Meta-analyses of genome-wide association data hold new promise for addiction genetics

Arpana Agrawal, Howard Edenberg, Joel Gelernter

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Meta-analyses of genome-wide association study data have begun to lead to promising new discoveries for behavioral and psychiatrically relevant phenotypes (e.g., schizophrenia, educational attainment). We outline how this methodology can similarly lead to novel discoveries in genomic studies of substance use disorders, and discuss challenges that will need to be overcome to accomplish this goal. We illustrate our approach with the work of the newly established Substance Use Disorders workgroup of the Psychiatric Genomics Consortium.

Original languageEnglish (US)
Pages (from-to)676-680
Number of pages5
JournalJournal of Studies on Alcohol and Drugs
Volume77
Issue number5
DOIs
StatePublished - Sep 1 2016

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schizophrenia
addiction
Substance-Related Disorders
Meta-Analysis
Genes
Genome
Genome-Wide Association Study
methodology
Genomics
Psychiatry
Schizophrenia
Phenotype
Genetics

ASJC Scopus subject areas

  • Health(social science)
  • Psychiatry and Mental health
  • Toxicology

Cite this

Meta-analyses of genome-wide association data hold new promise for addiction genetics. / Agrawal, Arpana; Edenberg, Howard; Gelernter, Joel.

In: Journal of Studies on Alcohol and Drugs, Vol. 77, No. 5, 01.09.2016, p. 676-680.

Research output: Contribution to journalArticle

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