Human immunodeficiency virus type 1 (HIV-1) infection is characterized by a progressive decrease in CD4+ T-cell count and immune dysfunction. The clinical benefits obtained by combined antiretroviral therapy (cART) are strongly correlated with CD4+ T-cell recovery.1,2 However, successful cART and effective control of HIV-1 replication do not always correlate with CD4+ T-cell count recovery.3–7 This inadequate immunological recovery increases AIDS and non–AIDS-related morbidity and mortality.1–3,7,8
One of the reasons that could limit CD4+ T-cell recovery could be a dysfunctional immune system characterized by cells with shorter telomeres, an index of cellular aging.9 Telomeres are DNA–protein complexes that protect chromosome ends to ensure chromosomal stability and regulation of the cellular replicative lifespan.10 With cell replication, telomeres shorten progressively, and ultimately result in apoptosis or permanent cell-cycle arrest. Historically, telomere shortening has been considered a hallmark of the classical form of replicative senescence. In addition to age, telomere length (TL) could also be shortened by chronic infections and stress, leading to immunosenescence in the elderly.11 Telomerase is a reverse transcriptase that restores TL during cell division.10,12 HIV-infected patients have a dysregulated telomerase activity.13–15 In previous studies, shortened TL and impaired telomerase activity were reported in patients with advanced HIV-1 infection,16–18 whereas normal telomerase activity levels were found in patients in an early stage of the disease.15,17 Moreover, telomerase activity could be also compromised by HIV-1 treatment because this enzyme shares homology with one of the main cART targets, the nucleoside reverse transcriptase.19 In fact, nucleoside reverse transcriptase inhibitors (NRTI) have been shown to inhibit telomerase activity both in vitro and ex vivo20–22 and to shorten TL.22–24
Oxidative reactions are also important factors underlying the aging process.25,26 Further, age-related changes of immune functions have as their basis an oxidative and inflammatory stress situation, and a causal relationship between higher oxidative stress (OS) and lower telomerase activity has also been described.27,28 In addition, increased OS may influence many aspects of HIV pathogenesis including viral replication, inflammatory response, decreased immune-cell proliferation, and loss of immune function.29
Finally, nitric oxide is a free radical with a controversial role in aging, although a reduced nitric oxide production by endothelial nitric oxide synthase activity concomitant with an increased inducible nitric oxide synthase activity has been described in senescent cells.30,31 In HIV-1–infected individuals, a lower CD4+ T-cell count and higher viral load (VL) are associated with low endothelial nitric oxide production and endothelial dysfunction, corroborating the importance of nitric oxide in HIV-1–associated cardiovascular disease.32
The purpose of this study was to evaluate the potential relationship between TL and immunological response at 48 weeks of cART initiation, and to assess the role of nitrosative stress and OS in HIV-1 immunorecovery after cART.
CoRIS is an open, prospective, multicenter cohort of HIV-1–positive subjects, which has been described elsewhere in detail33 and that is linked to a BioBank.34 Approval has been obtained from all Hospital Ethics' Committees, and all patients have signed informed consent forms.33
The study population for this analysis included antiretroviral-naive patients who started their first cART regimen between January 1, 2004, and October 31, 2010 (administrative censoring date). We selected those patients with an undetectable VL (<50 copies HIV-1-RNA/mL) after 48 (±6) weeks of their first cART and who had a serum sample available at 48 (±12) weeks.
Samples from patients were kindly provided by the HIV BioBank integrated in the Spanish AIDS Research Network (RIS).34 The HIV HGM BioBank possesses the certification of quality under Regulation UNE-EN-ISO 9001:2008 Systems of Quality Management Requirements. The UNE-EN-ISO 9001:2008 is a regulation for implementing the Systems of Quality Management that has permitted the standardization and documentation of all the procedures and tasks carried out in the HIV HGM BioBank. Therefore, the HIV HGM BioBank guarantees that it owns the technical infrastructure to deliver biological samples of the maximum quality and fulfill all the requirements of this article.
Leukocyte TL was measured using a quantitative polymerase chain reaction (PCR) technique developed by Cawthon.35 This technique compares signals from the telomere repeat copy number (T) with that of a single-copy gene 36B4 copy number (S), and allows calculation of a relative T/S ratio. Briefly, genomic DNA was extracted directly from white blood cells (1.0 × 106 cells per patient) by standard procedures, and the PCR reactions were performed in a 25-μL volume containing 12.5 μL of SYBR Green PCR Master Mix (Applied Biosystems; Foster City, CA), 2 μL of diluted DNA, and specific primers. The sequences (written 5′–3′) and final concentrations of the telomere primers were Tel1 GGTTTTTGAGGGTGAGGGTGAGGGTGAGGGTGAGGGT, 270 nM; Tel2 TCCCGACTATCCCTATCCCTATCCCTATCCCTATCCCTA, 900 nM. The control-gene primers were 36B4u CAGCAAGTGGGAAGGTGTAATCC, 300 nM; 36B4d CCCATTCTATCATCAACGGGTACAA, 500 nM.
The telomere PCR reaction was subjected to 40 cycles of 95°C for 15 seconds, and 54°C for 2 minutes. For 36B4, the PCR mix was exposed to 40 cycles of 95°C for 15 seconds, and 58°C for 1 minute in a 7300 Real Time PCR thermocycler (Applied Biosystems). TL and the presence of 36B4 were calculated using absolute quantification by interpolation into a standard curve.36 All telomere values were divided by the expression of the single-copy gene, 36B4.
Determination of Plasma Nitrosative Stress Level
Nitric oxide production was indirectly quantified by determining nitrate/nitrite and S-nitroso compounds (NOx), using an ozone chemiluminescence-based assay adapted to plasma samples.37,38 This method has a sensitivity of 1 pmole and a repeatability of ±5% and is superior to other methods because many samples can be analyzed sequentially without the necessity of sample prereduction. In brief, plasma samples were deproteinized with 0.8 N NaOH and 16% ZnSO4 solutions (1/0.5/0.5). After centrifugation at 10,000g for 5 minutes, the resulting supernatants were removed for chemiluminescence analysis39 in an NO analyzer (NOA 280i; Sievers Instrumments, Boulder, CO). NOx concentration was calculated by comparison with standard solutions of sodium nitrate. Final NOx values were expressed micromolar (μM).
Determination of Plasma OS Level
Lipid peroxidation was measured by the thiobarbituric acid reactive substances (TBARS) method. TBARS is a major indicator of OS and was determined using an adaptation of the method described by Buege and Aust.40 This method, widely used in the literature, has a limit of detection of 1 µM and a repeatability of ±5%. Specifically, 8% sodium dodecyl sulfate was added (1:1) to each plasma sample. Samples were vortexed and mixed (1:6) with a reagent containing 15% trichloroacetic acid, 0.38% thiobarbituric acid, and 2% HCl and then heated for 30 minutes at 96°C, cooled, and centrifuged (3000g for 5 minutes). The supernatants were collected, and the absorbance was measured at 532 nm. The concentration of TBARS was determined by extrapolation from the malondialdehyde standard curve. Results were expressed micromolar (μM).
Linear regression models were used to assess the relationship between TL and CD4+ T-cell count increase at 48 weeks after cART initiation. After checking the linear model's assumption, a linear relationship between TL and CD4+ T-cell count increase (ie, a constant change in CD4+ T-cell count increase per unit increase in TL) could not be assumed, so TL was categorized into tertiles [<0.13 for the lowest tertile (short), 0.13–0.27 for the middle tertile (medium), and >0.27 for the highest tertile (long)], due to the absence of standardized cutoffs, to satisfy the model's assumptions.
We calculated the mean increases (95%) in CD4+ T-cell counts at week 48 from cART initiation for patients with long, medium, and short TLs and the estimated mean differences [95% confidence interval (CI)] in CD4+ T-cell count mean increases, comparing medium and short lengths versus long TL.
To highlight the clinical relevance of our findings, we also calculated the proportion of patients increasing at least 100 cells per milliliter at 48 weeks from cART initiation41 and used logistic regression models to estimate odds ratios (ORs) (95% CI) for association between tertiles of TL and the odds of increasing at least 100 cells per milliliter.
Multivariate models were initially adjusted for factors potentially associated with immunological response: sex (male, female) and age (<50, ≥50 years), CD4+ T-cell count (<200, 200–350, >350 cells/mL), VL (≤100,000, >100,000 copies/mL), and hepatitis C virus (HCV) infection at the start of cART. Second, to assess the role of nitrosative stress and OS in HIV-1 immunorecovery after cART, NOx and TBARS were included in multivariate models. As for TL, NOx and TBARS were categorized into tertiles to be included into multivariate models due to the absence of a linear relationship with CD4+ T-cell count increase at 48 weeks after cART. We assessed whether the association between TL and immunological response was different according to the age of patients at cART initiation by including interaction terms between TL and age into multivariate models. To adjust for clustering of patients within centers, robust methods were used to estimate standard errors and, thus, to calculate 95% CIs and P values. Wald tests were used to derive P values. All statistical analyses were performed by using Stata software (version 11.0; College Station, TX).
The CoRIS database, updated on October 31, 2010, included data from 6811 antiretroviral-naive patients. Of these, 6679 were excluded from the analyses as follows: 2330 who never initiated cART, 2885 who did not achieve an undetectable VL after 48 (±6) weeks of their first cART, 216 as a CD4+ T-cell count measurement within 6 months previously at cART initiation was not available, 23 who did not have a CD4+ T-cell count measurement at 48 (±6) weeks from the initiation of cART and 1216 as no serum sample at 48 (±12) weeks from cART was available. We further excluded 9 patients who did not have information on TL. A total of 132 patients were included in the analyses, 86% male and 81% aged <50 years at cART initiation. Median [interquartile range (IQR)] TL was 0.19 (0.09–0.33), and median (IQR) NOx and TBARS were 15 (10.5–20.6) µM and 25.4 (19.0–30.7) µM, respectively. There were no significant differences in sociodemographic and clinical characteristics of the patients according to tertiles of TL (Table 1).
Increases in CD4+ T-cell counts at 48 weeks from cART initiation were greater in patients with long TL than in those with medium and short TLs (P = 0.007) with mean (95% CI) increases of 266 (236 to 297) cells per milliliter versus 189 (144 to 235) and 189 (114 to 265), respectively. After adjustment for sex, age, CD4+ T-cell counts, VL, and HCV infection at cART initiation in a multivariate linear regression model, differences in mean CD4+ T-cell count increases remained statistically significant (P = 0.02): patients with medium and short TLs increased 73.9 (95% CI: 17.5 to 130.4) and 84.2 (95% CI: 5.3 to 163.2) cells per milliliter less, respectively, than those with long TL (Table 2). Additional adjustment for NOx and TBARS did not change the results in patients with medium and short TLs showing an increase of 73.4 (95% CI: 19.8 to 127.0) and 90.8 (95% CI: 21.0 to 160.5) cells per milliliter less than those with long TL (data not shown).
An association between NOx and CD4+ T-cell count increase at 48 weeks after cART was found (P = 0.04) with patients with lower NOx (<12.1 µM) showing an increase of 50.6 (95% CI: 12.5 to 88.6) cells per milliliter more than those with higher NOx (>18.9). However, we failed to find an association between tertiles of TBARS and CD4+ T-cell count increase (P = 0.29) (data not shown).
When analyzing the association between TL and the increase of at least 100 cells per milliliter at 48 weeks from cART, a similar pattern was observed [ORs (95% CI) for medium and short TLs compared with long TL were 0.46 (0.10 to 2.17) and 0.51 (0.09 to 2.73)], although differences did not reach statistical significance (P = 0.60). We found an interaction between TL and age at cART initiation (P < 0.001): there was a suggestion of a higher impact of TL on the odds of increasing at least 100 cells per milliliter in patients aged ≥50 years [ORs (95% CI) for medium and short TLs compared with long TL were 0.53 (0.05 to 5.04) and 0.08 (0.02 to 0.39)] than in those aged <50 years (Fig. 1). Similar results were obtained after additional adjustment for NOx and TBARS (data not shown).
In this study, we have observed a significant direct association between TL and immunological recovery after adjusting for other variables in a population of HIV-1–infected patients with suppressed viremia under cART. Moreover, the association was stronger in patients aged >50 years. Notably, this effect was not related to nitrosative stress or OS level.
Telomere shortening is also emerging as an important issue in HIV infection. This could be because HIV infection, by itself, shortens TL and mimics a state of immunosenescence.42–44 So, Bestilny et al42 observed that there was a clear (P < 0.0001) inverse relationship between TL and progression of immunosuppression, with HIV infection resulting in a ≥5-fold acceleration of aging of the circulating peripheral blood mononuclear cell component of the immune system. Tendeiro et al18 showed that HIV-2–infected patients in an advanced disease stage (<300 CD4+ T-cell) featured the lowest naive CD4+ T-cell TL. According to these authors, all but one of these patients (n = 8) was on long-term cART, with poor immunological recovery despite their undetectable viremia. Meanwhile, Pathai et al44 observed in HIV-1–infected patients from sub-Saharan Africa that TL was shorter in HIV-infected patients than in HIV-seronegative people, and that TL decreases with the chronological age of HIV-infected individuals. However, these authors also observed that HIV-infected patients aged >50 years (n = 40) had a significantly shorter TL than did HIV-seronegative individuals in the same age group. An interesting finding of this article was the fact that in those patients on cART with a viral suppression (<50 copies/mL), the current number of CD4+ T-cells was positively correlated with TL. However, unlike in our study, the majority of this population were females (75%), who have longer telomeres than males,45 and their median age was lower (39 years). More recently, Zanet et al46 reported in HIV-infected patients that the predictors of shorter TL were older age, smoking status, HIV infection, and active HCV infection. However, among HIV-infected patients on cART having an undetectable VL (<40 copies/mL), the results were similar to those for all HIV-infected individuals except for the active HCV infection. The other interesting results of this study were that neither time since HIV nor the current or nadir CD4 was related to the TL, and that there was no relationship between TL and cART exposure, including among others cART duration or current type of cART. However, unlike in our study, the majority of this population was female (76%), nonwhite race (58%), and at least 80% of the patients on cART with undetectable VL had received ≥2 different cART regimens. Perhaps all of these conditions could explain the differences in the results found in our study.
In our study, it came to our attention that the group of patients under 50 years experienced an adequate immunorecovery, defined as increasing 100 cells per milliliter at 48 weeks after cART initiation, regardless of the length of their telomeres. However, a shorter TL was associated with lower chances of experiencing an adequate immunorecovery in patients >50 years. In this sense, it is important to note that telomere shortening in aging subjects has been reported, among others, in human peripheral blood leukocytes and in T-cells,47,48 and although its significance is unclear, it could be related to the diminished immunity that occurs in older age.
Increased OS contributes to accelerate telomere shortening.27,28,49,50 HIV-infected patients are under chronic OS.51 Indeed, the HIV virus itself, and its envelope glycoprotein (gp120) and transregulatory protein (Tat), has been implicated in the production of reactive oxygen species.52,53 Indeed, Borges-Santos et al54 reported that HIV-infected patients had an antioxidant deficiency that could contribute to HIV progression. Moreover, it has been shown that levels of C-reactive protein are inversely correlated with TL in leukocytes of premenopausal women.55 Consequently, we evaluated OS as a potential cause for the telomere shortening. The reason could be that OS accelerates telomere erosion during somatic cell replication, and inflammation increases leukocyte turnover rate, thus creating a vicious circle.50 In previous studies performed in asymptomatic HIV-1–infected patients, the mean value plasma TBARS was clearly higher than that in seronegative donors, but a correlation between TBARS and CD4+ T-cell count could not be shown.56 In the same way, Ngondi et al57 observed that TBARS levels were significantly elevated in HIV-infected patients on treatment compared with those not following therapy or non–HIV-infected controls. This could be because cART may induce an increase in oxidant generation, a decrease in antioxidant protection, or a failure to repair oxidative damage.57 In this article, multiple linear regression analysis confirmed that body mass index, sex, age, CD4+ T-cell load, and HIV VL did not have a significant impact on TBARS levels. Meanwhile, Mandas et al58 observed that patients with optimal cART adherence had a significantly higher oxidative status than those who had a poor cART adherence. The oxidative status in females was higher than in males. However, CD4+ T-cell count and HIV/HCV coinfection did not seem to correlate with oxidative status.
However, in previous studies, serum nitrate levels were positively correlated with the amount of HIV-DNA in peripheral blood mononuclear cells and plasma HIV-1-RNA levels but not with the number of CD4+ T-cells.52 In this sense, cART interruption may induce a pro-OS/nitrosative stress.59 However, the relationship between cART and OS is controversial. Thus, although some studies showed that cART had a protective effect against OS,59–61 others found a prooxidative state associated with cART.59,62,63 The differences may be due to the specific antiretroviral regimen used but, again, the results are inconclusive.59,60,62
Our study could have some limitations that need to be considered. First, this is not a randomized clinical trial. Second, we had not matched baseline samples before starting the cART that would let us analyze changes in TL or OS and nitrosative stress levels induced by the treatment. Third, the number of patients analyzed. Although the number of patients could be considered limited, our patients were well characterized and identified according to strict selective criteria. Fourth, although it would have been interesting to have other biomarkers of aging inflammation, or immunoactivation, these parameters were not available in this study. However, previous studies performed in HIV-infected patients showed that TL and CDKN2A expression, a mediator of cellular senescence, were both consistent with increased biological aging in these patients,44 and that there was no association between current C-reactive protein and the TL.46 This is really important because although telomere shortening has been linked to the aging process, it is not well known whether shorter telomeres are just a sign of aging or something that contribute to aging. Fifth, we were not able to evaluate the role of other confounding factors linked to an increase in OS or nitrosative stress levels such as smoking status.64,65 However, in the case of the TL, this risk factor is controversial. So, some authors have observed in >4500 Danish individuals from the general population that changes in leukocyte TL during 10 years was associated inversely with baseline TL and age at baseline, but not with baseline or 10-year interobservational tobacco consumption, body weight, physical activity, or alcohol intake.66 The same applies to the study of Zanet et al.46 Unlike the above, Huzen et al67 observed in >8000 Netherland participants from the Prevention of Renal and Vascular End-stage Disease study that smoking and variables linked to the metabolic syndrome were modifiable lifestyle factors that accelerate telomere attrition. Finally, we did not collect information on some variables, including comorbidities, or non–HIV-related medications that could impact the results. So, the effect of these potential confounders could not be determined.
In conclusion, short TLs in HIV-1–infected patients predict a lower immunological response despite a successful virological response and NOx and TBARS do not explain this association. Thus, TL could be a useful marker of immunological response in HIV-1–infected patients. Given our results, it is reasonable to evaluate the impact that early HIV-1 treatment or the use of free NRTI therapies could have on TL and immune recovery and its relation with other immunosenescence markers. Further studies will be necessary to corroborate the potential usefulness of the TL as an immunological recovery biomarker.
The authors particularly acknowledge the patients in this study for their participation and the HIV Biobank integrated in the RIS and collaborating centers for the generous gifts of clinical samples used in this work. This study would not have been possible without the collaboration of all the patients, medical and nursery staff, and data managers who have taken part in the project (Appendix 1). The authors wish to thank Esther Martinez-Lara for her excellent laboratory support.
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Annex: Centers and Investigators Participating in CoRIS
Coordinating committee: Juan Berenguer, Julia del Amo, Federico García, Félix Gutiérrez, Pablo Labarga, Santiago Moreno, and María Ángeles Muñoz.
Field work, data Management, and analysis: Paz Sobrino Vegas, Victoria Hernando Sebastián, Belén Alejos Ferreras, Débora Álvarez, Susana Monge, Inmaculada Jarrín, and Adela Castelló.
BioBanco: M Ángeles Muñoz-Fernández, Isabel García-Merino, Coral Gómez Rico, Jorge Gallego de la Fuente, and Almudena García Torre.
Hospital General Universitario de Alicante (Alicante): Joaquín Portilla Sogorb, Esperanza Merino de Lucas, Sergio Reus Bañuls, Vicente Boix Martínez, Livia Giner Oncina, Carmen Gadea Pastor, Irene Portilla Tamarit, and Patricia Arcaina Toledo.
Hospital Universitario de Canarias (Santa Cruz de Tenerife): Juan Luis Gómez Sirvent, Patricia Rodríguez Fortúnez, María Remedios Alemán Valls, María del Mar Alonso Socas, Ana María López Lirola, María Inmaculada Hernández Hernández, and Felicitas Díaz-Flores.
Hospital Carlos III (Madrid): Vicente Soriano, Pablo Labarga, Pablo Barreiro, Pablo Rivas, Francisco Blanco, Luz Martín Carbonero, Eugenia Vispo, and Carmen Solera.
Hospital Universitario Central de Asturias (Oviedo): Victor Asensi, Eulalia Valle, and José Antonio Cartón.
Hospital Clinic (Barcelona): José M. Miró, María López-Dieguez, Christian Manzardo, Laura Zamora, Iñaki Pérez, Mª Teresa García, Carmen Ligero, José Luis Blanco, Felipe García-Alcaide, Esteban Martínez, Josep Mallolas, and José M. Gatell.
Hospital Doce de Octubre (Madrid): Rafael Rubio, Federico Pulido, Silvana Fiorante, Jara Llenas, Violeta Rodríguez, and Mariano Matarranz.
Hospital Donostia (San Sebastián): José Antonio Iribarren, Julio Arrizabalaga, María José Aramburu, Xabier Camino, Francisco Rodríguez-Arrondo, Miguel Ángel von Wichmann, Lidia Pascual Tomé, Miguel Ángel Goenaga, Mª Jesús Bustinduy, and Harkaitz Azkune Galparsoro.
Hospital General Universitario de Elche (Elche): Félix Gutiérrez, Mar Masiá, José Manuel Ramos, Sergio Padilla, Andrés Navarro, Fernando Montolio, Yolanda Peral, and Catalina Robledano García.
Hospital Germans Trías i Pujol (Badalona): Bonaventura Clotet, Cristina Tural, Lidia Ruiz, Cristina Miranda, Roberto Muga, Jordi Tor, and Arantza Sanvisens.
Hospital General Universitario Gregorio Marañón (Madrid): Juan Berenguer, Juan Carlos López Bernaldo de Quirós, Pilar Miralles, Jaime Cosín Ochaíta, Isabel Gutiérrez Cuellar, Margarita Ramírez Schacke, Belén Padilla Ortega, Paloma Gijón Vidaurreta, Ana Carrero Gras, Teresa Aldamiz-Echevarría Lois, and Francisco Tejerina Picado.
Hospital Universitari de Tarragona Joan XXIII, IISPV, Universitat Rovira i Virgili (Tarragona): Francesc Vidal, Joaquín Peraire, Consuelo Viladés, Sergio Veloso, Montserrat Vargas, Miguel López-Dupla, Montserrat Olona, Alba Aguilar, Verónica Alba, Olga Calavia, and Raúl Beltrán-Debón.
Hospital Universitario La Fe (Valencia): José López Aldeguer, Marino Blanes Juliá, José Lacruz Rodrigo, Miguel Salavert, Marta Montero, Eva Calabuig, and Sandra Cuéllar.
Hospital Universitario La Paz (Madrid): Juan González García, Ignacio Bernardino de la Serna, José María Peña Sánchez de Rivera, José Ramón Arribas López, María Luisa Montes Ramírez, José Francisco Pascual Pareja, Blanca Arribas, Juan Miguel Castro, Fco Javier Zamora Vargas, Ignacio Pérez Valero, Miriam Estebanez, Raphael Mohr, and Francisco Arnalich Fernández.
Hospital de la Princesa (Madrid): Ignacio de los Santos, Jesús Sanz Sanz, Johana Rodríguez, Ana Salas Aparicio, and Cristina Sarriá Cepeda.
Hospital San Pedro-CIBIR (Logroño): José Antonio Oteo, José Ramón Blanco, Valvanera Ibarra, Luis Metola, Mercedes Sanz, and Laura Pérez-Martínez.
Hospital San Pedro II (Logroño): Javier Pinilla Moraza.
Hospital de Navarra (Pamplona): Julio Sola Boneta, Javier Uriz, Jesús Castiello, Jesús Reparaz, María Jesús Arraiza, Carmen Irigoyen, and David Mozas.
Hospital Ramón y Cajal (Madrid): Santiago Moreno, José Luis Casado, Fernando Dronda, Ana Moreno, María Jesús Pérez Elías, Dolores López, Carolina Gutiérrez, Beatriz Hernández, María Pumares, and Paloma Martí.
Hospital Reina Sofía (Murcia): Alfredo Cano Sánchez, Enrique Bernal Morell, and Ángeles Muñoz Pérez.
Hospital San Cecilio (Granada): Federico García García, José Hernández Quero, Alejandro Peña Monje, Leopoldo Muñoz Medina, and Jorge Parra Ruiz.
Centro Sanitario Sandoval (Madrid): Jorge Del Romero Guerrero, Carmen Rodríguez Martín, Teresa Puerta López, Juan Carlos Carrió Montiel, Cristina González, and Mar Vera.
Hospital Universitario Santiago de Compostela (Santiago de Compostela): Antonio Antela, Arturo Prieto, and Elena Losada.
Hospital Son Espases (Palma de Mallorca): Melchor Riera, Javier Murillas, Maria Peñaranda, Maria Leyes, Mª Angels Ribas, Antoni Campins, Concepcion Villalonga, and Carmen Vidal.
Hospital Universitario de Valme (Sevilla): Juan Antonio Pineda, Eva Recio Sánchez, Fernando Lozano de León, Juan Macías, José del Valle, Jesús Gómez-Mateos, and Rosario Mata.
Hospital Virgen de la Victoria (Málaga): Jesús Santos González, Manuel Márquez Solero, Isabel Viciana Ramos, and Rosario Palacios Muñoz.
Hospital Universitario Virgen del Rocío (Sevilla): Pompeyo Viciana, Manuel Leal, Luis Fernando López-Cortés, and Mónica Trastoy.