CardioDx, Inc., 2500 Faber Place, Palo Alto, CA 94303, USA.
BMC Med Genomics. 2012 Dec 3;5:58. doi: 10.1186/1755-8794-5-58.
Smoking is the leading cause of preventable death worldwide and has been shown to increase the risk of multiple diseases including coronary artery disease (CAD). We sought to identify genes whose levels of expression in whole blood correlate with self-reported smoking status.
Microarrays were used to identify gene expression changes in whole blood which correlated with self-reported smoking status; a set of significant genes from the microarray analysis were validated by qRT-PCR in an independent set of subjects. Stepwise forward logistic regression was performed using the qRT-PCR data to create a predictive model whose performance was validated in an independent set of subjects and compared to cotinine, a nicotine metabolite.
Microarray analysis of whole blood RNA from 209 PREDICT subjects (41 current smokers, 4 quit ≤ 2 months, 64 quit > 2 months, 100 never smoked; NCT00500617) identified 4214 genes significantly correlated with self-reported smoking status. qRT-PCR was performed on 1,071 PREDICT subjects across 256 microarray genes significantly correlated with smoking or CAD. A five gene (CLDND1, LRRN3, MUC1, GOPC, LEF1) predictive model, derived from the qRT-PCR data using stepwise forward logistic regression, had a cross-validated mean AUC of 0.93 (sensitivity=0.78; specificity=0.95), and was validated using 180 independent PREDICT subjects (AUC=0.82, CI 0.69-0.94; sensitivity=0.63; specificity=0.94). Plasma from the 180 validation subjects was used to assess levels of cotinine; a model using a threshold of 10 ng/ml cotinine resulted in an AUC of 0.89 (CI 0.81-0.97; sensitivity=0.81; specificity=0.97; kappa with expression model = 0.53).
We have constructed and validated a whole blood gene expression score for the evaluation of smoking status, demonstrating that clinical and environmental factors contributing to cardiovascular disease risk can be assessed by gene expression.
吸烟是全球可预防死亡的主要原因，并且已被证明会增加多种疾病的风险，包括冠心病（CAD）。我们试图确定在全血中表达水平与自我报告的吸烟状况相关的基因。
使用微阵列鉴定与自我报告的吸烟状况相关的全血基因表达变化；从微阵列分析中选择一组重要的基因，通过 qRT-PCR 在一组独立的受试者中进行验证。使用 qRT-PCR 数据进行逐步向前逻辑回归，以创建一个预测模型，该模型在一组独立的受试者中进行验证，并与尼古丁代谢物可替宁进行比较。
对 209 名 PREDICT 受试者（41 名当前吸烟者，4 名戒烟≤2 个月，64 名戒烟>2 个月，100 名从不吸烟者；NCT00500617）的全血 RNA 进行微阵列分析，鉴定出 4214 个与自我报告的吸烟状况显著相关的基因。在与吸烟或 CAD 显著相关的 256 个微阵列基因中，对 1071 名 PREDICT 受试者进行了 qRT-PCR。使用逐步向前逻辑回归从 qRT-PCR 数据中得出的五个基因（CLDND1、LRRN3、MUC1、GOPC、LEF1）预测模型的交叉验证平均 AUC 为 0.93（敏感性=0.78；特异性=0.95），并使用 180 名独立的 PREDICT 受试者进行了验证（AUC=0.82，CI 0.69-0.94；敏感性=0.63；特异性=0.94）。来自 180 名验证受试者的血浆用于评估可替宁水平；使用可替宁 10ng/ml 阈值的模型导致 AUC 为 0.89（CI 0.81-0.97；敏感性=0.81；特异性=0.97；与表达模型的kappa=0.53）。
我们已经构建并验证了一种用于评估吸烟状况的全血基因表达评分，证明了可以通过基因表达评估导致心血管疾病风险的临床和环境因素。
