Abstract
Objective We aimed to investigate the influence of lean and fatty fish consumption on MS risk and to what extent a potential effect may be mediated by vitamin D. We also studied the interplay between fish consumption, sun exposure, DRB1*15:01, and A*02:01.
Methods We used 2 population-based case-control studies (6,914 cases and 6,590 controls). Subjects with different fish consumption habits were compared regarding MS risk by calculating ORs with 95% CIs using logistic regression models. The mediation effect of vitamin D on the relationship between fish consumption and MS risk was assessed. Potential interactions between fish consumption, sun exposure, and MS-associated HLA genes were assessed on the additive scale.
Results Irrespective of sun exposure habits, low fish consumption, including both lean and fatty fish, was associated with increased MS risk (OR 1.2, 95% CI 1.1–1.4) and interacted with the DRB1*15:01 allele (AP 0.3, p < 0.0001). The mediation analysis did not support vitamin D as a mediator of the association between fish consumption and MS risk. There was no interaction between fish consumption and sun exposure habits with regard to MS risk.
Conclusions Low fish consumption and low sun exposure seem to be separate risk factors for MS. Our findings suggest that fish consumption predominantly influences MS risk by other means than by effecting vitamin D status, which is of relevance for prevention, in particular for those with a genetic susceptibility to MS.
Glossary
- BMI=
- body mass index;
- EIMS=
- Epidemiological Investigation of Multiple Sclerosis;
- GEMS=
- Genes and Environment in Multiple Sclerosis
MS is an immune-mediated inflammatory disorder of the CNS. Both genetic and environmental factors and their interactions influence susceptibility to the disease. The primary genetic risk factor for MS is the DRB1*15:01 allele of the HLA-DRB1 gene, which increases the risk of disease approximately 3-fold, but a large number of other HLA-associated alleles, such as A*02:01, also affect disease risk.1,2 There are reports suggesting an association between fish consumption and MS,3,–,6 which is also the case for sun exposure and vitamin D.7 However, it is unclear to what extent sun exposure and fish consumption associate with reduced MS risk by being sources of vitamin D.
Recently, we demonstrated an interaction between the presence of DRB1*15:01 and both low sun exposure and vitamin D deficiency, with regard to MS risk.8 However, no previous studies have investigated the influence of fish consumption in different genetic contexts.
Using 2 population-based case-control studies, we aimed to investigate the influence of lean and fatty fish consumption on MS risk and to what extent a potential effect may be mediated by vitamin D. We also studied the potential interplay between fish consumption, sun exposure habits, vitamin D status, DRB1*15:01, and A*02:01 status.
Methods
Study design and study participants
We used the Epidemiological Investigation of Multiple Sclerosis (EIMS) and Genes and Environment in Multiple Sclerosis (GEMS), which are Swedish population-based case-control studies on genetic and environmental factors for MS. The study population is the Swedish population aged 16–70 years. During the EIMS study period, April 2005–June 2015, incident cases of MS were recruited via 42 neurology units in Swedish hospitals, including all university hospitals. Cases were diagnosed by a neurologist according to the McDonald criteria.9 With regard to selection of controls, we have a link with direct access to the Swedish Tax Agency. For each included case in EIMS, we request 2 controls matched by age in 5-year intervals, sex, and residential area. The controls are randomly selected among those eligible by software designed for random selection at the Tax Agency. During the GEMS study period, November 2009–November 2011, all cases registered in the Swedish MS registry10 who fulfilled the McDonald criteria9 were asked to participate in GEMS if they were not included in EIMS. One control for each case was randomly selected from the national population register, matched by age in 5-year intervals, sex, and residential area where the case received its diagnosis. Controls were selected for all cases at the same time, using the same procedure as in EIMS.
Standard protocol approvals, registrations, and patient consents
Both studies were approved by the Regional Ethical Review Board at Karolinska Institutet, and all participants gave their informed consent to participate.
Data collection
In both studies, information regarding environmental exposures and lifestyle factors was collected using a standardized questionnaire. The EIMS and GEMS questionnaires were similar but not identical. Completed EIMS questionnaires were obtained from 2,880 cases and 6,122 controls, with a response rate of 93% for cases and 73% for controls. Completed GEMS questionnaires were obtained from 6,156 cases and 5,408 controls, with a response rate of 82% for cases and 66% for controls. Those who could not specify their sun exposure habits or fish consumption habits were excluded (79 cases and 95 controls in EIMS and 458 cases and 245 controls in GEMS). HLA status was available for 2,053 EIMS cases and 2,878 EIMS controls and for 4,861 GEMS cases and 3,712 GEMS controls, and these were included in the present study.
Self-reported exposure information
In EIMS, participants were asked how often, on average, they have consumed lean and fatty fish during the last 5 years. In GEMS, participants were asked how often, on average, they consumed lean and fatty fish at age 20 years. Fatty fish species were defined as species with a fat content of more than 3%, such as herring, mackerel, tuna fish, salmon, and trout, whereas lean fish species were defined as species with a fat content of less than 3%, such as cod, pollock, haddock, whiting, and pike perch. Each answer alternative was reported on a 4-point scale, with the answer alternatives never/seldom, 1–3 times/months, weekly, or daily. Very few participants reported daily consumption of fish, and the last 2 answer alternatives were therefore merged into one. We constructed an index by adding the numbers together and thus acquired a value between 2 (the lowest exposure) and 6 (the highest exposure). The fish consumption index is illustrated in table 1. Low fish consumption was defined as having a value below the median among controls (<4), whereas more frequent consumption was defined as high fish consumption. In EIMS, information on sun exposure habits during the last 5 years was collected by asking 3 questions regarding ultraviolet radiation exposure.5 Each answer alternative was reported on a 4-point scale, and by adding the numbers together, we constructed an index ranging between 3 (the lowest exposure) and 12 (the highest exposure).
Fish consumption habits among cases and controls
The same questions and the same answer alternatives regarding sun exposure were used in GEMS, but participants were instructed to estimate their sun exposure during summer and winter, respectively, in 10-year intervals. Sun exposure between age 10 and 29 years was considered when constructing a similar sun exposure index in GEMS, ranging between 6 (the lowest exposure) and 24 (the highest exposure). In both studies, low sun exposure was defined as having a value below the median among controls (<6 in EIMS and <12 in GEMS), whereas more frequent exposure was defined as high sun exposure.
Genotyping and measurement of vitamin D
HLA-DRB1 and HLA-A alleles were determined at 4-digit resolution. Genotyping was performed on the MS replication chip,11 which is based on an Illumina exome chip to which approximately 90,000 custom markers were added with extra high density in the HLA region, and HLA alleles were then imputed with HLA*IMP:02.12 For EIMS participants recruited between 2005 and 2009 (N = 2,462), vitamin D status was measured as levels of 25-hydroxyvitamin D using a chemiluminescent immunoassay from DiaSorin (DiaSorin AB, Sundbyberg, Sweden) and a Liaison instrument provided by DiaSorin AB with equimolar measurement of both 25-hydroxyvitamin D2 and D3. All samples were analyzed in a single batch. Vitamin D deficiency was defined as a value less than 50 nM/L.
Statistical analysis
Subjects with different fish consumption habits were compared with regard to MS risk by calculating ORs with 95% CIs using unconditional logistic regression models.13 Lean and fatty fish were also analyzed separately. The trend test for a dose-response relationship regarding fish consumption and risk of MS was performed by using a continuous variable for fish consumption (the fish consumption index) in a logistic regression model. Trend tests for dose-response relationships were also performed for lean and fatty fish separately. The analysis of fish consumption and MS risk was stratified by sex.
Causal mediation analysis was performed to asses to what extent the relationship between consumption of fatty fish and MS risk was mediated by vitamin D status. The exposure variable was low consumption of fatty fish, the mediator was vitamin D deficiency, and the outcome MS. The causal effects were estimated on the OR scale, and the CIs were calculated using the delta method.14
Potential biologic interactions were assessed on an additive scale by calculating the attributable proportion due to interaction with 95% CI. To elucidate the relationship between fish consumption, sun exposure, and DRB1*15:01 status, the analysis of interaction between low fish consumption and carriage of DRB1*15:01 was stratified by sun exposure habits. We also assessed potential interactions between low sun exposure and DRB1*15:01, stratified by fish consumption habits, and between low sun exposure and low fish consumption, stratified by DRB1*15:01 status. Similar analyses were performed to study the relationship between fish consumption, sun exposure, and A*02:01 status.
All analyses were adjusted for age, residential area, ancestry, and the following MS-associated HLA alleles that have been associated with MS risk independently of DRB1*15:01 status1: DRB1*03:01, DRB1*13:03, DRB1*08:01, B*44:02, B*38:01, B*55:01, DQA1*01:01, DQB1*03:02, and homozygote correction for DRB1*15:01, DRB1*03:01, and A*02:01. Ancestry was dichotomized into Nordic vs non-Nordic origin. A participant who was born in any of the Nordic countries, whose parents had not immigrated from outside the Nordic countries, was classified as Nordic. When appropriate, the analyses were also adjusted for sex, sun exposure habits, fish consumption habits, DRB1*15:01, and A*02:01 status.
Adjustments were also made for a number of potential confounding variables that only had minor influence on the results. These factors were not kept in the final analyses and included educational level, intake of vitamin supplements, adolescent body mass index (BMI), a history of infectious mononucleosis, smoking, passive smoking, and alcohol consumption. Educational level was categorized into no postsecondary education, postsecondary education without a university degree, or university degree. Intake of vitamin supplements was dichotomized into regular intake of multivitamins or vitamin D supplements or not. Adolescent BMI was calculated by dividing self-reported weight in kilograms by self-reported height in meters squared and dichotomized into BMI <25 or BMI ≥25 kg/m2. A history of mononucleosis was dichotomized into yes or no. Smoking and passive smoking were considered before the onset of disease among cases and during the same period among the corresponding controls. Smoking was dichotomized into current, past, or never smokers. Passive smoking was dichotomized into ever or never exposed. Alcohol consumption was categorized into low, moderate, or high consumption based on the number of drinks per week.15
We performed 2 subanalyses based on EIMS to be able to adjust the analyses for dietary habits and salt intake. Participants with disease onset during the last 5 years before study inclusion were included in the first subanalysis (2,209 cases and 4,610 controls). Based on a question regarding dietary habits 5 years ago, participants could choose between the following answer alternatives (1) normal diet/mixed diet, (2) vegetarian food, (3) vegetarian food including fish and shellfish, (4) vegan diet, (5) Mediterranean diet, (6) GI diet, and (7) other diet. Dietary habits were categorized based on the answer alternatives, using normal diet/mixed diet as the reference group. In the second subanalysis, we adjusted for salt intake. In November 2013, complementary questions were sent to all participants who had answered the standardized questionnaire during April 2005 to March 2013. The complementary questions were answered by 1,762 cases (82%) and 2,975 controls (66%). Among other questions, participants were asked to report their salt intake during different age periods. The questions were as follows: (1) how often do you eat at restaurants, including takeaway? (2) how often do you eat prepared meals or dishes that are bought at the supermarket, and (3) how often do you use extra salt on your food? The answer alternatives were less than 1 time/month, 1–3 times/month, 1–2 times/week, 3–6 times/week, daily, and several times/day. Each question was categorized based on the answer alternatives, using less than 1 time/month as the reference group. All analyses were conducted using Statistical Analysis System (SAS) version 9.4.
Data availability
Anonymized data will be shared by request from any qualified investigator who wants to analyze questions that are related to the published article.
Results
In EIMS, the mean age at MS onset was 34 years. Almost all cases were recruited within 1 year after the diagnosis, and the questionnaires were completed after a median of 2.0 years following the onset of the disease. Characteristics of cases and controls, overall and by fish consumption habits during the 5-year period before study inclusion, are presented in table 2. The mean age at MS onset was 33 years in GEMS. The median duration between disease onset and study inclusion was 17 years. Characteristics of cases and controls, overall and by fish consumption habits at age 20 years, are presented in table 2.
Characteristics of cases and controls, overall and by fish consumption habits
The fish consumption index was created to estimate the overall fish consumption (table 1). In both studies, the risk of MS was increased among subjects with low fish consumption (OR 1.2, 95% CI 1.1–1.4) compared with those with high fish consumption. There were no significant sex differences (table 3). Low consumption of both lean and fatty fish was significantly associated with increased MS risk in both studies, and there was a significant trend showing increasing MS risk with decreasing consumption of fatty fish (p for trend <0.001 in EIMS and 0.02 in GEMS). In EIMS, there was also a significant trend showing increasing MS risk with decreasing consumption of lean fish (p for trend 0.002).
OR with 95% CI of MS for subjects with low fish intake compared with those with high fish intake, overall and stratified by sex
There was a positive correlation between consumption of fatty fish and vitamin D status (p < 0.0001) and a borderline significant correlation between consumption of lean fish and vitamin D status (p = 0.05). Causal mediation analysis showed that the total effect of low consumption of fatty fish with regard to MS risk was 1.2 (95% CI 1.0–1.5). The direct effect was 1.2 (95% CI 1.0–1.5), whereas the magnitude of the indirect effect, mediated by vitamin D deficiency, was very small (OR 1.03, 95% CI 1.00–1.06) but statistically significant. Similar results were obtained with lean fish as the exposure variable. Both the total and direct effect was 1.3 (95% CI 1.0–1.6), and the indirect effect, mediated by vitamin D deficiency, was 1.01 (95% CI 0.98–1.03). There was a synergistic effect between low fish consumption and DRB1*15:01, both among those who reported high and low sun exposure (table 4). The interaction became more pronounced with lower consumption of fish (table 5). There was no suggestion of an interaction between fish consumption and A*02:01 status with regard to MS risk (table 6). No interaction was observed between sun exposure and fish consumption with regard to MS risk, irrespective of DRB1*15:01 status (table 7). In the subanalyses, results remained similar after adjustment for dietary habits and salt intake (data not shown).
OR with 95% CI of MS for subjects with different combinations of DRB1*15:01 status and fish consumption habits compared with DRB1*15:01-negative subjects with high fish consumption, overall and stratified by sun exposure habits
OR with 95% CI of MS for subjects with different combinations of DRB1*15:01 status and fish consumption habits compared with DRB1*15:01-negative subjects with high fish consumption
OR with 95% CI of MS for subjects with different combinations of A*02:01 status and fish consumption habits compared with A*02:01-positive subjects with high fish consumption, overall and stratified by sun exposure habits
OR with 95% CI of MS for subjects with different combinations of sun exposure and fish consumption habits compared with those with high sun exposure and high fish consumption, overall and stratified by DRB1*15:01 status
Discussion
According to the results of the present study, low fish consumption is associated with an increased risk of developing MS. The mediation analysis did not support vitamin D as a mediator of the association between fish consumption and MS risk. Low fish consumption and low sun exposure seem to be separate risk factors for MS, and significant interactions occurred between each of these lifestyle factors and the DRB1*15:01 allele.
The mechanisms behind the association between the studied lifestyle factors and MS risk have yet to be elucidated. Fish consumption and sun exposure are important sources of vitamin D, which has repeatedly been associated with reduced MS risk.16,17 However, the mediation analysis did not support vitamin D as a mediator of the association between fish consumption and MS risk. Low consumption of lean fish showed a similar impact on MS risk as did low consumption of fatty fish. Furthermore, if the influence of low sun exposure and low fish consumption both had been mediated by low levels of vitamin D, we would have expected less impact of fish consumption on MS risk among those with high sun exposure, which was not the case.
Our findings suggest that high consumption of both lean and fatty fish may potentially protect against the development of MS. The mechanism behind the protective effect may involve any nutrient found in both types of fish. This view is strengthened by the finding that there was less than an additive effect among those who consumed high amounts of both lean and fatty fish. Lean fish is a poor source of vitamin D compared with fatty fish, and a potential protective effect of lean fish on MS risk has been less studied. Omega-3 fatty acids, almost exclusively found in aquatic organisms, are capable of attenuating several aspects of inflammation and have been inversely associated with both MS risk18,19 and MS progression.20 Generally, fatty fish contains more omega-3 fatty acids than lean fish, but all fish and shellfish contain some omega-3 fatty acids. Fish also contains taurine, a semiessential amino acid with anti-inflammatory and neuroprotective effects.21 Taurine analogs have been considered as potential therapeutic agents for neurologic disorders.21 Diet also has a profound influence on the gut microbiota hypothesized to affect the composition of fatty acids, which, in turn, may affect immune functions such as T regulatory cells.22,23
In our previous report on fish consumption and MS risk,6 based on EIMS, we found inverse associations of both lean and fatty fish in relation to risk of MS, but the association between lean fish and MS risk was not statistically significant, probably because of insufficient statistical power.
Our studies, which were designed as case-control studies, retrospectively gathered self-reported information regarding exposures and lifestyle factors. We took great care to obtain information in an identical way for cases and controls. Moreover, the questionnaires contained a wide range of questions regarding many potential environmental factors, and no section in the questionnaire was given prime focus. The risk of recall bias is greater in GEMS in which prevalent MS cases were asked to recall their fish consumption habits at age 20 years. In EIMS, incident cases of MS were asked to provide information regarding their fish consumption habits during the past 5 years. In this study, we primarily included cases of MS who had received their diagnosis within the past year to minimize recall bias. However, our observation of an association between low fish consumption and MS risk was similar in GEMS and EIMS and also in agreement with previous studies.
The recruitment of cases and controls may introduce selection bias. Some cases may have been unidentified in our studies. However, the Swedish health care system provides free-of-charge access to all Swedish residents, and almost all cases of MS are referred to hospital-based neurologic units. In total, 42 study centers reported cases of MS to EIMS, including all university hospitals. It is unlikely that the relatively few unidentified cases at participating centers would cause a substantial bias. A potential selection bias may result from the relatively high proportion of nonresponders among the controls. However, this bias is most likely to be modest because the prevalence of lifestyle factors, such as smoking, alcohol intake, and body mass index, among the controls was in line with that of the general population.24 There were no significant differences with respect to age, sex, or fish consumption habits between those who provided a blood sample and those who did not, indicating that selection bias did not take place in this step. The observed interactions between DRB1*15:01 and both low sun exposure and low fish consumption also alleviate some potential biases in the interpretation of the influence from the lifestyle factors on MS risk because the HLA alleles are not likely to determine exposure habits. We thus consider it unlikely that our findings would be affected by bias to a large extent, especially because such a bias would then depend on HLA types. In the present study, we had the opportunity to take a large number of potential confounding factors into account, including education, smoking, alcohol, vitamin supplements, adolescent obesity, and genetics. The factors considered only had minor influence on the results. However, the observed associations were weak or modest, and we cannot completely rule out residual confounding.
In conclusion, low fish consumption and low sun exposure seem to be separate risk factors for MS, and significant interactions take place between each of these lifestyle factors and the DRB1*15:01 allele. Our findings suggest that fish consumption predominantly influences MS risk by other means than by effecting vitamin D status, which is of relevance for prevention, in particular for those with a genetic susceptibility to MS.
Study funding
The study was supported by grants from the Swedish Medical Research Council, the Swedish Research Council for Health, Working Life and Welfare, the Swedish Brain Foundation, and the Swedish Society for Medical Research.
Disclosure
A.K. Hedström reports no disclosures relevant to the manuscript. T. Olsson reports grants from the Swedish Research Council, the Knut and Alice Wallenberg Foundation, and the Swedish Brain Foundation, during the conduct of the study; grants and personal fees from Biogen, Genzyme, and Novartis; and personal fees from Merck, outside the submitted work. I. Kockum reports no disclosures relevant to the manuscript. J. Hillert received honoraria for serving on advisory boards of Biogen and Novartis and speaker's fees from Biogen, Merck Serono, Bayer Schering, Teva, and Sanofi-Aventis. He has served as principal investigator for projects sponsored by or received unrestricted research support from Biogen, Merck Serono, Teva, Novartis, and Bayer Schering. L. Alfredsson reports grants from the Swedish Research Council, the Swedish Research Council for Health Working Life and Welfare, and the Swedish Brain Foundation. Go to Neurology.org/NN for full disclosures.
Appendix Authors
Footnotes
Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article.
The Article Processing Charge was funded by the authors.
- Received December 12, 2019.
- Accepted in final form February 25, 2020.
- Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.
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References
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