SNP-to-gene linking strategies reveal contributions of enhancer-related and candidate master-regulator genes to autoimmune disease

Abstract

We assess contributions to autoimmune disease of genes whose regulation is driven by enhancer regions (enhancer-related) and genes that regulate other genes in trans (candidate master-regulator). We link these genes to SNPs using several SNP-to-gene (S2G) strategies and apply heritability analyses to draw three conclusions about 11 autoimmune/blood-related diseases/traits. First, several characterizations of enhancer-related genes using functional genomics data are informative for autoimmune disease heritability after conditioning on a broad set of regulatory annotations. Second, candidate master-regulator genes defined using trans-eQTL in blood are also conditionally informative for autoimmune disease heritability. Third, integrating enhancer-related and master-regulator gene sets with protein-protein interaction (PPI) network information magnified their disease signal. The resulting PPI-enhancer gene score produced >2-fold stronger heritability signal and >2-fold stronger enrichment for drug targets, compared with the recently proposed enhancer domain score. In each case, functionally informed S2G strategies produced 4.1- to 13-fold stronger disease signals than conventional window-based strategies.

Graphical abstract

Figure 1

Illustration of S2G strategies and gene scores (A) SNP annotations defined by integration of genes in gene set with proximal (close to gene body) and distal S2G strategies. (B) Examples of approaches used to define enhancer-related genes. (C) A Trans-master gene regulates multiple distal genes via a cis-eQTL that is a trans-eQTL of the distal genes. (D) PPI-enhancer genes have high connectivity to enhancer-related genes in a PPI network.

Figure 2

Disease informativeness of S2G annotations We evaluated ten S2G annotations defined from the corresponding S2G strategies by SNPs linked to the set of all genes. (A) Heritability enrichment (log scale), conditional on the baseline-LD model. Horizontal line denotes no enrichment. (B) Standardized effect size (τ^∗), conditional on either the baseline-LD model (marginal analyses: left column, white) or the baseline-LD+ model, which includes all ten S2G annotations (right column, dark shading). Results are meta-analyzed across 11 blood-related traits. ∗∗p < 0.05/10. Error bars denote 95% confidence intervals. Numerical results are reported in Tables S2 and S4.

Figure 3

Disease informativeness of enhancer-related and PPI-enhancer annotations We evaluated 80 annotations constructed by combining seven enhancer-related + 1 PPI-enhancer gene scores with ten S2G strategies. (A) Standardized effect size (τ^∗), conditional on the baseline-LD+ model. (B) Comparison of meta-analyzed standardized effect size (τ^∗) across six autoimmune diseases versus five blood cell traits. (C) Enrichment of enhancer-related and PPI-enhancer genes in five “gold-standard” disease-related gene sets. (D) Standardized effect size (τ^∗), conditional on the baseline-LD+ model plus seven jointly significant enhancer-related + PPI-enhancer annotations. In (A) and (D), results are meta-analyzed across 11 blood-related traits. In (A) and (C), double asterisks denote Bonferroni-significant p values (∗∗p < 0.05/110 in A and ∗∗p < 0.05/55 in C) and single asterisk (∗) denotes FDR < 0.05. In (A), the black box in each row denotes the S2G strategy with highest τ^∗. In (B), circled dots denote annotations with significant (FDR < 5%) difference in effect size between the two meta-analyses, the solid line denotes y = x, and the dashed line denotes the regression slope. We report the slope of the regression and the Pearson correlation for enhancer-related and PPI-enhancer annotations (slope = 1.3, r = 0.57 for enhancer-related annotations only). Error bars in (D) denote 95% confidence intervals. Numerical results are reported in Tables S6, S8, S10, S11, S23, and S26.

Figure 4

Disease informativeness of master-regulator and PPI-master annotations We evaluated 30 annotations constructed by combining two master-regulator + 1 PPI-master gene scores with ten S2G strategies. (A) Standardized effect size (τ^∗), conditional on the 113 baseline-LD+ cis model annotations. (B) Comparison of meta-analyzed standardized effect size (τ^∗) across six autoimmune diseases versus five blood cell traits. (C) Enrichment of master-regulator and PPI-master genes in five “gold-standard” disease-related gene sets. (D) Standardized effect size (τ^∗), conditional on the baseline-LD+ cis model plus five jointly significant master-regulator + PPI-master annotations. In (A) and (D), results are meta-analyzed across 11 blood-related traits. In (A) and (C), double asterisks denote Bonferroni-significant p values (∗∗p < 0.05/110 in A and ∗∗p < 0.05/55 in C), and single asterisk (∗) denotes FDR < 0.05. In (A), the black box in each row denotes the S2G strategy with highest τ^∗. In (B), circled dots denote annotations with significant (FDR < 5%) difference in effect size between the two meta-analyses, the solid line denotes y = x, and the dashed line denotes the regression slope. We report the slope of the regression and the Pearson correlation for master-regulator and PPI-master annotations (slope = 0.57, r = 0.56 for master-regulator annotations only). Error bars in (D) denote 95% confidence intervals. Numerical results are reported in Tables S6, S29, S38, S39, S47, and S51.

Figure 5

Combined joint model (A) Heritability enrichment (log scale) of the eight jointly significant enhancer-related, master-regulator, PPI-enhancer-related, and PPI-master-regulator annotations, conditional on the baseline-LD+ cis model. Horizontal line denotes no enrichment. (B) Standardized effect size (τ^∗) conditional on the baseline-LD+ cis model plus the eight jointly significant annotations. Significance is corrected for multiple testing by Bonferroni correction (p < 0.05/110). Errors bars denote 95% confidence intervals. Numerical results are reported in Table S52.