Spontaneous, persistent T-cell dependent IFN-γ release in patients who progress to Long COVID

Spontaneous, persistent T-cell dependent IFN-γ release in patients who progress to Long COVID | 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 Article Spontaneous, persistent T-cell dependent IFN-γ release in patients who progress to Long COVID Benjamin Krishna, Eleanor Lim, Lenette Mactavous, Sarah Jackson, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2034285/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract After acute infection with Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), a significant proportion (0.2 – 30%) of patients experience persistent symptoms beyond 12 weeks, termed Long COVID. Understanding the mechanisms which cause this debilitating disease and identifying biomarkers for diagnostic, therapeutic and monitoring purposes is urgently required. Persistently high levels of IFN-γ were detected from peripheral blood mononuclear cells (PBMCs) of Long COVID patients using highly sensitive FluoroSpot assays. This IFN-γ release was seen in the absence of ex vivo peptide stimulation and remains persistently elevated in Long Covid patients, unlike the resolution seen in patients recovering from acute SARS-CoV-2 infection. IFN-γ release was CD8 + T cell mediated and dependent on MHC-I antigen presentation by CD14 + cells. After vaccination, a significant decrease in IFN-γ correlated with resolution of some Long COVID symptoms. Our study highlights a key mechanism underlying Long COVID, enabling the search for biomarkers and therapeutics in patients with Long COVID. Biological sciences/Immunology/Cytokines/Interferons Health sciences/Biomarkers/Diagnostic markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction A significant proportion of people infected with SARS-CoV-2 exhibit persistent distressing symptoms, or the emergence of new symptoms. These are difficult to delineate into specific endotypes and are broadly grouped as post-COVID syndrome or Long COVID. There is a lack of consensus for diagnosing Long COVID and causes of Long COVID remain unclear, with resultant lack of approved pharmacological therapeutic interventions. Long COVID has a plethora of relapsing and remitting symptoms [1] and multi-systemic organ involvement [2-4] with prevalence rates ranging from 0.27%-33% [5-8]. It is likely that some differences between studies are due to differences in diagnostic criteria and definition of Long COVID. As the pathogenesis of this heterogenous disease is unclear, there is also a lack of diagnostic biomarkers and treatments. Adding to the diagnostic conundrum is the mounting evidence that Long COVID is not attributed to the severity of the preceding acute illness as it even affects patients with asymptomatic and/or mild acute COVID illness [9]. Although some patients improve without therapeutic interventions, a significant proportion of patients have not improved and/or have relapsing and worsening symptoms. Anecdotal reports from some Long COVID patients suggest that vaccination either significantly improved or ameliorated their symptoms, though the pathophysiological basis for these finding remain unknown [10]. In view of the urgent clinical need to determine the pathophysiological basis of Long COVID and ascertain the relevant biomarker/s to aid diagnosis and assist with objective disease monitoring, we studied cytokine secretion from peripheral blood mononuclear cells (PBMCs) from a cohort of undifferentiated patients diagnosed with Long COVID as defined by clinical symptoms, as well as controls of never infected individuals and longitudinal follow up of those acutely infected. To better understand the disease process and immune parameters we performed immunophenotyping combined with intracellular cytokine staining of donor PBMCs. We now show that SARS-CoV-2 infection induces a large increase in CD8 + T-cell-mediated IFN-γ release, not requiring any ex-vivo peptide stimulation. This state persists for several months post-acute infection in all patients. Patients with Long COVID fail to return to baseline IFN-γ levels, though some patients show improvement post vaccination. We identify antigen detection by CD8 + T cells as the cause of the IFN-γ production suggesting that this is caused by antigen presentation by CD14 + monocytes. Taken together, we identify IFN-γ release as a biomarker for long COVID and highlight an immunological mechanism underlying this debilitating disease, paving the way for the development of novel therapies. Results SARS-CoV-2 infection induces spontaneous and persistent IFN-γ production in Long COVID patients We recently reported a highly sensitive T cell FluoroSpot assay which measured IL-2 and IFN-γ responses in patients with Long-COVID[11]. The release of cytokines following stimulation of patient-derived PBMC with SARS-CoV-2 antigens allowed us to determine the frequency of T cells specific for overlapping peptide pools of Spike (S), Nucleocapsid (N) and membrane (M) proteins in patients with Long-COVID[11]. In addition to using in vitro peptides to stimulate cytokine release from PBMC, we also measured spontaneous cytokine release in the absence of any stimulation with SARS-CoV-2 antigens. The detection of cytokine-secreting cells from unstimulated PBMC is usually very low [12], but a significantly higher proportion / percentage of cells producing IFN-γ was clearly observed in PBMCs from Long COVID patients as compared to unexposed pre-pandemic, historic negative control samples taken between 2014-2019 (Figure 1a). We thus compared PBMC samples from Long COVID patients who had been symptomatic for at least 6 months (median symptom duration of 7 months), to PBMC from pre-pandemic negative controls (Figure 1a). As an additional control for acute SARS-CoV-2 infection, we also examined PBMC from patients taken at 28, 90 and 180 days post-positive SARS-CoV-2 RT-qPCR. PBMC from SARS-CoV-2 infected individuals showed a substantially higher spontaneous frequency of IFN-γ positive cells at 28 and 90 days post positive PCR as compared to uninfected controls. By 180 days this IFN-γ release had resolved, with IFN-γ producing cells at a similar level as uninfected controls (Figure 1b). However, a high frequency of IFN-γ release persisted in Long COVID patients even beyond 180 days of symptom onset (Figure 1c). This phenotype was also specific for IFN-γ, as we saw no change in IL-2 production (Figure S1). SARS-CoV-2 induced IFN-γ is produced by activated CD8 + T cells in a CD14 + cell-dependent mechanism To determine the cell types that produce IFN-γ in patients with Long COVID, we conducted a series of independent cell depletion assays. We removed CD4 + or CD8 + T cells, or CD14 + cells from donor PBMCs by magnetic bead cell sorting (MACS) and measured IFN-γ release from these cell populations by FluoroSpot assay. Depletion of CD14 + cells reduced IFN-γ release in all cases. Isolated CD14 + cells release negligible IFN-γ, suggesting they are required for IFN-γ production but are not the source of IFN-γ (Figure 2a). The addition of isolated CD14 + cells into the CD14 + cell-depleted PBMC population restored IFN-γ production (Figure 2a). CD8 + T cells and subpopulations of CD4 + T cells are a major source of IFN-γ. We performed the same cell depletion assays on these populations and found that depletion of CD8 + cells significantly decreased IFN-γ production. A much smaller decrease was noted after CD4 + cell depletion, which was not significant alone but did appear to be additive after CD8 + cell depletion (Figure 2b). Taken together, our data suggest that CD8 + T-cells and CD14 + cells are required for unstimulated IFN-γ production in PBMCs from Long COVID patients. To further validate our findings, we used intracellular flow cytometry to co-stain for IFN-γ with markers of cellular differentiation status. Comparing Long COVID patients to healthy controls, we found that IFN-γ was increased in CD3 + cells in general and CD8 + cells in particular, but not in CD14 + or CD4 + cells (Figure 2c). These data validate our Fluorospot data using subset-depleted PBMC showing that the IFN-γ release is predominantly CD8 + T cell mediated. As CD14 + cells are required for the release of IFN-γ in Long COVID patients (Figure 2a), we therefore tested whether antigen presentation by CD14 + cells induced T-cell dependent IFN-γ release. Anti-MHC Class I and/or Class II antibodies were used to block the cell surface of isolated CD14 + cells and subsequently cultured with CD14 + cell depleted autologous PBMC. MHC Class I blocking antibodies significantly reduced the frequency of IFN-γ positive cells, while Class II blocking antibodies had only a minor and non-significant effect (Figure 2d). Taken together our results suggest that MHC-I-dependent antigen presentation by CD14 + cells to CD8 + T cells triggers IFN-γ release. We measured absolute leukocyte subsets using Becton Dickinson Trucount tubes to identify any differences in leukocyte populations between Long COVID patients and healthy donors. Increased monocyte populations and decreased regulatory T cells were found in Long COVID patients as well as a profound decrease n NKG2C + natural killer (NK) cells, a phenotype also seen in persistent HCMV infection (Figure S2). Persistent IFN-γ release is specific to patients with Long COVID Given the known generalised cytokine perturbation in SARS-CoV-2 infection, we assessed whether Long COVID specifically correlated with increased IFN-γ or whether PBMCs from patients with Long COVID also released other cytokines. A small increase in TNF-α but no change in IL-2 or IL-10 (Figure 3a-c) was seen using Fluorospot analysis. A bead-based immunoassay (Legendplex, BioLegend) analysing 25 different cytokines showed a general increase in pro-inflammatory cytokines, though IFN-γ showed the largest increase in Long COVID patients (Figure S3). Smaller increases in G-CSF and GM-CSF, which may explain the higher monocyte numbers in figure S2, were seen. The significant difference seen for TNF-α (Figure 3) was not reproduced by Legendplex analysis (Figure S3). IFN-γ production correlates with past SARS-CoV-2 infection Given the prominence of the IFN-γ signal, we further investigated the aetiology of this cytokine production. Although many of the PBMCs from patients in the Long COVID cohort showed elevated unstimulated IFN-γ release, there was considerable variation. Some individuals may have been symptomatic due to the unstimulated IFN-γ release, while for others, symptoms were likely to be driven by an independent pathway To test this, we stratified our undifferentiated Long COVID cohort of patients based on strong diagnostic evidence of past SARS-CoV-2 infection. Our first group included patients who were either seropositive or who had a positive SARS-CoV-2 RT-qPCR result at the time of their initial symptoms. The next group consisted of seronegative patients with no positive SARS-CoV-2 RT-qPCR but a positive IL-2 T cell response following stimulation with nucleocapsid and membrane peptides [11]. The final group showed no evidence of past SARS-CoV-2 infection, either by RT-qPCR, antibody serology or IL-2 T cell responses to nucleocapsid and membrane peptides. Unstimulated IFN-γ release correlated with highest confidence of previous SARS-CoV-2 infection (Figure 4a). Our data therefore suggests that our Long COVID cohort comprises a mixed population of patients who (i) were infected previously with SARS-CoV-2, whose PBMCs spontaneously release IFN-γ after infection, and (ii) another group of patients with no serological or T-cell evidence of previous SARS-CoV-2 infection and low levels of unstimulated IFN-γ release. These patients’ may have indeed had COVID-19 and be false negatives, or have symptoms that overlap with Long COVID patients but are likely driven by other, non-SARS-CoV-2 factors. Our analysis in Figure 1 used longitudinal cohorts of different patients with only some overlap at each timepoint. We therefore tracked changes in unstimulated IFN-γ release across individual patients over time. Unstimulated IFN-γ release in PBMCs from the same 7 patients with no Long COVID symptoms showed a clear decrease in spontaneous IFN-γ release by D180 (Figure 4b). By contrast, unstimulated IFN-γ release across 8 patients with Long COVID was persistent, with no overall downward trend but significant patient to patient variation (Figure 4c). Taken together, these data show that unstimulated IFN-γ release usually resolves following acute infection but persist in the cohort of patients who progress to Long COVID. Vaccination-induced anti-Spike antibody correlates with decreased IFN-γ production and Long COVID symptoms improvement Finally, a considerable number of patients experienced an alleviation of some, if not all, Long COVID symptoms following SARS-CoV-2 vaccination during Long COVID [10]. We postulated that unstimulated IFN-γ release may correlate with some of the Long COVID symptoms and therefore tested whether unstimulated IFN-γ release decreases post vaccination. We measured unstimulated IFN-γ release in Long COVID patients before and after vaccination, which we confirmed by anti-spike fluorospot assay (Figure 5a) and found a significant decrease post vaccination (Figure 5b), which correlated with their improved symptoms (Figure 5c), reinforcing the evidence that unstimulated IFN-γ release correlates with Long COVID symptoms (Figure 5). To demonstrate that these patients responded to vaccination, we also measured IL-2 release following spike stimulation. All donors showed increased responses to spike post vaccination (Figure 5). Despite a reported lack of T cell responses after vaccination [13], we observed an increase in all donors. No pattern of discernible symptoms were associated with post vaccination improvement (Table S1). Discussion Long COVID is an important, emerging, long-term clinical problem resulting from the COVID-19 pandemic. Although the likelihood of acute COVID-19 illness progressing to severe Long COVID may be low, with over 600 million infections by August 2022, the large number of people living with Long COVID will be a burden for health services with negative impact on different facets of society as a whole. Understanding the molecular mechanisms underlying Long COVID is therefore of paramount importance, as this will help in designing novel treatment options for patients in need. In this study, we reveal that CD8 + T cells from patients diagnosed with Long COVID secrete increased levels of IFN-γ, spontaneously without peptide stimulation, compared to healthy controls. Vaccination appears to decrease this IFN-γ secretion, correlating with improved symptoms in patients with Long COVID. Our study shows that infection with SARS-CoV-2 triggers increased spontaneous IFN-γ secretion, which resolves in most patients by 6 months post-infection. This suggests that Long COVID lasting over 6 months could be differently classified to that lasting 12 weeks based on this IFN-γ signature. Indeed, our data suggests that most patients have not resolved their IFN-γ secretion at 3 months post infection, which agrees with studies finding that many patients report ongoing symptoms 12 weeks after infection. We also observed increases in IL-1β, IL-6, GM-CSF and G-CSF secretion from patients with Long COVID, raising the possibility that other pro-inflammatory cytokines maybe perturbed as well, as has been observed by others at 8 months post infection [14]. IFN-γ secretion showed the strongest change however. We observed that our Long COVID cohort had variable IFN-γ secretion: around 30% showed levels within the range seen for our unexposed controls. Conversely, four of our unexposed controls showed high levels of IFN-γ secretion. We believe that the four unexposed donors may have been infected or recovering from an infection at the time of donation, which led to higher IFN-γ secretion. From the Long COVID cohort, the lower IFN-γ secretion may occur for a number of reasons. Firstly, as IFN-γ secretion varies with time (Figure 4c), it may be the case that these patients donated at a nadir in their cycle of IFN-γ secretion, causing a low result. We would like to follow these patients with longitudinal blood sampling and analysis to determine if IFN-γ secretion does indeed cycle and if it correlates with symptom severity. Secondly, we expect that some donors in this cohort do not have Long COVID, but instead have different underlying conditions that manifest with symptoms overlapping with those found in Long COVID patients. In the setting of a large patient cohort, it may be possible to compare symptom profiles between patients with high IFN-γ secretion and those with consistently low IFN-γ secretion to narrow the range of symptoms that are associated with Long COVID and exclude others. At this stage it is not clear whether IFN-γ is a mediator or a biomarker of Long COVID symptoms. Use of IFN-γ treatment for viral infections such as hepatitis C is associated with symptoms such as fever, diarrhoea, headache, chills, nausea, myalgia, and/or fatigue [15] as well as psychological symptoms such as depression and anxiety [16]. As some of the symptoms of IFN-γ therapy are similar to those in patients with Long COVID, it is plausible that aberrant unstimulated IFN-γ production may be a causative factor. If not, our findings of IFN-γ secretion makes it an essential biomarker for Long COVID, which if explored in the context of a larger patient cohort, has the potential to reveal pathophysiological basis of Long COVID and lead to the discovery of pharmacological treatments. Dysregulated interferon signalling is a hallmark of SARS-CoV-2 infection and plays a key role in disease severity and progression [17] [18]. It is possible that viral antigens carried by antigen presenting CD14 + cells stimulate CD8 + T cells, leading to IFN-γ secretion in the absence of ex-vivo peptide stimulation. The fact that many SARS-CoV-2 infected patients show this IFN-γ secretion phenomenon more than 3 months after infection is in line with observations by others that SARS-CoV-2 antigens persist long after infection, even up to 15 months post infection [19-21]. We find the Long COVID patients tend to show persistent unstimulated IFN-γ secretion, in keeping with their unremitting symptoms. In conjunction with patients’ reports, our findings highlight that SARS-CoV-2 is indeed the trigger leading to symptoms. Long COVID has some features similar to generic post viral syndrome, hence the accumulation of pro-inflammatory cytokines is suggested as a cause of Long COVID [22]. Increased CD14+ cells and decreased regulatory T cells may be exacerbating this inflammatory state. Given that conditions associated with post-infectious autoimmunity are well characterised, it is also possible that molecular mimicry is generating a class of anti-self T cells that are responding to self-antigens presented by CD14 + cells. This hypothesis would agree with the detected presence of auto antibodies in those with Long COVID prior to infection [23, 24]. Chronic post viral symptoms occur for other infections including 10% of those infected with SARS-CoV-1 and Middle Eastern Respiratory Syndrome (MERS) [25-31]; EBV, dengue and influenza, [32-36], regardless of disease severity [32]. For future work, it is worthwhile investigating whether patients with chronic post viral symptoms also exhibit high IFN-γ secretion, and if this is the case, then it could be a biomarker with wider utility. As both the build-up of inflammatory cytokines in the central nervous system has been proposed as a cause for Long COVID and chronic fatigue syndrome (CFS) [22, 37], and also since CFS can be triggered by viral infections [33], it will be interesting to see if IFN-γ secretion is higher in patients with CFS as well. Finally, although we observed that vaccination reduced IFN-γ secretion in those with Long COVID, consistent with IFN-γ being a marker associated with the symptoms, the mechanism behind this remains unclear. If SARS-CoV-2 antigens continue to persist in people with Long COVID, triggering an IFN-γ response, then vaccination may be helping to clear this antigen. Alternatively, activation of the immune system by vaccination may allow for expression of PD-1 and other markers to switch the immune system off. Vaccination perhaps could be used as a method to alleviate Long COVID symptoms, at least until better treatments are developed. We hope that our discoveries will provide a basis for Long COVID treatments and diagnostics in the future. Methods Ethics and sample collection Baseline characteristics, patient demographics and clinical symptoms of the study cohort are found in [11]. Study participants were recruited between 31 st of May 2020 and 31 st of July 2021 from patients attending the Infectious Diseases led Long COVID clinic at Addenbrooke’s Hospital. The majority were non-hospitalised patients from the initial phase of the pandemic and the clinical and epidemiological history played the most significant part in triaging patients into the Long COVID clinic. However, a combination of any of the following parameters were used to triage patients into the clinic; epidemiological and clinical history (both initially assessed by referring General Practitioners), a confirmed diagnosis of COVID-19 by nucleic acid amplification test (including point-of-care testing) and SARS-CoV-2 seropositivity. The Long COVID study patients were recruited and consented under the Cambridge COVID-19 NIHR BioResource joint Consent Form (Research Ethics Committee (NRES number (REC)) no. T1gC1) study NBR87. The COVID confirmed hospitalised patients (Day 28, Day 90 and Day 180), were enrolled following admission to Addenbrooke’s hospital, Royal Papworth and Cambridge and Peterborough Foundation Trust with a confirmed diagnosis of COVID-19 via a positive RT-qPCR test for SARS-CoV-2 as stated in [38]. Recruitment of inpatients at Addenbrooke’s Hospital and health-care workers was undertaken by the National Institute for Health Research (NIHR) Cambridge Clinical Research Facility outreach team and the NIHR BioResource research nurse team as stated in [38]. Informed consent was obtained from all participants. Each participant provided 32ml of peripheral venous blood collected into a 9-ml sodium citrate tube. Clinical data was collected at clinic visit and routine laboratory tests and inflammatory cytokine panel were assayed appropriately where clinically relevant. Serology testing SARS-CoV-2 serology by multiplex particle-based flow cytometry (Luminex): Recombinant SARS-CoV-2 N, S and RBD were covalently coupled to distinct carboxylated bead sets (Luminex; Netherlands) to form a 3-plex assay. The S protein construct used is S-R/PP [39]. The RBD protein construct used is described by Stadlbauer et. al, [40]. Beads were first activated with 1-ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride (Thermo Fisher Scientific) in the presence of N-hydroxysuccinimide (Thermo Fisher Scientific), according to the manufacturer’s instructions, to form amine-reactive intermediates. The activated bead sets were incubated with the corresponding proteins at a concentration of 50 μg/ml in the reaction mixture for 3 hours at room temperature on a rotator. Beads were washed and stored in a blocking buffer (10 mM PBS, 1% BSA, 0.05% NaN3). The N-, S- and RBD-coupled bead sets were incubated with proband sera at a 1/100 dilution for 1 h in 96-well filter plates (MultiScreen HTS; Millipore) at room temperature in the dark on a horizontal shaker. Fluids were aspirated with a vacuum manifold and beads were washed three times with 10 mM PBS/0.05% Tween 20. Beads were incubated for 30 min with a PE-labelled anti–human IgG-Fc antibody (Leinco/Biotrend), washed as described above, and resuspended in 100 μl PBS/Tween. They were then analysed on a Luminex analyser (Luminex / R&D Systems) using Exponent Software V31. Specific binding was reported as mean fluorescence intensities (MFI). N protein was kindly provided by Dr Leo James. RBD was provided by Dr James Nathan. Trimeric S was provided by Dr John Briggs. PBMC isolation from patient blood and magnetic activated cell sorting (MACS) Peripheral blood mononuclear cells (PBMCs) were isolated from citrated blood samples by layering blood onto Lymphoprep (Axis-shield, Oslo, Norway) and performing density gradient centrifugation at 1200 xg for 10 mins. PBMCs at the interface were collected and washed 2x in PBS. Positive selection of monocytes was performed using magnetic activated cell sorting (MACS) with CD14 + , CD4 + or CD8 + microbeads (Miltenyi Biotec) as detailed in the manufacturer’s protocol. Whenever PBMCs, CD4/8/14 + cell-depleted PBMCs or isolated cells were plated for fluorospot analysis, cells were resuspended in the same volume (2 × 10 5 PBMCs per well) and then plated. Dual FluoroSpot Assays 2 × 10 5 PBMCs suspended in TexMACS (Miltenyi Biotech) supplemented with 5% Human AB serum (Sigma Aldrich) were incubated on FluoroSpot plates coated with Human IFN-γ and IL-2 antibodies or Human IFN-γ, TNF-α or IL-10 antibodies [FluoroSpot (Mabtech AB, Nacka Strand, Sweden)] in duplicate with spike ORF peptides (final peptide concentration 2 μg/ml/peptide) or TexMACS-only negative control and positive control mix [containing anti-CD3 (Mabtech AB), Staphylococcus Enterotoxin B, and Lipopolysaccharide (all Sigma-Aldrich)] at 37°C in a humidified CO2 atmosphere for 48 h (or 24 h where indicated). The cells and medium were decanted from the plate and the assay developed following the manufacturer’s instructions. Developed plates were read using an AID iSpot reader (Oxford Biosystems, Oxford, UK) and counted using AID EliSpot v7 software (Autoimmun Diagnostika GmbH, Strasberg, Germany) using distinct counting protocols for IFN-γ, TNF-α, IL-10 or IL-2 secretion. Donor results were discounted from further analysis if there was less than 100 sfu in the positive control relative to the background sfu. Spike response data in Figure 5 was corrected for background cytokine production by subtracting the negative control. We used a peptide pool for spike as recently published [41]: “A peptide pool was generated using the following: 1. PepTivator SARS-CoV-2 Prot_S containing the sequence domains aa 304-338, 421- 475, 492-519, 683-707, 741-770, 785-802, and 885 – 1273 and S1 N-terminal S1 domain of the surface glycoprotein ("S") of SARS-Coronavirus 2 (GenBank MN908947.3, Protein QHD43416.1). 2. The PepTivator SARS-CoV-2 Prot_S1 containing the aa sequence 1–692. The peptides used are 15aa amino acids with 11 amino acid overlaps.” Absolute count enumeration of lymphocyte subsets The absolute number of immune cells present in whole blood samples was enumerated using Becton Dickinson Trucount tubes (BD Biosciences, Oxford, UK) following the manufacturer’s instructions. Briefly, 50µl of the EDTA treated whole blood samples was stained in the Trucount tube with a pre-mixed antibody cocktail (detailed in Table S2) allowing the identification of monocytes, B cells, CD4+ and CD8+ T cells, T cell memory subsets and activated T cells and NK cells. Following staining, the red blood cells were lysed and the cells fixed using FACS Lysing solution (BD Biosciences) and then stored at -80°C until acquisition[42]. Samples were acquired on a 5-laser LSR Fortessa (BD Biosciences) with Fluorescence Minus One Controls and single colour compensation controls (AbC Total Antibody Compensation Bead Kit – Thermo Fisher Scientific) utilized. Samples were analysed and enumerated using Flowjo software (BD Biosciences) following the gating strategy and the formula illustrated in Figure S4. Results were expressed as the number of each immune cell subset per microliter of blood (cells/µl). Measuring IFNγ secretion by flow cytometry PBMC (2.5 x106) from long covid patients and healthy controls were suspended in TexMACS medium (Miltenyi Biotec) were unstimulated or stimulated with a positive-control mix (containing anti-CD3 (Mabtech AB), Staphylococcus Enterotoxin B (SEB), Phytohemagglutinin (PHA), Pokeweed Mitogen (PWM), and Lipopolysaccharide (LPS) (all Sigma-Aldrich)) for 1 hour and then 5 µg/ml brefeldin A and 2 µM monensin (both from BioLegend) were added and the cells were incubated overnight at 37°C in a humidified CO2 atmosphere. The cells were then washed and stained with a combination of surface antibodies comprising CD3 BV650, CD14 FITC, CD19 BV510 (BioLegend) and LIVE/DEAD fixable Aqua dead cell stain (Thermo Fisher Scientific) at 4°C. The cells were fixed, permeabilized using a FIX & PERM™ cell permeabilization kit (Thermo Fisher Scientific) and stained intracellularly with CD69 Pacific Blue, CD8 BV570, CD4 BV605, CD134 (OX-40) PE, 4-1BB PE–Cy5, CD40L PerCP-Cy5.5 (BioLegend) and IFN-γ BV786 (BD Biosciences) at 4°C in the dark. Full details of the antibodies used in the assay are provided in Table S3. Samples were washed and fixed with FluoroFix™ Buffer (BioLegend) and acquired on a BD LSR Fortessa cytometer using FACSDiva software. The data were analyzed using FlowJo software following the gating strategy illustrated in Figure S5 the production of IFN-γ and expression of activation markers on resting and stimulated CD4+ and CD8+ T cells in healthy controls compared to long covid patients was assessed. Measuring cytokine secretion by Legendplex Cytokine secretion between Long COVID and healthy control PBMCs were compared using LEGENDplex COVID-19 Cytokine Storm Panels 1&2 (13 plex & 12 plex, Cat Nos: 741091&741142 respectively) from Biolegend. PBMCs from n=10 healthy controls and n=14 patients with Long COVID. After 48 hours incubation, media was collected and loaded onto Legenplex plates at 1:2 dilution, following manufacturer’s protocol. Samples were analysed using a BD Accuri C6 following manufacturer’s instructions, and cytokine concentrations were calculated against a standard curve provided by the manufacturer using Biolegend’s software (https://www.biolegend.com/en-us/legendplex). Data Handling Data were determined to be non-parametric by Shapiro-Wilk analysis. We therefore used non-parametric statistical analysis (Mann–Whitney U, Kruskal–Wallis one-way analysis of variance, Wilcoxon signed-rank test) throughout. Declarations Author contributions Conceptualisation, MRW, NS; Methodology, MRW, NS, BAK; Investigation & Data Collection, BAK, EYL, LM, RD, MRW, NS; Supervision – NJM, PJL, MRW, NS; Writing – Original Draft, BAK, MRW, NS; Writing – Review & Editing, BAK, EYL, LM, PL, RD, JB, KGCS, JS, NJM, PJL, MRW and NS. Acknowledgements This work was funded by the Addenbrooke's Charitable Trust (900276 to NS), NIHR award (G112259 to NS), a BIA grant (G101370 to NS), and supported by the NIHR Cambridge Biomedical Research Centre. NJM is supported by the MRC (TSF MR/T032413/1) and NHSBT (WPA15-02). PJL is supported by the Wellcome Trust (PRF 210688/Z/18/Z, 084957/Z/08/Z), a Medical Research Council research grant MR/V011561/1 and the United Kingdom Research and an Innovation COVID Immunology Consortium grant (MR/V028448/1). We would also like to thank Meritxell Nus for helpful communications. Competing Interests The authors declare no competing interests NIHR BioResource John Allison, Heather Biggs, John Bradley, Helen Butcher, Daniela Caputo, Matt Chandler, Debbie Clapham-Riley, Patrick Chinnery, Anne-Maree Dean, Eleanor Dewhurst, Christian Fernandez, Anita Furlong, Anne George, Barbara Graves, Jennifer Gray, Sabine Hein, Tasmin Ivers, Mary Kasanicki, Nathalie Kingston, Emma Le Gresley, Rachel Linger, Sarah Meloy, Alexei Moulton, Francesca Muldoon, Nigel Ovington, Roxana Paraschiv, Sofia Papadia, Isabel Phelan, Christopher Penkett, Venkatesh Ranganath, Jennifer Sambrook, Katherine Schon, Hannah Stark, Kathleen E Stirrups, Paul Townsend, Julie von Ziegenweidt, Neil Walker, Jennifer Webster References Scherlinger, M., et al., Refining “Long-COVID” by a Prospective Multimodal Evaluation of Patients with Long-Term Symptoms Attributed to SARS-CoV-2 Infection. Infectious Diseases and Therapy, 2021: p. 1-17. Huang, C., et al., 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study. The Lancet, 2021. 397 (10270): p. 220-232. Ayoubkhani, D., et al., Post-covid syndrome in individuals admitted to hospital with covid-19: retrospective cohort study. bmj, 2021. 372 . Gupta, A., et al., Extrapulmonary manifestations of COVID-19. Nature medicine, 2020. 26 (7): p. 1017-1032. Thompson, E.J., et al., Risk factors for long COVID: analyses of 10 longitudinal studies and electronic health records in the UK. medRxiv, 2021. Logue, J.K., et al., Sequelae in adults at 6 months after COVID-19 infection. JAMA network open, 2021. 4 (2): p. e210830-e210830. Petersen, M.S., et al., Long COVID in the Faroe Islands-a longitudinal study among non-hospitalized patients. Clinical infectious diseases: an official publication of the Infectious Diseases Society of America, 2020. LaVergne, S.M., et al., A longitudinal SARS-CoV-2 biorepository for COVID-19 survivors with and without post-acute sequelae. BMC Infect Dis, 2021. 21 (1): p. 677. Townsend, L., et al., Persistent poor health after COVID-19 is not associated with respiratory complications or initial disease severity. Annals of the American Thoracic Society, 2021. 18 (6): p. 997-1003. Strain, W.D., et al., The Impact of COVID Vaccination on Symptoms of Long COVID. An International Survey of People with Lived Experience of Long COVID. An International Survey of People with Lived Experience of Long COVID. Krishna, B.A., et al., Evidence of previous SARS-CoV-2 infection in seronegative patients with long COVID. eBioMedicine, 2022. 81 : p. 104129. Jackson, S.E., et al., Latent cytomegalovirus (CMV) infection does not detrimentally alter T cell responses in the healthy old, but increased latent CMV carriage is related to expanded CMV-specific T cells. Frontiers in immunology, 2017. 8 : p. 733. Reynolds, C.J., et al., Prior SARS-CoV-2 infection rescues B and T cell responses to variants after first vaccine dose. Science, 2021. 372 (6549): p. 1418. Phetsouphanh, C., et al., Immunological dysfunction persists for 8 months following initial mild-moderate SARS-CoV-2 infection. medRxiv, 2021. Miller, C.H.T., S.G. Maher, and H.A. Young, Clinical Use of Interferon-gamma. Annals of the New York Academy of Sciences, 2009. 1182 : p. 69-79. Pinto, E.F. and C. Andrade, Interferon-Related Depression: A Primer on Mechanisms, Treatment, and Prevention of a Common Clinical Problem. Current neuropharmacology, 2016. 14 (7): p. 743-748. Acharya, D., G. Liu, and M.U. Gack, Dysregulation of type I interferon responses in COVID-19. Nat Rev Immunol, 2020. 20 (7): p. 397-398. Initiative, C.-H.G., Mapping the human genetic architecture of COVID-19. Nature. García-Abellán, J., et al., Antibody Response to SARS-CoV-2 is Associated with Long-term Clinical Outcome in Patients with COVID-19: a Longitudinal Study. Journal of Clinical Immunology, 2021. Patterson, B.K., et al., Persistence of SARS CoV-2 S1 protein in CD16+ monocytes in post-acute sequelae of COVID-19 (PASC) up to 15 months post-infection. bioRxiv, 2021. Carmo, A., et al., Clearance and persistence of SARS‐CoV‐2 RNA in patients with COVID‐19. Journal of medical virology, 2020. 92 (10): p. 2227-2231. Perrin, R., et al., Into the looking glass: Post-viral syndrome post COVID-19. Medical hypotheses, 2020. 144 : p. 110055-110055. Wang, E.Y., et al., Diverse Functional Autoantibodies in Patients with COVID-19. medRxiv, 2021: p. 2020.12.10.20247205. Nalbandian, A., et al., Post-acute COVID-19 syndrome. Nature medicine, 2021. 27 (4): p. 601-615. Ahmed, H., et al., Long-term clinical outcomes in survivors of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronavirus outbreaks after hospitalisation or ICU admission: a systematic review and meta-analysis. Journal of rehabilitation medicine, 2020. 52 (5): p. 1-11. Hui, D., et al., Impact of severe acute respiratory syndrome (SARS) on pulmonary function, functional capacity and quality of life in a cohort of survivors. Thorax, 2005. 60 (5): p. 401-409. Lam, M.H.-B., et al., Mental morbidities and chronic fatigue in severe acute respiratory syndrome survivors: long-term follow-up. Archives of internal medicine, 2009. 169 (22): p. 2142-2147. Lee, A.M., et al., Stress and psychological distress among SARS survivors 1 year after the outbreak. The Canadian Journal of Psychiatry, 2007. 52 (4): p. 233-240. Moldofsky, H. and J. Patcai, Chronic widespread musculoskeletal pain, fatigue, depression and disordered sleep in chronic post-SARS syndrome; a case-controlled study. BMC neurology, 2011. 11 (1): p. 1-7. Ong, K.C., et al., Pulmonary function and exercise capacity in survivors of severe acute respiratory syndrome. European Respiratory Journal, 2004. 24 (3): p. 436-442. Lee, S.H., et al., Depression as a mediator of chronic fatigue and post-traumatic stress symptoms in Middle East respiratory syndrome survivors. Psychiatry investigation, 2019. 16 (1): p. 59. Seet, R.C.S., A.M.L. Quek, and E.C.H. Lim, Post-infectious fatigue syndrome in dengue infection. Journal of Clinical Virology, 2007. 38 (1): p. 1-6. White, P.D., et al., Predictions and associations of fatigue syndromes and mood disorders that occur after infectious mononucleosis. The Lancet, 2001. 358 (9297): p. 1946-1954. Buchwald, D.S., et al., Acute infectious mononucleosis: characteristics of patients who report failure to recover. Am J Med, 2000. 109 (7): p. 531-7. Petersen, I., et al., Risk and predictors of fatigue after infectious mononucleosis in a large primary-care cohort. Qjm, 2006. 99 (1): p. 49-55. Katz, B.Z., et al., Chronic fatigue syndrome after infectious mononucleosis in adolescents. Pediatrics, 2009. 124 (1): p. 189-193. Hives, L., et al., Can physical assessment techniques aid diagnosis in people with chronic fatigue syndrome/myalgic encephalomyelitis? A diagnostic accuracy study. BMJ open, 2017. 7 (11): p. e017521. Bergamaschi, L., et al., Longitudinal analysis reveals that delayed bystander CD8+ T cell activation and early immune pathology distinguish severe COVID-19 from mild disease. Immunity, 2021. 54 (6): p. 1257-1275.e8. Xiong, X., et al., A thermostable, closed SARS-CoV-2 spike protein trimer. Nature structural & molecular biology, 2020. 27 (10): p. 934-941. Stadlbauer, D., et al., SARS‐CoV‐2 seroconversion in humans: a detailed protocol for a serological assay, antigen production, and test setup. Current protocols in microbiology, 2020. 57 (1): p. e100. Collier, D.A., et al., Age-related immune response heterogeneity to SARS-CoV-2 vaccine BNT162b2. Nature, 2021: p. 1-9. Hensley-McBain, T., et al., Optimization of a whole blood phenotyping assay for enumeration of peripheral blood leukocyte populations in multicenter clinical trials. Journal of immunological methods, 2014. 411 : p. 23-36. Additional Declarations There is NO Competing Interest. Supplementary Files NatureCommunicationsSupplement.docx Supplementary Figures and Table Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions 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-2034285","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":153594391,"identity":"6e0f8e0c-99eb-4836-9407-740c7363af13","order_by":0,"name":"Benjamin Krishna","email":"","orcid":"","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Krishna","suffix":""},{"id":153594392,"identity":"abcd6772-fcd4-4659-90b4-549d9f3c3e6e","order_by":1,"name":"Eleanor Lim","email":"","orcid":"","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Eleanor","middleName":"","lastName":"Lim","suffix":""},{"id":153594393,"identity":"91e88901-f8b5-4a11-acd4-e26be2b6fa82","order_by":2,"name":"Lenette Mactavous","email":"","orcid":"","institution":"Cambridge University Hospitals NHS Foundation Trust","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lenette","middleName":"","lastName":"Mactavous","suffix":""},{"id":153594394,"identity":"0cd046ef-8927-492a-bfb9-890756ca32d7","order_by":3,"name":"Sarah Jackson","email":"","orcid":"https://orcid.org/0000-0002-4230-9220","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Jackson","suffix":""},{"id":153594395,"identity":"71972e12-a06c-46a8-96fa-42e618f74701","order_by":4,"name":"NIHR BioResource Team NIHR BioResource Team","email":"","orcid":"","institution":"Cambridge National Institute for Health Research (NIHR) Bioresource \u0026 Cambridge Bioresource, University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"NIHR","middleName":"BioResource Team NIHR BioResource","lastName":"Team","suffix":""},{"id":153594396,"identity":"cd13e7ab-0dcf-4ffc-875d-12a6e4c8f289","order_by":5,"name":"Paul Lyons","email":"","orcid":"https://orcid.org/0000-0001-7035-8997","institution":"Cambridge Institute for Medical Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Lyons","suffix":""},{"id":153594397,"identity":"88da9f59-bcef-4183-afcc-edc0b2d19f95","order_by":6,"name":"Rainer Doffinger","email":"","orcid":"https://orcid.org/0000-0002-9841-3617","institution":"Addenbrooke's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rainer","middleName":"","lastName":"Doffinger","suffix":""},{"id":153594398,"identity":"b32443da-af57-4565-86cc-2403019a86f5","order_by":7,"name":"John Bradley","email":"","orcid":"https://orcid.org/0000-0002-7774-8805","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Bradley","suffix":""},{"id":153594399,"identity":"0a451414-fad2-49c0-a7d5-05f20f1f7a4c","order_by":8,"name":"Kenneth Smith","email":"","orcid":"","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kenneth","middleName":"","lastName":"Smith","suffix":""},{"id":153594400,"identity":"dd47c922-6e2e-41d7-ba1d-532ff866da70","order_by":9,"name":"John Sinclair","email":"","orcid":"","institution":"Cambridge University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Sinclair","suffix":""},{"id":153594401,"identity":"476c865c-b0ef-4cfe-9ec3-53f95fb6555b","order_by":10,"name":"Nicholas Matheson","email":"","orcid":"https://orcid.org/0000-0002-3318-1851","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nicholas","middleName":"","lastName":"Matheson","suffix":""},{"id":153594402,"identity":"954e1d3f-6b2c-49c9-a499-890b2355de72","order_by":11,"name":"Paul Lehner","email":"","orcid":"https://orcid.org/0000-0001-9383-1054","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Lehner","suffix":""},{"id":153594403,"identity":"6fda5134-2357-4ec6-b430-b2c536c7e2e4","order_by":12,"name":"Nyaradzai Sithole","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuklEQVRIiWNgGAWjYFAC/gcHPlTAeQnEaOFhPDjjDIlamA/ztpGixZz/7IHDvPPs5HUbmB9+YGxLI6zFckZewsG525INtx1gM5ZgbMshrMXgBoPBgbfbDjBuO8BgxsDYVkGElvMHDA7wzjlgv+0A+zcitRzIMTjI23AgcdsBHpAtRDksLeHgjGPJydsO8xRLJJwjwvsG5w8f/vChxs522/H2jR8+lCUT1oIAzAxERuQoGAWjYBSMAsIAAPTIPtZ02J9RAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-8020-223X","institution":"University of Cambridge","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Nyaradzai","middleName":"","lastName":"Sithole","suffix":""},{"id":153594404,"identity":"e68af687-b2e2-4263-b2e7-d4c1167fdf6c","order_by":13,"name":"Mark Wills","email":"","orcid":"","institution":"University of Cambridge","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Wills","suffix":""}],"badges":[],"createdAt":"2022-09-05 14:40:39","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-2034285/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-2034285/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":29346377,"identity":"a6c78d66-716c-4d05-bea4-272b634614b7","added_by":"auto","created_at":"2022-11-21 17:59:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":480215,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpontaneous IFN-γ release is triggered by SARS-CoV-2 infection and fails to resolve to baseline in patients with diagnosed Long COVID. \u003c/strong\u003ePBMCs were isolated from the blood of negative control unexposed donors (red), patients diagnosed with Long COVID (burgundy), and positive-control RT-qPCR-confirmed donors at 28, 90 or 180 days post PCR test (cyan, green, blue). These PBMCs were not stimulated with any peptides ex-vivo. After 48 hours incubation IFN-γ release was measured by fluorospot assay as spot forming units per million PBMCs. Each donor was run in duplicate and zero results were set as 0.1 to allow their inclusion on a log scale. L.O.D. = limit of detection. Significance calculated by Kruskal-Wallis ANOVA, ****p\u0026gt;0.0001\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2034285/v2/3447dbfe4c1e77589a52c8a2.png"},{"id":29346698,"identity":"4b257925-5233-41cf-b84d-75bbac90162a","added_by":"auto","created_at":"2022-11-21 18:07:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":329757,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpontaneous IFN-γ release from the PBMCs of Long COVID patients is caused by CD8+ T cell interaction with CD14+ cells via MHC Class I peptide presentation.\u003c/strong\u003e (a) MACS separation was used to isolate CD14+ cells from PBMC donations from Long COVID patients. Whole PBMCs (red), PBMCs depleted of CD14+ cells by MAC separation (cyan), isolated CD14+ cells alone (green) or CD14+ cells combined with CD14+ depleted PBMCs (blue) from 8 patients diagnosed with Long COVID were plated without peptide stimulation for 48 hours to measure IFN-γ release by fluorospot assay. b) MACS separation was utilised as in a, but PBMCs depleted of CD4+ T cells (cyan), PBMCs depleted of CD8+ T cells (green) or PBMCs depleted of both CD4 and CD8+ T cells (blue) were plated instead without peptide stimulation for 48 hours to measure IFN-γ release by fluorospot assay. C) PBMCs from patients diagnosed with Long COVID (LC) or healthy controls (HE) were incubated for 24 hours with brefeldin a and monensin to allow intracellular accumulation of IFN-γ. Cells were then stained for CD3, CD4, CD8 and IFN-γ, to compare IFN-γ production in these cells types between HE and LC. D) CD14+ cells were isolated by MACs separation from PBMCs of patients with Long COVID. These cells were incubated for 1 hour with anti-MHC Class I and/or anti-MHC Class II blocking antibodies, or an isotype control antibody, at room temperature. The cells were then washed and returned to the donor PBMCs, and IFN-γ release measured by fluorospot assay after 24 hours incubation. (a,b,d) IFN-γ release was quantified as spot forming units per million PBMCs. Each donor was run in duplicate and zero results were set as 0.1 to allow their inclusion on a log scale. L.O.D. = limit of detection. Significance calculated by Kruskal-Wallis ANOVA (a,b), or Friedman Analysis of Variance (ANOVA) test (d) *p\u0026gt;0.05, **p\u0026gt;0.01, ****p\u0026gt;0.0001. (c) Data is shown as percentage of cells that were positive for IFN-y. Significance was calculated using multiple Mann-Whitney U tests.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2034285/v2/4bf7e557756f7e0297a417fc.png"},{"id":29346696,"identity":"e985f258-6fa2-419b-8551-da04039bdc50","added_by":"auto","created_at":"2022-11-21 18:07:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":260933,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePBMCs from Long COVID patients produce IFN-γ and TNF-α but not IL-10. \u003c/strong\u003ePBMCs were isolated from the blood of Long COVID patients (blue) and those never infected with SARS-CoV-2 (unexposed, red). Spontaneous production of IFN-γ, IL-10 and TNF-α was measured by flurospot assay on unstimulated cells. After 48 hours incubation cytokine release was measured by fluorospot assay as spot forming units per million PBMCs. Each donor was run in duplicate and zero results were set as 0.1 to allow their inclusion on a log scale. L.O.D. = limit of detection. Significance calculated by Mann-Whitney U test, *p\u0026gt;0.05, **p\u0026gt;0.01, ***p\u0026gt;0.001.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2034285/v2/3d53e4d3ed14b9fc298b15ca.png"},{"id":29346378,"identity":"00a41642-7bba-4f0c-831c-0e1c5ff6e0af","added_by":"auto","created_at":"2022-11-21 17:59:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":341801,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpontaneous IFN-γ production correlates with evidence of COVID-19 disease and resolves in individuals with symptom resolution. \u003c/strong\u003e\u0026nbsp;a) Data from Figure 1a was replotted so that the Long COVID cohort was stratified into Long COVID patients who were seropositive for anti-spike and anti-nucleocapsid antibodies (dark blue), those who were negative for anti-spike and anti-nucleocapsid antibodies but positive for IL-2 responsive T cells against nucleocapsid or membrane (blue), and those which were negative for antibodies or IL-2 T cell responses (cyan). B) Data from Figure 1b was replotted for PBMCs from 10 donors who gave samples at 28 and 180 days post-positive RT-qPCR result. C) IFN-γ release was measured by fluorospot assay for patients with Long COVID who donated at roughly 6 and 9 months post symptom onset. (A-C) IFN-γ release was quantified as spot forming units per million PBMCs. Each donor was run in duplicate and zero results were set as 0.1 to allow their inclusion on a log scale. L.O.D. = limit of detection. Significance calculated by Kruskal-Wallis ANOVA for A or Wilcoxon Signed Rank test for B and C, **p\u0026gt;0.01, ****p\u0026gt;0.0001.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-2034285/v2/89996dc2321596d33af50d45.png"},{"id":29347127,"identity":"1f6978f5-32be-46aa-b903-468cb2a7414b","added_by":"auto","created_at":"2022-11-21 18:15:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":268017,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLong COVID symptoms and spontaneous IFN-γ release are reduced after vaccination\u003c/strong\u003e. PBMCs were isolated from patients diagnosed with Long COVID before and after first vaccination and either stimulated with anti-spike peptide ex-vivo or not stimulated. a) After 48 hours incubation IL-2 release from spike peptide-stimulated T cells was measured, with negative control IL-2 subtracted. B) After 48 hours IFN-γ release from negative controls was counted. a\u0026amp;b) For both datasets, IL-2 and IFN-γ were quantified as spot forming units per million PBMCs. Each donor was run in duplicate and zero results were set as 0.1 to allow their inclusion on a log scale. L.O.D. = limit of detection. Significance calculated by Wilcoxon Ranked Sign Test, ****p\u0026gt;0.0001. c) Patient report symptoms before and after vaccination.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-2034285/v2/df8ebdced856371f60fb8511.png"},{"id":29639301,"identity":"ac1e6f80-8081-48f4-a1e5-80f48f988494","added_by":"auto","created_at":"2022-11-29 08:56:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1412496,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2034285/v2/eb113ff0-9a15-473e-9c45-6cbaefca0aea.pdf"},{"id":29346381,"identity":"99896b5a-9216-44f7-a3bf-70f8a8bae249","added_by":"auto","created_at":"2022-11-21 17:59:31","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4752665,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figures and Table\u003c/p\u003e","description":"","filename":"NatureCommunicationsSupplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-2034285/v2/2f27b539baf8e1680250bf38.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Spontaneous, persistent T-cell dependent IFN-γ release in patients who progress to Long COVID","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA significant proportion of people infected with SARS-CoV-2 exhibit persistent distressing symptoms, or the emergence of new symptoms. These are difficult to delineate into specific endotypes and are broadly grouped as post-COVID syndrome or Long COVID. There is a lack of consensus for diagnosing Long COVID and causes of Long COVID remain unclear, with resultant lack of approved pharmacological therapeutic interventions. Long COVID has a plethora of relapsing and remitting symptoms\u0026nbsp;[1]\u0026nbsp;and multi-systemic organ involvement\u0026nbsp;[2-4]\u0026nbsp;with prevalence rates ranging from 0.27%-33%\u0026nbsp;[5-8]. It is likely that some differences between studies are due to differences in diagnostic criteria and definition of Long COVID. As the pathogenesis of this heterogenous disease is unclear, there is also a lack of diagnostic biomarkers and treatments. Adding to the diagnostic conundrum is the mounting evidence that Long COVID is not attributed to the severity of the preceding acute illness as it even affects patients with asymptomatic and/or mild acute COVID illness\u0026nbsp;[9]. Although some patients improve without therapeutic interventions, a significant proportion of patients have not improved and/or have relapsing and worsening symptoms. Anecdotal reports from some Long COVID patients suggest that vaccination either significantly improved or ameliorated their symptoms, though the pathophysiological basis for these finding remain unknown\u0026nbsp;[10].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn view of the urgent clinical need to determine the pathophysiological basis of Long COVID and ascertain the relevant biomarker/s to aid diagnosis and assist with objective disease monitoring, we studied cytokine secretion from peripheral blood mononuclear cells (PBMCs) from a cohort of undifferentiated patients diagnosed with Long COVID as defined by clinical symptoms, as well as controls of never infected individuals and longitudinal follow up of those acutely infected. To better understand the disease process and immune parameters we performed immunophenotyping combined with intracellular cytokine staining of donor PBMCs. We now show that SARS-CoV-2 infection induces a large increase in CD8\u003csup\u003e+\u003c/sup\u003e T-cell-mediated IFN-γ release, not requiring any ex-vivo peptide stimulation. This state persists for several months post-acute infection in all patients. Patients with Long COVID fail to return to baseline IFN-γ levels, though some patients show improvement post vaccination. We identify antigen detection by CD8\u003csup\u003e+\u003c/sup\u003e T cells as the cause of the IFN-γ production suggesting that this is caused by antigen presentation by CD14\u003csup\u003e+\u003c/sup\u003e monocytes. \u0026nbsp;Taken together, we identify IFN-γ release as a biomarker for long COVID and highlight an immunological mechanism underlying this debilitating disease, paving the way for the development of novel therapies.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSARS-CoV-2 infection induces spontaneous and persistent IFN-\u0026gamma; production in Long COVID patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe recently reported a highly sensitive T cell FluoroSpot assay which measured IL-2 and IFN-\u0026gamma; responses in patients with Long-COVID[11]. The release of cytokines following stimulation of patient-derived PBMC with \u0026nbsp;SARS-CoV-2 antigens allowed us to determine the frequency of T cells specific for overlapping peptide pools of Spike (S), Nucleocapsid (N) and membrane (M) proteins in patients with Long-COVID[11]. In addition to using in vitro peptides to stimulate cytokine release from PBMC, we also measured spontaneous cytokine release in the absence of any stimulation with SARS-CoV-2 antigens. The detection of cytokine-secreting cells from unstimulated PBMC is usually very low\u0026nbsp;[12], but a significantly higher proportion / percentage of cells producing IFN-\u0026gamma; was clearly observed in PBMCs from Long COVID patients as compared to unexposed pre-pandemic, historic negative control samples taken between 2014-2019 (Figure 1a).\u003c/p\u003e\n\u003cp\u003eWe thus compared PBMC samples from Long COVID patients who had been symptomatic for at least 6 months (median symptom duration of 7 months), to PBMC from pre-pandemic negative controls (Figure 1a). As an additional control for acute SARS-CoV-2 infection, we also examined PBMC from patients taken at 28, 90 and 180 days post-positive SARS-CoV-2 RT-qPCR. PBMC from SARS-CoV-2 infected individuals showed a substantially higher spontaneous frequency of IFN-\u0026gamma; positive cells at 28 and 90 days post positive PCR as compared to uninfected controls. By 180 days this IFN-\u0026gamma; release had resolved, with IFN-\u0026gamma; producing cells at a similar level as uninfected controls (Figure 1b). However, a high frequency of IFN-\u0026gamma; release persisted in Long COVID patients even beyond 180 days of symptom onset (Figure 1c). This phenotype was also specific for IFN-\u0026gamma;, as we saw no change in IL-2 production (Figure S1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSARS-CoV-2 induced IFN-\u0026gamma; is produced by activated CD8\u003csup\u003e+\u003c/sup\u003e T cells in a CD14\u003csup\u003e+\u003c/sup\u003e cell-dependent mechanism\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo determine the cell types that produce IFN-\u0026gamma; in patients with Long COVID, we conducted a series of independent cell depletion assays. We removed CD4\u003csup\u003e+\u003c/sup\u003e or CD8\u003csup\u003e+\u003c/sup\u003e T cells, or CD14\u003csup\u003e+\u003c/sup\u003e cells from donor PBMCs by magnetic bead cell sorting (MACS) and measured IFN-\u0026gamma; release from these cell populations by FluoroSpot assay. Depletion of CD14\u003csup\u003e+\u003c/sup\u003e cells reduced IFN-\u0026gamma; release in all cases. Isolated CD14\u003csup\u003e+\u003c/sup\u003e cells release negligible IFN-\u0026gamma;, suggesting they are required for IFN-\u0026gamma; production but are not the source of IFN-\u0026gamma; (Figure 2a). The addition of isolated CD14\u003csup\u003e+\u003c/sup\u003e cells into the CD14\u003csup\u003e+\u003c/sup\u003e cell-depleted PBMC population restored IFN-\u0026gamma; production (Figure 2a).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells and subpopulations of CD4\u003csup\u003e+\u003c/sup\u003e T cells are a major source of IFN-\u0026gamma;. We performed the same cell depletion assays on these populations and found that depletion of CD8\u003csup\u003e+\u003c/sup\u003e cells significantly decreased IFN-\u0026gamma; production. A much smaller decrease was noted after CD4\u003csup\u003e+\u003c/sup\u003e cell depletion, which was not significant alone but did appear to be additive after CD8\u003csup\u003e+\u003c/sup\u003e cell depletion (Figure 2b). Taken together, our data suggest that CD8\u003csup\u003e+\u003c/sup\u003e T-cells and CD14\u003csup\u003e+\u003c/sup\u003e cells are required for unstimulated IFN-\u0026gamma; production in PBMCs from Long COVID patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further validate our findings, we used intracellular flow cytometry to co-stain for IFN-\u0026gamma; with markers of cellular differentiation status. Comparing Long COVID patients to healthy controls, we found that IFN-\u0026gamma; was increased in CD3\u003csup\u003e+\u003c/sup\u003e cells in general and CD8\u003csup\u003e+\u003c/sup\u003e cells in particular, but not in CD14\u003csup\u003e+\u003c/sup\u003e or CD4\u003csup\u003e+\u003c/sup\u003e cells (Figure 2c). These data validate our Fluorospot data using subset-depleted PBMC showing that the IFN-\u0026gamma; release is predominantly CD8\u003csup\u003e+\u003c/sup\u003e T cell mediated.\u003c/p\u003e\n\u003cp\u003eAs CD14\u003csup\u003e+\u003c/sup\u003e cells are required for the release of IFN-\u0026gamma; in Long COVID patients (Figure 2a), we therefore tested whether antigen presentation by CD14\u003csup\u003e+\u003c/sup\u003e cells induced T-cell dependent IFN-\u0026gamma; release. Anti-MHC Class I and/or Class II antibodies were used to block the cell surface of isolated CD14\u003csup\u003e+\u003c/sup\u003e cells and subsequently cultured with CD14\u003csup\u003e+\u003c/sup\u003e cell depleted autologous PBMC.\u0026nbsp;MHC Class I blocking antibodies significantly reduced the frequency of IFN-\u0026gamma; positive cells, while Class II blocking antibodies had only a minor and non-significant effect (Figure 2d). Taken together our results suggest that MHC-I-dependent antigen presentation by CD14\u003csup\u003e+\u003c/sup\u003e cells to CD8\u003csup\u003e+\u003c/sup\u003e T cells triggers IFN-\u0026gamma; release.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe measured absolute leukocyte subsets using Becton Dickinson Trucount tubes to identify any differences in leukocyte populations between Long COVID patients and healthy donors. Increased monocyte populations and decreased regulatory T cells were found in Long COVID patients as well as a profound decrease n NKG2C\u003csup\u003e+\u003c/sup\u003e natural killer (NK) cells, a phenotype also seen in persistent HCMV infection (Figure S2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePersistent IFN-\u0026gamma; release is specific to patients with Long COVID\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the known generalised cytokine perturbation in SARS-CoV-2 infection, we assessed whether Long COVID specifically correlated with increased IFN-\u0026gamma; or whether PBMCs from patients with Long COVID also released other cytokines. A small increase in TNF-\u0026alpha; but no change in IL-2 or IL-10 (Figure 3a-c) was seen using Fluorospot analysis. A bead-based immunoassay (Legendplex, BioLegend) analysing 25 different cytokines showed a general increase in pro-inflammatory cytokines, though IFN-\u0026gamma; showed the largest increase in Long COVID patients (Figure S3). Smaller increases in G-CSF and GM-CSF, which may explain the higher monocyte numbers in figure S2, were seen. The significant difference seen for TNF-\u0026alpha; (Figure 3) was not reproduced by Legendplex analysis (Figure S3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIFN-\u0026gamma; production correlates with past SARS-CoV-2 infection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the prominence of the IFN-\u0026gamma; signal, we further investigated the aetiology of this cytokine production. Although many of the PBMCs from patients in the Long COVID cohort showed elevated unstimulated IFN-\u0026gamma; release, there was considerable variation. Some individuals may have been symptomatic due to the unstimulated IFN-\u0026gamma; release, while for others, symptoms were likely to be driven by an independent pathway\u003c/p\u003e\n\u003cp\u003eTo test this, we stratified our undifferentiated Long COVID cohort of patients based on strong diagnostic evidence of past SARS-CoV-2 infection. Our first group included patients who were either seropositive or who had a positive SARS-CoV-2 RT-qPCR result at the time of their initial symptoms. The next group consisted of seronegative patients with no positive SARS-CoV-2 RT-qPCR but a positive IL-2 T cell response following stimulation with nucleocapsid and membrane peptides\u0026nbsp;[11]. The final group showed no evidence of past SARS-CoV-2 infection, either by RT-qPCR, antibody serology or IL-2 T cell responses to nucleocapsid and membrane peptides.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnstimulated IFN-\u0026gamma; release correlated with highest confidence of previous SARS-CoV-2 infection (Figure 4a). Our data therefore suggests that our Long COVID cohort comprises a mixed population of patients who (i) were infected previously with SARS-CoV-2, whose PBMCs spontaneously release IFN-\u0026gamma; after infection, and (ii) another group of patients with no serological or T-cell evidence of previous SARS-CoV-2 infection and low levels of unstimulated IFN-\u0026gamma; release. These patients\u0026rsquo; may have indeed had COVID-19 and be false negatives, or have symptoms that overlap with Long COVID patients but are likely driven by other, non-SARS-CoV-2 factors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur analysis in Figure 1 used longitudinal cohorts of different patients with only some overlap at each timepoint. We therefore tracked changes in unstimulated IFN-\u0026gamma; release across individual patients over time. Unstimulated IFN-\u0026gamma; release in PBMCs from the same 7 patients with no Long COVID symptoms showed a clear decrease in spontaneous IFN-\u0026gamma; release by D180 (Figure 4b). By contrast, unstimulated IFN-\u0026gamma; release across 8 patients with Long COVID was persistent, with no overall downward trend but significant patient to patient variation (Figure 4c). Taken together, these data show that unstimulated IFN-\u0026gamma; release usually resolves following acute infection but persist in the cohort of patients who progress to Long COVID.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVaccination-induced anti-Spike antibody correlates with decreased IFN-\u0026gamma; production and Long COVID symptoms improvement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinally, a considerable number of patients experienced an alleviation of some, if not all, Long COVID symptoms following SARS-CoV-2 vaccination during Long COVID [10]. We postulated that unstimulated IFN-\u0026gamma; release may correlate with some of the Long COVID symptoms and therefore tested whether unstimulated IFN-\u0026gamma; release decreases post vaccination. We measured unstimulated IFN-\u0026gamma; release in Long COVID patients before and after vaccination, which we confirmed by anti-spike fluorospot assay (Figure 5a) and found a significant decrease post vaccination (Figure 5b), which correlated with their improved symptoms (Figure 5c), reinforcing the evidence that unstimulated IFN-\u0026gamma; release correlates with Long COVID symptoms (Figure 5). To demonstrate that these patients responded to vaccination, we also measured IL-2 release following spike stimulation. All donors showed increased responses to spike post vaccination (Figure 5). Despite a reported lack of T cell responses after vaccination [13], we observed an increase in all donors. No pattern of discernible symptoms were associated with post vaccination improvement (Table S1).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLong COVID is an important, emerging, long-term clinical problem resulting from the COVID-19 pandemic. Although the likelihood of acute COVID-19 illness progressing to severe Long COVID may be low, with over 600 million infections by August 2022, the large number of people living with Long COVID will be a burden for health services with negative impact on different facets of society as a whole. Understanding the molecular mechanisms underlying Long COVID is therefore of paramount importance, as this will help in designing novel treatment options for patients in need. In this study, we reveal that CD8\u003csup\u003e+\u003c/sup\u003e T cells from patients diagnosed with Long COVID secrete increased levels of IFN-\u0026gamma;, spontaneously without peptide stimulation, compared to healthy controls. Vaccination appears to decrease this\u0026nbsp;IFN-\u0026gamma; secretion, correlating with improved symptoms in patients with Long COVID.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study shows that infection with SARS-CoV-2 triggers increased spontaneous IFN-\u0026gamma; secretion, which resolves in most patients by 6 months post-infection. This suggests that Long COVID lasting over 6 months could be differently classified to that lasting 12 weeks based on this\u0026nbsp;IFN-\u0026gamma; signature. Indeed, our data suggests that most patients have not resolved their\u0026nbsp;IFN-\u0026gamma; secretion at 3 months post infection, which agrees with studies finding that many patients report ongoing symptoms 12 weeks after infection.\u003c/p\u003e\n\u003cp\u003eWe also observed increases in IL-1\u0026beta;, IL-6, GM-CSF and G-CSF\u0026nbsp;secretion from patients with Long COVID, raising the possibility that other pro-inflammatory cytokines maybe perturbed as well, as has been observed by others at 8 months post infection\u0026nbsp;[14].\u0026nbsp;IFN-\u0026gamma; secretion showed the strongest change however. We observed that our Long COVID cohort had variable IFN-\u0026gamma; secretion: around 30% showed levels within the range seen for our unexposed controls. Conversely, four of our unexposed controls showed high levels of\u0026nbsp;IFN-\u0026gamma; secretion. We believe that the four unexposed donors may have been infected or recovering from an infection at the time of donation, which led to higher\u0026nbsp;IFN-\u0026gamma; secretion. From the Long COVID cohort, the lower\u0026nbsp;IFN-\u0026gamma; secretion may occur for a number of reasons. Firstly, as\u0026nbsp;IFN-\u0026gamma; secretion varies with time (Figure 4c), it may be the case that these patients donated at a nadir in their cycle of IFN-\u0026gamma;\u0026nbsp;secretion, causing a low result. We would like to follow these patients with longitudinal blood sampling and analysis to determine if\u0026nbsp;IFN-\u0026gamma; secretion does indeed cycle and if it correlates with symptom severity. Secondly, we expect that some donors in this cohort do not have Long COVID, but instead have different underlying conditions that manifest with symptoms overlapping with those found in Long COVID patients. In the setting of a large patient cohort, it may be possible to compare symptom profiles between patients with high IFN-\u0026gamma;\u0026nbsp;secretion and those with consistently low IFN-\u0026gamma;\u0026nbsp;secretion to narrow the range of symptoms that are associated with Long COVID and exclude others.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt this stage it is not clear whether\u0026nbsp;IFN-\u0026gamma; is a mediator or a biomarker of Long COVID symptoms. Use of\u0026nbsp;IFN-\u0026gamma; treatment for viral infections such as hepatitis C is associated with symptoms such as\u0026nbsp;fever, diarrhoea,\u0026nbsp; headache, chills, nausea, myalgia, and/or fatigue\u0026nbsp;[15]\u0026nbsp;as well as psychological symptoms such as depression and anxiety\u0026nbsp;[16]. As some of the symptoms of IFN-\u0026gamma; therapy are similar to those in patients with Long COVID, it is plausible that aberrant unstimulated\u0026nbsp;IFN-\u0026gamma; production may be a causative factor. If not, our findings of\u0026nbsp;IFN-\u0026gamma; secretion makes it an essential biomarker for Long COVID, which if explored in the context of a larger patient cohort, has the potential to reveal pathophysiological basis of Long COVID and lead to the discovery of pharmacological treatments. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDysregulated interferon signalling is a hallmark of SARS-CoV-2 infection and plays a key role in disease severity and progression\u0026nbsp;[17]\u0026nbsp;[18]. It is possible that viral antigens carried by antigen presenting CD14\u003csup\u003e+\u003c/sup\u003e cells stimulate CD8\u003csup\u003e+\u003c/sup\u003e T cells, leading to\u0026nbsp;IFN-\u0026gamma; secretion in the absence of \u003cem\u003eex-vivo\u003c/em\u003e peptide stimulation. The fact that many SARS-CoV-2 infected patients show this\u0026nbsp;IFN-\u0026gamma; secretion phenomenon more than 3 months after infection is in line with observations by others that SARS-CoV-2 antigens persist long after infection, even up to 15 months post infection\u0026nbsp;[19-21]. We find the Long COVID patients tend to show persistent\u0026nbsp;unstimulated IFN-\u0026gamma; secretion, in keeping with their unremitting symptoms. In conjunction with patients\u0026rsquo; reports, our findings highlight that SARS-CoV-2 is indeed the trigger leading to symptoms. Long COVID has some features similar to generic post viral syndrome, hence the accumulation of pro-inflammatory cytokines is suggested as a cause of Long COVID\u0026nbsp;[22]. Increased CD14+ cells and decreased regulatory T cells may be exacerbating this inflammatory state.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven that conditions associated with post-infectious autoimmunity are well characterised, it is also possible that molecular mimicry is generating a class of anti-self T cells that are responding to self-antigens presented by CD14\u003csup\u003e+\u003c/sup\u003e cells. This hypothesis would agree with the detected presence of auto antibodies in those with Long COVID prior to infection\u0026nbsp;[23, 24].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eChronic post viral symptoms occur for other infections including\u0026nbsp;10% of those infected with SARS-CoV-1 and Middle Eastern Respiratory Syndrome (MERS)\u0026nbsp;[25-31]; EBV, dengue and influenza,\u0026nbsp;[32-36], regardless of disease severity\u0026nbsp;[32]. For future work, it is worthwhile investigating whether patients with chronic post viral symptoms also exhibit high\u0026nbsp;IFN-\u0026gamma; secretion, and if this is the case, then it could be a biomarker with wider utility. As both the build-up of inflammatory cytokines in the central nervous system has been proposed as a cause for Long COVID and chronic fatigue syndrome (CFS)\u0026nbsp;[22, 37], and also since CFS can be triggered by viral infections\u0026nbsp;[33], it will be interesting to see if\u0026nbsp;IFN-\u0026gamma; secretion is higher in patients with CFS as well.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, although we observed that vaccination reduced IFN-\u0026gamma; secretion in those with Long COVID, consistent with IFN-\u0026gamma; being a marker associated with the symptoms, the mechanism behind this remains unclear. If SARS-CoV-2 antigens continue to persist in people with Long COVID, triggering an IFN-\u0026gamma; response, then vaccination may be helping to clear this antigen. Alternatively, activation of the immune system by vaccination may allow for expression of PD-1 and other markers to switch the immune system off. Vaccination perhaps could be used as a method to alleviate Long COVID symptoms, at least until better treatments are developed. We hope that our discoveries will provide a basis for Long COVID treatments and diagnostics in the future.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eEthics and sample collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline characteristics, patient demographics and clinical symptoms of the study cohort are found in\u0026nbsp;[11].\u0026nbsp;Study participants were recruited between 31\u003csup\u003est\u003c/sup\u003e of May 2020 and 31\u003csup\u003est\u003c/sup\u003e of July 2021 from patients attending the Infectious Diseases led Long COVID clinic at Addenbrooke\u0026rsquo;s Hospital. The majority were non-hospitalised patients from the initial phase of the pandemic and the clinical and epidemiological history played the most significant part in triaging patients into the Long COVID clinic. However, a combination of any of the following parameters were used to triage patients into the clinic; epidemiological and clinical history (both initially assessed by referring General Practitioners), a confirmed diagnosis of COVID-19 by nucleic acid amplification test (including point-of-care testing) and SARS-CoV-2 seropositivity. The Long COVID study patients were recruited and consented under the Cambridge COVID-19 NIHR BioResource joint Consent Form (Research Ethics Committee (NRES number (REC)) no. T1gC1) study NBR87.\u003c/p\u003e\n\u003cp\u003eThe COVID confirmed hospitalised patients (Day 28, Day 90 and Day 180), were enrolled following admission to Addenbrooke\u0026rsquo;s hospital, Royal Papworth and Cambridge and Peterborough Foundation Trust with a confirmed diagnosis of COVID-19 via a positive RT-qPCR test for SARS-CoV-2 as stated in\u0026nbsp;[38]. Recruitment of inpatients at Addenbrooke\u0026rsquo;s Hospital and health-care workers was undertaken by the National Institute for Health Research (NIHR) Cambridge Clinical Research Facility outreach team and the NIHR BioResource research nurse team as stated in\u0026nbsp;[38]. Informed consent was obtained from all participants. Each participant provided 32ml of peripheral venous blood collected into a 9-ml sodium citrate tube. Clinical data was collected at clinic visit and routine laboratory tests and inflammatory cytokine panel were assayed appropriately where clinically relevant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSerology testing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSARS-CoV-2 serology by multiplex particle-based flow cytometry (Luminex): Recombinant SARS-CoV-2 N, S and RBD were covalently coupled to distinct carboxylated bead sets (Luminex; Netherlands) to form a 3-plex assay. The S protein construct used is S-R/PP\u0026nbsp;[39]. The RBD protein construct used is described by Stadlbauer et. al,\u0026nbsp;[40].\u0026nbsp;Beads were first activated with 1-ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride\u0026nbsp;(Thermo Fisher Scientific) in the presence of N-hydroxysuccinimide (Thermo Fisher Scientific),\u0026nbsp;according to the manufacturer\u0026rsquo;s instructions, to form amine-reactive intermediates. The\u0026nbsp;activated bead sets were incubated with the corresponding proteins at a concentration of 50\u0026nbsp;\u0026mu;g/ml in the reaction mixture for 3 hours at room temperature on a rotator. Beads were washed\u0026nbsp;and stored in a blocking buffer (10 mM PBS, 1% BSA, 0.05% NaN3).\u003c/p\u003e\n\u003cp\u003eThe N-, S- and RBD-coupled bead sets were incubated with proband sera at a 1/100 dilution for\u0026nbsp;1 h in 96-well filter plates (MultiScreen HTS; Millipore) at room temperature in the dark on a\u0026nbsp;horizontal shaker. Fluids were aspirated with a vacuum manifold and beads were washed three\u0026nbsp;times with 10 mM PBS/0.05% Tween 20. Beads were incubated for 30 min with a PE-labelled\u0026nbsp;anti\u0026ndash;human IgG-Fc antibody (Leinco/Biotrend), washed as described above, and resuspended in\u0026nbsp;100 \u0026mu;l PBS/Tween. They were then analysed on a Luminex analyser (Luminex / R\u0026amp;D Systems)\u0026nbsp;using Exponent Software V31. Specific binding was reported as mean fluorescence intensities\u0026nbsp;(MFI). N protein was kindly provided by Dr Leo James. RBD was provided by Dr James Nathan. Trimeric S was provided by Dr John Briggs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePBMC isolation from patient blood and magnetic activated cell sorting (MACS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral blood mononuclear cells (PBMCs) were isolated from citrated blood samples by layering blood onto Lymphoprep (Axis-shield, Oslo, Norway) and performing density gradient centrifugation at 1200 xg for 10 mins. PBMCs at the interface were collected and washed 2x in PBS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePositive selection of monocytes was performed using magnetic activated cell sorting (MACS) with CD14\u003csup\u003e+\u003c/sup\u003e, CD4\u003csup\u003e+\u003c/sup\u003e or CD8\u003csup\u003e+\u003c/sup\u003e microbeads (Miltenyi Biotec) as detailed in the manufacturer\u0026rsquo;s protocol. Whenever PBMCs, CD4/8/14\u003csup\u003e+\u003c/sup\u003e cell-depleted PBMCs or isolated cells were plated for fluorospot analysis, cells were resuspended in the same volume (2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e PBMCs per well) and then plated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDual FluoroSpot Assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e PBMCs suspended in TexMACS (Miltenyi Biotech) supplemented with 5% Human AB serum (Sigma Aldrich) were incubated on FluoroSpot plates coated with Human IFN-\u0026gamma; and IL-2 antibodies or Human IFN-\u0026gamma;, TNF-\u0026alpha; or IL-10 antibodies [FluoroSpot (Mabtech AB, Nacka Strand, Sweden)] in duplicate with spike ORF peptides (final peptide concentration 2 \u0026mu;g/ml/peptide) or TexMACS-only negative control and positive control mix [containing anti-CD3 (Mabtech AB), Staphylococcus Enterotoxin B, and Lipopolysaccharide (all Sigma-Aldrich)] at 37\u0026deg;C in a humidified CO2 atmosphere for 48 h (or 24 h where indicated). The cells and medium were decanted from the plate and the assay developed following the manufacturer\u0026rsquo;s instructions. Developed plates were read using an AID iSpot reader (Oxford Biosystems, Oxford, UK) and counted using AID EliSpot v7 software (Autoimmun Diagnostika GmbH, Strasberg, Germany) using distinct counting protocols for IFN-\u0026gamma;, TNF-\u0026alpha;, IL-10 or IL-2 secretion. Donor results were discounted from further analysis if there was less than 100 sfu in the positive control relative to the background sfu. Spike response data in Figure 5 was corrected for background cytokine production by subtracting the negative control.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe used a peptide pool for spike as recently published\u0026nbsp;[41]: \u0026ldquo;A peptide pool was generated using the following: 1. PepTivator SARS-CoV-2 Prot_S containing the sequence domains aa 304-338, 421- 475, 492-519, 683-707, 741-770, 785-802, and 885 \u0026ndash; 1273 and S1\u0026nbsp;N-terminal S1 domain of the surface glycoprotein (\u0026quot;S\u0026quot;) of SARS-Coronavirus 2 (GenBank MN908947.3, Protein QHD43416.1). 2. The PepTivator SARS-CoV-2 Prot_S1 containing the aa sequence 1\u0026ndash;692. The peptides used are 15aa\u0026nbsp;amino\u0026nbsp;acids with 11 amino acid overlaps.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbsolute count enumeration of lymphocyte subsets\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe absolute number of immune cells present in whole blood samples was enumerated using Becton Dickinson Trucount tubes (BD Biosciences, Oxford, UK) following the manufacturer\u0026rsquo;s instructions. Briefly, 50\u0026micro;l of the EDTA treated whole blood samples was stained in the Trucount tube with a pre-mixed antibody cocktail (detailed in Table S2) allowing the identification of monocytes, B cells, CD4+ and CD8+ T cells, T cell memory subsets and activated T cells and NK cells. \u0026nbsp;Following staining, the red blood cells were lysed and the cells fixed using FACS Lysing solution (BD Biosciences) and then stored at -80\u0026deg;C until acquisition[42]. Samples were acquired on a 5-laser LSR Fortessa (BD Biosciences) with Fluorescence Minus One Controls and single colour compensation controls (AbC Total Antibody Compensation Bead Kit \u0026ndash; Thermo Fisher Scientific) utilized. Samples were analysed and enumerated using Flowjo software (BD Biosciences) following the gating strategy and the formula illustrated in Figure S4. \u0026nbsp;Results were expressed as the number of each immune cell subset per microliter of blood (cells/\u0026micro;l).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasuring IFN\u0026gamma; secretion by flow cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePBMC (2.5 x106) from long covid patients and healthy controls were suspended in TexMACS medium (Miltenyi Biotec) were unstimulated or stimulated with a positive-control mix (containing anti-CD3 (Mabtech AB), Staphylococcus Enterotoxin B (SEB), Phytohemagglutinin (PHA), Pokeweed Mitogen (PWM), and Lipopolysaccharide (LPS) (all Sigma-Aldrich)) for 1 hour and then 5 \u0026micro;g/ml brefeldin A and 2 \u0026micro;M monensin (both from BioLegend) were added and the cells were incubated overnight at 37\u0026deg;C in a humidified CO2 atmosphere. The cells were then washed and stained with a combination of surface antibodies comprising CD3 BV650, CD14 FITC, CD19 BV510 (BioLegend) and LIVE/DEAD fixable Aqua dead cell stain (Thermo Fisher Scientific) at 4\u0026deg;C. The cells were fixed, permeabilized using a FIX \u0026amp; PERM\u0026trade; cell permeabilization kit (Thermo Fisher Scientific) and stained intracellularly with CD69 Pacific Blue, CD8 BV570, CD4 BV605, CD134 (OX-40) PE, 4-1BB PE\u0026ndash;Cy5, CD40L PerCP-Cy5.5 (BioLegend) and IFN-\u0026gamma; BV786 (BD Biosciences) at 4\u0026deg;C in the dark. Full details of the antibodies used in the assay are provided in Table S3. Samples were washed and fixed with FluoroFix\u0026trade; Buffer (BioLegend) and acquired on a BD LSR Fortessa cytometer using FACSDiva software. The data were analyzed using FlowJo software following the gating strategy illustrated in Figure S5 the production of IFN-\u0026gamma; and expression of activation markers on resting and stimulated CD4+ and CD8+ T cells in healthy controls compared to long covid patients was assessed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasuring cytokine secretion by Legendplex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCytokine secretion between Long COVID and healthy control PBMCs were compared using LEGENDplex COVID-19 Cytokine Storm Panels 1\u0026amp;2 (13 plex \u0026amp; 12 plex, Cat Nos: 741091\u0026amp;741142 respectively) from Biolegend. \u0026nbsp;PBMCs from n=10 healthy controls and n=14 patients with Long COVID. After 48 hours incubation, media was collected and loaded onto Legenplex plates at 1:2 dilution, following manufacturer\u0026rsquo;s protocol. Samples were analysed using a BD Accuri C6 following manufacturer\u0026rsquo;s instructions, and cytokine concentrations were calculated against a standard curve provided by the manufacturer using Biolegend\u0026rsquo;s software (https://www.biolegend.com/en-us/legendplex).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Handling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were determined to be non-parametric by Shapiro-Wilk analysis. We therefore used non-parametric statistical analysis (Mann\u0026ndash;Whitney U, Kruskal\u0026ndash;Wallis one-way analysis of variance, Wilcoxon signed-rank test) throughout.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualisation, MRW, NS; Methodology, MRW, NS, BAK; Investigation \u0026amp; Data Collection, BAK, EYL, LM, RD, MRW, NS; Supervision \u0026ndash; NJM, PJL, MRW, NS; Writing \u0026ndash; Original Draft, BAK, MRW, NS; Writing \u0026ndash; Review \u0026amp; Editing, BAK, EYL, LM, PL, RD, JB, KGCS, JS, NJM, PJL, MRW and NS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Addenbrooke\u0026apos;s Charitable Trust (900276 to NS), NIHR award (G112259 to NS), a BIA grant (G101370 to NS), and supported by the NIHR Cambridge Biomedical Research Centre. NJM is supported by the MRC (TSF MR/T032413/1) and NHSBT (WPA15-02). PJL is supported by the Wellcome Trust (PRF 210688/Z/18/Z, 084957/Z/08/Z), a Medical Research Council research grant MR/V011561/1 and the United Kingdom Research and an Innovation COVID Immunology Consortium grant (MR/V028448/1). We would also like to thank Meritxell Nus\u0026nbsp;for helpful communications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNIHR BioResource\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJohn Allison, Heather Biggs, John Bradley, Helen Butcher, Daniela Caputo, Matt Chandler, Debbie Clapham-Riley, Patrick Chinnery, Anne-Maree Dean, Eleanor Dewhurst, Christian Fernandez, Anita Furlong, Anne George, Barbara Graves, Jennifer Gray, Sabine Hein, Tasmin Ivers, Mary Kasanicki, Nathalie Kingston, Emma Le Gresley, Rachel Linger, Sarah Meloy, Alexei Moulton, Francesca Muldoon, Nigel Ovington, Roxana Paraschiv, Sofia Papadia, Isabel Phelan, Christopher Penkett, Venkatesh Ranganath, Jennifer Sambrook, Katherine Schon, Hannah Stark, Kathleen E Stirrups, Paul Townsend, Julie von Ziegenweidt, Neil Walker, \u0026nbsp;Jennifer Webster\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eScherlinger, M., et al., \u003cem\u003eRefining “Long-COVID” by a Prospective Multimodal Evaluation of Patients with Long-Term Symptoms Attributed to SARS-CoV-2 Infection.\u003c/em\u003e Infectious Diseases and Therapy, 2021: p. 1-17.\u003c/li\u003e\n\u003cli\u003eHuang, C., et al., \u003cem\u003e6-month consequences of COVID-19 in patients discharged from hospital: a cohort study.\u003c/em\u003e The Lancet, 2021. \u003cstrong\u003e397\u003c/strong\u003e(10270): p. 220-232.\u003c/li\u003e\n\u003cli\u003eAyoubkhani, D., et al., \u003cem\u003ePost-covid syndrome in individuals admitted to hospital with covid-19: retrospective cohort study.\u003c/em\u003e bmj, 2021. \u003cstrong\u003e372\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eGupta, A., et al., \u003cem\u003eExtrapulmonary manifestations of COVID-19.\u003c/em\u003e Nature medicine, 2020. \u003cstrong\u003e26\u003c/strong\u003e(7): p. 1017-1032.\u003c/li\u003e\n\u003cli\u003eThompson, E.J., et al., \u003cem\u003eRisk factors for long COVID: analyses of 10 longitudinal studies and electronic health records in the UK.\u003c/em\u003e medRxiv, 2021.\u003c/li\u003e\n\u003cli\u003eLogue, J.K., et al., \u003cem\u003eSequelae in adults at 6 months after COVID-19 infection.\u003c/em\u003e JAMA network open, 2021. \u003cstrong\u003e4\u003c/strong\u003e(2): p. e210830-e210830.\u003c/li\u003e\n\u003cli\u003ePetersen, M.S., et al., \u003cem\u003eLong COVID in the Faroe Islands-a longitudinal study among non-hospitalized patients.\u003c/em\u003e Clinical infectious diseases: an official publication of the Infectious Diseases Society of America, 2020.\u003c/li\u003e\n\u003cli\u003eLaVergne, S.M., et al., \u003cem\u003eA longitudinal SARS-CoV-2 biorepository for COVID-19 survivors with and without post-acute sequelae.\u003c/em\u003e BMC Infect Dis, 2021. \u003cstrong\u003e21\u003c/strong\u003e(1): p. 677.\u003c/li\u003e\n\u003cli\u003eTownsend, L., et al., \u003cem\u003ePersistent poor health after COVID-19 is not associated with respiratory complications or initial disease severity.\u003c/em\u003e Annals of the American Thoracic Society, 2021. \u003cstrong\u003e18\u003c/strong\u003e(6): p. 997-1003.\u003c/li\u003e\n\u003cli\u003eStrain, W.D., et al., \u003cem\u003eThe Impact of COVID Vaccination on Symptoms of Long COVID. An International Survey of People with Lived Experience of Long COVID.\u003c/em\u003e An International Survey of People with Lived Experience of Long COVID.\u003c/li\u003e\n\u003cli\u003eKrishna, B.A., et al., \u003cem\u003eEvidence of previous SARS-CoV-2 infection in seronegative patients with long COVID.\u003c/em\u003e eBioMedicine, 2022. \u003cstrong\u003e81\u003c/strong\u003e: p. 104129.\u003c/li\u003e\n\u003cli\u003eJackson, S.E., et al., \u003cem\u003eLatent cytomegalovirus (CMV) infection does not detrimentally alter T cell responses in the healthy old, but increased latent CMV carriage is related to expanded CMV-specific T cells.\u003c/em\u003e Frontiers in immunology, 2017. \u003cstrong\u003e8\u003c/strong\u003e: p. 733.\u003c/li\u003e\n\u003cli\u003eReynolds, C.J., et al., \u003cem\u003ePrior SARS-CoV-2 infection rescues B and T cell responses to variants after first vaccine dose.\u003c/em\u003e Science, 2021. \u003cstrong\u003e372\u003c/strong\u003e(6549): p. 1418.\u003c/li\u003e\n\u003cli\u003ePhetsouphanh, C., et al., \u003cem\u003eImmunological dysfunction persists for 8 months following initial mild-moderate SARS-CoV-2 infection.\u003c/em\u003e medRxiv, 2021.\u003c/li\u003e\n\u003cli\u003eMiller, C.H.T., S.G. Maher, and H.A. Young, \u003cem\u003eClinical Use of Interferon-gamma.\u003c/em\u003e Annals of the New York Academy of Sciences, 2009. \u003cstrong\u003e1182\u003c/strong\u003e: p. 69-79.\u003c/li\u003e\n\u003cli\u003ePinto, E.F. and C. Andrade, \u003cem\u003eInterferon-Related Depression: A Primer on Mechanisms, Treatment, and Prevention of a Common Clinical Problem.\u003c/em\u003e Current neuropharmacology, 2016. \u003cstrong\u003e14\u003c/strong\u003e(7): p. 743-748.\u003c/li\u003e\n\u003cli\u003eAcharya, D., G. Liu, and M.U. Gack, \u003cem\u003eDysregulation of type I interferon responses in COVID-19.\u003c/em\u003e Nat Rev Immunol, 2020. \u003cstrong\u003e20\u003c/strong\u003e(7): p. 397-398.\u003c/li\u003e\n\u003cli\u003eInitiative, C.-H.G., \u003cem\u003eMapping the human genetic architecture of COVID-19.\u003c/em\u003e Nature.\u003c/li\u003e\n\u003cli\u003eGarcía-Abellán, J., et al., \u003cem\u003eAntibody Response to SARS-CoV-2 is Associated with Long-term Clinical Outcome in Patients with COVID-19: a Longitudinal Study.\u003c/em\u003e Journal of Clinical Immunology, 2021.\u003c/li\u003e\n\u003cli\u003ePatterson, B.K., et al., \u003cem\u003ePersistence of SARS CoV-2 S1 protein in CD16+ monocytes in post-acute sequelae of COVID-19 (PASC) up to 15 months post-infection.\u003c/em\u003e bioRxiv, 2021.\u003c/li\u003e\n\u003cli\u003eCarmo, A., et al., \u003cem\u003eClearance and persistence of SARS‐CoV‐2 RNA in patients with COVID‐19.\u003c/em\u003e Journal of medical virology, 2020. \u003cstrong\u003e92\u003c/strong\u003e(10): p. 2227-2231.\u003c/li\u003e\n\u003cli\u003ePerrin, R., et al., \u003cem\u003eInto the looking glass: Post-viral syndrome post COVID-19.\u003c/em\u003e Medical hypotheses, 2020. \u003cstrong\u003e144\u003c/strong\u003e: p. 110055-110055.\u003c/li\u003e\n\u003cli\u003eWang, E.Y., et al., \u003cem\u003eDiverse Functional Autoantibodies in Patients with COVID-19.\u003c/em\u003e medRxiv, 2021: p. 2020.12.10.20247205.\u003c/li\u003e\n\u003cli\u003eNalbandian, A., et al., \u003cem\u003ePost-acute COVID-19 syndrome.\u003c/em\u003e Nature medicine, 2021. \u003cstrong\u003e27\u003c/strong\u003e(4): p. 601-615.\u003c/li\u003e\n\u003cli\u003eAhmed, H., et al., \u003cem\u003eLong-term clinical outcomes in survivors of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronavirus outbreaks after hospitalisation or ICU admission: a systematic review and meta-analysis.\u003c/em\u003e Journal of rehabilitation medicine, 2020. \u003cstrong\u003e52\u003c/strong\u003e(5): p. 1-11.\u003c/li\u003e\n\u003cli\u003eHui, D., et al., \u003cem\u003eImpact of severe acute respiratory syndrome (SARS) on pulmonary function, functional capacity and quality of life in a cohort of survivors.\u003c/em\u003e Thorax, 2005. \u003cstrong\u003e60\u003c/strong\u003e(5): p. 401-409.\u003c/li\u003e\n\u003cli\u003eLam, M.H.-B., et al., \u003cem\u003eMental morbidities and chronic fatigue in severe acute respiratory syndrome survivors: long-term follow-up.\u003c/em\u003e Archives of internal medicine, 2009. \u003cstrong\u003e169\u003c/strong\u003e(22): p. 2142-2147.\u003c/li\u003e\n\u003cli\u003eLee, A.M., et al., \u003cem\u003eStress and psychological distress among SARS survivors 1 year after the outbreak.\u003c/em\u003e The Canadian Journal of Psychiatry, 2007. \u003cstrong\u003e52\u003c/strong\u003e(4): p. 233-240.\u003c/li\u003e\n\u003cli\u003eMoldofsky, H. and J. Patcai, \u003cem\u003eChronic widespread musculoskeletal pain, fatigue, depression and disordered sleep in chronic post-SARS syndrome; a case-controlled study.\u003c/em\u003e BMC neurology, 2011. \u003cstrong\u003e11\u003c/strong\u003e(1): p. 1-7.\u003c/li\u003e\n\u003cli\u003eOng, K.C., et al., \u003cem\u003ePulmonary function and exercise capacity in survivors of severe acute respiratory syndrome.\u003c/em\u003e European Respiratory Journal, 2004. \u003cstrong\u003e24\u003c/strong\u003e(3): p. 436-442.\u003c/li\u003e\n\u003cli\u003eLee, S.H., et al., \u003cem\u003eDepression as a mediator of chronic fatigue and post-traumatic stress symptoms in Middle East respiratory syndrome survivors.\u003c/em\u003e Psychiatry investigation, 2019. \u003cstrong\u003e16\u003c/strong\u003e(1): p. 59.\u003c/li\u003e\n\u003cli\u003eSeet, R.C.S., A.M.L. Quek, and E.C.H. Lim, \u003cem\u003ePost-infectious fatigue syndrome in dengue infection.\u003c/em\u003e Journal of Clinical Virology, 2007. \u003cstrong\u003e38\u003c/strong\u003e(1): p. 1-6.\u003c/li\u003e\n\u003cli\u003eWhite, P.D., et al., \u003cem\u003ePredictions and associations of fatigue syndromes and mood disorders that occur after infectious mononucleosis.\u003c/em\u003e The Lancet, 2001. \u003cstrong\u003e358\u003c/strong\u003e(9297): p. 1946-1954.\u003c/li\u003e\n\u003cli\u003eBuchwald, D.S., et al., \u003cem\u003eAcute infectious mononucleosis: characteristics of patients who report failure to recover.\u003c/em\u003e Am J Med, 2000. \u003cstrong\u003e109\u003c/strong\u003e(7): p. 531-7.\u003c/li\u003e\n\u003cli\u003ePetersen, I., et al., \u003cem\u003eRisk and predictors of fatigue after infectious mononucleosis in a large primary-care cohort.\u003c/em\u003e Qjm, 2006. \u003cstrong\u003e99\u003c/strong\u003e(1): p. 49-55.\u003c/li\u003e\n\u003cli\u003eKatz, B.Z., et al., \u003cem\u003eChronic fatigue syndrome after infectious mononucleosis in adolescents.\u003c/em\u003e Pediatrics, 2009. \u003cstrong\u003e124\u003c/strong\u003e(1): p. 189-193.\u003c/li\u003e\n\u003cli\u003eHives, L., et al., \u003cem\u003eCan physical assessment techniques aid diagnosis in people with chronic fatigue syndrome/myalgic encephalomyelitis? A diagnostic accuracy study.\u003c/em\u003e BMJ open, 2017. \u003cstrong\u003e7\u003c/strong\u003e(11): p. e017521.\u003c/li\u003e\n\u003cli\u003eBergamaschi, L., et al., \u003cem\u003eLongitudinal analysis reveals that delayed bystander CD8+ T cell activation and early immune pathology distinguish severe COVID-19 from mild disease.\u003c/em\u003e Immunity, 2021. \u003cstrong\u003e54\u003c/strong\u003e(6): p. 1257-1275.e8.\u003c/li\u003e\n\u003cli\u003eXiong, X., et al., \u003cem\u003eA thermostable, closed SARS-CoV-2 spike protein trimer.\u003c/em\u003e Nature structural \u0026amp; molecular biology, 2020. \u003cstrong\u003e27\u003c/strong\u003e(10): p. 934-941.\u003c/li\u003e\n\u003cli\u003eStadlbauer, D., et al., \u003cem\u003eSARS‐CoV‐2 seroconversion in humans: a detailed protocol for a serological assay, antigen production, and test setup.\u003c/em\u003e Current protocols in microbiology, 2020. \u003cstrong\u003e57\u003c/strong\u003e(1): p. e100.\u003c/li\u003e\n\u003cli\u003eCollier, D.A., et al., \u003cem\u003eAge-related immune response heterogeneity to SARS-CoV-2 vaccine BNT162b2.\u003c/em\u003e Nature, 2021: p. 1-9.\u003c/li\u003e\n\u003cli\u003eHensley-McBain, T., et al., \u003cem\u003eOptimization of a whole blood phenotyping assay for enumeration of peripheral blood leukocyte populations in multicenter clinical trials.\u003c/em\u003e Journal of immunological methods, 2014. \u003cstrong\u003e411\u003c/strong\u003e: p. 23-36.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-2034285/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2034285/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAfter acute infection with Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), a significant proportion (0.2 – 30%) of patients experience persistent symptoms beyond 12 weeks, termed Long COVID. Understanding the mechanisms which cause this debilitating disease and identifying biomarkers for diagnostic, therapeutic and monitoring purposes is urgently required. Persistently high levels of IFN-γ were detected from peripheral blood mononuclear cells (PBMCs) of Long COVID patients using highly sensitive FluoroSpot assays. This IFN-γ release was seen in the absence of \u003cem\u003eex vivo \u003c/em\u003epeptide stimulation and remains persistently elevated in Long Covid patients, unlike the resolution seen in patients recovering from acute SARS-CoV-2 infection. IFN-γ release was CD8\u003csup\u003e+\u003c/sup\u003e T cell mediated and dependent on MHC-I antigen presentation by CD14\u003csup\u003e+\u003c/sup\u003e cells. After vaccination, a significant decrease in IFN-γ correlated with resolution of some Long COVID symptoms. Our study highlights a key mechanism underlying Long COVID, enabling the search for biomarkers and therapeutics in patients with Long COVID.\u003c/p\u003e","manuscriptTitle":"Spontaneous, persistent T-cell dependent IFN-γ release in patients who progress to Long COVID","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2022-11-21 17:59:26","doi":"10.21203/rs.3.rs-2034285/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2022-09-13 15:00:30","doi":"10.21203/rs.3.rs-2034285/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"feed5060-75ae-4841-a30b-9798ea3eb43e","owner":[],"postedDate":"November 21st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":17103836,"name":"Biological sciences/Immunology/Cytokines/Interferons"},{"id":17103837,"name":"Health sciences/Biomarkers/Diagnostic markers"}],"tags":[{"value":"featured","date":"2022-11-21 19:47:23"}],"updatedAt":"2022-11-29T08:56:36+00:00","versionOfRecord":[],"versionCreatedAt":"2022-11-21 17:59:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-2034285","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2034285","identity":"rs-2034285","version":["v2"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}