HLA-A03:01 as predictive genetic biomarker for glatiramer acetate treatment response in multiple sclerosis: a retrospective cohort analysis
Bibliographic record
Abstract
BACKGROUND: Glatiramer acetate (GA) is a well-tolerated treatment for multiple sclerosis (MS) and comparable in its efficacy to high-dose interferon beta (IFN). As a lack of validated treatment response biomarkers for MS hampers progress in personalised treatment, the study goal was to search for biomarkers of a successful treatment response utilising the known observation of T-cell expansions after GA treatment. METHODS: T-cell receptor beta chain (TRB) sequencing was performed in 3021 patients with MS: a discovery cohort of 1627 patients with MS, 204 of whom had previously been treated with GA, and then validated in 1394 patients with MS, 424 of whom had previously been treated with GA. Clinical data from 1987 patients with MS treated with GA or IFN and available HLA information from the NationMS, ACP, EPIC, BIONAT, and CombiRx trial cohorts were used for a subsequent analysis. FINDINGS: Common GA-associated TRB expansions were exclusively detected in HLA-A03:01 or in HLA-DRB115:01 backgrounds, within CD8+ effector- or CD4+ central-memory T cells. Both sets of common sequences clonally expanded after GA treatment in a first validation cohort and predicted GA exposure in two further validation cohorts. To evaluate whether restriction of public TRBs to only two HLA alleles is also associated with GA's clinical efficacy, we analysed five cohorts of patients with MS for a potential benefit of the two HLAs concerning the GA response compared to IFN. We consistently found positive interactions with HLA-A03:01. This included a relative reduction in relapse risk compared to IFN in HLA-A03:01 carriers of 33% (CombiRx: GA + IFN arm: HR 0.67 [95% CI: 0.47-0.96], p = 0.0269) and 34% (CombiRx: GA arm: HR 0.66 [95% CI: 0.45-0.98], p = 0.0377), and in risk to first relapse of 63% (NationMS: HR 0.37 [95% CI: 0.16-0.88], p = 0.0246), but no positive association with DRB115:01. INTERPRETATION: HLA-A03:01 carrying patients with MS specifically benefit from GA treatment and GA significantly outperforms IFN in these patients. Therefore, determining HLA-A03:01 status before choosing a platform treatment for MS, would allow for a personalised treatment decision between GA and IFN. FUNDING: German Research Foundation, National Institutes of Health, National Multiple Sclerosis Society, Valhalla Foundation, Westridge Foundation, Mayer Foundation, German Federal Ministry of Education and Research.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".