Literature DB >> 26147742

Comparison of genotypic and virtual phenotypic drug resistance interpretations with laboratory-based phenotypes among CRF01_AE and subtype B HIV-infected individuals.

Awachana Jiamsakul1, Romanee Chaiwarith2, Nicolas Durier3, Sunee Sirivichayakul4, Sasisopin Kiertiburanakul5, Peter Van Den Eede6, Rossana Ditangco7, Adeeba Kamarulzaman8, Patrick C K Li9, Winai Ratanasuwan10, Thira Sirisanthana2.   

Abstract

HIV drug resistance assessments and interpretations can be obtained from genotyping (GT), virtual phenotyping (VP) and laboratory-based phenotyping (PT). We compared resistance calls obtained from GT and VP with those from PT (GT-PT and VP-PT) among CRF01_AE and subtype B HIV-1 infected patients. GT predictions were obtained from the Stanford HIV database. VP and PT were obtained from Janssen Diagnostics BVBA's vircoType(TM) HIV-1 and Antivirogram®, respectively. With PT assumed as the "gold standard," the area under the curve (AUC) and the Bland-Altman plot were used to assess the level of agreement in resistance interpretations. A total of 80 CRF01_AE samples from Asia and 100 subtype B from Janssen Diagnostics BVBA's database were analysed. CRF01_AE showed discordances ranging from 3 to 27 samples for GT-PT and 1 to 20 samples for VP-PT. The GT-PT and VP-PT AUCs were 0.76-0.97 and 0.81-0.99, respectively. Subtype B showed 3-61 discordances for GT-PT and 2-75 discordances for VP-PT. The AUCs ranged from 0.55 to 0.95 for GT-PT and 0.55 to 0.97 for VP-PT. Didanosine had the highest proportion of discordances and/or AUC in all comparisons. The patient with the largest didanosine FC difference in each subtype harboured Q151M mutation. Overall, GT and VP predictions for CRF01_AE performed significantly better than subtype B for three NRTIs. Although discrepancies exist, GT and VP resistance interpretations in HIV-1 CRF01_AE strains were highly robust in comparison with the gold-standard PT.
© 2015 Wiley Periodicals, Inc.

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Keywords:  algorithm; drug resistance; subtype

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Year:  2015        PMID: 26147742      PMCID: PMC4698354          DOI: 10.1002/jmv.24320

Source DB:  PubMed          Journal:  J Med Virol        ISSN: 0146-6615            Impact factor:   2.327


  27 in total

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Journal:  J Virol Methods       Date:  2007-06-15       Impact factor: 2.014

3.  A comparison of HIV-1 drug susceptibility as provided by conventional phenotyping and by a phenotype prediction tool based on viral genotype.

Authors:  Margriet Van Houtte; Gaston Picchio; Koen Van Der Borght; Theresa Pattery; Pierre Lecocq; Lee T Bacheler
Journal:  J Med Virol       Date:  2009-10       Impact factor: 2.327

4.  Comparison of algorithms that interpret genotypic HIV-1 drug resistance to determine the prevalence of transmitted drug resistance.

Authors:  Lin Liu; Susanne May; Douglas D Richman; Frederick M Hecht; Martin Markowitz; Eric S Daar; Jean-Pierre Routy; Joseph B Margolick; Ann C Collier; Christopher H Woelk; Susan J Little; Davey M Smith
Journal:  AIDS       Date:  2008-04-23       Impact factor: 4.177

5.  Predictors for the emergence of the 2 multi-nucleoside/nucleotide resistance mutations 69 insertion and Q151M and their impact on clinical outcome in the Swiss HIV cohort study.

Authors:  Alexandra U Scherrer; Viktor von Wyl; Beda Joos; Thomas Klimkait; Philippe Bürgisser; Sabine Yerly; Jürg Böni; Bruno Ledergerber; Huldrych F Günthard
Journal:  J Infect Dis       Date:  2011-02-01       Impact factor: 5.226

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Journal:  Top Antivir Med       Date:  2013 Feb-Mar

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Authors:  G Yebra; M de Mulder; J del Romero; C Rodríguez; A Holguín
Journal:  Antiviral Res       Date:  2009-12-11       Impact factor: 5.970

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Authors:  Diane E Bennett; Ricardo J Camacho; Dan Otelea; Daniel R Kuritzkes; Hervé Fleury; Mark Kiuchi; Walid Heneine; Rami Kantor; Michael R Jordan; Jonathan M Schapiro; Anne-Mieke Vandamme; Paul Sandstrom; Charles A B Boucher; David van de Vijver; Soo-Yon Rhee; Tommy F Liu; Deenan Pillay; Robert W Shafer
Journal:  PLoS One       Date:  2009-03-06       Impact factor: 3.240

10.  Human immunodeficiency virus reverse transcriptase and protease sequence database.

Authors:  Soo-Yon Rhee; Matthew J Gonzales; Rami Kantor; Bradley J Betts; Jaideep Ravela; Robert W Shafer
Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

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Authors:  Ying Mu; Sunitha Kodidela; Yujie Wang; Santosh Kumar; Theodore J Cory
Journal:  Expert Opin Pharmacother       Date:  2018-09-20       Impact factor: 3.889

2.  Natural polymorphisms in HIV-1 CRF01_AE strain and profile of acquired drug resistance mutations in a long-term combination treatment cohort in northeastern China.

Authors:  Zesong Sun; Jinming Ouyang; Bin Zhao; Minghui An; Lin Wang; Haibo Ding; Xiaoxu Han
Journal:  BMC Infect Dis       Date:  2020-02-26       Impact factor: 3.090

3.  Guidelines are needed for studies of pre-treatment HIV drug resistance: a methodological study.

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