Literature DB >> 12824435

Geno2pheno: Estimating phenotypic drug resistance from HIV-1 genotypes.

Niko Beerenwinkel1, Martin Däumer, Mark Oette, Klaus Korn, Daniel Hoffmann, Rolf Kaiser, Thomas Lengauer, Joachim Selbig, Hauke Walter.   

Abstract

Therapeutic success of anti-HIV therapies is limited by the development of drug resistant viruses. These genetic variants display complex mutational patterns in their pol gene, which codes for protease and reverse transcriptase, the molecular targets of current antiretroviral therapy. Genotypic resistance testing depends on the ability to interpret such sequence data, whereas phenotypic resistance testing directly measures relative in vitro susceptibility to a drug. From a set of 650 matched genotype-phenotype pairs we construct regression models for the prediction of phenotypic drug resistance from genotypes. Since the range of resistance factors varies considerably between different drugs, two scoring functions are derived from different sets of predicted phenotypes. Firstly, we compare predicted values to those of samples derived from 178 treatment-naive patients and report the relative deviance. Secondly, estimation of the probability density of 2000 predicted phenotypes gives rise to an intrinsic definition of a susceptible and a resistant subpopulation. Thus, for a predicted phenotype, we calculate the probability of membership in the resistant subpopulation. Both scores provide standardized measures of resistance that can be calculated from the genotype and are comparable between drugs. The geno2pheno system makes these genotype interpretations available via the Internet (http://www.genafor.org/).

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Year:  2003        PMID: 12824435      PMCID: PMC168981          DOI: 10.1093/nar/gkg575

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  11 in total

1.  World-wide variation in HIV-1 phenotypic susceptibility in untreated individuals: biologically relevant values for resistance testing.

Authors:  P R Harrigan; J S Montaner; S A Wegner; W Verbiest; V Miller; R Wood; B A Larder
Journal:  AIDS       Date:  2001-09-07       Impact factor: 4.177

2.  Diversity and complexity of HIV-1 drug resistance: a bioinformatics approach to predicting phenotype from genotype.

Authors:  Niko Beerenwinkel; Barbara Schmidt; Hauke Walter; Rolf Kaiser; Thomas Lengauer; Daniel Hoffmann; Klaus Korn; Joachim Selbig
Journal:  Proc Natl Acad Sci U S A       Date:  2002-06-11       Impact factor: 11.205

3.  Methods for optimizing antiviral combination therapies.

Authors:  Niko Beerenwinkel; Thomas Lengauer; Martin Däumer; Rolf Kaiser; Hauke Walter; Klaus Korn; Daniel Hoffmann; Joachim Selbig
Journal:  Bioinformatics       Date:  2003       Impact factor: 6.937

4.  Construction, training and clinical validation of an interpretation system for genotypic HIV-1 drug resistance based on fuzzy rules revised by virological outcomes.

Authors:  Andrea De Luca; Marilena Vendittelli; Francesco Baldini; Simona Di Giambenedetto; Maria Paola Trotta; Antonella Cingolani; Alessandra Bacarelli; Caterina Gori; Carlo Federico Perno; Andrea Antinori; Giovanni Ulivi
Journal:  Antivir Ther       Date:  2004-08

5.  The Genetic Basis of HIV-1 Resistance to Reverse Transcriptase and Protease Inhibitors.

Authors:  Robert W Shafer; Rami Kantor; Matthew J Gonzales
Journal:  AIDS Rev       Date:  2000       Impact factor: 2.500

6.  HIV treatment failure: testing for HIV resistance in clinical practice.

Authors:  L Perrin; A Telenti
Journal:  Science       Date:  1998-06-19       Impact factor: 47.728

7.  Rapid, phenotypic HIV-1 drug sensitivity assay for protease and reverse transcriptase inhibitors.

Authors:  H Walter; B Schmidt; K Korn; A M Vandamme; T Harrer; K Uberla
Journal:  J Clin Virol       Date:  1999-06       Impact factor: 3.168

8.  Methods for investigation of the relationship between drug-susceptibility phenotype and human immunodeficiency virus type 1 genotype with applications to AIDS clinical trials group 333.

Authors:  A D Sevin; V DeGruttola; M Nijhuis; J M Schapiro; A S Foulkes; M F Para; C A Boucher
Journal:  J Infect Dis       Date:  2000-07-06       Impact factor: 5.226

9.  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

Review 10.  Managing resistance to anti-HIV drugs: an important consideration for effective disease management.

Authors:  A M Vandamme; K Van Laethem; E De Clercq
Journal:  Drugs       Date:  1999-03       Impact factor: 11.431

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  76 in total

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Authors:  Brendan A Larder; Andrew Revell; Joann M Mican; Brian K Agan; Marianne Harris; Carlo Torti; Ilaria Izzo; Julia A Metcalf; Migdalia Rivera-Goba; Vincent C Marconi; Dechao Wang; Daniel Coe; Brian Gazzard; Julio Montaner; H Clifford Lane
Journal:  AIDS Patient Care STDS       Date:  2011-01       Impact factor: 5.078

2.  A support vector machine approach to assess drug efficacy of interferon-alpha and ribavirin combination therapy.

Authors:  Eugene Lin; Yuchi Hwang
Journal:  Mol Diagn Ther       Date:  2008       Impact factor: 4.074

3.  Genetically Intact but Functionally Impaired HIV-1 Env Glycoproteins in the T-Cell Reservoir.

Authors:  Anne de Verneuil; Julie Migraine; Fabrizio Mammano; Jean-Michel Molina; Sébastien Gallien; Hugo Mouquet; Allan J Hance; François Clavel; Jacques Dutrieux
Journal:  J Virol       Date:  2018-01-30       Impact factor: 5.103

4.  Web resources for HIV type 1 genotypic-resistance test interpretation.

Authors:  Tommy F Liu; Robert W Shafer
Journal:  Clin Infect Dis       Date:  2006-04-28       Impact factor: 9.079

Review 5.  Review of HIV antiretroviral drug resistance.

Authors:  Tempe K Chen; Grace M Aldrovandi
Journal:  Pediatr Infect Dis J       Date:  2008-08       Impact factor: 2.129

6.  Only slight impact of predicted replicative capacity for therapy response prediction.

Authors:  Hendrik Weisser; André Altmann; Saleta Sierra; Francesca Incardona; Daniel Struck; Anders Sönnerborg; Rolf Kaiser; Maurizio Zazzi; Monika Tschochner; Hauke Walter; Thomas Lengauer
Journal:  PLoS One       Date:  2010-02-03       Impact factor: 3.240

7.  A Rough Set-Based Model of HIV-1 Reverse Transcriptase Resistome.

Authors:  Marcin Kierczak; Krzysztof Ginalski; Michał Dramiński; Jacek Koronacki; Witold Rudnicki; Jan Komorowski
Journal:  Bioinform Biol Insights       Date:  2009-10-05

8.  Phylogenetic approach reveals that virus genotype largely determines HIV set-point viral load.

Authors:  Samuel Alizon; Viktor von Wyl; Tanja Stadler; Roger D Kouyos; Sabine Yerly; Bernard Hirschel; Jürg Böni; Cyril Shah; Thomas Klimkait; Hansjakob Furrer; Andri Rauch; Pietro L Vernazza; Enos Bernasconi; Manuel Battegay; Philippe Bürgisser; Amalio Telenti; Huldrych F Günthard; Sebastian Bonhoeffer
Journal:  PLoS Pathog       Date:  2010-09-30       Impact factor: 6.823

9.  Selecting anti-HIV therapies based on a variety of genomic and clinical factors.

Authors:  Michal Rosen-Zvi; Andre Altmann; Mattia Prosperi; Ehud Aharoni; Hani Neuvirth; Anders Sönnerborg; Eugen Schülter; Daniel Struck; Yardena Peres; Francesca Incardona; Rolf Kaiser; Maurizio Zazzi; Thomas Lengauer
Journal:  Bioinformatics       Date:  2008-07-01       Impact factor: 6.937

10.  Host sequence motifs shared by HIV predict response to antiretroviral therapy.

Authors:  William Dampier; Perry Evans; Lyle Ungar; Aydin Tozeren
Journal:  BMC Med Genomics       Date:  2009-07-23       Impact factor: 3.063

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