Abstract

Recent advances in genome-wide DNA methylation (DNAm) profiling for smoking behaviour have given rise to a new, molecular biomarker of smoking exposure. It is unclear whether a smoking-associated DNAm (epigenetic) score has predictive value for ageing-related health outcomes which is independent of contributions from self-reported (phenotypic) smoking measures. Blood DNA methylation levels were measured in 895 adults aged 70 years in the Lothian Birth Cohort 1936 (LBC1936) study using the Illumina 450K assay. A DNA methylation score based on 230 CpGs was used as a proxy for smoking exposure. Associations between smoking variables and health outcomes at age 70 were modelled using general linear modelling (ANCOVA) and logistic regression. Additional analyses of smoking with brain MRI measures at age 73 (n = 532) were performed. Smoking-DNAm scores were positively associated with self-reported smoking status (P < 0.001, eta-squared ɳ2 = 0.63) and smoking pack years (r = 0.69, P < 0.001). Higher smoking DNAm scores were associated with variables related to poorer cognitive function, structural brain integrity, physical health, and psychosocial health. Compared with phenotypic smoking, the methylation marker provided stronger associations with all of the cognitive function scores, especially visuospatial ability (P < 0.001, partial eta-squared ɳp2 = 0.022) and processing speed (P < 0.001, ɳp2 = 0.030); inflammatory markers (all P < 0.001, ranges from ɳp2 = 0.021 to 0.030); dietary patterns (healthy diet (P < 0.001, ɳp2 = 0.052) and traditional diet (P < 0.001, ɳp2 = 0.032); stroke (P = 0.006, OR 1.48, 95% CI 1.12, 1.96); mortality (P < 0.001, OR 1.59, 95% CI 1.42, 1.79), and at age 73; with MRI volumetric measures (all P < 0.001, ranges from ɳp2 = 0.030 to 0.052). Additionally, education was the most important life-course predictor of lifetime smoking tested. Our results suggest that a smoking-associated methylation biomarker typically explains a greater proportion of the variance in some smoking-related morbidities in older adults, than phenotypic measures of smoking exposure, with some of the accounted-for variance being independent of phenotypic smoking status.

Highlights

  • Smoking is an exposure with broad and wellcharacterised adverse health effects

  • Associations between smoking variables Higher scores on the smoking-DNA methylation (DNAm) marker were strongly associated with higher self-reported smoking exposure

  • There was a significant association between DNAm and self-reported smoking status (F(2,892) = 764.03, P < 0.001, ɳ2 = 0.63)

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Summary

Introduction

Smoking is an exposure with broad and wellcharacterised adverse health effects. Smoking-associated death and disability remains a major global public health problem[1,2]. Understanding the mechanisms by which smoking predisposes individuals to chronic disease is crucial for the provision of therapeutic targets[3,4], yet they are not well understood. (DNAm) has been proposed as one possible partial explanation, which could mean that these changes could act as a biomarker of smoking exposure. Analyses are usually dependent on self-report data, such as smoking status and pack years, which are prone to underestimation and reporting biases[5]. A metabolite of nicotine, is a widely used biomarker, but due to a half-life of around 15–20 h, it reflects only short-term exposure to smoke[6]

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