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

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.

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.

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.

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.