Discovering in vivo cytokine-eQTL interactions from a lupus clinical trial

Abstract

Background: Cytokines are critical to human disease and are attractive therapeutic targets given their widespread influence on gene regulation and transcription. Defining the downstream regulatory mechanisms influenced by cytokines is central to defining drug and disease mechanisms. One promising strategy is to use interactions between expression quantitative trait loci (eQTLs) and cytokine levels to define target genes and mechanisms.

Results: In a clinical trial for anti-IL-6 in patients with systemic lupus erythematosus, we measure interferon (IFN) status, anti-IL-6 drug exposure, and whole blood genome-wide gene expression at three time points. We show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point. We observe a statistically significant enrichment of in vivo eQTL interactions with IFN status and anti-IL-6 drug exposure and find many novel interactions that have not been previously described. Finally, we find transcription factor binding motifs interrupted by eQTL interaction SNPs, which point to key regulatory mediators of these environmental stimuli and therefore potential therapeutic targets for autoimmune diseases. In particular, genes with IFN interactions are enriched for ISRE binding site motifs, while those with anti-IL-6 interactions are enriched for IRF4 motifs.

Conclusions: This study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.

Keywords: Clinical trials; Cytokines; Interactions; eQTL.

Fig. 1

Identifying eQTLs in SLE patients. a Clinical trial structure and sampling strategy for the individuals used for eQTL analysis. The samples available are summarized in Table 1. b Number of eQTL genes identified using a linear model (left) and a linear mixed model (right). For the linear model, we used the first available time point for each individual (week 0 sample for n = 152, week 12 sample for n = 5). c Volcano plot of eQTL effects for the most significantly associated SNP for each gene (red color indicates p < 8.5 × 10^− 9). d Concordance of SLE eQTL effects (p < 8.5 × 10^− 9) with eQTLs observed in the BIOS cohort [11] of healthy individuals (FDR < 0.05). Each point represents the most significant SNP-gene pair for the SLE eQTL

Fig. 2

eQTL interactions with IFN status. a Designation of IFN status for each sample from the real-time PCR expression of 11 genes (first principal component). b IFN status interaction with the SLFN5 eQTL plotted with respect to rs12602407 genotype (left) and IFN status of the sample (right). c The ISRE motif enriched among eQTLs magnified in IFN high samples. Arrows indicate positions of the motif interrupted by interaction SNPs (or SNPs in strong LD). Red indicates these SNPs correspond to magnified eQTLs. d IFN status interaction with the GTF2A2 eQTL plotted with respect to rs2306355 genotype (left) and IFN status of the sample (right)

Fig. 3

eQTL interactions with drug exposure. a Drug exposure interaction with the CLEC18A eQTL plotted with respect to rs3192882 genotype (left) and drug exposure (right). b The IRF4 motif enriched among eQTLs magnified following drug treatment. Arrows indicate positions of the motif interrupted by interaction SNPs (or SNPs in strong LD). Red and blue indicate SNPs corresponding to magnified and dampened eQTLs respectively. c Concordance of free IL-6 protein interaction effects with drug exposure interaction effects (gray indicates consistent direction)