BACKGROUND: Various studies support the inclusion of cannabis withdrawal in the diagnosis of cannabis use disorder (CUD) in the upcoming DSM-5. The aims of the current study were to (1) estimate the prevalence of DSM-5 cannabis withdrawal (criterion B), (2) estimate the role of genetic and environmental influences on individual differences in cannabis withdrawal and (3) determine the extent to which genetic and environmental influences on cannabis withdrawal overlap with those on DSM-IV-defined abuse/dependence. METHOD: The sample included 2276 lifetime cannabis-using adult Australian twins. Cannabis withdrawal was defined in accordance with criterion B of the proposed DSM-5 revisions. Cannabis abuse/dependence was defined as endorsing one or more DSM-IV criteria of abuse or three or more dependence criteria. The classical twin model was used to estimate the genetic and environmental influences on variation in cannabis withdrawal, along with its covariation with abuse/dependence. RESULTS: Of all the cannabis users, 11.9% met criteria for cannabis withdrawal. Around 50% of between-individual variation in withdrawal could be attributed to additive genetic variation, and the rest of the variation was mostly due to non-shared environmental influences. Importantly, the genetic influences on cannabis withdrawal almost completely (99%) overlapped with those on abuse/dependence. CONCLUSIONS: We have shown that cannabis withdrawal symptoms exist among cannabis users, and that cannabis withdrawal is moderately heritable. Genetic influences on cannabis withdrawal are the same as those affecting abuse/dependence. These results add to the wealth of literature that recommends the addition of cannabis withdrawal to the diagnosis of DSM-5 CUD.
BACKGROUND: Various studies support the inclusion of cannabis withdrawal in the diagnosis of cannabis use disorder (CUD) in the upcoming DSM-5. The aims of the current study were to (1) estimate the prevalence of DSM-5 cannabis withdrawal (criterion B), (2) estimate the role of genetic and environmental influences on individual differences in cannabis withdrawal and (3) determine the extent to which genetic and environmental influences on cannabis withdrawal overlap with those on DSM-IV-defined abuse/dependence. METHOD: The sample included 2276 lifetime cannabis-using adult Australian twins. Cannabis withdrawal was defined in accordance with criterion B of the proposed DSM-5 revisions. Cannabis abuse/dependence was defined as endorsing one or more DSM-IV criteria of abuse or three or more dependence criteria. The classical twin model was used to estimate the genetic and environmental influences on variation in cannabis withdrawal, along with its covariation with abuse/dependence. RESULTS: Of all the cannabis users, 11.9% met criteria for cannabis withdrawal. Around 50% of between-individual variation in withdrawal could be attributed to additive genetic variation, and the rest of the variation was mostly due to non-shared environmental influences. Importantly, the genetic influences on cannabis withdrawal almost completely (99%) overlapped with those on abuse/dependence. CONCLUSIONS: We have shown that cannabis withdrawal symptoms exist among cannabis users, and that cannabis withdrawal is moderately heritable. Genetic influences on cannabis withdrawal are the same as those affecting abuse/dependence. These results add to the wealth of literature that recommends the addition of cannabis withdrawal to the diagnosis of DSM-5 CUD.
Authors: A C Heath; K K Bucholz; P A Madden; S H Dinwiddie; W S Slutske; L J Bierut; D J Statham; M P Dunne; J B Whitfield; N G Martin Journal: Psychol Med Date: 1997-11 Impact factor: 7.723
Authors: Arpana Agrawal; Michael T Lynskey; Kathleen K Bucholz; Manav Kapoor; Laura Almasy; Danielle M Dick; Howard J Edenberg; Tatiana Foroud; Alison Goate; Dana B Hancock; Sarah Hartz; Eric O Johnson; Victor Hesselbrock; John R Kramer; Samuel Kuperman; John I Nurnberger; Marc Schuckit; Laura J Bierut Journal: Drug Alcohol Depend Date: 2013-11-16 Impact factor: 4.492
Authors: M Smolkina; K I Morley; F Rijsdijk; A Agrawal; J E Bergin; E C Nelson; D Statham; N G Martin; M T Lynskey Journal: Behav Genet Date: 2017-05-02 Impact factor: 2.805
Authors: Tom G Richardson; Camelia Minica; Jon Heron; Jeremy Tavare; Alasdair MacKenzie; Ian Day; Glyn Lewis; Matthew Hickman; Jacqueline M Vink; Joel Gelernter; Henry R Kranzler; Lindsay A Farrer; Marcus Munafò; David Wynick Journal: Am J Med Genet B Neuropsychiatr Genet Date: 2014-09-16 Impact factor: 3.568