The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Smoking and two human leukocyte antigen genes interact to increase the risk for multiple sclerosis
Abstract
Both genetic and environmental factors display low or modest associations with multiple sclerosis. Hypothetically, gene-environment interactions may exert much stronger effects. In this study, we investigated potential interactions between genetic risk factors and smoking in relation to risk of developing multiple sclerosis. A population-based case-control study involving incident cases of multiple sclerosis (843 cases, 1209 controls) was performed in Sweden. Cases and controls were classified according to their smoking status and human leukocyte antigen DRB1 as well as human leukocyte antigen A genotypes. Subjects with different genotypes and smoking habits were compared with regard to incidence of multiple sclerosis, by calculating odds ratios with 95% confidence intervals employing logistic regression. The potential interaction between different genotypes, as well as between genotype and smoking, was evaluated by calculating attributable proportion due to interaction. A significant interaction between two genetic risk factors, carriage of human leukocyte antigen DRB1*15 and absence of human leukocyte antigen A*02, was observed among smokers whereas such an interaction was absent among non-smokers. There were considerable differences in odds ratios between the various groups. Compared with non-smokers with neither of the genetic risk factors, the odds ratio was 13.5 (8.1-22.6) for smokers with both genetic risk factors. The odds ratio for smokers without genetic risk was 1.4 (0.9-2.1) and the odds ratio for non-smokers with both genetic risk factors was 4.9 (3.6-6.6). Among those with both genetic risk factors, smoking increased the risk by a factor of 2.8 in comparison with a factor of 1.4 among those without the genetic risk factors. The risk of developing multiple sclerosis associated with human leukocyte antigen genotypes may be strongly influenced by smoking status. The findings are consistent with our hypothesis that priming of the immune response in the lungs may subsequently lead to multiple sclerosis in genetically susceptible people.
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Citations
Cites
Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”
Polman, C. H., Reingold, S. C., Edan, G., Filippi, M., Hartung, H., Kappos, L., Lublin, F. D., Metz, L. M., McFarland, H. F., O'Connor, P. W., et al. (2005) · Annals of Neurology · doi:10.1002/ana.20703 · Cited by 5,017
Serum 25-Hydroxyvitamin D Levels and Risk of Multiple Sclerosis
Munger, K. L., Levin, L. I., Hollis, B. W., Howard, N. S., & Ascherio, A. (2006) · JAMA · doi:10.1001/jama.296.23.2832 · Cited by 1,897
Olerup, O., & Zetterquist, H. (1992) · Tissue Antigens · doi:10.1111/j.1399-0039.1992.tb01940.x · Cited by 1,796
Klareskog, L., Stolt, P., Lundberg, K., Källberg, H., Bengtsson, C., Grunewald, J., Rönnelid, J., Erlandsson Harris, H., Ulfgren, A., Rantapää‐Dahlqvist, S., et al. (2006) · Arthritis & Rheumatism · doi:10.1002/art.21575 · Cited by 1,515
Self-citationCalculating measures of biological interaction
Andersson, T., Alfredsson, L., Källberg, H., Zdravkovic, S., & Ahlbom, A. (2005) · European Journal of Epidemiology · doi:10.1007/s10654-005-7835-x · Cited by 1,498
Self-citationDiagnostic criteria for multiple sclerosis
Poser, C. M., & Brinar, V. V. (2001) · Clinical Neurology and Neurosurgery · doi:10.1016/s0303-8467(00)00125-6 · Cited by 1,283
Confidence interval estimation of interaction
Hosmer, D. W., & Lemeshow, S. (1992) · Epidemiology · doi:10.1097/00001648-199209000-00012 · Cited by 1,239
Pedigree disequilibrium tests for multilocus haplotypes.
Dudbridge, F. (2003) · Genetic Epidemiology · doi:10.1002/gepi.10252 · Cited by 1,135
ROTHMAN, K. J., GREENLAND, S., & WALKER, A. M. (1980) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a113015 · Cited by 859 · cited 2×
“Gene–environment and gene–gene interactions were examined by quantification of departure from additivity of effects, described as the method most appropriate for identifying specific biological interactions (Rothman et al., 1980).”
MethodSchottenfeld, D. (2002) · American Journal of Epidemiology · doi:10.1093/aje/kwf028 · Cited by 622
Cited by
Filippi, M., Bar-Or, A., Piehl, F., Preziosa, P., Solari, A., Vukusic, S., & Rocca, M. A. (2018) · Nature Reviews Disease Primers · doi:10.1038/s41572-018-0041-4 · Cited by 1,562
Dietary fatty acids directly impact central nervous system autoimmunity via the small intestine
Haghikia, A., Jörg, S., Duscha, A., Berg, J., Manzel, A., Waschbisch, A., Hammer, A., Lee, D.-H., May, C., Wilck, N., et al. (2015) · Immunity · doi:10.1016/j.immuni.2015.09.007 · Cited by 927
Genetic insights into common pathways and complex relationships among immune-mediated diseases
Parkes, M., Cortes, A., van Heel, D. A., & Brown, M. A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3502 · Cited by 526
Miller, D. H., Chard, D. T., & Ciccarelli, O. (2012) · The Lancet Neurology · doi:10.1016/s1474-4422(11)70274-5 · Cited by 507
Class II HLA interactions modulate genetic risk for multiple sclerosis
the International Multiple Sclerosis Genetics Consortium (2015) · Nature Genetics · doi:10.1038/ng.3395 · Cited by 418
Metadata
- Authors
- Hedström, A. K., Sundqvist, E., Bäärnhielm, M., Nordin, N., Hillert, J., Kockum, I., Olsson, T., & Alfredsson, L.
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-02-08
- Volume
- 134
- Issue
- 3
- Pages
- 653-664
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- OpenAlex
- W1970849805
- Cited by
- 271
- References
- 44
- FWCI
- 17.61
- Type
- journal article
- Language
- en
- Open access
- closed
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- Hedström, A. K., Sundqvist, E., Bäärnhielm, M., Nordin, N., Hillert, J., Kockum, I., Olsson, T., & Alfredsson, L. (2011). Smoking and two human leukocyte antigen genes interact to increase the risk for multiple sclerosis. Brain. https://doi.org/10.1093/brain/awq371
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