2025/04/06 by Anton Öberg Sysojev, Bénédicte Delcoigne, Thomas Frisell +8 · 1 voice
Medicine · Biochemistry, Genetics and Molecular Biology · #Rheumatoid Arthritis Research and Therapies #Genetic Associations and Epidemiology #Bioinformatics and Genomic Networks
paper · pdf · doi:10.1111/joim.20087
openalex publication_date 2025/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
BACKGROUND: Methotrexate (MTX) is the mainstay initial treatment of rheumatoid arthritis (RA), but individual response varies and remains difficult to predict. The role of genetics remains unclear, but studies suggest its importance. METHODS: Incident RA patients starting MTX-monotherapy were identified through a large-scale Swedish register linkage. Demographic, clinical, medical, and drug history features were combined with fully imputed genotype data and used to train and evaluate multiple learning models to predict key MTX treatment outcomes. RESULTS: Among 2432 patients, we consistently observed an estimated area under the curve (AUC) of ∼0.62, outperforming models trained on sex and age. The best performance was observed for EULAR primary response (AUC = 0.67), whereas models struggled the most with predicting discontinuation. Genetics provided negligible improvements to prediction quality. CONCLUSIONS: Despite an extensive study population with broad multi-modal data, predicting MTX treatment outcomes remains a challenge. Common genetic variants added minimal predictive power over clinical features.