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      SARS-CoV-2 and the Brain: What Do We Know about the Causality of ‘Cognitive COVID?

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          Abstract

          The second year of the COVID-19 (coronavirus disease) pandemic has seen the need to identify and assess the long-term consequences of a SARS-CoV-2 infection on an individual’s overall wellbeing, including adequate cognitive functioning. ‘Cognitive COVID’ is an informal term coined to interchangeably refer to acute changes in cognition during COVID-19 and/or cognitive sequelae with various deficits following the infection. These may manifest as altered levels of consciousness, encephalopathy-like symptoms, delirium, and loss of various memory domains. Dysexecutive syndrome is a peculiar manifestation of ‘Cognitive COVID’ as well. In the previous major outbreaks of viruses like SARS-CoV, MERS-CoV and Influenza. There have been attempts to understand the underlying mechanisms describing the causality of similar symptoms following SARS-CoV-2 infection. This review, therefore, is attempting to highlight the current understanding of the various direct and indirect mechanisms, focusing on the role of neurotropism of SARS-CoV-2, the general pro-inflammatory state, and the pandemic-associated psychosocial stressors in the causality of ‘Cognitive COVID.’ Neurotropism is associated with various mechanisms including retrograde neuronal transmission via olfactory pathway, a general hematogenous spread, and the virus using immune cells as vectors. The high amounts of inflammation caused by COVID-19, compounded with potential intubation, are associated with a deleterious effect on the cognition as well. Finally, the pandemic’s unique psychosocial impact has raised alarm due to its possible effect on cognition. Furthermore, with surfacing reports of post-COVID-vaccination cognitive impairments after vaccines containing mRNA encoding for spike glycoprotein of SARS-CoV-2, we hypothesize their causality and ways to mitigate the risk. The potential impact on the quality of life of an individual and the fact that even a minor proportion of COVID-19 cases developing cognitive impairment could be a significant burden on already overwhelmed healthcare systems across the world make it vital to gather further evidence regarding the prevalence, presentation, correlations, and causality of these events and reevaluate our approach to accommodate early identification, management, and rehabilitation of patients exhibiting cognitive symptoms.

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          Most cited references104

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          Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

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            Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding

            Summary Background In late December, 2019, patients presenting with viral pneumonia due to an unidentified microbial agent were reported in Wuhan, China. A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). As of Jan 26, 2020, more than 2000 cases of 2019-nCoV infection have been confirmed, most of which involved people living in or visiting Wuhan, and human-to-human transmission has been confirmed. Methods We did next-generation sequencing of samples from bronchoalveolar lavage fluid and cultured isolates from nine inpatients, eight of whom had visited the Huanan seafood market in Wuhan. Complete and partial 2019-nCoV genome sequences were obtained from these individuals. Viral contigs were connected using Sanger sequencing to obtain the full-length genomes, with the terminal regions determined by rapid amplification of cDNA ends. Phylogenetic analysis of these 2019-nCoV genomes and those of other coronaviruses was used to determine the evolutionary history of the virus and help infer its likely origin. Homology modelling was done to explore the likely receptor-binding properties of the virus. Findings The ten genome sequences of 2019-nCoV obtained from the nine patients were extremely similar, exhibiting more than 99·98% sequence identity. Notably, 2019-nCoV was closely related (with 88% identity) to two bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21, collected in 2018 in Zhoushan, eastern China, but were more distant from SARS-CoV (about 79%) and MERS-CoV (about 50%). Phylogenetic analysis revealed that 2019-nCoV fell within the subgenus Sarbecovirus of the genus Betacoronavirus, with a relatively long branch length to its closest relatives bat-SL-CoVZC45 and bat-SL-CoVZXC21, and was genetically distinct from SARS-CoV. Notably, homology modelling revealed that 2019-nCoV had a similar receptor-binding domain structure to that of SARS-CoV, despite amino acid variation at some key residues. Interpretation 2019-nCoV is sufficiently divergent from SARS-CoV to be considered a new human-infecting betacoronavirus. Although our phylogenetic analysis suggests that bats might be the original host of this virus, an animal sold at the seafood market in Wuhan might represent an intermediate host facilitating the emergence of the virus in humans. Importantly, structural analysis suggests that 2019-nCoV might be able to bind to the angiotensin-converting enzyme 2 receptor in humans. The future evolution, adaptation, and spread of this virus warrant urgent investigation. Funding National Key Research and Development Program of China, National Major Project for Control and Prevention of Infectious Disease in China, Chinese Academy of Sciences, Shandong First Medical University.
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              An interactive web-based dashboard to track COVID-19 in real time

              In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                J Clin Med
                J Clin Med
                jcm
                Journal of Clinical Medicine
                MDPI
                2077-0383
                02 August 2021
                August 2021
                : 10
                : 15
                : 3441
                Affiliations
                [1 ]Department of Internal Medicine, Dow Medical College, Karachi 74200, Pakistan; hashiraliawan@ 123456gmail.com (H.A.A.); mufdiwan@ 123456gmail.com (M.N.D.); alifiya.aamir521@ 123456gmail.com (A.A.); muneeza1998@ 123456gmail.com (M.A.)
                [2 ]Department of Neurosciences and Imaging, Chair of Psychiatry, University “G. D’Annunzio”, 66100 Chieti, Italy; digiannantonio@ 123456unich.it
                [3 ]Department of Internal Medicine, Kabir Medical College, Gandhara University, Peshawar 25000, Pakistan; irfanullahecp2@ 123456gmail.com
                [4 ]Department of Internal Medicine, Jawahar Lal Nehru Memorial Hospital, Srinagar 190003, India; Sheikshoib22@ 123456gmail.com
                [5 ]NHS, National Health Service, Department of Mental Health, Psychiatric Service for Diagnosis and Treatment, Hospital “G. Mazzini,” ASL 4, 64100 Teramo, Italy
                Author notes
                [* ]Correspondence: domenico.deberardis@ 123456aslteramo.it ; Tel.: +39-08-6142-0515
                Author information
                https://orcid.org/0000-0002-3579-810X
                https://orcid.org/0000-0001-7926-9763
                https://orcid.org/0000-0003-1100-101X
                https://orcid.org/0000-0003-4415-5058
                Article
                jcm-10-03441
                10.3390/jcm10153441
                8347421
                34362224
                0c643d56-ecd9-4209-b29a-b5143ac48c88
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 17 June 2021
                : 28 July 2021
                Categories
                Review

                covid-19,sars-cov-2,brain,neurotropism,cognitive,prevention,diagnosis

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