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Genetic Epidemiology of Smoking Behavior

Genetic Epidemiology of Smoking Behavior. Kenneth S. Kendler. Lifetime Prevalences of Externalizing and Substance Use Disorders Among Twins from Same-Sex Pairs. 3-Stage Conditional Model Contingent Causal Common Pathway. Proportions of variance Best fitting CCC model. TI. .89 .69. RU. ND.

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Genetic Epidemiology of Smoking Behavior

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  1. Genetic Epidemiology of Smoking Behavior Kenneth S. Kendler

  2. Lifetime Prevalences of Externalizing and Substance Use Disorders Among Twins from Same-Sex Pairs

  3. 3-Stage Conditional ModelContingent Causal Common Pathway

  4. Proportions of varianceBest fitting CCC model TI .89 .69 RU ND TI .87 .93 RU -.29 FTND TI .87 .70 RU P 0% 20% 40% 60% 80% 100% Ai Ar Ad Ei Er Ed No significant sex differences in proportions of variance or causal paths, but sex differences allowed in thresholds, No significant shared environmental effects for TI, RU and ND

  5. Genetic Epidemiology of Alcoholism • Family Studies • Adoption Studies • Denmark • Sweden • Twin Studies • Virginia, Sweden, Australia, WW-II and Vietnam Era Veteran twin registries

  6. 0 Estimated Genetic Proportions of Variance in Risk for Substance Abuse/Dependence

  7. Genetic Epidemiology of Substance Abuse • How do genetic risk factors for drug abuse relate to risk for psychiatric disorders?

  8. Genetic Factors AC2 AC1 .13 .33 .06 .54 .24 .53 .10 .58 .18 .65 .21 .56 .11 .37 Major Depression GAD Phobia Alcohol Dep Drug Abuse or Dep Adult Antisocial Behavior Conduct Disorder .00 .00 .22 .38 .46 .00 .17 ASP ASP ASP ASP ASP ASP ASP

  9. Genetic Epidemiology of Substance Abuse • How well does personality capture the genetic risk factors for substance initiation?

  10. Results from Bivariate Twin Model for Overlap of Novelty Seeking and Cannabis Use among Males Adapted from Table 1, Agrawal et al (2004), Twin Research, 7, 72-81

  11. Are the Genetic Risk Factors for Drug Abuse in Part Genes for Personality? • Genetic correlation between Novelty seeking (NS) and • Cannabis use – Males +0.96, Females +0.19 • Cocaine use – Males +0.62, Female +0.30

  12. Are the Genetic Risk Factors for Drug Use in Part Genes for Personality? • Genetic correlation between Extraversion and • Cannabis use +0.42 • Cocaine use +0.36 • Genetic correlation between Neuroticism and • Cannabis use +0.18 • Cocaine use +0.18

  13. Genetic Epidemiology of Substance Abuse • How do the genetic risk for different forms of substance abuse relate to each other?

  14. Genetic Epidemiology of Substance Abuse • Begin to consider mediational models • Genes → Intermediate phenotype → Drug Use • Or, how do genes contribute to well understood risk factors for drug use and abuse?

  15. Study the Availability of Drugs Life history data collection 8-11yrs 12-14yrs 15-17yrs 18-21yrs 22-25yrs Measures of drug availability - Alcohol - Marijuana - Stimulants - Cigarettes - Cocaine

  16. “When you were…how easy would it have been to get [substance] if you wanted to use (it / them)?” 0. Very easy 1. Somewhat easy 2. Somewhat difficult 3. Very difficult

  17. Item endorsement Alcohol

  18. Item endorsement Marijuana

  19. Item endorsement Cocaine

  20. Alcohol 8-11yrs 12-14yrs 18-21yrs 15-17yrs 8-11yrs 12-14yrs 18-21yrs 15-17yrs

  21. Marijuana 8-11yrs 12-14yrs 15-17yrs 18-21yrs 22-25yrs 8-11yrs 12-14yrs 15-17yrs 18-21yrs 22-25yrs

  22. Cocaine 8-11yrs 12-14yrs 15-17yrs 18-21yrs 22-25yrs 8-11yrs 12-14yrs 15-17yrs 18-21yrs 22-25yrs

  23. Unstandardized and standardized proportions of variance in CIGARETTE availability. Variance components include latent genetic and environmental effects attributable to intercept and slope factors in the full biometrical DCS model.

  24. Other Key Intermediate Phenotype – Peer Group Deviance • Genes can act to increase liability to drug use disorders through influencing selection into high risk environments. • Example here – deviance of peer group • Many studies show peer group deviance to be a powerful predictor of subsequent drug use.

  25. Modeling Time and Development and “Outside the Skin” Pathways • Measures of peer group deviance retrospectively reported by a life history method. • ~750 male-male twin pairs from Virginia Twin Registry. • Evaluate 4 ages. • Use a latent biometrical growth curve model • Can look separately at “genetics” of mean levels at different ages and • “Genetics” of slope (or trajectory).

  26. Genetics of the Trajectory of Change in Peer Group DevianceFrom Ages 8-22 • a2 = 0.43 • c2 = 0.22 • e2 = 0.35 • So, not only is the mean levels of peer group deviance influenced by genetic factors, but so is the rate of change over time.

  27. Prevalence And Heritability OfRegular Tobacco UseThree Birth Cohorts Of Men And Women In Sweden PrevalenceOfHeritability

  28. Linkage And Association • Linkage – in families. Sweeps entire genome. Good for genes of moderate to large effect. • Association – in populations. Examines only small distances. Can detect genes of relatively small effect. • If a base pair equals 1 cm, the human genome equals 33,000 km – around 80% of the way around the world. A linkage peak for a complex trait is ~ 200 km and association is detectable over distances from 50-200 meters.

  29. Irish Affected Sib-Pair Study of Alcohol DependenceSamples & Measures Probands ascertained Interview & DNA N=591 (M=364, F=227) Affected siblings referred Interview & DNA N=610 (M=413, F=197) 733 sib pairs (sibship size: 2-8) Parents contacted Brief Interview & DNA N=213 (M=82, F=131) Control Groups Screened n = 72 Semi-screened ~ 600 Prescott et al., Alc Clin Exp Res, 2005

  30. Sample & Measures IASPSAD families with DNA and informative for linkage (N=511 sib pairs, 485 families) 4 cM genome scan - deCODE genetics (Iceland) 1081 markers x 1500 individuals (1,621,500) Outcomes used for linkage analysis AD: DSM-IV Alcohol dependence SX: DSM-IV AD symptom count (range 3-7)

  31. Genome-wide LOD Scores for DSM-IV Alcohol Dependence Ch22 Ch13 Ch1

  32. Genome-wide LOD Scores for DSM-IV Alcohol Dependence Symptoms Ch4

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