已发表论文

云南布朗族重要药物基因变异的遗传多态性

 

Authors Wang Y, Peng L, Lu H, Zhang Z, Xing S, Li D, He C, Jin T, Wang L 

Received 8 July 2021

Accepted for publication 10 November 2021

Published 17 December 2021 Volume 2021:14 Pages 1647—1660

DOI https://doi.org/10.2147/PGPM.S327313

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Martin H Bluth

Background: We aimed to enrich the pharmacogenomic information of a Blang population (BP) from Yunnan Province in China.
Methods: We genotyped 55 very important pharmacogene (VIP) variants from the PharmGKB database and compared their genotype distribution (GD) in a BP with that of 26 populations by the χ 2 test. The minor allele frequency (MAF) distribution of seven significantly different single-nucleotide polymorphisms (SNPs) was conducted to compare the difference between the BP and 26 other populations.
Results: Compared with the GD of 55 loci in the BP, among 26 studied populations, GWD, YRI, GIH, ESN, MSL, TSI, PJL, ACB, FIN and IBS were the top-10 populations, which showed a significantly different GD > 35 loci. CHB, JPT, CDX, CHS, and KHV populations had a significantly different GD < 20 loci. A GD difference of 27– 34 loci was found between the BP and 11 populations (LWK, CEU, ITU, STU, PUR, CLM, GBR, ASW, BEB, MXL and PEL). The GD of five loci (rs750155 (SULT1A1 ), rs4291 (ACE), rs1051298 (SLC19A1 ), rs1131596 (SLC19A1 ) and rs1051296 (SLC19A1 )) were the most significantly different in the BP as compared with that of the other 26 populations. The genotype frequency of rs1800764 (ACE ) and rs1065852 (CYP2D6 ) was different in all populations except for PEL and LWK, respectively. MAFs of rs1065852 (CYP2D6 ) and rs750155 (SULT1A1 ) showed the largest fluctuation between the BP and SAS, EUR, AFR and AMR populations.
Conclusion: Our data can provide theoretical guidance for safe and efficacious personalized drug use in the Blang population.
Keywords: Blang population, single-nucleotide polymorphism, SNP, very important pharmacogene, genotype distribution, pharmacogenomics, personalized drug use