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Genome-wide association for methamphetamine dependence: Convergent results from 2 samples

  • George R. Uhl
  • , Tomas Drgon
  • , Qing Rong Liu
  • , Catherine Johnson
  • , Donna Walther
  • , Tokutaro Komiyama
  • , Mutsuo Harano
  • , Yoshimoto Sekine
  • , Toshiya Inada
  • , Norio Ozaki
  • , Masaomi Iyo
  • , Nakao Iwata
  • , Mitsuhiko Yamada
  • , Ichiro Sora
  • , Chih Ken Chen
  • , Hsing Cheng Liu
  • , Hiroshi Ujike
  • , Shih Ku Lin
  • National Institutes of Health
  • Molecular Neurobiology
  • National Center of Neurology and Psychiatry Kodaira
  • Kurume University
  • Hamamatsu University School of Medicine
  • Nagoya University
  • Teikyo University
  • Chiba University
  • Fujita Health University
  • Showa Medical University
  • Tohoku University
  • Taipei City Hospital
  • Okayama University

Research output: Contribution to journal › Journal Article › peer-review

124 Scopus citations

Abstract

Context: We can improve understanding of human methamphetamine dependence, and possibly our abilities to prevent and treat this devastating disorder, by identifying genes whose allelic variants predispose to methamphetamine dependence. Objective: To find "methamphetamine dependence" genes identified by each of 2 genome-wide association (GWA) studies of independent samples of methamphetamine-dependent individuals and matched controls. Design: Replicated GWA results in each of 2 casecontrol studies. Setting: Japan and Taiwan. Participants: Individuals with methamphetamine dependence and matched control subjects free from psychiatric, substance abuse, or substance dependence diagnoses (N=580). Main Outcome Measures: "Methamphetamine dependence" genes that were reproducibly identified by clusters of nominally positive single-nucleotide polymorphisms (SNPs) in both samples in ways that were unlikely to represent chance observations, based on Monte Carlo simulations that corrected for multiple comparisons, and subsets of "methamphetamine dependence" genes that were also identified by GWA studies of dependence on other addictive substances, success in quitting smoking, and memory. Results: Genes identified by clustered nominally positive SNPs from both samples were unlikely to represent chance observations (Monte Carlo P<.00001). Variants in these "methamphetamine dependence" genes are likely to alter cell adhesion, enzymatic functions, transcription, cell structure, and DNA, RNA, and/or protein handling or modification. Cell adhesion genes CSMD1 and CDH13 displayed the largest numbers of clustered nominally positive SNPs. "Methamphetamine dependence" genes overlapped, to extents much greater than chance, with genes identified in GWA studies of dependence on other addictive substances, success in quitting smoking, and memory (Monte Carlo P range <.04 to <.00001). Conclusion: These data support polygenic contributions to methamphetamine dependence from genes that include those whose variants contribute to dependence on several addictive substances, success in quitting smoking, and mnemonic processes.

Original languageEnglish
Pages (from-to)345-385
Number of pages41
JournalArchives of General Psychiatry
Volume65
Issue number3
DOIs
StatePublished - 03 2008

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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