Fernald Guy Haskin, Yeh Ru-Fang, Hauser Stephen L, Oksenberg Jorge R, Baranzini Sergio E
Department of Neurology, School of Medicine, University of California, 513 Parnassus Avenue, S-256, San Francisco, CA 94143-0435, USA.
J Neuroimmunol. 2005 Oct;167(1-2):157-69. doi: 10.1016/j.jneuroim.2005.06.032.
Genetic predisposition contributes to the pathogenesis of most common diseases. Genetic studies have been extremely successful in the identification of genes responsible for a number of Mendelian disorders. However, with a few exceptions, genes predisposing to diseases with complex inheritance remain unknown despite multiple efforts. In this article we collected detailed information for all genome-wide genetic screens performed to date in multiple sclerosis (MS) and in its animal model experimental autoimmune encephalomyelitis (EAE), and integrated these results with those from all high throughput gene expression studies in humans and mice. We analyzed a total of 55 studies. We found that differentially expressed genes (DEG) are not uniformly distributed in the genome, but rather appear in clusters. Furthermore, these clusters significantly differ from the known heterogeneous organization characteristic of eukaryotic gene distributions. We also identified regions of susceptibility that overlapped with clusters of DEG leading to the prioritization of candidate genes. Integration of genomic and transcriptional information is a powerful tool to dissect genetic susceptibility in complex multifactorial disorders like MS.
遗传易感性在大多数常见疾病的发病机制中起作用。遗传研究在鉴定导致多种孟德尔疾病的基因方面极为成功。然而,除了少数例外,尽管进行了多次努力,导致复杂遗传疾病的基因仍然未知。在本文中,我们收集了迄今为止在多发性硬化症(MS)及其动物模型实验性自身免疫性脑脊髓炎(EAE)中进行的所有全基因组遗传筛选的详细信息,并将这些结果与人类和小鼠所有高通量基因表达研究的结果进行整合。我们总共分析了55项研究。我们发现差异表达基因(DEG)并非均匀分布在基因组中,而是呈簇状出现。此外,这些簇与真核基因分布的已知异质组织特征有显著差异。我们还确定了与DEG簇重叠的易感区域,从而确定了候选基因的优先级。整合基因组和转录信息是剖析像MS这样复杂多因素疾病遗传易感性的有力工具。