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Pooled association genome scanning for alcohol dependence using 104,268 SNPs: Validation and use to identify alcoholism vulnerability loci in unrelated individuals from the collaborative study on the genetics of alcoholism
Author(s) -
Johnson Catherine,
Drgon Tomas,
Liu QingRong,
Walther Donna,
Edenberg Howard,
Rice John,
Foroud Tatiana,
Uhl George R.
Publication year - 2006
Publication title -
american journal of medical genetics part b: neuropsychiatric genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.393
H-Index - 126
eISSN - 1552-485X
pISSN - 1552-4841
DOI - 10.1002/ajmg.b.30346
Subject(s) - alcohol dependence , genetics , single nucleotide polymorphism , snp , biology , genome wide association study , allele , pedigree chart , allele frequency , gene , alcohol , genotype , biochemistry
Abstract Association genome scanning can identify markers for the allelic variants that contribute to vulnerability to complex disorders, including alcohol dependence. To improve the power and feasibility of this approach, we report validation of “100k” microarray‐based allelic frequency assessments in pooled DNA samples. We then use this approach with unrelated alcohol‐dependent versus control individuals sampled from pedigrees collected by the Collaborative Study on the Genetics of Alcoholism (COGA). Allele frequency differences between alcohol‐dependent and control individuals are assessed in quadruplicate at 104,268 autosomal SNPs in pooled samples. One hundred eighty‐eight SNPs provide (1) the largest allele frequency differences between dependent versus control individuals; (2) t values ≥ 3 for these differences; and (3) clustering, so that 51 relatively small chromosomal regions contain at least three SNPs that satisfy criteria 1 and 2 above (Monte Carlo P = 0.00034). These positive SNP clusters nominate interesting genes whose products are implicated in cellular signaling, gene regulation, development, “cell adhesion,” and Mendelian disorders. The results converge with linkage and association results for alcohol and other addictive phenotypes. The data support polygenic contributions to vulnerability to alcohol dependence. These SNPs provide new tools to aid the understanding, prevention, and treatment of alcohol abuse and dependence. © 2006 Wiley‐Liss, Inc.