid (CSF) metabolome, and PTSD were obtained from publicly available summary-level genome-wide association studies (GWAS), respectively. The inverse variance weighted (IVW) approach represented the main analytic method for assessing exposure-outcome causal associations, employing multiple sensitivity analyses to verify the results' stability. In addition, replication and meta-analysis, steiger test and reverse MR analysis methods were performed to clarify further that these metabolites have independent causal effects on PTSD. Finally, the results of blood and CSF metabolomics analyses were synthesized to obtain biological markers with a causal link to PTSD.

Results: Conclusively, we identified potential causal associations between six blood metabolites and PTSD. The sensitivity analyses elucidated the absence of pleiotropy or heterogeneity in the MR results. The Steiger test and reverse MR analysis did not reveal reverse causal associations, proving the robustness of our results. Combined blood and CSF metabolome analyses showed the same trend for theophylline.

Conclusion: This study reveals a strong causal link between metabolites and PTSD, which can be used as a biomarker for clinical PTSD disease screening and prevention. This study also provides a new perspective on the mechanism of metabolite-mediated PTSD development by combining genomics and metabolomics.