4.7 Article

Higher order addiction molecular genetics: Convergent data from genome-wide association in humans and mice

期刊

BIOCHEMICAL PHARMACOLOGY
卷 75, 期 1, 页码 98-111

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.bcp.2007.06.042

关键词

association genome scanning; substance dependence; microarray; pooled; neuronal connections

资金

  1. Intramural NIH HHS [Z01 DA000492-02, Z01 DA000165-12, Z01 DA000401-10] Funding Source: Medline
  2. NIAAA NIH HHS [R29 AA011114, AA011114, R01 AA011114, P60 AA010760, AA10760] Funding Source: Medline
  3. NIDA NIH HHS [DA05228, R01 DA005228] Funding Source: Medline
  4. NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM [R29AA011114, P50AA010760, R01AA011114, P60AA010760] Funding Source: NIH RePORTER
  5. NATIONAL INSTITUTE ON DRUG ABUSE [Z01DA000165, R01DA005228, Z01DA000401, Z01DA000492] Funding Source: NIH RePORTER

向作者/读者索取更多资源

Family, adoption and twin data each support substantial heritability for addictions. Most of this heritable influence is not substance-specific. The overlapping genetic vulnerability for developing dependence on a variety of addictive substances suggests large roles for higher order pharamacogenomics in addiction molecular genetics. We and others have now completed genome-wide association (GWA) studies of DNAs from individuals with dependence on a variety of addictive substances versus appropriate controls. Recently reported replicated GWA observations identify a number of genes based on comparisons between controls and European-American and African-American polysubstance abusers. Here we review the convergence between these results and data that compares control samples and (a) alcohol-dependent European-Americans, (b) methamphetamine-dependent Asians and (c) nicotine dependent samples from European backgrounds. We also compare these human data to quantitative trait locus (QTL) results from studies of addiction-related phenotypes in mice that focus on alcohol, methamphetamine and barbiturates. These comparisons support a genetic architecture built from largely polygenic contributions of common allelic variants to dependence on a variety of legal and illegal substances. Many of the gene variants identified in this way are likely to alter specification and maintenance of neuronal connections. Published by Elsevier Inc.

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