HIV subtypes and cellular tropism of newly reported infections in Qinzhou, Guangxi, 2017–2019

  Objective   To understand the HIV genotypes, drug resistance and cell tropism in newly reported HIV infection cases in Qinzhou of Guangxi from 2017 to 2019.

  Methods   Newly reported HIV infection cases reported in Qinzhou from 2017 to 2019 were selected. The number of CD4⁺ T lymphocytes in blood samples collected from the cases were detected. The pol and env gene regions of HIV virus were amplified and sequenced. Phylogenetic trees were constructed to determine gene subtypes. The Stanford Drug Resistance Database was used to determine drug resistance. Geno2pheno was used to determine tropism. The difference in number of CD4⁺ T lymphocytes among the cases infected with the viruses of different subtypes and different tropisms were analyzed.

  Results   Among the 764 newly reported HIV infection cases, the cases infected with the viruses of subtype CRF01_AE, CRF08_BC, and CRF07_BC accounted for 50.1% (383/764), 31.2% (238/764), and 10.9% (83/764). The cases with first cluster (Cluster1) and the second cluster (Cluster2) in the cases infected with HIV of CRF01_AE accounted for 18.3% (70/383) and 72.3% (277/383). In the newly reported HIV infection cases, 48 had drug resistance before treatment, the drug resistance rate was 6.3%. The cases with CD4⁺ T lymphocytes less than 200 accounted for 51.4%. The median M (P₂₅, P₇₅) of CD4⁺ T lymphocytes in the cases infected with the viruses of subtype CRF01_AE, CRF08_BC and CRF07_BC were 205(41, 303), 238(105, 336), 308(179, 394), and the levels were not all equal (P<0.0001). Coreceptor utilization prediction indicated that 108 cases were CXCR4 and 656 cases were CCR5. The number of CD4⁺ T lymphocytes in the cases with X4 tropism was significantly lower than that in the cases with R5 tropism.

  Conclusion   There were multiple virus subtypes in newly reported HIV infection cases in Qinzhou from 2017 to 2019, and the level of drug resistance before treatment was high. The predictive analysis of virus tropism will facilitate the targeted prevention and treatment of HIV infection.