ArticleAIDS research and human retroviruses2012
Concordance of HIV type 1 tropism phenotype to predictions using web-based analysis of V3 sequences: composite algorithms may be needed to properly assess viral tropism.
Article in AIDS research and human retroviruses, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 7 citations in OpenAlex.
- Net charge and position 22 of the V3 loop are associated with HIV-1 tropism in recently infected female sex workers in Nairobi, Kenya.Medicine · 2022Article
- A diagnostic HIV-1 tropism system based on sequence relatedness.Journal of clinical microbiology · 2015Article
- Parameters Influencing Baseline HIV-1 Genotypic Tropism Testing Related to Clinical Outcome in Patients on Maraviroc.PloS one · 2015Article
- Bioinformatic analysis of HIV-1 entry and pathogenesis.Current HIV research · 2014Review
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7 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Genotypic prediction of HIV-1 tropism has been considered a practical surrogate for phenotypic tests and recently an European Consensus has set up recommendations for its use in clinical practice. Twenty-five antiretroviral-experienced patients, all heavily treated cases with a median of 16 years of antiretroviral therapy, had viral tropism determined by the Trofile assay and predicted by HIV-1 sequencing of partial env, followed by interpretation using web-based tools. Trofile determined 17/24 (71%) as X4 tropic or dual/mixed viruses, with one nonreportable result. The use of European consensus recommendations for single sequences (geno2pheno false-positive rates 20% cutoff) would lead to 4/24 (16.7%) misclassifications, whereas a composite algorithm misclassified 1/24 (4%). The use of the geno2pheno clinical option using CD4 T cell counts at collection was useful in resolving some discrepancies. Applying the European recommendations followed by additional web-based tools for cases around the recommended cutoff would resolve most misclassifications.
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