Maternal – offspring HLA‐DRB1 compatibility in multiple sclerosis
Bibliographic record
Abstract
Major histocompatibility complex (MHC) compatibility has been reported to facilitate the long-term tolerance of fetal or maternally derived stem cells exchanged during pregnancy. Furthermore, such compatibility has been suggested to play a role in fetal viability. An increase in maternal - fetal human leukocyte antigen (HLA) compatibility for class II DR alleles has previously been observed in the autoimmune disease scleroderma. Here, we examined the hypothesis that increased maternal - fetal MHC class II DR compatibility was associated with multiple sclerosis (MS) risk. HLA-DRB1 typing was performed in 2170 affected individuals and 2894 unaffected relatives from 1006 families with MS in at least two members. We found no evidence for increased HLA compatibility between affected individuals and their mothers, compared with unaffected individuals and their mothers, nor compared with affected individuals and their fathers. We also observed no excess of homozygosity of mothers compared with fathers of individuals with MS. In families in which the father shared exactly one allele with the mother, we found no excess in transmission of this allele to affected or unaffected offspring. These findings do not support a role for an excess maternal - fetal HLA-DRB1 compatibility in MS susceptibility.
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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 | 0.001 | 0.002 |
| 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".