Using Twin Data To Identify Alternative Drug Abuse Phenotypes Ming T. Tsuang, MD, Ph.D. University Professor, University of California & Director, Institute of Behavioral Genomics, Dept. of Psychiatry, UC San Diego; Director, Harvard Institute of Psychiatric Epidemiology and Genetics, Depts. of Epidemiology & Psychiatry, Harvard University

Background Some of the difficulty in identifying genes for drug abuse stems from underlying etiologic complexity of this phenotype. Unlike disorders such as Huntington’s disease, drug abuse is presumed to have a multifactorial polygenic etiology, in which numerous genes and environmental factors all make small contributions to the overall risk for the illness.

Moving Beyond “Off the Shelf” DSM Phenotypes Empirical methods, such as factor analysis, may help to identify useful “quantitative traits.” Transitions may reflect different phenotypes with different genetic determinants Psychiatric disorders that co-occur with substance abuse may reflect the same genetic vulnerability

Previous Relevant Research Using the Vietnam Era Twin Registry

Sample Demographics Mean age years (+2.8 years) Age range - 36 to 55 years Ethnicity non-Hispanic white 90.4% African American 4.9% Hispanic 2.7% Native American 1.3% “Other” 0.7%

Sample Size Number of individuals: 8,169 response rate: 79.7% completed pairs: MZ - 1,874 DZ - 1,498

Vietnam Era Twin Registry Consists of 7,375 male-male twin pairs Both served on active duty during the Vietnam Era ( ) Born between 1939 and 1957 Identified from Dept. of Defense data files by computer algorithm

Vietnam Era Twin Registry Zygosity determined by questions on sibling similarity and blood group typing data from military records All were raised together

Using Transitions in Drug Use to Define Phenotypes for Genetic Research “Unaffected” phenotype should be restricted to individuals with the opportunity to become “abusers” who did not become “abusers” Individuals without the opportunity to become “abusers” should be classified “phenotype unknown”

Exposure to Drug Initiation – “First Use” Regular Use Abuse (Problematic Use) Dependence Discontinuation of Use Stages in Drug Usage Phenotype Unknown Affected Phenotype ?

Conclusions There is no single, unitary “drug phenotype” that will encompass all aspects of the relevant phenomena. There is considerable overlap among the various “drug phenotypes” that could be formulated.

Univariate Analyses of Drug Abuse

Pairwise Concordance Rates for Drug Abuse

Correlations for Drug Abuse P<.001

Influences on Drug Abuse/Dependence

Conclusions from Univariate Analyses Genetic factors are the most important determinants of heroin addiction. Genetic factors may be more important for heroin addiction than for addiction to other drugs. Results for heroin suggest there may be both polygenic effects and a single gene of major effect or epistasis.

Question for Multivariate Analyses To what extent are determinants of addiction shared among all drugs versus unique to each individual drug?

Vulnerability to Drug Dependence Common Vulnerability Stimulants 77% Heroin/ Opiates 50% Psychedelics 85% Marijuana 71% Sedatives 69%

Determinants of Common Vulnerability to Drug Dependence

Family Environmental Influences on Drug Dependence Common Family Environmental Vulnerability 100% Stimulants (c 2 =18%) (c 2 =15%) Heroin/ Opiates 100% (c 2 =19%) Psychedelics 100% 59% Marijuana (c 2 =29%) 100% Sedatives (c 2 =17%)

Non-Family Environmental Influences on Drug Dependence Common Non-Family Environmental Vulnerability 71% Stimulants (e 2 =48%) (e 2 =33%) Heroin/ Opiates 64% (e 2 =52%) Psychedelics 71% 84% Marijuana (e 2 =38%) 54% Sedatives (e 2 =56%)

Genetic Influences on Drug Dependence Common Genetic Vulnerability 73% Stimulants (h 2 =33%) (h 2 =54%) Heroin/ Opiates 30% (h 2 =26%) Psychedelics 100% (h 2 =33%) Marijuana 67% (h 2 =27%) Sedatives 81%

Conclusions from Multivariate Analyses The best model to explain the co-occurrence of addiction to different drugs is a common latent vulnerability. The “Marijuana Gateway” model is a poor fit to the data.

Conclusions from Multivariate Analyses About half of the influences on heroin addiction also impart risk for addiction to other illicit drugs. About half of the influences on heroin addiction are unique to heroin (i.e, they don’t affect the risk for addiction to other drugs).

Conclusions from Multivariate Analyses Everything about the family environment that imparts risk for heroin addiction also imparts risk for addiction to all other illicit drugs. Only marijuana is affected by family environmental factors that don’t also influence other illicit drugs.

Conclusions from Multivariate Analyses Some aspects of the non-family environment that affect heroin addiction also affect addiction to other drugs. Some aspects of the non-family environment that affect heroin addiction are unique to heroin addiction (i.e., don’t affect addiction to other drugs).

Conclusions from Multivariate Analyses 70% of the genetic influence on heroin addiction is unique to heroin addiction (more than for any other drug). Heroin addiction is the most “heritable” addiction to an illicit drug (at least given the environmental circumstances of our sample).

Future Directions for Investigating Phenotypes for Genetic Research on Drug Abuse

Background & Significance A genetic contribution to the liability toward illicit drug use has been firmly established. The task is now to identify specific genes that influence the liability to substance use disorders (SUDs). Defining genetically homogenous phenotypes is critical to the success of genetic linkage and association studies.

Alternative Phenotypes Heterogeneous nature of phenotypes compounds difficulty of identifying genes that impart risk. DSM diagnosis of drug abuse may not map neatly onto its genetic foundations.

Alternative Phenotypes May provide a stronger ‘signal’ in the search for underlying risk genes. We propose to utilize data from both twin and molecular genetic samples to generate and refine alternative phenotypic definitions of substance use disorders (SUDs).

Summary There is good evidence for genetic influences on SUDs. The specific genes that influence SUDs have remained elusive. A rate-limiting step in finding genes for SUDs may be specifying the best phenotypes.