Non-nucleoside reverse transcriptase inhibitor-based combination antiretroviral therapy is associated with lower cell-associated HIV RNA and DNA levels compared to protease inhibitor-based therapy

In individuals who are able to adhere to combination antiretroviral therapy (ART), therapy suppresses human immunodeficiency virus (HIV) replication, restores immune function, and prevents the development of acquired immunodeficiency syndrome (AIDS) (Deeks et al., 2013). More than 20 different antiretroviral drugs belonging to six main classes are currently approved for clinical use (Pau and George, 2014). Depending on the class, these drugs block different steps of the HIV replication cycle, such as reverse transcription, proviral integration, or virus particle maturation. Current ART regimens typically consist of two nucleotide or nucleoside reverse transcriptase inhibitors (NRTIs) and a third drug of another class, for example, a non-nucleoside reverse transcriptase inhibitor (NNRTI), a protease inhibitor (PI), or an integrase strand transfer inhibitor (INSTI).

Despite the efficient suppression of HIV replication, ART is not curative and has to be sustained lifelong. Persistence of viral reservoirs forms the major obstacle to an HIV cure (Deeks et al., 2016). Viral reservoir markers, such as low-level HIV RNA in plasma (residual viremia) and cell-associated (CA) HIV DNA and RNA, can be measured in most treated individuals with plasma HIV RNA suppressed to below the limit of quantification of commercial assays (Jacobs et al., 2019; Pasternak and Berkhout, 2018; Pasternak et al., 2013; Avettand-Fènoël et al., 2016; Sharaf and Li, 2017). Although HIV latent reservoirs persist primarily by cell longevity and proliferation (Chomont et al., 2009; Maldarelli et al., 2014; Wagner et al., 2014), replenishment of the reservoirs by residual virus replication despite ART has been proposed as an alternative mechanism of HIV persistence (Chun et al., 2005; Lorenzo-Redondo et al., 2016; Sigal et al., 2011). The latter possibility remains a matter of longstanding debate in HIV research field (Martinez-Picado and Deeks, 2016). Residual HIV replication can result from insufficient penetration of antiretroviral drugs into tissues and anatomic sanctuaries, causing reduced local drug concentrations in tissue sites (Estes et al., 2017; Fletcher et al., 2014). However, most (but not all) studies could not demonstrate any measurable virus evolution in peripheral blood and tissues of ART-treated individuals (Bozzi et al., 2019; Van Zyl et al., 2017; Joos et al., 2008). This lack of significant virus evolution on ART is considered one of the strongest arguments against residual HIV replication. On the other hand, a transient increase in episomal HIV DNA has been demonstrated in a number of trials of ART intensification with raltegravir, an INSTI (Buzón et al., 2010; Hatano et al., 2013a). This accumulation of unintegrated HIV DNA, observed upon blocking integration, revealed ongoing integration events prior to intensification. Because all other antiretroviral drug classes act upstream of INSTIs, this implies that complete rounds of HIV replication (infection of new cells) had been ongoing pre-intensification. However, no decrease in residual HIV viremia could be demonstrated in these and other intensification trials (Gandhi et al., 2010; McMahon et al., 2010; Hatano et al., 2011).

It is also a matter of debate whether different ART regimens are equally potent in suppressing residual HIV replication. All current antiretroviral drugs act by preventing the infection of new cells and are not expected to inhibit HIV RNA transcription or virus production in the long-lived reservoir cells that were infected prior to ART initiation, or in the progeny of such cells. Therefore, if regimens are equally potent in stopping the infection of new cells, one would not expect to detect a difference in residual viremia or CA RNA levels between ART regimens. Consequently, finding such a difference would suggest that some regimens are more potent in suppressing residual replication than others, arguing that virus suppression is less complete with at least some of the regimens. A number of studies reported lower levels of residual viremia in individuals treated with NNRTI-based, compared to PI-based, ART regimens (Geretti et al., 2019; Darcis et al., 2020a, reviewed in Darcis et al., 2020b). However, to date, few studies have compared levels of CA HIV reservoir markers between different ART regimens (Nicastri et al., 2008; Sarmati et al., 2012; Kiselinova et al., 2015). Here, we cross-sectionally measured CA HIV RNA and DNA in two cohorts of individuals receiving suppressive ART containing two NRTIs and either an NNRTI or a PI.

In this study, we demonstrated in two independent cohorts of individuals on suppressive ART that NNRTI-based triple ART regimens are associated with lower levels of CA HIV RNA compared with PI-based regimens. To the best of our knowledge, this is the largest study comparing CA HIV RNA levels between individuals on different ART regimens. Although several studies have compared residual viremia between ART regimens and most have found lower levels in NNRTI-treated than in PI-treated individuals (Darcis et al., 2020b), very few groups included other HIV reservoir markers in such comparisons. Nicastri et al., 2008 reported lower total HIV DNA levels in individuals treated with PI-based regimens and Sarmati et al., 2012 found no difference in the HIV DNA level by regimen, despite the fact that both studies reported higher residual viremia in PI-treated individuals. Kiselinova et al., 2015 performed a matched case-control study comparing nevirapine and PIs for residual viremia, total and episomal HIV DNA, and CA HIV RNA and did not find any differences by regimen for any of these markers. Notably, the latter study matched participants for the duration of PI-based or nevirapine-based regimens, but despite this, significant differences were still observed between the nevirapine- and PI-treated groups in total ART duration and duration of plasma HIV RNA suppression. In our study, we reasoned that, in the absence of a priori knowledge of the factors associated with CA HIV levels, such matching, albeit potentially reducing confounding, could introduce a selective bias and the results would therefore not be representative of the total ART-treated population. Instead, we chose for a cohort study design, controlling for a number of factors in the multivariable models.

Among all demographic and clinical variables, only duration of current regimen and duration of virological suppression were associated with the ART regimen, being longer in NNRTI- than in PI-treated individuals. This can be explained by the fact that while efavirenz and nevirapine, the drugs used by the absolute majority of our NNRTI-treated individuals, were approved for medical use in the late 1990s, modern PIs like atazanavir and darunavir, which were used by most of our PI-treated individuals, were only approved in the mid- or late 2000s. This means that most of the NNRTI-treated individuals in this study started ART, or switched to NNRTIs from the first-generation PIs, earlier than the PI-treated individuals. Because the HIV reservoir generally decays with time on ART (Siliciano et al., 2003), this association of duration of suppression with the ART regimen could have potentially confounded the association of the ART regimen with the HIV reservoir measures such as CA RNA and DNA. Indeed, we found that both these HIV markers were negatively associated with the duration of suppression in the AIMS cohort. Interestingly, low-level plasma HIV RNA detectability in that cohort was also negatively associated with the duration of suppression (Figure 1—figure supplement 2), confirming the results of a previous study (Darcis et al., 2020a). However, to our surprise, no association of CA RNA or DNA with the duration of suppression was found in the COBRA cohort. One possible reason for this difference between the two cohorts is that the COBRA participants were on average much longer on ART than the AIMS participants (117.8 vs 47.1 months of cumulative virological suppression, respectively). Decay of the HIV reservoir after ART initiation is multiphasic (Perelson et al., 1997; Blankson et al., 2000), and while the long-term dynamics of CA RNA has not yet been studied in detail, reports on the dynamics of total HIV DNA and residual plasma viremia have demonstrated that these markers reach a plateau after 5–7 years of treatment (Palmer et al., 2008; Besson et al., 2014; Bachmann et al., 2019), possibly due to clonal expansion of the viral reservoir cells (Maldarelli et al., 2014; Wagner et al., 2014). If the same applies to CA RNA, then it may be expected that after several years on ART, this reservoir measure will also no longer depend on the time on therapy, something that we indeed observed in the COBRA cohort. Instead, in the COBRA cohort, CA RNA and especially total DNA positively correlated with the plasma HIV RNA zenith, suggesting that even after a decade of ART, the HIV reservoir size is still partly determined by its pre-therapy values. Interestingly, most proviral DNA sequences from ART-treated individuals were recently shown to match circulating HIV variants detected shortly before the start of therapy, suggesting that the HIV reservoir quickly turns over in the untreated infection and that the reservoir that persists on ART has been primarily established at the start of therapy (Abrahams et al., 2019; Brodin et al., 2016; Pankau et al., 2020).

Another variable that could have confounded the association of the ART regimen with the HIV reservoir measures such as CA HIV RNA is the adherence to ART. Earlier studies have reported lower adherence among individuals treated with older PI-based ART regimens (O'Connor et al., 2013). However, we and others have not previously observed a difference in adherence between individuals treated with modern PI- and NNRTI-based regimens (Pasternak et al., 2015; Konstantopoulos et al., 2015), and in this study, adherence was also not associated with the therapy regimen. We have previously shown that modest non-adherence correlates with longitudinal changes in CA RNA (Pasternak et al., 2012). However, no significant association between adherence and CA RNA levels was observed in this study. Adherence was also not associated with low-level plasma HIV RNA detectability (Figure 1—figure supplement 2). The relation between adherence and CA HIV RNA or residual viremia is undoubtedly complex and deserves further research, but it must be noted that while in our previous report the adherence was measured over 1-week periods immediately prior to the HIV sampling moments, in this study we used 1-month adherence measurements taken within 20 days from the sampling moments. Whether short-term adherence is more strongly associated with CA RNA levels or residual viremia remains to be studied.

Notwithstanding the associations of CA RNA with other factors, in both cohorts, NNRTI-based ART was independently associated with lower CA RNA levels as compared with PI-based ART, as revealed by the multivariable analysis. This analysis revealed very similar effect sizes of the ART regimen on CA RNA in both cohorts, despite the fact that several factors, such as duration of virological suppression and the PI drugs, differed between the cohorts. On average, CA RNA levels were 1.75- to 2-fold lower in the NNRTI-treated participants. This confirms numerous reports that measured lower residual plasma viremia in NNRTI- compared to PI-treated individuals (Darcis et al., 2020b). In fact, also in this study, low-level plasma HIV RNA was more frequently detectable in PI-treated than in NNRTI-treated participants, despite no difference in therapy adherence by regimen. Notably, a recent large study of more than 12,000 participants starting ART revealed that PI-treated participants were on average 2.7 times more likely to experience virological failure compared with NNRTI-treated participants (El Bouzidi et al., 2020). Moreover, three independent clinical trials of triple ART intensification with raltegravir have previously demonstrated much stronger increases in episomal HIV DNA in PI- compared to NNRTI-treated participants, suggesting that at ‘baseline’, PI-treated individuals had higher levels of residual replication (Buzón et al., 2010; Hatano et al., 2013a; Hatano et al., 2011). Combined, this prior evidence and the results of this study strongly suggest that NNRTIs are more potent in suppressing HIV residual replication than PIs. Constant low-level viral replication, even if it does not cause the development of drug resistance and therapy failure, could exert continuous pressure on the immune system and cause additional morbidity as a result of persistent immune activation, inflammation, and immunosenescence (Klatt et al., 2013; Massanella et al., 2016). Several studies have reported excess morbidity and mortality rates in infected ART-treated individuals, compared with the general population (Schouten et al., 2014; Guaraldi et al., 2011; Lohse et al., 2007). Although it is still unclear whether this is due to the adverse effects of the antiretroviral drugs or due to the residual HIV activity, our results argue that an effort should be made to ensure HIV replication is maximally suppressed during therapy.

Interestingly, some NNRTIs, such as rilpivirine, efavirenz, and etravirine, but not nevirapine, can promote selective apoptosis of infected cells by inducing HIV protease-mediated cytotoxicity (Trinité et al., 2019). If these NNRTIs are present in cells that are actively producing viral proteins, they may bind to the reverse transcriptase portion of a newly translated Gag-Pol polyprotein and promote its homodimerization, resulting in premature protease activation. This leads to induction of apoptosis and pyroptosis, as well as CARD8 inflammasome activation (Figueiredo et al., 2006; Jochmans et al., 2010; Wang et al., 2021). However, it is very unlikely that such NNRTI effects could contribute to the levels of CA RNA in our cohorts, for two reasons. First, for this mechanism to work, a cell has to express HIV Gag-Pol, and cells that express HIV proteins without ex vivo stimulation are exceedingly rare in ART-treated individuals (Pardons et al., 2019). Second, nevirapine, in comparison with other NNRTIs, has no such activity (Trinité et al., 2019; Figueiredo et al., 2006; Wang et al., 2021), but in our study, nevirapine was associated with the same levels of CA RNA as efavirenz, and another study showed even lower levels of residual plasma viremia in nevirapine-treated compared to efavirenz-treated individuals (Haïm-Boukobza et al., 2011). This argues against induction of apoptosis of infected cells being a plausible mechanism behind the more pronounced virological suppression by NNRTIs.

Replenishment of the HIV reservoir by residual virus replication has been proposed as one of the mechanisms of HIV persistence (Chun et al., 2005). The association of the ART regimen with total HIV DNA in this study was similar to its association with CA RNA: in both cohorts, levels of total DNA were 1.8-fold lower in the NNRTI-treated participants. This suggests that persistent residual replication in the PI-treated participants may have resulted in a larger viral reservoir. However, this has to be interpreted with caution, as no single marker can at present provide a reliable estimate of the HIV reservoir size (Sharaf and Li, 2017). Moreover, different definitions of the HIV reservoir exist. Although total HIV DNA is mostly composed of genetically defective proviruses and thus its measurements overestimate the replication-competent reservoir (Bruner et al., 2016), these defective proviruses can be transcribed, translated, and even produce defective viral particles, and therefore can contribute to chronic immune activation and inflammation despite ART (Pollack et al., 2017; Imamichi et al., 2020; Imamichi et al., 2016; Finzi et al., 2006). Therefore, it has been proposed to extend the definition of the reservoir to all infected cells that can contribute to the residual HIV pathogenesis (Avettand-Fènoël et al., 2016; Baxter et al., 2018). Furthermore, both total HIV DNA and CA HIV RNA have been shown to predict the time to viral rebound after ART interruption (Williams et al., 2014; Li et al., 2016), and we have recently reported that CA HIV RNA was predictive of both time to and magnitude of viral rebound after interruption of temporary ART initiated during primary HIV infection (Pasternak et al., 2020). This argues that despite being partially composed of defective proviruses, the transcription-competent reservoir does reflect the replication-competent reservoir (Baxter et al., 2018; Abdel-Mohsen et al., 2020). In view of our present results, future studies should investigate the effects of different ART regimens on the replication-competent reservoir, as the latter is the main obstacle for the development of an HIV cure (Pasternak and Berkhout, 2016). Interestingly, Li et al., 2016 demonstrated that NNRTI-treated individuals experienced a significantly longer time to viral rebound after ART interruption. This may suggest lower replication-competent reservoirs in individuals treated with NNRTI-based ART regimens, although longer half-lives of NNRTIs, leading to prolonged NNRTI exposure after treatment interruption, provide a plausible additional explanation.

Our study has some limitations. First, we did not include individuals treated with INSTI-based ART, which is currently recommended as the first-line therapy (https://aidsinfo.nih.gov/guidelines/html/1/adult-and-adolescent-arv/11/what-to-start), because such individuals were rare (<5%) in the COBRA cohort and absent from the AIMS cohort. Studies in more recent cohorts are necessary to elucidate the differences in CA HIV markers between INSTI-based ART and other regimens. It must be noted that although NNRTI- and PI-based ART regimens are no longer recommended as the first-line therapy in all settings, millions of infected individuals are still treated with these regimens. Thus, our results are relevant for the clinical management of these individuals. Second, although our results provide strong evidence that individuals treated with PI-based ART undergo residual HIV replication, this evidence remains indirect as the direct demonstration of infection of new cells in an ART-treated individual is extremely difficult if not impossible. Therefore, although studies have used various approaches to prove or disprove the existence of residual replication on ART (reviewed in Pasternak et al., 2013; Martinez-Picado and Deeks, 2016), all these approaches have so far been indirect. Third, although we adjusted our models for a number of clinical parameters, the observational nature of these cohorts means that residual confounding cannot be entirely excluded. For instance, PI-based regimens could have been preferentially prescribed to individuals with a worse viro-immunological profile and/or expected poor therapy adherence, because PIs impose a relatively high genetic barrier to resistance and consequently will be more ‘forgiving’ to non-adherence. However, we did not observe any significant differences by regimen in plasma HIV RNA zenith, current and nadir CD4+ count, or therapy adherence, arguing against such a ‘prescription bias’. In this regard, a clinical trial with a factorial design, in which participants would switch from PI-based to NNRTI-based ART regimens and vice versa, would be important to confirm our findings.

In summary, here we have demonstrated in two independent cohorts that levels of HIV reservoir markers are lower in individuals treated with NNRTI- as compared to PI-based combination ART. We have previously proposed CA RNA as a sensitive marker of the active HIV reservoir and residual replication (Pasternak et al., 2013), a role that is further reinforced by the results of this study. Monitoring of CA RNA levels to detect residual HIV activity despite ART is warranted in order to prevent possible ART complications such as persistent immune activation or therapy failure (Pasternak et al., 2009; El Bouzidi et al., 2020; Hatano et al., 2013b), especially in individuals treated with PI-based regimens.

All data generated or analysed during this study are included in the manuscript and supporting files.

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Author details

1. Alexander O Pasternak

   Amsterdam UMC, University of Amsterdam, Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam, Netherlands

   Contribution

   Conceptualization, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review and editing

   For correspondence

   a.o.pasternak@amsterdamumc.nl

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4097-4251

2. Jelmer Vroom

   Amsterdam UMC, University of Amsterdam, Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam, Netherlands

   Contribution

   Investigation

   Competing interests

   No competing interests declared

3. Neeltje A Kootstra

   Amsterdam UMC, University of Amsterdam, Laboratory of Viral Immune Pathogenesis, Department of Experimental Immunology, Amsterdam, Netherlands

   Contribution

   Data curation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9429-7754

4. Ferdinand WNM Wit

   1. Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands
   2. Amsterdam UMC, University of Amsterdam, Department of Global Health, Amsterdam Institute for Infection and Immunity, Amsterdam, Netherlands
   3. HIV Monitoring Foundation, Amsterdam, Netherlands
   4. Amsterdam UMC, University of Amsterdam, Department of Internal Medicine, Amsterdam, Netherlands

   Contribution

   Conceptualization, Methodology

   Competing interests

   No competing interests declared

5. Marijn de Bruin

   1. Health Psychology Group, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
   2. Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, Netherlands

   Contribution

   Data curation

   Competing interests

   No competing interests declared

6. Davide De Francesco

   Institute for Global Health, University College London, London, United Kingdom

   Contribution

   Data curation

   Competing interests

   No competing interests declared

7. Margreet Bakker

   Amsterdam UMC, University of Amsterdam, Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam, Netherlands

   Contribution

   Resources, Data curation

   Competing interests

   No competing interests declared

8. Caroline A Sabin

   Institute for Global Health, University College London, London, United Kingdom

   Contribution

   Formal analysis, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

9. Alan Winston

   Department of Medicine, Imperial College London, London, United Kingdom

   Contribution

   Data curation

   Competing interests

   No competing interests declared

10. Jan M Prins

    Amsterdam UMC, University of Amsterdam, Department of Internal Medicine, Amsterdam, Netherlands

    Contribution

    Data curation, Project administration, Writing - review and editing

    Competing interests

    No competing interests declared

11. Peter Reiss

    1. Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands
    2. Amsterdam UMC, University of Amsterdam, Department of Global Health, Amsterdam Institute for Infection and Immunity, Amsterdam, Netherlands
    3. HIV Monitoring Foundation, Amsterdam, Netherlands

    Contribution

    Data curation, Funding acquisition, Project administration, Writing - review and editing

    Competing interests

    No competing interests declared

12. Ben Berkhout

    Amsterdam UMC, University of Amsterdam, Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam, Netherlands

    Contribution

    Conceptualization, Supervision, Funding acquisition, Writing - review and editing

    Competing interests

    No competing interests declared

13. The Co-morBidity in Relation to Aids (COBRA) Collaboration

    Contribution

    Funding acquisition

    Competing interests

    No competing interests declared

    1. P Reiss, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    2. FWNM Wit, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    3. J Schouten, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    4. KW Kooij, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    5. RA van Zoest, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    6. BC Elsenga, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    7. FR Janssen, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    8. M Heidenrijk, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    9. W Zikkenheiner, Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    10. M van der Valk, Division of Infectious Diseases, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    11. NA Kootstra, Department of Experimental Immunology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    12. T Booiman, Department of Experimental Immunology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    13. AM Harskamp-Holwerda, Department of Experimental Immunology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    14. I Maurer, Department of Experimental Immunology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    15. MM Mangas Ruiz, Department of Experimental Immunology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    16. AF Girigorie, Department of Experimental Immunology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    17. J Villaudy, Department of Medical Microbiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    18. E Frankin, Department of Medical Microbiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    19. AO Pasternak, Department of Medical Microbiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    20. B Berkhout, Department of Medical Microbiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    21. T van der Kuyl, Department of Medical Microbiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    22. P Portegies, Department of Neurology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    23. BA Schmand, Department of Neurology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    24. GJ Geurtsen, Department of Neurology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    25. JA ter Stege, Department of Neurology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    26. M Klein Twennaar, Department of Neurology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    27. CBLM Majoie, Department of Radiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    28. MWA Caan, Department of Radiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    29. T Su, Department of Radiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    30. K Weijer, Department of Cell Biology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    31. PHLT Bisschop, Division of Endocrinology and Metabolism, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    32. A Kalsbeek, Department of Experimental Neuroendocrinology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    33. M Wezel, Department of Ophthalmology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    34. I Visser, Department of Psychiatry, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    35. HG Ruhé, Department of Psychiatry, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, Netherlands
    36. C Franceschi, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum Universita di Bologna, Bologna, Italy
    37. P Garagnani, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum Universita di Bologna, Bologna, Italy
    38. C Pirazzini, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum Universita di Bologna, Bologna, Italy
    39. M Capri, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum Universita di Bologna, Bologna, Italy
    40. F Dall'Olio, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum Universita di Bologna, Bologna, Italy
    41. M Chiricolo, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum Universita di Bologna, Bologna, Italy
    42. S Salvioli, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum Universita di Bologna, Bologna, Italy
    43. J Hoeijmakers, Department of Genetics, Erasmus Universitair Medisch Centrum Rotterdam, Rotterdam, Netherlands
    44. J Pothof, Department of Genetics, Erasmus Universitair Medisch Centrum Rotterdam, Rotterdam, Netherlands
    45. M Prins, Cluster of Infectious Diseases, research department, GGD Amsterdam/Public Health Service Amsterdam, Amsterdam, Netherlands
    46. M Martens, Cluster of Infectious Diseases, research department, GGD Amsterdam/Public Health Service Amsterdam, Amsterdam, Netherlands
    47. S Moll, Cluster of Infectious Diseases, research department, GGD Amsterdam/Public Health Service Amsterdam, Amsterdam, Netherlands
    48. J Berkel, Cluster of Infectious Diseases, research department, GGD Amsterdam/Public Health Service Amsterdam, Amsterdam, Netherlands
    49. M Totté, Cluster of Infectious Diseases, research department, GGD Amsterdam/Public Health Service Amsterdam, Amsterdam, Netherlands
    50. S Kovalev, Cluster of Infectious Diseases, research department, GGD Amsterdam/Public Health Service Amsterdam, Amsterdam, Netherlands
    51. M Gisslén, Göteborgs Universitet, Gotenburg, Sweden
    52. D Fuchs, Göteborgs Universitet, Gotenburg, Sweden
    53. H Zetterberg, Göteborgs Universitet, Gotenburg, Sweden
    54. A Winston, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    55. J Underwood, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    56. L McDonald, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    57. M Stott, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    58. K Legg, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    59. A Lovell, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    60. O Erlwein, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    61. N Doyle, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    62. C Kingsley, Department of Medicine, Division of Infectious Diseases, Imperial College of Science, Technology and Medicine, London, United Kingdom
    63. DJ Sharp, Department of Medicine, Division of Brain Sciences, The Computational, Cognitive & Clinical Neuroimaging Laboratory, Imperial College of Science, Technology and Medicine, London, United Kingdom
    64. R Leech, Department of Medicine, Division of Brain Sciences, The Computational, Cognitive & Clinical Neuroimaging Laboratory, Imperial College of Science, Technology and Medicine, London, United Kingdom
    65. JH Cole, Department of Medicine, Division of Brain Sciences, The Computational, Cognitive & Clinical Neuroimaging Laboratory, Imperial College of Science, Technology and Medicine, London, United Kingdom
    66. S Zaheri, Stichting HIV Monitoring, Amsterdam, Netherlands
    67. MMJ Hillebregt, Stichting HIV Monitoring, Amsterdam, Netherlands
    68. YMC Ruijs, Stichting HIV Monitoring, Amsterdam, Netherlands
    69. DP Benschop, Stichting HIV Monitoring, Amsterdam, Netherlands
    70. D Burger, Stichting Katholieke Universiteit Nijmegen, Nijmegen, Netherlands
    71. M de Graaff-Teulen, Stichting Katholieke Universiteit Nijmegen, Nijmegen, Netherlands
    72. G Guaraldi, Department of Medical and Surgical Sciences for Children & Adults, Università degli studi di Modena e Reggio Emilia, Modena, Italy
    73. A Bürkle, Department of Biology, Universität Konstanz, Konstanz, Germany
    74. T Sindlinger, Department of Biology, Universität Konstanz, Konstanz, Germany
    75. M Moreno-Villanueva, Department of Biology, Universität Konstanz, Konstanz, Germany
    76. A Keller, Department of Biology, Universität Konstanz, Konstanz, Germany
    77. C Sabin, Research Department of Infection and Population Health, University College London, London, United Kingdom
    78. D de Francesco, Research Department of Infection and Population Health, University College London, London, United Kingdom
    79. C Libert, Inflammation Research Center, Vlaams Instituut voor Biotechnologie, Ghent, Belgium
    80. S Dewaele, Inflammation Research Center, Vlaams Instituut voor Biotechnologie, Ghent, Belgium

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