Shared genetics and causal relationships between major depressive disorder and COVID-19 related traits: a large-scale genome-wide cross-trait meta-analysis

Ziqi Li; Weijia Dang; Tianqi Hao; Hualin Zhang; Ziwei Yao; Wenchao Zhou; Liufei Deng; Hongmei Yu; Yalu Wen; Long Liu

doi:10.3389/fpsyt.2023.1144697

Shared genetics and causal relationships between major depressive disorder and COVID-19 related traits: a large-scale genome-wide cross-trait meta-analysis

Front Psychiatry. 2023 Jun 23:14:1144697. doi: 10.3389/fpsyt.2023.1144697. eCollection 2023.

Authors

Ziqi Li¹, Weijia Dang¹, Tianqi Hao¹, Hualin Zhang¹, Ziwei Yao¹, Wenchao Zhou¹, Liufei Deng¹, Hongmei Yu¹, Yalu Wen^{1

2}, Long Liu¹

Affiliations

¹ Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
² Department of Statistics, University of Auckland, Auckland, New Zealand.

Abstract

Introduction: The comorbidity between major depressive disorder (MDD) and coronavirus disease of 2019 (COVID-19) related traits have long been identified in clinical settings, but their shared genetic foundation and causal relationships are unknown. Here, we investigated the genetic mechanisms behind COVID-19 related traits and MDD using the cross-trait meta-analysis, and evaluated the underlying causal relationships between MDD and 3 different COVID-19 outcomes (severe COVID-19, hospitalized COVID-19, and COVID-19 infection).

Methods: In this study, we conducted a comprehensive analysis using the most up-to-date and publicly available GWAS summary statistics to explore shared genetic etiology and the causality between MDD and COVID-19 outcomes. We first used genome-wide cross-trait meta-analysis to identify the pleiotropic genomic SNPs and the genes shared by MDD and COVID-19 outcomes, and then explore the potential bidirectional causal relationships between MDD and COVID-19 outcomes by implementing a bidirectional MR study design. We further conducted functional annotations analyses to obtain biological insight for shared genes from the results of cross-trait meta-analysis.

Results: We have identified 71 SNPs located on 25 different genes are shared between MDD and COVID-19 outcomes. We have also found that genetic liability to MDD is a causal factor for COVID-19 outcomes. In particular, we found that MDD has causal effect on severe COVID-19 (OR = 1.832, 95% CI = 1.037-3.236) and hospitalized COVID-19 (OR = 1.412, 95% CI = 1.021-1.953). Functional analysis suggested that the shared genes are enriched in Cushing syndrome, neuroactive ligand-receptor interaction.

Discussion: Our findings provide convincing evidence on shared genetic etiology and causal relationships between MDD and COVID-19 outcomes, which is crucial to prevention, and therapeutic treatment of MDD and COVID-19.

Keywords: COVID-19; Mendelian randomization; cross-trait meta-analysis; functional annotation; major depressive disorder.