Indexing metadata

Introduction. As a result of routine testing of HIV-1 drug resistance (DR), a significant amount of viral nucleotide sequences and epidemiological data of HIV-infected individuals have been collected. Combined with the increasing use of bioinformatics methods in practice, it has become possible to study the features of HIV-1 resistant variants spread using molecular clustering analysis.

The aim of the study was to validate the molecular clustering analysis in a pilot region of Russia using a significant number of nucleotide sequences to study the features of the spread of HIV-1 resistant variants.

Materials and methods. HIV-1 nucleotide sequences were obtained from 899 HIV-infected patients who were registered at the Oryol AIDS Center in 2016–2021. HIV-1 genetic variants were determined using the Stanford University database, REGA and HIV BLAST. Resistance mutations and prognostic HIV-1 DR were determined using the Stanford University database. Phylogenetic analysis was carried out using the MEGA program. HIV-1 molecular clusters were identified using Cluster Picker software.

Results. In the pilot region, sub-subtype A6 dominated (85.7%); an increase in the share of CRF63_02A6 was noted. HIV-1 resistance was found in 13.6% of patients without antiretroviral therapy (ART) experience and in 52.0% with ART experience. Molecular clusters were more often formed by HIV-1 nucleotide sequences from ART-naïve patients. HIV-1 DR variants were less likely to fall into molecular clusters. The sources of transmitted mutations were more often patients with ART experience. The most actively and efficiently transmitted mutations were K103N, V179E/T, Y181C and G190S, associated with virus resistance to efavirenz and nevirapine.