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Updated: Nov 5, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Factors affecting the risk of relapsing-onset and progressive-onset multiple sclerosis
Anna Karin Hedström1, Jan Hillert2, Tomas Olsson2
1Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden anna.hedstrom@ki.se.
Objective:
It has been debated whether the different clinical disease courses in multiple sclerosis (MS) are the consequence of different pathogenic mechanisms, with distinct risk factors, or if all MS clinical phenotypes are variations of similar underlying disease mechanisms. We aimed to study environmental risk factors and their interactions with human leucocyte antigen DRB1*15:01 with regards to relapsing-onset and progressive-onset MS.
Methods:
We used two Swedish population-based case-control studies, including 7520 relapsing-onset cases, 540 progressive-onset cases and 11 386 controls matched by age, sex and residential area. Logistic regression was used to estimate ORs with 95% CIs for associations between the different MS phenotypes and a number of environmental and lifestyle factors. Interaction between the DRB1*15:01 allele and environmental risk factors was evaluated on the additive scale.
Results:
All environmental and lifestyle factors associated with risk of developing MS apply to both relapsing-onset and progressive-onset disease. Smoking, obesity and Epstein-Barr virus nuclear antigen-1 (EBNA-1) antibody levels were associated with increased risk of both MS phenotypes, whereas snuff use, alcohol consumption and sun exposure were associated with reduced risk. Additive interactions between DRB1*15:01 and smoking, obesity, EBNA-1 antibody levels and sun exposure, respectively, occurred to increase MS risk regardless of the clinical phenotype.
Interpretation:
Our finding that the same environmental and lifestyle factors affect both relapsing-onset and progressive-onset MS supports the notion that the different clinical phenotypes share common underlying disease mechanisms.
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