461
Views
3
CrossRef citations to date
0
Altmetric
Research Paper

Digital methylation assessments of alcohol and cigarette consumption account for common variance in accelerated epigenetic ageing

, , , , & ORCID Icon
Pages 1991-2005 | Received 12 Apr 2022, Accepted 07 Jul 2022, Published online: 22 Jul 2022

References

  • Fraga MF, Ballestar E, Paz MF, et al. Epigenetic differences arise during the lifetime of monozygotic twins. Proc Natl Acad Sci U S A. 2005;102:10604–10609.
  • Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14:3156.
  • Hannum G, Guinney J, Zhao L, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013;49:359–367.
  • Oblak L, van der Zaag J, Higgins-Chen AT, et al. A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration. Ageing Res Rev. 2021;69:101348.
  • Dupras C, Beauchamp E, Joly Y. Selling direct-to-consumer epigenetic tests: are we ready? Nat Rev Genet. 2020;21:335–336.
  • Mendelson MM. Epigenetic age acceleration: a biological doomsday clock for cardiovascular disease? Circ Genom Precis Med. 2018;11:e002089–e002089.
  • Sarno F, Benincasa G, List M, et al. Clinical epigenetics settings for cancer and cardiovascular diseases: real-life applications of network medicine at the bedside. Clin Epigenetics. 2021;13:66.
  • Centers for Disease Control and Prevention. Smoking-attributable mortality, years of potential life lost, and productivity losses – United States, 2000-2004. MMWR Morb Mortal Wkly Rep. 2008;57:1226–1228.
  • Mokdad AH, Marks JS, Stroup DF, et al. Actual causes of death in the United States. Jama. 2000;291(2004):1238–1245.
  • Kanny D, Brewer RD, Mesnick JB, et al. Vital signs: alcohol poisoning deaths—United States, 2010–2012. MMWR Morb Mortal Wkly Rep. 2015;63:1238.
  • US Department of Health Human Services. The health consequences of smoking—50 years of progress: a report of the surgeon general. (Atlanta, GA: US Department of Health and Human Services, Centers for Disease, 2014).
  • Zimmer DM. The accuracy of self-reported smoking among blacks. Rev Black Political Econ. 2018;45:166–180.
  • Esser MB, Sherk A, Liu Y, et al. Deaths and years of potential life lost from excessive alcohol use—United States, 2011–2015. Morbidity Mortality Weekly Rep. 2020;69:981.
  • Tsao CW, Vasan RS. Cohort profile: the Framingham Heart Study (FHS): overview of milestones in cardiovascular epidemiology. Int J Epidemiol. 2015;44:1800–1813.
  • Philibert RA, Dogan MV, Mills JA, et al. AHRR methylation is a significant predictor of mortality risk in Framingham Heart Study. J Insur Med. 2019;48(1):79–89.
  • Konen JC, Summerson JH, Bell RA, et al. Racial differences in symptoms and complications in adults with type 2 diabetes mellitus. Ethn Health. 1999;4:39–49.
  • Centers for Disease Control and Prevention. National diabetes fact sheet: national estimates and general information in diabetes and prediabetes in the United States. Atlanta GA: U.S. Department of Health and Human Services, Centeres for Disease Control and Prevention; 2011.
  • Gouin JP, Glaser R, Malarkey WB, et al. Chronic stress, daily stressors, and circulating inflammatory markers. Health Psychol. 2012;31:264–268.
  • Black PH. The inflammatory response is an integral part of the stress response: implications for atherosclerosis, insulin resistance, type II diabetes and metabolic syndrome X. Brain Behav Immunol. 2003;17:350–364.
  • Andersen AM, Philibert RA, Gibbons FX, et al. Accuracy and utility of an epigenetic biomarker for smoking in populations with varying rates of false self‐report. Am J Med Genet B Neuropsychiatr Genet. 2017;174:641–650.
  • Kandel DB, Schaffran C, Griesler P, et al. Salivary cotinine concentration versus self-reported cigarette smoking: three patterns of inconsistency in adolescence. Nicotine Tob Res. 2006;8:525–537.
  • Philibert R, Miller S, Noel A, et al. A four marker digital PCR toolkit for detecting heavy alcohol consumption and the effectiveness of its treatment. J Insur Med. 2019;48:90–102.
  • Miller S, Mills JA, Long J, et al. A comparison of the predictive power of DNA methylation with carbohydrate deficient transferrin for heavy alcohol consumption. Epigenetics. 2020;16(9):969–979.
  • Philibert R, Levin M, Privett M. Alcohol use, epigenetics & life insurance: quantifying the risk. On the Risk. 2021;37:72–77.
  • Philibert R, Dogan M, Noel A, et al. Dose response and prediction characteristics of a methylation sensitive digital PCR assay for cigarette consumption in adults. Front Genet. 2018;9. DOI:10.3389/fgene.2018.00137.
  • Philibert R, Dogan M, Beach SRH, et al. AHRR methylation predicts smoking status and smoking intensity in both saliva and blood DNA. Am J of Genet. 2019;183:51–60.
  • Dawes K, Andersen A, Reimer R, et al. The relationship of smoking to cg05575921 methylation in blood and saliva DNA samples from several studies. Sci Rep. 2021;11:21627.
  • Philibert R, Hollenbeck N, Andersen E, et al. A quantitative epigenetic approach for the assessment of cigarette consumption. Front Psychol. 2015;6. DOI:10.3389/fpsyg.2015.00656.
  • Andersen A, Reimer R, Dawes K, et al. DNA methylation differentiates smoking from vaping and non-combustible tobacco use. Epigenetics. 2021;17:1–13.
  • Besingi W, Johansson Å. Smoke related DNA methylation changes in the etiology of human disease. Hum Mol Genet. 2013;23(9):2290–2297.
  • Bortolotti F, Sorio D, Bertaso A, et al. Analytical and diagnostic aspects of carbohydrate deficient transferrin (CDT): a critical review over years 2007–2017. J Pharm Biomed Anal. 2018;147:2–12.
  • Pinheiro L, Emslie KR. Basic concepts and validation of digital PCR measurements. In: Karlin-Neumann G, Bizouarn F, editors. Digital PCR: methods and protocols. New York NY: Springer; 2018. p. 11–24.
  • Heiss JA, Just AC. Identifying mislabeled and contaminated DNA methylation microarray data: an extended quality control toolset with examples from GEO. Clin Epigenetics. 2018;10:73.
  • Ori A, Lu A, and Horvath S, et al. A systematic evaluation of 41 DNA methylation predictors across 101 data preprocessing and normalization strategies highlights considerable variation in algorithm performance. bioRxiv. 2021. https://www.biorxiv.org/content/10.1101/2021.09.29.462387v1
  • Kruppa J, Sieg M, Richter G, et al. Estimands in epigenome-wide association studies. Clin Epigenetics. 2021;13:98.
  • Brody GH, Ge X, Kim SY, et al. Neighborhood disadvantage moderates associations of parenting and older sibling problem attitudes and behavior with conduct disorders in African American children. J Consult Clin Psychol. 2003;71:211–222.
  • Philibert R, Penaluna B, White T, et al. A pilot examination of the genome-wide DNA methylation signatures of subjects entering and exiting short-term alcohol dependence treatment programs. Epigenetics. 2014;9:1212–1219.
  • Davis S, Bilke S. An Introduction to the methylumi package. Biocond Package. 2010;
  • Wong CC, Pidsley R, Schalkwyk LC. The wateRmelon package. BMC genomics.2013;14(1):1–0.
  • Illumina. Infinium human methylationEPIC array product files.
  • Dogan MV, Xiang J, Beach SRH, et al. Ethnicity and smoking-associated DNA methylation changes at HIV co-receptor GPR15. Front Psychiatry. 2015;6:132.
  • Teschendorff AE, Marabita F, Lechner M, et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics. 2013;29:189–196.
  • Pidsley R, Zotenko E, Peters TJ, et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome Biol. 2016;17:208.
  • Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10:573.
  • Lu AT, Lu AT, Quach A, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY). 2019;11:303.
  • Lu AT, Seeboth A, Tsai P-C, et al. DNA methylation-based estimator of telomere length. Aging (Albany NY). 2019;11:5895.
  • Belsky DW, Caspi A, Corcoran DL, et al. DunedinPACE, a DNA methylation biomarker of the pace of aging. Elife. 2022;11:e73420.
  • Belsky DW, Caspi A, Arseneault L, et al. Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm. Elife. 2020;9:e54870.
  • Houseman EA, Accomando WP, Koestler DC, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012;13:86.
  • Gelernter J, Polimanti R. Genetics of substance use disorders in the era of big data. Nat Rev Genet. 2021;22(11):712–729.
  • Dawes K, Sampson L, Reimer R, et al. Epigenetic analyses of alcohol consumption in combustible and non-combustible nicotine product users. Epigenomes. 2021;5:18.
  • Philibert RA, Beach S, Brody GH. The DNA methylation signature of smoking: an archetype for the identification of biomarkers for behavioral illness. Genes and motivation subst. 2014; 109–127.
  • Mills JA, Beach S, Dogan M, et al. A direct comparison of the relationship of epigenetic aging and epigenetic substance consumption markers to mortality in the Framingham Heart Study. Genes (Basel). 2019;10:51.
  • McClure JB. Are biomarkers a useful aid in smoking cessation? A review and analysis of the literature. Behav Med. 2001;27:37–47.
  • Subhani M, Knight H, Ryder S, et al. Does advice based on biomarkers of liver injury or non-invasive tests of liver fibrosis impact high-risk drinking behaviour: a systematic review with meta-analysis. Alcohol Alcohol. 2021;56:185–200.
  • Bergsma T, Rogaeva E. DNA methylation clocks and their predictive capacity for aging phenotypes and healthspan. Neurosci insights. 2020;15:2633105520942221.
  • Yousefi PD, Suderman M, Langdon R, et al. DNA methylation-based predictors of health: applications and statistical considerations. Nat Rev Genet. 2022;23(6):369–383.
  • Gaunt TR, Shihab HA, Hemani G, et al. Systematic identification of genetic influences on methylation across the human life course. Genome Biol. 2016;17:1–14.
  • Philibert R, Beach SRH, Lei M-K, et al. Array-based epigenetic aging indices may be racially biased. Genes (Basel). 2020;11:685.
  • Pfeiffer L, Wahl S, Pilling LC, et al. DNA methylation of lipid-related genes affects blood lipid levels. Circulation. 2015;8:334–342.
  • Hawe JS, Wilson R, Schmid KT, et al. Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function. Nat Genet. 2022;54:18–29.
  • Lee SJ, Eunae Kim, Hakyung Kim, Shuai Li, John L. Hopper, and Joohon Sung. Twin and Family Studies of Epigenetics. In: DNA methylation changes specific to environmental exposures: the strengths of twin studies using cigarette smoking as an example. Elsevier, 2021; 277–284.
  • Dogan MV, Knight S, Dogan TK, et al. External validation of integrated genetic-epigenetic biomarkers for predicting incident coronary heart disease. Epigenomics. 2021;13(14):1095–1112.
  • Dawes K, Simons R, and Darbro B, et al. Additive and interactive genetically contextual effects of HbA1c on cg19693031 methylation in type 2 diabetes. Genes (Basel). Genes 2022, 13(4), 683.
  • Guida F, Sandanger TM, Castagné R, et al. Dynamics of smoking-induced genome-wide methylation changes with time since smoking cessation. Hum Mol Genet. 2015;24:2349–2359.
  • Wilson R, Wahl S, Pfeiffer L, et al. The dynamics of smoking-related disturbed methylation: a two time-point study of methylation change in smokers, non-smokers and former smokers. BMC Genomics. 2017;18:805.
  • Witt SH, Frank J, Frischknecht U, et al. Acute alcohol withdrawal and recovery in men lead to profound changes in DNA methylation profiles: a longitudinal clinical study. Addiction. 2020;115:2034–2044.
  • Takeuchi F, Takano K, and Yamamoto M, et al. Clinical implication of smoking-related aryl-hydrocarbon receptor repressor (AHRR) hypomethylation in Japanese adults. Circ J. 2022;84:CJ-21–0958.
  • Tang R, Howe LD, Suderman M, et al. Adverse childhood experiences, DNA methylation age acceleration, and cortisol in UK children: a prospective population-based cohort study. Clin Epigenetics. 2020;12:55.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.