4.7 Article

Genome-Wide Association Study of Opioid Dependence: Multiple Associations Mapped to Calcium and Potassium Pathways

Journal

BIOLOGICAL PSYCHIATRY
Volume 76, Issue 1, Pages 66-74

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.biopsych.2013.08.034

Keywords

Calcium signaling; complex traits; convergence; genome-wide association; opioid dependence; potassium

Funding

  1. NIH Genes
  2. Environment and Health Initiative (GEI) [U01 HG004422]
  3. Gene Environment Association Studies (GENEVA) under GEI
  4. GENEVA Coordinating Center [U01 HG004446]
  5. Collaborative Study on the Genetics of Alcoholism (COGA) [U10 AA008401]
  6. Collaborative Genetic Study of Nicotine Dependence (COGEND) [P01 CA089392]
  7. Family Study of Cocaine Dependence (FSCD) [R01 DA013423]
  8. NIH GEI [U01HG004438]
  9. National Institute on Alcohol Abuse and Alcoholism
  10. National Institute on Drug Abuse
  11. NIH contract High throughput genotyping for studying the genetic contributions to human disease [HHSN268200782096C]
  12. Genetics and Environment (SAGE)

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Background: We report a genome-wide association study (GWAS) of two populations, African-American and European-American (AA, EA) for opioid dependence (OD) in three sets of subjects, to identify pathways, genes, and alleles important in OD risk. Methods: The design employed three phases (on the basis of separate sample collections). Phase 1 included our discovery GWAS dataset consisting of 5697 subjects (58% AA) diagnosed with opioid and/or other substance dependence and control subjects. Subjects were genotyped with the Illumina OmniQuad microarray, yielding 890,000 single nucleotide polymorphisms (SNPs) suitable for analysis. Additional genotypes were imputed with the 1000 Genomes reference panel. Top-ranked findings were further evaluated in Phase 2 by incorporating information from the publicly available Study of Addiction: Genetics and Environment dataset, with GWAS data from 4063 subjects (32% AA). In Phase 3, the most significant SNPs from Phase 2 were genotyped in 2549 independent subjects (32% AA). Analyses were performed with case-control and ordinal trait designs. Results: Most significant results emerged from the AA subgroup. Genome-wide-significant associations (p < 5.0 x 10(-8)) were observed with SNPs from multiple loci-KCNG2*rs62103177 was most significant after combining results from datasets in every phase of the study. The most compelling results were obtained with genes involved in potassium signaling pathways (e.g., KCNC1 and KCNG2). Pathway analysis also implicated genes involved in calcium signaling and long-term potentiation. Conclusions: This is the first study to identify risk variants for OD with GWAS. Our results strongly implicate risk pathways and provide insights into novel therapeutic and prevention strategies and might biologically bridge OD and other non-substance dependence psychiatric traits where similar pathways have been implicated.

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