Sensitive period-regulating genetic pathways and exposure to adversity shape risk for depression

2021 
Abstract Animal and human studies have documented the existence of developmental windows (or sensitive periods) when experience can have lasting effects in shaping brain structure or function, behavior, and disease risk. Sensitive periods for depression likely arise through a complex interplay of genes and experience, though this possibility has not been explored. We examined the effect of sensitive period-regulating genetic pathways identified in preclinical animal studies, alone and in interaction with socioeconomic disadvantage, a common childhood adversity, on depression risk. Using a translational approach, we: (1) performed gene-set association analyses using summary data from a genome-wide association study of depression (n=807,553) to assess the effects of three gene sets (60 genes) shown in animal studies to regulate sensitive periods; (2) evaluated the developmental expression patterns of these sensitive period-regulating genes using data from BrainSpan (n=31), a transcriptional atlas of postmortem brain samples; and (3) tested gene-by-development interplay by analyzing the combined effect of common variants in sensitive period genes and timing of exposure to socioeconomic disadvantage within a population-based birth cohort (n=6254). The gene set regulating sensitive period opening associated with increased depression risk. Notably, six of the 15 genes in this set showed developmentally regulated gene-level expression. A genome-wide polygenic risk score-by-environment analysis showed socioeconomic disadvantage during ages 1-5 years were independently associated with depression risk, but no gene-by-development interactions were found. Genes involved in regulating sensitive periods may be implicated in depression vulnerability and differentially expressed across the life course, though larger studies are needed to identify developmental interplays.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    84
    References
    1
    Citations
    NaN
    KQI
    []