Recent studies have provided insights into the pathogenesis of coronavirus disease 2019 (COVID-19) 1 – 4 . However, the longitudinal immunological correlates of disease outcome remain unclear. Here we serially analysed immune responses in 113 patients with moderate or severe COVID-19. Immune profiling revealed an overall increase in innate cell lineages, with a concomitant reduction in T cell number. An early elevation in cytokine levels was associated with worse disease outcomes. Following an early increase in cytokines, patients with moderate COVID-19 displayed a progressive reduction in type 1 (antiviral) and type 3 (antifungal) responses. By contrast, patients with severe COVID-19 maintained these elevated responses throughout the course of the disease. Moreover, severe COVID-19 was accompanied by an increase in multiple type 2 (anti-helminths) effectors, including interleukin-5 (IL-5), IL-13, immunoglobulin E and eosinophils. Unsupervised clustering analysis identified four immune signatures, representing growth factors (A), type-2/3 cytokines (B), mixed type-1/2/3 cytokines (C), and chemokines (D) that correlated with three distinct disease trajectories. The immune profiles of patients who recovered from moderate COVID-19 were enriched in tissue reparative growth factor signature A, whereas the profiles of those with who developed severe disease had elevated levels of all four signatures. Thus, we have identified a maladapted immune response profile associated with severe COVID-19 and poor clinical outcome, as well as early immune signatures that correlate with divergent disease trajectories.
CLIA-certified laboratories were enrolled through the IMPACT biorepository study 15. In the IMPACT study, biospecimens including blood, nasopharyngeal swabs, saliva, urine and stool samples were collected at study enrolment (baseline denotes the first time point) and longitudinally on average every 3 to 7 days (serial time points). The detailed demographics and clinical characteristics of these 98 participants are shown in Extended Data Table 1. Plasma and peripheral blood mononuclear cells (PBMCs) were isolated from whole blood, and plasma was used for titre measurements of SARS-CoV-2 spike S1 protein-specific IgG and IgM antibodies (anti-S1-IgG and-IgM) and cytokine or chemokine measurements. Freshly isolated PBMCs were stained and analysed by flow cytometry 15. We obtained longitudinal serial time-point samples from a subset of these 98 study participants (n = 48; information in Extended Data Table 1). To compare the immune phenotypes between sexes, two sets of data analyses were performed in parallel-baseline and longitudinal, as described below. As a control group, healthcare workers (HCWs) from Yale-New Haven Hospital were enrolled who were uninfected with COVID-19. Demographics and background information for the HCW group and the demographics of HCWs for cytokine assays and flow cytometry assays for the primary analyses are in Extended Data Table 1. Demographic data, time-point information of the samples defined by the days from the symptom onset (DFSO) in each patient, treatment information, and raw data used to generate figures and tables is in Supplementary Table 1. Baseline analysis The baseline analysis was performed on samples from the first time point of patients who met the following criteria: not in intensive care unit (ICU), had not received tocilizumab, and had not received high doses of corticosteroids (prednisone equivalent of more than 40 mg) before the first sample collection date. This patient group, cohort A, consisted of 39 patients (17 male and 22 female) (Extended Data Tables 1, 2). Intersex and transgender individuals were not represented in this study. Figures 1-4 represent analyses of baseline raw values obtained from patients in cohort A. In cohort A patients, male and female patients were matched in terms of age, body mass index (BMI), and DFSO at the first time point sample collection (Extended Data Fig. 1a). However, there were significant differences in age and BMI between HCW controls and patients (patients had higher age and BMI values) (Extended Data Table 1), and therefore an age-and BMI-adjusted difference-indifferences analysis was also performed in parallel (Extended Data Table 3). Longitudinal analysis As parallel secondary analyses, we performed longitudinal analysis on a total patient cohort (cohort B) to evaluate the difference in immune response over the course of the disease between male and female patients. Cohort B included all patient samples from cohort A (including several time-point samples from the cohort A patients) as well as an additional 59 patients who d...
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; previously called "2019-nCoV"; the virus that causes coronavirus disease [COVID-19]) has infected .1,773,000 patients and killed .111,650 people worldwide as of April 13, 2020 (1). It has been reported that a patient in Germany had high viral titers after the resolution of fever and infected two close contacts after the resolution of symptoms (2). In the wake of these cases, it is still unclear how long the patient was virus positive after the resolution of symptoms. In this study, we aimed to determine the time kinetics of viral clearance in reference to the resolution of symptoms in 16 patients treated in Beijing, China, and we show that half of the patients with COVID-19 were virus positive even after resolution of their symptoms. Cases We studied all 16 patients with confirmed COVID-19 released from the treatment center of People's Liberation Army General Hospital in Beijing, China, between January 28 and February 9, 2020. On alternate days, all patients had throat swabs collected, which were then analyzed. Patients were discharged after their recovery and confirmation of "virus-negative" status by at least two consecutive real-time PCRs (3). There was only one case of a false-negative result in our study: patient 6 had a negative test result followed by a positive detection and then two consecutive negative tests. Travel and possible exposure history were obtained from the patients and noted on their records. Epidemiologically, 10 patients visited Wuhan after the outbreak; 3 had exposure to a known infected patient; 2 came in contact with people from Wuhan; and 1 had no known exposure. The basic clinical characteristics are given in Table 1. The median age was 35.5 years (range, 3-68 yr), with 11 of 16 being male. The major symptoms in these patients were fever (14 of 16), cough (11 of 16), pharyngalgia (5 of 16), and dyspnea (2 of 16). The day of onset and resolution of these symptoms were noted. Details of symptoms are indicated in the online supplement. Ground-glass opacities were observed by computed tomography of the chest in both sides of the lungs in six patients and only in the right lung in one patient. Concentrations of C-reactive protein and procalcitonin between the first sample obtained at the time of hospitalization and the last sample obtained before discharge were comparable (Table 1). All the patients received various medical care to treat COVID-19. Fifteen patients were treated with IFN-a together with other antiviral drugs, including oseltamivir (1 of 16), lopinavir/ritonavir (11 of 16),
The COVID-19 pandemic has affected more than 20 million people worldwide, with mortality exceeding 800,000 patients. Risk factors associated with severe disease and mortality include advanced age, hypertension, diabetes, and obesity. Each of these risk factors pathologically disrupts the lipidome, including immunomodulatory eicosanoid and docosanoid lipid mediators (LMs). We hypothesized that dysregulation of LMs may be a defining feature of the severity of COVID-19. By examining LMs and polyunsaturated fatty acid precursor lipids in serum from hospitalized COVID-19 patients, we demonstrate that moderate and severe disease are separated by specific differences in abundance of immune-regulatory and proinflammatory LMs. This difference in LM balance corresponded with decreased LM products of ALOX12 and COX2 and an increase LMs products of ALOX5 and cytochrome p450. Given the important immune-regulatory role of LMs, these data provide mechanistic insight into an immunolipidomic imbalance in severe COVID-19.
Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100Ahi/HLA-DRlo classical monocytes and activated LAG-3hi T cells are hallmarks of progressive disease and highlights the abnormal MHC-II/LAG-3 interaction on myeloid and T cells, respectively. We also find skewed T cell receptor repertories in expanded effector CD8+ clones, unmutated IGHG+ B cell clones, and mutated B cell clones with stable somatic hypermutation frequency over time. In conclusion, our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19.
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