標題: A new method for post Genome-Wide Association Study (GWAS) analysis of colorectal cancer in Taiwan
作者: Wang, Hwei-Ming
Chang, Tzu-Hao
Lin, Feng-Mao
Chao, Te-Hsin
Huang, Wei-Chih
Liang, Chao
Chu, Chao-Fang
Chiu, Chih-Min
Wu, Wei-Yun
Chen, Ming-Cheng
Weng, Chen-Tsung
Weng, Shun-Long
Chiang, Feng-Fan
Huang, Hsien-Da
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
關鍵字: Genome-Wide Association Studies;GWAS;Single-nucleotide polymorphism;SNP;Colorectal cancer;Risk prediction
公開日期: 10-Apr-2013
摘要: Recently, single nucleotide polymorphisms (SNPs) located in specific loci or genes have been identified associated with susceptibility to colorectal cancer (CRC) in Genome-Wide Association Studies (GWAS). However, in different ethnicities and regions, the genetic variations and the environmental factors can widely vary. Therefore, here we propose a post-GWAS analysis method to investigate the CRC susceptibility SNPs in Taiwan by conducting a replication analysis and bioinformatics analysis. One hundred and forty-four significant SNPs from published GWAS results were collected by a literature survey, and two hundred and eighteen CRC samples and 385 normal samples were collected for post-GWAS analysis. Finally, twenty-six significant SNPs were identified and reported as associated with susceptibility to colorectal cancer, other cancers, obesity, and celiac disease in a previous GWAS study. Functional analysis results of 26 SNPs indicate that most biological processes identified are involved in regulating immune responses and apoptosis. In addition, an efficient prediction model was constructed by applying Jackknife feature selection and ANOVA testing. As compared to another risk prediction model of CRC for European Caucasians population, which performs 0.616 of AUC by using 54 SNPs, the proposed model shows good performance in predicting CRC risk within the Taiwanese population, i.e., 0.724 AUC by using 16 SNPs. We believe that the proposed risk prediction model is highly promising for predicting CRC risk within the Taiwanese population. In addition, the functional analysis results could be helpful to explore the potential associated regulatory mechanisms that may be involved in CRC development. (c) 2012 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/j.gene.2012.11.067
http://hdl.handle.net/11536/21324
ISSN: 0378-1119
DOI: 10.1016/j.gene.2012.11.067
期刊: GENE
Volume: 518
Issue: 1
起始頁: 107
結束頁: 113
Appears in Collections:Conferences Paper


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