Study summary
In our recently completed multiple sclerosis (MS) genome-wide association study (GWAS), we identified 57 non-MHC SNPs that are independently associated with susceptibility to MS. Collectively, these variants implicate 532 nearby genes. To further investigate these associations, we propose to examine allelic expression imbalance (AEI) in as many of these genes as possible by studying coding SNPs located within the implicated genes that are in linkage disequilibrium (LD) with the corresponding MS-associated variant.
Using data from Northern European populations within the 1000 Genomes Project, we have identified 138 such coding variants. As additional Immunochip data become available, the number of variants analysed may increase.
Genes with immune-related functions are markedly overrepresented within genomic regions containing established MS-associated SNPs. We hypothesise that many of these variants influence disease susceptibility by modulating the expression of nearby genes. To investigate this, we propose a systematic analysis of all identifiable coding SNPs within implicated genes that are highly correlated with MS-associated variants, with the aim of identifying cis-acting effects on gene expression.
As gene expression is known to be highly cell- and tissue-specific, AEI will be examined in CD4+ and CD8+ T lymphocytes, both of which play fundamental roles in the pathogenesis of MS. We plan to recruit 200 patients with multiple sclerosis through the Addenbrooke’s MS Clinic and 200 healthy, unrelated control participants matched for age, sex, and ethnicity.
Peripheral blood mononuclear cells (PBMCs) will be isolated from collected blood samples, and CD4+ and CD8+ T cells will subsequently be purified using magnetic bead separation. Each participant will be genotyped for the selected coding SNPs. For coding SNPs at which an individual is heterozygous, CD4+-derived cDNA, CD8+-derived cDNA, and genomic DNA (gDNA) samples will be amplified and sequenced using the Illumina MiSeq platform. Allele-specific read counts will be used to quantify AEI, with the corresponding gDNA sample serving as an internal control.
A total of 50 mL of blood will be collected from each control participant to ensure sufficient RNA yields for these analyses.
Brief Summary of publication from the study:
This study investigated how genetic variants associated with multiple sclerosis (MS) affect gene expression in immune cells. Researchers examined allele-specific expression (ASE) in CD4+ and CD8+ T cells from 106 MS patients and 105 healthy controls, focusing on coding variants linked to known MS risk loci.
Key findings:
- 200 coding variants across 112 genes were successfully analysed.
- 56 variants in 43 genes showed significant evidence of allele-specific expression, indicating that many MS risk variants influence how nearby genes are expressed.
- The strongest and most novel finding involved the gene LIME1, where the MS-associated variant rs2256814 altered the balance of different LIME1 transcripts rather than simply increasing or decreasing overall gene expression. This result was replicated in an independent cohort.
- The study also confirmed expression effects for several previously implicated MS genes, including TNFRSF1A, IL7R, CD40, and SP140.
- No major differences in ASE were observed between MS patients and controls, suggesting that these regulatory effects are largely determined by genotype rather than disease status.
Main Conclusion
Many MS susceptibility variants appear to influence disease risk by altering the expression and splicing of specific gene transcripts, rather than changing total gene expression levels. The findings highlight transcript-specific regulation, particularly in LIME1, as an important mechanism underlying genetic susceptibility to MS.