title: Common biological networks underlie genetic risk for alcoholism in African- and European-American populations.
abstract: Alcohol dependence (AD) is a heritable substance addiction with adverse physical and psychological consequences, representing a major health and economic burden on societies worldwide. Genes thus far implicated via linkage, candidate gene and genome-wide association studies (GWAS) account for only a small fraction of its overall risk, with effects varying across ethnic groups. Here we investigate the genetic architecture of alcoholism and report on the extent to which common, genome-wide SNPs collectively account for risk of AD in two US populations, African-Americans (AAs) and European-Americans (EAs). Analyzing GWAS data for two independent case-control sample sets, we compute polymarker scores that are significantly associated with alcoholism (P = 1.64 × 10(-3) and 2.08 × 10(-4) for EAs and AAs, respectively), reflecting the small individual effects of thousands of variants derived from patterns of allelic architecture that are population specific. Simulations show that disease models based on rare and uncommon causal variants (MAF < 0.05) best fit the observed distribution of polymarker signals. When scoring bins were annotated for gene location and examined for constituent biological networks, gene enrichment is observed for several cellular processes and functions in both EA and AA populations, transcending their underlying allelic differences. Our results reveal key insights into the complex etiology of AD, raising the possibility of an important role for rare and uncommon variants, and identify polygenic mechanisms that encompass a spectrum of disease liability, with some, such as chloride transporters and glycine metabolism genes, displaying subtle, modifying effects that are likely to escape detection in most GWAS designs.
authors.affiliation: Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA. markz@txbiomedgenetics.org
authors.forename: M Z
authors.initials: MZ
authors.lastname: Kos
authors.forename: J
authors.initials: J
authors.lastname: Yan
authors.forename: D M
authors.initials: DM
authors.lastname: Dick
authors.forename: A
authors.initials: A
authors.lastname: Agrawal
authors.forename: K K
authors.initials: KK
authors.lastname: Bucholz
authors.forename: J P
authors.initials: JP
authors.lastname: Rice
authors.forename: E O
authors.initials: EO
authors.lastname: Johnson
authors.forename: M
authors.initials: M
authors.lastname: Schuckit
authors.forename: S
authors.initials: S
authors.lastname: Kuperman
authors.forename: J
authors.initials: J
authors.lastname: Kramer
authors.forename: A M
authors.initials: AM
authors.lastname: Goate
authors.forename: J A
authors.initials: JA
authors.lastname: Tischfield
authors.forename: T
authors.initials: T
authors.lastname: Foroud
authors.forename: J
authors.initials: J
authors.lastname: Nurnberger
authors.forename: V
authors.initials: V
authors.lastname: Hesselbrock
authors.forename: B
authors.initials: B
authors.lastname: Porjesz
authors.forename: L J
authors.initials: LJ
authors.lastname: Bierut
authors.forename: H J
authors.initials: HJ
authors.lastname: Edenberg
authors.forename: L
authors.initials: L
authors.lastname: Almasy
mesh_terms: D000328:Adult; D001741:Black or African American / Q000235:genetics*; D000437:Alcoholism / Q000208:ethnology / Q000235:genetics*; D005260:Female; D053263:Gene Regulatory Networks; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D011110:Polymorphism, Genetic; D014481:United States; D044465:White People / Q000235:genetics*