BACKGROUND: Alcohol dependence tends to aggregate within families. We analyzed data from the family collection of the Collaborative Study on the Genetics of Alcoholism to quantify familial aggregation using several different criterion sets. We also assessed the aggregation of other psychiatric disorders in the same sample to identify areas of possible shared genetic vulnerability. DESIGN: Age-corrected lifetime morbid risk was estimated in adult first-degree relatives of affected probands and control subjects for selected disorders. Diagnostic data were gathered by semistructured interview (the Semi-Structured Assessment for the Genetics of Alcoholism), family history, and medical records. Rates of illness were corrected by validating interview and family history reports against senior clinicians' all sources best estimate diagnoses. Sex, ethnicity, comorbidity, cohort effects, and site of ascertainment were also taken into account. RESULTS: Including data from 8296 relatives of alcoholic probands and 1654 controls, we report lifetime risk rates of 28.8% and 14.4% for DSM-IV alcohol dependence in relatives of probands and controls, respectively; respective rates were 37.0% and 20.5% for the less stringent DSM-III-R alcohol dependence, 20.9% and 9.7% for any DSM-III-R diagnosis of nonalcohol nonnicotine substance dependence, and 8.1% and 5.2% for antisocial personality disorder. Rates of specific substance dependence were markedly increased in relatives of alcohol-dependent probands for cocaine, marijuana, opiates, sedatives, stimulants, and tobacco. Aggregation was also seen for panic disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and major depression. CONCLUSIONS: The risk of alcohol dependence in relatives of probands compared with controls is increased about 2-fold. The aggregation of antisocial personality disorder, drug dependence, anxiety disorders, and mood disorders suggests common mechanisms for these disorders and alcohol dependence within some families. These data suggest new phenotypes for molecular genetic studies and alternative strategies for studying the heterogeneity of alcohol dependence.
BACKGROUND:Alcohol dependence tends to aggregate within families. We analyzed data from the family collection of the Collaborative Study on the Genetics of Alcoholism to quantify familial aggregation using several different criterion sets. We also assessed the aggregation of other psychiatric disorders in the same sample to identify areas of possible shared genetic vulnerability. DESIGN: Age-corrected lifetime morbid risk was estimated in adult first-degree relatives of affected probands and control subjects for selected disorders. Diagnostic data were gathered by semistructured interview (the Semi-Structured Assessment for the Genetics of Alcoholism), family history, and medical records. Rates of illness were corrected by validating interview and family history reports against senior clinicians' all sources best estimate diagnoses. Sex, ethnicity, comorbidity, cohort effects, and site of ascertainment were also taken into account. RESULTS: Including data from 8296 relatives of alcoholic probands and 1654 controls, we report lifetime risk rates of 28.8% and 14.4% for DSM-IV alcohol dependence in relatives of probands and controls, respectively; respective rates were 37.0% and 20.5% for the less stringent DSM-III-R alcohol dependence, 20.9% and 9.7% for any DSM-III-R diagnosis of nonalcohol nonnicotine substance dependence, and 8.1% and 5.2% for antisocial personality disorder. Rates of specific substance dependence were markedly increased in relatives of alcohol-dependent probands for cocaine, marijuana, opiates, sedatives, stimulants, and tobacco. Aggregation was also seen for panic disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and major depression. CONCLUSIONS: The risk of alcohol dependence in relatives of probands compared with controls is increased about 2-fold. The aggregation of antisocial personality disorder, drug dependence, anxiety disorders, and mood disorders suggests common mechanisms for these disorders and alcohol dependence within some families. These data suggest new phenotypes for molecular genetic studies and alternative strategies for studying the heterogeneity of alcohol dependence.
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Authors: Chella Kamarajan; Ashwini K Pandey; David B Chorlian; Niklas Manz; Arthur T Stimus; Lance O Bauer; Victor M Hesselbrock; Marc A Schuckit; Samuel Kuperman; John Kramer; Bernice Porjesz Journal: Int J Psychophysiol Date: 2015-09-18 Impact factor: 2.997
Authors: David A Kareken; Veronique Bragulat; Mario Dzemidzic; Cari Cox; Thomas Talavage; Dena Davidson; Sean J O'Connor Journal: Neuroimage Date: 2010-01-08 Impact factor: 6.556
Authors: Sheketha R Hauser; Amy L Bracken; Gerald A Deehan; Jamie E Toalston; Zheng-Ming Ding; William A Truitt; Richard L Bell; William J McBride; Zachary A Rodd Journal: Addict Biol Date: 2013-03-18 Impact factor: 4.280
Authors: Brandon G Oberlin; Mario Dzemidzic; Stella M Tran; Christina M Soeurt; Daniel S Albrecht; Karmen K Yoder; David A Kareken Journal: Neuropsychopharmacology Date: 2013-04-15 Impact factor: 7.853
Authors: Ty S Schepis; Rani A Desai; Anne E Smith; Dana A Cavallo; Thomas B Liss; Amanda McFetridge; Marc N Potenza; Suchitra Krishnan-Sarin Journal: J Addict Med Date: 2008 Impact factor: 3.702