The genetics of autoimmune diseases: a networked perspective

被引：111

作者：

Baranzini, Sergio E. ^{[1
]}

机构：

[1] Univ Calif San Francisco, Dept Neurol, Sch Med, San Francisco, CA 94143 USA

来源：

CURRENT OPINION IN IMMUNOLOGY | 2009年 / 21卷 / 06期

关键词：

GENOME-WIDE ASSOCIATION; SYSTEMIC-LUPUS-ERYTHEMATOSUS; IDENTIFIES SUSCEPTIBILITY VARIANTS; SINGLE NUCLEOTIDE POLYMORPHISMS; INFLAMMATORY-BOWEL-DISEASE; 7 COMMON DISEASES; MULTIPLE-SCLEROSIS; RHEUMATOID-ARTHRITIS; CROHNS-DISEASE; RISK LOCUS;

D O I：

10.1016/j.coi.2009.09.014

中图分类号：

R392 [医学免疫学]; Q939.91 [免疫学];

学科分类号：

100102 ;

摘要：

Modern tools for genetic analysis are producing a large impact on our understanding of autoimmunity. More than 30 genome-wide association studies (GWAS) have been published to date in several autoimmune diseases (AID) and hundreds of common variants have been identified that confer risk or protection. While statistical adjustments are essential to refine the list of potential associations with each disease, valuable information can be extracted by the systematic collection of moderately significant variants present in more than one trait. In this article, a compilation of all GWAS published to date in seven common AID is provided and a network-based analysis of shared susceptibility genes at different levels of significance is presented. While involvement of the MHC region in chromosome 6p21 is not in question for most AID, the complex genetic architecture of this locus poses a significant analytical challenge. On the other hand, by considering the contribution of non-MHC-related genes, similarities and differences among AID can be readily computed thus gaining insights into possible pathogenic mechanisms. Statistically significant excess sharing of non-MHC genes was found between type I diabetes (T1D) and all other AID studied, a result also seen for RA. A smaller but significant degree of sharing was observed for multiple sclerosis (MS), Celiac disease (CeD) and Crohn's disease (CD). The availability of GWAS data allows for a systematic analysis of similarities and differences among several AID. Using this class of approaches the unique genetic landscape for each autoimmune disease can start to be defined.

引用

页码：596 / 605

页数：10

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