title: Geno2pheno: Estimating phenotypic drug resistance from HIV-1 genotypes.
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/).
authors.affiliation: Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66115 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de
authors.forename: Niko
authors.initials: N
authors.lastname: Beerenwinkel
authors.forename: Martin
authors.initials: M
authors.lastname: Däumer
authors.forename: Mark
authors.initials: M
authors.lastname: Oette
authors.forename: Klaus
authors.initials: K
authors.lastname: Korn
authors.forename: Daniel
authors.initials: D
authors.lastname: Hoffmann
authors.forename: Rolf
authors.initials: R
authors.lastname: Kaiser
authors.forename: Thomas
authors.initials: T
authors.lastname: Lengauer
authors.forename: Joachim
authors.initials: J
authors.lastname: Selbig
authors.forename: Hauke
authors.initials: H
authors.lastname: Walter
mesh_terms: D019380:Anti-HIV Agents / Q000627:therapeutic use; D016208:Databases, Factual; D024882:Drug Resistance, Viral / Q000235:genetics*; D015751:Genes, pol; D005838:Genotype; D015658:HIV Infections / Q000188:drug therapy; D015497:HIV-1 / Q000187:drug effects* / Q000235:genetics*; D006801:Humans; D020407:Internet; D010641:Phenotype; D012044:Regression Analysis; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
chemical_list: D019380:Anti-HIV Agents