Brassat D, Motsinger A A, Caillier S J, Erlich H A, Walker K, Steiner L L, Cree B A C, Barcellos L F, Pericak-Vance M A, Schmidt S, Gregory S, Hauser S L, Haines J L, Oksenberg J R, Ritchie M D
Department of Neurology and Center for Human Genetics, School of Medicine, University of California at San Francisco, USA.
Genes Immun. 2006 Jun;7(4):310-5. doi: 10.1038/sj.gene.6364299. Epub 2006 Apr 20.
Multiple sclerosis (MS) is a common disease of the central nervous system characterized by inflammation, myelin loss, gliosis, varying degrees of axonal pathology, and progressive neurological dysfunction. Multiple sclerosis exhibits many of the characteristics that distinguish complex genetic disorders including polygenic inheritance and environmental exposure risks. Here, we used a highly efficient multilocus genotyping assay representing variation in 34 genes associated with inflammatory pathways to explore gene-gene interactions and disease susceptibility in a well-characterized African-American case-control MS data set. We applied the multifactor dimensionality reduction (MDR) test to detect epistasis, and identified single-IL4R(Q576R)- and three-IL4R(Q576R), IL5RA(-80), CD14(-260)- locus association models that predict MS risk with 75-76% accuracy (P<0.01). These results demonstrate the importance of exploring both main effects and gene-gene interactions in the study of complex diseases.
多发性硬化症（MS）是一种常见的中枢神经系统疾病，其特征为炎症、髓鞘脱失、胶质增生、不同程度的轴索病变以及进行性神经功能障碍。多发性硬化症具有许多区分复杂遗传疾病的特征，包括多基因遗传和环境暴露风险。在此，我们使用了一种高效的多位点基因分型检测方法，该方法代表了与炎症途径相关的34个基因的变异，以在一个特征明确的非裔美国人MS病例对照数据集中探索基因-基因相互作用和疾病易感性。我们应用多因素降维（MDR）测试来检测上位性，并确定了单IL4R（Q576R）和三IL4R（Q576R）、IL5RA（-80）、CD14（-260）位点关联模型，这些模型预测MS风险的准确率为75 - 76%（P<0.01）。这些结果证明了在复杂疾病研究中探索主效应和基因-基因相互作用的重要性。
