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Prediction of HIV type 1 subtype C tropism by genotypic algorithms built from subtype B viruses. | LitMetric

AI Article Synopsis

  • Genotypic predictions of HIV-1 tropism could enhance the effectiveness of CCR5 antagonists, but algorithms developed for subtype B may not be reliable for non-B subtypes.
  • A study involving 73 patients (52 from Malawi and 21 from France) used genotypic sequencing and phenotypic assays to determine subtype C tropism.
  • Results showed that patients in Malawi had a higher prevalence of CXCR4-using viruses and indicated that several genotypic algorithms, including ones developed for subtype B, were effective in predicting coreceptor usage in subtype C, with significant sensitivity and specificity ratings.

Article Abstract

Background: Genotypic predictions of HIV-1 tropism could simplify CCR5 antagonist usage. However, the genotypic algorithms built from subtype B viruses could be inadequate for non-B subtypes. We therefore performed paired genotypic and phenotypic determination of subtype C tropism.

Methods: We studied 52 patients recruited in Malawi and 21 patients recruited in France. We directly sequenced the V3 env region and performed a recombinant virus phenotypic entry assay in parallel.

Results: The Malawi patients had 29% of CXCR4-using subtype C viruses compared with only 5% in the patients from France. For detecting CXCR4-using subtype C viruses, the genotypic rule combining the amino acids at positions 11/25 and the net charge of V3 was 93.3% sensitive and 96.4% specific. The Geno2pheno tool was 86.7% sensitive and 89.1% specific. The WebPSSM tool with the SI/NSI matrix was 80% sensitive and 98.2% specific in its subtype B version and 93.3% sensitive and 81.8% specific in its subtype C version.

Conclusions: The genotypic determinants of coreceptor usage for HIV-1 subtype C were mainly in V3 and were globally similar to those previously reported for subtype B viruses. The main genotypic algorithms built from subtype B viruses perform well when applied to subtype C viruses.

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Source
http://dx.doi.org/10.1097/QAI.0b013e3181c8413bDOI Listing

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