Improving lopinavir genotype algorithm through phenotype correlations

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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 (IC50) 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.

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