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Theys K

HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment.
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RegaDB: Community-driven data management and analysis for infectious diseases

RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface.
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Structural modifications induced by specific HIV-1 protease-compensatory mutations have an impact on the virological response to a first-line lopinavir/ritonavir-containing regimen

This study evaluates the impact of specific HIV-1 protease-compensatory mutations (wild-type amino acids in non-B subtypes) on virological response to a first-line lopinavir/ritonavir-containing regimen in an HIV-1 subtype B-infected population.
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Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients.

BACKGROUND:
The effect of drug resistance transmission on disease progression in the newly infected patient is not well understood. Major drug resistance mutations severely impair viral fitness in a drug free environment, and therefore are expected to revert quickly. Compensatory mutations, often already polymorphic in wild-type viruses, do not tend to revert after transmission.
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The demise of multidrug- resistant HIV-1: The national time trend in Portugal

Despite a decreasing mortality and morbidity in treated HIV-1 patients, highly active antiretroviral treatment (HAART) can still fail due to the development of drug resistance. Especially, multidrug-resistant viruses pose a threat to efficient therapy. We studied the changing prevalence of multidrug resistance (MDR) over time in a cohort of HIV-1-infected patients in Portugal.
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HIV-1 subtype is an independent predictor of reverse transcriptase mutation k65r in HIV-1 patients treated with combination antiretroviral therapy including tenofovir

Subtype-dependent selection of HIV-1 reverse transcriptase resistance mutation K65R was previously observed in cell culture and small clinical investigations. We compared K65R prevalence across subtypes A, B, C, F, G, and CRF02_AG separately in a cohort of 3,076 patients on combination therapy including tenofovir. K65R selection was significantly higher in HIV-1 subtype C. This could not be explained by clinical and demographic factors in multivariate analysis, suggesting subtype sequence-specific K65R pathways.
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Decreasing population selection rates of resistance mutation K65R over time in HIV-1 patients receiving com- bination therapy including tenofovir

The use of tenofovir is highly associated with the emergence of mutation K65R, which confers broad resistance to nucleoside/nucleotide analogue reverse transcriptase inhibitors (NRTIs), especially when tenofovir is combined with other NRTIs also selecting for K65R. Although recent HIV-1 treatment guidelines discouraging these combinations resulted in reduced K65R selection with tenofovir, updated information on the impact of currently recommended regimens on the population selection rate of K65R is presently lacking.
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HIV-1 sub- type distribution and its demographic determinants in newly diagnosed patients in Europe suggest highly compartmentalized epidemics

Understanding HIV-1 subtype distribution and epidemiology can assist preventive measures and clinical decisions. Sequence variation may affect antiviral drug resistance development, disease progression, evolutionary rates and transmission routes.
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