title: Improving lopinavir genotype algorithm through phenotype correlations: novel mutation patterns and amprenavir cross-resistance.
abstract: BACKGROUND
  Current genotypic algorithms suggest that the HIV-1 protease inhibitors (PI) lopinavir (LPV) and amprenavir (APV) have distinct resistance profiles. However, phenotypic data indicate that cross-resistance is more common than expected.
  
  
  METHODS
  Protease genotype (GT) and phenotype (PT) from 1418 patient viruses with reduced PI susceptibility and/or resistance-associated mutations (training data) were analyzed. Samples were classified as LPV resistant by GT (GT-R) if six or more LPV mutations were present, and by PT (PT-R) if the 50% inhibitory concentration (IC(50)) fold-change (FC) was over 10.
  
  
  RESULTS
  There were 182 samples (13%) that were GT-S but PT-R for LPV. A comparison of the mutation prevalence in PT-R/GT-S samples with that in PT-S/GT-S samples identified mutations associated with LPV PT-R. Several previously defined LPV mutations were found to have a stronger than average effect (e.g., M46I/L, I54V/T, V82A/F), and new variants at known positions (e.g., I54A/M/S, V82S) were identified. Other mutations, including known APV resistance mutations, were found to contribute to reduced LPV susceptibility. A new LPV genotypic interpretation algorithm was constructed that improved overall genotypic/phenotypic concordance from 80% to 91%. The algorithm demonstrated a concordance rate of 90% when tested on 523 new samples. Cross-resistance between APV and LPV was greater in samples with primary APV resistance mutations than in those lacking them.
  
  
  CONCLUSIONS
  The current LPV mutation score does not fully account for many resistant viruses. Consequently, cross-resistance between LPV and APV is underappreciated. Phenotypic results from large and diverse patient virus populations should be used to guide the development of more accurate GT interpretation algorithms.
authors.affiliation: ViroLogic, South San Francisco, California, USA.
authors.forename: Neil T
authors.initials: NT
authors.lastname: Parkin
authors.forename: Colombe
authors.initials: C
authors.lastname: Chappey
authors.forename: Christos J
authors.initials: CJ
authors.lastname: Petropoulos
mesh_terms: D000465:Algorithms; D002219:Carbamates; D024882:Drug Resistance, Viral / Q000235:genetics*; D005663:Furans; D005838:Genotype; D015658:HIV Infections / Q000188:drug therapy* / Q000235:genetics; D016333:HIV Protease / Q000235:genetics*; D017320:HIV Protease Inhibitors / Q000627:therapeutic use*; D015497:HIV-1 / Q000235:genetics*; D006801:Humans; D061466:Lopinavir; D009154:Mutation / Q000235:genetics*; D010641:Phenotype; D011744:Pyrimidinones / Q000627:therapeutic use*; D013449:Sulfonamides / Q000627:therapeutic use*
chemical_list: D002219:Carbamates; D005663:Furans; D017320:HIV Protease Inhibitors; D011744:Pyrimidinones; D013449:Sulfonamides; D061466:Lopinavir; C095108:amprenavir; D016333:HIV Protease