Latent class typology of nicotine withdrawal: genetic contributions and association with failed smoking cessation and psychiatric disorders
Open accessAbstract
Background. Nicotine withdrawal is associated with failed smoking cessation and thus contributes to continuance of the habit and increases risk of smoking-related illnesses. Withdrawal is also associated with psychiatric disorders such as depression and alcoholism. However, relatively little is known about how to characterize the severity of withdrawal, including whether withdrawal subtypes exist in male smokers. If so, do these subtypes represent quantitative or qualitative differences? Method. Smoking and withdrawal data were obtained from 4112 male–male twin pairs of the Vietnam Era Twin Registry during a 1992 administration of the Diagnostic Interview Schedule. Latent Class Analysis (LCA) was used to derive significantly different nicotine withdrawal profiles, and their association with psychiatric disorders was assessed. Genetic and environmental contributions and the correlation between these contributions were evaluated using bivariate biometrical modeling of the withdrawal phenotype and failed smoking cessation. Results. The LCA model which best fit the data was a four-class severity continuum. Psychiatric disorders were significantly associated with more severe classes and the magnitude of the association increased as withdrawal severity increased. Genetics accounted for 31% and 51% of the variance in risk for withdrawal and failed cessation, respectively. The genetic contributions were significantly correlated (r=0·37). Conclusions. Nicotine withdrawal classes are characterized by quantitative differences. The strong association between psychiatric disorders and withdrawal severity and the significant genetic correlation between withdrawal and cessation highlight the importance of withdrawal severity. Further refinement of the DSM definition of withdrawal to incorporate severity ratings may be warranted.
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Genetic factors may explain 29-53% of the variance in withdrawal symptoms and about half of the variance in quitting success.
“Genetic factors may also account for 29–53 % of the variance in withdrawal symptoms and approximately 50 % of the variance in quitting success (Xian et al. 2003, 2005; Pergadia et al. 2006).”
From Nicotine Withdrawal (2015) · cites this paper as Xian et al. 2005
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Self-citation
- Authors
- XIAN, H., SCHERRER, J. F., MADDEN, P. A. F., LYONS, M. J., TSUANG, M., TRUE, W. R., & EISEN, S. A.
- Affiliations
- Washington University in St. Louis (US)
- St. Louis VA Medical Center (US)
- Boston University (US)
- Harvard University (US)
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2004-09-29
- Volume
- 35
- Issue
- 3
- Pages
- 409-419
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- OpenAlex
- W1997762610
- Cited by
- 68
- References
- 26
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 3 · 2022: 2 · 2021: 4 · 2019: 3 · 2018: 1 · 2017: 3 · 2016: 5 · 2015: 3 · 2014: 5 · 2013: 2 · 2012: 1
- FWCI
- 2.06
- Type
- journal article
- Language
- en
- Open access
- Locations
- Psychological Medicine (publishedVersion)
- PubMed (publishedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
- Funders
- U.S. Department of Veterans Affairs
- Health Services Research and Development
- National Institutes of Health (1r03da013486-01)
- National Institute on Alcohol Abuse and Alcoholism (R01AA011822, AA11822)
- National Institute on Drug Abuse (R01DA004604, DA-00272, K21DA000272, R03-DA13486, DA4604)
- Topics
- Health Sciences › Medicine › Physiology › Smoking Behavior and Cessation
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- nicotine withdrawal, withdrawal severity, smoking cessation, mental illness, depression, alcoholism, genetic correlation, heritability, male smokers, twin pairs, Vietnam Era Twin Registry, latent class analysis
- MeSH terms
- Adult, Mental Disorders, Female, Ganglionic Stimulants, Humans, Male, Middle Aged, Nicotine, Risk Factors, Severity of Illness Index, Substance Withdrawal Syndrome, Tobacco Use Disorder, Smoking Cessation, Treatment Outcome
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