Abstract
Background: Observational studies have demonstrated strong bi-directional associations between depression and peripheral artery disease (PAD), and patients suffering from PAD who have depressive symptoms are known to have worse outcomes. Whether these associations represent causal pathways remains unknown but has important implications for disease management. Methods: We performed causal inference experiments using bi-directional Mendelian randomization. We employed summary statistics from the 2019 Psychiatric Genomics Consortium meta-analysis of major depressive disorder (MDD) comprised of 807,553 participants (246,363 cases) of European ancestry and the VA Million Veteran Program GWAS of PAD comprised of 243,060 participants (31,307 cases) of multiple ancestries to test the association between genetic liability to MDD and genetic liability to PAD. Genetic instruments for each exposure were constructed using independent (r 2 < 0.1 by 1000 Genomes EUR LD reference panel) variants associated with the exposure at genome-wide significance (p < 5x10 -8 ). Inverse-variance weighted MR was used as the primary analysis method, with weighted-median MR, MR-PRESSO, and Steiger filtering based MR performed as sensitivity analyses. F-statistics were calculated to assess weak-instrument bias. The Egger bias-intercept test was used to detect evidence of horizontal pleiotropy. Results: Increased genetic liability to MDD was associated with increased genetic liability to PAD (OR 1.2, 95%CI 1.1 - 1.3, p=.0001). We could not detect an effect of genetic liability to PAD on the genetic liability to MDD (OR 1.03, 95%CI 0.99 - 1.08). The results of sensitivity analyses that make different instrumental variable assumptions were consistent with these findings. Conclusions: These results suggest a causal relationship in which MDD increases the risk of PAD, but do not provide evidence to support the causal role of PAD in MDD. Ongoing analyses are focused on identifying potential mediators of the association between MDD and PAD and performing causal inference for the effect of other mental health traits on PAD.
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