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Molecular transmission network analysis of newly diagnosed HIV-1 infections in Nanjing from 2019 to 2021. | LitMetric

AI Article Synopsis

  • The study aimed to analyze molecular transmission networks and patterns of transmitted drug resistance (TDR) among newly diagnosed HIV-1 individuals in Nanjing from 2019 to 2021.
  • Researchers collected plasma samples, amplified the HIV pol gene, and used the sequences to determine TDR and identify viral subtypes, discovering multiple subtypes with CRF 07_BC and CRF01_AE being the most prevalent.
  • The study found a 7.84% TDR prevalence, identified 137 molecular transmission clusters, and noted that older, unemployed individuals with specific viral strains were more likely to be part of these clusters, indicating high local HIV transmission risk.

Article Abstract

Objective: The objective of this study was to conduct a comprehensive analysis of the molecular transmission networks and transmitted drug resistance (TDR) patterns among individuals newly diagnosed with HIV-1 in Nanjing.

Methods: Plasma samples were collected from newly diagnosed HIV patients in Nanjing between 2019 and 2021. The HIV pol gene was amplified, and the resulting sequences were utilized for determining TDR, identifying viral subtypes, and constructing molecular transmission network. Logistic regression analyses were employed to investigate the epidemiological characteristics associated with molecular transmission clusters.

Results: A total of 1161 HIV pol sequences were successfully extracted from newly diagnosed individuals, each accompanied by reliable epidemiologic information. The analysis revealed the presence of multiple HIV-1 subtypes, with CRF 07_BC (40.57%) and CRF01_AE (38.42%) being the most prevalent. Additionally, six other subtypes and unique recombinant forms (URFs) were identified. The prevalence of TDR among the newly diagnosed cases was 7.84% during the study period. Employing a genetic distance threshold of 1.50%, the construction of the molecular transmission network resulted in the identification of 137 clusters, encompassing 613 nodes, which accounted for approximately 52.80% of the cases. Multivariate analysis indicated that individuals within these clusters were more likely to be aged ≥ 60, unemployed, baseline CD4 cell count ≥ 200 cells/mm, and infected with the CRF119_0107 (P < 0.05). Furthermore, the analysis of larger clusters revealed that individuals aged ≥ 60, peasants, those without TDR, and individuals infected with the CRF119_0107 were more likely to be part of these clusters.

Conclusions: This study revealed the high risk of local HIV transmission and high TDR prevalence in Nanjing, especially the rapid spread of CRF119_0107. It is crucial to implement targeted interventions for the molecular transmission clusters identified in this study to effectively control the HIV epidemic.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11170874PMC
http://dx.doi.org/10.1186/s12879-024-09337-6DOI Listing

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