Zhang C, Jiang X, Chen W, Li Q, Yun F, Yang X, Dai R, Cheng Y. Population genetic difference of pharmacogenomic VIP gene variants in the Lisu population from Yunnan Province.
Medicine (Baltimore) 2018;
97:e13674. [PMID:
30593137 PMCID:
PMC6314765 DOI:
10.1097/md.0000000000013674]
[Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
Individual differences in drug clinical response are related to pharmacogenomics. The genetic variation of drug-metabolizing enzymes, drug receptors, and their downstream protein genes is the main factor causing individual differences in drug response. The genetic backgrounds among different ethnic groups are quite different. In this study, we aimed to detect the distribution difference of genotype frequency in very important pharmacogenetic (VIP) gene variants in the Lisu.Using the chi-squared test, we compared the genotype frequencies of the VIP variants in 105 Lisu people with those in 26 populations from the 1000 Genome project separately. Bonferroni's multiple adjustment was also conducted (P < .05/(26*49)). Moreover, Arlequin v3.5 and Structure v2.3.4 software were used to analyze the genetic distance and genetic structure.There were 9, 9, 11, 12, 11, 11, 9, 17, 13, 13, 16, 5, 3, 5, 3, 4, 17, 14, 16, 17, 16, 10, 13, 12, 10, and 9 single nucleotide polymorphisms that differed in frequency distribution, when Lisu people compared with the 26 populations separately. Only CYP2E1 rs2070676 was different in the Lisu population compared with the 26 groups from the 1000 Genome project. PTGS2 rs5275 and CYP2D6 rs1065852 were different in the Lisu population compared with most of the populations. Additionally, genetic backgrounds of Lisu and Han Chinese in Beijing were closest according to the lowest F-statistics value and resemblance in genetic structures.Our results complete the information of the Lisu population in pharmacogenomics database.
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