Preliminary evidence of ethnic divergence in associations of putative genetic variants for methamphetamine dependence
Introduction
Methamphetamine (METH) is a powerful illicit psychostimulant that has become increasingly popular throughout North America (Maxwell and Rutkowski, 2008). As a result, initiation of METH use and the progression to abuse and subsequent dependence have received increased attention in both research and clinical settings. However, unlike other substances of abuse (e.g., alcohol, cocaine), efforts to understand the genetic factors that may increase susceptibility to METH dependence have been limited. Twin studies have shown significantly high heritability of stimulant use disorders (Tsuang et al., 1996, Tsuang et al., 1998, Kendler et al., 2003); thus, the search for risk genes underlying these disorders is warranted. Some progress in identifying risk genes for METH dependence has been made, but almost exclusively in Asian populations (for reviews see Barr et al., 2006, Bousman et al., 2009). In these studies, several genes have been implicated across several biological pathways, ranging from dopamine-metabolism and signaling to neuronal survival factors. However, replication of these initial genotypic and allelic associations has not been attempted among non-Asian populations.
It is generally accepted, as a result of efforts by the International Haplotype Mapping Project (HapMap) (International HapMap Consortium, 2005), that genotypic and allelic variations can differ greatly from one ancestral group to the next. In fact, in a recent genome-wide association study of METH dependence (Uhl et al., 2008), it was reported that ethnic allelic divergence is probable. Thus, it is necessary to verify genetic associations not only within but also across populations. Since the completion of the human genome, a large amount of studies have purported gene-disorder associations that have not been replicated in similar and/or different populations. It is this particular propensity toward type-I errors that requires repeated investigations of genetic associations within and across populations. Thus, the purpose of this study was to explore for the first time, to our knowledge, putative single nucleotide polymorphisms (SNPs) for METH dependence in a non-Asian sample. We selected and examined, among a population of METH-dependent Caucasians, six putative SNPs (AKT1, ARRB2, BDNF, COMT, GSTP1, OPRM1) recently found to be associated with METH dependence in Asian populations.
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Participants
Participants were 193 nonpsychotic unrelated males (117 METH-dependent and 76 controls) evaluated at the HIV Neurobehavioral Research Center (HNRC) at the University of California, San Diego, as part of a cohort study focused on central nervous system effects of HIV and methamphetamine. The mean age of control (M = 39.6, standard deviation (S.D.) =10.2) and METH-dependent (M = 38.6, S.D. = 8.2) participants were not statistically different (t = 0.73, df = 191, P = 0.42).
Recruitment methods have been
Results
Table 2 displays genotype frequencies of the six SNPs (AKT1, ARRB2, BDNF, COMT, GSTP1, OPRM1) previously implicated in Asian samples. Among controls, each of the selected genotypes was in Hardy–Weinberg equilibrium (HWE) and allele frequencies were similar to those reported by the National Center for Biotechnology Information SNPs Database with the exception of OPRM1 (HWE: χ2 = 7.48, df = 1, P = 0.006). None of the polymorphisms found to be significantly associated with METH dependence among Asian
Discussion
To our knowledge, this study is the first to explore previously reported gene-associations for METH dependence in non-Asian (Caucasian) population and provide evidence that genotypic susceptibility to METH dependence may differ by ethnicity, albeit previous research (Sery et al., 2001) has examined genotypic susceptibility in Caucasian METH users. Among the six putative SNPs previously found to be associated with METH dependence among Asians, we did not statistically replicate any association
Acknowledgments
The authors wish to acknowledge support from the United States National Institutes of Health (grant numbers P01-DA12065 and P30-MH62512) and the contributions of study participants and staff at the HIV Neurobehavioral Research Center (HNRC), San Diego, CA, USA. The views expressed in this article are those of the authors and do not reflect the official policy or position of the Department of the Navy, Department of Defense, nor the United States Government.
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The HNRC Group is affiliated with the University of California, San Diego, the Naval Hospital, San Diego, and the Veterans Affairs San Diego Healthcare System, and includes: Director: Igor Grant, M.D.; Co-Directors: J. Hampton Atkinson, M.D., Ronald J. Ellis, M.D., Ph.D., and J. Allen McCutchan, M.D.; Center Manager: Thomas D. Marcotte, Ph.D.; Business Manager: Melanie Sherman; Naval Hospital San Diego: Braden R. Hale, M.D., M.P.H. (P.I.); Neuromedical Component: Ronald J. Ellis, M.D., Ph.D. (P.I.), J. Allen McCutchan, M.D., Scott Letendre, M.D., Edmund Capparelli, Pharm.D., Rachel Schrier, Ph.D.; Jennifer Marquie-Beck; Terry Alexander, R.N.; Neurobehavioral Component: Robert K. Heaton, Ph.D. (P.I.), Mariana Cherner, Ph.D., Steven Paul Woods, Psy.D., David J. Moore, Ph.D.; Matthew Dawson, Donald Franklin; Neuroimaging Component: Terry Jernigan, Ph.D. (P.I.), Christine Fennema-Notestine, Ph.D., Sarah L. Archibald, M.A., John Hesselink, M.D., Jacopo Annese, Ph.D., Michael J. Taylor, Ph.D., Neurobiology Component: Eliezer Masliah, M.D. (P.I.), Ian Everall, FRCPsych., FRCPath., Ph.D., Cristian Achim, M.D., Ph.D.; Neurovirology Component: Douglas Richman, M.D., (P.I.), David M. Smith, M.D.; International Component: J. Allen McCutchan, M.D., (P.I.); Developmental Component: Ian Everall, FRCPsych., FRCPath., Ph.D. (P.I.), Stuart Lipton, M.D., Ph.D.; Clinical Trials Component: J. Allen McCutchan, M.D., J. Hampton Atkinson, M.D., Ronald J. Ellis, M.D., Ph.D., Scott Letendre, M.D.; Participant Accrual and Retention Unit: J. Hampton Atkinson, M.D. (P.I.), Rodney von Jaeger, M.P.H.; Data Management Unit: Anthony C. Gamst, Ph.D. (P.I.), Clint Cushman (Data Systems Manager), Daniel R. Masys, M.D. (Senior Consultant); Statistics Unit: Ian Abramson, Ph.D. (P.I.), Florin Vaida, Ph.D., Christopher Ake, Ph.D.