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There has been much recent excitement concerning the apparent heritability of tobacco smoking and the identification of candidate genes that might contribute to this heritability (Tyndale 2003). Although the genetic contributions to smoking behavior hold significant explanatory potential, sometimes lost in the excitement is that we have yet to reach a satisfactory understanding of the environmental contributors to this behavior. Thus, it is particularly encouraging when a behavioral genetic design is used to isolate environmental effects by controlling for genetic effects, as Slomkowski et al. (2005) accomplished. This strategy has been underused in general, and particularly so within the tobacco literature. Yet the power of the design allowed Slomkowski et al. to demonstrate that the nature of sibling relationships (i.e. social connectedness) is associated with the transmission of smoking between the siblings.

One immediate question that emerges from these findings is how smoking behavior is transmitted between siblings via their relationship. That is, what are the units of communication? We suggest that the answer is likely to be found among the individuals’ expectancies regarding cigarette smoking (Brandon et al. 1999). Expectancies are the memory templates (both implicit and explicit) of the reinforcing value of a substance that can influence substance use (Goldman 1999). They are predictive of all phases of substance onset, maintenance and cessation, and they may serve as the final common pathway of multiple determinants of substance use and abuse. Thus, expectancies about the immediate and delayed, positive and negative consequences of smoking are natural candidates for investigation as the units of transmission between siblings.

It is impressive that the findings of the study emerged despite the use of an admittedly crude tobacco use measure—smoking frequency. The identification of smoking-related endophenotypes (an endogenous characteristic of a person that is a more direct product of a genotype; Iacono 1998), such as physiological reactivity to nicotine, might improve the partitioning of genetic variance, control for it more completely, and therefore elucidate environmental effects. Additionally, the dependent measure, while an improvement over a dichotomous smoker/non-smoker variable, none the less fails to capture the variability in either smoking behavior or tobacco dependence. This has been a limitation of much tobacco research, but there has been recent progress in developing sensitive, multi-modal indices of tobacco dependence (e.g. Piper et al. 2004). Indeed, a recent issue of this journal was dedicated to theory-based indices of tobacco dependence among adolescents per se (see Brandon et al. 2004; Eissenberg 2004; Glautier 2004).

In sum, by identifying an apparently robust environmental influence on adolescent smoking, Slomkowski et al. 2005) have set the stage for future research that can distill this effect by examining the units of sibling transmission and refining the measurement of tobacco use and dependence. Although substantial environmental variance in smoking remains to be identified, genetically informative designs offer the potential for further progress in this regard, through the isolation first of genetic influences, and now sibling transmission.

References

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  • Brandon, T. H., Herzog, T. A., Irvin, J. E. & Gwaltney, C. J. (2004) Cognitive and social learning models of drug dependence: implications for the assessment of tobacco dependence in adolescents. Addiction, 99, 5177.
  • Brandon, T. H., Juliano, L. M. & Copeland, A. L. (1999) Expectancies for tobacco smoking. In: Kirsch, I., ed. How Expectancies Shape Experience, pp. 263299. Washington, DC: American Psychological Association.
  • Eissenberg, T. (2004) Measuring the emergence of tobacco dependence: the contribution of negative reinforcement models. Addiction, 99, 529.
  • Glautier, S. (2004) Measures and models of nicotine dependence: positive reinforcement. Addiction, 99, 3050.
  • Goldman, M. S. (1999) Expectancy operation. Cognitive neural models and architectures. In: Kirsch, I., ed. How Expectancies Shape Experience, pp. 4163. Washington, DC: American Psychological Association.
  • Iacono, W. G. (1998) Identifying psychophysiologial risk for psychopathology: examples from substance abuse and schizophrenia research. Psychophysiology, 35, 621637.
  • Piper, M. E., Piasecki, T. M., Federman, E. B., Bolt, D. M., Smith, S. S., Fiore, M. C. & Baker, T. B. (2004) A multiple motives approach to tobacco dependence: the Wisconsin Inventory of Smoking Dependence Motives (WISDM-68). Journal of Consulting and Clinical Psychology, 72, 139154.
  • Slomowski, C., Rende, R., Novak, S., Lloyd-Richardson, E. & Niaura, R. (2005) Sibling effects on smoking in adolescence: evidence for social influence from a genetically informative design. Addiction, 100, 430438.
  • Tyndale, R. F. (2003) Genetics of alcohol and tobacco use in humans. Annals of Medicine, 35, 94121.