Molecular Biomarkers for Quantitative and Discrete COPD Phenotypes
Molecular Biomarkers for Quantitative and Discrete COPD Phenotypes
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DOI：
10.1165/rcmb.2008-0114oc
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发表时间：
2009-03-01
影响因子：
6.4
通讯作者：
Mariani, Thomas J.
中科院分区：
文献类型：
--
作者：
Bhattacharya, Soumyaroop;Srisuma, Sorachai;Mariani, Thomas J.
慢性阻塞性肺疾病（COPD）是一种病理特征复杂、病因不明的炎症性肺部疾病。这种疾病的生物标志物的鉴定可以帮助开发方法，以促进早期诊断，疾病亚型的分类，并提供一种方法来定义治疗反应。为了鉴定基因表达生物标志物，我们使用Affytron U133 Plus 2.0阵列完成了来自56名不同程度气流阻塞受试者肺组织的RNA表达谱分析。我们应用多种独立的分析方法来定义离散或定量疾病表型的生物标志物。病例（n = 15）和对照（n = 18）之间差异表达的分析确定了一组65个离散的生物标志物。基因表达与气流阻塞定量指标（FEV1%预测值或FEV 1/FVC）的相关性确定了一组220个生物标志物。生物标志物基因富含与DNA结合和转录调控相关的功能。我们使用这组生物标志物来预测来自严重肺气肿患者的不相关数据集的疾病，准确率为97%。我们的数据有助于了解阻塞性肺疾病患者肺组织中发生的基因表达变化，并为疾病过程中涉及的潜在机制提供额外的见解。此外，我们提出了第一个在独立数据集中验证的COPD基因表达生物标志物。
Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disorder with complex pathological features and largely unknown etiology. The identification of biomarkers for this disease could aid the development of methods to facilitate earlier diagnosis, the classification of disease subtypes, and provide a means to define therapeutic response. To identify gene expression biomarkers, we completed expression profiling of RNA derived from the lung tissue of 56 subjects with varying degrees of airflow obstruction using the Affymetrix U133 Plus 2.0 array. We applied multiple, independent analytical methods to define biomarkers for either discrete or quantitative disease phenotypes. Analysis of differential expression between cases (n = 15) and controls (n = 18) identified a set of 65 discrete biomarkers. Correlation of gene expression with quantitative measures of airflow obstruction (FEV1%predicted or FEV1/FVC) identified a set of 220 biomarkers. Biomarker genes were enriched in functions related to DNA binding and regulation of transcription. We used this group of biomarkers to predict disease in an unrelated data set, generated from patients with severe emphysema, with 97% accuracy. Our data contribute to the understanding of gene expression changes occurring in the lung tissue of patients with obstructive lung disease and provide additional insight into potential mechanisms involved in the disease process. Furthermore, we present the first gene expression biomarker for COPD validated in an independent data set.