Literature DB >> 20427374

High sensitivity of specific genotypic tools for detection of X4 variants in antiretroviral-experienced patients suitable to be treated with CCR5 antagonists.

Eduardo Seclén1, Carolina Garrido, María del Mar González, Juan González-Lahoz, Carmen de Mendoza, Vincent Soriano, Eva Poveda.   

Abstract

OBJECTIVES: Evaluation of the reliability of several V3-based genotypic predictors to infer viral tropism in patients infected with B and non-B strains of HIV-1.
METHODS: Several genotypic tropism predictors were evaluated in plasma (RNA) samples from 198 HIV-1-infected patients, taking as gold standard the results of the phenotypic recombinant virus assay Phenoscript((R)). In addition, for 37 B subtype HIV-1 patients the phenotypic results from plasma samples were also compared with tropism predictions based on V3 amplification from paired peripheral blood mononuclear cells (PBMCs).
RESULTS: A total of 150 paired genotypic/phenotypic results were obtained from plasma specimens. Concordance values ranged from 63% to 85%, depending on the genotypic algorithm used. The best predictors in terms of sensitivity/specificity to detect X4 variants were WebPSSM(X4/R5) (77%/87%), Geno2pheno(FPR) (=) (5%) (80%/77%) and an algorithm combining the '11/25' and 'Net charge' rules, termed Garrido's rule (80%/79%). The performance of genotypic predictors was better testing B than non-B clades. The overall sensitivity ranged from 28% to 94%, reaching 100% in subtype B antiretroviral-experienced patients using WebPSSM(SI/NSI), Geno2pheno(FPR) (> or =) (5%) and Garrido's rule. Conversely, the sensitivity when testing non-B subtypes was poorer, ranging from 17% to 67%. Interestingly, the correlation between genotypic and phenotypic results was better when testing PBMCs than plasma using all genotypic predictors.
CONCLUSIONS: Genotypic tools based on V3 sequences may provide reliable information on HIV-1 tropism when testing clade B viruses, especially in antiretroviral-experienced patients. The sensitivity to detect X4 variants using genotypic tools may improve by testing proviral DNA instead of plasma RNA.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20427374     DOI: 10.1093/jac/dkq137

Source DB:  PubMed          Journal:  J Antimicrob Chemother        ISSN: 0305-7453            Impact factor:   5.790


  22 in total

1.  Evolution of proviral DNA HIV-1 tropism under selective pressure of maraviroc-based therapy.

Authors:  Silvia Baroncelli; Clementina Maria Galluzzo; Liliana Elena Weimer; Maria Franca Pirillo; Anna Volpe; Alessandra Mercuri; Albertina Cavalli; Vincenzo Fragola; Laura Monno; Anna Degli Antoni; Nicoletta Ladisa; Daniela Francisci; Raffaella Bucciardini; Marco Floridia
Journal:  J Antimicrob Chemother       Date:  2012-02-23       Impact factor: 5.790

2.  Algorithm-based prediction of HIV-1 subtype D coreceptor use.

Authors:  Julia Dina; Stephanie Raymond; Anne Maillard; Helene Le Guillou-Guillemette; Audrey Rodalec; Agnes Beby-Defaux; Genevieve Giraudeau; Sophie Vallet; Thomas Mourez; Christopher Payan; Astrid Vabret; Annick Ruffault; Virginie Ferre; Jacques Izopet; Jean-Christophe Plantier
Journal:  J Clin Microbiol       Date:  2013-06-26       Impact factor: 5.948

3.  High concordance between the position-specific scoring matrix and geno2pheno algorithms for genotypic interpretation of HIV-1 tropism: V3 length as the major cause of disagreement.

Authors:  Eduardo Seclén; Vicente Soriano; María M González; Sagrario Gómez; Alexander Thielen; Eva Poveda
Journal:  J Clin Microbiol       Date:  2011-07-06       Impact factor: 5.948

4.  Concordance of HIV type 1 tropism phenotype to predictions using web-based analysis of V3 sequences: composite algorithms may be needed to properly assess viral tropism.

Authors:  Gabriela Bastos Cabral; João Leandro de Paula Ferreira; Luana Portes Osório Coelho; Mylva Fonsi; Denise Lotufo Estevam; Jaqueline Souza Cavalcanti; Luis Fernando de Macedo Brígido
Journal:  AIDS Res Hum Retroviruses       Date:  2011-12-02       Impact factor: 2.205

5.  Impact of baseline HIV-1 tropism on viral response and CD4 cell count gains in HIV-infected patients receiving first-line antiretroviral therapy.

Authors:  Eduardo Seclén; Vicente Soriano; María M González; Luz Martín-Carbonero; Holger Gellermann; Manuel Distel; Werner Kadus; Eva Poveda
Journal:  J Infect Dis       Date:  2011-07-01       Impact factor: 5.226

6.  Pace of Coreceptor Tropism Switch in HIV-1-Infected Individuals after Recent Infection.

Authors:  Muhammad Shoaib Arif; James Hunter; Ana Rachel Léda; Jean Paulo Lopes Zukurov; Sadia Samer; Michelle Camargo; Juliana Galinskas; Esper Georges Kallás; Shirley Vasconcelos Komninakis; Luiz Mario Janini; Maria Cecilia Sucupira; Ricardo Sobhie Diaz
Journal:  J Virol       Date:  2017-09-12       Impact factor: 5.103

7.  Genotypic prediction of HIV-1 CRF01-AE tropism.

Authors:  Stéphanie Raymond; Pierre Delobel; Sylvie Rogez; Stéphanie Encinas; Patrick Bruel; Christophe Pasquier; Karine Sandres-Sauné; Bruno Marchou; Patrice Massip; Jacques Izopet
Journal:  J Clin Microbiol       Date:  2012-12-05       Impact factor: 5.948

8.  Factors influencing the sensitivity and specificity of conventional sequencing in human immunodeficiency virus type 1 tropism testing.

Authors:  David J H F Knapp; Rachel A McGovern; Winnie Dong; Art F Y Poon; Luke C Swenson; Xiaoyin Zhong; Conan K Woods; P Richard Harrigan
Journal:  J Clin Microbiol       Date:  2012-11-21       Impact factor: 5.948

9.  Determination of the high prevalence of Dual/Mixed- or X4-tropism among HIV type 1 CRF01_AE in Hong Kong by genotyping and phenotyping methods.

Authors:  Sabrina Wai-Chi To; Jonathan Hon-Kwan Chen; Ka-Hing Wong; Kenny Chi-Wai Chan; Zhiwei Chen; Wing-Cheong Yam
Journal:  AIDS Res Hum Retroviruses       Date:  2013-05-31       Impact factor: 2.205

10.  A genotypic test for HIV-1 tropism combining Sanger sequencing with ultradeep sequencing predicts virologic response in treatment-experienced patients.

Authors:  Ron M Kagan; Erik P Johnson; Martin Siaw; Pinaki Biswas; Douglass S Chapman; Zhaohui Su; Jamie L Platt; Rick L Pesano
Journal:  PLoS One       Date:  2012-09-27       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.