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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Although microbial populations in the gut microbiome are associated with COVID-19 severity, a causal impact on patient health has not been established. Here we provide evidence that gut microbiome dysbiosis is associated with translocation of bacteria into the blood during COVID-19, causing life-threatening secondary infections. We first demonstrate SARS-CoV-2 infection induces gut microbiome dysbiosis in mice, which correlated with alterations to Paneth cells and goblet cells, and markers of barrier permeability. Samples collected from 96 COVID-19 patients at two different clinical sites also revealed substantial gut microbiome dysbiosis, including blooms of opportunistic pathogenic bacterial genera known to include antimicrobial-resistant species. Analysis of blood culture results testing for secondary microbial bloodstream infections with paired microbiome data indicates that bacteria may translocate from the gut into the systemic circulation of COVID-19 patients. These results are consistent with a direct role for gut microbiome dysbiosis in enabling dangerous secondary infections during COVID-19.