Association between antidepressant use and the risk of type 2 diabetes: a multi-stage Mendelian randomization study

Depression is a highly prevalent condition, and antidepressants are widely used to manage its symptoms. However, concerns have emerged regarding a potential causal relationship between antidepressant use and the development of type 2 diabetes (T2D). Understanding these potential relationships may provide insights into the metabolic heterogeneity of antidepressant medications.

This study utilized two-sample Mendelian randomization (MR) to investigate the potential causal effects of genetic liability to antidepressant use on the risk of T2D. Genome-wide association study (GWAS) summary datasets were employed, covering various classes of antidepressants (120,446 cases and 94,450 controls) and T2D (discovery set: 80,154 cases and 853,816 controls; validation set: 71,728 cases and 369,007 controls). MR analysis was performed to estimate odds ratios (ORs) and assess the causal associations between antidepressant use and T2D.

The MR analysis identified significant causal associations between liability to use of specific antidepressants, including citalopram and sertraline, and T2D susceptibility. Validation using meta-analysis data of T2D confirmed these findings, with citalopram (OR 1.05, 95% CI 1.01-1.09, P = 0.018) and sertraline (OR 1.02, 95% CI 1.01-1.04, P = 1.22E-03) demonstrating significant associations. Additionally, the use of amitriptyline showed a suggestive association with T2D susceptibility (OR 1.04, 95% CI 1.01-1.08, P = 0.018).

This study provides genetic evidence suggesting medication-specific associations between antidepressant use liability and T2D susceptibility. Although the observed effect sizes were modest, these results highlight that the metabolic effects of individual antidepressants may vary, thus, warranting further studies to determine the clinical relevance of our findings.