Differential methylation at MHC in CD4+ T cells is associated with multiple sclerosis independently of HLA-DRB1
Bibliographic record
Abstract
Although many genetic variants have been associated with multiple sclerosis (MS) risk, they do not explain all the disease risk and there remains uncertainty as to how these variants contribute to disease. DNA methylation is an epigenetic mechanism that can influence gene expression and has the potential to mediate the effects of environmental factors on MS. In a previous study, we found a differentially methylation region (DMR) at MHC HLA-DRB1 that was associated within relapsing-remitting MS (RRMS) patients in CD4 + T cells. This study aimed to confirm this earlier finding in an independent RRMS cohort of treatment-naïve female patients. Total genomic DNA was extracted from CD4 + T cells of 28 female RRMS and 22 age-matched healthy controls subjects. DNA was bisulfite-converted and hybridised to Illumina 450K arrays. Beta values for all CpGs were analysed using the DMPFinder function in the MINFI program, and a follow-up prioritisation process was applied to identify the most robust MS-associated DMRs. This study confirmed our previous findings of a hypomethylated DMR at HLA-DRB1 and a hypermethylated DMR at HLA-DRB5 in this RRMS patient cohort. In addition, we identified a large independent DMR at MHC, whereby 11 CpGs in RNF39 were hypermethylated in MS cases compared to controls (max. ∆beta = 0.19, P = 2.1 × 10 −4 ). We did not find evidence that SNP genotype was influencing the DMR in this cohort. A smaller MHC DMR was also identified at HCG4B , and two non-MHC DMRs at PM20D1 on chr1 and ERICH1 on chr8 were also identified. The findings from this study confirm our previous results of a DMR at HLA-DRB1 and also suggest hypermethylation in an independent MHC locus, RNF39 , is associated with MS . Taken together, our results highlight the importance of epigenetic factors at the MHC locus in MS independent of treatment, age and sex. Prospective studies are now required to discern whether methylation at MHC is involved in influencing risk of disease onset or whether the disease itself has altered the methylation profile.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".