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Publication - Dr Matthew Suderman

    Validation and characterization of a DNA methylation alcohol biomarker across the life course

    Citation

    Yousefi, PD, Richmond, RC, Langdon, RJ, Ness, AR, Liu, C, Levy, D, Relton, CL, Suderman, MJ & Zuccolo, L, 2019, ‘Validation and characterization of a DNA methylation alcohol biomarker across the life course’. Clinical Epigenetics.

    Abstract

    Background:
    Recently, an alcohol predictor was developed using DNA methylation at 144 CpG sites (DNAm-Alc) as a biomarker for improved clinical or epidemiologic assessment of alcohol-related ill health. We validate the performance and characterize the drivers of this DNAm-Alc for the first time in independent populations.

    Results:
    In N=1,049 parents from the Avon Longitudinal Study of Parents and Children (ALSPAC) Accessible Resource for Integrated Epigenomic Studies (ARIES) at midlife, we found DNAm-Alc explained 7.6% of the variation in alcohol intake, roughly half of what had been reported previously, and interestingly explained a larger 9.8% of AUDIT score, a scale of alcohol use disorder. Explanatory capacity in participants from the offspring generation of ARIES measured during adolescence was much lower. However, DNAm-Alc explained 14.3% of the variation in replication using the Head and Neck 5000 (HN5000) clinical cohort that had higher average alcohol consumption. To investigate whether this relationship was being driven by genetic and/or earlier environment confounding we examined how earlier vs. concurrent DNAm-Alc measures predicted AUDIT scores. In both ARIES parental and offspring generations, we observed associations between AUDIT and concurrent, but not earlier DNAm-Alc, suggesting independence from genetic and stable environmental contributions.

    Conclusions:
    The stronger relationship between DNAm-Alcs and AUDIT in parents at midlife compared to adolescents despite similar levels of consumption suggests that DNAm-Alc likely reflects long-term patterns of alcohol abuse. Such biomarkers may have potential applications for biomonitoring and risk prediction, especially in cases where reporting bias is a concern.

    Full details in the University publications repository