Periodic surveillance of new HIV-1 infections in a geographical area allows tracking the spread of new variants and transmission of drug resistance mutations (DRMs) [1–3], helping to guide preventive strategies and therapeutic decisions. Between 10 and 17% of antiretroviral-naive HIV-1 infected individuals in Western countries harbour viruses with DRM to at least one antiretroviral drug [4–6]. In Spain, a steadily decline in DRM has been noticed in recent HIV-1 seroconverters, remaining stable around 13% since 2007 [1,7,8]. The rate and profile of DRM in new HIV-1 infections at a given time indirectly reflect the effectiveness of antiretroviral treatment rules at different moments . Their periodic assessment is relevant and influence recommendations on first-line antiretroviral regimens.
Although baseline CD4+ cell counts and plasma HIV-RNA have been established as the most important prognostic markers for HIV-1 disease progression and accordingly are used to guide therapeutic decisions [9,10], the determination of viral tropism could be relevant given its important role in HIV-1 pathogenesis . HIV-1 isolates are classified as R5-tropic, X4-tropic or as dual/mixed-tropic, depending on coreceptor use [12,13]. The differential usage of chemokine C-C motif receptor 5 (CCR5) and chemokine C-X-C motif receptor 4 by viral strains significantly influences the natural history of HIV-1 disease . R5 viruses are more common among drug-naive patients and at early stages of infection, whereas X4-tropic variants generally emerge later over the course of the infection [14,15]. International antiretroviral guidelines suggest that a tropism assay may potentially be used in clinical practice for prognostic purposes and viral tropism should be tested before prescribing CCR5 antagonists . However, information on viral tropism among recent HIV-1 seroconverters and its relationship with DRM and CD4 outcomes is scarce [11,17]. In this context, we examined the immunovirological correlates of X4 tropism in a large cohort of HIV-1 seroconverters established in Spain two decades ago.
Patients and methods
All individuals newly diagnosed with HIV-1 infection identified as recent seroconverters and seen between January 1997 and December 2012 at 17 different hospitals distributed across Spain were included in the study. Recent HIV-1 seroconverters were all naive for antiretroviral drugs at the time of sampling. Seroconversion was defined as follows: laboratory evidence of acute primary HIV-1 infection (detectable plasma HIV-RNA and negative or indeterminate HIV-1 antibody test result), or current seroreactive ELISA and western blot being a negative test performed within the prior 12 months [1,8]. The length of infection was considered as 1 month for acute primary HIV-1 infection and the difference between the negative and the positive test for the rest. Demographic data were recorded for each individual using a questionnaire as well as from hospital clinical charts in a case report especially designed by the Spanish Seroconverter Study Group.
Plasma HIV-RNA was measured by the third-generation bDNA assay (Versant v3.0; Bayer, Barcelona, Spain) until January 2009; since then, a commercial real-time PCR assay was used [Versant HIV-1 RNA 1.0 Assay (kPCR; Siemens Healtcare Diagnostics, Tarrytown, New York, USA]. CD4+ cell counts were determined by flow cytometry (Coulter, Madrid, Spain). The study was approved by the Ethics Committees of all participating centres, and an informed consent was signed from each patient. Moreover, all patient information was anonymously recorded following established procedures.
Drug resistance mutations
HIV-1 DRMs were analysed at the protease and reverse transcriptase genomic regions. Both pr and RT genes were sequenced using the TRUGENE HIV-1 Genotyping Assay (Siemens Healthcare Diagnostics, Tarrytown, New York, USA). For mutation analysis, we considered all changes recorded by Bennett et al.  for surveillance of transmitted HIV-1 DRMs.
V3 sequence analysis for viral tropism
Determination of HIV-1 tropism was retrospectively performed in all individuals with enough plasma volume stored at −80°C that allowed genetic characterization of the HIV-1 env gene. Genotypic amino acid V3 loop analyses have already been described elsewhere [8,19,20]. Briefly, a RT-PCR followed by a nested PCR were performed. PCR amplicons were purified using the High Pure PCR Product Purification kit (Roche, Mannheim, Germany) and directly sequenced on the ABI PRISM 3130 Genetic Analyzer using the ABI PRISM Rhodamine Terminator reaction kit (Applied Biosystems, Foster City, California, USA).
In order to predict HIV-1 tropism, the bioinformatic tool geno2pheno (http://coreceptor.geno2pheno.org/index.php) was used, using a false positive rate (FRP) level of 10%, which already has shown to accurately predict X4-coreceptor usage in specimens from antiretroviral-naive individuals using one single RT-PCR and bulk sequencing [20,21]. All samples inferred as harbouring X4 or X4 dual-mixed tropic viruses in this study were considered as X4 tropic strains for further purposes.
Phylogenetic analyses for HIV subtype determination were performed using the MEGA program (MEGA, Lasergene; DNASTAR Inc., Madison, Wisconsin, USA). Previously, pol (RT and protease) sequences obtained from plasma collected from recent seroconverters were aligned with HIV-1 group M reference sequences (http://www.hiv.lanl.gov/) using the CLUSTAL X method.
To simplify our analysis, we split out the 16 years of study in five different periods: 1997–2000, 2001–2003, 2004–2006, 2007–2009 and 2010–2012. Results are reported as percentages, mean and standard deviations or as median values and 25–75% interquartile ranges (IQRs), although rates of DRM and proportion of patients infected by X4 or R5 viruses were recorded as absolute numbers and percentages. For the comparison of quantitative variables over time, we used variance analyses, including the Tukey test with multiples comparisons. The Student's t-test was used to compare quantitative variables, whereas categorical parameters were compared using contingency tables based on chi-square test and Pearson correlation for more than two comparisons at different time frames. Linear regression models were used for univariate and multivariate analyses. Differences were considered as significant if P values were below 0.05. All reported P values were two-sided. All statistical analyses were performed using the SPSS software version 15.0 (SPSS Inc., Chicago, Illinois, USA).
Characteristics of the study population
A total of 1032 recent HIV-1 seroconverters were identified during the study period. Their median age was 31 years (IQR: 27–37). The median time of HIV-1 infection was 8 months (IQR: 4–12). Remarkably, 92.2% of them were men and 84% had acquired HIV-1 infection through homosexual contacts. Baseline characteristics of the study population are recorded in Table 1.
HIV-1 subtyping could be examined on 984 individuals (95.3%). Overall, 136 (13.8%) were infected with HIV-1 non-B subtypes (40 CRF02_AG, 27 CRF14_BG, 14 F, 11 CRF12_BF, 10 C, nine CRF01_AE, eight G, five A, five BD, three DF, three KB and one KF). Interestingly, the first non-B subtypes begun to be recognized by 2001, showing a very significant increase from 0 in the period 1997–2000 to 18.1% in 2010–2012 (P = 0.002). The rate of non-B subtypes did not differ significantly comparing native Spaniards and foreigners (13.1 vs. 15.7%, respectively).
Trends in drug resistance mutations
Major transmitted primary DRMs were recognized in 13.4% of recent HIV-1 seroconverters. By antiretroviral drug class, 7.7% were for nucleos(t)ide reverse transcriptase inhibitors (NRTIs), 5.8% for non-NRTI (NNRTI) and 2.9% for protease inhibitors. The rate of DRM has remained stable over the last 10 years. However, NRTI resistance mutations, and more specifically thymidine analogue mutations (TAMs), significantly declined from 23.7% in 1997–2000 to 6.9% in 2010–2012 (P = 0.006). By contrast, transmission of NNRTI and protease inhibitor resistance mutations remained stable around 6 and 3%, respectively (Fig. 1). The most common resistance mutations at the reverse transcriptase were at position 215, being revertant forms recognized in 38 individuals; K103N in 36, M41L in 21; D67N in 13, T69N in 12 and L210W in 12. At the protease region, the most frequent resistance mutations were L90M (n = 13), M46I/L (n = 11) and V82A (n = 6). Overall, the rate of DRM did not differ comparing B and non-B viruses (13.8 vs. 10.2%, P = 0.15, respectively).
Viral tropism and CD4+ cell count depletion
Results for HIV-1 tropism derived from V3 sequences obtained from plasma could be obtained for 737 individuals (71.4%). Overall, X4 viruses were found in 19.7% (n = 145) of HIV-1 seroconverters. The rate significantly increased from 11.5% before 2001 to 23.3% after 2009 (P = 0.043) (Fig. 2). There were no significant differences between R5 and X4 in demographics, immunological or virological characteristics (Table 2).
Interestingly, CD4+ cell counts were significantly lower in recent HIV-1 seroconverters (2010–2012) than in the oldest ones (1997–2000), being 553 vs. 691 cells/μl (P = 0.009) for absolute numbers, and 26 vs. 34% (P = 0.001) for percentages. Seroconverters infected with non-B subtypes tended to present with lower CD4+ cell counts than those infected with HIV-1 subtype B (552 vs. 602 cells/μl, P = 0.064). In univariate analysis, higher plasma HIV-RNA (beta coefficient = −0.326, P
< 0.001) and foreign origin (beta coefficient = −0.079, P
= 0.022) predicted lower CD4+ cell counts. However, in multivariate analysis, after adjustment for potential confounders, factors that remained independently associated with lower CD4+ cell counts were X4 tropism (beta coefficient = −0.081, P
= 0.045), higher plasma HIV-RNA (beta coefficient = −0.286, P
= < 0.001), HIV-1 non-B subtype (beta coefficient = −0.094, P
= 0.021) and foreign origin (beta coefficient = −0.099, P
Trends in DRM, subtypes and tropism over 16 years were examined in more than a thousand recent HIV-1 seroconverters in Spain. Overall, transmission of DRM was recognized in 13.4% of individuals, being 7.7% for NRTI, 5.8% for NNRTI and 2.9% for protease inhibitor. Our results are in agreement with reports from other studies conducted across Europe that have reported rates of DRM of 7.4% for NRTI, 3.4% for NNRTI and 2.9% for protease inhibitor . We noticed a significant decline in NRTI DRM over time, mainly driven by a marked reduction in the transmission of TAM. In a previous study, we hypothesized that the rate of DRM in recent HIV-1 seroconverters inversely correlates with the proportion of chronically infected individuals with undetectable plasma HIV-RNA in the same region. Moreover, the relative proportion of distinct DRM in seroconverters may indirectly reflect antiretroviral treatment modalities at different time points in a given region . Given that current recommended antiretroviral regimens are very successful and more than 80% of treated patients achieve and keep on undetectable plasma viremia , the major source of new infections with viruses harbouring DRM has became the subset of treated patients failing on therapy. As thymidine analogues are no longer recommended, viruses with TAM are nowadays rarely transmitted [23,24].
The overall prevalence of HIV-1 non-B subtypes in our cohort was 13.8%. Interestingly, non-B variants only began to spread after year 2000. New infections with non-B subtypes occurred in both Spaniards and foreigners (13.1 vs. 15.7%, respectively), suggesting that infection networks were not significantly influenced by ethnicity. Similar observations have been previously reported in other European cohorts [18,23,24], some of which have noticed influences of HIV-1 subtype on CD4 outcomes regardless of viral load set point .
There was a significant increase over time in the proportion of recent seroconverters with X4 tropic viruses in our cohort. It goes up from 11.5% before 2001 to 23.3% within the last 3 years. R5 tropic viruses seem to be preferentially transmitted by sexual relationships, as cells present in the genital mucosa express CCR5 coreceptors in their membrane. By contrast, X4-tropic viruses seem to be transmitted preferentially by direct contact with contaminated blood (i.e. following transfusion or sharing needless). In our cohort, more than 80% of patients had acquired HIV infection by homosexual relationships. Hypothetically, trauma during anal intercourses could have favoured transmission of X4 variants.
Recent cross-sectional studies have claimed that 40–55% of patients failing antiretroviral therapy might bear X4-tropic viruses . The presence of X4-tropic viruses is associated with low CD4+ cell counts regardless of treatment exposure and the emergence of X4-tropic viruses in patients with previously harbouring R5 viruses has been associated with more rapid CD4+ cell count decline and disease progression [11,12,14]. Although we did not find an overall significant difference between CD4+ cell counts when comparing patients with X4 vs. R5 viruses, the regression analysis identified X4 tropic viruses along with higher viral load and non-B subtypes as independent predictors of lower CD4+ cell counts. The recognition of X4 tropic strains at relatively high CD4+ cell counts has been reported previously . The main implication of this finding is that a tropic test should be performed at first HIV diagnosis independently of CD4+ cell counts, given the value of this information for natural history and potential treatment with CCR5 antagonists.
In order to explain why X4-tropic viruses might be on the rise among recent HIV-1 seroconverters, we should refresh our knowledge about the potential sources of new infections nowadays. On one hand are individuals unaware of their HIV status engaged in risk practices. From other surveys in Spain, we know that 30% of these chronically infected individuals are diagnosed for the first time with CD4+ cell counts lower than 200 cells/μl . The prevalence of X4-tropic viruses in this subset of patients is high and could reach 50% . In addition, from a public health point of view, people unaware of their infection are more likely to transmit HIV than those who know their HIV status . A second group of potential new HIV-1 infections is represented by patients already diagnosed with HIV-1 who are failing biologically antiretroviral therapy. Although this subset of patients may be less often engaged in risk practices that people unaware of their HIV infection, it must be considered as the major source of transmission of viruses with DRM. From other studies conducted in our country, we know that the current rate of DRM in patients failing current antiretroviral regimens is 11% for NRTI, 21% for NNRTI and 23% for protease inhibitor . These figures can easily be reconciled with the transmission rates we found in our recent HIV-1 seroconverters during the last period.
Our study has several limitations. Firstly, viral tropism was estimated using bioinformatics tools rather than phenotypic tests. However, several studies have shown that there is a good correlation between genotypic and phenotypic tools [30–32]. Secondly, geno2pheno was originally designed on subtype B and may underestimate X4 and dual-mixed tropic viruses in non-B subtypes. In our study, we did not find significant differences in the rate of X4-tropic viruses when comparing B and non-B subtypes, and therefore, this limitation should not have influenced or only marginally influenced our final results.
In summary, transmission of HIV-1 DRM in Spain seems to remain stable, despite a significant decline in NRTI DRM during the last decade. There is a higher proportion of new infections with X4-tropic viruses. It is intriguing that these individuals present with lower CD4+ cell counts suggesting that circulating HIV-1 strains might have gained virulence. Testing of viral tropism could be worthwhile in all new HIV-1 diagnosis, as they may have both pathogenic and therapeutic implications.
This work was supported in part by grants from Fundación Investigación y Educación en SIDA; Fondo de Investigación Sanitaria (FIS, PI06/01826 & PI10/0520; RIS, RD06/0006/0040 & RD12/0017/0031; CES12/003); FIPSE (GEMES Madrid); Ministerio de Ciencia e Innovación (MICINN, SAF2010/22232); NEAT (European AIDS Treatment Network; grant LSHM-CT-2006-037570); and CHAIN (Collaborative HIV and Anti-HIV Drug Resistance Network; European Community's Seventh Framework Programme; grant 22313).
C.dM. and V.S. designed the study; R.S-E. and M.L. performed the laboratory work; C.dM. and R.S-E. performed the data analysis; R.S-E., V.S. and C.dM. wrote the manuscript; and C.R., A.A., F.G., JM.E., E.C., J.dR. and V.S. provided samples, clinical data and critically reviewed the manuscript.
Members of the Spanish HIV Seroconverter Study Group:
Javier Colomina, Hospital de la Ribera, Valencia; Concepción Tuset, Hospital General, Valencia; Félix Gutiérrez and Mar Masiá, Hospital General, Elche & Universidad Miguel Hernández, Alicante; Federico Garcia, Hospital Universitario, Granada; Isabel Viciana, Hospital Virgen de la Victoria, Málaga; Julián Torre-Cisneros, Hospital Reina Sofía, Córdoba; José M. Eiros and Raúl Ortíz de Lejarazu, Hospital Clínico, Valladolid; Antonio Aguilera, Hospital Xeral, Santiago de Compostela; Pilar Leiva, Hospital Central de Asturias, Oviedo; Jesús Agüero and Ana Sáez, Hospital Marqués de Valdecilla, Santander; María Saumoy, Hospital Joan XXIII, Tarragona; Estrella Caballero and Esteve Ribera, Hospital Vall d’Hebrón, Barcelona; Lidia Ruiz, Fundació IrsiCaixa, Badalona; Rafael Benito, Hospital Lozano Blesa, Zaragoza; José Luis Gómez, Hospital Nuestra Señora de la Candelaria, Santa Cruz de Tenerife; Manolo Leal, Hospital Virgen del Rocío, Sevilla; Carmen Rodríguez and Jorge del Romero, Centro Sanitario Sandoval, Madrid; Carmen de Mendoza, Rocío Sierra-Enguita, Patricia Parra, Mariana Lapaz and Vincent Soriano, Hospital Carlos III, Madrid.
Conflicts of interest
None for all authors. All have submitted their disclosures of potential conflicts of interest.
1. De Mendoza C, Rodriguez C, Eiros JM, Colomina J, Garcia F, Leiva P, et al. Antiretroviral recommendations may influence the rate of transmission of drug-resistant HIV type 1
. Clin Infect Dis
2. Shet A, Berry L, Mohri H, Mehandru S, Chung C, Kim A, et al. Tracking the prevalence of transmitted antiretroviral drug-resistant HIV-1: a decade of experience
. J Acquir Immune Defic Syndr
4. Frentz D, Boucher C, van de Vijver D. Temporal changes in the epidemiology of transmission of drug-resistant HIV-1 across the world
. AIDS Rev
5. Wittkop L, Günthard H, de Wolf F, Dunn D, Cozzi-Lepri A, de Luca A, et al. Effect of transmitted drug resistance on virological and immunological response to initial combination antiretroviral therapy for HIV (EuroCoord-CHAIN joint project): a European multicohort study
. Lancet Infect Dis
6. Recordon-Pinson P, Anies G, Bruyand M, Neau D, Morlat P, Pellegrin J-L, et al. HIV type 1 transmission dynamics in recent seroconverters: relationship with transmission of drug resistance and viral diversity
. Antivir Ther
7. De Mendoza C, del Romero J, Rodríguez C, Corral A, Soriano V. Decline in the rate of genotypic resistance to antiretroviral drugs in recent HIV seroconverters in Madrid
8. De Mendoza C, Rodriguez C, Garcia F, Eiros JM, Ruiz L, Caballero E, et al. Prevalence of X4 tropic viruses in patients recently infected with HIV-1 and lack of association with transmission of drug resistance
. J Antimicrob Chemother
9. Sterling T, Vlahov D, Astemborski J, Hoover D, Margolick J, Quinn T. Initial plasma HIV-1 RNA levels and progression to AIDS in women and men
. N Engl J Med
10. O’Brien W, Hartigan P, Martin D, Esinhart J, Hill A, Benoit S, et al. Changes in plasma HIV-1 RNA and CD4+ lymphocyte counts and the risk of progression to AIDS. Veterans Affairs Cooperative Study Group on AIDS
. N Engl J Med
11. Brumme Z, Goodrich J, Mayer H, Brumme C, Henrick B, Wynhoven B, et al. Molecular and clinical epidemiology of CXCR4-using HIV-1 in a large population of antiretroviral-naive individuals
. J Infect Dis
12. Verhofstede C, Nijhuis M, Vandekerckhove L. Correlation of coreceptor usage and disease progression
. Curr Opin HIV AIDS
13. Berger E, Doms R, Fenyö E, Korber B, Littman D, Moore J, et al. A new classification for HIV-1
14. Waters L, Mandalia S, Randell P, Wildfire A, Gazzard B, Moyle G. The impact of HIV tropism on decreases in CD4 cell count, clinical progression, and subsequent response to a first antiretroviral therapy regimen
. Clin Infect Dis
15. Goetz M, Leduc R, Kostman J, Labriola A, Lie Y, Weidler J, et al. Relationship between HIV coreceptor tropism and disease progression in persons with untreated chronic HIV infection
. J Acquir Immune Defic Syndr
16. Department of Health and Human Services. Guidelines for the use of antiretroviral agents in HIV-1
-infected adults and adolescents. AIDSinfo. http://aidsinfo.nih.gov/guidelines/
[Accessed 14 February 2014].
17. Poveda E, Briz V, de Mendoza C, Benito JM, Corral A, Zahonero N, et al. Prevalence of X4 tropic HIV-1 variants in patients with differences in disease stage and exposure to antiretroviral therapy
. J Med Virol
18. Bennett D, Camacho R, Otelea D, Kuritzkes D, Fleury H, Kiuchi M, et al. Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update
. PLoS One
19. Poveda E, Seclén E, González Mdel M, García F, Chueca N, Aguilera A, et al. Design and validation of new genotypic tools for easy and reliable estimation of HIV tropism before using CCR5 antagonists
. J Antimicrob Chemother
20. Poveda E, Paredes R, Moreno S, Alcamí J, Córdoba J, Delgado R, et al. Update on clinical and methodological recommendations for genotypic determination of HIV tropism to guide the usage of CCR5 antagonists
. AIDS Rev
21. Poveda E, Briz V, Quiñones-Mateu M, Soriano V. HIV tropism: diagnostic tools and implications for disease progression and treatment with entry inhibitors
22. Cescon A, Kanters S, Brumme CJ, Lepik KJ, Forrest JI, Hull M, et al. Trends in plasma HIV-RNA suppression and antiretroviral resistance in British Columbia, 1997–2010
. J Acquir Immune Defic Syndr
23. Abecasis A, Wensing AM, Paraskevis D, Vercauteren J, Theys K, Van de Vijver D, et al. HIV-1 subtype distribution and its demographic determinants in newly diagnosed patients in Europe suggest highly compartmentalized epidemics
24. Hemelaar J, Gouws E, Ghys P, Osmanov S. Global trends in molecular epidemiology of HIV-1 during 2000–2007
25. Touloumi G, Pantazis N, Pillay D, Paraskevis D, Chaix M-L, Boucher C, et al. Impact of HIV-1 subtype on CD4 count at HIV seroconversion, rate of decline, and viral load set point in European seroconverter cohorts
. Clin Infect Dis
26. Saracino A, Monno L, Scudeller L, Bruno G, Ladisa N, Punzi G, et al. X4 viruses are frequently archived in patients with long-term HIV infection but do not seem to influence the ‘inflamm-aging’ process
. BMC Infect Dis
27. Shepherd J, Jacobson L, Qiao W, Jamieson B, Phair J, Piazza P, et al. Emergence and persistence of CXCR4 tropic HIV-1 in a population of men from the multicenter AIDS cohort study
. J Infect Dis
28. Sobrino-Vegas P, García-San Miguel L, Caro-Murillo AM, Miró JM, Viciana P, Tural C, et al. Delayed diagnosis of HIV infection in a multicenter cohort: prevalence, risk factors, response to HAART and impact on mortality
. Curr HIV Res
29. De Mendoza C, Anta L, Barreiro P, Zahonero N, Lapaz M, Poveda E, et al. Trends in antiretroviral therapy use and drug resistance profiles by calendar in Spain
. Antivir Ther
2012; 17 (Suppl 1):1–175.
30. McGovern R, Thielen A, Portsmouth S, Mo T, Dong W, Woods C, et al. Population-based sequencing of the V3-loop can predict the virological response to maraviroc in treatment-naive patients of the MERIT trial
. J Acquir Immune Defic Syndr
31. Knapp D, McGovern R, Dong W, Poon A, Swenson L, Zhong X, et al. Factors influencing the sensitivity and specificity of conventional sequencing in HIV type 1 tropism testing
. J Clin Microbiol
32. Kagan R, Johnson E, Siaw M, Biswas P, Chapman D, Su Z, et al. A genotypic test for HIV-1 tropism combining Sanger and ultradeep sequencing predicts virological response in treatment-experienced patients
. PLoS One
Keywords:© 2014 Lippincott Williams & Wilkins, Inc.
chemokine C-X-C motif receptor 4; drug resistance; HIV-1; non-B subtypes; seroconverters; tropism