Blood-based epigenome-wide association study and prediction of alcohol consumption
Abstract Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alc...
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| Format: | Article |
| Language: | English |
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BMC
2025-01-01
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| Series: | Clinical Epigenetics |
| Online Access: | https://doi.org/10.1186/s13148-025-01818-y |
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| author | Elena Bernabeu Aleksandra D. Chybowska Jacob K. Kresovich Matthew Suderman Daniel L. McCartney Robert F. Hillary Janie Corley Maria Del C. Valdés-Hernández Susana Muñoz Maniega Mark E. Bastin Joanna M. Wardlaw Zongli Xu Dale P. Sandler Archie Campbell Sarah E. Harris Andrew M. McIntosh Jack A. Taylor Paul Yousefi Simon R. Cox Kathryn L. Evans Matthew R. Robinson Catalina A. Vallejos Riccardo E. Marioni |
| author_facet | Elena Bernabeu Aleksandra D. Chybowska Jacob K. Kresovich Matthew Suderman Daniel L. McCartney Robert F. Hillary Janie Corley Maria Del C. Valdés-Hernández Susana Muñoz Maniega Mark E. Bastin Joanna M. Wardlaw Zongli Xu Dale P. Sandler Archie Campbell Sarah E. Harris Andrew M. McIntosh Jack A. Taylor Paul Yousefi Simon R. Cox Kathryn L. Evans Matthew R. Robinson Catalina A. Vallejos Riccardo E. Marioni |
| author_sort | Elena Bernabeu |
| collection | DOAJ |
| description | Abstract Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait. Here, we explore the epigenetic architecture of self-reported weekly units of alcohol consumption in the Generation Scotland study. We first create a blood-based epigenetic score (EpiScore) of alcohol consumption using elastic net penalized linear regression. We explore the effect of pre-filtering for CpG features ahead of elastic net, as well as differential patterns by sex and by units consumed in the last week relative to an average week. The final EpiScore was trained on 16,717 individuals and tested in four external cohorts: the Lothian Birth Cohorts (LBC) of 1921 and 1936, the Sister Study, and the Avon Longitudinal Study of Parents and Children (total N across studies > 10,000). The maximum Pearson correlation between the EpiScore and self-reported alcohol consumption within cohort ranged from 0.41 to 0.53. In LBC1936, higher EpiScore levels had significant associations with poorer global brain imaging metrics, whereas self-reported alcohol consumption did not. Finally, we identified two novel CpG loci via a Bayesian penalized regression epigenome-wide association study of alcohol consumption. Together, these findings show how DNAm can objectively characterize patterns of alcohol consumption that associate with brain health, unlike self-reported estimates. |
| format | Article |
| id | doaj-art-ab3fa901d5b448ea9da2f20308538ac7 |
| institution | Kabale University |
| issn | 1868-7083 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Clinical Epigenetics |
| spelling | doaj-art-ab3fa901d5b448ea9da2f20308538ac72025-01-26T12:39:11ZengBMCClinical Epigenetics1868-70832025-01-0117111410.1186/s13148-025-01818-yBlood-based epigenome-wide association study and prediction of alcohol consumptionElena Bernabeu0Aleksandra D. Chybowska1Jacob K. Kresovich2Matthew Suderman3Daniel L. McCartney4Robert F. Hillary5Janie Corley6Maria Del C. Valdés-Hernández7Susana Muñoz Maniega8Mark E. Bastin9Joanna M. Wardlaw10Zongli Xu11Dale P. Sandler12Archie Campbell13Sarah E. Harris14Andrew M. McIntosh15Jack A. Taylor16Paul Yousefi17Simon R. Cox18Kathryn L. Evans19Matthew R. Robinson20Catalina A. Vallejos21Riccardo E. Marioni22Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghDepartment of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research InstituteMedical Research Council Integrative Epidemiology Unit, University of BristolCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghLothian Birth Cohorts, Department of Psychology, University of EdinburghLothian Birth Cohorts, Department of Psychology, University of EdinburghLothian Birth Cohorts, Department of Psychology, University of EdinburghLothian Birth Cohorts, Department of Psychology, University of EdinburghEdinburgh Medical School, Usher Institute, University of EdinburghEpidemiology Branch, National Institute of Environmental Health SciencesEpidemiology Branch, National Institute of Environmental Health SciencesCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghLothian Birth Cohorts, Department of Psychology, University of EdinburghDivision of Psychiatry, Royal Edinburgh Hospital, University of EdinburghNeurovascular Imaging Research Core, UCLAMedical Research Council Integrative Epidemiology Unit, University of BristolLothian Birth Cohorts, Department of Psychology, University of EdinburghCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghInstitute of Science and Technology AustriaMedical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of EdinburghCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of EdinburghAbstract Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait. Here, we explore the epigenetic architecture of self-reported weekly units of alcohol consumption in the Generation Scotland study. We first create a blood-based epigenetic score (EpiScore) of alcohol consumption using elastic net penalized linear regression. We explore the effect of pre-filtering for CpG features ahead of elastic net, as well as differential patterns by sex and by units consumed in the last week relative to an average week. The final EpiScore was trained on 16,717 individuals and tested in four external cohorts: the Lothian Birth Cohorts (LBC) of 1921 and 1936, the Sister Study, and the Avon Longitudinal Study of Parents and Children (total N across studies > 10,000). The maximum Pearson correlation between the EpiScore and self-reported alcohol consumption within cohort ranged from 0.41 to 0.53. In LBC1936, higher EpiScore levels had significant associations with poorer global brain imaging metrics, whereas self-reported alcohol consumption did not. Finally, we identified two novel CpG loci via a Bayesian penalized regression epigenome-wide association study of alcohol consumption. Together, these findings show how DNAm can objectively characterize patterns of alcohol consumption that associate with brain health, unlike self-reported estimates.https://doi.org/10.1186/s13148-025-01818-y |
| spellingShingle | Elena Bernabeu Aleksandra D. Chybowska Jacob K. Kresovich Matthew Suderman Daniel L. McCartney Robert F. Hillary Janie Corley Maria Del C. Valdés-Hernández Susana Muñoz Maniega Mark E. Bastin Joanna M. Wardlaw Zongli Xu Dale P. Sandler Archie Campbell Sarah E. Harris Andrew M. McIntosh Jack A. Taylor Paul Yousefi Simon R. Cox Kathryn L. Evans Matthew R. Robinson Catalina A. Vallejos Riccardo E. Marioni Blood-based epigenome-wide association study and prediction of alcohol consumption Clinical Epigenetics |
| title | Blood-based epigenome-wide association study and prediction of alcohol consumption |
| title_full | Blood-based epigenome-wide association study and prediction of alcohol consumption |
| title_fullStr | Blood-based epigenome-wide association study and prediction of alcohol consumption |
| title_full_unstemmed | Blood-based epigenome-wide association study and prediction of alcohol consumption |
| title_short | Blood-based epigenome-wide association study and prediction of alcohol consumption |
| title_sort | blood based epigenome wide association study and prediction of alcohol consumption |
| url | https://doi.org/10.1186/s13148-025-01818-y |
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