Epigenetics in multiple sclerosis susceptibility: difference in transgenerational risk localizes to the major histocompatibility complex
Bibliographic record
Abstract
Multiple sclerosis (MS) susceptibility demonstrates a complex pattern of inheritance. Haplotypes containing HLA-DRB1*1501 carry most of the genetic risk. Epidemiological evidence implicating epigenetic factors includes complex distortion of disease transmission seen in aunt/uncle-niece/nephew (AUNN) pairs. Unexpectedly, in AUNN families we found that allele frequencies for HLA-DRB1*1501 were different between the first and second generations affected. Affected aunts had significantly lower HLA-DRB1*15 frequency compared with their affected nieces (chi(2) = 9.90, P = 0.0016), whereas HLA-DRB1*15 frequency in affected males remains unaltered across the two generations (chi(2) = 0.23, P = 0.63). We compared transmissions for the HLA-DRB1*15 allele using a family-based transmission disequilibrium test approach in 1690 individuals from 350 affected sibling pair (ASP) families and 960 individuals from 187 AUNN families. Transmissions differed between the ASP and the AUNN families (chi(2) = 6.92; P = 0.0085). The risk carried by HLA-DRB1*15 was increased in families with affected second-degree relatives (AUNN: OR = 4.07) when compared with those consisting only first-degree relatives (ASP: OR = 2.17), establishing heterogeneity of risk among HLA-DRB1*15 haplotypes based on whether collateral parental relatives are affected. These observations strongly implicate gene-environment interactions in susceptibility and more specifically, that epigenetic modifications differentiate among human leukocyte antigen class II risk haplotypes and are involved in the determination of the gender bias in MS. These data strongly suggest that the female-specific increasing risk of MS is mediated through these alleles or adjacent variation. The comparison of transmission of the same allele in vertically affected pedigrees (AUNN) to collinear sibling pairs (ASP) may provide a useful screen for putative epigenetic marks.
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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 | 0.000 | 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) | 0.002 | 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".