Literature DB >> 17913806

Mapping protease inhibitor resistance to human immunodeficiency virus type 1 sequence polymorphisms within patients.

Art F Y Poon1, Sergei L Kosakovsky Pond, Douglas D Richman, Simon D W Frost.   

Abstract

Resistance genotyping provides an important resource for the clinical management of patients infected with human immunodeficiency virus type 1 (HIV-1). However, resistance to protease (PR) inhibitors (PIs) is a complex phenotype shaped by interactions among nearly half of the residues in HIV-1 PR. Previous studies of the genetic basis of PI resistance focused on fixed substitutions among populations of HIV-1, i.e., host-specific adaptations. Consequently, they are susceptible to a high false discovery rate due to founder effects. Here, we employ sequencing "mixtures" (i.e., ambiguous base calls) as a site-specific marker of genetic variation within patients that is independent of the phylogeny. We demonstrate that the transient response to selection by PIs is manifested as an excess of nonsynonymous mixtures. Using a sample of 5,651 PR sequences isolated from both PI-naive and -treated patients, we analyze the joint distribution of mixtures and eight PIs as a Bayesian network, which distinguishes residue-residue interactions from direct associations with PIs. We find that selection for resistance is associated with the emergence of nonsynonymous mixtures in two distinct groups of codon sites clustered along the substrate cleft and distal regions of PR, respectively. Within-patient evolution at several positions is independent of PIs, including those formerly postulated to be involved in resistance. These positions are under strong positive selection in the PI-naive patient population, implying that other factors can produce spurious associations with resistance, e.g., mutational escape from the immune response.

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Year:  2007        PMID: 17913806      PMCID: PMC2168824          DOI: 10.1128/JVI.01570-07

Source DB:  PubMed          Journal:  J Virol        ISSN: 0022-538X            Impact factor:   5.103


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