Integrated Early Life Factors and Depression: A Multi-Level Investigation of Brain Structural, Immunometabolic, and Genetic Mechanisms.

Abstract

Background: Early life factors before age 18 years significantly influence depression risk, but their differential contributions and biological mechanisms remain understudied.

Methods: In this prospective UK Biobank study (N=104,035), an early life factor score (ELFS) was constructed using elastic net Cox models incorporating 15 early life factors, including perinatal conditions, childhood adversities, physical development, and social-environmental exposures. Cox models assessed associations of both individual factors and ELFS with depression. We conducted genome-wide association study (GWAS) to identify genetic variants associated with ELFS, Mendelian randomization to assess causality, and linear regression to examine associations with brain structures and blood markers. Structural equation modeling (SEM) explored biological pathways linking early life factors to depression.

Results: During 14.6-year median follow-up, 4168 participants developed depression. Each 1-point increase in ELFS was associated with 49% higher depression risk, with high ELFS showing 2.8-fold increased risk compared to low ELFS. GWAS identified 46 significant SNPs associated with ELFS, mapped to 17 genes including FOXP2, with enrichment in metabolic pathways. Mendelian randomization analysis supported the causal relationship between ELFS and depression. Higher ELFS was associated with smaller volumes particularly in emotion-regulation brain regions, and with altered inflammatory markers and lipid metabolism. SEM integrating multi-level evidence revealed biological pathways linking early life factors, brain structure, immunometabolic markers, and depression.

Conclusions: Early life factors collectively influence depression risk through an integrated score capturing differential factor contributions. Multiple biological pathways involving brain structure and immunometabolic markers were identified, providing insights into potential mechanisms linking early life factors to depression.