Characteristics of the different HIV-1 risk populations based on the genetic transmission network of the newly diagnosed HIV cases in Jiangsu, Eastern China

Ying Zhou; Jing Lu; Zhi Zhang; Qi Sun; Xiaoqin Xu; Haiyang Hu

doi:10.1016/j.heliyon.2023.e22927

Characteristics of the different HIV-1 risk populations based on the genetic transmission network of the newly diagnosed HIV cases in Jiangsu, Eastern China

Heliyon. 2023 Nov 28;9(12):e22927. doi: 10.1016/j.heliyon.2023.e22927. eCollection 2023 Dec.

Authors

Ying Zhou¹, Jing Lu¹, Zhi Zhang¹, Qi Sun¹, Xiaoqin Xu¹, Haiyang Hu¹

Affiliation

¹ Institute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.

Abstract

Introduction: The HIV-1 prevalence has been steadily increasing in Jiangsu, China. HIV-1 genetic transmission network can be used to explore the transmission kinetics and precision intervention in high-risk populations. Thus, we generated an HIV-1 genetic transmission network, explored key risk populations based on different risk factors and found out the risk factors for HIV-1 prevention and control among the newly-diagnosed HIV-1 cases from 2017 to 2018.

Method: We amplified the HIV-1 pol sequences from the plasma samples of the newly-diagnosed HIV-1 cases from 2017 to 2018 and obtained the infection data from The National HIV/AIDS Surveillance System. HIV-Trace and Cytoscape Software were both used to construct the HIV-1 genetic network with a gene distance of <0.005. The R software was used to analyze the risk factors for inclusion into the network.

Results: We obtained 3362 sequences with the pol gene region, of which 3316 contained detailed individual information. CRF01_AE accounted for 42.3 % of the HIV-1 subtypes in the samples. The median CD4⁺T lymphocyte count was 329 cells/μL in 2017 and 313 cells/μL in 2018. At the gene distance threshold of 0.005, 481 sequences were incorporated into the HIV-1 gene network, constructing 202 clusters. Age over 60 years old, heterosexual transmission route, subtype (CRF105_0107, CRF55_01 B, and CRF67_01 B) and CD4⁺T lymphocyte count (>200) were the risk factors influencing inclusion into the HIV-1 gene network. Moreover, south Jiangsu cities had higher inclusion in the network. Thus, key risk populations in the clusters with different transmission routes, new emerging subtypes, drug resistance nodes, and individuals above 60 years of age in the network represented the critical risk populations that should be focused more on for intervention.

Conclusion: The HIV-1 genetic transmission network is adept at discovering undiagnosed HIV-infected cases and linking all diagnosed cases for determination of risk infections. Therefore we should pay more attention to these risk infections with further investigation and intervention, helping to achieve the goal of 95 % use combination prevention from the World Health Organization, and push to end AIDS epidemic.

Keywords: Genetic transmission network; HIV-1; Newly-diagnosed; Risk population.