Author(s):
Abecasis, AB ; Vandamme, AM ; the EuResist Network Study Group
Date: 2023
Persistent ID: http://hdl.handle.net/10362/165088
Origin: Repositório Institucional da UNL
Subject(s): antiretrovirus drug; antiviral agents; disease control; evolution; human immunodeficiency virus; infection; mutation/mutation rate; reservoir; resistance; virus classification; QR180 Immunology; QR355 Virology; RA0421 Public health. Hygiene. Preventive Medicine; RM Therapeutics. Pharmacology; Infectious Diseases; Virology; Public Health, Environmental and Occupational Health; Pharmacology, Toxicology and Pharmaceutics(all); SDG 3 - Good Health and Well-being; SDG 17 - Partnerships for the Goals
Description
Human immunodeficiency virus (HIV) can develop resistance to all antiretroviral drugs. Multidrug resistance, however, is a rare event in modern HIV treatment, but can be life‐threatening, particular in patients with very long therapy histories and in areas with limited access to novel drugs. To understand the evolution of multidrug resistance, we analyzed the EuResist database to uncover the accumulation of mutations over time. We hypothesize that the accumulation of resistance mutations is not acquired simultaneously and randomly across viral genotypes but rather tends to follow a predetermined order. The knowledge of this order might help to elucidate potential mechanisms of multidrug resistance. Our evolutionary model shows an almost monotonic increase of resistance with each acquired mutation, including less well‐known nucleoside reverse transcriptase (RT) inhibitor‐related mutations like K223Q, L228H, and Q242H. Mutations within the integrase (IN) (T97A, E138A/K G140S, Q148H, N155H) indicate high probability of multidrug resistance. Hence, these IN mutations also tend to be observed together with mutations in the protease (PR) and RT. We followed up with an analysis of the mutation‐specific error rates of our model given the data. We identified several mutations with unusual rates (PR: M41L, L33F, IN: G140S). This could imply the existence of previously unknown virus variants in the viral quasispecies. In conclusion, our bioinformatics model supports the analysis and understanding of multidrug resistance.
