Novel polygenic risk score links depression-related cortical transcriptomic changes to brain morphology and depressive symptoms in men

2021 
ABSTRACT Our group developed a transcriptome-based polygenic risk score (T-PRS) that uses common genetic variants to capture ‘depression-like’ shifts in cortical gene expression. Here, we mapped T-PRS onto diagnosis and symptom severity in major depressive disorder (MDD) cases and controls from the Psychiatric Genomics Consortium (PGC). To evaluate potential mechanisms, we further mapped T-PRS onto discrete measures of brain morphology and broad depression risk in healthy young adults. Genetic, self-report, and/or neuroimaging data were available in 29,340 PGC participants (59% women; 12,923 MDD cases, 16,417 controls) and 482 participants in the Duke Neurogenetics Study (DNS: 53% women; aged 19.8±1.2 years). T-PRS was computed from SNP data using PrediXcan to impute cortical expression levels of MDD-related genes from a previous post-mortem transcriptome meta-analysis. Sex-specific regressions were used to test effects of T-PRS on depression diagnosis, symptom severity, and Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index in the PGC and DNS samples, respectively. T-PRS did not predict depression diagnosis (OR=1.007, 95%CI=[0.997-1.018]); however, it correlated with symptom severity in men (rho=0.175, p=7.957×10−4) in one large PGC cohort (N=762, 48% men). In DNS, T-PRS was associated with smaller amygdala volume in women (β=-0.186, t=-3.478, p=.001) and less prefrontal gyrification (max≤-2.970, p≤.006) in both sexes. In men, prefrontal gyrification mediated an indirect effect of T-PRS on broad depression risk (b=.005, p=.029), indexed using self-reported family history of depression. Depression-like shifts in cortical gene expression predict symptom severity in men and may contribute to disease vulnerability through their effect on cortical gyrification.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    53
    References
    0
    Citations
    NaN
    KQI
    []