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Published on: July 12, 2024
Integrated Early-Life Factors and Depression: A Multilevel Investigation of Brain Structural, Immunometabolic, and
Guangrui Yang1, Hao Huang1, Jingxuan Wang1
1Department of Epidemiology and Biostatistics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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 were used to assess associations of both individual factors and the ELFS with depression. We conducted a genome-wide association study (GWAS) to identify genetic variants, Mendelian randomization to assess causality, and linear regression to examine associations with brain structures and blood markers. Structural equation modeling (SEM) was used to explore biological pathways linking early-life factors to depression.
Results:
During the follow-up period (median = 14.6 years), 4168 participants developed depression. Each 1-point increase in the ELFS was associated with a 49% higher depression risk. Individuals with a high ELFS showed a 2.8-fold higher risk than individuals with a low ELFS. GWAS identified 46 significant single nucleotide polymorphisms associated with the ELFS, mapped to 17 genes including FOXP2, with enrichment in metabolic pathways. Mendelian randomization analysis supported the causal relationship between the ELFS and depression. A higher ELFS was associated with smaller volumes particularly in brain regions linked to emotion regulation and with altered inflammation and lipid metabolism. SEM integrating multilevel evidence revealed biological pathways linking early-life factors, brain structure, immunometabolic markers, and depression.
Conclusions:
Early-life factors collectively influenced 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.
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