Background: Sertraline, a widely prescribed SSRI, has been linked to T2DM, with its target gene SLC29A4 also associated with increased diabetes risk. Understanding this relationship can optimize treatment strategies and enhance patient safety.
Objectives: This study aims to assess the association between sertraline use and metabolic disorders, particularly type 2 diabetes mellitus (T2DM). Aim 1 is to determine whether extended sertraline use increases the risk of metabolic disorders and to identify the most affected disorder using FAERS data. Aim 2 is to assess the causal relationship between sertraline and major metabolic disorder subtypes at the genetic level.
Methods: This study integrates pharmacovigilance analysis and MR to investigate the association between sertraline use and T2DM. We analyzed FAERS data using chi-square tests, proportional reporting ratios (PRR), reporting odds ratios (ROR), and relative reporting ratios (RRR). A PRR > 2, an ROR > 2, and an RRR > 2 indicate a significant signal. A chi-square value (χ²) > 3.84 with n > 1 also suggests a significant association. To infer causality, we performed an MR analysis using GWAS data from European populations. We examined SNPs near the sertraline target gene (SLC29A4) and estimated causal effects with the inverse-variance weighted (IVW) method.
Results: The aim 1, pharmacovigilance analysis of FAERS data filtered 653 T2DM cases associated with sertraline use, showing a significant risk signal (χ² = 1417.154, PRR = 3.999, 95% CI: 3.700–4.323; ROR = 4.016, 95% CI: 3.714–4.343; RRR = 3.896, 95% CI: 3.604–4.211). Other significant associations included hepatic steatosis (n = 269, PRR = 3.370, 95% CI: 2.985–3.804) and circulatory collapse (n = 181, PRR = 2.186, 95% CI: 1.887–2.533). No increased risk was observed for cardiovascular disorders or lipid metabolism disorders (PRR < 1, ROR < 1). In the aim2, MR analysis of SLC29A4 suggested a potential genetic mechanism (OR = 1.1566, 95% CI: 1.0012–1.3360, P = 0.048).
Conclusions: Aim 1 provides strong evidence that sertraline use increases the risk of metabolic disorders, with T2DM emerging as the primary outcome. Mendelian Randomization in aim 2 supports a potential causal relationship between sertraline and T2DM at the genetic level. Given the widespread use of sertraline, clinicians should monitor glucose levels in long-term users, especially those at risk for T2DM. Future research should focus on mechanistic studies, prospective cohorts, and RCTs to confirm these findings and identify high-risk populations. Expanding genetic analyses may enable personalized risk assessment. These findings highlight the need for greater clinical awareness and metabolic monitoring in sertraline users.
