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Fang F, Andersen AM, Philibert R, Hancock DB. Epigenetic biomarkers for smoking cessation. ADDICTION NEUROSCIENCE 2023; 6:100079. [PMID: 37123087 PMCID: PMC10136056 DOI: 10.1016/j.addicn.2023.100079] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Cigarette smoking has been associated with epigenetic alterations that may be reversible upon cessation. As the most-studied epigenetic modification, DNA methylation is strongly associated with smoking exposure, providing a potential mechanism that links smoking to adverse health outcomes. Here, we reviewed the reversibility of DNA methylation in accessible peripheral tissues, mainly blood, in relation to cigarette smoking cessation and the utility of DNA methylation as a biomarker signature to differentiate current, former, and never smokers and to quantify time since cessation. We summarized thousands of differentially methylated Cytosine-Guanine (CpG) dinucleotides and regions associated with smoking cessation from candidate gene and epigenome-wide association studies, as well as the prediction accuracy of the multi-CpG predictors for smoking status. Overall, there is robust evidence for DNA methylation signature of cigarette smoking cessation. However, there are still gaps to fill, including (1) cell-type heterogeneity in measuring blood DNA methylation; (2) underrepresentation of non-European ancestry populations; (3) limited longitudinal data to quantitatively measure DNA methylation after smoking cessation over time; and (4) limited data to study the impact of smoking cessation on other epigenetic features, noncoding RNAs, and histone modifications. Epigenetic machinery provides promising biomarkers that can improve success in smoking cessation in the clinical setting. To achieve this goal, larger and more-diverse samples with longitudinal measures of a broader spectrum of epigenetic marks will be essential to developing a robust DNA methylation biomarker assay, followed by meeting validation requirements for the assay before being implemented as a clinically useful tool.
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Affiliation(s)
- Fang Fang
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, 3040 East Cornwallis Road, P.O. Box 12194, Research Triangle Park, NC 27709, USA
| | - Allan M. Andersen
- Department of Psychiatry, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA
| | - Robert Philibert
- Department of Psychiatry, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA
- Behavioral Diagnostics LLC, 2500 Crosspark Rd, Coralville, IA 52241, USA
- Department of Biomedical Engineering, 5601 Seamans Center for the Engineering Arts and Sciences, University of Iowa, Iowa City, IA 52242, USA
| | - Dana B. Hancock
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, 3040 East Cornwallis Road, P.O. Box 12194, Research Triangle Park, NC 27709, USA
- Corresponding author. (D.B. Hancock)
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Skov-Jeppesen SM, Kobylecki CJ, Jacobsen KK, Bojesen SE. Changing Smoking Behavior and Epigenetics: A Longitudinal Study of 4,432 Individuals From the General Population. Chest 2023; 163:1565-1575. [PMID: 36621758 PMCID: PMC10258440 DOI: 10.1016/j.chest.2022.12.036] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/07/2022] [Accepted: 12/19/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Hypomethylation of the aryl hydrocarbon receptor repressor (AHRR) gene indicates long-term smoking exposure and might therefore be a monitor for smoking-induced disease risk. However, studies of individual longitudinal changes in AHRR methylation are sparse. RESEARCH QUESTION How does the recovery of AHRR methylation depend on change in smoking behaviors and demographic variables? STUDY DESIGN AND METHODS This study included 4,432 individuals from the Copenhagen City Heart Study, with baseline and follow-up blood samples and smoking information collected approximately 10 years apart. AHRR methylation at the cg05575921 site was measured in bisulfite-treated leukocyte DNA. Four smoking groups were defined: participants who never smoked (Never-Never), participants who formerly smoked (Former-Former), participants who quit during the study period (Current-Former), and individuals who smoked at both baseline and follow-up (Current-Current). Methylation recovery was defined as the increase in AHRR methylation between baseline and follow-up examination. RESULTS Methylation recovery was highest among participants who quit, with a median methylation recovery of 5.58% (interquartile range, 1.79; 9.15) vs 1.64% (interquartile range, -1.88; 4.96) in the Current-Current group (P < .0001). In individuals who quit smoking, older age was associated with lower methylation recovery (P < .0001). In participants who quit aged > 65 years, methylation recovery was 5.9% at 5.6 years after quitting; methylation recovery was 8.5% after 2.8 years for participants who quit aged < 55 years. INTERPRETATION AHRR methylation recovered after individuals quit smoking, and recovery was more pronounced and occurred faster in younger compared with older interim quitters.
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Affiliation(s)
- Sune Moeller Skov-Jeppesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Camilla Jannie Kobylecki
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Katja Kemp Jacobsen
- Department of Technology, Faculty of Health and Technology, University College Copenhagen, Copenhagen, Denmark
| | - Stig Egil Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark; The Copenhagen City Heart Study, Copenhagen University Hospital, Frederiksberg and Bispebjerg Hospital, Copenhagen, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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3
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Vidaki A, Planterose Jiménez B, Poggiali B, Kalamara V, van der Gaag KJ, Maas SCE, Ghanbari M, Sijen T, Kayser M. Targeted DNA methylation analysis and prediction of smoking habits in blood based on massively parallel sequencing. Forensic Sci Int Genet 2023; 65:102878. [PMID: 37116245 DOI: 10.1016/j.fsigen.2023.102878] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 03/28/2023] [Accepted: 04/18/2023] [Indexed: 04/30/2023]
Abstract
Tobacco smoking is a frequent habit sustained by > 1.3 billion people in 2020 and the leading preventable factor for health risk and premature mortality worldwide. In the forensic context, predicting smoking habits from biological samples may allow broadening DNA phenotyping. In this study, we aimed to implement previously published smoking habit classification models based on blood DNA methylation at 13 CpGs. First, we developed a matching lab tool based on bisulfite conversion and multiplex PCR followed by amplification-free library preparation and targeted paired-end massively parallel sequencing (MPS). Analysis of six technical duplicates revealed high reproducibility of methylation measurements (Pearson correlation of 0.983). Artificially methylated standards uncovered marker-specific amplification bias, which we corrected via bi-exponential models. We then applied our MPS tool to 232 blood samples from Europeans of a wide age range, of which 90 were current, 71 former and 71 never smokers. On average, we obtained 189,000 reads/sample and 15,000 reads/CpG, without marker drop-out. Methylation distributions per smoking category roughly corresponded to previous microarray analysis, showcasing large inter-individual variation but with technology-driven bias. Methylation at 11 out of 13 smoking-CpGs correlated with daily cigarettes in current smokers, while solely one was weakly correlated with time since cessation in former smokers. Interestingly, eight smoking-CpGs correlated with age, and one displayed weak but significant sex-associated methylation differences. Using bias-uncorrected MPS data, smoking habits were relatively accurately predicted using both two- (current/non-current) and three- (never/former/current) category model, but bias correction resulted in worse prediction performance for both models. Finally, to account for technology-driven variation, we built new, joint models with inter-technology corrections, which resulted in improved prediction results for both models, with or without PCR bias correction (e.g. MPS cross-validation F1-score > 0.8; 2-categories). Overall, our novel assay takes us one step closer towards the forensic application of viable smoking habit prediction from blood traces. However, future research is needed towards forensically validating the assay, especially in terms of sensitivity. We also need to further shed light on the employed biomarkers, particularly on the mechanistics, tissue specificity and putative confounders of smoking epigenetic signatures.
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Affiliation(s)
- Athina Vidaki
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| | - Benjamin Planterose Jiménez
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Brando Poggiali
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Vivian Kalamara
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | | | - Silvana C E Maas
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Titia Sijen
- Division of Biological Traces, Netherlands Forensic Institute, The Hague, the Netherlands; Swammerdam Institute of Life Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
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Long JD, Gehlsen MP, Moody J, Weeks G, Philibert R. Predictors of Smoking in Older Adults and an Epigenetic Validation of Self-Report. Genes (Basel) 2022; 14:genes14010025. [PMID: 36672765 PMCID: PMC9912258 DOI: 10.3390/genes14010025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/13/2022] [Accepted: 12/19/2022] [Indexed: 12/25/2022] Open
Abstract
There are several established predictors of smoking, but it is unknown if these predictors operate similarly for young and old smokers. We examined clinical data from the National Lung Screening Trial (NLST) to determine the predictive ability of gender, body mass index (BMI), marital status, and race on smoking behavior, with emphasis on gender interactions. In addition, we validated the self-report of smoking behaviors for a subgroup that had available epigenetic data in the form of cg05575921 methylation. Participants were N=9572 current or former smokers from the NLST biofluids database, age 55-74, minimum of 30 pack years, and mostly White. A subgroup of N=3084 who had DNA were used for the self-report validation analysis. The predictor analysis was based on the larger group and used penalized logistic regression to predict the self-report of being a former or current smoker at baseline. Cg05575921 methylation showed a moderate ability to discriminate among former and current smokers, AUC = 0.85 (95% confidence interval = [0.83, 0.86]). The final selected variables for the prediction model were BMI, gender, BMI by gender, age, divorced (vs. married), education, and race. The gender by BMI interaction was such that males had a higher probability of current smoking for lower BMI, but this switched to females having higher current smoking for overweight to obese. There is evidence that the self-reported smoking behavior in NLST is moderately accurate. The results of the primary analysis are consistent with the general smoking literature, and our results provide additional specificity regarding the gender by BMI interaction. Body weight issues might play a role in smoking cessation for older established smokers in a similar manner as younger smokers. It could be that women have less success with cessation when their BMI increases.
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Affiliation(s)
- Jeffrey D. Long
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, IA 52242, USA; (J.D.L.); (J.M.); (G.W.)
- Department of Biostatistics, College of Public Health, University of Iowa, Iowa, IA 52242, USA
| | - Michael P. Gehlsen
- South Saint Paul Public Schools, 104 5th Ave. S, South Saint Paul, MN 55075, USA;
| | - Joanna Moody
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, IA 52242, USA; (J.D.L.); (J.M.); (G.W.)
| | - Gracie Weeks
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, IA 52242, USA; (J.D.L.); (J.M.); (G.W.)
| | - Robert Philibert
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, IA 52242, USA; (J.D.L.); (J.M.); (G.W.)
- Behavioral Diagnostics LLC, 2500 Crosspark Rd., Suite W245, Coralville, IA 53341, USA
- Department of Biomedical Engineering, University of Iowa, Iowa, IA 52242, USA
- Correspondence:
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Philibert R, Dawes K, Moody J, Hoffman R, Sieren J, Long J. Using Cg05575921 methylation to predict lung cancer risk: a potentially bias-free precision epigenetics approach. Epigenetics 2022; 17:2096-2108. [PMID: 35920547 PMCID: PMC9665144 DOI: 10.1080/15592294.2022.2108082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 07/25/2022] [Indexed: 01/25/2023] Open
Abstract
The decision to engage in lung cancer screening (LCS) necessitates weighing benefits versus harms. Previously, clinicians in the United States have used the PLCOM2012 algorithm to guide LCS decision-making. However, that formula contains race and gender-based variables. Previously, using data from a European study, Bojesen and colleagues have suggested that cg05575921 methylation could guide decision-making. To test this hypothesis in a more diverse American population, we examined DNA and clinical data from 3081 subjects from the National Lung Screening Trial (NLST) study. Using survival analysis, we found a simple linear predictor consisting of age, pack-year consumption and cg05575921, to have the best predictive power among several alternatives (AUC = 0.66). Results showed that the highest quartile of risk was more than 2-fold more likely to develop lung cancer than those in the lowest quartile. Race, ethnicity, and gender had no effect on prediction with both cg05575921 and pack years contributing equally (both p < 0.003) to risk prediction. Current smokers had considerably lower methylation than former smokers (46% vs 67%; p < 0.001) with the average methylation of those who quit approaching 80% after 25 years of cessation. Finally, current male smokers had lower mean cg05575921 percentage than female smokers (46% vs 49%; p < 0.001). We conclude that cg05575921 (along with age and pack years) can be used to guide LCS decision-making, and additional studies might focus on how best to use methylation to inform decision-making.
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Affiliation(s)
- Rob Philibert
- Behavioural Diagnostics LLC, Coralville, IA, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Kelsey Dawes
- Behavioural Diagnostics LLC, Coralville, IA, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Joanna Moody
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Richard Hoffman
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
| | - Jessica Sieren
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
- Department of Radiology, University of Iowa, Iowa City, IA, USA
- Department of Biostatistics, University of Iowa, Iowa City, IA, USA
| | - Jeffrey Long
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
- Department of Biostatistics, University of Iowa, Iowa City, IA, USA
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Epigenetic and Proteomic Biomarkers of Elevated Alcohol Use Predict Epigenetic Aging and Cell-Type variation Better Than Self-Report. Genes (Basel) 2022; 13:genes13101888. [PMID: 36292773 PMCID: PMC9601579 DOI: 10.3390/genes13101888] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/12/2022] [Accepted: 10/15/2022] [Indexed: 11/17/2022] Open
Abstract
Excessive alcohol consumption (EAC) has a generally accepted effect on morbidity and mortality, outcomes thought to be reflected in measures of epigenetic aging (EA). As the association of self-reported EAC with EA has not been consistent with these expectations, underscoring the need for readily employable non-self-report tools for accurately assessing and monitoring the contribution of EAC to accelerated EA, newly developed alcohol consumption DNA methylation indices, such as the Alcohol T Score (ATS) and Methyl DetectR (MDR), may be helpful. To test that hypothesis, we used these new indices along with the carbohydrate deficient transferrin (CDT), concurrent as well as past self-reports of EAC, and well-established measures of cigarette smoking to examine the relationship of EAC to both accelerated EA and immune cell counts in a cohort of 437 young Black American adults. We found that MDR, CDT, and ATS were intercorrelated, even after controlling for gender and cotinine effects. Correlations between EA and self-reported EAC were low or non-significant, replicating prior research, whereas correlations with non-self-report indices were significant and more substantial. Comparing non-self-report indices showed that the ATS predicted more than four times as much variance in EA, CDT4 cells and B-cells as for both the MDR and CDT, and better predicted indices of accelerated EA. We conclude that each of the non-self-report indices have differing predictive capacities with respect to key alcohol-related health outcomes, and that the ATS may be particularly useful for clinicians seeking to understand and prevent accelerated EA. The results also underscore the likelihood of substantial underestimates of problematic use when self-report is used and a reduction in correlations with EA and variance in cell-types.
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Migliore L, Coppedè F. Gene-environment interactions in Alzheimer disease: the emerging role of epigenetics. Nat Rev Neurol 2022; 18:643-660. [PMID: 36180553 DOI: 10.1038/s41582-022-00714-w] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/18/2022] [Indexed: 12/15/2022]
Abstract
With the exception of a few monogenic forms, Alzheimer disease (AD) has a complex aetiology that is likely to involve multiple susceptibility genes and environmental factors. The role of environmental factors is difficult to determine and, until a few years ago, the molecular mechanisms underlying gene-environment (G × E) interactions in AD were largely unknown. Here, we review evidence that has emerged over the past two decades to explain how environmental factors, such as diet, lifestyle, alcohol, smoking and pollutants, might interact with the human genome. In particular, we discuss how various environmental AD risk factors can induce epigenetic modifications of key AD-related genes and pathways and consider how epigenetic mechanisms could contribute to the effects of oxidative stress on AD onset. Studies on early-life exposures are helping to uncover critical time windows of sensitivity to epigenetic influences from environmental factors, thereby laying the foundations for future primary preventative approaches. We conclude that epigenetic modifications need to be considered when assessing G × E interactions in AD.
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Affiliation(s)
- Lucia Migliore
- Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy. .,Department of Laboratory Medicine, Pisa University Hospital, Pisa, Italy.
| | - Fabio Coppedè
- Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy
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8
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El-Haddad NW, El Kawak M, El Asmar K, Jabbour ME, Moussa MA, Habib RR, Dhaini HR. AhRR methylation contributes to disease progression in urothelial bladder cancer. Cancer Biomark 2022; 35:167-177. [PMID: 36093686 DOI: 10.3233/cbm-220002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Bladder Cancer (BCa) is the tenth most incidental malignancy worldwide. BCa is mostly attributed to environmental exposure and lifestyle, particularly tobacco smoking. The Aryl Hydrocarbon Receptor Repressor (AhRR) participates in the induction of many enzymes involved in metabolizing carcinogens, including tobacco smoke components. Additionally, studies have shown that smoking demethylates the (AhRR) gene in blood, suggesting AhRR demethylation as a specific serum smoking biomarker. OBJECTIVE This study aimed to validate AhRR demethylation as a smoking biomarker in the target tissue and investigate its contribution to bladder carcinogenesis. METHODS AhRR percent methylation was tested for its association with patient smoking status and oncogenic outcome indicators, particularly p53, RB1, and FGFR3 activating mutations, muscle-invasiveness, and tumor grade, in 180 BCa tissue-based DNA. RESULTS Results showed significantly higher AhRR percent methylation in muscle-invasive compared to non-muscle invasive tumors (42.86% vs. 33.98%; p= 0.011), while lower AhRR methylation was significantly associated with FGFR3 Codon 248 mutant genotype compared to wild-type (28.11% ± 9.44 vs. 37.87% ± 22.53; p= 0.036). All other tested associations were non-statistically significant. CONCLUSIONS Although AhRR methylation did not predict smoking status in BCa tumors, it seems to play a role in carcinogenesis and disease progression. Our findings make a basis for further research.
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Affiliation(s)
- Nataly W El-Haddad
- Department of Environmental Health, American University of Beirut, Beirut, Lebanon
| | - Michelle El Kawak
- Department of Environmental Health, American University of Beirut, Beirut, Lebanon
| | - Khalil El Asmar
- Department of Epidemiology and Population Health, American University of Beirut, Beirut, Lebanon
| | - Michel E Jabbour
- Department of Urology, St George Hospital University Medical Center, Beirut, Lebanon.,Faculty of Medicine, University of Balamand, Beirut, Lebanon
| | - Mohamad A Moussa
- Department of Urology, Lebanese University, Beirut, Lebanon.,Department of Surgery, Division of Urology, Al-Zahraa University Hospital, Beirut, Lebanon
| | - Rima R Habib
- Department of Environmental Health, American University of Beirut, Beirut, Lebanon
| | - Hassan R Dhaini
- Department of Environmental Health, American University of Beirut, Beirut, Lebanon
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Allen JP, Danoff JS, Costello MA, Hunt GL, Hellwig AF, Krol KM, Gregory SG, Giamberardino SN, Sugden K, Connelly JJ. Lifetime marijuana use and epigenetic age acceleration: A 17-year prospective examination. Drug Alcohol Depend 2022; 233:109363. [PMID: 35231715 PMCID: PMC8982677 DOI: 10.1016/j.drugalcdep.2022.109363] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 01/19/2022] [Accepted: 02/15/2022] [Indexed: 12/12/2022]
Abstract
AIMS This study was designed to assess links between lifetime levels of marijuana use and accelerated epigenetic aging. DESIGN Prospective longitudinal study, following participants annually from age 13 to age 30. SETTING AND PARTICIPANTS A community sample of 154 participants recruited from a small city in the Southeastern United States. MEASUREMENTS Participants completed annual assessments of marijuana use from age 13 to age 29 and provided blood samples that yielded two indices of epigenetic aging (DNAmGrimAge and DunedinPoAm) at age 30. Additional covariates examined included history of cigarette smoking, anxiety and depressive symptoms, childhood illness, gender, adolescent-era family income, and racial/ethnic minority status. FINDINGS Lifetime marijuana use predicted accelerated epigenetic aging, with effects remaining even after covarying cell counts, demographic factors and chronological age (β's = 0.32 & 0.27, p's < 0.001, 95% CI's = 0.21-0.43 & 0.16-0.39 for DNAmGrimAge and DunedinPoAm, respectively). Predictions remained after accounting for cigarette smoking (β's = 0.25 & 0.21, respectively, p's < 0.001, 95% CI's = 0.14-0.37 & 0.09-0.32 for DNAmGrimAge and DunedinPoAm, respectively). A dose-response effect was observed and there was also evidence that effects were dependent upon recency of use. Effects of marijuana use appeared to be fully mediated by hypomethylation of a site linked to effects of hydrocarbon inhalation (cg05575921). CONCLUSIONS Marijuana use predicted epigenetic changes linked to accelerated aging, with evidence suggesting that effects may be primarily due to hydrocarbon inhalation among marijuana smokers. Further research is warranted to explore mechanisms underlying this linkage.
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Mather KA. Genetic and Environmental Factors in Ageing and Age-Related Disease. Genes (Basel) 2022; 13:genes13030396. [PMID: 35327950 PMCID: PMC8955976 DOI: 10.3390/genes13030396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 02/17/2022] [Indexed: 11/19/2022] Open
Affiliation(s)
- Karen A Mather
- Centre for Healthy Brain Ageing, Discipline of Psychiatry and Mental Health, Faculty of Medicine, University of New South Wales (UNSW), Sydney, NSW 2031, Australia
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Dawes K, Andersen A, Reimer R, Mills JA, Hoffman E, Long JD, Miller S, Philibert R. The relationship of smoking to cg05575921 methylation in blood and saliva DNA samples from several studies. Sci Rep 2021; 11:21627. [PMID: 34732805 PMCID: PMC8566492 DOI: 10.1038/s41598-021-01088-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/18/2021] [Indexed: 11/23/2022] Open
Abstract
Numerous studies have shown that cg05575921 methylation decreases in response to smoking. However, secondary to methodological issues, the magnitude and dose dependency of that response is as of yet unclear. This lack of certainty is a barrier to the use of DNA methylation clinically to assess and monitor smoking status. To better define this relationship, we conducted a joint analysis of methylation sensitive PCR digital (MSdPCR) assessments of cg05575921 methylation in whole blood and/or saliva DNA to smoking using samples from 421 smokers and 423 biochemically confirmed non-smokers from 4 previously published studies. We found that cg05575921 methylation manifested a curvilinear dose dependent decrease in response to increasing cigarette consumption. In whole blood DNA, the Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) of cg05575921 methylation for predicting daily smoking status was 0.98. In saliva DNA, the gross AUC was 0.91 with correction for cellular heterogeneity improving the AUC to 0.94. Methylation status was significantly associated with the Fagerstrom Test for Nicotine Dependence score, but with significant sampling heterogeneity. We conclude that MSdPCR assessments of cg05575921 methylation are a potentially powerful, clinically implementable tool for the assessment and management of smoking.
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Affiliation(s)
- Kelsey Dawes
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA
- Molecular Medicine Program, University of Iowa, Iowa City, IA, 52242, USA
| | - Allan Andersen
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA
| | - Rachel Reimer
- Department of Public Health, Des Moines University, Des Moines, IA, 50312, USA
| | - James A Mills
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA
| | - Eric Hoffman
- Department of Radiology, University of Iowa, Iowa City, IA, 52242, USA
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, 52242, USA
| | - Jeffrey D Long
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA
- Department of Biostatistics, University of Iowa, Iowa City, IA, 52242, USA
| | - Shelly Miller
- Behavioral Diagnostics LLC, Coralville, IA, 52241, USA
| | - Robert Philibert
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA.
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, 52242, USA.
- Behavioral Diagnostics LLC, Coralville, IA, 52241, USA.
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12
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Dawes K, Sampson L, Reimer R, Miller S, Philibert R, Andersen A. Epigenetic Analyses of Alcohol Consumption in Combustible and Non-Combustible Nicotine Product Users. EPIGENOMES 2021; 5:epigenomes5030018. [PMID: 34968367 PMCID: PMC8594674 DOI: 10.3390/epigenomes5030018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 08/18/2021] [Accepted: 08/30/2021] [Indexed: 11/16/2022] Open
Abstract
Alcohol and tobacco use are highly comorbid and exacerbate the associated morbidity and mortality of either substance alone. However, the relationship of alcohol consumption to the various forms of nicotine-containing products is not well understood. To improve this understanding, we examined the relationship of alcohol consumption to nicotine product use using self-report, cotinine, and two epigenetic biomarkers specific for smoking (cg05575921) and drinking (Alcohol T Scores (ATS)) in n = 424 subjects. Cigarette users had significantly higher ATS values than the other groups (p < 2.2 × 10−16). Using the objective biomarkers, the intensity of nicotine and alcohol consumption was correlated in both the cigarette and smokeless users (R = −0.66, p = 3.1 × 10−14; R2 = 0.61, p = 1.97 × 10−4). Building upon this idea, we used the objective nicotine biomarkers and age to build and test a Balanced Random Forest classification model for heavy alcohol consumption (ATS > 2.35). The model performed well with an AUC of 0.962, 89.3% sensitivity, and 85% specificity. We conclude that those who use non-combustible nicotine products drink significantly less than smokers, and cigarette and smokeless users drink more with heavier nicotine use. These findings further highlight the lack of informativeness of self-reported alcohol consumption and suggest given the public and private health burden of alcoholism, further research into whether using non-combustible nicotine products as a mode of treatment for dual users should be considered.
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Affiliation(s)
- Kelsey Dawes
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (L.S.); (R.P.); (A.A.)
- Behavioral Diagnostics LLC, Coralville, IA 52241, USA;
- Correspondence: ; Tel.: +1-319-361-2081
| | - Luke Sampson
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (L.S.); (R.P.); (A.A.)
| | - Rachel Reimer
- College of Public Health, Des Moines University, Des Moines, IA 50312, USA;
| | - Shelly Miller
- Behavioral Diagnostics LLC, Coralville, IA 52241, USA;
| | - Robert Philibert
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (L.S.); (R.P.); (A.A.)
- Behavioral Diagnostics LLC, Coralville, IA 52241, USA;
| | - Allan Andersen
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (L.S.); (R.P.); (A.A.)
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The Reversion of DNA Methylation at Coronary Heart Disease Risk Loci in Response to Prevention Therapy. Processes (Basel) 2021. [DOI: 10.3390/pr9040699] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Coronary heart disease (CHD) is preventable, but the methods for assessing risk and monitoring response rely on imprecise lipid-based assessments. Recently, we have shown that an integrated genetic–epigenetic test that includes three methylation-sensitive digital PCR assays predicts 3-year risk for incident CHD better than lipid-based methods. However, whether methylation sites change in response to therapies that alter CHD risk is not known. Therefore, we assessed methylation at these three incident CHD-related sites in DNA from 39 subjects before and after three months of biochemically verified smoking cessation, then analyzed the relationship between change in methylation at each of the sites to the change in smoking intensity as assessed by cg05575921 methylation. We found that, in those who quit smoking, methylation change at one CHD risk marker (cg00300879) was significantly associated with change in cg05575921 methylation (p < 0.04). We conclude that changes in incident CHD-related methylation occur within three months of cessation of smoking, a major risk factor for CHD. This suggests that the effectiveness of treatment of other CHD risk factors, such as high cholesterol, may be similarly quantifiable using epigenetic approaches. Further studies to determine the relationship of changes of methylation status in response to treatment of other CHD risk factors are indicated.
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