基因表达谱预测早期类风湿关节炎患者疾病严重程度

Zheng Liu, Tuulikki Sokka, Kevin Maas, Nancy J Olsen, Thomas M Aune
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引用次数: 29

摘要

为了测试外周血基因表达谱预测早期类风湿关节炎(RA)患者未来疾病严重程度的能力,在基线时对17例患者(病程1±0.2年)的基因表达谱进行了评估。平均5年后,使用疼痛、总体和重新编码的MHAQ评分相结合的指数评估疾病状态。无监督和有监督算法确定了“预测基因”,其组合表达水平与随访疾病严重程度评分相关。无监督聚类算法将患者分为两个分支。两组之间唯一的显著差异是疾病严重程度评分;人口统计学变量和用药情况无差异。监督t检验分析确定了19个未来疾病严重程度的“预测基因”。使用支持向量机和k -最近邻分类在已建立RA的受试者独立队列中验证了结果。我们的研究表明,外周血基因表达谱可能是预测早期和确诊类风湿性关节炎患者未来疾病严重程度的有用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Prediction of disease severity in patients with early rheumatoid arthritis by gene expression profiling.

In order to test the ability of peripheral blood gene expression profiles to predict future disease severity in patients with early rheumatoid arthritis (RA), a group of 17 patients (1 ± 0.2 years disease duration) was evaluated at baseline for gene expression profiles. Disease status was evaluated after a mean of 5 years using an index combining pain, global and recoded MHAQ scores. Unsupervised and supervised algorithms identified "predictor genes" whose combined expression levels correlated with follow-up disease severity scores. Unsupervised clustering algorithms separated patients into two branches. The only significant difference between these two groups was the disease severity score; demographic variables and medication usage were not different. Supervised T-Test analysis identified 19 "predictor genes" of future disease severity. Results were validated in an independent cohort of subjects of established RA with using Support Vector Machines and K-Nearest-Neighbor Classification. Our study demonstrates that peripheral blood gene expression profiles may be a useful tool to predict future disease severity in patients with early and established RA.

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