Mechanism: A new model combines HLA-DRB1 genetics, smoking exposure, and early CRP trajectory to predict methotrexate non-response in rheumatoid arthritis. Readout: Readout: This model significantly improves prediction accuracy (AUROC +0.15) and calibration compared to traditional baseline markers.
Hypothesis
A homomorphically encrypted, time-updated pharmacogenomic model that combines HLA-DRB1 shared-epitope status, smoking exposure, and early CRP trajectory will predict methotrexate non-response in rheumatoid arthritis better than baseline seropositivity alone, while preserving patient-level genomic privacy across decentralized cohorts.
Rationale
Methotrexate response in RA is heterogeneous. Shared-epitope biology and smoking both influence disease severity and treatment trajectory, but most prediction efforts rely on static baseline variables and underuse privacy-preserving multi-center validation. A federated or FHE-enabled design could validate response models without releasing raw genotype-level data.
Testable prediction
Across decentralized RA registries, a model with:
- HLA-DRB1 shared-epitope carrier status,
- smoking exposure,
- baseline disease activity, and
- 4- to 8-week CRP slope, will yield better calibration and higher AUROC for 3- to 6-month inadequate methotrexate response than a model based only on RF/anti-CCP seropositivity and baseline DAS28.
Falsification strategy
The hypothesis fails if privacy-preserving training materially degrades calibration or if shared-epitope plus smoking adds no incremental predictive value beyond routine baseline clinical markers.
Suggested study design
- Decentralized observational RA cohorts with standardized outcome definition for inadequate MTX response
- Local computation of encrypted summary statistics or encrypted gradient updates
- Internal-external cross-validation across sites
- Prespecified calibration slope/intercept and decision-curve analysis
Limitations
Shared-epitope testing is not universal, smoking exposure can be misclassified, and FHE workflows may increase computational cost. This is a validation hypothesis, not a claim of current clinical readiness.
References
- Viatte S, Massey J, Bowes J, et al. Replication of associations of genetic markers with radiographic severity in rheumatoid arthritis. Arthritis Rheumatol. 2013;65(9):2364-2368. DOI: 10.1002/art.38064
- Padyukov L, Silva C, Stolt P, Alfredsson L, Klareskog L. A gene-environment interaction between smoking and shared epitope genes in HLA-DR provides a high risk of seropositive rheumatoid arthritis. Arthritis Rheum. 2004;50(10):3085-3092. DOI: 10.1002/art.20553
- Fraenkel L, Bathon JM, England BR, et al. 2021 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis. Arthritis Rheumatol. 2021;73(7):1108-1123. DOI: 10.1002/art.41752
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