Regulation of Gene Expression in Autoimmune Disease Loci and the Genetic Basis of Proliferation in CD4+ Effector Memory T Cells

Abstract

Genome-wide association studies (GWAS) and subsequent dense-genotyping of associated loci identified over a hundred single-nucleotide polymorphism (SNP) variants associated with the risk of rheumatoid arthritis (RA), type 1 diabetes (T1D), and celiac disease (CeD). Immunological and genetic studies suggest a role for CD4-positive effector memory T (CD+ TEM) cells in the pathogenesis of these diseases. To elucidate mechanisms of autoimmune disease alleles, we investigated molecular phenotypes in CD4+ effector memory T cells potentially affected by these variants. In a cohort of genotyped healthy individuals, we isolated high purity CD4+ TEM cells from peripheral blood, then assayed relative abundance, proliferation upon T cell receptor (TCR) stimulation, and the transcription of 215 genes within disease loci before and after stimulation. We identified 46 genes regulated by cis-acting expression quantitative trait loci (eQTL), the majority of which we detected in stimulated cells. Eleven of the 46 genes with eQTLs were previously undetected in peripheral blood mononuclear cells. Of 96 risk alleles of RA, T1D, and/or CeD in densely genotyped loci, eleven overlapped cis-eQTLs, of which five alleles completely explained the respective signals. A non-coding variant, rs389862A, increased proliferative response (p = 4.75×10−8). In addition, baseline expression of seventeen genes in resting cells reliably predicted proliferative response after TCR stimulation. Strikingly, however, there was no evidence that risk alleles modulated CD4+ TEM abundance or proliferation. Our study underscores the power of examining molecular phenotypes in relevant cells and conditions for understanding pathogenic mechanisms of disease variants.

Genetic basis of autoimmunity

“…This is consistent with the finding of pervasive response eQTL (reQTL), where expression phenotypes are unmasked in response to selective stimulation conditions (104). Indeed, several recent studies have discovered sets of human reQTL variants that shape transcriptome responses to immune cell stimulation and polarization, demonstrating various degrees of overlap with the loci implicated by GWAS studies of immune-mediated diseases (75,(105)(106)(107). eQTL in CD4 + T cells overlap with disease-associated SNPs for RA and MS, whereas SNPs associated with Alzheimer's and Parkinson's diseases preferentially overlap with eQTL in monocytes, underscoring the cell type-specific dysregulation of gene expression that likely contributes to disease phenotype (108).…”

Disentangling effects of colocalizing genomic annotations to functionally prioritize non-coding variants within complex trait loci

“…1,47,48 We observed no enrichment (p ¼ 0.17) when we used the peak bodies of H3K4me3 in either CD4 þ memory T cells (p ¼ 0.17) or in an aggregate of all 118 cell types from our datasets (p ¼ 0.14; Figure 5A). Because the median width of H3K4me3 peak bodies varied widely (110-86,490 bp), we examined the summit regions (5100 bp from the H3K4me3 summits), where active gene-regulatory elements are most likely located.…”

Autoimmune diseases — connecting risk alleles with molecular traits of the immune system

“…eQTLs can be cell-type-specific (that is, active in one cell type but not in another), and their effect sizes may vary across cell types 122–127 . Reports have estimated that 11–30% of autoimmune risk loci involve cis eQTLs in blood-derived cells or CD4 + T cells 38,51,118,128 , and that trait-associated cis eQTLs have a higher degree of tissue specificity than expected 118 . In trans eQTLs, which can involve an intermediary gene, the variant is distant from the gene (typically >5 Mb away).…”

“…Early studies investigating the effects of variants on gene expression examined (B cell-derived) lymphoblastoid cell lines 131,132 , but recent studies have emphasized primary cells, such as monocytes, B cells, T cells, dendritic cells and neutrophils 117,118,122,125,128,133–136 to capture regulatory variation active in cell types that are highly relevant for autoimmunity. A critical issue is that many cell types of interest (for example, T cells) constitute a relatively small component of peripheral blood.…”