The genetics of multiple sclerosis: an up-to-date review

被引:182
作者
Gourraud, Pierre-Antoine [1 ]
Harbo, Hanne F. [1 ,2 ,3 ]
Hauser, Stephen L. [1 ]
Baranzini, Sergio E. [1 ]
机构
[1] Univ Calif San Francisco, Dept Neurol, San Francisco, CA 94143 USA
[2] Oslo Univ Hosp, Dept Neurol, Oslo, Norway
[3] Univ Oslo, Oslo, Norway
关键词
experimental autoimmune encephalitis; multiple sclerosis; major histocompatibility complex; neuroimmunology; GENOME-WIDE ASSOCIATION; INTERFERON-BETA TREATMENT; MAJOR HISTOCOMPATIBILITY COMPLEX; SUSCEPTIBILITY LOCI; HUMAN-DISEASE; RISK-FACTOR; INTERLEUKIN-7; RECEPTOR; MICROARRAY ANALYSIS; AUTOIMMUNE-DISEASE; AFRICAN-AMERICANS;
D O I
10.1111/j.1600-065X.2012.01134.x
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
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 geneenvironment 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.
引用
收藏
页码:87 / 103
页数:17
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