Trends in HIV-1 pretreatment drug resistance and HIV-1 variant dynamics among antiretroviral therapy-naive Ethiopians from 2003 to 2018: a pooled sequence analysis

Distinct Clusters of HIV-1 CRF01_AE in Zhejiang, China: High-Risk Transmission Cluster 4 Requires Heightened Surveillance

Background

HIV-1 CRF01_AE is becoming the predominant HIV-1 subtype among patients in China. The distribution and characteristics of transmission clusters of HIV-1 CRF01_AE in Zhejiang, Eastern China remains unclear. This study analyzed the epidemiologic characteristics and transmission clusters of HIV-1 CRF01_AE in Zhejiang.

Methods

Plasma samples obtained from 152 patients of HIV-1 CRF01_AE not undergoing ART were used to amplify HIV-1 pol and env gene. CRF01_AE drug resistance mutations (DRM) prevalence was analysed using Stanford University's HIV Drug Resistance Database. A phylogenetic tree was constructed using FastTree (version 2.1.11) based on the GTR nucleotide substitution model and visualized using Figtree (version 1.4.4) and The Interactive Tree of Life; the Chinese HIV Gene Sequence Data Platform was used to construct genetic transmission networks.

Results

Majority samples could be grouped into CRF01_AE transmission Clusters 1 (11.2%), 4 (64.5%), and 5 (7.2%). The CD4+ T-cell counts in Cluster 1, 4a, 4b are lower than 5 were 15, 38, 30, and 248 cells/mm3, respectively (P < 0.05). The high X4 tropism rates were 13.2%, 11.8%, 20.0%, and 0.0% in Clusters 1, 4a, 4b, and 5, respectively. DRM rates in Clusters 4a and 4b were 17.6%, and 25.45% respectively (P < 0.05), whereas they were 17.6% and 18.2% in Clusters 1 and 5, respectively. In total, 24 transmission genetic networks, comprising 72 sequences and 61 links, were discovered; of them, 61.2%, 11.7%, and 18.2% were from Clusters 4, 1, and 5, respectively (P < 0.05).

Conclusion

In Zhejiang, different CRF01_AE clusters displayed unique clinic features. Cluster 4, particularly Cluster 4b, was considered a high-risk transmission cluster. The surveillance of epidemiology of HIV-1 should be enhanced to minimize its transmission.

Development and emerging trends of drug resistance mutations in HIV: a bibliometric analysis based on CiteSpace

Background

Antiretroviral therapy has led to AIDS being a chronic disease. Nevertheless, the presence of constantly emerging drug resistance mutations poses a challenge to clinical treatment. A systematic analysis to summarize the advancements and uncharted territory of drug resistance mutations is urgently needed and may provide new clues for solving this problem.

Methods

We gathered 3,694 publications on drug resistance mutations from the Web of Science Core Collection with CiteSpace software and performed an analysis to visualize the results and predict future new directions and emerging trends. Betweenness centrality, count, and burst value were taken as standards.

Results

The number of papers on HIV medication resistance mutations during the last 10 years shows a wave-like trend. In terms of nation, organization, and author, the United States (1449), University of London (193), and Mark A. Wainberg (66) are the most significant contributors. The most frequently cited article is "Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update." Hot topics in this field include "next-generation sequencing," "tenofovir alafenamide," "children," "regimens," "accumulation," "dolutegravir," "rilpivirine," "sex," "pretreatment drug resistance," and "open label." Research on drug resistance in teenagers, novel mutation detection techniques, and drug development is ongoing, and numerous publications have indicated the presence of mutations related to current medications. Therefore, testing must be performed regularly for patients who have used medications for a long period. Additionally, by choosing medications with a longer half-life, patients can take fewer doses of their prescription, increasing patient compliance.

Conclusion

This study involved a bibliometric visualization analysis of the literature on drug resistance mutations, providing insight into the field's evolution and emerging patterns and offering academics a resource to better understand HIV drug resistance mutations and contribute to the field's advancement.

HIV protease resistance mutations in patients receiving second-line antiretroviral therapy in Libreville, Gabon

INTRODUCTION

In 2022, the WHO reported that 29.8 million people around the world were living with HIV (PLHIV) and receiving antiretroviral treatment (ART), including 25‌ 375 people in Gabon (54% of all those living with HIV in the country). The literature reports a frequency of therapeutic failure with first-line antiretrovirals (ARVs) of between 20% and 82%. Unfortunately, data relating to the failure of second-line ARVs are scarce in Gabon. This study aims to determine the profiles of HIV drug resistance mutations related to protease inhibitors in Gabon.

METHODOLOGY

Plasma from 84 PLHIV receiving ARVs was collected from 2019 to 2021, followed by RNA extraction, amplification, and sequencing of the protease gene. ARV resistance profiles were generated using the Stanford interpretation algorithm version 8.9-1 ( https://hivdb.stanford.edu ) and statistical analyses were performed using EpiInfo software version 7.2.1.0 (CDC, USA).

RESULTS

Of 84 HIV plasma samples collected from 45 men and 39 women, 342 mutations were detected. Of these, 43.3% (148/342) were associated with nucleoside reverse transcriptase inhibitors (NRTIs), 30.4% (104/342) with non-nucleoside reverse transcriptase inhibitors (NNRTIs), and 26.3% (90/342) with protease inhibitors (PIs). Most NRTI mutations were associated with thymidine analogues (TAMs) (50.7%; 75/148), including T215F/V (14.9%; 22/148), D67DN/E/G/N/T (10.1%; 15/148), M41L (9.5%; 14/148), and K70E/KN/S/R (9.5%; 14/148). Resistance mutations related to non-TAM NRTIs (33.1%; 49/148) were M184V (29.1%; 43/148), and L74I/V (8.1%; 12/148). NNRTI mutations were predominantly K103N/S (32.7%; 34/104), V108I (10.6%; 11/104), A98G (10.6%; 11/104), and P225H (9.6%; 10/104). Minor mutations associated with PIs (60.0%; 54/90) were predominantly K20I (15.6%; 14/90) and L10F/I/V (14.5%; 13/90). The major mutations associated with PIs (40.0%; 36/90) were M41L (12.2%; 11/90), I84V (6.7%; 06/90), and V82A (6.7%; 06/90). The four most prescribed therapeutic regimens were TDF + 3TC + LPV/r (20.3%; 17/84), ABC + DDI + LPV/r (17.9%; 15/84), TDF + FTC + LPV/r (11.9%; 10/84), and ABC + 3TC + LPV/r (11.9%; 10/84).

CONCLUSION

This study revealed that HIV drug resistance mutations are common in Gabon. The major mutations associated with PIs were M41L, I84V, and V82A. There is a need for access to new NRTIs, NNRTIs, and PIs for a better therapeutic management of PLHIV in Gabon.