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• W2094825933 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." @default.
• W2094825933 created "2016-06-24" @default.
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• W2094825933 date "2010-08-01" @default.
• W2094825933 modified "2023-09-26" @default.
• W2094825933 title "Phenotype prediction of deleterious nonsynonymous single nucleotide polymorphisms in human alcohol metabolism-related genes: a bioinformatics study" @default.
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• W2094825933 doi "https://doi.org/10.1016/j.alcohol.2010.05.009" @default.
• W2094825933 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/20804942" @default.
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