Patterns of HIV-1 drug resistance among HIV-infected patients receiving first-line antiretroviral therapy in Novosibirsk Region, Russia

ABSTRACT: Objectives: Antiretroviral (ARV) drugs have played a vital role in controlling the HIV-1 epidemic; however, some challenges remain. ARV drugs vary in their ability to control HIV infection, displaying differences in treatment-limiting factors and genetic barriers to resistance. The current report assesses the prevalence of HIV-1 drug resistance mutations (DRMs) among patients who failed first-line antiretroviral therapy (ART) and evaluates the genetic barrier of different regimens. Methods: The study cohort (n = 271) included HIV-infected individuals who visited the Novosibirsk, Russia, HIV/AIDS clinic in 2018–2022. All patients received first-line ART prior to virological failure. Sociodemographic and HIV-related data were collected from medical records and self-reported questionnaires. HIV-1 pol gene sequences were generated, and the presence of HIV-1 DRM was assessed. The genetic barrier to resistance was assessed by combining treatment regimen and adherence data. Results: Nonoptimal ART adherence was identified in 48.3% of patients and correlated with male sex, PWID, unemployment, and rural area residence. Most of the patients with high-level adherence were identified among those who were on TDF+3TC+DTG. HIV-1 DRMs were identified in 54.6% of the patients. The analysis of HIV-1 DRM, ART regimen, and adherence data classified TDF+3TC+DTG and TDF+3TC+LPV/r as treatment regimens with a high genetic barrier, whereas EFV-containing ART was classified as a regimen with a low genetic barrier. Conclusions: The current study delivers results on the efficacy of HIV-1 ART and treatment adherence in real-world practice settings. This report suggests that ART regimens with a high genetic barrier to resistance combined with improved treatment adherence may reduce the transmission of HIV-1 resistant variants

Image_3_Spatiotemporal dynamics of HIV-1 CRF63_02A6 sub-epidemic.JPEG

HIV-1 epidemic in Russia is one of the fastest growing in the world reaching 1.14 million people living with HIV-1 (PLWH) in 2021. Since mid-1990s, the HIV-1 epidemic in Russia has started to grow substantially due to the multiple HIV-1 outbreaks among persons who inject drugs (PWID) leading to expansion of the HIV-1 sub-subtype A6 (former Soviet Union (FSU) subtype A). In 2006, a local HIV-1 sub-epidemic caused by the distribution of novel genetic lineage CRF63_02A6 was identified in Siberia. In this study, we used a comprehensive dataset of CRF63_02A6 pol gene sequences to investigate the spatiotemporal dynamic of the HIV-1 CRF63_02A6 sub-epidemic. This study includes all the available CRF63_02A6 HIV-1 pol gene sequences from Los Alamos National Laboratory (LANL) HIV Sequence Database. The HIV-1 subtypes of those sequences were conferred using phylogenetic analysis, and two automated HIV-1 subtyping tools Stanford HIVdb Program and COMET. Ancestral state reconstruction and origin date were estimated using Nextstrain. Evolutionary rate and phylodynamic analysis were estimated using BEAST v 1.10.4. CRF63_02A6 was assigned for 872 pol gene sequences using phylogenetic analysis approach. Predominant number (n = 832; 95.4%) of those sequences were from Russia; the remaining 40 (4.6%) sequences were from countries of Central Asia. Out of 872 CRF63_02A6 sequences, the corresponding genetic variant was assigned for 75.7 and 79.8% of sequences by Stanford and COMET subtyping tools, respectively. Dated phylogenetic analysis of the CRF63_02A6 sequences showed that the virus most likely originated in Novosibirsk, Russia, in 2005. Over the last two decades CRF63_02A6 has been widely distributed across Russia and has been sporadically detected in countries of Central Asia. Introduction of new genetic variant into mature sub-subtype A6 and CRF02_AGFSU epidemics could promote the increase of viral genetic diversity and emergence of new recombinant forms. Further HIV-1 studies are needed due to a continuing rapid virus distribution. Also, the implementation of HIV-1 prevention programs is required to reduce HIV-1 transmission. This study also highlights the discrepancies in HIV-1 subtyping approaches. The reference lists of HIV-1 sequences implemented in widely used HIV-1 automated subtyping tools need to be updated to provide reliable results.</p