Epigenetic differences at the HTR2A locus in progressive multiple sclerosis patients
Bibliographic record
Abstract
Abstract The pathology of progressive multiple sclerosis (MS) is poorly understood. We have previously assessed DNA methylation in the CD4+ T cells of relapsing–remitting (RR) MS patients compared to healthy controls and identified differentially methylated regions (DMRs) in HLA-DRB1 and RNF39. This study aimed to investigate the DNA methylation profiles of the CD4+ T cells of progressive MS patients. DNA methylation was measured in two separate case/control cohorts using the Illumina 450K/EPIC arrays and data was analysed with the Chip Analysis Methylation Pipeline (ChAMP). Single nucleotide polymorphisms (SNPs) were assessed using the Illumina Human OmniExpress24 arrays and analysed using PLINK. Expression was assessed using the Illumina HT12 array and analysed in R using a combination of Limma and Illuminaio. We identified three DMRs at HTR2A, SLC17A9 and HDAC4 that were consistent across both cohorts. The DMR at HTR2A is located within the bounds of a haplotype block; however, the DMR remained significant after accounting for SNPs in the region. No expression changes were detected in any DMRs. HTR2A is differentially methylated in progressive MS independent of genotype. This differential methylation is not evident in RRMS, making it a potential biomarker of progressive disease.
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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".