Use of electronic monitoring induces a 40-day intervention effect in HIV patients.
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Anti-HIV Agents↗
Biomedical subjects
Anne-Mieke Vandamme
Publications and source records attributed to Anne-Mieke Vandamme.
Phylogeny of primate T lymphotropic virus type 1 (PTLV-1) including various new Asian and African non-human primate strains.
To further unravel intra- and interspecies PTLV-1 evolution in Asia and Africa, we phylogenetically analysed 15 new STLV-1 LTR and env sequences discovered in eight different Asian and African non-human primate species. We show that orang-utan STLV-1s form a tight, deeply branching monophyletic cluster between Asian STLV-1 macaque species clades, suggesting natural cross-species transmission. Novel viruses of Macaca maura, Macaca nigra and siamang cluster with other Sulawesian STLV-1s, demonstrating close relatedness among the STLV-1s in these insular species and suggesting cross-species transmission to a siamang in captivity. Viruses from Western chimpanzees and a Western lowland gorilla cluster within the HTLV-lb/STLV-1 clade, the latter close to a human strain, indicative of zoonosis. A new STLV-1 from Cercopithecus ascanius differs from the published STLV-Cas57, explainable by the existence of five geographically separated subspecies. Barbary macaques, not yet described to be STLV-infected, carry a relatively recent acquired, typical African STLV-1, giving us no clue on the phylogeographical origin of PTLV-1.
Africa↗
Assessment of automated genotyping protocols as tools for surveillance of HIV-1 genetic diversity.
BACKGROUND: The routine use of drug resistance testing provides an abundant source of HIV-1 sequence data. However, it is not clear how reliable standard genotyping of these sequences is for describing HIV-1 genetic variation and for detecting novel genetic variants and epidemiological trends. OBJECTIVES: To compare assignment of HIV-1 resistance test sequences to reference strains across commonly used genotyping protocols. METHODS: Subtype assignments were compared across three standard genotyping protocols for 10 537 resistance test sequences, representing approximately one-fifth of all reported infections in the United Kingdom. Sequences that were inconsistently genotyped across methods, or that were unassigned by at least one method, were examined for evidence of recombination using sliding-window-based approaches. RESULTS: Although agreement across methods was high for subtypes B, C and H, it was generally much lower (< 50%) for other subtypes. Disagreement between methods typically involved closely related, but epidemiologically distinct, groups or involved a significant proportion ( approximately 12%) of divergent sequences in which analysis revealed widespread evidence of recombination and a remarkable diversity of unusual recombinant forms. CONCLUSIONS: With frequent long-distance transfer of viral strains and widespread recombination between them, genetic and epidemiological relationships within HIV-1 are becoming increasingly complex. Current methods of subtype assignment vary in their ability to identify novel genetic variants and to distinguish epidemiologically distinct strains. Capturing meaningful epidemiological information from resistance test data will require a critical understanding of the methodologies used in order to appreciate the possible sources of error and misclassification.
Databases, Genetic↗
Algorithms for the interpretation of HIV-1 genotypic drug resistance information.
Drug resistance testing has proven its use to guide treatment decisions in HIV-1 infected patients. Genotyping is the preferred technique for clinical drug resistance testing. Many factors complicate the interpretation of mutations towards therapy response, such that an interpretation system is necessary to help the clinical virologist. No consensus interpretation exists to date and experts often have quite different opinions. As a result, several algorithms for the interpretation of HIV-1 genotypic drug resistance information have been designed. Clinical evaluation of their genotypic interpretation is not always straightforward. We describe a few publicly available systems and their clinical evaluation. We also stress that in addition to drug resistance, for effective management of HIV infection the clinician needs to take into account all potential causes of treatment failure. Successful therapy heavily relies on the expertise of the clinician.
Algorithms↗
Genetic analyses reveal structured HIV-1 populations in serially sampled T lymphocytes of patients receiving HAART.
HIV-1 infection and compartmentalization in diverse leukocyte targets significantly contribute to viral persistence during suppressive highly active antiretroviral therapy (HAART). Longitudinal analyses were performed on envelope sequences of HIV-1 populations from plasma, CD4+ and CD8+ T lymphocytes in 14 patients receiving HAART and 1 therapy-naive individual. Phylogenetic reconstructions and analysis of molecular variance revealed that HIV-1 populations in CD4+ and CD8+ T cells remained compartmentalized over time in most individuals. Analyses of viral genetic variation demonstrated that, despite compartmentalization remaining over time, viral subpopulations tended not to persist and evolve but instead broke down and became reconstituted by new founder viruses. Due to the profound impact of HAART on viral evolution, it was difficult to discern whether these dynamics were ongoing during treatment or predominantly established prior to the commencement of therapy. The genetic structure and viral founder effects observed in serially sampled T lymphocyte populations supported a scenario of metapopulation dynamics in the tissue(s) where different leukocytes become infected, a factor likely to contribute to the highly variable way that drug resistance evolves in different individuals during HAART.
Antiretroviral Therapy, Highly Active↗
Prevalence of antiretroviral drug resistance mutations and HIV-1 non-B subtypes in newly diagnosed drug-naïve patients in Slovenia, 2000-2004.
In order to estimate the prevalence and patterns of antiretroviral drug resistance mutations in drug-naïve HIV-1 infected patients in Slovenia, and the prevalence of non-B subtypes, a retrospective study was conducted on a cohort, representing 87% of the total of newly diagnosed HIV-1 infected patients, in a 5 year period (2000-2004). Protease (PR) and reverse transcriptase (RT) sequences were determined in 77 newly diagnosed HIV-1 patients. Non-B subtypes were present in 18% of the population tested. Transmitted drug resistance was identified as in the CATCH study: the presence of primary PR and RT gene mutations according to the IAS-USA mutation list including the revertant mutations in codon 215 and excluding mutations on the RT positions 44 and 118. The estimated prevalence of transmitted resistance mutations was 3.9%. Namely, three out of 77 patients had mutations associated with resistance to NRTIs: one patient carried M184V in association with A62V, while a revertant mutation T215D was found in two patients. No transmitted drug resistance to NNRTIs or PIs was detected. However, to score the expected response to therapy using the REGA and the Stanford algorithms, we also took into account secondary PR mutations and additional RT mutations. Reduced response to some therapeutic options was predicted in five patients (6.5%). In conclusion, testing the vast majority of all newly diagnosed HIV-1 patients in the last 5 years in Slovenia uncovered a relatively high prevalence of non-B subtypes and a low prevalence of transmitted drug resistance.
Adult↗
The calculated genetic barrier for antiretroviral drug resistance substitutions is largely similar for different HIV-1 subtypes.
BACKGROUND: The genetic barrier, defined as the number of mutations required to overcome drug-selective pressure, is an important factor for the development of HIV drug resistance. Because of high variability between subtypes, particular HIV-1 subtypes could have different genetic barriers for drug resistance substitutions. This study compared the genetic barrier between subtypes using some 2000 HIV-1 sequences (>600 of non-B subtype) isolated from anti-retroviral-naive patients in Europe. METHODS: The genetic barrier was calculated as the sum of transitions (scored as 1) and/or transversions (2.5) required for evolution to any major drug resistance substitution. In addition, the number of minor protease substitutions was determined for every subtype. RESULTS: Few dissimilarities were found. An increased genetic barrier was calculated for I82A (subtypes C and G), V108I (subtype G), V118I (subtype G), Q151M (subtypes D and F), L210W (subtypes C, F, G, and CRF02_AG), and P225H (subtype A) (P < 0.001 compared with subtype B). A decreased genetic barrier was found for I82T (subtypes C and G) and V106M (subtype C) (P < 0.001 vs subtype B). Conversely, minor protease substitutions differed extensively between subtypes. CONCLUSIONS: Based on the calculated genetic barrier, the rate of drug resistance development may be similar for different HIV-1 subtypes. Because of differences in minor protease substitutions, protease inhibitor resistance could be enhanced in particular subtypes once the relevant major substitutions are selected.
Adult↗
Genotypic drug resistance interpretation algorithms display high levels of discordance when applied to non-B strains from HIV-1 naive and treated patients.
Genotypic drug resistance interpretation algorithms have been developed on patients infected with HIV-1 subtype B to interpret complex patterns of mutations. As non-B strains are characterised by the natural presence of several resistance-related mutations, we examined to what extent this might result in interalgorithm discordances in naive and treated patients. We compared the prediction by three algorithms (ANRS, Stanford and Rega) of drug susceptibilities to diverse HIV-1 strains from 272 naive and 156 treated patients. In naive patients, higher levels of interalgorithm discordance were observed for predictions of protease inhibitor (0.60-39%) than for predictions of reverse transcriptase inhibitor susceptibility (0-4%). The main reason for discordant protease inhibitor interpretation was the presence of resistance mutations that were natural protease polymorphisms. In contrast, in the treated patients, more interalgorithm discordances were observed for predictions of reverse transcriptase inhibitor (5-48%) than protease inhibitor susceptibilities (10-31%). Discordances were related to disagreement between the intermediate and susceptible scores, the intermediate and resistant scores and the interpretations of complex mutation patterns, related to cross-resistance and antagonistic interactions.
Algorithms↗
Discordances between interpretation algorithms for genotypic resistance to protease and reverse transcriptase inhibitors of human immunodeficiency virus are subtype dependent.
The major limitation of drug resistance genotyping for human immunodeficiency virus remains the interpretation of the results. We evaluated the concordance in predicting therapy response between four different interpretation algorithms (Rega 6.3, HIVDB-08/04, ANRS [07/04], and VGI 8.0). Sequences were gathered through a worldwide effort to establish a database of non-B subtype sequences, and demographic and clinical information about the patients was gathered. The most concordant results were found for nonnucleoside reverse transcriptase (RT) inhibitors (93%), followed by protease inhibitors (84%) and nucleoside RT inhibitor (NRTIs) (76%). For therapy-naive patients, for nelfinavir, especially for subtypes C and G, the discordances were driven mainly by the protease (PRO) mutational pattern 82I/V + 63P + 36I/V for subtype C and 82I + 63P + 36I + 20I for subtype G. Subtype F displayed more discordances for ritonavir in untreated patients due to the combined presence of PRO 20R and 10I/V. In therapy-experienced patients, subtype G displayed a lot of discordances for saquinavir and indinavir due to mutational patterns involving PRO 90 M and 82I. Subtype F had more discordance for nelfinavir attributable to the presence of PRO 88S and 82A + 54V. For the NRTIs lamivudine and emtricitabine, CRF01_AE had more discordances than subtype B due to the presence of RT mutational patterns 65R + 115 M and 118I + 215Y, respectively. Overall, the different algorithms agreed well on the level of resistance scored, but some of the discordances could be attributed to specific (subtype-dependent) combinations of mutations. It is not yet known whether therapy response is subtype dependent, but the advice given to clinicians based on a genotypic interpretation algorithm differs according to the subtype.
Algorithms↗
Investigation of baseline susceptibility to protease inhibitors in HIV-1 subtypes C, F, G and CRF02_AG.
OBJECTIVE: To compare baseline susceptibility to protease inhibitors among HIV-1 isolates of subtypes C, F, G and CRF02_AG, and to identify polymorphisms that determine the differences in susceptibility. METHODS: A total of 42 samples of drug-naive patients infected with subtypes G (n=19), CRF02_AG (n = 10), F (n = 6) and C (n = 7) were phenotyped and genotyped with the Antivirogram and the ViroSeq 2.0 genotyping system, respectively. A Bayesian network approach was used for a preliminary analysis of the collected data and the dependencies indicated by the network were statistically confirmed. RESULTS: CRF02_AG samples were found to be more susceptible to nelfinavir and ritonavir than other subtypes. Hypersusceptibility to these drugs was associated with the 70R polymorphism. 37D/S/T was associated with reduced susceptibility to indinavir and 89M with reduced susceptibility to lopinavir. Susceptibility to tipranavir was the lowest among the subtype F samples and the highest for subtype G samples, with samples carrying 57R being more susceptible than samples carrying 57K. CONCLUSIONS: Our study suggests that there are baseline susceptibility differences between subtypes and these differences are due to naturally occurring polymorphisms in these subtypes. The predictive value for phenotype of these polymorphisms was even valid in subtypes where these polymorphisms are less prevalent. Taking into account such polymorphisms should improve current algorithms for interpretation of genotyping results in a subtype-independent way.
Algorithms↗
A genotypic assay for the amplification and sequencing of gag and protease from diverse human immunodeficiency virus type 1 group M subtypes.
In human immunodeficiency virus type 1 (HIV-1), an interaction exists between the in vivo evolution of Gag protein and protease to escape from antiretroviral drug selective pressure. Therefore, it was decided to develop a genotypic assay for the amplification and sequencing of HIV-1 gag and protease. As the HIV-1 pandemic is characterised by a large genetic diversity, the assay developed was evaluated on a panel of 28 genetically divergent samples belonging to the following subtypes A1, B, C, D, F1, F2, G, H, J, CRF01-AE, CRF02-AG and CRF13-cpx. The assay displayed a detection limit ranging between 500 RNA copies/ml and 5000 RNA copies/ml plasma. Full-length sequences could be obtained for 25 samples. The population sequences of the three other samples lacked a part of the sequence because of heterogeneous signal, probably due to the presence of quasi-species with insertions/deletions of a different length.
DNA Primers↗
Protease mutation M89I/V is linked to therapy failure in patients infected with the HIV-1 non-B subtypes C, F or G.
OBJECTIVE: To investigate whether and how mutations at position 89 of HIV-1 protease were associated with protease inhibitor (PI) failure, and what is the impact of the HIV-1 subtype. METHODS: In a database containing pol nucleotide sequences and treatment history, the correlation between PI experience and mutations at codon 89 was determined separately for subtype B and several non-B subtypes. A Bayesian network model was used to map the resistance pathways in which M89I/V is involved for subtype G. The phenotypic effect of M89I/V for several PIs was also measured. RESULTS: The analysis showed that for the subtypes C, F and G in which the wild-type codon at 89 was M compared to L for subtype B, M89I/V was significantly more frequently observed in PI-treated patients displaying major resistance mutations to PIs than in drug-naive patients. M89I/V was strongly associated with PI resistance mutations at codons 71, 74 and 90. Phenotypically, M89I/V alone did not confer a reduced susceptibility to PIs. However, when combined with L90M, a significantly reduced susceptibility to nelfinavir was observed (P < 0.05) in comparison with strains with L90M alone. CONCLUSIONS: The results of the present study show that M89I/V is associated with PI experience in subtypes C, F and G but not in subtype B. M89I/V should be considered a secondary PI mutation with an important effect on nelfinavir susceptibility in the presence of L90M.
Adult↗
Molecular testing of multiple HIV-1 transmissions in a criminal case.
OBJECTIVE: To test the a priori hypothesis of HIV-1 transmission from one suspect to six recipients in a criminal case. METHODS: Partial pol and/or env sequences were obtained for at least two samples of the suspect and the victims. Appropriate local controls were sampled based on epidemiological and subtype criteria. Phylogenetic testing was performed using different reconstruction methods. RESULTS: Phylogenetic analyses consistently inferred a monophyletic cluster for the suspect and victim samples in both genome regions. This was highly supported by parametric and non-parametric bootstrapping techniques. Moreover, the controls most closely related to the suspect-victim cluster had a similar geographical origin to the suspect. CONCLUSIONS: Taking into account the limitations on the conclusions that can be drawn from molecular investigations we could infer that our molecular data is consistent with a scenario of multiple HIV transmission between suspect and victims.
Bayes Theorem↗
Exploring full-genome sequences for phylogenetic support of HIV-1 transmission events.
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Genome, Viral↗
Prevalence of drug-resistant HIV-1 variants in untreated individuals in Europe: implications for clinical management.
BACKGROUND: Infection with drug-resistant human immunodeficiency virus type 1 (HIV-1) can impair the response to combination therapy. Widespread transmission of drug-resistant variants has the disturbing potential of limiting future therapy options and affecting the efficacy of postexposure prophylaxis. METHODS: We determined the baseline rate of drug resistance in 2208 therapy-naive patients recently and chronically infected with HIV-1 from 19 European countries during 1996-2002. RESULTS: In Europe, 1 of 10 antiretroviral-naive patients carried viruses with > or = 1 drug-resistance mutation. Recently infected patients harbored resistant variants more often than did chronically infected patients (13.5% vs. 8.7%; P=.006). Non-B viruses (30%) less frequently carried resistance mutations than did subtype B viruses (4.8% vs. 12.9%; P<.01). Baseline resistance increased over time in newly diagnosed cases of non-B infection: from 2.0% (1/49) in 1996-1998 to 8.2% (16/194) in 2000-2001. CONCLUSIONS: Drug-resistant variants are frequently present in both recently and chronically infected therapy-naive patients. Drug-resistant variants are most commonly seen in patients infected with subtype B virus, probably because of longer exposure of these viruses to drugs. However, an increase in baseline resistance in non-B viruses is observed. These data argue for testing all drug-naive patients and are of relevance when guidelines for management of postexposure prophylaxis and first-line therapy are updated.
Adult↗
An automated genotyping system for analysis of HIV-1 and other microbial sequences.
MOTIVATION: Genetic analysis of HIV-1 is important not only for vaccine development, but also to guide treatment strategies, track the emergence of new viral variants and ensure that diagnostic assays are contemporary and fully optimized. However, most genotyping methods are laborious and complex, and involve the use of multiple software applications. Here, we describe the development of an automated genotyping system that can be easily applied to HIV-1 and other rapidly evolving viral pathogens. RESULTS: The new REGA subtyping tool, developed using Java programming and PERL scripts, combines phylogenetic analyses with boot-scanning methods for the genetic subtyping of full-length and subgenomic fragments of HIV-1. When used to investigate the subtype of previously published reference datasets that were analysed using manual phylogenetic methods, the automated method correctly identified 97.5-100% of non-recombinant and circulating recombinant forms of HIV-1, including 108 full-length, 108 gag and 221 env sequences downloaded from the Los Alamos database.
Algorithms↗
Role of viral evolutionary rate in HIV-1 disease progression in a linked cohort.
BACKGROUND: The actual relationship between viral variability and HIV disease progression and/or non-progression can only be extrapolated through epidemiologically-linked HIV-infected cohorts. The rarity of such cohorts accents their existence as invaluable human models for a clear understanding of molecular factors that may contribute to the various rates of HIV disease. We present here a cohort of three patients with the source termed donor A--a non-progressor and two recipients called B and C. Both recipients gradually progressed to HIV disease and patient C has died of AIDS recently. By conducting 15 near full-length genome (8.7 kb) analysis from longitudinally derived patient PBMC samples enabled us to investigate the extent of molecular factors, which govern HIV disease progression. RESULTS: Four time points were successfully amplified for patient A, 4 for patient B and 7 from patient C. Using phylogenetic analysis our data confirms the epidemiological-linkage and transmission of HIV-1 from a non-progressor to two recipients. Following transmission the two recipients gradually progressed to AIDS and one died of AIDS. Viral divergence, selective pressures, recombination, and evolutionary rates of HIV-1 in each member of the cohort were investigated over time. Genetic recombination and selective pressure was evident in the entire cohort. However, there was a striking correlation between evolutionary rate and disease progression. CONCLUSION: Non-progressing individuals have the potential to transmit pathogenic variants, which in other host can lead to faster HIV disease progression. This was evident from our study and the accelerated disease progression in the recipient members of he cohort correlated with faster evolutionary rate of HIV-1, which is a unique aspect of this study.
Acquired Immunodeficiency Syndrome↗
Circulation of genetically distinct contemporary human coronavirus OC43 strains.
In this study, we report the complete genome sequence of two contemporary human coronavirus OC43 (HCoV-OC43) strains detected in 2003 and 2004, respectively. Comparative genetic analyses of the circulating strains and the prototype HCoV-OC43 strain (ATCC VR759) were performed. Remarkably, a lower than expected similarity is found between the complete genomes and more in particular between the spike genes of the BE03 and BE04 strains. This finding suggests the existence of two genetically distinct HCoV-OC43 strains, circulating in Belgium in 2003 and 2004. Spike gene sequencing of three additional 2003 and two additional 2004 HCoV-OC43 strains, and subsequent phylogenetic analysis confirm this assumption. Compared to the ATCC prototype HCoV-OC43 strain, an important amino acid substitution is present in the potential cleavage site sequence of the spike protein of all contemporary strains, restoring the N-RRXRR-C motif, associated with increased spike protein cleavability in bovine coronaviruses. We here describe specific characteristics associated with circulating HCoV-OC43 strains, and we provide substantial evidence for the genetic variability of HCoV-OC43.
Coronavirus Infections↗