T cell maturation and senescence after HCV cure in HIV-HCV coinfected patients: a prospective study

doi:10.21203/rs.3.rs-1546494/v1

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T cell maturation and senescence after HCV cure in HIV-HCV coinfected patients: a prospective study

https://doi.org/10.21203/rs.3.rs-1546494/v1

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Previously, we identified a stabilization of the HIV reservoir size in HIV + monoinfected and HIV+/HCV + coinfected patients who eliminated HCV with DAAs as well as a decrease in HIV reservoir size in HIV+/HCV- spontaneously clearers. However, variations in the distribution of memory CD4 + T cell subpopulations in coinfected patients after HCV clearance remains unclear. To analyze the expression pattern of T cell maturation (CD45RA and CD27) and senescence (CD28 and CD57) markers by flow cytometry in those patients. Longitudinal study (52 weeks follow-up) of 49 HIV+/HCV+, 38 HIV+/HCV- and 59 HIV + subjects, all of them aviremic. A generalized increase in expression of CD28 was observed for CD8 + and in CD4 + CD27 + cells. The proportion of both CD4 + TEM TH1 and TH2 cells decreased significantly in HIV+/HCV- while remained stable in HIV + and HIV+/HCV + individuals. The general decline in cell senescence of cytotoxic lymphocytes may be due to reduced antigenic stimulation of HIV-specific and HCV-specific lymphocytes. The dynamic of HIV viral reservoir in HIV+/HCV- patients matches the dynamic of CD4 + cells with a TH1 phenotype, which could mean a decrease in the number of circulating TFH1 lymphocytes after an improvement in generalized inflammation state.

HIV

HCV

coinfection

DAAs

ART

CD4+ T cell

CD8+ T cell

senescence

maturation

HIV reservoir

HIV splicing

Human immunodeficiency virus (HIV) infection affects 38 million people worldwide and currently infects 1.7 million people yearly ¹. Of these, an estimated 2.75 million people are also living with hepatitis C virus (HCV) because of shared routes of transmission ². HIV/HCV coinfection alters the natural course of both diseases affecting the rates of HCV spontaneous clearance, promoting the development of liver fibrosis, worsening the state of generalized inflammation and accelerating immune senescence ^{3, 4, 5}.

The administration of the new direct-acting antivirals (DAAs), IFN-free treatments, has made possible to eliminate HCV infection with great efficiency (> 90%) ⁶. However, in HIV infected individuals, although antiretroviral therapy (ART) has shown excellent results in the control of viremia and viral replication, finding a cure for this infection is still a challenge due to the ability of the virus to establish latency in viral reservoirs that remain inaccessible to treatments ^{7, 8, 9}.

Most of HIV reservoir is comprised of latently infected memory resting (r)CD4 + T cells including central memory (TCM), transitional memory (TTM), effector memory (TEM), terminally-differentiated effector memory (TEMRA), and others more recently described such as stem central memory (TSCM) and T follicular helper (TFH) cells ^{10, 11, 12}. Our group has demonstrated that HIV-1/HCV coinfection increases HIV reservoir size in rCD4 + T cells in HCV spontaneous clarifiers (HIV+/HCV-) and HCV chronically infected subjects (HIV+/HCV+) in comparison with HIV + monoinfected controls ¹³. Moreover we noted increased levels of multiple spliced mRNAs in rCD4 + T cells from coinfected patients which could indicate a higher Tat activity in these cells despite their resting state ¹⁴.

After a follow-up time of 52 weeks, we observed that HIV reservoir remained invariable in HIV+/HCV + patients even after HCV elimination with DAA treatment, in contrast to a decrease in the reservoir size of HIV+/HCV- individuals ¹⁵ coupled with a controlled production of multiple spliced viral mRNA in transcriptionally active cells (unpublished data).

The objective of this study was to analyze the expression pattern of T cell maturation (CD45RA and CD27) and senescence (CD28 and CD57) markers in chronically coinfected HIV+/HCV + individuals, HIV+/HCV- spontaneous clarifiers and HIV + monoinfected patients, as well as the dynamic of this expression after a follow-up time of 52 weeks, and after the administration of DAAs to HIV+/HCV + patients. Moreover, the dynamic of the different CD4 + T cell subsets was correlated to the previously observed change of HIV reservoir size in the same patient cohort ¹⁵.

Patients

Prospective longitudinal study including samples from HIV infected adults under suppressive ART. A total of 146 study participants were classified as: 1) HIV + group: 59 infected with HIV without previous contact with HCV (negative HCV PCR and antibodies); 2) HIV+/HCV- group: 38 HIV patients who spontaneously cleared the HCV (negative HCV PCR but positive HCV antibodies); and 3) HIV+/HCV + group: 49 HIV patients coinfected with HCV (positive HCV PCR and antibodies) who had never been treated for HCV before baseline, but had achieved SVR with DAAs at endpoint. Some participants were lost to follow-up, resulting in 79 endpoint patients: 31 HIV+, 22 HIV+/HCV- and 26 HIV+/HCV+. The STROME-ID checklist was used to strength the design and conduct the study ¹⁶.

All patients were selected from five tertiary hospitals in the Community of Madrid (Spain) belonging to COVIHEP group (Supplemental Acknowledgments). Baseline blood samples were collected between November 2016 and June 2017 and endpoint samples from January 2018 to March 2019, coinciding with a spacing time of 52 weeks for paired samples. Patient selection criteria were described in previous works ^{13, 14}. At baseline, none of the patients had previous treatment to HCV infection; however, all HIV+/HCV + individuals successfully eliminated HCV infection with DAAs and achieved sustained virological response (SVR) at endpoint.

Epidemiological and clinical variables of study patients were collected from medical records. Plasma HIV RNA viral load, plasma HCV RNA viral load, liver fibrosis and IFNL3 (IL-28B) rs12979860 single nucleotide polymorphism were evaluated as previously described ^{13, 14}.

Cell phenotyping and flow cytometry

T cell phenotyping was performed on fresh peripheral blood mononuclear cells (PBMCs) that were isolated by density gradient. Cells were resuspended in Brilliant Staining Buffer (BD Biosciences, 563794) and then stained with Fixable Viability Stain-PE (BD Biosciences, New Jersey, US, 564996) to exclude non-viable cells, and the following fluorescently-conjugated monoclonal antibodies: CD3-FITC (BD Biosciences, 555332), CD4-BUV395 (BD Biosciences, 564724), CD8-BV510 (BD Biosciences, 563256), CD45RA-APC-CyTM 7 (BD Biosciences, 560674), CD27-BV421 (BD Biosciences, 562513), CD28-PE-CyTM 7 (BD Biosciences, 560684) and CD57-APC (BD Biosciences 560845). After incubation and washing, cells were analyzed by flow cytometry using BD LSR FortessaTM X-20 flow cytometer and BD FACSDivaTM software (BD Biosciences). Data were analyzed with FlowJoTM v10 software (TreeStar).

After analysis (Supplemental file 1) CD4 + and CD8 + T cell populations were identified as part of different phenotypes: CD8 + and CD4 + naïve T cells (TN) (CD45RA + CD27 + CD28 + CD57-), CD8 + and CD4 + TCM (CD45RA-CD27 + CD28 + CD57-); CD8 + and CD4 + TTM (CD45RA-CD27 + CD28-CD57-); CD8 + TEM (CD45RA-CD27-CD28+/-CD57-), CD4 + TEM TH1 (CD45RA-CD27-CD28-CD57-), CD4 + TEM TH2 (CD45RA-CD27-CD28 + CD57-), and CD8 + and CD4 + TEMRA (CD45RA + CD27-CD28-CD57+), as previously described ^{17, 18, 19, 20, 21, 22, 23, 24, 25} (Supplemental file 2).

Statistical analysis

Epidemiological and clinical variables were presented as a percentage for categorical variables and as median and interquartile range (IQR) for continuous variables. Differences between groups for categorical variables were analyzed using χ2 test and the 2-sided Fisher exact test (non-parametric). For continuous variables, after studying normalization with Kolmogorov-Smirnov test, groups were compared using ANOVA test (parametric) or Kruskal-Wallis H test (non-parametric). Student’s T test (parametric) was used to determine differences in clinical characteristics between baseline and endpoint of the study.

The proportion of the different T cell populations was expressed as median and IQR of their percentage expression over total CD8 + and CD4 + T cells. Kruskal-Wallis H test was also used to compare the three study groups. Moreover, we aimed to assess significant relationships between cell prevalence and the measured time points (baseline or endpoint) by using mixed effect regression models for paired samples. We fit our flow cytometry data matrix to a beta inflated mixed effect regression model with the R package gamlss v5.2-0 ²⁶ where:

$$\left(1\right) {Y}_{ijk}={X}_{jk}+{Z}_{ijk}+{e}_{ijk}$$

In Eq. (1) Y is the raw cell prevalence data (model’s response variable) of the i^th cell type, X is the measurement time point with levels j = baseline or j = endpoint of the k^th patient, Z is the model’s random effect accounting for the dependency between paired measurements of patients in X_j=baseline and X_j=endpoint, and e is the random residual term.

All statistical analyses were executed using SPSS v22.0 (SPSS Inc.) and R statistical software (v4.0.2). Statistical significance was defined as P < 0.05 (2-tailed).

Ethics approval and consent to participate

Each individual signed an informed consent in order to assure privacy and confidentiality. The study was performed in accordance with the Declaration of Helsinki. The protocol study was revised and approved by ethic review broads from each institution involved [Comité de Ética de la Investigación (CEI) of Institute of Health Carlos III (Ref: CEI PI81_2017-v3), CEI Hospital La Paz (Ref: PI-3005), CEI Hospital La Princesa (Ref: PI15CIII/00031), CEI Hospital Infanta Leonor (Ref: 09/2016).

Study patients

Table 1 displays baseline epidemiological and clinical characteristics of the study population. All patients were Caucasian and 63.7% (n= 93) were men. They had a median age of 49.0 years (IQR: 42.8-54.0), median height of 169.0 cm (IQR: 162.0-174.0) and median weight of 70.0 Kg (IQR: 61.1-79.0), this being significantly lower in HIV+/HCV+ individuals [64.4 Kg (IQR: 55.0-74.0)] (p=0.004). Differences between study groups were also found in time of HIV infection, this being higher in HIV+/HCV+ patients with a median time of 23.5 years (10.2-28.7) (p<0.001); in HIV transmission route, with sexual transmission being predominant in HIV+ patients (n=42, 71.2%) and parenteral route in HCV exposed subjects (n=52, 59.8%) (p=0.002); and in IFNL3 (IL-28B) genotype (p<0.001), with CC being the predominant genotype in HIV+/HCV- patients (n=30, 78.9%), which would support spontaneous clearance of HCV infection. On the other hand, no differences were found between study groups regarding Centers for Disease Control and Prevention (CDC) classification system for HIV infection (p=0.165), ART regimen (p=0.348) and prevalence of CMV coinfection (p=0.174).

Table 2 shows CD4 and CD8 counts of the study patients. For all study participants, immune status showed no differences between baseline and endpoint in relation to the number of total CD4+ T cells [(763.0 cells/µL; IQR: 607.7-1009.5) vs. (835.0 cells/µL; IQR: 652.0-1108.0)] (p=0.945) and total CD8+ T cells [(889.0 cells/µL; IQR: 647.0-1230.3) vs. (941.0 cells/µL; IQR: 701.0-1479.0)] (p=0.406). All patients showed CD4+ values over 500 cells/µL demonstrating a good state of their immune system. CD8+ T-cell percentage was significantly higher at endpoint than at baseline [(39.0%; IQR: 33.0-44.8) vs. (39.5%; IQR: 35.5-45.2)] CD8+ T-cell percentage appeared to be statistically significant at endpoint than at baseline [(39.0%; IQR: 33.0-44.8) vs. (39.5%; IQR: 35.5-45.2)] (p=0.029). There were no differences when comparing CD4+/CD8+ ratios between baseline (0.92; IQR: 0.69-1.18) and endpoint (0.88; IQR: 0.71-1.10) (p=0.562).

Table 3 describes the clinical characteristics of HCV infection. HCV genotypes 1 (n=28, 57.1%) and 4 (n=12, 24.5%) were the most prevalent amongst patients. In relation to fibrosis stage, no differences were found as most HCV exposed individuals (n=61, 49.6%) were diagnosed with F0-F1 fibrosis stadium (p=0.090). Majority of HIV+/HCV+ individuals were given Ledipasvir plus Sofosbuvir (n=16, 61.5%) during follow-up to eliminate HCV infection.

Dynamic of cd8+T cell maturation and senescence

Figure 1 and Table 4 show the dynamic of the defined CD8+ T cell populations for paired samples. Analysis by beta inflated mixed effect regression model showed a general significant increase over time in the proportion of CD8+ TN, CD8+ TCM, CD8+ TEM (CD28+) and CD8+ TEMRA, except for HIV+/HCV- patients. Moreover, a general significant decrease in the proportion of CD8+ TEM (CD28-) was observed as well as in CD8+ TTM in HIV- and HIV+/HCV- groups but not in HIV+HCV+ group.

Supplemental file 3 shows cross-sectional studies of CD8+ populations at baseline and endpoint, and the resulting statistical significance from the comparison of the three study groups.

Dynamic of cd4+ T cell maturation and senescence

Figure 2 and Table 5show the dynamic of CD4+ T cells for paired samples. Analysis disclosed a general increase although mostly not statistically significant for CD4+ TN and CD4+ TCM. A general decrease was observed in the proportion of CD4+ TTM, CD4+ TEM TH1 and CD4+ TEM. However, the dynamic in CD4+ TEMRA proportions was heterogeneous between study groups. Supplemental file 4 shows cross-sectional studies of CD4+ T cell populations and differences between patient groups both at baseline and endpoint of the study

Understanding over time changes in T cell populations in HIV infected and HCV exposed patients help to get a better knowledge about the impact of prolonged ART and HCV elimination with DAAs on HIV reservoir size dynamic and immune senescence ¹⁵.

Overall, we observed a general decline in cell senescence since the proportion of CD8+ TN, CD8+ TCM, CD8+ TEM (CD28+) increased over time and the proportion of CD8+ TTM, CD8+ TEM (CD28-) decreased. The effect of ART regulation on early immune senescence has already been described in patients with chronic HIV infection and correlates with cessation of antigenic stimulation of HIV-specific CD8+ lymphocytes ^{27, 28, 29}. However, to our knowledge, this is the first study that identifies the same phenomenon in HIV infected patients previously exposed to HCV (both chronically coinfected and spontaneous clearers), which could possibly be explained by the end of the antigenic stimulation and sustained HCV-specific CD8+ cell death.

On the other hand, the most senescent population considered in this study, CD8+ TEMRA (CD28-CD57+), increased its proportion at the end of the study for HIV+ and HIV+/HCV+ patients, and it was only reduced for HIV+/HCV- individuals. During natural HIV infection, immune senescence increases with the accumulation of highly differentiated CD4+ and CD8+ cells that have lost the expression of CD28 and gained that of CD57 (CD8+ TEMRA). This may cause premature immune aging and contributes to the onset of acquired immune deficiency syndrome (AIDS) or serious non-AIDS-related pathologies ³⁰, in the absence of ART.

Despite successful ART, HIV infected individuals fail to normalize CD8+ T cell activation (HLADR+CD38+), which leads to a chronic inflammatory state and the appearance of comorbidities ^{31, 32, 33}. This could be reflected in the failure to normalize the proportion of late-senescent cells despite the control of viral replication as was observed in both HIV+ and HIV+/HCV+ patients, who still show altered levels of pro-inflammatory cytokines even after the elimination of HCV with DAAs ^{34, 35, 36, 37}. However, the significant increase observed in CD28+ TEM in all the studied groups, and more importantly in senescent CD57+ TEMRA, may reflect an antigenic stimulation of the cytotoxic T cells, in both HIV+ and HIV+/HCV+ patients differing of the spontaneous clearers group that showed a mild decrease in TEMRA. HIV+/HCV- individuals could managed to control immune aging as the potent immune response that allowed them to spontaneously clarify HCV infection.

The presence of HCV-specific CD8+ T cells, previously identified, with phenotypic features of T-cell exhaustion and memory, both before and after treatment with direct acting antiviral (DAA) agents may contribute to the differences observed in the spontaneous clearers group ³⁸.

Regarding CD4+ T cells, a similar dynamic of CD28 expressing cells was observed but only in non-effector CD27+ cells (CD4+ TN, CD4+TCM, CD4+ TTM). An increased number of CD28 expressing cells in HIV-infected CD4+ cells has been related to a high intracellular concentration of viral accessory proteins Nef and Vpu ³⁹. In fact, our group previously observed a generalized increase over time of single and multiple spliced viral RNA transcripts in the same cohort of patients (unpublished data). However, this would not explain why the dynamic of CD28 seemed to be CD27-dependent on CD4+ cells. This result may be explained by the fact that CD27 promotes T cell survival ^{40, 41, 42}. This could in turn promote resistance to apoptosis of infected CD4+ cells, viral transcription and the effect of Nef and Vpu on CD28.

As discussed above, effector CD4+ cells (CD27-) do not show the same dynamic as that observed in CD8+ cells. CD4+ TEM TH1 cells are especially noteworthy, as they show an identical dynamic to that of the HIV reservoir size in resting (r)CD4+ T cells (CD4+CD25-CD69-HLA-DR-) in the same patient cohort ¹⁵. Both viral reservoir size and proportion of CD4+ TEM TH1 significantly decreased in HIV+/HCV- patients and seemed to remain stable in HIV+ and HIV+/HCV+ individuals. Previously, it has been described that CD4+ TCM and TTM are major viral compartments ⁴³ and that under ART, long-lived CD4+ TEM cells replenish the majority of the stable HIV reservoir ⁴⁴. Moreover, there is now increasing evidence that another cellular subtype, TFH cells both lymph node resident and circulating, would also comprise a large part of the viral reservoir ^{45, 46}. We can relate TEM TH1 and TFH cells since most TFH present a TH1 phenotype (TFH1) with an enhanced production of IFN-γ ⁴⁷. Thus, we cannot rule out the possibility that the significant decrease in CD4+ cells with TH1 phenotype in HIV+/HCV- individuals could be related to a decrease in TEM TH1 and/or TFH1 cells. Since only TFH1 cells can express the CD4+CD25-CD69-HLA-DR- phenotype ^{19, 48, 49, 50, 51}, these cells correlate to the reduced viral reservoir size in rCD4+ T cell of spontaneous clarifiers ¹⁵.

During HIV infection, immune activation and the production of proinflammatory cytokines such as IFN-γ, IL-21, IL-6 and IP-10 increase. IFN-γ is the main stimulator of differentiation from TN to TH1 cells and from TFH0 to TFH1 cells ⁴⁷. Moreover, HIV+/HCV- patients may initially have a strong CD4+ TH1 response, as it has been related to spontaneous clearance of HCV ^{52, 53}. This could explain, in the context of simultaneous coinfection, the large size of the HIV reservoir observed in these patients prior to follow-up ¹³. However, over time, we observed that this response stabilized and reservoir diminished. We hypothesized that the decrease of the HIV reservoir size in HIV+/HCV- individuals was related to the decrease in CD4+ latently infected cells with TH1 phenotype since the apparent control of infection by these individuals would reduce immune activation and the production of proinflammatory cytokines. With the reduction of IFN-γ in particular, the proportion of TFH1 cells would decline and with them the amount of proviral DNA copies integrated by 10⁶ CD4+CD25-CD69-HLA-DR- cells.

A decrease in the proportion of TH1 cells and consequently in IFN-γ production would be expected to increase the proportion of TH2 ⁴⁶. However, our results showed a decrease in the proportion of these cells for both HIV+ and HIV+/HCV- patients. Other authors have previously described that the dramatically increased humoral TH2 response during HIV infection stabilizes under ART ⁵⁴. Therefore, we hypothesized that the generalized decrease in TH2 cell prevalence may be due to a normalization of the TH2 response, and that changes in the HIV viral reservoir are better explained by the dynamic of cellular populations of TH1 phenotype. Further research should be undertaken to investigate TH1 and TH2 cytokine production in these patients.

A decrease in antigen presentation of HIV-specific CD8+ lymphocytes occurs not only in HIV-infected patients under ART but also in patients chronically infected or that had been infected and recovered with HCV.

However, despite successful ART, only HCV spontaneous clarifiers seem to normalize late senescent cells. Furthermore, these patients seem to better control proinflammatory responses and the production of cytokines such as IFN-γ, which in turn would be related with a decrease in the number of TH1 cells, which harbor proviral DNA.

AIDS - Acquired immune deficiency syndrome

ART – Antiretroviral therapy

COVIHEP - Multidisciplinary Group of Viral Coinfection HIV/Hepatitis

DAAs - Direct-acting antivirals

HCV - Hepatitis C virus

HIV - Human immunodeficiency virus

IFN – Interferons

IFNL3 - Interferon lambda 3

IQR - Interquartile range

mRNA - Messenger ribonucleic acid

PBMCs - Peripheral blood mononuclear cells

PCR - Polymerase chain reaction

SVR - Sustained virological response

TCM - Central memory T cells

TEM - Effector memory T cells

TEMRA - Terminally-differentiated effector memory T cells

TFH - T follicular helper T cells

TN - naïve T cells

TSCM - Stem central memory T cells

TFH - T follicular helper T cells

TTM - Transitional memory T cells

Acknowledgements

The authors thank all the patients for their participation. See Supplemental Acknowledgments for consortium details.

Author contributions statement

VB conceived the study. IC, NR and JMB. participated in its design. LMC, LDD, PR, IDS, provided the patients’ data. PMR, CCB, VLA, SAL, IC, AFR and VB selected the data. PMR. designed the database. PMR, DVM, IC and VB analyzed the data. PMR drafted the manuscript. IC, DVM, CCB, NR, JMB, VLA, SAL, LMC, LDD, PR, IS, MC, CP, MLG, AFR and VB discussed the final manuscript. All the authors read and approved the final manuscript.

Funding

Financial support was provided by the Instituto de Salud Carlos III to VB and AFR (PI15CIII/00031 and PI18CIII/00020) and The SPANISH AIDS Research Network RD16CIII/0002/0002 and RD16CIII/0025/0013 - ISCIII – FEDER. AFR and NR are supported by the Miguel Servet programme from Fondo de Investigación Sanitaria (ISCIII) (CP14/CIII/00010 and CP14/00198, respectively). CP is financed by national funds via Fundação para a Ciência e a Tecnologia (FCT) through Norma Transitória - DL57/2016/CP1376/ CT0004.

Competing interests’ statement

The author(s) declare no competing interests.

Data availability

The data that support the findings of this study are available from the corresponding author, (IC or VB), upon reasonable request.

UNAIDS. Global HIV & AIDS statistics — 2020 fact sheet. Available from: https://www.unaids.org/en/resources/fact-sheet
(WHO), W.H.O. HIV and hepatitis coinfections. Available from: https://www.who.int/hiv/topics/hepatitis/en/
Mandorfer, M., Schwabl, P., Steiner, S., Reiberger, T. & Peck-Radosavljevic, M. Advances in the management of HIV/HCV coinfection. Hepatol Int 10, 424–435 (2016).
Liberto, M.C. et al. Virological Mechanisms in the Coinfection between HIV and HCV. Mediators Inflamm 2015, 320532 (2015).
Osibogun, O. et al. A systematic review of the associations between HIV/HCV coinfection and biomarkers of cardiovascular disease. Rev Med Virol 28 (2018).
Spengler, U. Direct antiviral agents (DAAs) - A new age in the treatment of hepatitis C virus infection. Pharmacol Ther 183, 118–126 (2018).
Cihlar, T. & Fordyce, M. Current status and prospects of HIV treatment. Curr Opin Virol 18, 50–56 (2016).
Coiras, M., López-Huertas, M.R., Pérez-Olmeda, M. & Alcamí, J. Understanding HIV-1 latency provides clues for the eradication of long-term reservoirs. Nat Rev Microb zol 7, 798–812 (2009).
Rose, R. et al. Eradication of HIV from Tissue Reservoirs: Challenges for the Cure. AIDS Res Hum Retroviruses 34, 3–8 (2018).
Buzon, M.J. et al. HIV-1 persistence in CD4 + T cells with stem cell-like properties. Nat Med 20, 139–142 (2014).
Banks, H.T. et al. Immuno-modulatory strategies for reduction of HIV reservoir cells. J Theor Biol 372, 146–158 (2015).
García, M., Buzón, M.J., Benito, J.M. & Rallón, N. Peering into the HIV reservoir. Rev Med Virol 28, e1981 (2018).
López-Huertas, M.R. et al. HCV-coinfection is related to an increased HIV-1 reservoir size in cART-treated HIV patients: a cross-sectional study. Sci Rep 9, 5606 (2019).
Martínez-Román, P. et al. Hepatitis C Virus Influences HIV-1 Viral Splicing in Coinfected Patients. J Clin Med 9 (2020).
Paula, Martínez-Román, C.C.-B., Amanda & Fernández-Rodríguez, M.C., Verónica Briz. Virological impact of HCV elimination with DAAs in the HIV reservoir in HIV/HCV patients. HIV Persistence During Therapy. Reservoirs ans Eradication Strategies Workshop. Miami, USA; 2019.
Field, N. et al. Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID): an extension of the STROBE statement. Lancet Infect Dis 14, 341–352 (2014).
Larbi, A. & Fulop, T. From "truly naïve" to "exhausted senescent" T cells: when markers predict functionality. Cytometry A 85, 25–35 (2014).
Okada, R., Kondo, T., Matsuki, F., Takata, H. & Takiguchi, M. Phenotypic classification of human CD4 + T cell subsets and their differentiation. Int Immunol 20, 1189–1199 (2008).
Mahnke, Y.D., Brodie, T.M., Sallusto, F., Roederer, M. & Lugli, E. The who's who of T-cell differentiation: human memory T-cell subsets. Eur J Immunol 43, 2797–2809 (2013).
van den Broek, T., Borghans, J.A.M. & van Wijk, F. The full spectrum of human naive T cells. Nat Rev Immunol 18, 363–373 (2018).
Sallusto, F., Geginat, J. & Lanzavecchia, A. Central memory and effector memory T cell subsets: function, generation, and maintenance. Annu Rev Immunol 22, 745–763 (2004).
Bour-Jordan, H. & Blueston, J.A. CD28 function: a balance of costimulatory and regulatory signals. J Clin Immunol 22, 1–7 (2002).
Tian, Y. et al. Unique phenotypes and clonal expansions of human CD4 effector memory T cells re-expressing CD45RA. Nat Commun 8, 1473 (2017).
Martin, M.D. & Badovinac, V.P. Defining Memory CD8 T Cell. Front Immunol 9, 2692 (2018).
Pangrazzi, L. et al. CD28 and CD57 define four populations with distinct phenotypic properties within human CD8. Eur J Immunol 50, 363–379 (2020).
Rigby & RA, S.D. Generalized additive models for location, scale and shape. Journal of the Royal Statistical Society: Series C. Applied Statistics; 2005. pp. 507–554
Plana, M. et al. Immunological benefits of antiretroviral therapy in very early stages of asymptomatic chronic HIV-1 infection. AIDS 14, 1921–1933 (2000).
Lee, S.A. et al. Impact of HIV on CD8 + T cell CD57 expression is distinct from that of CMV and aging. PLoS One 9, e89444 (2014).
Tassiopoulos, K. et al. CD28-negative CD4 + and CD8 + T cells in antiretroviral therapy-naive HIV-infected adults enrolled in adult clinical trials group studies. J Infect Dis 205, 1730–1738 (2012).
Appay, V. & Kelleher, A.D. Immune activation and immune aging in HIV infection. Curr Opin HIV AIDS 11, 242–249 (2016).
de Armas, L.R. et al. Reevaluation of immune activation in the era of cART and an aging HIV-infected population. JCI Insight 2 (2017).
Duffau, P. et al. Multimorbidity, age-related comorbidities and mortality: association of activation, senescence and inflammation markers in HIV adults. AIDS 32, 1651–1660 (2018).
Serrano-Villar, S. et al. HIV-infected individuals with low CD4/CD8 ratio despite effective antiretroviral therapy exhibit altered T cell subsets, heightened CD8 + T cell activation, and increased risk of non-AIDS morbidity and mortality. PLoS Pathog 10, e1004078 (2014).
Ghiglione, Y. et al. Hepatitis C Virus (HCV) Clearance After Treatment With Direct-Acting Antivirals in Human Immunodeficiency Virus (HIV)-HCV Coinfection Modulates Systemic Immune Activation and HIV Transcription on Antiretroviral Therapy. Open Forum Infect Dis 7, ofaa115 (2020).
Parisi, S.G. et al. Time course of cellular HIV-DNA and low-level HIV viremia in HIV-HCV co-infected patients whose HCV infection had been successfully treated with directly acting antivirals. Med Microbiol Immunol 206, 419–428 (2017).
Pavone, P. et al. Systemic adipokines, hepatokines and interleukin-6 in HCV-monoinfected and HCV/HIV coinfected patients treated with direct antiviral agents (DAAs). Clin Res Hepatol Gastroenterol 42, e45-e48 (2018).
Garcia-Broncano, P. et al. Mild profile improvement of immune biomarkers in HIV/HCV-coinfected patients who removed hepatitis C after HCV treatment: A prospective study. J Infect 80, 99–110 (2020).
Wieland, D. et al. TCF1 + hepatitis C virus-specific CD8 + T cells are maintained after cessation of chronic antigen stimulation. Nat Commun 8, 15050 (2017).
Pawlak, E.N., Dirk, B.S., Jacob, R.A., Johnson, A.L. & Dikeakos, J.D. The HIV-1 accessory proteins Nef and Vpu downregulate total and cell surface CD28 in CD4. Retrovirology 15, 6 (2018).
Remedios, K.A. et al. CD27 Promotes CD4. J Immunol 203, 639–646 (2019).
Peperzak, V., Xiao, Y., Veraar, E.A. & Borst, J. CD27 sustains survival of CTLs in virus-infected nonlymphoid tissue in mice by inducing autocrine IL-2 production. J Clin Invest 120, 168–178 (2010).
Song, D.G. et al. CD27 costimulation augments the survival and antitumor activity of redirected human T cells in vivo. Blood 119, 696–706 (2012).
Puertas, M.C. et al. Lack of concordance between residual viremia and viral variants driving de novo infection of CD4(+) T cells on ART. Retrovirology 13, 51 (2016).
Goonetilleke, N., Clutton, G., Swanstrom, R. & Joseph, S.B. Blocking Formation of the Stable HIV Reservoir: A New Perspective for HIV-1 Cure. Front Immunol 10, 1966 (2019).
Aid, M. et al. Follicular CD4 T Helper Cells As a Major HIV Reservoir Compartment: A Molecular Perspective. Front Immunol 9, 895 (2018).
Perreau, M. et al. Follicular helper T cells serve as the major CD4 T cell compartment for HIV-1 infection, replication, and production. J Exp Med 210, 143–156 (2013).
Velu, V., Mylvaganam, G., Ibegbu, C. & Amara, R.R. Tfh1 Cells in Germinal Centers During Chronic HIV/SIV Infection. Front Immunol 9, 1272 (2018).
Li, H. & Pauza, C.D. CD25(+) Bcl6(low) T follicular helper cells provide help to maturing B cells in germinal centers of human tonsil. Eur J Immunol 45, 298–308 (2015).
Sathaliyawala, T. et al. Distribution and compartmentalization of human circulating and tissue-resident memory T cell subsets. Immunity 38, 187–197 (2013).
Asrir, A., Aloulou, M., Gador, M., Pérals, C. & Fazilleau, N. Interconnected subsets of memory follicular helper T cells have different effector functions. Nat Commun 8, 847 (2017).
Zhou, M. et al. The effect of aging on the frequency, phenotype and cytokine production of human blood CD4 + CXCR5 + T follicular helper cells: comparison of aged and young subjects. Immun Ageing 11, 12 (2014).
Dustin, L.B., Cashman, S.B. & Laidlaw, S.M. Immune control and failure in HCV infection–tipping the balance. J Leukoc Biol 96, 535–548 (2014).
Isaguliants, M.G. & Ozeretskovskaia, N.N. [Role of a host in spontaneous recovery from viral hepatitis C: genetic predetermined factors]. Vopr Virusol 53, 40–45 (2008).
Kidd, P. Th1/Th2 balance: the hypothesis, its limitations, and implications for health and disease. Altern Med Rev 8, 223–246 (2003).

Table 1: Epidemiological and clinical characteristics of the study population.

	TOTAL n=146	HIV+ n=59	HIV+/HCV- n=38	HIV+/HCV+ n=49	p
Male, n (%)	93 (63.7%)	38 (64.4%)	26 (68.4%)	29 (59.2%)	0.691
Age, years *	49.0 (42.8-54.0)	45.0 (63.0-54.0)	51 (47.8-53.5)	50 (44.5-53.5)	0.113
Weight, Kg *	70.0 (61.1-79.0)	72.0 (63.0-80.5)	75.8 (64.3-82.9)	64.4 (55.0-74.0)	*0.004*
Height, cm *	169.0 (162.0-174.0)	168.0 (160.5-174.5)	169.0 (165.0-174.0)	168.0 (160.0-174.5)	0.405
Time of HIV infection, years *	17.4 (7.5-25.3)	10.2 (5.6-21.4)	21.3 (10.9-26.8)	23.5 (10.2-28.7)	*<0.001*
Transmission route, n (%)	-	-	-	-	*0.002*
IDUs	52 (35.6%)	0 (0.0%)	23 (60.5%)	29 (59.2%)	-
MSM	40 (27.4%)	22 (37.3%)	8 (21.1%)	10 (20.4%)	-
MSW	27 (18.5%)	20 (33.9%)	4 (10.5%)	3 (6.1%)	-
Others	12 (8.3%)	5 (8.5%)	1 (2.6%)	6 (12.2%)	-
Unknown	15 (10.3%)	12 (20.3%)	2 (5.3%)	1 (2.0%)
CDC category, n (%)	-	-	-	-	0.165
A	84 (57.5%)	42 (71.3%)	18 (47.4%)	24 (49.0%)	-
B	26 (17.8%)	9 (15.3%)	8 (21.1%)	9 (18.3%)	-
C	32 (21.9%)	5 (8.5%)	11 (28.9%)	16 (32.7%)	-
Unknown	4 (2.7%)	3 (5.1%)	1 (2.6%)	0 (0.0%)	-
cART regimen, n (%)	-	-	-	-	0.348
NNRTIs	49 (33.6%)	18 (30.5%)	17 (44.7%)	14 (28.6%)	-
NRTIs	3 (2.1%)	2 (3.4%)	0 (0.0%)	1 (2.0%)	-
PIs	13 (8.9%)	3 (5.1%)	5 (13.2%)	5 (10.2%)	-
INIs	52 (35.6%)	23 (39.0%)	12 (31.6%)	17 (34.7%)	-
Dual therapy	22 (15.1%)	12 (20.3%)	3 (7.9%)	7 (14.3%)	-
Monotherapy	4 (2.7%)	0 (0.0%)	1 (2.6%)	3 (6.1%)	-
Unknown	3 (2.1%)	1 (1.7%)	0 (0.0%)	2 (4.1%)	-
CMV coinfection, n (%)	-	-	-	-	0.174
Yes	58 (39.7%)	17 (28.8%)	19 (50.0%)	22 (44.9%)	-
No	14 (9.6%)	5 (8.5%)	4 (10.5%)	5 (10.2%)	-
Unknown	74 (50.7)	37 (62.7%)	15 (39.5%)	22 (44.9%)	-
IFNL3 (IL-28B) genotype, n (%)	-	-	-	-	*<0.001*
CC	68 (46.6%)	23 (39.0%)	30 (78.9%)	15 (30.6%)	-
Non-CC	59 (40.4%)	22 (37.3%)	8 (21.1%)	29 (59.2%)	-
Unknown	19 (13.0%)	14 (23.7%)	0 (0.0%)	5 (10.2%)	-

Legend: HIV = Human Immunodeficiency Virus; HCV = Hepatitis C Virus. n (%) = number (percentage); * = median (interquartile range); BMI = body mass index; IDUs = intravenous drug users; MSM = men who have sex with men; MSW = men who have sex with women/women who have sex with men; CDC = centers for disease control and prevention classification system for HIV infection; cART = combined antiretroviral therapy; NNRTIs = non-nucleoside reverse transcriptase inhibitors; NRTIs = nucleoside analogue reverse transcriptase inhibitors; PIs = protease inhibitors; INIs = integrase inhibitors; CMV = cytomegalovirus. For categorical variables, differences between study groups were analyzed via c2 test and the 2-sided Fisher exact test (non-parametric). For continuous variables, normalization was studied with Kolmogorov-Smirnov test and differences between groups with ANOVA test (parametric) and Kruskal-Wallis H test (non-parametric). Statistical significance was defined as P < 0.05 (2-tailed).

Table 2: Lymphocytic subpopulations of the study patients.

TOTAL

HIV+

HIV+/HCV-

HIV+/HCV+

BASELINE n= 146

ENDPOINT n= 79

BASELINE n= 59

ENDPOINT n= 31

BASELINE n= 38

ENDPOINT n= 22

BASELINE n= 49

ENDPOINT n= 26

CD4+ T-cell count, cells/𝝁L *

763.0

(607.7-1009.5)

835.0

(652.0-1108.0)

804.0

(647.0-1034.0)

788

(683.0-1065.0)

762.2

(569.4-992.8)

819.5

(516.3-1042.5)

712.8

(565.8-1039.0)

893.0

(707.0-1254.0)

0.945

CD4+, % *

35.0

(31.0-41.0)

36.0

(31.95

37.0

(32.0-42.4)

37.0

(33.0-44.0)

35.0

(31.0-38.0)

31.8

(27.1-36.4)

33.8

(29.3-43.0)

37.0

(32.9-43.8)

0.930

Nadir CD4+, cells/𝝁L *

242.0

(165.5-340.5)

273.0

(199.8-425.3)

210.0

(80.0-249.0)

246.0

(121.0-320.3)

Nadir CD4+, % *

18.9

(11.9-26.5)

22.5

(17.0-28.0)

14.0

(7.0-20.0)

20.0

(13.5-30.7)

CD8+ T-cell count, cells/𝝁L *

889.0

(647.0-1230.3)

941.0

(701.0-1479.0)

880.0

(613.5-1434.5)

815.5

(667.0-1341.5)

922.5

(592.3-1277.5)

941.0

(894.0-1148.0)

858.0

(663.0-1077.0)

1175.5

(965.6-1712.5)

0.406

CD8+, % *

39.0

(33.0-44.8)

39.5

(35.5-45.2)

38.3

(33.0-46.4)

38.6

(33.9-42.2)

38.2

(31.6-43.1)

39.2

(31.6-50.7)

42.0

(36.0-45.2)

44.4

(40.1-50.6)

0.029

CD4:CD8 Ratio, *

0.92

(0.69-1.18)

0.88

(0.71-1.10)

0.99

(0.71-1.26)

0.98

(0.74-1.18)

0.92

(0.74-1.13)

0.78

(0.65-1.10)

0.86

(0.61-1.00)

0.865

(0.55-0.93)

0.562

Legend: HIV = Human Immunodeficiency Virus; HCV = Hepatitis C Virus; * = median (interquartile range); % = percentage. Normalization was studied with Kolmogorov-Smirnov test and differences between baseline and endpoint with Student’s T test (parametric). Statistical significance was defined as P < 0.05 (2-tailed).

Table 3: Clinical characteristics of the study population related to HCV-infection.

	TOTAL n=87	HIV+/HCV- n=38	HIV+/HCV+ n=49	p
HCV genotype	-	-	-	n.a.
GT1	-	-	28 (57.1)	-
GT2	-	-	1 (2.0%)	-
GT3	-	-	3 (6.1%)	-
GT4	-	-	12 (24.5%)	-
Unknown	-	-	5 (10.2%)	-
Fibrosis stage	-	-	-	0.090
F0-F1 (<6 kPa)	61 (49.6%)	24 (63.2%)	37 (75.5%)	-
F2 (6-9 kPa)	8 (6.5%)	0 (0.0%)	8 (16.3%)	-
F3 (>9-12kPa)	2 (1.6%)	0 (0.0%)	2 (4.1%)	-
F4 (>12kPa)	1 (0.8%)	0 (0.0%)	1 (2.0%)	-
Unknown	15 (17.2%)	14 (36.8%)	1 (2.0%)	-
HCV treatment n= 26	-	-		n.a.
Ledipasvir + Sofosbuvir	-	-	16 (61.5%)	-
Elbasvir + Grazoprevir	-	-	3 (11.5%)	-
Sofosbuvir + Daclatasvir	-	-	2 (7.7%)	-
Sofosbuvir + Velpatasvir	-	-	1 (3.8%)	-
Sofosbuvir + Simeprevir	-	-	1 (3.8%)	-
Sofosbuvir + Ledipasvir			1 (3.8%)
Viekirax + Exviera	-	-	1 (3.8%)	-
Unknown	-	-	1 (3.8%)	-

Legend: HIV = Human Immunodeficiency Virus; HCV = Hepatitis C Virus; n (%) = number (percentage); kPa = kilopascals. 𝞆2 test and the 2-sided Fisher exact test (non-parametric) were used to analyze differences between study groups. Statistical significance was defined as P < 0.05 (2-tailed).

Table 4: Dynamic of maturation and senescence in CD8+ T cells.

	HIV+			HIV+/HCV-			HIV+/HCV+
	BASELINE n= 59	ENDPOINT n= 31	p	BASELINE n= 38	ENDPOINT n= 22	p	BASELINE n= 49	ENDPOINT n= 26	p
CD8+ TN, %*	13.44 (2.25-23.84)	23.63 (13.94-31.27)	*0.007*	16.67 (13.28-21.14)	23.59 (16.65-24.78)	*0.002*	26.09 (10.27-38.14)	26.33 (14.76-37.42)	*0.021*
CD8+ TCM, %*	16.54 (12.61-36.91)	19.86 (13.29-27.85)	*0.031*	26.12 (19.59-36.26)	31.36 (21.04-36.13)	*0.018*	18.84 (14.19-28.33)	20.09 (15.12-26.10)	0.636
CD8+ TTM, %*	3.42 (2.37-6.31)	0.77 (0.58-1.74)	*<0.001*	6.06 (2.51-7.87)	0.90 (0.29-1.90)	*<0.001*	3.72 (2.74-4.78)	1.01 (0.35-2.30)	0.100
CD8+ TEM (CD28-), %*	3.76 (2.17-5.88)	1.21 (0.76-1.96)	*<0.001*	3.65 (1.94-5.44)	0.91 (0.52-1.57)	*<0.001*	3.24 (1.18-5.64)	1.06 (0.52-2.11)	*0.003*
CD8+ TEM (CD28+), %*	4.11 (2.81-5.23)	4.57 (3.05-6.48)	*<0.001*	4.25 (2.80-6.84)	5.79 (4.28-6.87)	*<0.001*	2.76 (1.61-3.95)	3.72 (2.68-5.47)	*<0.001*
CD8+ TEMRA, %*	10.74 (6.38-25.92)	15.55 (7.15-22.15	*<0.001*	6.11 (4.21-8.62)	4.68 (2.19-10.56)	*0.017*	8.83 (3.66-19.20)	12.15 (6.46-15.92)	*<0.001*

Legend: HIV = Human Immunodeficiency Virus; HCV = Hepatitis C Virus; * = median (interquartile range); % = percentage; TN = naïve T cells; TCM = central memory T cells, TTM = transitional memory T cells; TEM= effector memory; TEMRA = terminally-differentiated effector memory T cells; baseline = time of the study when HIV+/HCV+ patients had never been treated for hepatitis; endpoint = time of the study when HIV+/HCV+ patients had cleared HCV by treatment with direct-acting antivirals. Differences between baseline and endpoint for the different study groups were calculated using a beta inflated mixed effect regression model. Statistical significance was defined as p<0.05 (2-tailed).

Table 5: Dynamic of maturation and senescence in CD4+ T cells

	HIV+			HIV+/HCV-			HIV+/HCV+
	BASELINE n= 59	ENDPOINT n= 31	p	BASELINE n= 38	ENDPOINT n= 22	p	BASELINE n= 49	ENDPOINT n= 26	p
CD4+ TN, %*	22.94 (12.76-33.21)	26.72 (20.36-35.08)	*0.005*	27.06 (15.38-36.60)	29.01 (20.38-32.15)	0.105	40.44 (25.76-47.09)	32.30 (22.52-37.51)	0.067
CD4+ TCM, %*	52.74 (43.14-70.46)	53.48 (47.21-60.36)	0.051	53.74 (46.74-60.06)	61.63 (54.12-70.89)	0.092	40.43 (32.97-48.11)	53.13 (44.86-58.13)	0.604
CD4+ TTM, %*	1.69 (0.80-2.50)	0.02 (0.01-0.35)	*0.008*	2.94 (0.52-5.77)	0.02 (0.01-0.8)	*0.015*	0.79 (0.18-1.95)	0.06 (0.01-0.55)	0.246
CD4+ TEM TH1, %*	0.77 (0.37-1.52)	0.58 (0.35-1.48)	0.797	0.41 (0.22-1.27)	0.20 (0.14-0.37)	*0.037*	0.46 (0.20-1.29)	0.31 (0.19-0.60)	0.736
CD4+ TEM TH2, %*	8.05 (6.44-10.60)	6.32 (4.50-9.32)	*0.034*	9.07 (5.22-13.65)	5.32 (3.81-6.71)	*0.049*	6.33 (3.72-9.41)	5.45 (3.07-7.19)	0.959
CD4+ TEMRA, %*	0.66 (0.11-2.40)	1.11 (0.30-2.71)	0.989	0.17 (0.04-1.59)	0.15 (0.02-0.65)	0.595	0.66 (0.09-1.33)	0.52 (0.21-0.86)	*0.024*

Legend: HIV = Human Immunodeficiency Virus; HCV = Hepatitis C Virus; * = median (interquartile range); % = percentage; TN = naïve T-cells; TCM = central memory T-cells, TTM = transitional memory T-cells; TEM= effector memory; TEMRA = terminally-differentiated effector memory T cells; baseline = time of the study when HIV+/HCV+ patients had never been treated for hepatitis; endpoint = time of the study when HIV+/HCV+ patients had cleared HCV by treatment with direct-acting antivirals. Differences between baseline and endpoint for the different study groups were calculated using a beta inflated mixed effect regression model. Statistical significance was defined as p<0.05 (2-tailed).

No competing interests reported.

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T cell maturation and senescence after HCV cure in HIV-HCV coinfected patients: a prospective study

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