Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands.
Mult Scler. 2010 Jun;16(6):652-9. doi: 10.1177/1352458510364633. Epub 2010 Apr 8.
Multiple sclerosis is a heterogeneous neurological disease with varying degrees of severity. The common hypothesis is that susceptibility to multiple sclerosis and its phenotype are caused by a combination of environmental and genetic factors. The genetic part exerts its effect through several genes, each having modest effects. We evaluated whether disease severity could be predicted by a model based on clinical data and data from a DNA chip. The DNA chip was designed containing several single nucleotide polymorphisms in 44 genes, previously described to be associated with multiple sclerosis. A total of 605 patients with multiple sclerosis were included in this analysis, using gender, onset type and age at onset as clinical covariates. We correlated 80 single nucleotide polymorphisms to the degree of disease severity using the following three outcome measures: linear Multiple Sclerosis Severity Score, dichotomous Multiple Sclerosis Severity Score (using a cut-off point of 2.5) and time to reach Expanded Disability Status Scale score 6. Sixty-nine single nucleotide polymorphisms were included in the analysis. No individual single nucleotide polymorphism showed a significant association; however, a combination of single nucleotide polymorphisms significantly improved the prediction of disease severity in addition to the clinical variables. In all three models the Interleukin 2 gene was included, confirming a previously reported modest effect on disease severity. The highest power was obtained using the dichotomized Multiple Sclerosis Severity Score as outcome. Several single nucleotide polymorphisms showed their added predictive value over the clinical data in the predictive models. These results support our hypothesis that disease severity is determined by clinical variables and genetic influences (through several genes with small effects) in concert.
多发性硬化症是一种具有不同严重程度的异质性神经疾病。常见的假设是多发性硬化症的易感性及其表型是由环境和遗传因素共同作用引起的。遗传部分通过几个基因发挥作用，每个基因的影响都较小。我们评估了基于临床数据和 DNA 芯片数据的模型是否可以预测疾病的严重程度。该 DNA 芯片设计包含 44 个基因中的几个单核苷酸多态性，这些基因先前被描述与多发性硬化症有关。共有 605 名多发性硬化症患者纳入本分析，使用性别、发病类型和发病年龄作为临床协变量。我们使用以下三种结果测量方法，将 80 个单核苷酸多态性与疾病严重程度相关联：线性多发性硬化症严重程度评分、二分多发性硬化症严重程度评分（使用 2.5 的截止值）和达到扩展残疾状况量表评分 6 的时间。69 个单核苷酸多态性被纳入分析。虽然没有单个单核苷酸多态性显示出显著相关性，但单核苷酸多态性的组合除了临床变量外，还显著改善了疾病严重程度的预测。在所有三个模型中，白细胞介素 2 基因都包含在内，证实了先前报道的对疾病严重程度的适度影响。使用二分多发性硬化症严重程度评分作为结果，获得了最高的功效。在预测模型中，一些单核苷酸多态性显示出比临床数据更高的预测价值。这些结果支持我们的假设，即疾病严重程度是由临床变量和遗传影响（通过几个具有较小影响的基因）共同决定的。
