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Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites
Alcoholism is a complex disease. As with other common diseases, genetic variants underlying alcoholism have been illusive, possibly due to the small effect from each individual susceptible variant, gene × environment and gene × gene interactions and complications in phenotype definition. We conducte...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866806/ https://www.ncbi.nlm.nih.gov/pubmed/16451589 http://dx.doi.org/10.1186/1471-2156-6-S1-S130 |
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author | Chen, Liang Liu, Nianjun Wang, Shuang Oh, Cheongeun Carriero, Nicholas J Zhao, Hongyu |
author_facet | Chen, Liang Liu, Nianjun Wang, Shuang Oh, Cheongeun Carriero, Nicholas J Zhao, Hongyu |
author_sort | Chen, Liang |
collection | PubMed |
description | Alcoholism is a complex disease. As with other common diseases, genetic variants underlying alcoholism have been illusive, possibly due to the small effect from each individual susceptible variant, gene × environment and gene × gene interactions and complications in phenotype definition. We conducted association tests, the family-based association tests (FBAT) and the backward haplotype transmission association (BHTA), on the Collaborative Study of the Genetics of Alcoholism (COGA) data provided by Genetic Analysis Workshop (GAW) 14. Efron's local false discovery rate method was applied to control the proportion of false discoveries. For FBAT, we compared the results based on different types of genetic markers (single-nucleotide polymorphisms (SNPs) versus microsatellites) and different phenotype definitions (clinical diagnoses versus electrophysiological phenotypes). Significant association results were found only between SNPs and clinical diagnoses. In contrast, significant results were found only between microsatellites and electrophysiological phenotypes. In addition, we obtained the association results for SNPs and microsatellites using COGA diagnosis as phenotype based on BHTA. In this case, the results for SNPs and microsatellites are more consistent. Compared to FBAT, more significant markers are detected with BHTA. |
format | Text |
id | pubmed-1866806 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18668062007-05-11 Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites Chen, Liang Liu, Nianjun Wang, Shuang Oh, Cheongeun Carriero, Nicholas J Zhao, Hongyu BMC Genet Proceedings Alcoholism is a complex disease. As with other common diseases, genetic variants underlying alcoholism have been illusive, possibly due to the small effect from each individual susceptible variant, gene × environment and gene × gene interactions and complications in phenotype definition. We conducted association tests, the family-based association tests (FBAT) and the backward haplotype transmission association (BHTA), on the Collaborative Study of the Genetics of Alcoholism (COGA) data provided by Genetic Analysis Workshop (GAW) 14. Efron's local false discovery rate method was applied to control the proportion of false discoveries. For FBAT, we compared the results based on different types of genetic markers (single-nucleotide polymorphisms (SNPs) versus microsatellites) and different phenotype definitions (clinical diagnoses versus electrophysiological phenotypes). Significant association results were found only between SNPs and clinical diagnoses. In contrast, significant results were found only between microsatellites and electrophysiological phenotypes. In addition, we obtained the association results for SNPs and microsatellites using COGA diagnosis as phenotype based on BHTA. In this case, the results for SNPs and microsatellites are more consistent. Compared to FBAT, more significant markers are detected with BHTA. BioMed Central 2005-12-30 /pmc/articles/PMC1866806/ /pubmed/16451589 http://dx.doi.org/10.1186/1471-2156-6-S1-S130 Text en Copyright © 2005 Chen et al; licensee BioMed Central Ltd http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Chen, Liang Liu, Nianjun Wang, Shuang Oh, Cheongeun Carriero, Nicholas J Zhao, Hongyu Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites |
title | Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites |
title_full | Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites |
title_fullStr | Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites |
title_full_unstemmed | Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites |
title_short | Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites |
title_sort | whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866806/ https://www.ncbi.nlm.nih.gov/pubmed/16451589 http://dx.doi.org/10.1186/1471-2156-6-S1-S130 |
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