E C Long1, S H Aggen2, M C Neale3, G P Knudsen4, R F Krueger5, S C South6, N Czajkowski7, R Nesvåg8, E Ystrom9, F A Torvik7, K S Kendler3, N A Gillespie2, T Reichborn-Kjennerud10. 1. Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA. Electronic address: longe@vcu.edu. 2. Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA. 3. Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA; Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA. 4. Department of Mental Disorders, Norwegian Institute of Public Health, Norway. 5. Department of Psychology, University of Minnesota, Minneapolis, MN, USA. 6. Department of Psychological Sciences, Purdue University, IN, USA. 7. Department of Mental Disorders, Norwegian Institute of Public Health, Norway; Department of Psychology, University of Oslo, Oslo, Norway. 8. Department of Mental Disorders, Norwegian Institute of Public Health, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway. 9. Department of Mental Disorders, Norwegian Institute of Public Health, Norway; Department of Psychology, University of Oslo, Oslo, Norway; School of Pharmacy, University of Oslo, Oslo, Norway. 10. Department of Mental Disorders, Norwegian Institute of Public Health, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Abstract
BACKGROUND: A clearer understanding of the etiological overlap between DSM-IV personality disorders (PDs) and alcohol use (AU) and alcohol use disorder (AUD) is needed. To our knowledge, no study has modeled the association between all 10 DSM-IV PDs and lifetime AU and AUD. The aim of the present study is to identify which PDs are most strongly associated with the phenotypic, genetic, and environmental risks of lifetime AU and AUD, and to determine if these associations are stable across time. METHODS: Participants were Norwegian twins assessed at two waves. At Wave 1, 2801 twins were assessed for all 10 DSM-IV PD criteria, lifetime AU, and DSM-IV AUD criteria. At Wave 2, six of the 10 PDs were again assessed along with AU and AUD among 2393 twins. Univariate and multiple logistic regressions were run. Significant predictors were further analyzed using bivariate twin Cholesky decompositions. RESULTS: Borderline and antisocial PD criteria were the strongest predictors of AU and AUD across the two waves. Despite moderate phenotypic and genetic correlations, genetic variation in these PD criteria explained only 4% and 3% of the risks in AU, and 5% to 10% of the risks in AUD criteria, respectively. At Wave 2, these estimates increased to 8% and 23% for AU, and 17% and 33% for AUD. CONCLUSIONS: Among a large Norwegian twin sample, borderline and antisocial PD criteria were the strongest predictors of the phenotypic and genotypic liability to AU and AUD. This effect remained consistent across time.
BACKGROUND: A clearer understanding of the etiological overlap between DSM-IV personality disorders (PDs) and alcohol use (AU) and alcohol use disorder (AUD) is needed. To our knowledge, no study has modeled the association between all 10 DSM-IV PDs and lifetime AU and AUD. The aim of the present study is to identify which PDs are most strongly associated with the phenotypic, genetic, and environmental risks of lifetime AU and AUD, and to determine if these associations are stable across time. METHODS:Participants were Norwegian twins assessed at two waves. At Wave 1, 2801 twins were assessed for all 10 DSM-IV PD criteria, lifetime AU, and DSM-IV AUD criteria. At Wave 2, six of the 10 PDs were again assessed along with AU and AUD among 2393 twins. Univariate and multiple logistic regressions were run. Significant predictors were further analyzed using bivariate twin Cholesky decompositions. RESULTS: Borderline and antisocial PD criteria were the strongest predictors of AU and AUD across the two waves. Despite moderate phenotypic and genetic correlations, genetic variation in these PD criteria explained only 4% and 3% of the risks in AU, and 5% to 10% of the risks in AUD criteria, respectively. At Wave 2, these estimates increased to 8% and 23% for AU, and 17% and 33% for AUD. CONCLUSIONS: Among a large Norwegian twin sample, borderline and antisocial PD criteria were the strongest predictors of the phenotypic and genotypic liability to AU and AUD. This effect remained consistent across time.
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Authors: Nathan A Gillespie; Steven H Aggen; Amanda E Gentry; Michael C Neale; Gun P Knudsen; Robert F Krueger; Susan C South; Nikolai Czajkowski; Ragnar Nesvåg; Eivind Ystrom; Tom H Rosenström; Fartein A Torvik; Ted Reichborn-Kjennerud; Kenneth S Kendler Journal: Twin Res Hum Genet Date: 2018-02 Impact factor: 1.587
Authors: Nathan A Gillespie; Steven H Aggen; Michael C Neale; Gun Peggy Knudsen; Robert F Krueger; Susan C South; Nikolai Czajkowski; Ragnar Nesvåg; Eivind Ystrom; Kenneth S Kendler; Ted Reichborn-Kjennerud Journal: Addiction Date: 2018-04-13 Impact factor: 6.526
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