From In Vitro Genotoxicity Assays to Human Biomarkers: Interpreting DNA Damage Signals in Long-Term SSRI Therapy through a Translational Neurotoxicology Lens.

Selective serotonin reuptake inhibitors (SSRIs) are among the most frequently prescribed long-term neuropsychiatric medications, making any potential impact on genomic stability a clinically relevant safety question. Interpreting an SSRI “genotoxicity signal,” however, is challenging because evidence spans heterogeneous endpoints (DNA strand breaks, oxidative base lesions, micronuclei/chromosomal damage, and DNA-damage response markers) and experimental systems with widely different exposure conditions. In this translational review, we synthesize in vitro, in vivo, and human biomarker evidence to clarify what reported DNA-damage findings do—and do not—imply for chronic SSRI therapy. Across cell-based models, several SSRIs can induce oxidative stress–linked DNA-damage endpoints and DNA-damage response activation, but these effects commonly emerge at micromolar concentrations that are supratherapeutic and/or near cytotoxicity thresholds, and their magnitude can vary with metabolic competence and exposure design. Animal studies show mixed outcomes, including endpoint discordance between comet and micronucleus assays and occasional evidence of clastogenic or aneugenic effects under specific dosing regimens, limiting generalization from any single positive finding. Human biomarker studies are the most direct evidence for clinical relevance but remain limited and sensitive to confounding by indication. Available data are more consistent with an absence of a robust, clinically meaningful peripheral-blood genotoxic signal during SSRI therapy, while acknowledging scarce longitudinal follow-up, heterogeneous endpoints, and incomplete control for disease state, lifestyle, and co-medications. We propose an “interpretation ladder” to reconcile discrepancies across evidence streams and outline priorities for future research, including therapeutically relevant exposure modeling (with attention to unbound exposure), standardized reporting and quality practices, and well-controlled multi-endpoint longitudinal cohorts with transparent data sharing.