Accuracy and utility of an epigenetic biomarker for smoking in populations with varying rates of false self‐report

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.

Genome‐wide and digital polymerase chain reaction epigenetic assessments of alcohol consumption

“…The extent to which this takes place with respect to studies of alcohol consumption is not clearly established. However, for smoking, the potential for high rates of unreliable self‐report have been documented in single investigator and national cohorts have been clearly demonstrated (Andersen et al, ; Caraballo, Sharapova, & Asman, ). Hence, our decision on recruiting case subjects directly from inpatient alcohol treatment centers and biochemically verified substance free controls from low risk settings which generated marker sets that have AUC above 0.95 and account for 67% of the variance seems to have worked well.…”

“…The methylation status of individual CpG residues of interest was determined using a droplet digital PCR (ddPCR) paradigm as previously described (Andersen, Philibert, Gibbons, Simons, & Long, ). In brief, 1 μg of DNA from each subject was bisulfite converted using the Fast 96 Bisulfite Conversion kit (Qiagen, Germany).…”

MTHFR regulatory effects on methylation of CG05575921 in response to smoking: Effects are also discernable using MTHFR expression

“…methylation array data using qPCR has been previously published (Dogan et al, 2014) and ddPCR at CG05575921 has been successfully used to quantify reversion of smoking (Philibert et al, 2015). The reliability of the ddPCR method to quantify cg05575921 methylation was also examined by Andersen, Philibert, Gibbons, Simons, and Long (2017), showing that this approach is reliably associated with smoking status, as confirmed by serum cotinine. In addition, a direct comparison of Epic methylation array assessment of cg05575921 to ddPCR assessment, along with establishment of a normal range with 400 adult subjects is in preparation (Philibert et al, Manuscript in preparation), again showing good correspondence (r 5 .991) across methods.…”

Epigenetics applied to psychiatry: Clinical opportunities and future challenges

“…74 Finally, the generation of a DNA methylation biosignature in blood or © 2018 The Authors Psychiatry and Clinical Neurosciences © 2018 Japanese Society of Psychiatry and Neurology saliva has been shown to improve a suicide-prediction model. 75 Some novel approaches based on multiplex DNA methylation profile, 75 methylation specificquantitative analysis 67 and droplet/digital PCR assay 76 promise new avenues for early, specific, and quantitative detection of phenotype-associated DNA methylation signature in combination with other biomarkers.…”