A whole blood gene expression-based signature for smoking status

Abstract

BackgroundSmoking 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.MethodsMicroarrays 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.ResultsMicroarray 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).ConclusionWe 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.

The Effect of Different Case Definitions of Current Smoking on the Discovery of Smoking-Related Blood Gene Expression Signatures in Chronic Obstructive Pulmonary Disease

“…The two strongest enrichments were discovered in two studies that reported the effects of smoking on gene expression and methylation profiles. Fifty genes in the study by Charlesworth et al, 29 15 CpG sites corresponding to 14 unique genes in the study by Wan et al, 30 and five genes in the study by Beineke et al 31 showed significant enrichment against the 7366 unique genes pre-ranked by their absolute t-statistics in our gene set from the combined phenotype analysis using FDR q-values of 0.00058, 0.0012 and 0.0385, respectively.…”

“…In lung tissue, Bossé et al reported up-regulation of FUCA1 among smokers. 32 The study of Beineke et al 31 reported up-regulation of LRRN3, PID1, GPR15 and FUCA1 gene expression in the whole blood of current smokers with LRRN3 being the most statistically significant gene. In a recent study by Guida et al, 33 CpG sites at both LRRN3 and GPR15 were found to be hypomethylated in blood.…”

Identification of gene expression signature for cigarette smoke exposure response—from man to mouse

“…Interestingly, the performance of the models based on these six genes in the human samples was only slightly lower than the classification of the human blood samples (correct classification rate BLD-SMK-01 FS ¼ 0.77, QASMC CS ¼ 0.89, QASMC NCS ¼ 0.79; Figure 3 and Table 4). We further retrained a logistic and an LDA model on the same set of genes as Beineke et al 62 While still performing reasonably in cross-validation, the blood signature failed to translate in mice (data not shown).…”

The Expressed Genome in Cardiovascular Diseases and Stroke: Refinement, Diagnosis, and Prediction: A Scientific Statement From the American Heart Association

“…For example, a series of studies using microarray analysis of either unfractionated peripheral blood or purified lymphocytes across the spectrum of tobacco smoke exposure compared with never smokers have identified several genes representing inflammatory pathways that may contribute to CAD. [17][18][19] Those with secondhand smoke exposure could not be distinguished from primary smokers, 17 and neither could recent smokers (quit <2 months previously) be separated from current smokers. 19 However, former smokers (quit >2 months previously) most closely resembled never smokers from the perspective of their gene expression in peripheral blood.…”

“…[17][18][19] Those with secondhand smoke exposure could not be distinguished from primary smokers, 17 and neither could recent smokers (quit <2 months previously) be separated from current smokers. 19 However, former smokers (quit >2 months previously) most closely resembled never smokers from the perspective of their gene expression in peripheral blood. 19 These relationships suggest a dose-response relationship, reinforce the dangers of secondhand smoke exposure, and confirm that smoking cessation is associated with reversible effects on biological pathways that may underlie CAD.…”