Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts

Abstract

To reveal post-traumatic stress disorder (PTSD) genetic risk influences on tissue-specific gene expression, we use brain and non-brain transcriptomic imputation. We impute genetically regulated gene expression (GReX) in 29,539 PTSD cases and 166,145 controls from 70 ancestry-specific cohorts and identify 18 significant GReX-PTSD associations corresponding to specific tissue-gene pairs. The results suggest substantial genetic heterogeneity based on ancestry, cohort type (military versus civilian), and sex. Two study-wide significant PTSD associations are identified in European and military European cohorts; ZNF140 is predicted to be upregulated in whole blood, and SNRNP35 is predicted to be downregulated in dorsolateral prefrontal cortex, respectively. In peripheral leukocytes from 175 marines, the observed PTSD differential gene expression correlates with the predicted differences for these individuals, and deployment stress produces glucocorticoid-regulated expression changes that include downregulation of both ZNF140 and SNRNP35. SNRNP35 knockdown in cells validates its functional role in U12-intron splicing. Finally, exogenous glucocorticoids in mice downregulate prefrontal Snrnp35 expression.

Keywords: GWAS; PTSD; blood; civilian; glucocorticoid; military; prefrontal cortex; sex; splicing; transcriptomic imputation.

Figure 1.. Gene-by-Tissue Associations with PTSD in EA

(A–C) Manhattan plots showing the −log₁₀ of the p value of association of the genes-by-tissue in each chomosome with PTSD. In (A), one association reached study-wide significance (depicted by red discontinuous line) in our overall EA meta-analysis (23,195 cases/151,447 controls), and two genes reached within-tissue significance (depicted by purple discontinuous line). In (B), one gene reached study-wide significance in the military-only EA meta-analysis (6,004 cases/21,534 controls), and one reached within-tissue significance, while (C) two genes reached within-tissue significance in the civilian-only EA meta-analysis (16,959 cases/129,607 controls). Gene-tissue pairs with p 10–4 are color coded according to tissue type.

Figure 2.. PTSD GReX Differences Are Concordant with the Observed Blood PTSD Gene Expression Differences in U.S. Marines

(A and B) Correlation between PTSD (versus controls) log₂ of fold change (FC) of observed peripheral leukocyte gene expression (x axis) measured at pre- (A) and post-deployment (B) and whole-blood GReX (y axis). (C and D) Coefficients of correlation between log₂FCs of peripheral leukocyte gene expression and GReX across multiple tissues (x axis) and level of correspondent significance (−log₁₀ of p value in y axis) at pre- (C) and post-deployment (D); data points are color coded according to tissue type. (E and F) Gene expression changes in U.S. Marines following deployment. Correlation between log₂FCs based on in vivo DEX stimulation (x axis) (Arloth et al., 2015) and deployment stress (y axis) in PTSD subjects (E) and in control subjects (F). Red data points in (E) and (F) depict significant upregulation by deployment stress at FDR-significance threshold, while the blue data points depict significant downregulation by deployment stress at FDR-significance threshold. (G and H) The GSEAs of the gene set of downregulated genes by DEX (Arloth et al., 2015) in the pre- to post-deployment expression changes in PTSD subjects (G) and in control subjects (H). The y axis represents enrichment score (ES), and on the x axis are genes (vertical black lines) represented in the gene set. ES is the maximum deviation from zero as calculated for each gene going down the ranked list and represents the degree of over-representation of a gene set at the top or the bottom of the ranked gene list (boxplot) based on deployment-stress effects.

Figure 3.. SNRNP35 Validation Experiments

(A) SNRNP35 knockdown in human cells. In HEK cells, the five shRNAs (SH1, SH2, SH3, SH4, and SH5) significantly downregulated all the three protein-coding SNRNP35 RNA isoforms compared to scrambled (SC) RNA: for isoform 201 (hg38), p = 4.68e–5, 4.71e–5, 3.67e–4, 2.36e–4, and 1.29e–4, respectively; for isoform 202 (hg38), p = 1.61e–7, 1.2e–5, 1.11e–5, 1.23e–5, and 5.47e–6, respectively; for isoform p = 203 (hg38), p = 0.0106, 1.72e–4, 1.61e–3, 1.91e–3, and 4.03e–3), respectively. Data are represented as mean fold change (FC) ± standard error of mean (SEM). Asterisk indicates significant difference (p < 0.05) between shRNA and SC. (B) SNRNP35 knockdown affected U12 of CHD1L target RNA. The repeated-measures ANOVA with technical replicate as within-subject factor and knockdown status as the between-subjects factor revealed an effect of knockdown status on U12 splicing, F(1, 17) = 5.779; p = 0.0279. Data are represented as mean (standardized ratio of unspliced Ct values over spliced Ct values) ± SEM. Asterisk indicates significant difference (p < 0.05) between shRNA-SH5 and SC. (C) SNRNP35 downregulation by stress hormones. In mice, dexamethasone (DEX) intraperitoneal (i.p.) injection (10 mg/kg) downregulated prefrontal cortex (PFC) Snrnp35: Kruskal-Wallis H(2, 21) = 6.75, p = 0.0280; DEX versus HOME CAGE, adj. p = 0.0303. Data are represented as mean FC ± SEM. Pound sign indicates significant difference (p < 0.05) between DEX and HOME CAGE.