Low-usage splice junctions underpin immune-mediated disease risk

Abstract

The majority of immune-mediated disease (IMD) risk loci are located in non-coding regions of the genome, making it difficult to decipher their functional effects. To assess the extent to which alternative splicing contributes to IMD risk, we mapped genetic variants associated with alternative splicing (splicing quantitative trait loci or sQTL) in macrophages exposed to 24 cellular conditions. We found that genes involved in innate immune response pathways undergo extensive differential splicing in response to stimulation and detected significant sQTL effects for over 5,734 genes across all conditions. We colocalised sQTL signals for over 700 genes with IMD-associated risk loci from 21 IMDs with high confidence (PP4 ≥ 0.75). Approximately half of the colocalisations implicate lowly-used splice junctions (mean usage ratio < 0.1). Finally, we demonstrate how an inflammatory bowel disease (IBD) risk allele increases the usage of a lowly-used isoform of PTPN2, a negative regulator of inflammation. Together, our findings highlight the role alternative splicing plays in IMD risk, and suggest that lowly-used splicing events significantly contribute to complex disease risk.

Global impact of aberrant splicing on human gene expression levels

“…Notably, we find that these sQTLs largely affect low-usage splice junctions, such that 57% of these splice junctions are spliced-in at PSI<5% ( Figure 4C ). This observation is consistent with that of a recent study 64 from the HipSci consortium, and naturally poses questions as to how such low-usage isoforms might impact traits. We found that most of these low-usage sQTLs are u-sQTLs that alter the balance of unproductive and productive isoforms, consistent with AS-NMD mechanisms mediating these loci.…”

“…Across all complex traits, approximately 70% of GWAS loci could not be colocalized with any molecular QTL ( Fig. 4B ), in line with previous studies with similar sample sizes 56,57 . Approximately 18% of GWAS loci colocalize with either an hQTL, eQTL, or some combination of molecular QTLs ( Fig.…”

“…To better resolve the mechanisms at these GWAS loci, we used multi-trait colocalization to identify GWAS signals that colocalize with hQTLs, eQTLs, sQTLs, or various combinations of QTLs. Across all complex traits, approximately 70% of GWAS loci could not be colocalized with any molecular QTL ( Figure 4B ), in line with previous studies with similar sample sizes 64,65 . Approximately 18% of GWAS loci colocalize with either an hQTL, eQTL, or some combination of molecular QTLs ( Figure 4B ).…”

“…For example, GWAS variants that affect ALS risk and COVID-19-susceptibility increase the inclusion of a cryptic exon in UNC13A and OAS1, respectively, leading to lower protein expression [51][52][53] . More generally, recent studies [54][55][56][57] have found that approximately half of GWAS loci that share a causal variant (colocalize) with splicing quantitative trait loci (sQTLs) also colocalize with an eQTL, suggesting that the impact of AS is often mediated by gene expression levels rather than alternate protein isoforms. However, the overlap of sQTLs, eQTLs, and GWAS does not immediately imply AS-NMD mechanisms because alternative promoters, isoform-specific mRNA decay, and other molecular processes can similarly affect both expression and splicing measurements [44][45][46][47] .…”