Genetic associations and candidate functional genes linking depression and obesity: a multi-omics integrative study.

Introduction: Major depressive disorder (MDD) and obesity are intersecting global crises. Despite observational links, a clinical paradox persists: antidepressants often improve metabolic status, while weight loss rarely alleviates core depressive symptoms. This prompts closer examination of whether the depression-obesity relationship reflects asymmetric genetic architecture, shared liability, or statistical constraints that obscure definitive conclusions. Methods: We developed an integrative multi-omics framework leveraging large-scale population data from the National Health and Nutrition Examination Survey (NHANES) and East Asian genetic data. Epidemiological regression was applied to NHANES to characterize real-world phenotypic cross-talk. We utilized bidirectional Mendelian randomization (MR) to explore the direction of association, targeted summary-data-based MR (SMR) with heterogeneity in dependent instruments (HEIDI) testing to prioritize candidate functional genes, and single-cell RNA sequencing (scRNA-seq) of regulatory T cells (Tregs). In silico cell composition adjustment and virtual knockout (VKO) simulations were implemented to distinguish intrinsic cellular remodeling from compositional shifts and to infer convergent downstream programs. Results: Bidirectional MR yielded a nominally significant association from MDD to obesity risk (β = 0.0458, P = 0.0209), whereas the reverse path was inconclusive due to low statistical power (<10%), precluding definitive conclusions about directionality. SMR/HEIDI identified multiple FDR-significant obesity-associated genes, including NT5C2, ACYP2, and TMEM180, whereas on the depression side only ACAT1 reached nominal significance, positioning it as a borderline hypothesis-generating candidate. Cell composition adjustment suggested that transcriptional signals reflected intrinsic remodeling, preserving up to 98% of effect sizes for top candidates. At the molecular level, the conditions diverged: obesity risk was dominated by immune-compartment inflammation and post-transcriptional splicing dysregulation, whereas MDD risk was characterized by ribosomal translation perturbations. Strikingly, VKO simulations revealed convergence on a shared downstream program anchored in cytoskeletal reorganization and E2F-target modulation. Exploratory druggability screening nominated FDFT1 (with a phase 3 inhibitor) and ADORA2A as potential repurposing candidates requiring experimental validation. Conclusion: Our findings provide a hypothesis-generating reframing of the traditional comorbidity model, suggesting that divergent molecular programs may converge on shared pathways. Although the full extent of bidirectional genetic relationships remains unconfirmed, these findings offer a preliminary foundation for exploring therapeutic strategies at the mood-metabolism interface.