Predicting risk of lung function impairment and all-cause mortality using a DNA methylation-based classifier of tobacco smoke exposure. (August 2022)

• Record Type: Journal Article
• Authors: Eckhardt, Christina M.; Wu, Haotian; Prada, Diddier; Vokonas, Pantel S.; Sparrow, David; Hou, Lifang; Schwartz, Joel; Baccarelli, Andrea A.
• Is Part Of: Respiratory medicine. Volume 200(2022)
• Publication Date: 2022-08
• Subjects: Smoking -- DNA Methylation -- Lung function -- All-cause mortality; Chest -- Diseases -- Periodicals; Chest -- Diseases -- Great Britain -- Periodicals; Respiratory organs -- Diseases -- Periodicals; Respiratory Tract Diseases -- Periodicals; Appareil respiratoire -- Maladies -- Périodiques; Thorax -- Maladies -- Périodiques; Appareil respiratoire -- Maladies -- Traitement -- Périodiques; Electronic journals; 616.2
• DOI: 10.1016/j.rmed.2022.106896
• Languages: English
• ISSNs: 0954-6111

Abstract

Abstract: Background: The Epigenetic Smoking Status Estimator (EpiSmokEr) predicts smoking phenotypes based on DNA methylation at 121 CpG sites. Objective: Evaluate associations of EpiSmokEr-predicted versus self-reported smoking phenotypes with lung function and all-cause mortality in a cohort of older adults. Methods: The prospective Normative Aging Study collected DNA methylation measurements from 1999 to 2012 with follow-up through 2016. The R package EpiSmokEr derived predicted smoking phenotypes based on DNA methylation levels assayed by the Illumina HumanMethylation450 Beadchip. Spirometry was collected every 3–5 years. Airflow limitation was defined as forced expiratory volume in 1 s/forced vital capacity <0.7. Vital status was monitored through periodic mailings. Results: Among 784 participants contributing 5414 person-years of follow-up, the EpiSmokEr-predicted smoking phenotypes matched the self-reported phenotypes for 228 (97%) never smokers and 22 (71%) current smokers. In contrast, EpiSmokEr classified 407 (79%) self-reported former smokers as never smokers. Nonetheless, the EpiSmokEr-predicted former smoking phenotype was more strongly associated with incident airflow limitation (hazard ratio [HR] = 3.15, 95% confidence interval [CI] = 1.50–6.59) and mortality (HR = 2.11, 95% CI = 1.56–2.85) compared to the self-reported former smoking phenotype (airflow limitation: HR = 2.21, 95% CI = 1.13–4.33; mortality: HR = 1.08, 95% CI = 0.86–1.36). Risk of airflow limitation and death did not differ among self-reported never smokers and former smokers who were classified as never smokers. The discriminative accuracy of EpiSmokEr-predicted phenotypes for incident airflow limitation and mortality was improved compared to self-reported phenotypes. Conclusions: The DNA methylation-based EpiSmokEr classifier may be a useful surrogate of smoking-induced lung damage and may identify former smokers most at risk of adverse smoking-related health effects. Graphical abstract: Image 1 Highlights: The EpiSmokEr classifier predicts smoking status based on DNA methylation at 121 CpG sites. EpiSmokEr effectively identified former smokers with increased risk of lung disease and death. EpiSmokEr may identify former smokers most at risk of adverse smoking-related health effects.