Genetic correlations between smoking initiation and smoking behaviors in a twin sample

Hardie, Thomas; Moss, Howard B.; Lynch, Kevin G.

doi:10.1016/j.addbeh.2006.02.010

Cited by 32 publications

(29 citation statements)

References 22 publications

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“…Analysis of heritability for the tested dose suggests that conditioned place preference has a relatively high heritability (42%–57%) among inbred mouse strains. These results are in line with previous reports in humans that suggest nicotine addiction-associated behaviors are highly heritable (Haberstick et al, 2007; Hardie et al, 2006; Li et al, 2003; Sullivan & Kendler, 1999) and a study showing CPP in B6 mice but not D2 mice (Grabus, Martin, Brown, & Damaj, 2006). …”

Section: Discussionsupporting

confidence: 93%

Strain-dependent performance in nicotine-induced conditioned place preference.

Kutlu

Ortega

Gould

2015

Behavioral Neuroscience

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Nicotine addiction is most likely a result of a combination of factors including the rewarding effects of the drug; these effects, however, might be influenced by genetic background. Using a conditioned place preference (CPP) paradigm and 8 inbred mouse strains, we conducted an initial examination of the role of genetic background in the rewarding effects of nicotine. Following habituation and initial place preference test, inbred strains (A/J, BALB/cByJ, C3H/HeJ, C57BL/6J, CBA/J, DBA/1J, DBA/2J, and 129/SvEv) were trained and tested in CPP for nicotine (0.35 mg/kg). Although several strains (C57BL/6J, CBA/J, and 129/SvEv) showed nicotine-induced CPP, 1 strain (DBA/1J) showed conditioned place aversion (CPA), and other strains (A/J, BALB/cByJ, C3H/HeJ, and DBA/2J) did not show CPP. Overall, these results indicate that nicotine’s rewarding effects tested in CPP are differentially affected by the genetic background, and this trait has a relatively high heritability (42%–57%). This initial investigation lays the foundation for future studies examining the genetic substrates of nicotine reward.

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Section: Discussionsupporting

confidence: 93%

Strain-dependent performance in nicotine-induced conditioned place preference.

Kutlu

Ortega

Gould

2015

Behavioral Neuroscience

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“…The moderate correlations between the 4 polygenic risk scores might be the result of a lot of error variance resulting from random, non-generalizable, non-linear and/or interactive genetic effects. Previous twin studies have suggested some overlap between smoking-related variables, varying from only a small proportion of shared genetic variance (45,46) between age at first cigarette and smoking variables, to a higher genetic overlap between smoking persistence and initiation (47). A study of the Netherlands Twin Register showed two separate dimensions for smoking initiation and nicotine dependence, but those dimensions were not independent (5).…”

Section: Discussionmentioning

confidence: 99%

Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

Vink

Hottenga²,

Geus³

et al. 2014

Addiction

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Background and Aims A strong correlation exists between smoking and the use of alcohol and cannabis. This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors. Those scores reflect a combined effect of selected risk alleles for smoking. Methods Summary-level p-values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (N between 22,000 and 70,000 subjects). Using different p-value thresholds (.1, .2 and .5) from the meta-analyses, sets of ‘risk alleles’ were defined and used to generate a polygenic risk score (weighted sum of the alleles) for each subject in an independent target sample from the Netherlands Twin Register (N=1583). The association between polygenic smoking scores and alcohol/cannabis use was investigated with regression analyses. Results The polygenic scores for ‘cigarettes per day’ were significantly associated with, the number of glasses alcohol per week (p=.005, R2=.4–.5%) and cannabis initiation (p=.004, R2=0.6–.9%). The polygenic scores for ‘age at onset of smoking’ were significantly associated with ‘age at regular drinking’ (p=.001, R2=1.1–1.5%), while the scores for ‘smoking initiation’ and ‘smoking cessation’ did not significantly predict alcohol or cannabis use. Conclusions Smoking, alcohol and cannabis use are influenced by aggregated genetic risk factors shared between these substances. The many common genetic variants each have a very small individual effect size.

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“…Twin studies suggest that additive genetic factors account for about 45-85% of variability of smoking initiation and persistence [37-40] as well as up to 75% of the variability in nicotine dependence [41-46]. Other studies suggest that 40% to 60% of individual differences in the ability to successfully quit may be attributable to additive genetic effects [47-49].…”

Section: Genetic Biomarkersmentioning

confidence: 99%

Biomarkers of Response to Smoking Cessation Pharmacotherapies: Progress to Date

et al. 2015

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For the past thirty years, research examining predictors of successful smoking cessation treatment response has focused primarily on clinical variables, such as levels of tobacco dependence, craving, and self-efficacy. Recent research, however, has begun to determine biomarkers (such as genotype, nicotine and metabolite levels, and brain imaging findings) that may have utility in predicting smoking cessation. For genotype, genes associated with nicotinic acetylcholine receptors (nAChRs) and related proteins have been found to predict response to first line medications (e.g., nicotine replacement therapy [NRT], bupropion, or varenicline) or quitting over time without a controlled treatment trial. For nicotine and metabolite levels, function of the CYP 2A6 liver enzyme, which can be assessed with the nicotine metabolite ratio or via genotype, has been found to predict response, with slow nicotine metabolizers having less severe nicotine dependence and a greater likelihood of quitting with NRT than normal metabolizers. And for brain imaging, decreased activation of brain regions associated with emotion regulation and increased connectivity in emotion regulation networks, increased responsiveness to pleasant cues, and altered activation with the Stroop effect have been found in smokers who quit with the first-line medications listed above or counseling. In addition, our group recently demonstrated that lower pre-treatment brain nAChR density is associated with a greater chance of quitting smoking with NRT or placebo. Several of these studies found that specific biomarkers may provide additional information for predicting response beyond subjective symptom or rating scale measures, thereby giving an initial indication that biomarkers may, in the future, be useful for guiding smoking cessation treatment intensity, duration, and type.

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Genetic correlations between smoking initiation and smoking behaviors in a twin sample

Cited by 32 publications

References 22 publications

Strain-dependent performance in nicotine-induced conditioned place preference.

Strain-dependent performance in nicotine-induced conditioned place preference.

Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

Biomarkers of Response to Smoking Cessation Pharmacotherapies: Progress to Date

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