The interplay between environmental risk factors for multiple sclerosis
Not peer reviewed
MetadataShow full item record
Background: Multiple sclerosis (MS) is a chronic demyelinating disease of the central nervous system whose etiology is unknown. While several genetic factors and environmental exposures, including low vitamin D, smoking, infectious mononucleosis (IM) and obesity, have been consistently associated with increased MS risk, they are unlikely to fully explain the individual disease risk. Further, little is known about the underlying mechanisms by which they may affect disease risk.
Objective: The main objectives of this study were to examine how exposure to selected environmental factors in specific age periods was associated with MS risk and to disclose whether the associations varied between different populations using the same methodology. In detail, we sought 1) to examine how frequency of outdoor activity, as a proxy for sun exposure and vitamin D levels, in specific age periods from birth to disease onset was associated with MS risk, 2) to examine to which degree prior exposure to known environmental risk factors could explain the association between level of education and MS risk and 3) to examine how the interplay between smoking and IM affected MS risk in our study populations.
Methods: We used data from the large multi-national population-based case-control study Environmental Risk Factors in MS (EnvIMS), which included participants from Norway, Italy, Serbia, Sweden and Canada. For the two first articles, data from Norway and Italy was available, while for the third article data from Sweden was also available. In total, this included 1904 patients and 3694 controls. In the countries included in our analyses, patients were recruited from regional or national MS registries, while four times as many age and sex frequency-matched controls were randomly selected from population registries. All patients had been diagnosed according to the McDonald or the Poser criteria, and had clinical onset within 10 years prior to data collection. All participants were older than 18 years at time of selection. Cases and controls in each country reported on prior exposure to selected environmental factors in specific age periods of life using an identical selfadministered questionnaire (EnvIMS-Q), which had been developed specifically for our study. For the current analyses, information on outdoor activity, sunscreen use, hair color, smoking, IM, body size, cod liver oil supplementation, fatty fish intake and level of education was used. The controls were randomly assigned an index age based on the distribution of age of onset among the cases and exposure after disease onset or index age was not considered exposure. The association between disease and exposure was estimated as odds ratios (OR) with 95% confidence intervals (95% CI) using logistic regression. All analyses were adjusted for age and sex.
Results: In the first article, we found a significant inverse association between frequency of outdoor activity and MS risk in Norway and Italy. The magnitude of the association was strongest between age 16 and 18 in Norway (OR 1.83, 95% CI: 1.30- 2.59), and between birth and age 5 years in Italy (OR 1.56, 95% CI: 1.16-2.10). We observed seasonal differences in the association in Norway, whereas we observed a significant association for outdoor activity during summer, but not in the winter. For Italy, the association was similar for summer and winter. In addition, we found a significant association between sunscreen use and MS risk during childhood in Norway after accounting for outdoor activity (OR 1.67, 95% CI: 1.06-2.63).
In the second article, we found an inverse association between level of education and MS risk in Norway (OR highest vs lowest level: 0.53, 95% CI: 0.41-0.68). The association remained significant after adjusting for smoking, IM, outdoor activity, cod liver oil, fatty fish consumption and body size. Further, the association remained similar after we excluded patients with early onset of disease, defined as onset before age 28.
In the third article, we found a statistical significant negative multiplicative interaction between smoking and IM in the risk of MS. Among those who reported IM, we observed no increased disease risk associated with smoking. Similarly, the effect estimates for the association between IM and MS risk were considerably lower among ever-smokers compared to never smokers. The interaction was similar in Norway, Italy, and Sweden. Lastly, we observed similar results on when estimating the interaction on the additive scale, although they did not reach statistical significance.
Conclusion: The findings of this study add to the evidence that vitamin D has a protective effect on MS risk, and indicate that adolescence is a sensitive period for exposure. Still, exposure earlier in life might also be of importance. Further, established risk factors cannot fully explain the association between level of education and MS risk in Norway, suggesting that currently unknown environmental exposures associated with lower level of education may be important for disease risk. Lastly, our findings indicate a competing antagonism between smoking and IM in the risk of MS, which suggests that the two risk factors operate on shared biological pathways.