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Home / Archives for Grossman Z

Grossman Z

Limited cross-border infections in patients newly diagnosed with HIV in Europe

  • Autores: Abecasis AB, Albert J, Åsjö B, Balotta C, Beshkov D, Boucher CAB, Camacho RJ, Clotet B, Coughlan S, De Wit S, Frentz D, Griskevicius A, Grossman Z, Hamouda O, Horban A, Jørgensen LB, Kolupajeva T, Korn K, Kostrikis LG, Kücherer C, Liitsola K, Linka M, Nielsen C, Otelea D, Paraskevis D, Paredes R, Poljak M, Puch-hammer-Stöckl E, Schmit JC, Sönnerborg A, Staneková D, Stanojevic M, Struck D, Van de Vijver DAMC, Vandamme AM, Wensing AMJ
  • Ano de Publicação: 2013
  • Journal: Retrovirology
  • Link: http://www.retrovirology.com/content/10/1/36

International travel plays a role in the spread of HIV-1 across Europe. It is, however, not known whether international travel is more important for spread of the epidemic as compared to endogenous infections within single countries. In this study, phylogenetic associations among HIV of newly diagnosed patients were determined across Europe.
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HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

  • Autores: Beheydt G, Bruzzone B, Camacho RJ, De Luca A, Deforche K, Grossman Z, Imbrechts S, Incardona F, Libin P, Pironti A, Rhee SY, Ruiz L, Sangeda RZ, Shafer RW, Sönnerborg A, Theys K, Torti C, Van de Vijver DA, Van Laethem K, Van Wijngaerden E, Vandamme AM, Vercauteren J, Zazzi M
  • Ano de Publicação: 2013
  • Journal: Infection Genetics and Evolution
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/23523594

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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Study of the regimen-specific HIV-1 genotypic susceptibility score after treatment failure

  • Autores: Beheydt G, Camacho R, Carvalho AP, Diogo I, Grossman Z, Ram D, Rudich H, Van Laethem K, Vandamme AM, Zazzi M
  • Ano de Publicação: 2010
  • Journal: Antiviral Therapy
  • Link: https://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&qid=3&SID=Z1yZbyGlNxI3xGo9eDj&page=1&doc=1

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Expected HIV-1 etravirine resistance after treatment failure with efavirenz and/or nevirapine

  • Autores: Beheydt G, Camacho R, Carvalho AP, Grossman Z, Levy I, Ram D, Rudich H, Van Laethem K, Vandamme AM, Vercauteren J
  • Ano de Publicação: 2010
  • Journal: Antiviral Therapy
  • Link: https://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&qid=2&SID=Z1yZbyGlNxI3xGo9eDj&page=1&doc=1

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RegaDB: Community-driven data management and analysis for infectious diseases

  • Autores: Alcantara LCJ, Assel M, Ayouba A, Beheydt G, Boucher C, Camacho RJ, Carvalho AP, Cavaco-Silva J, De Bel A, De Munter P, De Oliveira T, Deforche K, Ferreira F, Grossman Z, Imbrechts S, Kaiser R, Lacor P, Lapadula G, Libin P, Otelea D, Paraschiv S, Peeters M, Ruelle J, Sloot P, Snoeck J, Theys K, Torti C, Van Laethem K, Van Wijngaerden E, Vandamme AM, Wesner S, Zazzi M
  • Ano de Publicação: 2013
  • Journal: Bioinformatics
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/23645815

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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Cellular HIV-1 DNA levels in drug sensitive strains are equivalent to those in drug resistant strains in newly-diagnosed patients in Europe

  • Autores: Balotta C, Clotet B, Demetriou VL, Grossman Z, Jørgensen LB, Kostrikis LG, Kousiappa I, Lepej SZ, Levy I, Nielsen C, Paraskevis D, Poljak M, Roman F, Ruiz L, Schmidt JC, Van de Vijver DA, Van Laethem K, Vandamme AM, Vercauteren J
  • Ano de Publicação: 2010
  • Journal: PLoS One
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/20544014

BACKGROUND:
HIV-1 genotypic drug resistance is an important threat to the success of antiretroviral therapy and transmitted resistance has reached 9% prevalence in Europe. Studies have demonstrated that HIV-1 DNA load in peripheral blood mononuclear cells (PBMC) have a predictive value for disease progression, independently of CD4 counts and plasma viral load.
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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.

  • Autores: Albert J, Åsjö B, Balotta C, Boucher CA, Bruckova M, Camacho RJ, Clotet B, Coughlan S, Deforche K, Grossman Z, Hamouda O, Horban A, Korn K, Kostrikis LG, Kücherer C, Libin P, Liitsola K, Nielsen C, Paraskevis D, Poljak M, Puchhammer-Stöckl E, Riva C, Ruiz L, Schmit JC, Schuurman R, Sönnerborg A, SPREAD-programme, Staneková D, Stanojevic M, Struck D, Theys K, Van de Vijver DA, Van Laethem K, Vandamme AM, Vercauteren J, Wensing AM
  • Ano de Publicação: 2012
  • Journal: Retrovirology
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/?term=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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Clinical Evaluation of Rega 8: An Updated Genotypic Interpretation System That Significantly Predicts HIV-Therapy Response

  • Autores: Beheydt G, Camacho R, Clotet B, De Luca A, Geretti AM, Grossman Z, Imbrechts S, Kaiser R, Libin P, Prosperi M, Schmit JC, Sönnerborg A, Torti C, Van Laethem K, Van Wijngaerden E, Vandamme AM, Vercauteren J, Zazzi M
  • Ano de Publicação: 2013
  • Journal: PLoS One
  • Link: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0061436

Clinically evaluating genotypic interpretation systems is essential to provide optimal guidance in designing potent individualized HIV-regimens. This study aimed at investigating the ability of the latest Rega algorithm to predict virological response on a short and longer period.
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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

  • Autores: Abecasis AB, Camacho RJ, Clotet B, De Luca A, Grossman Z, Schülter E, Snoeck J, Sönnerborg A, Struck D, Theys K, Torti C, Vandamme AM, Vercauteren J, Zazzi M
  • Ano de Publicação: 2013
  • Journal: Antimicrobial Agents and Chemotherapy
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/23183438

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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HIV-1 sub- type distribution and its demographic determinants in newly diagnosed patients in Europe suggest highly compartmentalized epidemics

  • Autores: Abecasis AB, Albert J, Åsjö B, Balotta C, Beshkov D, Boucher CB, Camacho RJ, Clotet B, De Gascun C, Griskevicius A, Grossman Z, Hamouda O, Horban A, Kolupajeva T, Korn K, Kostrikis LG, Kücherer C, Liitsola K, Linka M, Nielsen C, Otelea D, Paraskevis D, Paredes R, Poljak M, Puchhammer-Stöckl E, Schmit JC, Sönnerborg A, Staneková D, Stanojevic M, Struck D, Theys K, Van de Vijver DMC, Vandamme AM, Vercauteren J, Wensing AMJ
  • Ano de Publicação: 2013
  • Journal: Retrovirology
  • Link: http://www.retrovirology.com/content/10/1/7

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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