Gag-protease coevolution shapes the outcome of lopinavir-inclusive treatment regimens in chronically infected HIV-1 subtype C patients

Marie, Veronna; Gordon, Michelle

doi:10.1093/bioinformatics/btz076

Cited by 7 publications

(9 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Barber et al [36] have suggested that PI resistance mutations are more likely to accumulate under prolonged virological failure. Second, there is increasing evidence that mutations in the gag gene play a role in decreasing susceptibility to protease inhibitors by, e.g., inhibiting the proteolytic cleavages necessary for protein maturation [23,59,60]. Virions with immature particles may not adequately complete cell entry or reverse transcription [60].…”

Section: Discussionmentioning

confidence: 99%

“…To leverage information from large cohorts and cross-sectional studies, different statistical models have been proposed to investigate inter-dependencies of mutations. On the one hand, approaches such as Bayesian networks [21][22][23] and Cox proportionalhazards models [24] provide insights into statistical dependencies between resistance mutations without explicitly modeling the ordering among such mutations. On the other hand, order-aware approaches for investigating evolutionary pathways leading to drug resistance include mutagenetic trees [25,26]; discrete and continuous-time Conjunctive Bayesian Networks (CBN) [27,28]; and Suppes-Bayes Causal Networks (e.g., CAPRI [29,30]).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

et al. 2021

View full text Add to dashboard Cite

Although combination antiretroviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance mutations accumulate in different subtypes also remain poorly understood. Most of this knowledge is derived from studies of subtype B genotypes, despite not being the most abundant subtype worldwide. Here, we present a methodology for the comparison of mutational networks in different HIV-1 subtypes, based on Hidden Conjunctive Bayesian Networks (H-CBN), a probabilistic model for inferring mutational networks from cross-sectional genotype data. We introduce a Monte Carlo sampling scheme for learning H-CBN models for a larger number of resistance mutations and develop a statistical test to assess differences in the inferred mutational networks between two groups. We apply this method to infer the temporal progression of mutations conferring resistance to the protease inhibitor lopinavir in a large cross-sectional cohort of HIV-1 subtype C genotypes from South Africa, as well as to a data set of subtype B genotypes obtained from the Stanford HIV Drug Resistance Database and the Swiss HIV Cohort Study. We find strong support for different initial mutational events in the protease, namely at residue 46 in subtype B and at residue 82 in subtype C. The inferred mutational networks for subtype B versus C are significantly different sharing only five constraints on the order of accumulating mutations with mutation at residue 54 as the parental event. The results also suggest that mutations can accumulate along various alternative paths within subtypes, as opposed to a unique total temporal ordering. Beyond HIV drug resistance, the statistical methodology is applicable more generally for the comparison of inferred mutational networks between any two groups.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Barber et al [33] have suggested that PI resistance mutations are more likely to accumulate under prolonged virological failure. Second, there is increasing evidence that mutations in the gag gene play a role in decreasing susceptibility to protease inhibitors by, e.g., inhibiting the proteolytic cleavages necessary for protein maturation [19,55,56]. Virions with immature particles may not adequately complete cell entry or reverse transcription [56].…”

Section: Discussionmentioning

confidence: 99%

“…To leverage information from large cohorts and cross-sectional studies, different statistical models have been proposed to investigate mutational pathways leading to drug resistance. These approaches include several probabilistic graphical models, such as Markov processes [13]; a Markov model incorporating information from phylogenetic trees [4]; mutagenetic trees [3,14]; Bayesian networks [15][16][17][18][19]; discrete and continuous-time Conjunctive Bayesian Networks (CBN) [20,21]; and Suppes-Bayes Causal Networks (SBCN) [22]; as well as a Cox proportional-hazards model which is used to identify pairs of resistance mutations, in which one mutation alters the hazard of the other one [6].…”

Section: Introductionmentioning

confidence: 99%

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

Posada-Céspedes

Zyl

Montazeri

et al. 2020

Preprint

View full text Add to dashboard Cite

Although combination antiretoviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance mutations accumulate in different subtypes also remain poorly understood. Here, we present a methodology for the comparison of mutational pathways in different HIV-1 subtypes, based on Hidden Conjunctive Bayesian Networks (H-CBN), a probabilistic model for inferring mutational pathways from cross-sectional genotype data. We introduce a Monte Carlo sampling scheme for learning H-CBN models on a large number of resistance mutations and develop a statistical test to assess differences in the inferred mutational pathways between two groups. We apply this method to the temporal progression of mutations conferring resistance to the protease inhibitor lopinavir in a large cross-sectional data set of South African individuals living with HIV-1 subtype C, as well as a genotype data set of subtype B infections derived from the Stanford HIV Drug Resistance Database and the Swiss HIV Cohort Study. We find strong support for different initial mutational events in the protease, namely at residue 46 in subtype B and at residue 82 in subtype C. Our results also show that mutations can accumulate along various alternative paths within subtypes, as opposed to a unique total temporal ordering. Furthermore, the maximum likelihood mutational networks for subtypes B and C share only 7 edges (Jaccard distance 0.802) and imply many different evolutionary pathways. Beyond HIV drug resistance, the statistical methodology is applicable more generally for the comparison of inferred mutational pathways between any two groups.Author summaryThere is a disparity in the distribution of infections by HIV-1 subtype in the world. Subtype B is predominant in America, Western Europe and Australia, and most therapeutic strategies are based on research and clinical studies on this subtype. However, non-B subtypes represent the majority of global HIV-1 infections; e.g., subtype C alone accounts for nearly half of all HIV-1 infections. We present a statistical framework enabling the comparison of patterns of accumulating mutations in different HIV-1 subtypes. Specifically, we study lopinavir resistance pathways in HIV-1 subtypes B versus C, but the methodology can be generally applied to compare the temporal ordering of genetic events in different subgroups.

show abstract

“…This retrospective study used 24 stored plasma samples obtained from virologically failing PI-treated patients enrolled in the Protease Cleavage Site (PCS) study (2009)(2010)(2011)(2012)(2013) at McCord and King Edward VIII hospitals Durban, South Africa [26]. All enrolled patients received Lopinavir/Ritonavir therapy for at least six months and had plasma HIV-1 RNA levels > 1000 copies/mL.…”

Section: Study Cohortmentioning

confidence: 99%

Potential Associations of Mutations within the HIV-1 Env and Gag Genes Conferring Protease Inhibitor (PI) Drug Resistance

Maphumulo

Gordon

2021

Microbiology Research

View full text Add to dashboard Cite

An increasing number of patients in Africa are experiencing virological failure on a second-line antiretroviral protease inhibitor (PI)-containing regimen, even without resistance-associated mutations in the protease region, suggesting a potential role of other genes in PI resistance. Here, we investigated the prevalence of mutations associated with Lopinavir/Ritonavir (LPV/r) failure in the Envelope gene and the possible coevolution with mutations within the Gag-protease (gag-PR) region. Env and Gag-PR sequences generated from 24 HIV-1 subtype C infected patients failing an LPV/r inclusive treatment regimen and 344 subtype C drug-naïve isolates downloaded from the Los Alamos Database were analyzed. Fisher’s exact test was used to determine the differences in mutation frequency. Bayesian network probability was applied to determine the relationship between mutations occurring within the env and gag-PR regions and LPV/r treatment. Thirty-five mutations in the env region had significantly higher frequencies in LPV/r-treated patients. A combination of Env and Gag-PR mutations was associated with a potential pathway to LPV/r resistance. While Env mutations were not directly associated with LPV/r resistance, they may exert pressure through the Gag and minor PR mutation pathways. Further investigations using site-directed mutagenesis are needed to determine the impact of Env mutations alone and in combination with Gag-PR mutations on viral fitness and LPV/r efficacy.

show abstract

Gag-protease coevolution shapes the outcome of lopinavir-inclusive treatment regimens in chronically infected HIV-1 subtype C patients

Cited by 7 publications

References 36 publications

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

Potential Associations of Mutations within the HIV-1 Env and Gag Genes Conferring Protease Inhibitor (PI) Drug Resistance

Contact Info

Product

Resources

About