The S68G polymorphism is a compensatory mutation associated with the drug resistance mutation K65R in CRF01_AE strains

The profile of HIV-1 drug resistance in Shanghai, China: a retrospective study from 2017 to 2021

BACKGROUND

HIV-1 drug resistance is a huge challenge in the era of ART.

OBJECTIVES

To investigate the prevalence and characteristics of acquired HIV-1 drug resistance (ADR) in Shanghai, China.

METHODS

An epidemiological study was performed among people living with human immunodeficiency virus (PLWH) receiving ART in Shanghai from January 2017 to December 2021. A total of 8669 PLWH were tested for drug resistance by genotypic resistance testing. Drug resistance mutations (DRMs) were identified using the Stanford University HIV Drug Resistance Database program.

RESULTS

Ten HIV-1 subtypes/circulating recombinant forms (CRFs) were identified, mainly including CRF01_AE (46.8%), CRF07_BC (35.7%), B (6.4%), CRF55_01B (2.8%) and CRF08_BC (2.4%). The prevalence of ADR was 48% (389/811). Three NRTI-associated mutations (M184V/I/L, S68G/N/R and K65R/N) and four NNRTI-associated mutations (V179D/E/T/L, K103N/R/S/T, V106M/I/A and G190A/S/T/C/D/E/Q) were the most common DRMs. These DRMs caused high-level resistance to lamivudine, emtricitabine, efavirenz and nevirapine. The DRM profiles appeared to be significantly different among different subtypes.

CONCLUSIONS

We revealed HIV-1 subtype characteristics and the DRM profile in Shanghai, which provide crucial guidance for clinical treatment and management of PLWH.

HIV-1 Resistance to Islatravir/Tenofovir Combination Therapy in Wild-Type or NRTI-Resistant Strains of Diverse HIV-1 Subtypes

Tenofovir disoproxil fumarate (TDF) and islatravir (ISL, 4'-ethynyl-2-fluoro-2'-deoxyadensine, or MK-8591) are highly potent nucleoside reverse transcriptase inhibitors. Resistance to TDF and ISL is conferred by K65R and M184V, respectively. Furthermore, K65R and M184V increase sensitivity to ISL and TDF, respectively. Therefore, these two nucleoside analogs have opposing resistance profiles and could present a high genetic barrier to resistance. To explore resistance to TDF and ISL in combination, we performed passaging experiments with HIV-1 WT, K65R, or M184V in the presence of ISL and TDF. We identified K65R, M184V, and S68G/N mutations. The mutant most resistant to ISL was S68N/M184V, yet it remained susceptible to TDF. To further confirm our cellular findings, we implemented an endogenous reverse transcriptase assay to verify in vitro potency. To better understand the impact of these resistance mutations in the context of global infection, we determined potency of ISL and TDF against HIV subtypes A, B, C, D, and circulating recombinant forms (CRF) 01_AE and 02_AG with and without resistance mutations. In all isolates studied, we found K65R imparted hypersensitivity to ISL whereas M184V conferred resistance. We demonstrated that the S68G polymorphism can enhance fitness of drug-resistant mutants in some genetic backgrounds. Collectively, the data suggest that the opposing resistance profiles of ISL and TDF suggest that a combination of the two drugs could be a promising drug regimen for the treatment of patients infected with any HIV-1 subtype, including those who have failed 3TC/FTC-based therapies.

Artificial-Intelligence-Based Models Coupled with Correspondence Analysis Visualization on ART—Cases from Gombe State, Nigeria: A Comparative Study

Antiretroviral therapy (ART) is the common hope for HIV/AIDS-treated patients. Total commitments from individuals and the entire community are the major challenges faced during treatment. This study investigated the progress of ART in the Federal Teaching Hospital in Gombe state, Nigeria by using various records of patients receiving treatment in the ART hospital unit. We combined artificial intelligence (AI)-based models and correspondence analysis (CA) techniques to predict and visualize the progress of ART from the beginning to the end. The AI models employed are artificial neural networks (ANNs), adaptive neuro-fuzzy inference systems (ANFISs) and support-vector machines (SVMs) and a classical linear regression model of multiple linear regression (MLR). According to the outcome of this study, ANFIS in both training and testing outperformed the remaining models given the R2 (0.903 and 0.904) and MSE (7.961 and 3.751) values, revealing that any increase in the number of years of taking ART medication will provide HIV/AIDS-treated patients with safer and elongated lives. The contingency results for the CA and the chi-square test did an excellent job of capturing and visualizing the patients on medication, which gave similar results in return, revealing there is a significant association between ART drugs and the age group, while the association between ART drugs and marital status (93.7%) explained a higher percentage of variation compared with the remaining variables.