The expected effectiveness of protease inhibitors was assessed according to the Agence Nationale de Recherches sur le SIDA (ANRS), Rega and Stanford 2007 resistance algorithms in 93 and 87 antiretroviral therapy-naive patients, respectively, infected with B and non-B subtype viruses.
Either B or non-B subtypes were considered fully susceptible to protease inhibitors, except to tipranavir/ritonavir, for which the 2007 ANRS algorithm scored non-B subtypes as naturally resistant when this algorithm was extended to these subtypes.
aCRESGE-LEM-CNRS, Lille, France
bVirology Department, University Medical Centre, Lille, France
cCTRS-INSERM U795, Lille, France
dGastroenterology Department, Hôtel-Dieu Hospital, Hospices Civils, Lyon, France
eINSERM U871, Lyon, France
fVirology Department, Hospices Civils, Lyon, France
gInfectious Diseases Department, Medical Centre Tourcoing, France
hMedicine Faculty, University of Lille II, Lille, France.
Correspondence to Karen Champenois, CRESGE-LEM-CNRS, 41 rue du Port, 59046 Lille Cedex, France. Tel: +33 3 20 13 40 60; fax: +33 3 20 13 40 70; e-mail: firstname.lastname@example.org
Most studies designed to evaluate the natural history of HIV and the effectiveness of antiretroviral therapy (ART) were conducted in the northern countries and therefore mainly in patients infected with the HIV-1 B subtype. Few data are available about the pathogenicity and susceptibility to ART of HIV-1 non-B subtypes. Non-B subtypes harbour a large number of natural polymorphisms, especially in their protease [1–4].
The present study determined the expected effectiveness of protease inhibitors in ART-naive patients infected with HIV-1 non-B subtypes, as indicated by available resistance algorithms taking into account primary, secondary and polymorphic mutations.
This French study included 180 HIV-1-infected patients: 46 from the Hôtel-Dieu Hospital in Lyons and 134 from the Tourcoing AIDS Reference Centre. All patients had an available genotype resistance testing and were ART-naive at the time of the study, and initiated a first-line protease inhibitor-containing ART regimen between June 2004 and August 2006.
In Lyons, genotypes resistance testing was performed with the modified ANRS technique used with BeckmanCeq 2000 (Beckman Coulter Inc., USA). Subtypes were determined on the Stanford and Rega websites (http://hivdb.stanford.edu/, http://www.rega.kuleuven.be/cev). In Tourcoing, genotypes were performed with the Trugene HIV-1 genotyping Kit and the OpenGene DNA Sequencing System and subtypes determination with reverse transcriptase genotyping GeneObjects/GeneLibrarian Software (all from Siemens Medical Solutions Diagnostics SAS, France).
Three resistance algorithms, ANRS (July 2007, http://www.hivfrenchresistance.org), Rega (July 2007, http://www.rega.kuleuven.be/cev ) and Stanford (September 2007, http://hivdb.stanford.edu) were applied to genotypes resistance testing to determine the expected proportions of B and non-B viruses resistant to the following boosted protease inhibitors: atazanavir (ATZ/r), darunavir (DRV/r), fosamprenavir (FPV/r), lopinavir (LPV/r), saquinavir (SQV/r) and tipranavir (TPV/r). The authors of the study  that highlighted the TPV/r mutation score for the 2007 ANRS algorithm stated that this score should only be applied to the B subtype, given the small number of TPV/r-treated patients infected with non-B subtypes. However, in the absence of an updated TPV/r algorithm for non-B subtypes, we applied the 2007 ANRS algorithm to them. The ANRS and Rega algorithms define three levels of resistance: susceptible, intermediate and resistant. For the Stanford algorithm, we used the score indicating viral resistance to the drug when the total score was over 30.
Of the 180 patients enrolled, 93 (52%) were infected with a B subtype virus and 87 (48%) with a non-B subtype virus (A: n = 6, C: n = 6, D: n = 6, G: n = 8, J: n = 3, K: n = 2, CRF01: n = 7, CRF02: n = 41, CRF06: n = 4, CRF09: n = 1, CRF15: n = 3). Of patients with a non-B subtype, 56 (64.4%) were sub-Saharan Africans and 31 (35.6%) were Caucasians. At enrolment, the CD4 cell count was similar for both subtype groups (218/μl for non-B versus 224 for B, P = 0.76), but the viral load was lower in non-B than B subtypes (4.83 versus 5.09 log10 copies/ml, P = 0.008). The median period between HIV-infection diagnosis and genotype resistance testing was 1.7 months (interquartile range = 0.4–29.7).
One hundred thirty-five distinct mutations were identified at 50 protease positions. The most prevalent were S37N (63%), R41K (57%), M36I (53%), I13V (48%), L89M (45%), H69K (44%), E35D (39%), L63P (36%) and K20I (30%). Non-B subtype viruses harboured more protease mutations than B subtype viruses (median 11 versus 7, P < 10−4). According to the algorithms, the mutations found were either polymorphisms or secondary resistance mutations. No primary mutation of resistance to the protease inhibitors studied was noted.
Each algorithm was applied to the viral genotype of each patient. The ANRS, Rega and Stanford algorithms scored all patients, whatever their viral subtype, as susceptible to ATZ/r, DRV/r, FPV/r and LPV/r. With the ANRS algorithm, seven patients (3.9%), two with B and five with non-B subtypes, were considered intermediately resistant to SQV/r, with the Rega algorithm, one patient with a B subtype (0.6%), but with the Stanford algorithm, none (Fig. 1). For TPV/r, algorithm interpretations were discrepant. The Rega and Stanford algorithms scored all patients with B and non-B subtypes as fully susceptible to TPV/r, whereas the ANRS algorithm scored 78 patients (43.3%) [all harboured non-B subtypes and constituted 89.7% of all the non-B subtypes (Fig. 1)] as resistant to TPV/r and eight patients (4.4%), two with B and six with non-B subtypes, as intermediately resistant to TPV/r.
As the 2007 ANRS algorithm can only be applied to the B subtype, the results of this study should be interpreted with caution. However, algorithms for the B subtype are usually applied to non-B subtypes. The discordant results for TPV/r were due to the differences in mutations algorithms retain as leading to resistance. Thus, in the ANRS algorithm for TPV/r, mutations M36I, H69K and L89M are taken into account, and each of these mutations was recorded in about 90% of non-B subtype viruses studied. However, the Rega algorithm for TPV/r only takes into account mutations M36I and H69K, considered to confer low-resistance potency. None of these mutations are retained by the Stanford algorithm.
The 2007 ANRS TPV/r mutation score was based on the in-vivo results for 127 B and 16 non-B subtypes-infected ART-experienced patients. Although the small number of these non-B subtypes did not allow the authors to extend the mutation score to all subtypes, TPV/r was found to be less effective in patients infected with non-B subtypes (25% of non-B versus 59% of B subtype had a virological response at 3 months, P = 0.015) . Nevertheless, Abecasis et al.  found in vitro that all the 32 non-B viruses they studied were susceptible to TPV/r.
The present study showed that, according to available resistance algorithms, non-B subtypes were susceptible to nearly all protease inhibitors without any discrepancies between algorithms. However, we found discordance between the TPV/r algorithms, with a very high proportion of non-B subtype viruses expected to be resistant to TPV/r in ART-naive patients when the 2007 ANRS algorithm was extended to non-B subtypes. This shows the need for clinical studies to validate a TPV/r mutation score in HIV-1 non-B subtypes. In the era of widespread ART, it is important to establish whether or not non-B subtypes, which predominate in developing countries and are increasingly frequent in developed countries [7–9], are naturally resistant to TPV/r.
We are grateful to the Stop SIDA association for financial support.
1. Abecasis AB, Deforche K, Bacheler LT, McKenna P, Carvalho AP, Gomes P, et al
. Investigation of baseline susceptibility to protease inhibitors in HIV-1 subtypes C, F, G and CRF02_AG. Antivir Ther 2006; 11:581–589.
2. Vergne L, Stuyver L, Van Houtte M, Butel C, Delaporte E, Peeters M. Natural polymorphism in protease and reverse transcriptase genes and in vitro antiretroviral drug susceptibilities of non-B HIV-1 strains from treatment-naive patients. J Clin Virol 2006; 36:43–49.
3. Koizumi Y, Ndembi N, Miyashita M, Lwembe R, Kageyama S, Mbanya D, et al
. Emergence of antiretroviral therapy resistance-associated primary mutations among drug-naive HIV-1-infected individuals in rural western Cameroon. J Acquir Immune Defic Syndr 2006; 43:15–22.
4. Frater AJ, Beardall A, Ariyoshi K, Churchill D, Galpin S, Clarke JR, et al
. Impact of baseline polymorphisms in RT and protease on outcome of highly active antiretroviral therapy in HIV-1-infected African patients. AIDS 2001; 15:1493–1502.
5. Van Laethem K, De Luca A, Antinori A, Cingolani A, Perna CF, Vandamme AM. A genotypic drug resistance interpretation algorithm that significantly predicts therapy response in HIV-1-infected patients. Antivir Ther 2002; 7:123–129.
6. Flandre P, Marcelin AG, Masquelier B, Descamps D, Izopet J, Charpentier C, et al
. Impact of HIV-1 subtype in selecting mutations associated with response to boosted tipranavir in HIV-1-infected protease inhibitor experienced patients. Antivir Ther 2007; 12:S83.
7. Chaix ML, Descamps D, Harzic M, Schneider V, Deveau C, Tamalet C, et al
. Stable prevalence of genotypic drug resistance mutations but increase in non-B virus among patients with primary HIV-1 infection in France. AIDS 2003; 17:2635–2643.
8. Lawrence P, Lutz MF, Saoudin H, Fresard A, Cazorla C, Fascia P, et al
. Analysis of polymorphism in the protease and reverse transcriptase genes of HIV type 1 CRF02-AG subtypes from drug-naive patients from Saint-Etienne, France. J Acquir Immune Defic Syndr 2006; 42:396–404.
9. Spira S, Wainberg MA, Loemba H, Turner D, Brenner BG. Impact of clade diversity on HIV-1 virulence, antiretroviral drug sensitivity and drug resistance. J Antimicrob Chemother 2003; 51:229–240.