Bernabeu Elena, Chybowska Aleksandra D, Kresovich Jacob K, Suderman Matthew, McCartney Daniel L, Hillary Robert F, Corley Janie, Valdés-Hernández Maria Del C, Maniega Susana Muñoz, Bastin Mark E, Wardlaw Joanna M, Xu Zongli, Sandler Dale P, Campbell Archie, Harris Sarah E, McIntosh Andrew M, Taylor Jack A, Yousefi Paul, Cox Simon R, Evans Kathryn L, Robinson Matthew R, Vallejos Catalina A, Marioni Riccardo E
Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Clin Epigenetics. 2025 Jan 25;17(1):14. doi: 10.1186/s13148-025-01818-y.
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.
饮酒是多种疾病的重要风险因素。通常通过自我报告来评估饮酒情况，而自我报告容易因回忆偏差产生测量误差。相反，诸如基于血液的DNA甲基化（DNAm）等分子数据可通过纳入已知与该特征相关的胞嘧啶 - 磷酸 - 鸟嘌呤（CpG）位点的信息，来得出更客观的饮酒量测量方法。在此，我们在“苏格兰世代”研究中探索自我报告的每周饮酒量单位的表观遗传结构。我们首先使用弹性网络惩罚线性回归创建基于血液的饮酒表观遗传评分（EpiScore）。我们探讨了在弹性网络之前对CpG特征进行预过滤的效果，以及按性别和相对于平均周数的上周饮酒量划分的差异模式。最终的EpiScore在16717名个体上进行了训练，并在四个外部队列中进行了测试：1921年和1936年的洛锡安出生队列（LBC）、姐妹研究以及雅芳亲子纵向研究（各研究的总样本量N > 10000）。队列内EpiScore与自我报告的饮酒量之间的最大皮尔逊相关系数在0.41至0.53之间。在LBC1936中，较高的EpiScore水平与较差的全脑成像指标显著相关，而自我报告的饮酒量则不然。最后，我们通过饮酒的贝叶斯惩罚回归表观基因组全关联研究确定了两个新的CpG位点。总之，这些发现表明，与自我报告的估计不同，DNAm能够客观地表征与大脑健康相关的饮酒模式。
