Phenotype prediction of deleterious nonsynonymous single nucleotide polymorphisms in human alcohol metabolism-related genes: a bioinformatics study

Wang, Lin-Lin; Yang, An-Kui; Li, Yong; Liu, Jun-Ping; Zhou, Shu-Feng

doi:10.1016/j.alcohol.2010.05.009

« Previous Next »Alcohol
Volume 44, Issue 5 , Pages 425-438, August 2010

Phenotype prediction of deleterious nonsynonymous single nucleotide polymorphisms in human alcohol metabolism-related genes: a bioinformatics study

Lin-Lin Wang
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100191, China
- Institute of Reproductive and Child Health, Peking University, Beijing 100191, China
- These two authors contributed equally to this work.
An-Kui Yang
- Department of Head and Neck Surgery, Cancer Center, Sun Yat-sen University, Guangzhou 510060, China
- State Key Laboratory of Oncology in South China, Cancer Center, Sun Yat-sen University, Guangzhou 510060, China
- These two authors contributed equally to this work.
Yong Li
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100191, China
- Corresponding author. Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100083, P. R. China. Tel.: +86-10-8280-1177; fax: +86-10-8280-1177.
Jun-Ping Liu
- Department of Immunology, Central and Eastern Clinical School, Monash University, Prahran, Victoria 3181, Australia
Shu-Feng Zhou
- School of Health Sciences & Health Innovations Research Institute, RMIT University, Bundoora, Victoria 3083, Australia
- Corresponding author. School of Health Sciences & Health Innovations Research Institute, RMIT University, PO Box 71, Bundoora, Victoria 3083, Australia. Tel.: +61-3-9925-7794; fax: +61-3-9925-7178.

Received 27 November 2009; received in revised form 16 May 2010; accepted 16 May 2010. published online 21 June 2010.

Abstract

Nonsynonymous single nucleotide polymorphisms (nsSNPs) are thought as potential disease modifiers because they alter the encoded amino acid sequence and are likely to affect the function of the proteins accounting for susceptibility to disease. Distinguishing the functionally significant nsSNPs from tolerant nsSNPs is helpful to characterize the genetic basis of human diseases and assess individual susceptibility to diseases. Many nsSNPs have been found in alcohol metabolism-related genes but there is poor knowledge on the relationship between the genotype and phenotype of nsSNPs in these genes. In this study, we have identified a total of 203 nsSNPs in 29 human alcohol metabolism-related genes from the National Center for Biotechnology Information (NCBI) dbSNP and SWISS-Prot databases. Using the PolyPhen and SIFT algorithms, 43% of nsSNPs in alcohol metabolism-related genes were predicted to have functional impacts on protein function with a significant concordance of the prediction results between the two algorithms. The prediction accuracy is about 77–81% of all the nsSNPs based on the results of in vivo and in vitro studies. These amino acid substitutions are supposed to be the pathogenetic basis for the alteration of metabolism enzyme activity and the association with disease susceptivity. The phenotype of nsSNPs predicted as deleterious needs to be clarified in further studies and the prediction of nsSNPs in human alcohol metabolism-related genes would be useful hints for further genotype–phenotype studies on the individual difference in susceptivity to alcohol-related diseases.

Keywords: Alcohol metabolism, Bioinformatics, Phenotype, Single nucleotide polymorphisms