DNA methylation has become a biomarker of great interest in the forensic and clinical fields. In criminal investigations, the study of this epigenetic marker has allowed the development of DNA intelligence tools providing information that can be useful for investigators, such as age prediction. Following a similar trend, when the origin of a sample in a criminal scenario is unknown, the inference of an individual’s lifestyle such as tobacco use and alcohol consumption could provide relevant information to help in the identification of DNA donors at the crime scene. At the same time, in the clinical domain, prediction of these trends of consumption could allow the identification of people at risk or better identification of the causes of different pathologies. In the present study, DNA methylation data from the UK AIRWAVE study was used to build two binomial logistic models for the inference of smoking and drinking status. A total of 348 individuals (116 non-smokers, 116 former smokers and 116 smokers) plus a total of 237 individuals (79 non-drinkers, 79 moderate drinkers and 79 drinkers) were used for development of tobacco and alcohol consumption prediction models, respectively. The tobacco prediction model was composed of two CpGs (cg05575921 in and cg01940273) and the alcohol prediction model three CpGs (cg06690548 in , cg0886875 and cg21294714 in ), providing correct classifications of 86.49% and 74.26%, respectively. Validation of the models was performed using leave-one-out cross-validation. Additionally, two independent testing sets were also assessed for tobacco and alcohol consumption. Considering that the consumption of these substances could underlie accelerated epigenetic ageing patterns, the effect of these lifestyles on the prediction of age was evaluated. To do that, a quantile regression model based on previous studies was generated, and the potential effect of tobacco and alcohol consumption with the epigenetic age was assessed. The Wilcoxon test was used to evaluate the residuals generated by the model and no significant differences were observed between the categories analyzed.

中文翻译：

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从血液DNA甲基化分析推断烟酒消费习惯

DNA甲基化已成为法医学和临床领域备受关注的生物标志物。在刑事调查中，对这种表观遗传标记的研究使得 DNA 情报工具的开发成为可能，为调查人员提供有用的信息，例如年龄预测。遵循类似的趋势，当犯罪场景中样本的来源未知时，对个人生活方式（例如吸烟和饮酒）的推断可以提供相关信息，以帮助识别犯罪现场的 DNA 捐献者。与此同时，在临床领域，对这些消费趋势的预测可以识别处于危险中的人或更好地识别不同病理的原因。在本研究中，来自英国 AIRWAVE 研究的 DNA 甲基化数据被用来构建两个二项式逻辑模型来推断吸烟和饮酒状况。总共 348 人（116 名非吸烟者、116 名前吸烟者和 116 名吸烟者）加上总共 237 人（79 名不饮酒者、79 名中度饮酒者和 79 名饮酒者）分别用于开发烟草和酒精消费预测模型。烟草预测模型由两个 CpG（中的 cg05575921 和 cg01940273）组成，酒精预测模型由三个 CpG（中的 cg06690548、中的 cg0886875 和 cg21294714）组成，正确分类率分别为 86.49% 和 74.26%。使用留一法交叉验证对模型进行验证。此外，还评估了两个独立的测试组的烟草和酒精消耗量。考虑到这些物质的消耗可能会加速表观遗传衰老模式，因此评估了这些生活方式对年龄预测的影响。为此，生成了基于先前研究的分位数回归模型，并评估了烟草和酒精消费对表观遗传年龄的潜在影响。 Wilcoxon 检验用于评估模型生成的残差，并且在分析的类别之间没有观察到显着差异。