4.7 Article

Molecular Genetics of Addiction and Related Heritable Phenotypes Genome-Wide Association Approaches Identify Connectivity Constellation and Drug Target Genes with Pleiotropic Effects

Journal

ADDICTION REVIEWS 2008
Volume 1141, Issue -, Pages 318-381

Publisher

WILEY-BLACKWELL
DOI: 10.1196/annals.1441.018

Keywords

pleiotropic; cell adhesion; Monte Carlo

Funding

  1. EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH &HUMAN DEVELOPMENT [N01HD013138] Funding Source: NIH RePORTER
  2. NATIONAL CANCER INSTITUTE [P50CA084718, P50CA084719, R01CA063562] Funding Source: NIH RePORTER
  3. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL051429, R01HL032318] Funding Source: NIH RePORTER
  4. NATIONAL INSTITUTE ON DRUG ABUSE [ZIADA000401, R01DA008511, ZIADA000492, K08DA014276, Z01DA000537, Z01DA000165] Funding Source: NIH RePORTER
  5. Intramural NIH HHS [Z01 DA000492-03, Z01 DA000401-10, Z01 DA000165-12, Z01 DA000537-02] Funding Source: Medline
  6. NCI NIH HHS [P50 CA/DA84718, P50 CA084719, R01 CA63562, P50 CA84719, R01 CA063562] Funding Source: Medline
  7. NHLBI NIH HHS [HL32318, HL51429] Funding Source: Medline
  8. NICHD NIH HHS [N01 HD13138] Funding Source: Medline
  9. NIDA NIH HHS [1K08 DA14276-05, DA08511, K08 DA014276] Funding Source: Medline
  10. Wellcome Trust [076113] Funding Source: Medline

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Genome-wide association (GWA) can elucidate molecular genetic bases for human individual differences in complex phenotypes that include vulnerability to addiction. Here, we review (a) evidence that supports polygenic models with (at least) modest heterogeneity for the genetic architectures of addiction and several related phenotypes; (b) technical and ethical aspects of importance for understanding GWA data, including genotyping in individual samples versus DNA pools, analytic approaches, power estimation, and ethical issues in genotyping individuals with illegal behaviors; (c) the samples and the data that shape our current understanding of the molecular genetics of individual differences in vulnerability to substance dependence and related phenotypes; (d) overlaps between GWA data sets for dependence on different substances; and (e) overlaps between GWA data for addictions versus other heritable, brain-based phenotypes that include bipolar disorder, cognitive ability, frontal lobe brain volume, the ability to successfully quit smoking, neuroticism, and Alzheimer's disease. These convergent results identify potential targets for drugs that might modify addictions and play roles in these other phenotypes. They add to evidence that individual differences in the quality and quantity of brain connections make pleiotropic contributions to individual differences in vulnerability to addictions and to related brain disorders and phenotypes. A connectivity constellation of brain phenotypes and disorders appears to receive substantial pathogenic contributions from individual differences in a constellation of genes whose variants provide individual differences in the specification of brain connectivities during development and in adulthood. Heritable brain differences that underlie addiction vulnerability thus lie squarely in the midst of the repertoire of heritable brain differences that underlie vulnerability to other common brain disorders and phenotypes.

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