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      Sex differences in immune responses that underlie COVID-19 disease outcomes

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          Abstract

          A growing body of evidence indicates sex differences in the clinical outcomes of coronavirus disease 2019 (COVID-19) 15 . However, whether immune responses against SARS-CoV-2 differ between sexes, and whether such differences explain male susceptibility to COVID-19, is currently unknown. In this study, we examined sex differences in viral loads, SARS-CoV-2-specific antibody titers, plasma cytokines, as well as blood cell phenotyping in COVID-19 patients. By focusing our analysis on patients with moderate disease who had not received immunomodulatory medications, our results revealed that male patients had higher plasma levels of innate immune cytokines such as IL-8 and IL-18 along with more robust induction of non-classical monocytes. In contrast, female patients mounted significantly more robust T cell activation than male patients during SARS-CoV-2 infection, which was sustained in old age. Importantly, we found that a poor T cell response negatively correlated with patients’ age and was associated with worse disease outcome in male patients, but not in female patients. Conversely, higher innate immune cytokines in female patients associated with worse disease progression, but not in male patients. These findings reveal a possible explanation underlying observed sex biases in COVID-19, and provide important basis for the development of sex-based approach to the treatment and care of men and women with COVID-19.

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          Most cited references16

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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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            A Novel Coronavirus from Patients with Pneumonia in China, 2019

            Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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              Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

              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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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                10 September 2020
                26 August 2020
                December 2020
                26 February 2021
                : 588
                : 7837
                : 315-320
                Affiliations
                [1 ]Department of Immunobiology, Yale University School of Medicine, New Haven, CT, 06520, USA
                [2 ]Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520, USA
                [3 ]Department of Medicine, Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT, 06520, USA
                [4 ]Department of Biomedical Engineering, Yale School of Engineering & Applied Science, New Haven, CT, 06511, USA
                [5 ]Boyer Center for Molecular Medicine, Department of Microbial Pathogenesis, Yale University, New Haven, CT, 06510, USA
                [6 ]Department of Comparative Medicine, Yale University School of Medicine, New Haven, CT, 06520, USA
                [7 ]Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA
                [8 ]Department of Medicine, Section of Pulmonary and Critical Care Medicine; Yale University School of Medicine, New Haven, CT, 06520, USA
                [9 ]Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, 06520, USA
                [10 ]Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, 06520, USA
                [11 ]Yale Institute for Global Health, Yale University, New Haven, CT, 06520, USA
                [12 ]Yale School of Nursing, Yale University, Orange, CT, 06477, USA
                [13 ]Howard Hughes Medical Institute, Chevy Chase, MD, 20815, USA
                Author notes
                [21]

                These authors contributed equally

                [*]

                A list of authors and their affiliations appears at the end of the paper

                Author contributions

                A.I., S.B.O., A.I.K. conceived the study. C.L., P.W., J.K., J.S., T.M., J.E.O. defined parameters for flow cytometry experiments, collected and processed patient PBMC samples. P.W. acquired and analyzed the flow cytometry data. B.I., J.K., C.L., C.D.O. collected epidemiological and clinical data. F.L., A.M., J.S., E.Y.W., A.R. acquired and analyzed ELISA data. A.L.W., C.B.F.V., I.M.O., R.E., S.L., P.L., A.V., A.P., M.T. performed the virus RNA concentration assays. N.D.G. supervised virus RNA concentration assays. A.C-M., A.J.M. processed and stored patient specimens, J.B.F., C.D.C., and S.F. assisted in patient recruitment, W.L.S. supervised clinical data management, A.S. coordinated and secured funding for PBMC collection. T.T. designed the analysis scheme, analyzed, and interpreted the data for the baseline analyses. M.K.E. and S.B.O. designed the analysis scheme, and interpreted the data for the longitudinal analyses. M.K.E. analyzed the longitudinal data. T.T., M.K.E., and A.I. drafted the manuscript. A.I., A.M.R., S.B.O. revised the manuscript. A.I. secured funds and supervised the project.

                [] Address correspondence to Akiko Iwasaki, Department of Immunobiology, Yale University School of Medicine, S655, 300 Cedar Street, New Haven, CT, 06511. akiko.iwasaki@ 123456yale.edu
                Article
                NIHMS1622076
                10.1038/s41586-020-2700-3
                7725931
                32846427
                063fe402-0635-4ac1-b4b4-4070a2725c61

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