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Objective: The aim of this study was to evaluate tropism prediction performances of three algorithms [geno2pheno false-positive rate 10% (G2P10), position-specific scoring matrix (PSSM) and a combination of the 11/25 and net charge rules] and to investigate the viral and host factors potentially involved in the X4 or R5 prediction in human immunodeficiency virus-1 (HIV-1) patients., Methods: Viral tropism was determined in 179 HIV-1-infected patients eligible for CCR5 antagonist therapy. HIV-1 RNA or DNA was extracted and amplified for env gp120 sequencing. In parallel, demographic, viral, immunological and clinical determinants were analyzed., Results: According to the G2P10 algorithm, 48 patients harbored X4 or X4R5 virus. The tropism prediction was concordant for 87.7 and 88.2% of samples when comparing G2P10 with PSSM or with a combination of the 11/25 and net charge rules, respectively. X4 prediction was significantly associated with more than 35 amino acids in the V3 domain (p < 0.0001) and loss of an N-linked glycosylation site (p < 0.0001). Of the factors studied, only the nadir CD4 T-cell count was significantly associated with X4 tropism (p = 0.01)., Conclusion: We determined that the X4 virus detection is closely linked to the nadir CD4 T-cell count below 100 cells/mm(3) that must be taken into account when considering a CCR5 antagonist therapy switch.

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.