Characterization of Specific Responses to Three Models of Viral Antigens in Immunocompetent Older Adults

Characterization of Specific Responses to Three Models of Viral Antigens in Immunocompetent Older Adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Characterization of Specific Responses to Three Models of Viral Antigens in Immunocompetent Older Adults Beatriz Rioseras, Eva Bueno-García, Alejandra García-Torre, Rocío López-Martínez, and 24 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4735076/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Dec, 2024 Read the published version in Immunity & Ageing → Version 1 posted 11 You are reading this latest preprint version Abstract Background Memory responses to the antigens that an individual encounters throughout life may vary with the intensity and duration of antigen contacts or even changes in immune status over time. This work aims to characterise specific responses to chronic CMV, seasonal influenza and novel SARS-CoV-2 infections in immunocompetent individuals over 60 years of age. Specific cellular and humoral responses were identified by IFN-γ and granzyme-B released by ELISpot and antibody level measurement. T lymphocyte subpopulation phenotypes were characterized by flow cytometry. Results Cellular and humoral responses to these viruses were detected in almost all patients. Influenza and SARS-CoV-2 cellular responses were positively correlated. There was no significant correlation of CMV with influenza or SARS-CoV-2 responses although both were consistently lower in CMV-seropositive patients. CMV responses were negatively correlated with the levels of the least differentiated subsets of T lymphocytes, and positively correlated with the most differentiated ones, contrary to what happened with the influenza responses. Nevertheless, SARS-CoV-2 cellular responses were negatively correlated with the most differentiated CD8 + T lymphocytes, while humoral responses were negatively correlated with the least differentiated T lymphocytes. Responses to the three viruses were correlated with a Th1/Th2/Th17 balance in favour of Th1. Conclusions Results indicate that memory responses differ depending on the durability of the antigen stimulus. Cellular responses to novel pathogens resemble those generated by seasonal but not chronic antigens. Subpopulation distribution and the level of specific T lymphocytes against previous pathogens could be used as immunocompetent status biomarkers in older adults reflecting their ability to generate memory responses to new pathogens. Immunosenescence Anti-viral immune memory Cytomegalovirus Influenza SARS-CoV-2 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 BACKGROUND Contact with antigens throughout an individual’s life leads to the generation of a specific memory cellular and humoral immune response. Two consequences of this process are a reduction in the number of naïve T lymphocytes and an increase in the abundance of memory cells. In the case of viruses, the type of infection they cause, and the stage of life when it occurs, may determine the type and intensity of the memory generated. The effect will be more pronounced in older adults, whose memory T repertoire is more conditioned by successive reactivations of the viruses that cause chronic infections, or by repeated immunizations, through infection or vaccination, against seasonal viruses. Older adults may be more susceptible to infections by viruses and other pathogens as a consequence of the changes in the immune system that accompany aging, known as immunosenescence. During aging it also appears a chronic low-grade inflammation known as inflammaging ( 1 ). Some of the changes that occur in the T lymphocyte compartment during immunosenescence have been associated with clinical consequences such as the generation of weaker vaccine responses, a reduction in the ability to secrete antibodies and a defective immune response to viruses, mainly those to which there has been no previous exposure ( 2 ). The consequences of viral infection vary depending on the virus characteristics, the viral lifecycle and the ability of the host’s immune system to eliminate the infection, in which age is an important factor. Thus, some viral infections cause acute disease after a short incubation period, while others can remain in a latent state or cause chronic infections or diseases. Chronic cytomegalovirus (CMV), seasonal influenza and the novel SARS-CoV-2 infection are examples of three distinct models of viral infection, all of which have important implications for older adults and can induce different immune memory mechanisms. CMV is a DNA herpesvirus that is ubiquitous in human populations worldwide. As is typical of all herpesviruses, CMV has biological properties of latency and reactivation, whereby once an individual has been infected, the virus remains latent as a chronic infection for the rest of their life ( 3 ). The important contribution of CMV infection to immunosenescence in older adults is well known ( 2 , 4 , 5 ), but it is also of significance in immunosuppressed situations such as in kidney transplant, in onco-haematological patients ( 6 , 7 ), and in some chronic diseases such as chronic heart failure and renal disease ( 8 – 10 ). Conversely, influenza is a highly contagious, annual respiratory illness caused by several RNA viruses belonging to the Orthomyxoviridae family. Most people come into contact with these viruses several times during their life and are able to eliminate them without any complication. However, these viruses can increase morbidity and mortality in some groups of individuals, particularly the immunocompromised, as older adults tend to be. It is well documented that older adults are at higher risk of developing severe influenza disease and serious complications than are those in younger age groups ( 11 , 12 ). Vaccination is the main preventive measure against influenza infection, and it is recommended that chronically ill individuals and adults over the age of 65 years be vaccinated annually ( 13 , 14 ). SARS-CoV-2 is a very recently emerged coronavirus that infects humans. It was first detected in 2019 as the causative agent of the current coronavirus disease 2019 (COVID-19) pandemic. It differs significantly from previously identified coronaviruses and offers an opportunity to study the immune response generated by individuals to a new viral antigen. COVID-19 disease follows a course with very diverse clinical presentations and symptoms. The severity of this infection is also highly variable, ranging from completely asymptomatic, through very mild, to extremely serious symptoms ( 15 ). The main risk factors include age, obesity, hypertension, diabetes mellitus, heart disease and lung disease. In the case of age, patients aged above 60 years were found to be around five times more likely to die after developing symptoms than patients aged between 30–59 years ( 16 ). Our group previously reported that specific immunity to SARS-CoV-2 is preserved in older surviving adults. The aim of the current study was to characterise and compare the specific cellular and humoral responses to these three different models of viral infection (chronic, repeated and new) in immunocompetent older adults. The ultimate goal is to find new biomarkers of the immunocompetence status of older adults, based on the characterization of responses against known previous infections that could reflect their ability to generate specific memory responses to new pathogens. METHODS Donors Fifty-nine volunteers with a positive PCR for SARS-CoV-2 were recruited by the Emergency Service of the Hospital Universitario Central de Asturias (Oviedo, Spain). Inclusion criteria for this study were age over 60 years old and their SARS-CoV-2 infection had been asymptomatic or very mildly symptomatic not requiring admission to hospital. Peripheral blood samples were drawn for analysis from all participants an average of 5 months after being infected with SARS-CoV-2 for the first time between March and May 2020. Informed consent was obtained from all volunteers before they participated. Haemogram and biochemical characteristics Counts of leukocytes, overall and separately for lymphocytes, monocytes and neutrophils, were obtained from donors’ whole blood, anticoagulated with EDTA, by fluorescent flow cytometry and hydrodynamic focusing in a Sysmex XT-2000 i analyser (Sysmex, Kobe, Japan) following the manufacturer’s specifications. The levels of D-Dimer and NT-proBNP were measured in donor serum by turbidimetric immunoassay using an ACL TOP 750 analyser (Werfen, Barcelona, Spain), and by electrochemiluminescence using a COBAS e801 analyser (Roche, Basel, Switzerland), both following the manufacturer’s specifications. Immunophenotyping For flow cytometry analysis of lymphocyte subpopulations, peripheral blood cells were surface-stained with a combination of antibodies appropriate for the cell population analysed. T/B/NK populations were analysed with anti-CD45 (FITC), anti-CD56+16 (RD1), anti-CD19 (ECD) and anti-CD3 (PC5) using the AQUIOS Tetra-2+ Monoclonal Antibody Reagents Panel (Beckman-Coulter, Brea, CA, USA). The naïve cells and the different maturation stages of memory CD4 + and CD8 + T lymphocytes were analysed using anti-CD3 (FITC), anti-CD8a (PE), anti-CD45 (PerCP), anti-CD27 (PECy7), anti-CCR7 (APC), anti-CD45RA (APCFire), anti-CD28 (BV) (BioLegend, San Diego, CA, USA), and anti-CD4 (ECD) (Beckman-Coulter). This staining made it possible to discriminate the different subpopulations of CD4 + and CD8 + T lymphocytes: naïve (N) (CD45RA+CCR7+), central memory (CM) (CD45RA-CCR7+), effector memory (EM) (CD45RA-CCR7-) and terminally differentiated effector T cells re-expressing CD45RA (EMRA) (CD45RA+CCR7-). The absolute frequency of cells per millilitre and the percentage of CD4 + or CD8 + T lymphocytes of these subsets of cells were measured. In the EM subpopulation it was possible to detect several maturation stages: less differentiated effector memory cells that are memory-like, i.e., EM1 (CD27+CD28+) and EM4 (CD27-CD28+); and the more differentiated effector memory cells that are effector-like, i.e., EM3 (CD27-CD28-) and EM2 (CD27+CD28-). The EM2 subtype is only present in CD8 + T lymphoyctes but is absent from CD4+ T lymphocytes. Functional differentiation of memory CD4 + T lymphocytes was studied with anti-CXCR3 (AF488), anti-CD4 (ECD), anti-CCR6 (PC7) (Beckman-Coulter), anti-CCR7 (PerCP), anti-CD45RA (APCFire) and anti-CD28 (BV) (BioLegend), which were able to detect various Th subpopulations: Th1 (CCR6+CXCR3+), Th2 (CCR6-CXCR3-), Th17 (CCR6+CXCR3-) and Th1.17 (CCR6-CXCR3+). These different stains were performed with 100 µL of whole blood anticoagulated with EDTA from the donors. Samples were stained with the corresponding combination of labelled monoclonal antibodies for 20 minutes at room temperature. Red blood samples were lysed for 10 minutes at room temperature with FACS Lysing Solution (BD Biosciences), washed in PBS and analysed using Kaluza software in a Navios cytometer (Beckman-Coulter). Appropriate isotype control mAbs were used for marker settings. Specific T cellular response measurement ELISpot assays were performed to quantify IFN-g and granzyme B-producing specific T cells against CMV, influenza and SARS-CoV-2 viruses. Peripheral blood mononuclear cells (PBMCs) were isolated from peripheral blood anticoagulated with EDTA by centrifugation on Ficoll–Hypaque gradients (Lymphoprep, Nycomed, Oslo, Norway). PBMCs (2.5 x 10 5 /well) were then cultured for 18 h on a filter plate (Millipore, Billerica, MA, USA) previously coated with anti-IFN-g or anti-granzyme B antibodies (15 μg/mL) (Mabtech, Nacka Strand, Sweden) and cultured in medium alone for negative control, in the presence of anti-CD3 (1 ng/mL) for positive control, and with peptides from the different viruses. The peptide pool included pp50, pp65, IE1, IE2 and envelope glycoprotein B antigens from CMV (2 μg/mL) (Mabtech), the influenza virus quadrivalent vaccine used in the 2019-2020 campaign (1/100 dilution) or S1, S2 and N SARS-CoV-2 peptide pools (2 μg/mL) (Mabtech). IFN-g and granzyme B produced by T lymphocytes under specific stimulation were captured and detected by biotinylated anti-IFN-g and anti-granzyme B antibody (1 μg/mL) (Mabtech), respectively, followed by streptavidin–horseradish peroxidase (Mabtech). Spots were developed using tetramethylbenzidine (TMB) substrate (Mabtech) and counted with ImageJ software. Results were considered to be negative when there were ten or fewer dots. The results were expressed as the frequency of IFN-g or granzyme B producer T lymphocytes per 10 6 T cells. Humoral response measurement Levels of anti-CMV antigen antibodies (CMV-IgG) were detected in serum from the donors by chemiluminescence analysis using the LIAISON® CMV IgG II assay (DiaSorin, Milan, Italy). CMV seropositivity was defined as CMV-IgG > 14 U/mL. Anti-influenza virus antibodies in serum obtained from individuals were measured semiquantitatively by ELISA as previously described (18), with some modifications (19). The OD values of individual samples were compared against a calibration curve made by serial dilutions of the same internal control serum for all the experiments. The detection limit was 0.5. Anti-SARS-CoV-2-specific IgG antibodies were quantified with a Human anti-SARS-CoV-2 (S) IgG ELISA kit and a Human anti-SARS-CoV-2 (N) IgG ELISA kit (Fine Test, Wuhan, China), following the manufacturer’s specifications. Statistical analysis and graphical presentation Pearson’s chi-squared test and Fisher’s exact test were used to determine whether there were any significant associations between pairs of qualitative variables. The Kolmogorov–Smirnov test was used to determine whether quantitative variables were normally distributed. Haemogram and biochemical parameters data that were measured before and after the SARS-CoV-2 infection were analysed using Student’s t test for paired samples or Wilcoxon’s signed‐rank test when the data were normally or non-normally distributed, respectively. The cellular responses to the three viral antigens were compared with a general linear model for repeated measures using Bonferroni-corrected post hoc pairwise comparisons. Group differences between quantitative variables were assessed with Student’s t test or the nonparametric Mann–Whitney U test when the data were normally or non-normally distributed, respectively. Correlations between variables were assessed using the nonparametric Spearman test (ρ). Statistical analyses were carried out with SPSS 17.0 (SPSS Inc., Chicago, IL) and values of p<0.05 were considered significant. All graphs were created with GraphPad Prism (version 8.0.2). RESULTS Features of studied group All the 59 donors recruited were more than 60 years old, with a mean age of 72.15 years (SD: 12 years), of whom 39 were female (66%) and 20 were male (34%). Details of underlying diseases (64.4% of the patients) and symptoms of patients that had mild symptomatic SARS CoV-2 infection (61%) are summarised in Table 1. Laboratory characteristics, such as the level of the leukocyte subsets, D-Dimer and NT-proBNP, were also measured in most patients. Regarding influenza immunology status, 33 patients had received the influenza vaccine some months before the samples were collected, while 26 had not been vaccinated in the most recent vaccination campaign. Forty-nine patients were CMV-seropositive and 10 were CMV-seronegative (Table 1). Table 1 . Participant characteristics Variables Patients (n=59) AGE ± SD (years) 72.2 ± 12 FEMALES 39 (66) Underlying disease 38/56 (64.4) Hypertension 25 (65.8) Diabetes mellitus 13 (34.2) Asthma 7 (18.4) Heart disease 14 (36.8) Renal disease 4 (10.5) Smoker 3 (7.9) Drinker 4 (10.5) ALTERED D-DIMER (>500 ng/mL) 18/49 (36.7) ALTERED NT-proBNP (>300 pg/mL) 9/58 (15.5) INFLUENZA-VACCINATED 33 (55.9) CMV-SEROPOSITIVE 49 (83) Symptomatic of COVID-19 disease 36/56 (61) Fever 24 (66.7) Cough 24 (66.7) Dyspnoea 9 (25) Chest pain 5 (13.9) Ageusia 9 (25) Anosmia 11 (30.6) Mean days with symptoms ± SD 3.3 ± 2.7 Numbers in brackets represent percentages. Haemogram and biochemical characteristic recovery after SARS-CoV-2 infection Since recruited patients had recently been infected with SARS-CoV-2, we wanted to determine whether some of the characteristics that are known to be altered during this infection had already returned to normal. As is well known, SARS-CoV-2 infection produces lymphopenia, as was seen in five of the patients for whom these data were available during the infection process (Supplementary Figure 1). We wanted to establish whether patients showed normal levels of leukocytes when the study began. It was possible to obtain the basal haemogram information from 2 months to 4 years before the SARS-CoV-2 infection in 52 of the 59 patients. When the levels of the different leukocyte populations were compared before and after the infection, no statistically significant differences, or statistically significant but not biologically significant differences, were seen in the total leukocytes (Wilcoxon test, p<0.01), lymphocytes (paired-samples t test, p<0.01), monocytes (Wilcoxon test, p0.05) (Figure 1A). SARS-CoV-2 infection appeared not to affect leukocyte populations substantively once patients had completely recovered. We now consider the biochemical characteristics that are known to be altered in SARS-CoV-2-infected patients and are considered indicators of a more severe COVID-19 disease. We measured D-Dimer and NT-proBNP levels in serum samples of 49 and 58 of the 59 patients, respectively. Eighteen and nine individuals had an elevated level of D-Dimer (>500ng/mL) and NT-proBNP (>300 pg/mL), respectively, when the study began (Table 1). This finding was not associated with the patients’ gender or COVID-19 symptomatology. Elevated levels of both factors were more likely to occur in older patients, since individuals with altered characteristics were significantly older than those whose parameters were within the normal range (Student’s t test, p<0.05, for both) (Figure 1B). With respect to individuals’ existing underlying pathologies a higher prevalence of altered NT-proBNP was observed in patients who were suffering from an underlying cardiopathy (Pearson’s chi-squared test, p<0.05) (Figure 1C). Cellular and humoral responses to the three virus models Cellular and humoral memory responses to the three viral antigens were determined. Cellular responses were measured by IFN-g ELISpot and granzyme B ELISpot. Humoral responses were measured as the level of specific antibodies against the different viruses in sera. It was not possible to obtain all results for all patients, especially in the case of granzyme B ELISpot since not enough cells could be isolated from some patients. Complete results of the three measurements were achieved in 74.6% of patients for CMV, 84.7% for influenza and 83% for SARS-CoV-2 of the 59 patients enrolled in the study. No responses were obtained for some measurements, especially cellular memory measured by granzyme B ELIspot (Figure 2A). No cellular or humoral response was detected in 17% of CMV (corresponding to seronegative CMV patients) and 3% of SARS-CoV-2 cases. However, most patients showed both cellular (with at least one of the two measurements obtained) and humoral responses to CMV, influenza and SARS-CoV-2 viruses (83%, 83% and 85%, respectively) (Figure 2B). Isolated cellular responses with no accompanying humoral response were seen for influenza in 17% of the patients (Figure 2B). Conversely, an isolated humoral response with no detectable cellular response was observed for SARS-CoV-2 in 12% of the patients. Of these, 14% showed anti-N antibodies and the remaining 86% had both anti-N and anti-S antibodies. Likewise, 96% of the patients with humoral and cellular responses had both anti-N and anti-S antibodies, while the other 4% had isolated anti-N (2%) or anti-S (2%) antibodies (Figure 2B). In all cases, positive cellular responses occurred mainly at the expense of IFN-g-ELISpot measurement or both IFN-g and granzyme B ELIspot. Just in the case of cellular responses to SARS-CoV-2, 5% of the patients showed granzyme B-ELISpot-positive results with negative IFN-g-ELISpot. (Figure 2B). a. Anti-CMV responses Eighty three percent of the patients were CMV-seropositive. Distributions of the different response measurements against CMV are represented in Figure 3A. As mentioned above, humoral and cellular responses to CMV matched perfectly, whereby all seronegative patients were also negative for cellular responses, while the seropositive group of patients showed cellular responses. There was a positive correlation in the seropositive CMV patients between the two cellular responses measured as IFN-g and granzyme B-producer-specific T lymphocytes (Spearman test; r=0.6, p<0.01). However, no significant correlation was observed between the anti-CMV cellular and humoral responses (Supplementary Figure 2A). b. Anti-influenza responses The influenza-vaccinated status of all patients was known: 55.9% of them had been vaccinated in the most recent vaccination campaign. Nevertheless, it can be assumed that all the patients, vaccinated and unvaccinated, had been exposed to this seasonal virus during their lives. In fact, the cellular memory response to influenza (IFN-g and/or granzyme-B-producing T lymphocytes) was detected in all the patients. Regarding the humoral response, 94% of vaccinated and 69% of unvaccinated patients had antibodies against influenza at a level above our detection threshold. The great majority (80%) of the 17% patients who showed cellular responses without antibodies to the influenza vaccine were unvaccinated (Figure 2B). As expected, the group of vaccinated individuals had a significantly higher specific cellular memory response (Mann–Whitney test, p<0.05 for IFN-g and p<0.01 for granzyme B producer T lymphocytes per 10 6 T lymphocytes) and anti-influenza antibody titre (Mann–Whitney test, p<0.01) compared with the unvaccinated group (Figure 3B). The two different measurements of cellular response (IFN-g and granzyme B production) and the values for IFN-g-producer T lymphocytes and humoral response against influenza virus were both positively correlated (Spearman test; r=0.6, p<0.01 and r= 0.3, p<0.05, respectively) (Supplementary Figure 2B). c. Anti-SARS-CoV-2 responses All the patients had been infected with SARS-CoV-2 for the first time and an adequate response to the virus was expected as they were asymptomatic or suffered only very mild symptoms. As described above, cellular or humoral responses to SARS-CoV-2 virus were observed in 97% of the cases (85% showed both types of response, while 12% presented only a humoral response). No response was detected in two patients studied by any of the methods used (Figure 2B). Distributions of the different response measurements against SARS-CoV-2 are represented in figure 3C. As described above, some biochemical characteristics related to the severity of the SARS-CoV-2 infection, D-Dimer and NT-proBNP levels were measured. No significant differences were found in the responses to SARS-CoV-2 between patients with and without altered parameters (Supplementary Figure 3). Positive correlations were noted between cellular responses, measured as specific IFN-g-producer T lymphocytes, and humoral responses to SARS-CoV-2. The correlation was higher for anti-N antibodies (Spearman test, r=0.5, p<0.01) than for anti-S antibodies (Spearman test; r=0.3, p<0.05). As expected, the two humoral response measurements were significantly positively correlated (Spearman test, r=0.5, p<0.01). However, no significant correlation was observed between the two cellular response measurements (Supplementary Figure 2C). Relation between viral antigen model responses Comparing the cellular responses to the three viruses showed that the specific anti-CMV cellular response was stronger, in the CMV-seropositive group of patients, than the cellular response to the influenza virus, and both were stronger than the response to SARS-CoV-2, particularly when the cellular response was measured with IFN-g ELIspot, since the differences between all the three viral antigens responses were statistically significant (Bonferroni test, p<0.01). When measured by Granzyme B ELIspot, there were significant differences between CMV and SARS-CoV-2 (Bonferroni test, p<0.05) and between influenza and SARS-CoV-2 (Bonferroni test, p<0.01) but not between CMV and influenza in either of the unvaccinated and vaccinated patient groups (Figure 4). Humoral responses could not be compared because they were measured in different ways. We found a significant positive correlation between cellular responses to influenza and SARS-CoV-2 for IFN-g-producer T lymphocytes (Spearman test; r=0.4, p<0.01) and granzyme B-producer T lymphocytes (Spearman test; r=0.4, p<0.05) although these were not apparent at the humoral level (Figure 5A). On the other hand, there were no significant correlations of any of the measurements of the responses between CMV and SARS-CoV-2 or between CMV and influenza. However, comparing influenza and SARS-CoV-2 specific responses in seropositive-CMV and seronegative-CMV patients showed them to be consistently lower in CMV-seropositive than in CMV seronegative patients, in both cases (Figure 5B and 5C). This comparison was not significant probably because there were too few CMV-seronegative individuals in the sample for a difference of that magnitude to be significant. Characterization of the responses to the three antigen models in relation to the T lymphocyte phenotype Immunosenescence may be related to the intensity of responses to the different virus infections. The immunophenotype of T lymphocytes by their degree of maturation (naïve/memory) and functional differentiation of CD4 + T lymphocytes (Th1/Th2/Th17) and their correlations with the viral responses were analysed. a. CMV Agreeing with what is already well known and stablished, differences in the distribution of the T lymphocyte subpopulations were observed between CMV-seropositive and CMV-seronegative individuals (Supplementary Figure 4A). CMV-seronegative patients had a significantly lower proportion of CD4 + EM3 than did CMV-seropositive individuals (median: 0.03% vs 6.8%; Mann–Whitney test, p<0.01). However, the median proportions of CD4 + CM and CD8 + N were significantly higher in CMV-seronegative than in CMV-seropositive patients (30.4% vs 22.6%; Mann–Whitney test, p<0.05, and 16.2% vs 7.1%; Mann Whitney test, p<0.01, respectively) (Supplementary Figure 4A). With respect to the distribution of the functional subpopulations of CD4 + memory T lymphocytes, there was a significantly lower mean percentage of Th1 in CMV-seronegative than in CMV-seropositive patients (29.2% vs 39.2%; Student’s t test, p<0.01) (Supplementary Figure 4B). Considering the CMV-seropositive group of patients, the cellular response (IFN-g and/or granzyme B-producing T lymphocytes) was negatively correlated with CD4 + N, CD4 + EM1 and CD8 + N while there was a significant positive correlation with CD4 + EM4. Regarding the humoral responses to CMV, there were negative correlations with CD4 + CM, CD4 + EM1, CD8 + N CD8 + CM and CD8 + EM1. However, a significant positive correlation was seen with the CD4 + EM4, CD4 + EM3, CD4 + EMRA, CD8 + EM3 and CD8 + EMRA subsets (Figure 6A). In the case of the functional differentiation of memory CD4 + T lymphocytes, the humoral response to CMV was positively correlated with Th1 type and negatively correlated with Th2 and Th17 (Figure 6B). b. Influenza It is expected that recently vaccinated patients are a more homogeneous group with respect to the immune responses generated against influenza seasonal pathogen. In vaccinated patients, the cellular memory responses to the influenza virus (IFN-g and/or granzyme B-producing T lymphocytes) were negatively correlated with CD4 + EM3, CD8 + EM3 and CD8 + EMRA cells, and positively correlated with CD4 + EM4 and CD4 + EM1 cells. No significant correlations were noted between the level of antibodies and the distribution of any of the subpopulations (Figure 6A). Regarding the functional differentiation of memory CD4 + T lymphocytes, the cellular response measured as IFN-g-producer-specific T lymphocytes was negatively correlated with the Th2 subpopulation but positively correlated with the Th1.17 subpopulation (Figure 6B). c. SARS-CoV-2 T lymphocyte cellular responses to SARS-CoV-2 (IFN-g and/or granzyme B-producing T lymphocytes) were correlated negatively with CD4 + EM4 and positively with CD4 + EMRA. Regarding CD8 + T lymphocyte responses, there was a negative correlation between cellular responses and the CD8 + EM3 and CD8 + EMRA subsets. Analysis of the humoral responses revealed that the level of anti-S antibodies was negatively correlated with the CD4 + N, CD4 + CM, CD4 + EM1 and CD8 + N subsets, whereas anti-N antibodies were not significantly correlated with the distribution of any of the subpopulations (Figure 6A). In terms of the functional differentiation of memory CD4 + T lymphocytes, the humoral response, measured as anti-S antibodies, was negatively correlated with the Th2 and Th17 subpopulations. The negative correlation with Th17 lymphocytes was also seen at the cellular level (Figure 6B). DISCUSSION In this work we have characterised the cellular and humoral immunoresponses to three viral infection models in immunocompetent older adults. It is well known that gradual changes that trigger the deterioration of the immune system occur as an individual ages. These immunosenescence processes are also accompanied by a chronic low-grade inflammation, known as inflammaging, which is increased by some factors, CMV infection being one of the most widely studied ( 4 , 5 ). All these changes associated with aging affect innate and especially adaptive immunity, in which T lymphocytes have a crucial role in controlling the mechanisms of viral infections ( 1 ). All the patients studied in this work were older adults that had recently been infected with SARS-CoV-2 for the first time, but who had been asymptomatic or had experienced only very mild symptoms. This group of patients could be considered less affected by immunosenesce than indivuals in the same range of age since the risk of severe illness from COVID-19 is well known to increase with age and older adults are more likely to have poor outcomes ( 20 ). In addition to not presenting clinical outcomes related to SARS-CoV-2 infection, the typical laboratory abnormalities associated with this infection, such as leukopenia or elevated levels of D-Dimer and NT-proBNP serum biomarkers, had already returned to normal in the majority of the patients by the time the study began ( 21 ). The elevated levels of the biochemical factors, D-Dimer and NT-proBNP, detected in some of the patients studied are related to age and the presence of underlying cardiac pathology, as reported elsewhere ( 22 , 23 ), rather than to the severity of the symptoms or the strength of the response to SARS-CoV-2. For these reasons, there was no bias regarding the clinical status of the patients in this study. We know which individuals had been vaccinated in the previous influenza vaccination campaign, but information about the history of influenza infections or previous vaccinations was not available, which is a limitation of the study. The individuals studied therefore form a heterogeneous group with respect to influenza virus contact during their lives. Vaccinated individuals make up a more homogeneous group with respect to the immune memory that they would have developed to this seasonal pathogen. However, it is important to bear in mind that the immunoresponse generated in this group of patients is almost certainly not only due to the most recent vaccination received since it is very likely that they had been in contact with the virus at other times during their lives. Specific adaptive cellular responses to viruses are mainly orchestrated by T lymphocytes, especially by cytotoxic CD8 + T lymphocytes. In this study cellular responses are measured by detecting IFN-γ and granzyme B release after specific antigen stimulation. IFN-γ is produced by T lymphocytes, mainly CD4 + Th1 and CD8 + , while granzyme B is basically produced by CD8 + T lymphocytes ( 24 , 25 ). The humoral response, which was also measured in these patients, was also involved in these infections through the production of neutralizing antibodies that act against the virus ( 26 ). CMV-seronegative patients, as expected, did not show cellular responses neither as they never have been infected by CMV. There were also two individuals in whom no cellular or humoral responses were detected against SARS-CoV-2. The lack of response of these two patients was surprising since all 59 individuals had been diagnosed with SARS-CoV-2 infection some months before. One possible explanation is that the RT-PCR used to diagnose SARS-CoV-2 infection has a specificity of greater than 95% ( 27 ), meaning that up to 5% of results could be false-positives. However, all the individuals studied were positive at least twice for the RT-PCR diagnostic test, making it unlikely that these two people were false-positives cases. On the other hand, it is important to bear in mind that all the individuals studied had had just one encounter with the SARS-CoV-2 virus, so it is possible that, in some cases, this stimulus was not strong enough to elicit a detectable memory response. This lack of response has been described before, especially in patients whose infection caused mild or no symptoms ( 17 , 28 ), as is the case of the patients studied in this work. With the exception of these two cases, all the patients showed cellular and/or humoral responses to the three viruses. The responses generated are known to depend largely on the conditions of antigen exposure and persistence ( 29 , 30 ), which could explain some of the differences found between the responses to the three viruses. CMV is a chronic virus whose exposure persists over time because the immune system is exposed to the antigen at each reactivation ( 30 , 31 ). This explains why responses to this virus in CMV-infected individuals were the strongest and the most consistent. Conversely, the influenza virus is a seasonal, rather than a chronic virus, exposure to which is frequent but not persistent over a lifetime, and the antigens to which people are exposed are continuously changing ( 13 ). In this case, as expected, most of the patients recently vaccinated against influenza developed detectable humoral and cellular responses. Many of the unvaccinated people showed a cellular response but no detectable humoral response, possibly because most of them had not been in contact with the viral antigen for a longer time than the individuals vaccinated in the most recent campaign; it is well known that antibodies have a shorter live than cellular memory ( 32 , 33 ). In the case of SARS-CoV-2 responses, some individuals had anti-SARS-CoV-2 antibodies but no detectable specific T cellular response. As mentioned above, asymptomatic or mild disease triggers a less intense memory response. It is likely that in this small group of patients the single encounter with the SARS-CoV-2 antigen enabled memory T cells to develop, although not to detectable levels. This is consistent with what happens in other coronavirus infections, such as SARS and MERS, in which higher levels of specific T cells against the virus were found in patients with more severe symptoms ( 34 ). The persistence of exposure to the three viruses differs, with chronic CMV being the most and SARS-CoV-2 the least persistent. This concurs with the results of the comparison of the strengths of cellular responses made in this study. However, it is also important to bear in mind that the antigenic stimuli used to measure the cellular responses could be immunogenically differently. Beside this, the correlations between the different virus responses reflect the greater similarity of the responses to the novel SARS-CoV-2 virus to that of influenza than to the response to chronic CMV. To investigate this in greater depth, the different responses were characterized in more detail taking into account the immunophenotyping of the lymphocyte subpopulations. CMV is a chronic virus which infection is characterized by the generation of a more differentiated T lymphocyte phenotype, due to the persistent exposure of the immune system to this virus over time once the individual has been infected ( 9 , 35 ). This effect was also seen in our patients whereby CMV-seropositive individuals tended to have a higher frequency of highly differentiated T lymphocytes and a lower frequency of naïve T lymphocytes than CMV-seronegative patients. Consistent with this, it was observed that the stronger the responses were to CMV the more abundant were T lymphocytes with a differentiated phenotype. Many studies support this finding. CMV infection triggers the activation of B, T CD4 + and T CD8 + lymphocytes, and the persistent production of CMV virus results in a continuous and peribiomic stimulation of these cells, especially T CD8 + ( 4 , 36 ). Each viral reactivation cycle generates a subset of CMV-specific T lymphocytes, which thereby reduces the T lymphocyte repertoire. The majority of these CMV-specific T lymphocytes are known to be terminally differentiated, corresponding to an exhausted and immunosenescent T cell phenotype ( 4 , 37 ). This situation of continuous immune stimulation also favours the pro-inflammatory chronic state that typically accompanies aging ( 5 , 38 ). Otherwise, our results suggest that a better cellular response to the influenza virus is associated with a less T lymphocyte-differentiated phenotype. This is consistent with findings reported in young mice infected with the influenza virus, whose CD4 + T lymphocyte compartment is comprised mainly of naïve cells that rapidly proliferate and differentiate into influenza-specific effector subsets that allow the clearance of the virus ( 39 ). These correlations were seen at the cellular response level in vaccinated individuals, but there was no correlation with the humoral response in these patients. This might be because recently vaccinated patients, as expected, given the purpose of vaccination ( 13 ), had elevated levels of antibodies against influenza at the time of the study, maybe independently of their T lymphocyte phenotype. Consistent with the correlations of the responses seen, SARS-CoV-2 showed mostly similar results to those of influenza with respect to cellular responses, especially CD8 + T lymphocytes ones, provoking stronger cellular responses when less-differentiated T CD8 + lymphocyte phenotypes were predominant. However, humoral responses to the SARS-CoV-2 virus (especially levels of anti-S antibodies) were negatively correlated with the abundance of naïve and less-differentiated memory T lymphocytes, similar to what happens in CMV. This could be because individuals with a more senescent immune system are less capable of generating an adequate cellular response —the main type of response for controlling viral infections— to this new viral antigen. Therefore, in these cases, the SARS-CoV-2 infection could persist for longer and could allow a stronger humoral response to be generated before the infection is resolved. This explanation is consistent with that previously proposed by Wu et al., who reported that severe SARS-CoV-2 patients had higher IgG-S and IgG-N titres ( 40 ), and with our earlier work, which determined that although there were no significant differences in cellular responses between hospital-admitted and non-admitted patients, anti-S and anti-N antibody titres were significantly higher in patients who required admission ( 17 ). Regarding T CD4 + differentiation into Th1/Th2/Th17 phenotypes, the Th1 response is the most prevalent in viral infections. Antiviral IFN-γ, mainly produced by this Th1 subset, enhances the stimulation of the adaptive antiviral response to clear the infection and generate a memory to protect against future infections. Accordingly, our results also implied that the immune response to the three viruses was associated with a Th1/Th2/Th17 balance in favour of Th1. These responses were positively correlated with the Th1 cells, as occurs in the case of CMV, coinciding with what was previously reported ( 41 ), or negatively correlated with the Th2 cells, as occurs in CMV, influenza and SARS-CoV-2. In the case of the response to influenza, it may seem to contradict our results that most of the licensed vaccines have been developed for the purpose of ensuring a Th2 response and the consequent production of antibodies ( 42 ). However, these vaccines also collaterally induce cellular responses that favour the Th1 phenotype. This finding, and the greater persistence of the memory cellular response, are evidences supporting the proposal to modify the current criteria for developing influenza vaccines to ensure T cell-mediated protection, as other studies have already suggested ( 42 , 43 ). In the case of SARS-CoV-2 it is the humoral response that is negatively correlated with Th2 cells. Higher levels of Th2 cytokines, especially IL-4 and IL-5, can inhibit protective Th1 antiviral responses in COVID-19 patients. This was seen mainly in patients with severe COVID-19 disease, so it was hypothesized that Th2 inhibition might offer protection against severe COVID-19 symptoms, as seems to have happened in patients who were asymptomatic or who had mild COVID-19 disease ( 44 ). Generally, there seem to be no differences in the three viruses’ responses with respect to the distribution of the various functional differentiation subpopulations of memory CD4 + T lymphocytes. CONCLUSIONS In conclusion, this work allowed us to accurately characterise the cellular and humoral responses generated against three viral infection models —chronic, seasonal and novel infection— in immunocompetent older adults. Average older adults, whose immunosenescence would be more pronounced, partly due to a higher prevalence and persistence of CMV chronic infection over their lifetime, would be less effective for fighting an infection generated by a novel antigen. The immune system was shown to react in a different way and with different intensity, depending on the durability and type of viral stimulus with which it is in contact. The results suggest that specific responses, especially cellular responses, to novel pathogens resemble the memory response enhanced by repeated, but not chronic, viral encounters. Both responses to novel and repeated pathogens may be favoured by a more naïve CD8 + T lymphocyte phenotype compared with what happens when the immunosenescence is induced by chronic CMV infection. The subpopulation distribution and the level of antigen-specific T lymphocytes acting against known previous pathogens could be good biomarkers of the immunocompetence status of older adults, reflecting their ability to generate specific memory responses to new pathogens. Declarations Ethics approval and consent to participate: Informed consent was obtained from all the volunteers before they participated in the study. The study was approved in accordance with the Declaration of Helsinki by the ethics committee of the Hospital Central de Asturias (Oviedo, Spain) (nº 2020.269). Consent for publication: Complete written informed consent was obtained from all the volunteers for the publication of this study. Human Ethics and Consent to Participate declarations: Not applicable Availability of data and materials Data will be deposited in the Instituto de Salud Carlos III (ISCIII)-COVID19 repository, constituted to deposit data generated in the studies funded by the call for “Proyectos de investigación sobre el SARS-COV-2 Y LA ENFERMEDAD COVID-19”. Also raw and derived data supporting the findings of this study are available from the corresponding author [R. Alonso-Arias] on request. Competing interests The authors declare that they have no conflict of interest. Funding This research was partially supported by the Instituto de Salud Carlos III (COV20/0968) and by grant PI17/00714 from the Spanish I+D+i 2013–2016 State Program, which was cofounded by the Instituto de Salud Carlos III and the European Regional Development Fund (ERDF). Bueno-García E is sponsored by the Principado de Asturias (Programa de Ayudas “Severo Ochoa”; BP20-030). Authors' contributions The authors’ responsibilities were as follows: R Alonso-Arias, MA Moro-García and S Alonso-Alvarez designed the study; A García-Torre, E Bueno-García, B Rioseras, R López-Martínez, V Menéndez-García prepared protocols, collected and processed all the samples, performed or oversaw the experimental protocols, and analysed data; R Alonso-Arias , B Rioseras wrote the manuscript; A Lluna-González, A Sousa-Fernández, M Fernández-Goudin, L Campos-Riopedre, C Castro-Cueto, AB Pérez-Fernández, A Alonso-Rodríguez, C Menéndez-Peña, L Menéndez-Peña, N García-Arnaldo, E Feito-Díaz, A Fernández-Lorences, A Fraile-Manzano, C Fernández-Iglesias, JA Rivera, C Pérez-Fonseca, E Urdiales-Ruano, M Debán-Fernández, H Mendes-Moreira and P Herrero-Puente selected and recruited volunteers and organized their blood extractions and collected their clinical information; MA Moro-García and S Alonso-Alvarez reviewed the manuscript. Acknowledgements The authors are grateful to the Instituto de Salud Carlos III for supporting the study and to the donors for their selfless contribution to help us better understand immunity to SARS-CoV-2 infection. References Wik JA, Skalhegg BS. T cell metabolism in infection. Front Imm unol 2022;13:840610. Cunha LL, Valsecchi V, Ward LS. Investigating population-level immunosenescence: From bench to bedside. Front Immunol 2022;13:949928. Alford CA, Stagno S, Pass RF, Britt WJ. Congenital and perinatal cytomegalovirus infections. Rev Infect Dis 1990;12 Suppl 7:S745-753. Nikolich-Zugich J, van Lier RAW. Cytomegalovirus (cmv) research in immune senescence comes of age: Overview of the 6th international workshop on cmv and immunosenescence. Geroscience 2017;39:245-249. Moro-Garcia MA, Alonso-Arias R, Lopez-Vazquez A, Suarez-Garcia FM, Solano-Jaurrieta JJ, Baltar J, Lopez-Larrea C. Relationship between functional ability in older people, immune system status, and intensity of response to cmv. Age (Dordr) 2012;34:479-495. Alonso-Alvarez S, Colado E, Moro-Garcia MA, Alonso-Arias R. Cytomegalovirus in haematological tumours. Front Immunol 2021;12:703256. Iglesias-Escudero M, Moro-Garcia MA, Marcos-Fernandez R, Garcia-Torre A, Alvarez-Arguelles ME, Suarez-Fernandez ML, Martinez-Camblor P, Rodriguez M, Alonso-Arias R. Levels of anti-cmv antibodies are modulated by the frequency and intensity of virus reactivations in kidney transplant patients. PLoS One 2018;13:e0194789. Garcia-Torre A, Bueno-Garcia E, Lopez-Martinez R, Rioseras B, Diaz-Molina B, Lambert JL, Quiros C, Alonso-Alvarez S, Alonso-Arias R, Moro-Garcia MA. Cmv infection is directly related to the inflammatory status in chronic heart failure patients. Front Immunol 2021;12:687582. Moro-Garcia MA, Lopez-Iglesias F, Marcos-Fernandez R, Bueno-Garcia E, Diaz-Molina B, Lambert JL, Suarez-Garcia FM, Moris de la Tassa C, Alonso-Arias R. More intensive cmv-infection in chronic heart failure patients contributes to higher t-lymphocyte differentiation degree. Clin Immunol 2018;192:20-29. Yang TO, Chuang YF, Chiu YL. T-cell aging in end-stage renal disease: An evolving story with cmv. Med Microbiol Immunol 2019;208:281-287. Maruyama T, Fujisawa T, Suga S, Nakamura H, Nagao M, Taniguchi K, Tsutsui K, Ihara T, Niederman MS. Outcomes and prognostic features of patients with influenza requiring hospitalization and receiving early antiviral therapy: A prospective multicenter cohort study. Chest 2016;149:526-534. Garg S, Jain S, Dawood FS, Jhung M, Perez A, D'Mello T, Reingold A, Gershman K, Meek J, Arnold KE, et al. Pneumonia among adults hospitalized with laboratory-confirmed seasonal influenza virus infection-united states, 2005-2008. BMC Infect Dis 2015;15:369. Nypaver C, Dehlinger C, Carter C. Influenza and influenza vaccine: A review. J Midwifery Womens Health 2021;66:45-53. Keilman LJ. Seasonal influenza (flu). Nurs Clin North Am 2019;54:227-243. Forchette L, Sebastian W, Liu T. A comprehensive review of covid-19 virology, vaccines, variants, and therapeutics. Curr Med Sci 2021;41:1037-1051. Gao YD, Ding M, Dong X, Zhang JJ, Kursat Azkur A, Azkur D, Gan H, Sun YL, Fu W, Li W, et al. Risk factors for severe and critically ill covid-19 patients: A review. Allergy 2021;76:428-455. Garcia-Torre A, Bueno-Garcia E, Lopez-Martinez R, Rioseras B, Moro-Garcia MA, Alonso-Alvarez S, Lluna-Gonzalez A, Sousa-Fernandez A, Fernandez-Gudin M, Campos-Riopedre L, et al. Surviving older patients show preserved cellular and humoral immunological memory several months after sars-cov-2 infection. J Gerontol A Biol Sci Med Sci 2022;77:33-40. Ohishi K, Ninomiya A, Kida H, Park CH, Maruyama T, Arai T, Katsumata E, Tobayama T, Boltunov AN, Khuraskin LS, et al. Serological evidence of transmission of human influenza a and b viruses to caspian seals (phoca caspica). Microbiol Immunol 2002;46:639-644. Kang I, Hong MS, Nolasco H, Park SH, Dan JM, Choi JY, Craft J. Age-associated change in the frequency of memory cd4+ t cells impairs long term cd4+ t cell responses to influenza vaccine. J Immunol 2004;173:673-681. Dadras O, SeyedAlinaghi S, Karimi A, Shamsabadi A, Qaderi K, Ramezani M, Mirghaderi SP, Mahdiabadi S, Vahedi F, Saeidi S, et al. Covid-19 mortality and its predictors in the elderly: A systematic review. Health Sci Rep 2022;5:e657. Ferrari D, Seveso A, Sabetta E, Ceriotti D, Carobene A, Banfi G, Locatelli M, Cabitza F. Role of time-normalized laboratory findings in predicting covid-19 outcome. Diagnosis (Berl) 2020;7:387-394. Draper J, Webb J, Jackson T, Jones H, Rinaldi CA, Schiff R, McDonagh T, Razavi R, G SC-W. Comparison of the diagnostic accuracy of plasma n-terminal pro-brain natriuretic peptide in patients 80 years of age with heart failure. Am J Cardiol 2018;122:2075-2079. Johnson ED, Schell JC, Rodgers GM. The d-dimer assay. Am J Hematol 2019;94:833-839. Aoshi T, Koyama S, Kobiyama K, Akira S, Ishii KJ. Innate and adaptive immune responses to viral infection and vaccination. Curr Opin Virol 2011;1:226-232. Morris AG. Interferons. Immunol Suppl 1988;1:43-45. Ali MG, Zhang Z, Gao Q, Pan M, Rowan EG, Zhang J. Recent advances in therapeutic applications of neutralizing antibodies for virus infections: An overview. Immunol Res 2020;68:325-339. Healy B, Khan A, Metezai H, Blyth I, Asad H. The impact of false positive covid-19 results in an area of low prevalence. Clin Med (Lond) 2021;21:e54-e56. Boechat JL, Chora I, Morais A, Delgado L. The immune response to sars-cov-2 and covid-19 immunopathology - current perspectives. Pulmonology 2021;27:423-437. Harari A, Vallelian F, Meylan PR, Pantaleo G. Functional heterogeneity of memory cd4 t cell responses in different conditions of antigen exposure and persistence. J Immunol 2005;174:1037-1045. Kalia V, Sarkar S, Ahmed R. Cd8 t-cell memory differentiation during acute and chronic viral infections. Adv Exp Med Biol 2010;684:79-95. Kim J, Kim AR, Shin EC. Cytomegalovirus infection and memory t cell inflation. Immune Netw 2015;15:186-190. Janeway C, Travers P, Walport M, Shlomchik M. Immunobiology: The immune system in health and disease, 5th edition ed. United Kingdom; Garland Science; 2001. Le Bert N, Tan AT, Kunasegaran K, Tham CYL, Hafezi M, Chia A, Chng MHY, Lin M, Tan N, Linster M, et al. Sars-cov-2-specific t cell immunity in cases of covid-19 and sars, and uninfected controls. Nature 2020;584:457-462. Sariol A, Perlman S. Lessons for covid-19 immunity from other coronavirus infections. Immunity 2020;53:248-263. Khairallah C, Dechanet-Merville J, Capone M. Gammadelta t cell-mediated immunity to cytomegalovirus infection. Front Immunol 2017;8:105. Wertheimer AM, Bennett MS, Park B, Uhrlaub JL, Martinez C, Pulko V, Currier NL, Nikolich-Zugich D, Kaye J, Nikolich-Zugich J. Aging and cytomegalovirus infection differentially and jointly affect distinct circulating t cell subsets in humans. J Immunol 2014;192:2143-2155. Karrer U, Sierro S, Wagner M, Oxenius A, Hengel H, Koszinowski UH, Phillips RE, Klenerman P. Memory inflation: Continuous accumulation of antiviral cd8+ t cells over time. J Immunol 2003;170:2022-2029. Pawelec G, Gouttefangeas C. T-cell dysregulation caused by chronic antigenic stress: The role of cmv in immunosenescence? Aging Clin Exp Res 2006;18:171-173. Lanzer KG, Johnson LL, Woodland DL, Blackman MA. Impact of ageing on the response and repertoire of influenza virus-specific cd4 t cells. Immun Ageing 2014;11:9. Wu J, Liang B, Chen C, Wang H, Fang Y, Shen S, Yang X, Wang B, Chen L, Chen Q, et al. Sars-cov-2 infection induces sustained humoral immune responses in convalescent patients following symptomatic covid-19. Nat Commun 2021;12:1813. Rentenaar RJ, Gamadia LE, van DerHoek N, van Diepen FN, Boom R, Weel JF, Wertheim-van Dillen PM, van Lier RA, ten Berge IJ. Development of virus-specific cd4(+) t cells during primary cytomegalovirus infection. J Clin Invest 2000;105:541-548. Kim YH, Hong KJ, Kim H, Nam JH. Influenza vaccines: Past, present, and future. Rev Med Virol 2022;32:e2243. Pleguezuelos O, Robinson S, Fernandez A, Stoloff GA, Mann A, Gilbert A, Balaratnam G, Wilkinson T, Lambkin-Williams R, Oxford J, et al. A synthetic influenza virus vaccine induces a cellular immune response that correlates with reduction in symptomatology and virus shedding in a randomized phase ib live-virus challenge in humans. Clin Vaccine Immunol 2015;22:828-835. Pavel AB, Glickman JW, Michels JR, Kim-Schulze S, Miller RL, Guttman-Yassky E. Th2/th1 cytokine imbalance is associated with higher covid-19 risk mortality. Front Genet 2021;12:706902. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigurelegends.docx Supplementaryfigure1.tif Supplementaryfigure2.tif Supplementaryfigure3.tif Supplementaryfigure4.tif Cite Share Download PDF Status: Published Journal Publication published 05 Dec, 2024 Read the published version in Immunity & Ageing → Version 1 posted Editorial decision: Revision requested 05 Oct, 2024 Reviews received at journal 27 Sep, 2024 Reviewers agreed at journal 05 Sep, 2024 Reviewers agreed at journal 05 Sep, 2024 Reviews received at journal 13 Aug, 2024 Reviewers agreed at journal 24 Jul, 2024 Reviewers agreed at journal 22 Jul, 2024 Reviewers invited by journal 19 Jul, 2024 Editor assigned by journal 19 Jul, 2024 Submission checks completed at journal 19 Jul, 2024 First submitted to journal 13 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4735076","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338989593,"identity":"03705443-d918-420b-a4d5-ab002454ef0d","order_by":0,"name":"Beatriz Rioseras","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Beatriz","middleName":"","lastName":"Rioseras","suffix":""},{"id":338989594,"identity":"c62a1604-f6a0-46d0-b220-5a6778736fdd","order_by":1,"name":"Eva Bueno-García","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Eva","middleName":"","lastName":"Bueno-García","suffix":""},{"id":338989595,"identity":"05d821e2-3f1b-46e8-a84b-f9dec7ee8b88","order_by":2,"name":"Alejandra García-Torre","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Alejandra","middleName":"","lastName":"García-Torre","suffix":""},{"id":338989596,"identity":"43c59107-7e5e-486e-916f-6773498fd12e","order_by":3,"name":"Rocío López-Martínez","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Rocío","middleName":"","lastName":"López-Martínez","suffix":""},{"id":338989597,"identity":"8edf52d3-c197-4270-bcaa-882978de5d86","order_by":4,"name":"Marco Antonio Moro-García","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Marco","middleName":"Antonio","lastName":"Moro-García","suffix":""},{"id":338989598,"identity":"56ac2c32-6d9c-4550-8ee7-d9fa8840d876","order_by":5,"name":"Sara Alonso-Alvarez","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Alonso-Alvarez","suffix":""},{"id":338989599,"identity":"2ab35ac7-402f-47cf-a4be-9e9503e156a5","order_by":6,"name":"Victoria Menéndez-García","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Victoria","middleName":"","lastName":"Menéndez-García","suffix":""},{"id":338989600,"identity":"d55c087d-2cfb-4eff-be6c-964ed49babc0","order_by":7,"name":"Alba Lluna-González","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Alba","middleName":"","lastName":"Lluna-González","suffix":""},{"id":338989601,"identity":"53c1ff49-74aa-4ed3-9338-6d2106a902c9","order_by":8,"name":"Alejandra Sousa-Fernández","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Alejandra","middleName":"","lastName":"Sousa-Fernández","suffix":""},{"id":338989602,"identity":"d3319570-96cd-400e-8d7c-a94d960a0fc6","order_by":9,"name":"Marta Fernández Gudin","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"Fernández","lastName":"Gudin","suffix":""},{"id":338989603,"identity":"bf9ce3da-83dc-4cdf-aece-cfba7e9614b2","order_by":10,"name":"Laura Campos Riopedre","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"Campos","lastName":"Riopedre","suffix":""},{"id":338989604,"identity":"1af14db4-0602-4430-962e-a8113b835e00","order_by":11,"name":"Corina Castro del Cueto","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Corina","middleName":"Castro del","lastName":"Cueto","suffix":""},{"id":338989605,"identity":"909c33d8-e1d0-4b6b-ae27-87feca631b3b","order_by":12,"name":"Ana Belén Pérez Fernández","email":"","orcid":"","institution":"Health Research Institute of the Principality of Asturias (ISPA)","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Belén Pérez","lastName":"Fernández","suffix":""},{"id":338989606,"identity":"15b34a34-f9d1-4ba7-824c-2ed9536ea30c","order_by":13,"name":"Ana Alonso Rodríguez","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Alonso","lastName":"Rodríguez","suffix":""},{"id":338989607,"identity":"6b1e6f9a-f3b1-4b4c-b9c9-a62787d6bf5b","order_by":14,"name":"Carla Menéndez Peña","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Carla","middleName":"Menéndez","lastName":"Peña","suffix":""},{"id":338989608,"identity":"94d4c90f-95ed-4616-a235-e61e503ca3fb","order_by":15,"name":"Lara Menéndez Peña","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Lara","middleName":"Menéndez","lastName":"Peña","suffix":""},{"id":338989609,"identity":"5a3ffc92-52cf-4948-a8c2-a38c84bc8b25","order_by":16,"name":"Noelia García Arnaldo","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Noelia","middleName":"García","lastName":"Arnaldo","suffix":""},{"id":338989610,"identity":"f06bfba5-61d7-4659-bd69-7e84fee84a7b","order_by":17,"name":"Estefanía Feito Díaz","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Estefanía","middleName":"Feito","lastName":"Díaz","suffix":""},{"id":338989611,"identity":"808651ab-d9b0-468f-a92c-344c673edb18","order_by":18,"name":"Adriana Fernández Lorences","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Adriana","middleName":"Fernández","lastName":"Lorences","suffix":""},{"id":338989612,"identity":"1f472857-3291-4e8a-95d1-b511a5eff908","order_by":19,"name":"Agustín Fraile Manzano","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Agustín","middleName":"Fraile","lastName":"Manzano","suffix":""},{"id":338989613,"identity":"8103165f-51d7-4242-a8ad-d4acfcbb53b5","order_by":20,"name":"Carolina Fernández Iglesias","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Carolina","middleName":"Fernández","lastName":"Iglesias","suffix":""},{"id":338989614,"identity":"f0255e10-ec3e-4065-a50b-08200c1649c8","order_by":21,"name":"Jose Arturo Rivera","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Jose","middleName":"Arturo","lastName":"Rivera","suffix":""},{"id":338989615,"identity":"ee655c31-3e86-44a7-870a-6416a594c513","order_by":22,"name":"Carmen Pérez Fonseca","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Carmen","middleName":"Pérez","lastName":"Fonseca","suffix":""},{"id":338989616,"identity":"2e240e36-5663-415f-a98a-94fbb8152771","order_by":23,"name":"Estibaliz Urdiales Ruano","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Estibaliz","middleName":"Urdiales","lastName":"Ruano","suffix":""},{"id":338989617,"identity":"19b0dedb-84cf-4e85-bf3a-c901184aff84","order_by":24,"name":"María Debán Fernández","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"Debán","lastName":"Fernández","suffix":""},{"id":338989618,"identity":"3f144c2c-cd49-4e50-ac92-7b4c0d5387e4","order_by":25,"name":"Hugo Mendes Moreira","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Hugo","middleName":"Mendes","lastName":"Moreira","suffix":""},{"id":338989619,"identity":"eca4cba2-204b-42cc-a260-eebb4b139485","order_by":26,"name":"Pablo Herrero Puente","email":"","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":false,"prefix":"","firstName":"Pablo","middleName":"Herrero","lastName":"Puente","suffix":""},{"id":338989620,"identity":"ce6e6183-65c3-4528-a4cc-3cd0032bfc97","order_by":27,"name":"Rebeca Alonso-Arias","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYFAC5gYoDcQfwWzGxgP4tTAitDDObGCQAIkQqQWkixeshYEBrxbz9oONjwv+2MibtzM//my7w6ZOt/0w0JaKOpxaZM4kNhvPbEsznHOYzUw690yahNmZRKCWM4dxapFgSGyT5m04zDiDmcGMObftsITZAaAWxjbcbpPgf9gmzfPnsP0MZvbPny1BWs4/BGr5h9thEhJAW3jYDifOYOYxkGYEabkBsqWBGY+Wh83GvG1pyUAtZZK9bWmS224AbUk4hscv/MkHH/P8sbGdwX9884efbTb8ZufTHz74UIPbYThAAqkaRsEoGAWjYBSgAADYD1bhA66I3wAAAABJRU5ErkJggg==","orcid":"","institution":"Central University Hospital of Asturias","correspondingAuthor":true,"prefix":"","firstName":"Rebeca","middleName":"","lastName":"Alonso-Arias","suffix":""}],"badges":[],"createdAt":"2024-07-13 12:10:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4735076/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4735076/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12979-024-00488-3","type":"published","date":"2024-12-05T15:57:19+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62730299,"identity":"e90e6b28-de8e-433f-ba84-a33652ea0152","added_by":"auto","created_at":"2024-08-18 23:15:09","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":272154,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBiochemical factors affected by SARS-CoV2 infection. \u003c/strong\u003e(A) Comparison between the level of total leukocytes, lymphocytes and monocytes populations before and after the SARS-CoV2 infection. (B) Comparison of patients’ age between individuals with altered and unaltered D-dimer and NT-proBNP biochemical indicators (C) Representation of number of individuals without and with cardiopathie underlying disease. It is indicated the percentage of individuals with altered NT-proBNP in each case.\u003c/p\u003e\n\u003cp\u003e** statistically significant differences (p\u0026lt;0.01)\u003c/p\u003e\n\u003cp\u003e* statistically significant differences (p\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/3b111936ed45d64d3574bfc6.jpg"},{"id":62729693,"identity":"8ca0ad5e-84f8-4e12-b51b-3b6cbb201453","added_by":"auto","created_at":"2024-08-18 23:07:09","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":362593,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCellular and humoral responses detected. (A)\u003c/strong\u003e Representation of the percentage of cases in which responses to the viruses (CMV in black, influenza in grey and SARS-CoV-2 in white) were not detected with each of the different measurements performed. (\u003cstrong\u003eB) \u003c/strong\u003eSchematization of the type of memory responses detected for the three viral infections (CMV, influenza and SARS-CoV-2). The percentage of patients in the different situations found for each virus is indicated (no detectable response in black, cellular response with no humoral response detected in dark grey, humoral response with no cellular response detected in light grey, and cellular and humoral responses detected in white). In the upper part is represented the percentage of patients that showed anti-S, anti N or both humoral responses against SARS-CoV-2. In the bottom it is represented the percentage of patients that showed IFN-g production, Granzyme-B production or both types of cellular responses against the three viruses.\u003c/p\u003e\n\u003cp\u003eVac: vaccinated.\u003c/p\u003e\n\u003cp\u003eUnvac: unvaccinated\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/01b697604f1ed39865f00a51.jpg"},{"id":62730300,"identity":"9258a0ce-abc8-493c-8418-7f10cbd3a8a5","added_by":"auto","created_at":"2024-08-18 23:15:09","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":344978,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of anti-CMV, anti-influenza and anti SARS-CoV2 memory responses (A) \u003c/strong\u003eAnti-CMV cellular (left and middle graphs) and humoral (right graph) responses among the CMV seropositive patients. \u003cstrong\u003e(B) \u003c/strong\u003eComparison of anti-influenza cellular (left and middle graphs) and humoral (right graph) responses between the vaccinated and unvaccinated patients. \u003cstrong\u003e(C) \u003c/strong\u003eAnti-SARS-CoV-2 cellular (left and middle graphs) and humoral (right graph) responses.\u003c/p\u003e\n\u003cp\u003e* statistically significant differences (p\u0026lt;0.05) Mann-Whitney U test\u003c/p\u003e\n\u003cp\u003e** statistically significant differences (p\u0026lt;0.01) Mann-Whitney U test\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/a7556af134af6d4f714def1a.jpg"},{"id":62729699,"identity":"befce1bd-3331-444b-8aaa-cfc5614de004","added_by":"auto","created_at":"2024-08-18 23:07:09","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":255342,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of celular responses generated against the three viruses.\u003c/strong\u003e \u003cstrong\u003e(A) \u003c/strong\u003eInfluenza unvaccinated patients. \u003cstrong\u003e(B) \u003c/strong\u003eInfluenza vaccinated patients.\u003c/p\u003e\n\u003cp\u003e* statistically significant differencces (p\u0026lt;0.05)\u003c/p\u003e\n\u003cp\u003e** statistically significant differences (p\u0026lt;0.01)\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/e2b0d92ca36c669bbc92ba0e.jpg"},{"id":62729695,"identity":"eecb5025-5649-466b-bc35-999c1b35c82b","added_by":"auto","created_at":"2024-08-18 23:07:09","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":401060,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelation between viral antigen model responses. (A) \u003c/strong\u003eThe relationship between anti-influenza and anti-SARS-CoV-2 cellular (left and middle) and humoral responses (right). Spearman correlation coefficients and p values are shown. n.s. = no significative. \u003cstrong\u003e(B) \u003c/strong\u003eAnti-influenza specific responses comparison between seropositive and seronegative CMV patients. \u003cstrong\u003e(C) \u003c/strong\u003eAnti-SARS-CoV-2 specific responses comparison between seropositive and seronegative CMV patients.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/f0e1090fd399cab6395b8b54.jpg"},{"id":62730301,"identity":"714c5d15-40c4-468e-aa0b-22124b4c28d0","added_by":"auto","created_at":"2024-08-18 23:15:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":141010,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeat maps showing the correlations between the viral responses and the different T lymphocytes subpopulations distribution. \u003c/strong\u003eVertical columns represent the different types of cellular or humoral responses (labeled at the bottom). Horizontally are represented T lymphocyte subpopulations (labeled on the left); for each subpopulation the upper line is expressed as percentage while the bottom line is expressed as absolute values in cells/µL. The correlation scale (Spearman correlation coefficients) is represented in a greyscale from darker (negative correlation) to lighter (positive correlation). An asterisk indicates a statistically significative correlation (Spearman correlation, p\u0026lt;0.05) while two asterisks indicate a highly statistically significative corrrelation (Spearman correlation, p\u0026lt;0.01). (A) Correlations of responses with the different T lymphocyte subpopulation according to their differentiation stage (naïve-memory). The subpopulations indicated on the left on a light background correspond to the least differentiated subpopulations while on a dark background to the most differentiated for both CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes. Percentages are referred to the total CD4\u003csup\u003e+\u003c/sup\u003e or CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes but in the case of subtypes of EM they are referred to CD4\u003csup\u003e+\u003c/sup\u003eEM or CD8\u003csup\u003e+\u003c/sup\u003eEM. \u003cstrong\u003e(B) \u003c/strong\u003eCorrelations of responses with the different functional differentiation subpopulations of memory CD4\u003csup\u003e+ \u003c/sup\u003eT lymphocytes. Percentages are referred to the memory CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/fd2eab1d087ec56ed2540ddf.png"},{"id":70965276,"identity":"cd1405b4-d968-4e09-9151-54c92a7528d2","added_by":"auto","created_at":"2024-12-09 16:18:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2903944,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/20582a51-f57e-4e15-bdb4-f869184c953a.pdf"},{"id":62729691,"identity":"c1b334a8-23f3-47ab-bbc9-e823186ec9ad","added_by":"auto","created_at":"2024-08-18 23:07:09","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10759,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigurelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/0a6422331e20d0c554832ce5.docx"},{"id":62729690,"identity":"796007ff-f224-4286-820b-ac32e5726602","added_by":"auto","created_at":"2024-08-18 23:07:09","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":282172,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/31a19a49ecba1c774ecdcb3c.tif"},{"id":62729696,"identity":"698d4c21-6b3f-4258-8fe8-eb8e0a1d1fa6","added_by":"auto","created_at":"2024-08-18 23:07:09","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":6815480,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/ac56ced0c465ffb480feab4c.tif"},{"id":62729700,"identity":"d7ddc127-421f-4466-b589-3852c8ca7af0","added_by":"auto","created_at":"2024-08-18 23:07:09","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":6702728,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/dcd4a00ed33b3320c6ba5087.tif"},{"id":62729698,"identity":"039b0600-3802-4227-b744-1a083da03b2c","added_by":"auto","created_at":"2024-08-18 23:07:09","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":6662304,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure4.tif","url":"https://assets-eu.researchsquare.com/files/rs-4735076/v1/218640a1a1e0f92cc4ee777f.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eCharacterization of Specific Responses to Three Models of Viral Antigens in Immunocompetent Older Adults\u003c/p\u003e","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eContact with antigens throughout an individual\u0026rsquo;s life leads to the generation of a specific memory cellular and humoral immune response. Two consequences of this process are a reduction in the number of na\u0026iuml;ve T lymphocytes and an increase in the abundance of memory cells. In the case of viruses, the type of infection they cause, and the stage of life when it occurs, may determine the type and intensity of the memory generated. The effect will be more pronounced in older adults, whose memory T repertoire is more conditioned by successive reactivations of the viruses that cause chronic infections, or by repeated immunizations, through infection or vaccination, against seasonal viruses.\u003c/p\u003e \u003cp\u003eOlder adults may be more susceptible to infections by viruses and other pathogens as a consequence of the changes in the immune system that accompany aging, known as immunosenescence. During aging it also appears a chronic low-grade inflammation known as inflammaging (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Some of the changes that occur in the T lymphocyte compartment during immunosenescence have been associated with clinical consequences such as the generation of weaker vaccine responses, a reduction in the ability to secrete antibodies and a defective immune response to viruses, mainly those to which there has been no previous exposure (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe consequences of viral infection vary depending on the virus characteristics, the viral lifecycle and the ability of the host\u0026rsquo;s immune system to eliminate the infection, in which age is an important factor. Thus, some viral infections cause acute disease after a short incubation period, while others can remain in a latent state or cause chronic infections or diseases. Chronic cytomegalovirus (CMV), seasonal influenza and the novel SARS-CoV-2 infection are examples of three distinct models of viral infection, all of which have important implications for older adults and can induce different immune memory mechanisms.\u003c/p\u003e \u003cp\u003eCMV is a DNA herpesvirus that is ubiquitous in human populations worldwide. As is typical of all herpesviruses, CMV has biological properties of latency and reactivation, whereby once an individual has been infected, the virus remains latent as a chronic infection for the rest of their life (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The important contribution of CMV infection to immunosenescence in older adults is well known (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), but it is also of significance in immunosuppressed situations such as in kidney transplant, in onco-haematological patients (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), and in some chronic diseases such as chronic heart failure and renal disease (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConversely, influenza is a highly contagious, annual respiratory illness caused by several RNA viruses belonging to the Orthomyxoviridae family. Most people come into contact with these viruses several times during their life and are able to eliminate them without any complication. However, these viruses can increase morbidity and mortality in some groups of individuals, particularly the immunocompromised, as older adults tend to be. It is well documented that older adults are at higher risk of developing severe influenza disease and serious complications than are those in younger age groups (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Vaccination is the main preventive measure against influenza infection, and it is recommended that chronically ill individuals and adults over the age of 65 years be vaccinated annually (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSARS-CoV-2 is a very recently emerged coronavirus that infects humans. It was first detected in 2019 as the causative agent of the current coronavirus disease 2019 (COVID-19) pandemic. It differs significantly from previously identified coronaviruses and offers an opportunity to study the immune response generated by individuals to a new viral antigen. COVID-19 disease follows a course with very diverse clinical presentations and symptoms. The severity of this infection is also highly variable, ranging from completely asymptomatic, through very mild, to extremely serious symptoms (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The main risk factors include age, obesity, hypertension, diabetes mellitus, heart disease and lung disease. In the case of age, patients aged above 60 years were found to be around five times more likely to die after developing symptoms than patients aged between 30\u0026ndash;59 years (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Our group previously reported that specific immunity to SARS-CoV-2 is preserved in older surviving adults.\u003c/p\u003e \u003cp\u003eThe aim of the current study was to characterise and compare the specific cellular and humoral responses to these three different models of viral infection (chronic, repeated and new) in immunocompetent older adults. The ultimate goal is to find new biomarkers of the immunocompetence status of older adults, based on the characterization of responses against known previous infections that could reflect their ability to generate specific memory responses to new pathogens.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eDonors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFifty-nine volunteers with a positive PCR for SARS-CoV-2 were recruited by the Emergency Service of the Hospital Universitario Central de Asturias (Oviedo, Spain). Inclusion criteria for this study were age over 60 years old and their SARS-CoV-2 infection had been asymptomatic or very mildly symptomatic not requiring admission to hospital. Peripheral blood samples were drawn for analysis from all participants an average of 5 months after being infected with SARS-CoV-2 for the first time between March and May 2020. Informed consent was obtained from all volunteers before they participated. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHaemogram and biochemical characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCounts of leukocytes, overall and separately for lymphocytes, monocytes and neutrophils, were obtained from donors\u0026rsquo; whole blood, anticoagulated with EDTA, by fluorescent flow cytometry and hydrodynamic focusing in a Sysmex XT-2000\u003cem\u003ei\u0026nbsp;\u003c/em\u003eanalyser (Sysmex, Kobe, Japan) following the manufacturer\u0026rsquo;s specifications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe levels of D-Dimer and NT-proBNP were measured in donor serum by turbidimetric immunoassay using an ACL TOP 750 analyser (Werfen, Barcelona, Spain), and by electrochemiluminescence using a COBAS e801 analyser (Roche, Basel, Switzerland), both following the manufacturer\u0026rsquo;s specifications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunophenotyping\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor flow cytometry analysis of lymphocyte subpopulations, peripheral blood cells were surface-stained with a combination of antibodies appropriate for the cell population analysed. T/B/NK populations were analysed with anti-CD45 (FITC), anti-CD56+16 (RD1), anti-CD19 (ECD) and anti-CD3 (PC5) using the AQUIOS Tetra-2+ Monoclonal Antibody Reagents Panel (Beckman-Coulter, Brea, CA, USA). The na\u0026iuml;ve cells and the different maturation stages of memory CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes were analysed using anti-CD3 (FITC), anti-CD8a (PE), anti-CD45 (PerCP), anti-CD27 (PECy7), anti-CCR7 (APC), anti-CD45RA (APCFire), anti-CD28 (BV) (BioLegend, San Diego, CA, USA), and anti-CD4 (ECD) (Beckman-Coulter). This staining made it possible to discriminate the different subpopulations of CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes: na\u0026iuml;ve (N) (CD45RA+CCR7+), central memory (CM) (CD45RA-CCR7+), effector memory (EM) (CD45RA-CCR7-) and terminally differentiated effector T cells re-expressing CD45RA (EMRA) (CD45RA+CCR7-). The absolute frequency of cells per millilitre and the percentage of CD4\u003csup\u003e+\u003c/sup\u003e or CD8\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eT lymphocytes of these subsets of cells were measured. In the EM subpopulation it was possible to detect several maturation stages: less differentiated effector memory cells that are memory-like, i.e., EM1 (CD27+CD28+) and EM4 (CD27-CD28+); and the more differentiated effector memory cells that are effector-like, i.e., EM3 (CD27-CD28-) and EM2 (CD27+CD28-). The EM2 subtype is only present in CD8\u003csup\u003e+\u003c/sup\u003e T lymphoyctes but is absent from CD4+ T lymphocytes. Functional differentiation of memory CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes was studied with anti-CXCR3 (AF488), anti-CD4 (ECD), anti-CCR6 (PC7) (Beckman-Coulter), anti-CCR7 (PerCP), anti-CD45RA (APCFire) and anti-CD28 (BV) (BioLegend), which were able to detect various Th subpopulations: Th1 (CCR6+CXCR3+), Th2 (CCR6-CXCR3-), Th17 (CCR6+CXCR3-) and Th1.17 (CCR6-CXCR3+).\u003c/p\u003e\n\u003cp\u003eThese different stains were performed with 100 \u0026micro;L of whole blood anticoagulated with EDTA from the donors. Samples were stained with the corresponding combination of labelled monoclonal antibodies for 20 minutes at room temperature. Red blood samples were lysed for 10 minutes at room temperature with FACS Lysing Solution (BD Biosciences), washed in PBS and analysed using Kaluza software in a Navios cytometer (Beckman-Coulter). Appropriate isotype control mAbs were used for marker settings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSpecific T cellular response measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eELISpot assays were performed to quantify IFN-g\u0026nbsp;and granzyme B-producing specific T cells against CMV, influenza and SARS-CoV-2 viruses. Peripheral blood mononuclear cells (PBMCs) were isolated from peripheral blood anticoagulated with EDTA by centrifugation on Ficoll\u0026ndash;Hypaque gradients (Lymphoprep, Nycomed, Oslo, Norway). PBMCs (2.5 x 10\u003csup\u003e5\u003c/sup\u003e/well) were then cultured for 18 h on a filter plate (Millipore, Billerica, MA, USA) previously coated with anti-IFN-g\u0026nbsp;or anti-granzyme B antibodies (15 \u0026mu;g/mL) (Mabtech, Nacka Strand, Sweden) and cultured in medium alone for negative control, in the presence of anti-CD3 (1 ng/mL) for positive control, and with peptides from the different viruses. The peptide pool included pp50, pp65, IE1, IE2 and envelope glycoprotein B antigens from CMV (2 \u0026mu;g/mL) (Mabtech), the influenza virus quadrivalent vaccine used in the 2019-2020 campaign (1/100 dilution) or S1, S2 and N SARS-CoV-2 peptide pools (2 \u0026mu;g/mL) (Mabtech). IFN-g\u0026nbsp;and granzyme B produced by T lymphocytes under specific stimulation were captured and detected by biotinylated anti-IFN-g\u0026nbsp;and anti-granzyme B antibody (1 \u0026mu;g/mL) (Mabtech), respectively, followed by streptavidin\u0026ndash;horseradish peroxidase (Mabtech). Spots were developed using tetramethylbenzidine (TMB) substrate (Mabtech) and counted with ImageJ software. Results were considered to be negative when there were ten or fewer dots. The results were expressed as the frequency of IFN-g\u0026nbsp;or granzyme B producer T lymphocytes per 10\u003csup\u003e6\u003c/sup\u003e T cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHumoral response measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLevels of anti-CMV antigen antibodies (CMV-IgG) were detected in serum from the donors by chemiluminescence analysis using the LIAISON\u0026reg; CMV IgG II assay (DiaSorin, Milan, Italy). CMV seropositivity was defined as CMV-IgG \u0026gt; 14 U/mL.\u003c/p\u003e\n\u003cp\u003eAnti-influenza virus antibodies in serum obtained from individuals were measured semiquantitatively by ELISA as previously described (18), with some modifications (19). The OD values of individual samples were compared against a calibration curve made by serial dilutions of the same internal control serum for all the experiments. The detection limit was 0.5.\u003c/p\u003e\n\u003cp\u003eAnti-SARS-CoV-2-specific IgG antibodies were quantified with a Human anti-SARS-CoV-2 (S) IgG ELISA kit and a Human anti-SARS-CoV-2 (N) IgG ELISA kit (Fine Test, Wuhan, China), following the manufacturer\u0026rsquo;s specifications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis and graphical presentation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePearson\u0026rsquo;s chi-squared test and Fisher\u0026rsquo;s exact test were used to determine whether there were any significant associations between pairs of qualitative variables. The Kolmogorov\u0026ndash;Smirnov test was used to determine whether quantitative variables were normally distributed. Haemogram and biochemical parameters data that were measured before and after the SARS-CoV-2 infection were analysed using Student\u0026rsquo;s t test for paired samples or Wilcoxon\u0026rsquo;s signed‐rank test when the data were normally or non-normally distributed, respectively. The cellular responses to the three viral antigens were compared with a general linear model for repeated measures using Bonferroni-corrected post hoc pairwise comparisons. Group differences between quantitative variables were assessed with Student\u0026rsquo;s t test or the nonparametric Mann\u0026ndash;Whitney U test when the data were normally or non-normally distributed, respectively. Correlations between variables were assessed using the nonparametric Spearman test (\u0026rho;). Statistical analyses were carried out with SPSS 17.0 (SPSS Inc., Chicago, IL) and values of p\u0026lt;0.05 were considered significant.\u003c/p\u003e\n\u003cp\u003eAll graphs were created with GraphPad Prism (version 8.0.2).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eFeatures of studied group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the 59 donors recruited were more than 60 years old, with a mean age of 72.15 years (SD: 12 years), of whom 39 were female (66%) and 20 were male (34%). Details of underlying diseases (64.4% of the patients) and symptoms of patients that had mild symptomatic SARS CoV-2 infection (61%) are summarised in Table 1. Laboratory characteristics, such as the level of the leukocyte subsets, D-Dimer and NT-proBNP, were also measured in most patients. Regarding influenza immunology status, 33 patients had received the influenza vaccine some months before the samples were collected, while 26 had not been vaccinated in the most recent vaccination campaign. Forty-nine patients were CMV-seropositive and 10 were CMV-seronegative (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Participant characteristics\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients (n=59)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAGE \u0026plusmn; SD (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e72.2 \u0026plusmn; 12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEMALES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e39 (66)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eUnderlying disease\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e38/56 (64.4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 25 (65.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Diabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 13 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Asthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 7 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 14 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Renal disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 4 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 3 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Drinker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 4 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eALTERED D-DIMER (\u0026gt;500 ng/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e18/49 (36.7)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eALTERED NT-proBNP (\u0026gt;300 pg/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e9/58 (15.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eINFLUENZA-VACCINATED\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e33 (55.9)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCMV-SEROPOSITIVE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e49 (83)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eSymptomatic of COVID-19 disease\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e36/56 (61)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Fever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 24 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Cough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 24 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Dyspnoea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 9 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Chest pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 5 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Ageusia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 9 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Anosmia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; 11 (30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.19587628865979%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Mean days with symptoms \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026nbsp;3.3 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNumbers in brackets represent percentages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHaemogram and biochemical characteristic recovery after SARS-CoV-2 infection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSince recruited patients had recently been infected with SARS-CoV-2, we wanted to determine whether some of the characteristics that are known to be altered during this infection had already returned to normal. As is well known, SARS-CoV-2 infection produces lymphopenia, as was seen in five of the patients for whom these data were available during the infection process (Supplementary Figure 1). We wanted to establish whether patients showed normal levels of leukocytes when the study began. It was possible to obtain the basal haemogram information from 2 months to 4 years before the SARS-CoV-2 infection in 52 of the 59 patients. When the levels of the different leukocyte populations were compared before and after the infection, no statistically significant differences, or statistically significant but not biologically significant differences, were seen in the total leukocytes (Wilcoxon test, p\u0026lt;0.01), lymphocytes (paired-samples t test, p\u0026lt;0.01), monocytes (Wilcoxon test, p\u0026lt;0.01) or neutrophils (Wilcoxon test, p\u0026gt;0.05) (Figure 1A). SARS-CoV-2 infection appeared not to affect leukocyte populations substantively once patients had completely recovered.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe now consider the biochemical characteristics that are known to be altered in SARS-CoV-2-infected patients and are considered indicators of a more severe COVID-19 disease. We measured D-Dimer and NT-proBNP levels in serum samples of 49 and 58 of the 59 patients, respectively. Eighteen and nine individuals had an elevated level of D-Dimer (\u0026gt;500ng/mL) and NT-proBNP (\u0026gt;300 pg/mL), respectively, when the study began (Table 1). This finding was not associated with the patients\u0026rsquo; gender or COVID-19 symptomatology. Elevated levels of both factors were more likely to occur in older patients, since individuals with altered characteristics were significantly older than those whose parameters were within the normal range (Student\u0026rsquo;s t test, p\u0026lt;0.05, for both) (Figure 1B). With respect to individuals\u0026rsquo; existing underlying pathologies a higher prevalence of altered NT-proBNP was observed in patients who were suffering from an underlying cardiopathy (Pearson\u0026rsquo;s chi-squared test, p\u0026lt;0.05)\u0026nbsp;(Figure 1C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCellular and humoral responses to the three virus models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCellular and humoral memory responses to the three viral antigens were determined. Cellular responses were measured by IFN-g\u0026nbsp;ELISpot\u0026nbsp;and granzyme B ELISpot. Humoral responses were measured as the level of specific antibodies against the different viruses in sera. It was not possible to obtain all results for all patients, especially in the case of granzyme B ELISpot since not enough cells could be isolated from some patients. Complete results of the three measurements were achieved in 74.6% of patients for CMV, 84.7% for influenza and 83% for SARS-CoV-2 of the 59 patients enrolled in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo responses were obtained for some measurements, especially cellular memory measured by granzyme B ELIspot (Figure 2A). No cellular or humoral response was detected in 17% of CMV (corresponding to seronegative CMV patients) and 3% of SARS-CoV-2 cases. However, most patients showed both cellular (with at least one of the two measurements obtained) and humoral responses to CMV, influenza and SARS-CoV-2 viruses (83%, 83% and 85%, respectively) (Figure 2B).\u003c/p\u003e\n\u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003eIsolated cellular responses with no accompanying humoral response were seen for influenza in 17% of the patients (Figure 2B). Conversely, an isolated humoral response with no detectable cellular response was observed for SARS-CoV-2 in 12% of the patients. Of these, 14% showed anti-N antibodies and the remaining 86% had both anti-N and anti-S antibodies. Likewise, 96% of the patients with humoral and cellular responses had both anti-N and anti-S antibodies, while the other 4% had isolated anti-N (2%) or anti-S (2%) antibodies (Figure 2B).\u003c/p\u003e\n\u003cp\u003eIn all cases, positive cellular responses occurred mainly at the expense of IFN-g-ELISpot measurement or both IFN-g and granzyme B ELIspot. Just in the case of cellular responses to SARS-CoV-2, 5% of the patients showed granzyme B-ELISpot-positive results with negative IFN-g-ELISpot. (Figure 2B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea. Anti-CMV responses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEighty three percent of the patients were CMV-seropositive. Distributions of the different response measurements against CMV are represented in Figure 3A. As mentioned above, humoral and cellular responses to CMV matched perfectly, whereby all seronegative patients were also negative for cellular responses, while the seropositive group of patients showed cellular responses. There was a positive correlation in the seropositive CMV patients between the two cellular responses measured as IFN-g\u0026nbsp;and granzyme B-producer-specific T lymphocytes (Spearman test; r=0.6, p\u0026lt;0.01). However, no significant correlation was observed between the anti-CMV cellular and humoral responses (Supplementary Figure 2A).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb. Anti-influenza responses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe influenza-vaccinated status of all patients was known: 55.9% of them had been vaccinated in the most recent vaccination campaign. Nevertheless, it can be assumed that all the patients, vaccinated and unvaccinated, had been exposed to this seasonal virus during their lives. In fact, the cellular memory response to influenza (IFN-g\u0026nbsp;and/or granzyme-B-producing T lymphocytes) was detected in all the patients. Regarding the humoral response, 94% of vaccinated and 69% of unvaccinated patients had antibodies against influenza at a level above our detection threshold. The great majority (80%) of the 17% patients who showed cellular responses without antibodies to the influenza vaccine were unvaccinated (Figure 2B).\u0026nbsp;As expected, the group of vaccinated individuals had a significantly higher specific cellular memory response (Mann\u0026ndash;Whitney test, p\u0026lt;0.05 for IFN-g\u0026nbsp;and p\u0026lt;0.01 for granzyme B producer T lymphocytes per 10\u003csup\u003e6\u003c/sup\u003e T lymphocytes) and anti-influenza antibody titre (Mann\u0026ndash;Whitney test, p\u0026lt;0.01) compared with the unvaccinated group (Figure 3B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe two different measurements of cellular response (IFN-g\u0026nbsp;and granzyme B production) and the values for IFN-g-producer T lymphocytes and humoral response against influenza virus were both positively correlated (Spearman test; r=0.6, p\u0026lt;0.01 and r= 0.3, p\u0026lt;0.05, respectively) (Supplementary Figure 2B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec. Anti-SARS-CoV-2 responses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the patients had been infected with SARS-CoV-2 for the first time and an adequate response to the virus was expected as they were asymptomatic or suffered only very mild symptoms. As described above, cellular or humoral responses to SARS-CoV-2 virus were observed in 97% of the cases (85% showed both types of response, while 12% presented only a humoral response). No response was detected in two patients studied by any of the methods used (Figure 2B). Distributions of the different response measurements against SARS-CoV-2 are represented in figure 3C. As described above, some biochemical characteristics related to the severity of the SARS-CoV-2 infection, D-Dimer and NT-proBNP levels were measured. No significant differences were found in the responses to SARS-CoV-2 between patients with and without altered parameters (Supplementary Figure 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePositive correlations were noted between cellular responses, measured as specific IFN-g-producer T lymphocytes, and humoral responses to SARS-CoV-2. The correlation was higher for anti-N antibodies (Spearman test, r=0.5, p\u0026lt;0.01) than for anti-S antibodies (Spearman test; r=0.3, p\u0026lt;0.05). As expected, the two humoral response measurements were significantly positively correlated (Spearman test, r=0.5, p\u0026lt;0.01). However, no significant correlation was observed between the two cellular response measurements (Supplementary Figure 2C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelation between viral antigen model responses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComparing the cellular responses to the three viruses showed that the specific anti-CMV cellular response was stronger, in the CMV-seropositive group of patients, than the cellular response to the influenza virus, and both were stronger than the response to SARS-CoV-2, particularly when the cellular response was measured with IFN-g\u0026nbsp;ELIspot, since the differences between all the three viral antigens responses were statistically significant (Bonferroni test, p\u0026lt;0.01). When measured by Granzyme B ELIspot, there were significant differences between CMV and SARS-CoV-2 (Bonferroni test, p\u0026lt;0.05) and between influenza and SARS-CoV-2 (Bonferroni test, p\u0026lt;0.01) but not between CMV and influenza in either of the unvaccinated and vaccinated patient groups (Figure 4). Humoral responses could not be compared because they were measured in different ways.\u003c/p\u003e\n\u003cp\u003eWe found a significant positive correlation between cellular responses to influenza and SARS-CoV-2 for IFN-g-producer T lymphocytes (Spearman test; r=0.4, p\u0026lt;0.01) and granzyme B-producer T lymphocytes (Spearman test; r=0.4, p\u0026lt;0.05) although these were not apparent at the humoral level (Figure 5A). On the other hand, there were no significant correlations of any of the measurements of the responses between CMV and SARS-CoV-2 or between CMV and influenza. However, comparing influenza and SARS-CoV-2 specific responses in seropositive-CMV and seronegative-CMV patients showed them to be consistently lower in CMV-seropositive than in CMV seronegative patients, in both cases (Figure 5B and 5C). This comparison was not significant probably because there were too few CMV-seronegative individuals in the sample for a difference of that magnitude to be significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacterization of the responses to the three antigen models in relation to the T lymphocyte phenotype\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImmunosenescence may be related to the intensity of responses to the different virus infections.\u0026nbsp;The\u0026nbsp;immunophenotype of T lymphocytes by their degree of maturation (na\u0026iuml;ve/memory) and functional differentiation of CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes (Th1/Th2/Th17) and their correlations with the viral responses were analysed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ea. CMV\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAgreeing with what is already well known and stablished, differences in the distribution of the T lymphocyte subpopulations were observed between CMV-seropositive and CMV-seronegative individuals (Supplementary Figure 4A). CMV-seronegative patients had a significantly lower proportion of CD4\u003csup\u003e+\u003c/sup\u003eEM3 than did CMV-seropositive individuals (median: 0.03% vs 6.8%; Mann\u0026ndash;Whitney test, p\u0026lt;0.01). However, the median proportions of CD4\u003csup\u003e+\u003c/sup\u003eCM and CD8\u003csup\u003e+\u003c/sup\u003eN were significantly higher in CMV-seronegative than in CMV-seropositive patients (30.4% vs 22.6%; Mann\u0026ndash;Whitney test, p\u0026lt;0.05, and 16.2% vs 7.1%; Mann Whitney test, p\u0026lt;0.01, respectively) (Supplementary Figure 4A). With respect to the distribution of the functional subpopulations of CD4\u003csup\u003e+\u003c/sup\u003e memory T lymphocytes, there was a significantly lower mean percentage of Th1 in CMV-seronegative than in CMV-seropositive patients (29.2% vs 39.2%; Student\u0026rsquo;s t test, p\u0026lt;0.01) (Supplementary Figure 4B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering the CMV-seropositive group of patients, the cellular response (IFN-g\u0026nbsp;and/or granzyme B-producing T lymphocytes) was negatively correlated with CD4\u003csup\u003e+\u003c/sup\u003eN, CD4\u003csup\u003e+\u003c/sup\u003eEM1 and CD8\u003csup\u003e+\u003c/sup\u003eN while there was a significant positive correlation with CD4\u003csup\u003e+\u003c/sup\u003eEM4. Regarding the humoral responses to CMV, there were negative correlations with CD4\u003csup\u003e+\u003c/sup\u003eCM, CD4\u003csup\u003e+\u003c/sup\u003eEM1, CD8\u003csup\u003e+\u003c/sup\u003eN CD8\u003csup\u003e+\u003c/sup\u003eCM and CD8\u003csup\u003e+\u003c/sup\u003eEM1. However, a significant positive correlation was seen with the CD4\u003csup\u003e+\u003c/sup\u003eEM4, CD4\u003csup\u003e+\u003c/sup\u003eEM3, CD4\u003csup\u003e+\u003c/sup\u003eEMRA, CD8\u003csup\u003e+\u003c/sup\u003eEM3 and CD8\u003csup\u003e+\u003c/sup\u003eEMRA subsets (Figure 6A). In the case of the functional differentiation of memory CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes, the humoral response to CMV was positively correlated with Th1 type and negatively correlated with Th2 and Th17 (Figure 6B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb. Influenza\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt is expected that recently vaccinated patients are a more homogeneous group with respect to the immune responses generated against influenza seasonal pathogen. In vaccinated patients, the cellular memory responses to the influenza virus (IFN-g\u0026nbsp;and/or granzyme B-producing T lymphocytes) were negatively correlated with CD4\u003csup\u003e+\u003c/sup\u003eEM3, CD8\u003csup\u003e+\u003c/sup\u003eEM3 and CD8\u003csup\u003e+\u003c/sup\u003eEMRA cells, and positively correlated with CD4\u003csup\u003e+\u003c/sup\u003eEM4 and CD4\u003csup\u003e+\u003c/sup\u003eEM1 cells. No significant correlations were noted between the level of antibodies and the distribution of any of the subpopulations (Figure 6A). Regarding the functional differentiation of memory CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes, the cellular response measured as IFN-g-producer-specific T lymphocytes was negatively correlated with the Th2 subpopulation but positively correlated with the Th1.17 subpopulation (Figure 6B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec. SARS-CoV-2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eT lymphocyte cellular responses to SARS-CoV-2 (IFN-g\u0026nbsp;and/or granzyme B-producing T lymphocytes) were correlated negatively with CD4\u003csup\u003e+\u003c/sup\u003eEM4 and positively with CD4\u003csup\u003e+\u003c/sup\u003eEMRA. Regarding CD8\u003csup\u003e+\u003c/sup\u003e T lymphocyte responses, there was a negative correlation between cellular responses and the CD8\u003csup\u003e+\u003c/sup\u003eEM3 and CD8\u003csup\u003e+\u003c/sup\u003eEMRA subsets. Analysis of the humoral responses revealed that the level of anti-S antibodies was negatively correlated with the CD4\u003csup\u003e+\u003c/sup\u003eN, CD4\u003csup\u003e+\u003c/sup\u003eCM, CD4\u003csup\u003e+\u003c/sup\u003eEM1 and CD8\u003csup\u003e+\u003c/sup\u003eN subsets, whereas anti-N antibodies were not significantly correlated with the distribution of any of the subpopulations (Figure 6A). In terms of the functional differentiation of memory CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes, the humoral response, measured as anti-S antibodies, was negatively correlated with the Th2 and Th17 subpopulations. The negative correlation with Th17 lymphocytes was also seen at the cellular level (Figure 6B).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this work we have characterised the cellular and humoral immunoresponses to three viral infection models in immunocompetent older adults. It is well known that gradual changes that trigger the deterioration of the immune system occur as an individual ages. These immunosenescence processes are also accompanied by a chronic low-grade inflammation, known as inflammaging, which is increased by some factors, CMV infection being one of the most widely studied (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). All these changes associated with aging affect innate and especially adaptive immunity, in which T lymphocytes have a crucial role in controlling the mechanisms of viral infections (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAll the patients studied in this work were older adults that had recently been infected with SARS-CoV-2 for the first time, but who had been asymptomatic or had experienced only very mild symptoms. This group of patients could be considered less affected by immunosenesce than indivuals in the same range of age since the risk of severe illness from COVID-19 is well known to increase with age and older adults are more likely to have poor outcomes (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In addition to not presenting clinical outcomes related to SARS-CoV-2 infection, the typical laboratory abnormalities associated with this infection, such as leukopenia or elevated levels of D-Dimer and NT-proBNP serum biomarkers, had already returned to normal in the majority of the patients by the time the study began (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The elevated levels of the biochemical factors, D-Dimer and NT-proBNP, detected in some of the patients studied are related to age and the presence of underlying cardiac pathology, as reported elsewhere (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), rather than to the severity of the symptoms or the strength of the response to SARS-CoV-2. For these reasons, there was no bias regarding the clinical status of the patients in this study.\u003c/p\u003e \u003cp\u003eWe know which individuals had been vaccinated in the previous influenza vaccination campaign, but information about the history of influenza infections or previous vaccinations was not available, which is a limitation of the study. The individuals studied therefore form a heterogeneous group with respect to influenza virus contact during their lives. Vaccinated individuals make up a more homogeneous group with respect to the immune memory that they would have developed to this seasonal pathogen. However, it is important to bear in mind that the immunoresponse generated in this group of patients is almost certainly not only due to the most recent vaccination received since it is very likely that they had been in contact with the virus at other times during their lives.\u003c/p\u003e \u003cp\u003eSpecific adaptive cellular responses to viruses are mainly orchestrated by T lymphocytes, especially by cytotoxic CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes. In this study cellular responses are measured by detecting IFN-γ and granzyme B release after specific antigen stimulation. IFN-γ is produced by T lymphocytes, mainly CD4\u003csup\u003e+\u003c/sup\u003e Th1 and CD8\u003csup\u003e+\u003c/sup\u003e, while granzyme B is basically produced by CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The humoral response, which was also measured in these patients, was also involved in these infections through the production of neutralizing antibodies that act against the virus (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCMV-seronegative patients, as expected, did not show cellular responses neither as they never have been infected by CMV. There were also two individuals in whom no cellular or humoral responses were detected against SARS-CoV-2. The lack of response of these two patients was surprising since all 59 individuals had been diagnosed with SARS-CoV-2 infection some months before. One possible explanation is that the RT-PCR used to diagnose SARS-CoV-2 infection has a specificity of greater than 95% (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), meaning that up to 5% of results could be false-positives. However, all the individuals studied were positive at least twice for the RT-PCR diagnostic test, making it unlikely that these two people were false-positives cases. On the other hand, it is important to bear in mind that all the individuals studied had had just one encounter with the SARS-CoV-2 virus, so it is possible that, in some cases, this stimulus was not strong enough to elicit a detectable memory response. This lack of response has been described before, especially in patients whose infection caused mild or no symptoms (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), as is the case of the patients studied in this work. With the exception of these two cases, all the patients showed cellular and/or humoral responses to the three viruses. The responses generated are known to depend largely on the conditions of antigen exposure and persistence (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), which could explain some of the differences found between the responses to the three viruses. CMV is a chronic virus whose exposure persists over time because the immune system is exposed to the antigen at each reactivation (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This explains why responses to this virus in CMV-infected individuals were the strongest and the most consistent. Conversely, the influenza virus is a seasonal, rather than a chronic virus, exposure to which is frequent but not persistent over a lifetime, and the antigens to which people are exposed are continuously changing (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In this case, as expected, most of the patients recently vaccinated against influenza developed detectable humoral and cellular responses. Many of the unvaccinated people showed a cellular response but no detectable humoral response, possibly because most of them had not been in contact with the viral antigen for a longer time than the individuals vaccinated in the most recent campaign; it is well known that antibodies have a shorter live than cellular memory (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). In the case of SARS-CoV-2 responses, some individuals had anti-SARS-CoV-2 antibodies but no detectable specific T cellular response. As mentioned above, asymptomatic or mild disease triggers a less intense memory response. It is likely that in this small group of patients the single encounter with the SARS-CoV-2 antigen enabled memory T cells to develop, although not to detectable levels. This is consistent with what happens in other coronavirus infections, such as SARS and MERS, in which higher levels of specific T cells against the virus were found in patients with more severe symptoms (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). The persistence of exposure to the three viruses differs, with chronic CMV being the most and SARS-CoV-2 the least persistent. This concurs with the results of the comparison of the strengths of cellular responses made in this study. However, it is also important to bear in mind that the antigenic stimuli used to measure the cellular responses could be immunogenically differently.\u003c/p\u003e \u003cp\u003eBeside this, the correlations between the different virus responses reflect the greater similarity of the responses to the novel SARS-CoV-2 virus to that of influenza than to the response to chronic CMV. To investigate this in greater depth, the different responses were characterized in more detail taking into account the immunophenotyping of the lymphocyte subpopulations. CMV is a chronic virus which infection is characterized by the generation of a more differentiated T lymphocyte phenotype, due to the persistent exposure of the immune system to this virus over time once the individual has been infected (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). This effect was also seen in our patients whereby CMV-seropositive individuals tended to have a higher frequency of highly differentiated T lymphocytes and a lower frequency of na\u0026iuml;ve T lymphocytes than CMV-seronegative patients. Consistent with this, it was observed that the stronger the responses were to CMV the more abundant were T lymphocytes with a differentiated phenotype. Many studies support this finding. CMV infection triggers the activation of B, T CD4\u003csup\u003e+\u003c/sup\u003e and T CD8\u003csup\u003e+\u003c/sup\u003e lymphocytes, and the persistent production of CMV virus results in a continuous and peribiomic stimulation of these cells, especially T CD8\u003csup\u003e+\u003c/sup\u003e (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Each viral reactivation cycle generates a subset of CMV-specific T lymphocytes, which thereby reduces the T lymphocyte repertoire. The majority of these CMV-specific T lymphocytes are known to be terminally differentiated, corresponding to an exhausted and immunosenescent T cell phenotype (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). This situation of continuous immune stimulation also favours the pro-inflammatory chronic state that typically accompanies aging (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Otherwise, our results suggest that a better cellular response to the influenza virus is associated with a less T lymphocyte-differentiated phenotype. This is consistent with findings reported in young mice infected with the influenza virus, whose CD4\u003csup\u003e+\u003c/sup\u003e T lymphocyte compartment is comprised mainly of na\u0026iuml;ve cells that rapidly proliferate and differentiate into influenza-specific effector subsets that allow the clearance of the virus (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). These correlations were seen at the cellular response level in vaccinated individuals, but there was no correlation with the humoral response in these patients. This might be because recently vaccinated patients, as expected, given the purpose of vaccination (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), had elevated levels of antibodies against influenza at the time of the study, maybe independently of their T lymphocyte phenotype. Consistent with the correlations of the responses seen, SARS-CoV-2 showed mostly similar results to those of influenza with respect to cellular responses, especially CD8\u0026thinsp;+\u0026thinsp;T lymphocytes ones, provoking stronger cellular responses when less-differentiated T CD8\u0026thinsp;+\u0026thinsp;lymphocyte phenotypes were predominant. However, humoral responses to the SARS-CoV-2 virus (especially levels of anti-S antibodies) were negatively correlated with the abundance of na\u0026iuml;ve and less-differentiated memory T lymphocytes, similar to what happens in CMV. This could be because individuals with a more senescent immune system are less capable of generating an adequate cellular response \u0026mdash;the main type of response for controlling viral infections\u0026mdash; to this new viral antigen. Therefore, in these cases, the SARS-CoV-2 infection could persist for longer and could allow a stronger humoral response to be generated before the infection is resolved. This explanation is consistent with that previously proposed by Wu et al., who reported that severe SARS-CoV-2 patients had higher IgG-S and IgG-N titres (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), and with our earlier work, which determined that although there were no significant differences in cellular responses between hospital-admitted and non-admitted patients, anti-S and anti-N antibody titres were significantly higher in patients who required admission (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding T CD4\u003csup\u003e+\u003c/sup\u003e differentiation into Th1/Th2/Th17 phenotypes, the Th1 response is the most prevalent in viral infections. Antiviral IFN-γ, mainly produced by this Th1 subset, enhances the stimulation of the adaptive antiviral response to clear the infection and generate a memory to protect against future infections. Accordingly, our results also implied that the immune response to the three viruses was associated with a Th1/Th2/Th17 balance in favour of Th1. These responses were positively correlated with the Th1 cells, as occurs in the case of CMV, coinciding with what was previously reported (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), or negatively correlated with the Th2 cells, as occurs in CMV, influenza and SARS-CoV-2. In the case of the response to influenza, it may seem to contradict our results that most of the licensed vaccines have been developed for the purpose of ensuring a Th2 response and the consequent production of antibodies (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). However, these vaccines also collaterally induce cellular responses that favour the Th1 phenotype. This finding, and the greater persistence of the memory cellular response, are evidences supporting the proposal to modify the current criteria for developing influenza vaccines to ensure T cell-mediated protection, as other studies have already suggested (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). In the case of SARS-CoV-2 it is the humoral response that is negatively correlated with Th2 cells. Higher levels of Th2 cytokines, especially IL-4 and IL-5, can inhibit protective Th1 antiviral responses in COVID-19 patients. This was seen mainly in patients with severe COVID-19 disease, so it was hypothesized that Th2 inhibition might offer protection against severe COVID-19 symptoms, as seems to have happened in patients who were asymptomatic or who had mild COVID-19 disease (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Generally, there seem to be no differences in the three viruses\u0026rsquo; responses with respect to the distribution of the various functional differentiation subpopulations of memory CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, this work allowed us to accurately characterise the cellular and humoral responses generated against three viral infection models \u0026mdash;chronic, seasonal and novel infection\u0026mdash; in immunocompetent older adults. Average older adults, whose immunosenescence would be more pronounced, partly due to a higher prevalence and persistence of CMV chronic infection over their lifetime, would be less effective for fighting an infection generated by a novel antigen. The immune system was shown to react in a different way and with different intensity, depending on the durability and type of viral stimulus with which it is in contact. The results suggest that specific responses, especially cellular responses, to novel pathogens resemble the memory response enhanced by repeated, but not chronic, viral encounters. Both responses to novel and repeated pathogens may be favoured by a more na\u0026iuml;ve CD8\u0026thinsp;+\u0026thinsp;T lymphocyte phenotype compared with what happens when the immunosenescence is induced by chronic CMV infection. The subpopulation distribution and the level of antigen-specific T lymphocytes acting against known previous pathogens could be good biomarkers of the immunocompetence status of older adults, reflecting their ability to generate specific memory responses to new pathogens.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all the volunteers before they participated in the study. The study was approved in accordance with the Declaration of Helsinki by the ethics committee of the Hospital Central de Asturias (Oviedo, Spain) (n\u0026ordm; 2020.269).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComplete written informed consent was obtained from all the volunteers for the publication of this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be deposited in the Instituto de Salud Carlos III (ISCIII)-COVID19 repository, constituted to deposit data generated in the studies funded by the call for \u0026ldquo;Proyectos de investigaci\u0026oacute;n sobre el SARS-COV-2 Y LA ENFERMEDAD COVID-19\u0026rdquo;.\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eAlso raw and derived data supporting the findings of this study are available from the corresponding author [R. Alonso-Arias] on request.\u0026nbsp;\u003c/h4\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was partially supported by the Instituto de Salud Carlos III (COV20/0968) and by grant PI17/00714 from the Spanish I+D+i 2013\u0026ndash;2016 State Program, which was cofounded by the Instituto de Salud Carlos III and the European Regional Development Fund (ERDF). Bueno-Garc\u0026iacute;a E is sponsored by the Principado de Asturias (Programa de Ayudas \u0026ldquo;Severo Ochoa\u0026rdquo;; BP20-030).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors\u0026rsquo; responsibilities were as follows: \u003cstrong\u003eR Alonso-Arias, MA Moro-Garc\u0026iacute;a\u003c/strong\u003e and \u003cstrong\u003eS Alonso-Alvarez\u003c/strong\u003e designed the study; \u003cstrong\u003eA Garc\u0026iacute;a-Torre, E Bueno-Garc\u0026iacute;a, B Rioseras, R L\u0026oacute;pez-Mart\u0026iacute;nez, V Men\u0026eacute;ndez-Garc\u0026iacute;a\u0026nbsp;\u003c/strong\u003eprepared protocols, collected and processed all the samples, performed or oversaw the experimental protocols, and analysed data; \u003cstrong\u003eR Alonso-Arias\u003c/strong\u003e, \u003cstrong\u003eB Rioseras\u003c/strong\u003e wrote the manuscript; \u003cstrong\u003eA Lluna-Gonz\u0026aacute;lez, A Sousa-Fern\u0026aacute;ndez, M Fern\u0026aacute;ndez-Goudin, L Campos-Riopedre, C Castro-Cueto, AB P\u0026eacute;rez-Fern\u0026aacute;ndez, A Alonso-Rodr\u0026iacute;guez, C Men\u0026eacute;ndez-Pe\u0026ntilde;a, L Men\u0026eacute;ndez-Pe\u0026ntilde;a, N Garc\u0026iacute;a-Arnaldo, E Feito-D\u0026iacute;az, A Fern\u0026aacute;ndez-Lorences, A Fraile-Manzano, C Fern\u0026aacute;ndez-Iglesias, JA Rivera, C P\u0026eacute;rez-Fonseca, E Urdiales-Ruano, M Deb\u0026aacute;n-Fern\u0026aacute;ndez, H Mendes-Moreira\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003e\u0026nbsp;P Herrero-Puente\u003c/strong\u003e selected and recruited volunteers and organized their blood extractions and collected their clinical information; \u003cstrong\u003eMA Moro-Garc\u0026iacute;a\u003c/strong\u003e and \u003cstrong\u003eS Alonso-Alvarez\u003c/strong\u003e reviewed the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the Instituto de Salud Carlos III for supporting the study and to the donors for their selfless contribution to help us better understand immunity to SARS-CoV-2 infection.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWik JA, Skalhegg BS. T cell metabolism in infection. \u003cem\u003eFront Imm\u003c/em\u003e\u003cem\u003eunol\u003c/em\u003e 2022;13:840610.\u003c/li\u003e\n\u003cli\u003eCunha LL, Valsecchi V, Ward LS. Investigating population-level immunosenescence: From bench to bedside. \u003cem\u003eFront Immunol\u003c/em\u003e 2022;13:949928.\u003c/li\u003e\n\u003cli\u003eAlford CA, Stagno S, Pass RF, Britt WJ. Congenital and perinatal cytomegalovirus infections. \u003cem\u003eRev Infect Dis\u003c/em\u003e 1990;12 Suppl 7:S745-753.\u003c/li\u003e\n\u003cli\u003eNikolich-Zugich J, van Lier RAW. Cytomegalovirus (cmv) research in immune senescence comes of age: Overview of the 6th international workshop on cmv and immunosenescence. \u003cem\u003eGeroscience\u003c/em\u003e 2017;39:245-249.\u003c/li\u003e\n\u003cli\u003eMoro-Garcia MA, Alonso-Arias R, Lopez-Vazquez A, Suarez-Garcia FM, Solano-Jaurrieta JJ, Baltar J, Lopez-Larrea C. Relationship between functional ability in older people, immune system status, and intensity of response to cmv. \u003cem\u003eAge (Dordr)\u003c/em\u003e 2012;34:479-495.\u003c/li\u003e\n\u003cli\u003eAlonso-Alvarez S, Colado E, Moro-Garcia MA, Alonso-Arias R. Cytomegalovirus in haematological tumours. \u003cem\u003eFront Immunol\u003c/em\u003e 2021;12:703256.\u003c/li\u003e\n\u003cli\u003eIglesias-Escudero M, Moro-Garcia MA, Marcos-Fernandez R, Garcia-Torre A, Alvarez-Arguelles ME, Suarez-Fernandez ML, Martinez-Camblor P, Rodriguez M, Alonso-Arias R. Levels of anti-cmv antibodies are modulated by the frequency and intensity of virus reactivations in kidney transplant patients. \u003cem\u003ePLoS One\u003c/em\u003e 2018;13:e0194789.\u003c/li\u003e\n\u003cli\u003eGarcia-Torre A, Bueno-Garcia E, Lopez-Martinez R, Rioseras B, Diaz-Molina B, Lambert JL, Quiros C, Alonso-Alvarez S, Alonso-Arias R, Moro-Garcia MA. Cmv infection is directly related to the inflammatory status in chronic heart failure patients. \u003cem\u003eFront Immunol\u003c/em\u003e 2021;12:687582.\u003c/li\u003e\n\u003cli\u003eMoro-Garcia MA, Lopez-Iglesias F, Marcos-Fernandez R, Bueno-Garcia E, Diaz-Molina B, Lambert JL, Suarez-Garcia FM, Moris de la Tassa C, Alonso-Arias R. More intensive cmv-infection in chronic heart failure patients contributes to higher t-lymphocyte differentiation degree. \u003cem\u003eClin Immunol\u003c/em\u003e 2018;192:20-29.\u003c/li\u003e\n\u003cli\u003eYang TO, Chuang YF, Chiu YL. T-cell aging in end-stage renal disease: An evolving story with cmv. \u003cem\u003eMed Microbiol Immunol\u003c/em\u003e 2019;208:281-287.\u003c/li\u003e\n\u003cli\u003eMaruyama T, Fujisawa T, Suga S, Nakamura H, Nagao M, Taniguchi K, Tsutsui K, Ihara T, Niederman MS. Outcomes and prognostic features of patients with influenza requiring hospitalization and receiving early antiviral therapy: A prospective multicenter cohort study. \u003cem\u003eChest\u003c/em\u003e 2016;149:526-534.\u003c/li\u003e\n\u003cli\u003eGarg S, Jain S, Dawood FS, Jhung M, Perez A, D\u0026apos;Mello T, Reingold A, Gershman K, Meek J, Arnold KE, et al. Pneumonia among adults hospitalized with laboratory-confirmed seasonal influenza virus infection-united states, 2005-2008. \u003cem\u003eBMC Infect Dis\u003c/em\u003e 2015;15:369.\u003c/li\u003e\n\u003cli\u003eNypaver C, Dehlinger C, Carter C. Influenza and influenza vaccine: A review. \u003cem\u003eJ Midwifery Womens Health\u003c/em\u003e 2021;66:45-53.\u003c/li\u003e\n\u003cli\u003eKeilman LJ. Seasonal influenza (flu). \u003cem\u003eNurs Clin North Am\u003c/em\u003e 2019;54:227-243.\u003c/li\u003e\n\u003cli\u003eForchette L, Sebastian W, Liu T. A comprehensive review of covid-19 virology, vaccines, variants, and therapeutics. \u003cem\u003eCurr Med Sci\u003c/em\u003e 2021;41:1037-1051.\u003c/li\u003e\n\u003cli\u003eGao YD, Ding M, Dong X, Zhang JJ, Kursat Azkur A, Azkur D, Gan H, Sun YL, Fu W, Li W, et al. Risk factors for severe and critically ill covid-19 patients: A review. \u003cem\u003eAllergy\u003c/em\u003e 2021;76:428-455.\u003c/li\u003e\n\u003cli\u003eGarcia-Torre A, Bueno-Garcia E, Lopez-Martinez R, Rioseras B, Moro-Garcia MA, Alonso-Alvarez S, Lluna-Gonzalez A, Sousa-Fernandez A, Fernandez-Gudin M, Campos-Riopedre L, et al. Surviving older patients show preserved cellular and humoral immunological memory several months after sars-cov-2 infection. \u003cem\u003eJ Gerontol A Biol Sci Med Sci\u003c/em\u003e 2022;77:33-40.\u003c/li\u003e\n\u003cli\u003eOhishi K, Ninomiya A, Kida H, Park CH, Maruyama T, Arai T, Katsumata E, Tobayama T, Boltunov AN, Khuraskin LS, et al. Serological evidence of transmission of human influenza a and b viruses to caspian seals (phoca caspica). \u003cem\u003eMicrobiol Immunol\u003c/em\u003e 2002;46:639-644.\u003c/li\u003e\n\u003cli\u003eKang I, Hong MS, Nolasco H, Park SH, Dan JM, Choi JY, Craft J. Age-associated change in the frequency of memory cd4+ t cells impairs long term cd4+ t cell responses to influenza vaccine. \u003cem\u003eJ Immunol\u003c/em\u003e 2004;173:673-681.\u003c/li\u003e\n\u003cli\u003eDadras O, SeyedAlinaghi S, Karimi A, Shamsabadi A, Qaderi K, Ramezani M, Mirghaderi SP, Mahdiabadi S, Vahedi F, Saeidi S, et al. Covid-19 mortality and its predictors in the elderly: A systematic review. \u003cem\u003eHealth Sci Rep\u003c/em\u003e 2022;5:e657.\u003c/li\u003e\n\u003cli\u003eFerrari D, Seveso A, Sabetta E, Ceriotti D, Carobene A, Banfi G, Locatelli M, Cabitza F. Role of time-normalized laboratory findings in predicting covid-19 outcome. \u003cem\u003eDiagnosis (Berl)\u003c/em\u003e 2020;7:387-394.\u003c/li\u003e\n\u003cli\u003eDraper J, Webb J, Jackson T, Jones H, Rinaldi CA, Schiff R, McDonagh T, Razavi R, G SC-W. Comparison of the diagnostic accuracy of plasma n-terminal pro-brain natriuretic peptide in patients \u0026lt;80 to those \u0026gt;80 years of age with heart failure. \u003cem\u003eAm J Cardiol\u003c/em\u003e 2018;122:2075-2079.\u003c/li\u003e\n\u003cli\u003eJohnson ED, Schell JC, Rodgers GM. The d-dimer assay. \u003cem\u003eAm J Hematol\u003c/em\u003e 2019;94:833-839.\u003c/li\u003e\n\u003cli\u003eAoshi T, Koyama S, Kobiyama K, Akira S, Ishii KJ. Innate and adaptive immune responses to viral infection and vaccination. \u003cem\u003eCurr Opin Virol\u003c/em\u003e 2011;1:226-232.\u003c/li\u003e\n\u003cli\u003eMorris AG. Interferons. \u003cem\u003eImmunol Suppl\u003c/em\u003e 1988;1:43-45.\u003c/li\u003e\n\u003cli\u003eAli MG, Zhang Z, Gao Q, Pan M, Rowan EG, Zhang J. Recent advances in therapeutic applications of neutralizing antibodies for virus infections: An overview. \u003cem\u003eImmunol Res\u003c/em\u003e 2020;68:325-339.\u003c/li\u003e\n\u003cli\u003eHealy B, Khan A, Metezai H, Blyth I, Asad H. The impact of false positive covid-19 results in an area of low prevalence. \u003cem\u003eClin Med (Lond)\u003c/em\u003e 2021;21:e54-e56.\u003c/li\u003e\n\u003cli\u003eBoechat JL, Chora I, Morais A, Delgado L. The immune response to sars-cov-2 and covid-19 immunopathology - current perspectives. \u003cem\u003ePulmonology\u003c/em\u003e 2021;27:423-437.\u003c/li\u003e\n\u003cli\u003eHarari A, Vallelian F, Meylan PR, Pantaleo G. Functional heterogeneity of memory cd4 t cell responses in different conditions of antigen exposure and persistence. \u003cem\u003eJ Immunol\u003c/em\u003e 2005;174:1037-1045.\u003c/li\u003e\n\u003cli\u003eKalia V, Sarkar S, Ahmed R. Cd8 t-cell memory differentiation during acute and chronic viral infections. \u003cem\u003eAdv Exp Med Biol\u003c/em\u003e 2010;684:79-95.\u003c/li\u003e\n\u003cli\u003eKim J, Kim AR, Shin EC. Cytomegalovirus infection and memory t cell inflation. \u003cem\u003eImmune Netw\u003c/em\u003e 2015;15:186-190.\u003c/li\u003e\n\u003cli\u003eJaneway C, Travers P, Walport M, Shlomchik M. Immunobiology: The immune system in health and disease, 5th edition ed. United Kingdom; Garland Science; 2001.\u003c/li\u003e\n\u003cli\u003eLe Bert N, Tan AT, Kunasegaran K, Tham CYL, Hafezi M, Chia A, Chng MHY, Lin M, Tan N, Linster M, et al. Sars-cov-2-specific t cell immunity in cases of covid-19 and sars, and uninfected controls. \u003cem\u003eNature\u003c/em\u003e 2020;584:457-462.\u003c/li\u003e\n\u003cli\u003eSariol A, Perlman S. Lessons for covid-19 immunity from other coronavirus infections. \u003cem\u003eImmunity\u003c/em\u003e 2020;53:248-263.\u003c/li\u003e\n\u003cli\u003eKhairallah C, Dechanet-Merville J, Capone M. Gammadelta t cell-mediated immunity to cytomegalovirus infection. \u003cem\u003eFront Immunol\u003c/em\u003e 2017;8:105.\u003c/li\u003e\n\u003cli\u003eWertheimer AM, Bennett MS, Park B, Uhrlaub JL, Martinez C, Pulko V, Currier NL, Nikolich-Zugich D, Kaye J, Nikolich-Zugich J. Aging and cytomegalovirus infection differentially and jointly affect distinct circulating t cell subsets in humans. \u003cem\u003eJ Immunol\u003c/em\u003e 2014;192:2143-2155.\u003c/li\u003e\n\u003cli\u003eKarrer U, Sierro S, Wagner M, Oxenius A, Hengel H, Koszinowski UH, Phillips RE, Klenerman P. Memory inflation: Continuous accumulation of antiviral cd8+ t cells over time. \u003cem\u003eJ Immunol\u003c/em\u003e 2003;170:2022-2029.\u003c/li\u003e\n\u003cli\u003ePawelec G, Gouttefangeas C. T-cell dysregulation caused by chronic antigenic stress: The role of cmv in immunosenescence? \u003cem\u003eAging Clin Exp Res\u003c/em\u003e 2006;18:171-173.\u003c/li\u003e\n\u003cli\u003eLanzer KG, Johnson LL, Woodland DL, Blackman MA. Impact of ageing on the response and repertoire of influenza virus-specific cd4 t cells. \u003cem\u003eImmun Ageing\u003c/em\u003e 2014;11:9.\u003c/li\u003e\n\u003cli\u003eWu J, Liang B, Chen C, Wang H, Fang Y, Shen S, Yang X, Wang B, Chen L, Chen Q, et al. Sars-cov-2 infection induces sustained humoral immune responses in convalescent patients following symptomatic covid-19. \u003cem\u003eNat Commun\u003c/em\u003e 2021;12:1813.\u003c/li\u003e\n\u003cli\u003eRentenaar RJ, Gamadia LE, van DerHoek N, van Diepen FN, Boom R, Weel JF, Wertheim-van Dillen PM, van Lier RA, ten Berge IJ. Development of virus-specific cd4(+) t cells during primary cytomegalovirus infection. \u003cem\u003eJ Clin Invest\u003c/em\u003e 2000;105:541-548.\u003c/li\u003e\n\u003cli\u003eKim YH, Hong KJ, Kim H, Nam JH. Influenza vaccines: Past, present, and future. \u003cem\u003eRev Med Virol\u003c/em\u003e 2022;32:e2243.\u003c/li\u003e\n\u003cli\u003ePleguezuelos O, Robinson S, Fernandez A, Stoloff GA, Mann A, Gilbert A, Balaratnam G, Wilkinson T, Lambkin-Williams R, Oxford J, et al. A synthetic influenza virus vaccine induces a cellular immune response that correlates with reduction in symptomatology and virus shedding in a randomized phase ib live-virus challenge in humans. \u003cem\u003eClin Vaccine Immunol\u003c/em\u003e 2015;22:828-835.\u003c/li\u003e\n\u003cli\u003ePavel AB, Glickman JW, Michels JR, Kim-Schulze S, Miller RL, Guttman-Yassky E. Th2/th1 cytokine imbalance is associated with higher covid-19 risk mortality. \u003cem\u003eFront Genet\u003c/em\u003e 2021;12:706902.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"immunity-and-ageing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iage","sideBox":"Learn more about [Immunity \u0026 Ageing](http://immunityageing.biomedcentral.com/)","snPcode":"12979","submissionUrl":"https://submission.nature.com/new-submission/12979/3","title":"Immunity \u0026 Ageing","twitterHandle":"@ImmunAllergyBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Immunosenescence, Anti-viral immune memory, Cytomegalovirus, Influenza, SARS-CoV-2","lastPublishedDoi":"10.21203/rs.3.rs-4735076/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4735076/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMemory responses to the antigens that an individual encounters throughout life may vary with the intensity and duration of antigen contacts or even changes in immune status over time. This work aims to characterise specific responses to chronic CMV, seasonal influenza and novel SARS-CoV-2 infections in immunocompetent individuals over 60 years of age. Specific cellular and humoral responses were identified by IFN-γ and granzyme-B released by ELISpot and antibody level measurement. T lymphocyte subpopulation phenotypes were characterized by flow cytometry.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCellular and humoral responses to these viruses were detected in almost all patients. Influenza and SARS-CoV-2 cellular responses were positively correlated. There was no significant correlation of CMV with influenza or SARS-CoV-2 responses although both were consistently lower in CMV-seropositive patients. CMV responses were negatively correlated with the levels of the least differentiated subsets of T lymphocytes, and positively correlated with the most differentiated ones, contrary to what happened with the influenza responses. Nevertheless, SARS-CoV-2 cellular responses were negatively correlated with the most differentiated CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes, while humoral responses were negatively correlated with the least differentiated T lymphocytes. Responses to the three viruses were correlated with a Th1/Th2/Th17 balance in favour of Th1.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eResults indicate that memory responses differ depending on the durability of the antigen stimulus. Cellular responses to novel pathogens resemble those generated by seasonal but not chronic antigens. Subpopulation distribution and the level of specific T lymphocytes against previous pathogens could be used as immunocompetent status biomarkers in older adults reflecting their ability to generate memory responses to new pathogens.\u003c/p\u003e","manuscriptTitle":"Characterization of Specific Responses to Three Models of Viral Antigens in Immunocompetent Older Adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-18 23:07:04","doi":"10.21203/rs.3.rs-4735076/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-05T12:54:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-27T08:03:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"267362629878008972867478415955362935322","date":"2024-09-05T17:06:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81982050502093052088085930829933001216","date":"2024-09-05T14:41:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-13T08:44:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263875182367677763440406520196852264278","date":"2024-07-24T07:24:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5026232178513023620254516694484277266","date":"2024-07-23T02:12:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-19T07:44:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-19T05:28:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-19T05:28:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Immunity \u0026 Ageing","date":"2024-07-13T12:08:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"immunity-and-ageing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iage","sideBox":"Learn more about [Immunity \u0026 Ageing](http://immunityageing.biomedcentral.com/)","snPcode":"12979","submissionUrl":"https://submission.nature.com/new-submission/12979/3","title":"Immunity \u0026 Ageing","twitterHandle":"@ImmunAllergyBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f83775a9-3f1f-4178-913e-75ae9e4db6a7","owner":[],"postedDate":"August 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-09T16:08:47+00:00","versionOfRecord":{"articleIdentity":"rs-4735076","link":"https://doi.org/10.1186/s12979-024-00488-3","journal":{"identity":"immunity-and-ageing","isVorOnly":false,"title":"Immunity \u0026 Ageing"},"publishedOn":"2024-12-05 15:57:19","publishedOnDateReadable":"December 5th, 2024"},"versionCreatedAt":"2024-08-18 23:07:04","video":"","vorDoi":"10.1186/s12979-024-00488-3","vorDoiUrl":"https://doi.org/10.1186/s12979-024-00488-3","workflowStages":[]},"version":"v1","identity":"rs-4735076","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4735076","identity":"rs-4735076","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}