Antiviral Research 85 (2010) 409–417 Contents lists available at ScienceDirect Antiviral Research journal homepage: www.elsevier.com/locate/antiviral HIV-1 non-B subtypes: High transmitted NNRTI-resistance in Spain and impaired genotypic resistance interpretation due to variability G. Yebra a , M. de Mulder a , J. del Romero b , C. Rodríguez b , A. Holguín a,* a HIV-1 Molecular Epidemiology Laboratory, Department of Microbiology, Hospital Universitario Ramón y Cajal and CIBER-ESP, Crta. Colmenar Viejo, Km. 9.100, Madrid 28034, Spain b Centro Sanitario Sandoval, Madrid, Spain article info Article history: Received 15 September 2009 Received in revised form 29 October 2009 Accepted 30 November 2009 Keywords: HIV-1 subtypes Drug-resistance mutations Genotypic resistance algorithms Subtyping tools abstract Genotypic resistance algorithms interpret drug-resistance mutations, but are mainly developed for HIV- 1 subtype B, meanwhile non-B subtypes cause 90% of worldwide infections. They include clade-specific amino acid at drug-resistance positions different than subtype B. This study explores: (i) the variability at resistance-related positions in 128 non-B and 226 B sequences from 354 treatment-naïve patients diagnosed in Spain (1999–2007); (ii) the discordances between five resistance interpretation algorithms (ANRS, Stanford, Rega, Geno2pheno, RIS); and (iii) the reliability of five subtyping tools (Stanford, Geno2pheno, Rega, NCBI, EuResist) for each HIV-1 variant. Primary drug-resistance prevalence was 13.6%, although higher in non-B vs. B subtypes (18.7% vs. 10.6%), due to a twofold higher NNRTI-resistance prevalence (15.7% vs. 7.6%). Most secondary PI- resistances, more frequent in non-B, were in fact clade-specific residues. Most sequences were interpreted as susceptible to all antiretrovirals by the five resistance algorithms, except for tipranavir by ANRS in non- B clades. Interalgorithm discordances were significantly higher in non-B variants for specific drugs. The agreement with phylogenetic analysis differed among subtyping tools testing non-B variants. We found a higher prevalence of NNRTI-resistance mutations in non-B subtypes. Certain algorithms overestimate the resistance in non-B subtypes due to natural patterns of mutations. Subtyping tools should be optimised for non-B variants. © 2009 Elsevier B.V. All rights reserved. 1. Introduction The expanding use of antiretroviral drugs for the treatment against human immunodeficiency virus type-1 (HIV-1) favours the emergence of virus harbouring resistance mutations. This can gen- erate an increasing prevalence of primary resistance mutations in viruses from treatment-naïve patients who have been infected by pre-treated subjects, compromising the effectiveness of the first antiretroviral therapy. Transmission of drug resistant viruses has been widely reported in Europe and the USA, with a prevalence ranging from 5% to 15% (Booth and Geretti, 2007; Sagir et al., 2007; Wensing et al., 2005; Wheeler et al., 2007). In Spain, the rate of pri- mary resistance mutations differs among regions and time periods, but these mutations are present in around 10% of treatment-naïve patients (de Mendoza et al., 2005; Martínez-Picado et al., 2005; Palacios et al., 2008; Sanchez-O ˜ noro et al., 2007). The rate rarely reaches 10% in treatment-naïve patients from developing coun- tries (Geretti, 2007; Nyombi et al., 2008; Ojesina et al., 2006), and is * Corresponding author. Tel.: +34 91 3368152; fax: +34 91 3368809. E-mail addresses: aholguin.hciii@salud.madrid.org, aholguinhciii@gmail.com (A. Holguín). mainly limited to a few reverse transcriptase inhibitors (RTI), which are the most available drugs in these countries. International guidelines recommend routine HIV resistance testing for the selection of an optimal antiretroviral therapy selec- tion. Genotypic resistance tests are used more than phenotypic tests, due to their lower costs and easier implementation. Several online algorithms have been developed by correlating genotypic patterns with clinical or phenotypic data. Recent reports have demonstrated their utility to predict virological response in the clinical settings (Rhee et al., 2009). Furthermore, they are inexpen- sive and widely used for detection and interpretation of resistance mutations using pol (protease, PR and reverse transcriptase, RT) sequences. Both genotypic drug-resistance interpretation algorithms and resistance prevalence studies have been mainly based on results derived from patients infected by subtype B. This is the most prevalent HIV-1 variant in industrialized countries where all antiretroviral drugs are available. However, the remaining HIV-1 variants (non-B subtypes and recombinants), traditionally ignored in the studies, are responsible for 90% of the 33 million infections worldwide (Hemelaar et al., 2006; UNAIDS, 2009). They are preva- lent in developing regions and are continuously increasing among new infections in Western countries, including Spain (Holguín et 0166-3542/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.antiviral.2009.11.010