IntroductionThe specificity of drug therapy in individuals and races has promoted the development and improvement of pharmacogenomics and precision medicine. While there is a few cognition on the minorities in China, especially in Lisu nationality from the Yunnan Province. Therefore, we performed the research to improve the role of pharmacogenomics in the Lisu population from the Yunnan province of China.Materials and MethodsIn our study, 54 variants of very important pharmacogenes (VIPs) selected from the PharmGKB database were genotyped in 199 unrelated and healthy Lisu adults from the Yunnan province of China, and then, genotyping data wtih χ2 test were analyzed.ResultsWe compared our date with those of other 26 populations from the 1000 Genomes Project, and acquired that the Lisu ethnicity is similar with the CDX(Chinese Dai in Xishuangbanna, China) and CHS(Southern Han Chinese, China). Furthermore, rs776746 (CYP3A5), rs1805123 (KCNH2), rs4291 (ACE), rs1051298 (SLC19A1) and rs1065852 (CYP2D6) were deemed as the most varying loci. The MAF of “G” at rs1805123 (KCNH2) in the Lisu population was the largest with the value of 51.0%.ConclusionsOur results show that there are significant differences in SNP (single nucleotide polymorphism) loci, supplementing the pharmacogenomic information of the Lisu population in Yunnan province, China, and can provide a theoretical basis for individualized medication in the future.

Aim: Interindividual and interethnic differences in drug efficacy drive the development and progress of pharmacogenomics and precision medicine. This study was performed to enrich the pharmacogenomic information for the Lisu population from China. Methods: Fifty-four very important pharmacogene variants were selected from PharmGKB and genotyped in 199 Lisu individuals. The genotype distribution data of 26 populations were downloaded from the 1000 Genomes Project and analyzed with the χ2 test. Results: Among the 26 populations in the 1000 Genomes Project, African Caribbeans in Barbados; Esan in Nigeria; Gambian in Western Divisions, The Gambia; Luhya in Webuye, Kenya; Yoruba in Ibadan; Finnish in Finland; Toscani in Italy and Sri Lankan Tamil in the UK were the top eight nationalities with the most significant differences in genotype distribution from the Lisu population. The loci of CYP3A5 rs776746, KCNH2 rs1805123, ACE rs4291, SLC19A1 rs1051298 and CYP2D6 rs1065852 were significantly different in the Lisu. Conclusion: The results showed that there were substantial differences in SNPs of very important pharmacogene variants, which can provide a theoretical basis for individualized drug use for the Lisu.

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.