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      Proteomic blood profiling in mild, severe and critical COVID-19 patients

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          Abstract

          The recent SARS-CoV-2 pandemic manifests itself as a mild respiratory tract infection in most individuals, leading to COVID-19 disease. However, in some infected individuals, this can progress to severe pneumonia and acute respiratory distress syndrome (ARDS), leading to multi-organ failure and death. This study explores the proteomic differences between mild, severe, and critical COVID-19 positive patients to further understand the disease progression, identify proteins associated with disease severity, and identify potential therapeutic targets. Blood protein profiling was performed on 59 COVID-19 mild (n = 26), severe (n = 9) or critical (n = 24) cases and 28 controls using the OLINK inflammation, autoimmune, cardiovascular and neurology panels. Differential expression analysis was performed within and between disease groups to generate nine different analyses. From the 368 proteins measured per individual, more than 75% were observed to be significantly perturbed in COVID-19 cases. Six proteins (IL6, CKAP4, Gal-9, IL-1ra, LILRB4 and PD-L1) were identified to be associated with disease severity. The results have been made readily available through an interactive web-based application for instant data exploration and visualization, and can be accessed at https://phidatalab-shiny.rosalind.kcl.ac.uk/COVID19/. Our results demonstrate that dynamic changes in blood proteins associated with disease severity can potentially be used as early biomarkers to monitor disease severity in COVID-19 and serve as potential therapeutic targets.

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          Clinical Characteristics of Coronavirus Disease 2019 in China

          Wei-jie Guan, Zheng-yi Ni, Yu Hu … (2020)
          Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)
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            Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

            Nanshan Chen, Min Zhou, Xuan Dong … (2022)
            Summary Background In December, 2019, a pneumonia associated with the 2019 novel coronavirus (2019-nCoV) emerged in Wuhan, China. We aimed to further clarify the epidemiological and clinical characteristics of 2019-nCoV pneumonia. Methods In this retrospective, single-centre study, we included all confirmed cases of 2019-nCoV in Wuhan Jinyintan Hospital from Jan 1 to Jan 20, 2020. Cases were confirmed by real-time RT-PCR and were analysed for epidemiological, demographic, clinical, and radiological features and laboratory data. Outcomes were followed up until Jan 25, 2020. Findings Of the 99 patients with 2019-nCoV pneumonia, 49 (49%) had a history of exposure to the Huanan seafood market. The average age of the patients was 55·5 years (SD 13·1), including 67 men and 32 women. 2019-nCoV was detected in all patients by real-time RT-PCR. 50 (51%) patients had chronic diseases. Patients had clinical manifestations of fever (82 [83%] patients), cough (81 [82%] patients), shortness of breath (31 [31%] patients), muscle ache (11 [11%] patients), confusion (nine [9%] patients), headache (eight [8%] patients), sore throat (five [5%] patients), rhinorrhoea (four [4%] patients), chest pain (two [2%] patients), diarrhoea (two [2%] patients), and nausea and vomiting (one [1%] patient). According to imaging examination, 74 (75%) patients showed bilateral pneumonia, 14 (14%) patients showed multiple mottling and ground-glass opacity, and one (1%) patient had pneumothorax. 17 (17%) patients developed acute respiratory distress syndrome and, among them, 11 (11%) patients worsened in a short period of time and died of multiple organ failure. Interpretation The 2019-nCoV infection was of clustering onset, is more likely to affect older males with comorbidities, and can result in severe and even fatal respiratory diseases such as acute respiratory distress syndrome. In general, characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia. Further investigation is needed to explore the applicability of the MuLBSTA score in predicting the risk of mortality in 2019-nCoV infection. Funding National Key R&D Program of China.
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              Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

              Xiaobo Yang, Yuan Yu, Jiqian Xu … (2020)
              Summary Background An ongoing outbreak of pneumonia associated with the severe acute respiratory coronavirus 2 (SARS-CoV-2) started in December, 2019, in Wuhan, China. Information about critically ill patients with SARS-CoV-2 infection is scarce. We aimed to describe the clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia. Methods In this single-centered, retrospective, observational study, we enrolled 52 critically ill adult patients with SARS-CoV-2 pneumonia who were admitted to the intensive care unit (ICU) of Wuhan Jin Yin-tan hospital (Wuhan, China) between late December, 2019, and Jan 26, 2020. Demographic data, symptoms, laboratory values, comorbidities, treatments, and clinical outcomes were all collected. Data were compared between survivors and non-survivors. The primary outcome was 28-day mortality, as of Feb 9, 2020. Secondary outcomes included incidence of SARS-CoV-2-related acute respiratory distress syndrome (ARDS) and the proportion of patients requiring mechanical ventilation. Findings Of 710 patients with SARS-CoV-2 pneumonia, 52 critically ill adult patients were included. The mean age of the 52 patients was 59·7 (SD 13·3) years, 35 (67%) were men, 21 (40%) had chronic illness, 51 (98%) had fever. 32 (61·5%) patients had died at 28 days, and the median duration from admission to the intensive care unit (ICU) to death was 7 (IQR 3–11) days for non-survivors. Compared with survivors, non-survivors were older (64·6 years [11·2] vs 51·9 years [12·9]), more likely to develop ARDS (26 [81%] patients vs 9 [45%] patients), and more likely to receive mechanical ventilation (30 [94%] patients vs 7 [35%] patients), either invasively or non-invasively. Most patients had organ function damage, including 35 (67%) with ARDS, 15 (29%) with acute kidney injury, 12 (23%) with cardiac injury, 15 (29%) with liver dysfunction, and one (2%) with pneumothorax. 37 (71%) patients required mechanical ventilation. Hospital-acquired infection occurred in seven (13·5%) patients. Interpretation The mortality of critically ill patients with SARS-CoV-2 pneumonia is considerable. The survival time of the non-survivors is likely to be within 1–2 weeks after ICU admission. Older patients (>65 years) with comorbidities and ARDS are at increased risk of death. The severity of SARS-CoV-2 pneumonia poses great strain on critical care resources in hospitals, especially if they are not adequately staffed or resourced. Funding None.
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                Author and article information

                Contributors
                Hamel Patel:
                ORCID: http://orcid.org/0000-0001-7951-6728
                hamel.patel@kcl.ac.uk
                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 18 March 2021
                Publication date PMC-release: 18 March 2021
                Publication date Collection: 2021
                Volume: 11
                Electronic Location Identifier: 6357
                Affiliations
                [1 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, , King’s College London, ; London, UK
                [2 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), , King’s College London, ; De Crespigny Park, London, SE5 8AF UK
                [3 ]GRID grid.8761.8, ISNI 0000 0000 9919 9582, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, , University of Gothenburg, ; Göteborg, Sweden
                [4 ]Department of Psychiatry and Neurochemistry, Wallenberg Centre for Molecular and Translational Medicine, Institute of Neuroscience and Physiology, the SAHLGRENSKA Academy at the University of Gothenburg, Sahlgrenska University Hospital, MedTech West, Röda stråket 10B, 413 45 Göteborg, Sweden
                [5 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, , King’s College London, ; London, UK
                [6 ]GRID grid.454378.9, NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, ; London, UK
                [7 ]UK Dementia Research Institute at UCL, London, UK
                [8 ]GRID grid.83440.3b, ISNI 0000000121901201, Health Data Research UK London, University College London, ; 222 Euston Road, London, UK
                [9 ]GRID grid.83440.3b, ISNI 0000000121901201, Institute of Health Informatics, , University College London, ; 222 Euston Road, London, UK
                [10 ]GRID grid.485385.7, ISNI 0000 0004 0495 5357, The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, ; 222 Euston Road, London, UK
                [11 ]GRID grid.8761.8, ISNI 0000 0000 9919 9582, Department of Infectious Diseases, Institute of Biomedicine, , Sahlgrenska Academy, University of Gothenburg, ; Gothenburg, Sweden
                [12 ]GRID grid.1649.a, ISNI 000000009445082X, Department of Infectious Diseases, , Region Västra Götaland, Sahlgrenska University Hospital, ; Gothenburg, Sweden
                [13 ]GRID grid.1649.a, ISNI 000000009445082X, Clinical Neurochemistry Laboratory, , Sahlgrenska University Hospital, ; Mölndal, Sweden
                [14 ]GRID grid.83440.3b, ISNI 0000000121901201, Department of Neurodegenerative Disease, , UCL Institute of Neurology, ; London, UK
                [15 ]UK Dementia Research Institute at UCL, London, UK
                Author information
                http://orcid.org/0000-0001-7951-6728
                http://orcid.org/0000-0002-3579-8804
                http://orcid.org/0000-0003-4224-9245
                http://orcid.org/0000-0003-3930-4354
                Article
                Publisher ID: 85877
                DOI: 10.1038/s41598-021-85877-0
                PMC ID: 7973581
                PubMed ID: 33737684
                SO-VID: c4a92e24-839a-40e1-9664-6398eb17265a
                Copyright © © The Author(s) 2021
                License:

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 1 July 2020
                Date accepted : 8 March 2021
                Categories
                Subject: Article
                Custom metadata
                issue-copyright-statement © The Author(s) 2021

                ScienceOpen disciplines: Uncategorized
                Keywords: viral infection,proteomics
                Data availability:
                ScienceOpen disciplines: Uncategorized
                Keywords: viral infection, proteomics

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