Dataset Information

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.

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 >or= 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.

SUBMITTER: Johnson C

PROVIDER: S-EPMC3922200 | biostudies-literature | 2006 Dec

REPOSITORIES: biostudies-literature

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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.

Johnson Catherine C Drgon Tomas T Liu Qing-Rong QR Walther Donna D Edenberg Howard H Rice John J Foroud Tatiana T Uhl George R GR

American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 20061201 8

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). A ...[more]

PMID: 16894614

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Project description:BackgroundClassical genetic studies indicate that nicotine dependence is a substantially heritable complex disorder. Genetic vulnerabilities to nicotine dependence largely overlap with genetic vulnerabilities to dependence on other addictive substances. Successful abstinence from nicotine displays substantial heritable components as well. Some of the heritability for the ability to quit smoking appears to overlap with the genetics of nicotine dependence and some does not. We now report genome wide association studies of nicotine dependent individuals who were successful in abstaining from cigarette smoking, nicotine dependent individuals who were not successful in abstaining and ethnically-matched control subjects free from substantial lifetime use of any addictive substance.ResultsThese data, and their comparison with data that we have previously obtained from comparisons of four other substance dependent vs control samples support two main ideas: 1) Single nucleotide polymorphisms (SNPs) whose allele frequencies distinguish nicotine-dependent from control individuals identify a set of genes that overlaps significantly with the set of genes that contain markers whose allelic frequencies distinguish the four other substance dependent vs control groups (p < 0.018). 2) SNPs whose allelic frequencies distinguish successful vs unsuccessful abstainers cluster in small genomic regions in ways that are highly unlikely to be due to chance (Monte Carlo p < 0.00001).ConclusionThese clustered SNPs nominate candidate genes for successful abstinence from smoking that are implicated in interesting functions: cell adhesion, enzymes, transcriptional regulators, neurotransmitters and receptors and regulation of DNA, RNA and proteins. As these observations are replicated, they will provide an increasingly-strong basis for understanding mechanisms of successful abstinence, for identifying individuals more or less likely to succeed in smoking cessation efforts and for tailoring therapies so that genotypes can help match smokers with the treatments that are most likely to benefit them.

Dataset Information

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.

Publications

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.

Similar Datasets

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