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      Defining the features and duration of antibody responses to SARS-CoV-2 infection associated with disease severity and outcome

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      1 , 2 , 1 , 1 , 1 , 3 , 4 , 1 , 1 , 1 , 1 , 5 , 6 , 1 , 3 , 1 , 7 , 8 , 5 , 9 , 8 , 10 , 11 , 3 , 1 , 8 , 10 , 12 , 13 , 14 , 1 , 13 , 14 , 5 , 6 , 2 , 10 , 1 , 8 , 1 , 6 , *
      Science Immunology
      American Association for the Advancement of Science

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          Abstract

          Illness severity in COVID-19 correlates with specificity of serological responses, but antibody levels decrease in most patients.

          Abstract

          SARS-CoV-2-specific antibodies, particularly those preventing viral spike receptor binding domain (RBD) interaction with host angiotensin-converting enzyme 2 (ACE2) receptor, can neutralize the virus. It is, however, unknown which features of the serological response may affect clinical outcomes of COVID-19 patients. We analyzed 983 longitudinal plasma samples from 79 hospitalized COVID-19 patients and 175 SARS-CoV-2-infected outpatients and asymptomatic individuals. Within this cohort, 25 patients died of their illness. Higher ratios of IgG antibodies targeting S1 or RBD domains of spike compared to nucleocapsid antigen were seen in outpatients who had mild illness versus severely ill patients. Plasma antibody increases correlated with decreases in viral RNAemia, but antibody responses in acute illness were insufficient to predict inpatient outcomes. Pseudovirus neutralization assays and a scalable ELISA measuring antibodies blocking RBD-ACE2 interaction were well correlated with patient IgG titers to RBD. Outpatient and asymptomatic individuals’ SARS-CoV-2 antibodies, including IgG, progressively decreased during observation up to five months post-infection.

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

            Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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              A pneumonia outbreak associated with a new coronavirus of probable bat origin

              Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats 1–4 . Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans 5–7 . Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV.
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                Author and article information

                Journal
                Sci Immunol
                Sci Immunol
                SciImmunol
                immunology
                Science Immunology
                American Association for the Advancement of Science
                2470-9468
                07 December 2020
                : 5
                : 54
                : eabe0240
                Affiliations
                [1 ]Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
                [2 ]Stanford ChEM-H and Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.
                [3 ]Department of Structural Biology, Stanford University, Stanford, USA.
                [4 ]ATUM, Newark, CA, USA
                [5 ]Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, Stanford University, Stanford, CA, USA.
                [6 ]Sean N. Parker Center for Allergy and Asthma Research, Stanford, CA, USA.
                [7 ]Stanford Blood Center, Palo Alto, CA, USA.
                [8 ]Department of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA.
                [9 ]Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA
                [10 ]Chan Zuckerberg Biohub, San Francisco, CA, USA.
                [11 ]Department of Bioengineering, Stanford University, Stanford, CA, USA.
                [12 ]Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA.
                [13 ]Department of Statistics, Stanford University, Stanford, CA, USA.
                [14 ]Department of Biomedical Data Sciences, Stanford University, Stanford, CA, USA.
                Author notes
                [* ]Corresponding author: sboyd1@ 123456stanford.edu
                [†]

                these authors contributed equally to this work.

                [‡]

                these authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-1582-1720
                http://orcid.org/0000-0001-6408-9495
                http://orcid.org/0000-0003-0377-6464
                http://orcid.org/0000-0002-1713-3163
                http://orcid.org/0000-0003-1977-253X
                http://orcid.org/0000-0002-3712-9188
                http://orcid.org/0000-0001-9837-4032
                http://orcid.org/0000-0003-2606-9367
                http://orcid.org/0000-0002-6921-1012
                http://orcid.org/0000-0001-6969-6200
                http://orcid.org/0000-0001-9385-7158
                http://orcid.org/0000-0001-6946-7627
                http://orcid.org/0000-0002-6532-9873
                http://orcid.org/0000-0002-3664-0072
                http://orcid.org/0000-0002-3894-685X
                http://orcid.org/0000-0001-5852-7639
                http://orcid.org/0000-0003-0553-5090
                http://orcid.org/0000-0002-2146-2955
                http://orcid.org/0000-0001-6503-4541
                http://orcid.org/0000-0001-8751-4810
                http://orcid.org/0000-0003-0963-044X
                Article
                abe0240
                10.1126/sciimmunol.abe0240
                7857392
                33288645
                2b943d2f-1088-4561-ba49-832c872fbe8b
                Copyright © 2020, American Association for the Advancement of Science

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 July 2020
                : 05 October 2020
                : 03 December 2020
                Categories
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                Coronavirus

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