Performance of genotypic algorithms for predicting tropism of HIV-1CRF02_AG subtype

J Clin Virol. 2016 Mar:76:51-4. doi: 10.1016/j.jcv.2016.01.010. Epub 2016 Jan 21.

Abstract

Background: Several genotypic rules for predicting HIV-1 non-B subtypes tropism are commonly used, but there is no consensus about their performances.

Objectives: Three genotypic methods were compared for CRF02_AG HIV-1 tropism determination.

Study design: V3 env region of 178HIV-1 CRF02_AG from Pitié-Salpêtrière and Saint-Antoine Hospitals was sequenced from plasma HIV-1 RNA. HIV-1 tropism was determined by Geno2Pheno algorithm, false positive rate (FPR) 5% or 10%, the 11/25 rule or the combined criteria of the 11/25 and net charge rule.

Results: A concordance of 91.6% was observed between Geno2pheno 5% and the combined criteria. The results were nearly similar for the comparison between Geno2pheno 5% and the 11/25 rule. More mismatches were observed when Geno2pheno was used with the FPR 10%. A lower nadir CD4 cell count was associated with a discordance of tropism prediction between Geno2pheno 5% and the combined criteria or the 11/25 rule (p=0.02 and p=0.03, respectively). A lower HIV-1 viral load was associated with some discordance for the comparison of Geno2pheno 10% and the combined rule (p=0.02).

Conclusion: Geno2pheno FPR 5% or 10% predicted more X4-tropic viruses for this set of CRF02_AG sequences than the combined criteria or the 11/25 rule alone. Furthermore, Geno2pheno FPR 5% was more concordant with the 11/25 rule and the combined rule than Geno2pheno 10% to predict HIV-1 tropism. Overall, Geno2pheno 5% could be used to predict CRF02_AG tropism as well as other genotypic rules.

Keywords: Genotypic prediction; HIV tropism; Non B subtype.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • CD4 Lymphocyte Count
  • Computational Biology
  • Genotype
  • HIV Envelope Protein gp120 / genetics*
  • HIV Infections / virology*
  • HIV-1 / classification
  • HIV-1 / genetics
  • HIV-1 / physiology*
  • Humans
  • Peptide Fragments / genetics*
  • Phenotype
  • RNA, Viral / blood
  • Receptors, HIV
  • Viral Load
  • Viral Tropism*

Substances

  • HIV Envelope Protein gp120
  • HIV envelope protein gp120 (305-321)
  • Peptide Fragments
  • RNA, Viral
  • Receptors, HIV