genomic regions identified by overlapping clusters of nominally-positive snps from genome-wide studies of alcohol and illegal substance dependence的基因组区域的重叠集群nominally-positive从全基因组单核苷酸多态性的研究酒精和非法药物依赖.pdfVIP

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2017-09-01 发布于上海
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genomic regions identified by overlapping clusters of nominally-positive snps from genome-wide studies of alcohol and illegal substance dependence的基因组区域的重叠集群nominally-positive从全基因组单核苷酸多态性的研究酒精和非法药物依赖.pdf

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genomic regions identified by overlapping clusters of nominally-positive snps from genome-wide studies of alcohol and illegal substance dependence的基因组区域的重叠集群nominally-positive从全基因组单核苷酸多态性的研究酒精和非法药物依赖

Genomic Regions Identified by Overlapping Clusters of Nominally-Positive SNPs from Genome-Wide Studies of Alcohol and Illegal Substance Dependence Catherine Johnson, Tomas Drgon, Donna Walther, George R. Uhl* Molecular Neurobiology Branch, National Institutes of Health, Intramural Research Program, National Institutes on Drug Abuse, Baltimore, Maryland, United States of America Abstract Declaring ‘‘replication’’ from results of genome wide association (GWA) studies is straightforward when major gene effects provide genome-wide significance for association of the same allele of the same SNP in each of multiple independent samples. However, such unambiguous replication is unlikely when phenotypes display polygenic genetic architecture, allelic heterogeneity, locus heterogeneity and when different samples display linkage disequilibria with different fine structures. We seek chromosomal regions that are tagged by clustered SNPs that display nominally-significant association in each of several independent samples. This approach provides one ‘‘nontemplate’’ approach to identifying overall replication of groups of GWA results in the face of difficult genetic architectures. We apply this strategy to 1 M SNP GWA results for dependence on: a) alcohol (including many individuals with dependence on other addictive substances) and b) at least one illegal substance (including many individuals dependent on alcohol). This approach provides high confidence in rejecting the null hypothesis that chance alone accounts for the extent to which clustered, nominally-significant SNPs from samples of the same racial/ethnic background identify the same sets of chromosomal regions. It identifies several genes that are also reported in other independent alcohol-dependence GWA datasets. There is more modest confidence in: a) identification of i