title: Correlation between rules-based interpretation and virtual phenotype interpretation of HIV-1 genotypes for predicting drug resistance in HIV-infected individuals.
abstract: Drug resistance testing provides useful information for managing HIV-infected patients. Phenotyping could add complementary information to genotyping and occasionally be more useful, although is less available to clinicians. Large paired geno-pheno databases have allowed the prediction of phenotypes from genotypes. However, the accuracy of these virtual phenotypes (vPT) in a clinical setting has not been well assessed yet. We analyzed the concordance between vPT and interpreted genotype (GT) in 105 samples belonging to treatment-experienced HIV-infected patients. A high concordance was seen when examining both non-nucleoside reverse transcriptase inhibitors (NNRTI) and protease inhibitors (PI) (r = 0.95 either), while it was lower for nucleoside analogs (r = 0.79). The drugs with lower concordance were abacavir (71.1%), tenofovir (71.5%) and didanosine (71.9%). In 20% of specimens (21/105), the vPT did not provide results for all approved drugs. These were mainly samples with a high number of drug resistance mutations or rare genotypes, which seem to be underepresented in the VircoNET database. Overall, there is good correlation between vPT/GT, especially for PI and NNRTI. The inclusion of additional sequences in the VircoNET database, mainly those derived from heavily treatment-experienced patients and/or from patients failing the most recently approved drugs might improve its performance.
authors.affiliation: Service of Infectious Diseases, Hospital Carlos III, Madrid, Spain.
authors.forename: Oscar
authors.initials: O
authors.lastname: Gallego
authors.forename: Luz
authors.initials: L
authors.lastname: Martin-Carbonero
authors.forename: Jesus
authors.initials: J
authors.lastname: Aguero
authors.forename: Carmen
authors.initials: C
authors.lastname: de Mendoza
authors.forename: Angelica
authors.initials: A
authors.lastname: Corral
authors.forename: Vincent
authors.initials: V
authors.lastname: Soriano
mesh_terms: D000225:Adenine / Q000031:analogs & derivatives* / Q000494:pharmacology; D019943:Amino Acid Substitution; D019380:Anti-HIV Agents / Q000494:pharmacology*; D016049:Didanosine / Q000494:pharmacology; D015224:Dideoxynucleosides / Q000494:pharmacology; D024882:Drug Resistance, Viral / Q000235:genetics*; D005838:Genotype; D015658:HIV Infections / Q000188:drug therapy / Q000821:virology*; D015497:HIV-1 / Q000187:drug effects* / Q000235:genetics*; D006801:Humans; D008826:Microbial Sensitivity Tests; D009154:Mutation; D009705:Nucleosides / Q000494:pharmacology; D063065:Organophosphonates / Q000494:pharmacology; D010641:Phenotype; D011480:Protease Inhibitors / Q000494:pharmacology; D018894:Reverse Transcriptase Inhibitors / Q000494:pharmacology; D000068698:Tenofovir; D000099227:Abacavir
chemical_list: D000225:Adenine; D019380:Anti-HIV Agents; D016049:Didanosine; D015224:Dideoxynucleosides; D009705:Nucleosides; D063065:Organophosphonates; D011480:Protease Inhibitors; D018894:Reverse Transcriptase Inhibitors; D000068698:Tenofovir; D000099227:Abacavir