RT Journal Article
T1 Inference of tobacco and alcohol consumption habits from DNA methylation analysis of blood
A1 Ambroa Conde, Adrián
A1 Casares de Cal, María de los Ángeles
A1 Gómez Tato, Antonio
A1 Robinson, Oliver
A1 Mosquera Miguel, Ana
A1 Puente Vila, María del Carmen de la
A1 Ruiz Ramírez, Jorge
A1 Phillips, Christopher Paul
A1 Lareu Huidobro, María Victoria
A1 Freire Aradas, Ana María
K1 DNA methylation
K1 Logistic regression
K1 Quantile regression
K1 Blood
K1 Tobacco
K1 Alcohol
K1 Age estimation
AB 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 AHRR and cg01940273) and the alcohol prediction model three CpGs (cg06690548 in SLC7A11, cg0886875 and cg21294714 in MIR4435–2HG), 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
PB Elsevier
SN 1872-4973
YR 2024
FD 2024
LK http://hdl.handle.net/10347/33760
UL http://hdl.handle.net/10347/33760
LA eng
NO Forensic Science International: Genetics, Volume 70, 2024, 103022
NO MVL is supported by the Ministerio de Educación, Cultura y Ciencia, Spain (PID2019-107876RB-I00). MdlP is supported by a postdoctoral fellowship awarded by the Gobierno de España: IJC2020-042638-I, funded by MCIN/AEI/10.13039/501100011033 and the European Union "NextGenerationEU/PRTR". J.R. is supported by the “Programa de axudas á etapa predoutoral” funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (ED481A-2020/039). The Airwave Health Monitoring Study is funded by the Medical Research Council (MRC), (MR/R023484/1), the National Institute for Health Care Research (NIHR) Health Protection Research Unit in Chemical and Radiation Threats and Hazards (NIHR-200922), the Imperial College Biomedical Research Centre (BRC) 2017–22, and the Imperial College Healthcare NHS Trust. The initial phase of the study, including participant recruitment, was funded by the Home Office (780-TETRA; 2003-18). Views expressed are those of the authors and not necessarily those of the study sponsors. We thank all study participants for their involvement. DPUK provided data access for this project: Elliott, P. (2017). Airwave [Data set]. Dementias Platform UK. https://doi.org/10.48532/002000 through MRC grant ref MR/L023784/2″ (core funding)
DS Minerva
RD 23 abr 2026