Objective To understand the characteristics of drug resistance and molecular network transmission among pre-treatment human immunodeficiency virus-1(HIV-1)infected patients in Jilin province.Methods Two hundred and twenty-eight pre-treatment HIV infected patients in 2022 were recruited.Plasma RNA was extracted and pol gene fragment was amplified by reverse transcription-polymerase chain reaction(RT-PCR).The phylogenetic tree was reconstructed for subtype determination,drug-resistance mutations(DRMs)analysis.The molecular networks were constructed to evaluate the transmission relationship.Results Two hundred and six sequences were obtained successfully from the 228 samples.The main subtypes were CRF01_AE(60.68％,125/206),CRF07_BC(30.10％,62/206)and B(5.34％,11/206).The overall drug-resistance rate was 9.22％(19/206),and the DRMs were mainly associated with from non-nucleoside reverse transcriptase inhibitors(NNRTIs),accounting for 8.25％(17/206).Multivariable logistic regression analysis showed that the risk of drug resistance were higher in groups of 40-49 years old,≥50 years old and divorced or widowed individuals(P＜0.05).The infected people in Baicheng city and patients with CRF07_BC infection were more likely to access the network(P＜0.05).There were 63 sequences enrolled in the network and formed 23 molecular clusters(30.58％,63/206).Among the cases in the network,6 cases carried DRMs.There existed the"intra-city"and"inter-city"connection relationships and a mixing junction between heterosexual and homosexual transmission groups.Conclusions The drug resistance rate of pre-treatment HIV infected patients was at moderate level,and the virus strains clustered by geographical regions.The surveillance of drug resistance should be enhanced.The targeted intervention measures for the bridge-population should be applied to reduce the possibility of pre-treatment drug-resistance transmission.
关键词
艾滋病病毒/治疗前耐药/传播性耐药/分子网络
Key words
Human immunodeficiency virus/Pretreatment drug resistance/Transmitted drug resistance/Molecular network
维普
万方数据