Neurology · 2010 · 132 citations · 32 references
Life SciencesImmunologyAutoimmunityEpidemiologic MethodsEpidemiologyAnalytic EpidemiologyAutoimmune DiseasesMultiple SclerosisTobacco EpidemiologyTobacco Use Risk AssessmentCase-control Association StudiesCase-control Study DesignConfidence Intervals For Odds RatiosInverse Variance WeightingMultiple Sclerosis AssociationsNested Case-control DesignPooled Odds RatiosSmoking Epidemiology
OBJECTIVE: To examine the interplay between smoking, serum antibody titers to the Epstein-Barr virus nuclear antigens (anti-EBNA), and HLA-DR15 on multiple sclerosis (MS) risk. METHODS: Individual and pooled analyses were conducted among 442 cases and 865 controls from 3 MS case-control studies-a nested case-control study in the Nurses' Health Study/Nurses' Health Study II, the Tasmanian MS Study, and a Swedish MS Study. Conditional logistic regression models were used to calculate odds ratios (ORs) and 95% CIs for the association between smoking, anti-EBNA titers, HLA-DR15, and MS risk. Study estimates were pooled using inverse variance weights to determine a combined effect and p value. RESULTS: Among MS cases, anti-EBNA titers were significantly higher in ever smokers compared to never smokers. The increased risk of MS associated with high anti-EBNA Ab titers was stronger among ever smokers (OR = 3.9, 95% CI = 2.7-5.7) compared to never smokers (OR = 1.8, 95% CI = 1.4-2.3; p for interaction = 0.001). The increased risk of MS associated with a history of smoking was no longer evident after adjustment for anti-EBNA Ab titers. No modification or confounding by HLA-DR15 was observed. The increased risk of MS associated with ever smoking was only observed among those who had high anti-EBNA titers (OR = 1.7, 95% CI = 1.1-2.6). CONCLUSIONS: Smoking appears to enhance the association between high anti-EBNA titer and increased multiple sclerosis (MS) risk. The association between HLA-DR15 and MS risk is independent of smoking. Further work is necessary to elucidate possible biologic mechanisms to explain this finding.
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