Scientific Publications by FDA Staff

PLoS One 2014 Nov 7;9(11):e112434

Genotypic Prediction of Tropism of Highly Diverse HIV-1 Strains from Cameroon.

Mbondji-Wonje C, Ragupathy V, Zhao J, Nanfack A, Lee S, Torimiro J, Nyambi P, Hewlett IK

BACKGROUND: The use of CCR5 antagonists involves determination of HIV-1 tropism prior to initiation of treatment. HIV-1 tropism can be assessed either by phenotypic or genotypic methods. Genotypic methods are extensively used for tropism prediction. However, their validation in predicting tropism of viral isolates belonging to group M non-B subtypes remains challenging. In Cameroon, the genetic diversity of HIV-1 strains is the broadest reported worldwide. To facilitate the integration of CCR5 antagonists into clinical practice in this region, there is a need to evaluate the performance of genotypic methods for predicting tropism of highly diverse group M HIV-1 strains. METHODS: Tropism of diverse HIV-1 strains isolated from PBMCs from Cameroon was determined using the GHOST cell assay. Prediction, based on V3 sequences from matched plasma samples, was determined using bioinformatics algorithms and rules based on position 11/25 and net charge applied independently or combined according to Delobel's and Garrido's rules. Performance of genotypic methods was evaluated by comparing prediction generated with tropism assigned by the phenotypic assay. RESULTS: Specificity for predicting R5-tropic virus was high, ranging from 83.7% to 97.7% depending on the genotypic methods used. Sensitivity for X4-tropic viruses was fairly low, ranging from 33.3% to 50%. In our study, overall, genotypic methods were less able to accurately predict X4-tropic virus belonging to subtype CRF02_AG. In addition, it was found that of the methods we used the Garrido rule has the highest sensitivity rate of over 50% with a specificity of 93%. CONCLUSION: Our study demonstrated that overall, genotypic methods were less sensitive for accurate prediction of HIV-1 tropism in settings where diverse HIV-1 strains co-circulate. Our data suggest that further optimization of genotypic methods is needed and that larger studies to determine their utility for tropism prediction of diverse HIV-1 strains may be warranted.