Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder

Abstract

Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of depression compared to unaffected individuals. Meta-analysis of genome-wide interaction studies (GWIS) in UK Biobank (N = 23,092) and Generation Scotland: Scottish Family Health Study (N = 7,155) identified no genome-wide significance SNP interactions. However, gene-based tests identified a genome-wide significant gene, ZNF366, a negative regulator of glucocorticoid receptor function implicated in alcohol dependence (p = 1.48x10-7; Bonferroni-corrected significance threshold p < 2.79x10-6). Using summary statistics from the stress-sensitivity term of the GWIS, SNP heritability for stress-sensitivity was estimated at 5.0%. In models fitting polygenic risk scores of both MDD and neuroticism derived from independent GWAS, we show that polygenic risk scores derived from the UK Biobank stress-sensitivity GWIS significantly improved the prediction of MDD in Generation Scotland. This study may improve interpretation of larger genome-wide association studies of MDD and other stress-related illnesses, and the understanding of the etiological mechanisms underpinning stress-sensitivity.

Fig 1. Manhattan plots showing stress-sensitivity associations.

Manhattan plots of the GWIS from (A) UKB, (B) GS:SFHS and (C) sample size weighted meta-analysis of UKB and GS:SFHS. The x-axis is chromosomal position and y-axis is the p value (-log10 p value) of association with stress-sensitivity effect. Suggestive genome-wide significance threshold (p = 1x10^-5) is shown by solid line at y = 5. Genes or closest gene up- and down-stream from SNP position (/) are annotated. “-“: No gene within 100kb of the SNP.

Fig 2. Miami plots showing comparison between association profile between stress-sensitivity GWIS and MDD GWAS.

Miami plots from meta-analysis filter at p = 1x10^-3: (A) filtering for stress-sensitivity p values (•), (B) filtering for MDD p values (×). The x-axis is chromosomal position and y-axis is the p value (-log10 p value) of association with stress-sensitivity (up; red dots) and MDD p value (down; blue crosses). Dot line: genome-wide suggestive threshold (p = 1x10^-5) at the filtered effect; dashed lines: p = 0.01 and 0.05 at unfiltered effect.

Fig 3. MDD is best predicted using multiple PRS.

MDD risk explained (R² coefficient (%); top bar values) on the liability scale by each PRS in GS:SFHS; weighted by GWAS main additive and GWIS stress-sensitivity effects independently and combined. (A) Using summary statistics from UKB as discovery sample. There is an increment on MDD risk prediction from adding PRS_SS to PRS_D model of 53.1% and 24.6% when combining PRS_SS with both MDD and neuroticism PRS. (B) Replication of fitting PRS_D and PRS_N using summary statistics from worldwide consortiums (i.e. PGC &GPC). Significance codes: p values *** < 0.001 < ** < 0.01 < * < 0.05 < • < 0.1; derived from likelihood ratio tests. SS stands for stress-sensitivity.