Abstract
BACKGROUND: Depression is a leading global health challenge, yet the role of Social Determinants of Health (SDH) in shaping depression risk – particularly through underlying biological mechanisms – remains insufficiently understood. This study leverages a multi-omics approach to explore how unfavorable social conditions influence depression through neural, and physiological pathways.
METHODS: Drawing on data from 257,698 participants in the UK Biobank. Cox proportional hazards regression models were used to examine the relationship between SDH, polygenic risk scores (PRS), and depression. Correlation analyses were conducted to explore associations between SDH, biomarkers, brain structure, and depression. Two-sample mendelian randomization (MR) was applied to investigate causal relationships, while structural equation modeling (SEM) was used to examine interactions among SDH, depression, brain structure, PRS, and immune-metabolic biomarkers.
RESULTS: Depression was significantly associated with SDH. Multivariable Cox regression showed that unfavorable SDH increased depression risk (HR = 1.916), and higher PRS was also linked to increased risk (HR = 1.288). The combination of unfavorable SDH and high PRS yielded the highest depression risk (HR = 2.578). MR analysis further emphasized the causal relationship between unfavorable SDH and depression. SDH was also linked to brain structural changes and metabolic markers, with smaller brain volumes in regions like the hippocampus and insula in the unfavorable SDH group, along with associations with biomarkers such as triglycerides and C-reactive protein. SEM analysis revealed that SDH influenced depression through immune-metabolic and brain structural pathways.
CONCLUSIONS: These findings underscore the multifaceted nature of depression, highlighting how social disadvantage becomes biologically embedded through genetic and physiological mechanisms. Addressing key modifiable components of SDH may represent a powerful strategy for targeted prevention, especially in genetically at-risk populations.