Kenneth S Kendler1, Henrik Ohlsson2, Alexis C Edwards3, Katherine J Karriker-Jaffe4, Jan Sundquist5, Kristina Sundquist6. 1. Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond VA, USA; Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA. Electronic address: Kenneth.Kendler@vcuhealth.org. 2. Center for Primary Health Care Research, Lund University, Malmö, Sweden. Electronic address: Henrik.Ohlsson@med.lu.se. 3. Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond VA, USA. Electronic address: Alexis.Edwards@vcuhealth.org. 4. Alcohol Research Group, Public Health Institute, Emeryville, CA, USA. Electronic address: KKarrikerjaffe@arg.org. 5. Center for Primary Health Care Research, Lund University, Malmö, Sweden. Electronic address: Jan.Sundquist@med.lu.se. 6. Center for Primary Health Care Research, Lund University, Malmö, Sweden. Electronic address: Kristina.Sundquist@med.lu.se.
Abstract
BACKGROUND: Alcohol Use Disorder (AUD) is clinically heterogeneous. Using a large epidemiological sample ascertained via public registries, is it possible to identify clinical and historical features of AUD that reflect familial risk? METHODS: Using registration in national medical, legal or pharmacy registries, we identified four kinds of relative pairs (n=683,223) starting with a proband with AUD: cousins, half-siblings, full-siblings and monozygotic cotwins. Using linear hazard regression, we examined the interaction between five clinical/historical features of AUD in the proband and risk for AUD in these relatives. RESULTS: Increased risk for AUD in relatives was predicted by the proband's early age at first registration, total number of registrations, recurrence, history of drug abuse and ascertainment in the medical versus the legal or pharmacy registry. In multivariate models, age at first registration, number of registrations, recurrence and history of drug abuse remained significant and in aggregate strongly predicted the risk for AUD in relatives. The risk for AUD in siblings of AUD probands in the highest decile of genetic risk predicted by these four indices was more than twice as great as that predicted in siblings of probands in the lowest risk decile. CONCLUSIONS: In an epidemiological sample, familial risk for AUD can be assessed by simple clinical and historical variables.
BACKGROUND:Alcohol Use Disorder (AUD) is clinically heterogeneous. Using a large epidemiological sample ascertained via public registries, is it possible to identify clinical and historical features of AUD that reflect familial risk? METHODS: Using registration in national medical, legal or pharmacy registries, we identified four kinds of relative pairs (n=683,223) starting with a proband with AUD: cousins, half-siblings, full-siblings and monozygotic cotwins. Using linear hazard regression, we examined the interaction between five clinical/historical features of AUD in the proband and risk for AUD in these relatives. RESULTS: Increased risk for AUD in relatives was predicted by the proband's early age at first registration, total number of registrations, recurrence, history of drug abuse and ascertainment in the medical versus the legal or pharmacy registry. In multivariate models, age at first registration, number of registrations, recurrence and history of drug abuse remained significant and in aggregate strongly predicted the risk for AUD in relatives. The risk for AUD in siblings of AUD probands in the highest decile of genetic risk predicted by these four indices was more than twice as great as that predicted in siblings of probands in the lowest risk decile. CONCLUSIONS: In an epidemiological sample, familial risk for AUD can be assessed by simple clinical and historical variables.
Authors: Kenneth S Kendler; Sara Larsson Lönn; Hermine H Maes; Paul Lichtenstein; Jan Sundquist; Kristina Sundquist Journal: Behav Genet Date: 2015-10-22 Impact factor: 2.805
Authors: Kenneth S Kendler; Henrik Ohlsson; Alexis Edwards; Jan Sundquist; Kristina Sundquist Journal: Am J Med Genet B Neuropsychiatr Genet Date: 2017-08-29 Impact factor: 3.568
Authors: Derek B Kosty; Richard F Farmer; John R Seeley; Kathleen R Merikangas; Daniel N Klein; Jeff M Gau; Susan C Duncan; Peter M Lewinsohn Journal: Addict Behav Date: 2019-10-31 Impact factor: 3.913
Authors: Alexis C Edwards; Henrik Ohlsson; Jan Sundquist; Kristina Sundquist; Kenneth S Kendler Journal: Am J Psychiatry Date: 2020-03-12 Impact factor: 18.112