Modification of Multiple Sclerosis Phenotypes by African Ancestry at HLA
Bibliographic record
Abstract
BACKGROUND: In those with multiple sclerosis (MS), African American individuals have a more severe disease course, an older age at onset, and more often have clinical manifestations restricted to the optic nerves and spinal cord (opticospinal MS) than white persons. OBJECTIVE: To determine whether genetic variation influences clinical MS patterns. DESIGN: Retrospective multicenter cohort study. PARTICIPANTS: Six hundred seventy-three African American and 717 white patients with MS. MAIN OUTCOME MEASURES: Patients with MS were genotyped for HLA-DRB1 and HLA-DQB1 alleles. The proportion of European ancestry at HLA was estimated by genotyping single-nucleotide polymorphisms with known significant frequency differences in West African and European populations. These genotypes were correlated with the opticospinal disease phenotype, disability measures, and age at onset. RESULTS: Subjects with DRB1*15 alleles were twice as likely to have typical MS rather than opticospinal MS (P = .001). Of the subjects with opticospinal MS or a history of recurrent transverse myelitis who were seropositive for anti-aquaporin 4 antibodies (approximately 5%), none carried DRB1*15 alleles (P = .008). Independently of DRB1*15, African ancestry at HLA correlated with disability as measured by the Multiple Sclerosis Severity Score (P < .001) and risk of cane dependency (hazard ratio, 1.36; P < .001); DRB1*15 alleles were associated with a 2.1-year earlier age at onset (P < .001). CONCLUSIONS: These data indicate that the role of HLA in MS is not limited to disease susceptibility but that genes embedded in this locus also influence clinical outcomes.
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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 | 0.001 | 0.001 |
| 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".