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Related Experiment Videos

Improving lopinavir genotype algorithm through phenotype correlations: novel mutation patterns and amprenavir

Neil T Parkin1, Colombe Chappey, Christos J Petropoulos

  • 1ViroLogic, South San Francisco, California, USA.

AIDS (London, England)
|April 18, 2003
PubMed
Summary

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Current HIV-1 genotypic algorithms underestimate cross-resistance between lopinavir (LPV) and amprenavir (APV). Phenotypic data reveal more common cross-resistance, necessitating improved genotypic interpretation algorithms for accurate HIV-1 protease inhibitor resistance assessment.

Area of Science:

  • Virology
  • Infectious Diseases
  • Pharmacogenomics

Background:

  • Current genotypic algorithms for HIV-1 protease inhibitors (PI) suggest distinct resistance profiles for lopinavir (LPV) and amprenavir (APV).
  • Phenotypic data indicate a higher degree of cross-resistance between LPV and APV than currently predicted by genotypic methods.

Purpose of the Study:

  • To investigate discrepancies between genotypic and phenotypic resistance profiles for LPV and APV.
  • To identify specific mutations contributing to LPV resistance and cross-resistance with APV.
  • To develop an improved genotypic interpretation algorithm for LPV resistance.

Main Methods:

  • Analysis of protease genotype (GT) and phenotype (PT) data from 1418 HIV-1 patient viruses with reduced PI susceptibility.
  • Classification of samples as LPV resistant by GT (GT-R) with ≥6 mutations or by PT (PT-R) with IC(50) fold-change >10.

Related Experiment Videos

  • Identification of mutations associated with LPV PT-R in samples discordant between GT and PT.

    • Main Results:

    • 182 samples (13%) were genotypically susceptible but phenotypically resistant to LPV.
    • Several known LPV mutations (e.g., M46I/L, I54V/T, V82A/F) showed a stronger effect, and new variants were identified.
    • Known APV resistance mutations contributed to reduced LPV susceptibility, indicating significant cross-resistance.
    • A new LPV genotypic interpretation algorithm improved concordance from 80% to 91% and showed 90% concordance on new samples.

    Conclusions:

    • The current LPV mutation scoring system inadequately accounts for resistant HIV-1 variants.
    • Cross-resistance between LPV and APV is underestimated by existing genotypic algorithms.
    • Incorporating phenotypic data from diverse patient populations is crucial for developing more accurate genotypic interpretation algorithms for HIV-1 PI resistance.