Accuracy and utility of an epigenetic biomarker for smoking in populations with varying rates of false self‐report. Issue 6 (14th June 2017)

• Record Type: Journal Article
• Authors: Andersen, Allan M.; Philibert, Robert A.; Gibbons, Fredrick X.; Simons, Ronald L.; Long, Jeffrey
• Other Names: Philibert Robert guestEditor.; Glatt Stephen J. guestEditor.
• Is Part Of: American journal of medical genetics. Volume 174:Issue 6(2017)
• Page Start: 641
• Page End: 650
• Publication Date: 2017-06-14
• Subjects: addiction -- biomarkers -- epigenetics -- substance use disorders -- tobacco; Neuropsychiatry -- Periodicals; Medical genetics -- Periodicals; 616.8904205
• DOI: 10.1002/ajmg.b.32555
• Languages: English
• ISSNs: 1552-4841

Abstract

Abstract : Better biomarkers to detect smoking are needed given the tremendous public health burden caused by smoking. Current biomarkers to detect smoking have significant limitations, notably a short half‐life for detection and lack of sensitivity for light smokers. These limitations may be particularly problematic in populations with less accurate self‐reporting. Prior epigenome‐wide association studies indicate that methylation status at cg05575921, a CpG residue located in the aryl hydrocarbon receptor repressor (AHRR) gene, may be a robust indicator of smoking status in individuals with as little as half of a pack‐year of smoking. In this study, we show that a novel droplet digital PCR assay for measuring methylation at cg05575921 can reliably detect smoking status, as confirmed by serum cotinine, in populations with different demographic characteristics, smoking histories, and rates of false‐negative self‐report of smoking behavior. Using logistic regression models, we show that obtaining maximum accuracy in predicting smoking status depends on appropriately weighting self‐report and cg05575921 methylation according to the characteristics of the sample being tested. Furthermore, models using only cg05575921 methylation to predict smoking perform nearly as well as those also including self‐report across populations. In conclusion, cg05575921 has significant potential as a clinical biomarker to detect smoking in populations with varying rates of accuracy in self‐report of smoking behavior.