The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
The genetics of multiple sclerosis: an up‐to‐date review
Open accessAbstract
Summary: Multiple sclerosis (MS) is a prevalent inflammatory disease of the central nervous system that often leads to disability in young adults. Treatment options are limited and often only partly effective. The disease is likely caused by a complex interaction between multiple genes and environmental factors, leading to inflammatory‐mediated central nervous system deterioration. A series of genomic studies have confirmed a central role for the immune system in the development of MS, including genetic association studies that have now dramatically expanded the roster of MS susceptibility genes beyond the longstanding human leukocyte antigen (HLA) association in MS first identified nearly 40 years ago. Advances in technology together with novel models for collaboration across research groups have enabled the discovery of more than 50 non‐HLA genetic risk factors associated with MS. However, with a large proportion of the disease heritability still unaccounted for, current studies are now geared towards identification of causal alleles, associated pathways, epigenetic mechanisms, and gene–environment interactions. This article reviews recent efforts in addressing the genetics of MS and the challenges posed by an ever increasing amount of analyzable data, which is spearheading development of novel statistical methods necessary to cope with such complexity.
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Cites
Network biology: understanding the cell's functional organization
Barabási, A.-L., & Oltvai, Z. N. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1272 · Cited by 7,903
Network medicine: a network-based approach to human disease
Barabási, A.-L., Gulbahce, N., & Loscalzo, J. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2918 · Cited by 5,034
Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
The International Multiple Sclerosis Genetics Consortium & The Wellcome Trust Case Control Consortium 2 (2011) · Nature · doi:10.1038/nature10251 · Cited by 2,697
Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S., & Hirschhorn, J. N. (2003) · Nature Genetics · doi:10.1038/ng1071 · Cited by 1,900
Risk Alleles for Multiple Sclerosis Identified by a Genomewide Study
(2007) · New England Journal of Medicine · doi:10.1056/nejmoa073493 · Cited by 1,746
Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants
Wellcome Trust Case Control Consortium, & The Australo-Anglo-American Spondylitis Consortium (TASC) (2007) · Nature Genetics · doi:10.1038/ng.2007.17 · Cited by 1,374
Ideker, T., & Sharan, R. (2008) · Genome Research · doi:10.1101/gr.071852.107 · Cited by 817
Ioannidis, J. P. A. (2009) · Canadian Medical Association Journal · doi:10.1503/cmaj.081086 · Cited by 716
Pervasive Sharing of Genetic Effects in Autoimmune Disease
Cotsapas, C., Voight, B. F., Rossin, E., Lage, K., Neale, B. M., Wallace, C., Abecasis, G. R., Barrett, J. C., Behrens, T., Cho, J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002254 · Cited by 606
Detecting shared pathogenesis from the shared genetics of immune-related diseases
Zhernakova, A., van Diemen, C. C., & Wijmenga, C. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2489 · Cited by 551
Cited by
Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility
International Multiple Sclerosis Genetics Consortium, Patsopoulos, N. A., Baranzini, S. E., Santaniello, A., Shoostari, P., Cotsapas, C., Wong, G., Beecham, A. H., James, T., Replogle, J., et al. (2019) · Science · doi:10.1126/science.aav7188 · Cited by 1,471
“Although the exact amount of MS’s heritability varies given the data and method used, (36-38) we report that our findings can explain up to 48% of the heritability that can be estimated using large-scale GWAS data.”
MethodSelf-citationAnalysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis
International Multiple Sclerosis Genetics Consortium (IMSGC) (2013) · Nature Genetics · doi:10.1038/ng.2770 · Cited by 1,386
Sex and gender issues in multiple sclerosis
Harbo, H. F., Gold, R., & Tintoré, M. (2013) · Therapeutic Advances in Neurological Disorders · doi:10.1177/1756285613488434 · Cited by 529
Self-citationFrom Identification to Characterization of the Multiple Sclerosis Susceptibility Gene CLEC16A
Berge, T., Leikfoss, I., & Harbo, H. (2013) · International Journal of Molecular Sciences · doi:10.3390/ijms14034476 · Cited by 45
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Metadata
- Authors
- Gourraud, P., Harbo, H. F., Hauser, S. L., & Baranzini, S. E.
- Venue
- Immunological Reviews
- Publisher
- Wiley
- Published
- 2012-06-21
- Volume
- 248
- Issue
- 1
- Pages
- 87-103
- ISSN
- 0105-2896 (ISSN-L)
- 1600-065X
- OpenAlex
- W2137277521
- Cited by
- 282
- References
- 18
- FWCI
- 5.99
- Type
- journal article
- Language
- en
- Open access
- green
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