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      Characterization and Biomarker Analyses of Post-COVID-19 Complications and Neurological Manifestations

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          Abstract

          As the SARS-CoV-2 pandemic continues, reports have demonstrated neurologic sequelae following COVID-19 recovery. Mechanisms to explain long-term neurological sequelae are unknown and need to be identified. Plasma from 24 individuals recovering from COVID-19 at 1 to 3 months after initial infection were collected for cytokine and antibody levels and neuronal-enriched extracellular vesicle (nEV) protein cargo analyses. Plasma cytokine IL-4 was increased in all COVID-19 participants. Volunteers with self-reported neurological problems (nCoV, n = 8) had a positive correlation of IL6 with age or severity of the sequalae, at least one co-morbidity and increased SARS-CoV-2 antibody compared to those COVID-19 individuals without neurological issues (CoV, n = 16). Protein markers of neuronal dysfunction including amyloid beta, neurofilament light, neurogranin, total tau, and p-T181-tau were all significantly increased in the nEVs of all participants recovering from COVID-19 compared to historic controls. This study suggests ongoing peripheral and neuroinflammation after COVID-19 infection that may influence neurological sequelae by altering nEV proteins. Individuals recovering from COVID-19 may have occult neural damage while those with demonstrative neurological symptoms additionally had more severe infection. Longitudinal studies to monitor plasma biomarkers and nEV cargo are warranted to assess persistent neurodegeneration and systemic effects.

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          Most cited references56

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Neurologic Manifestations of Hospitalized Patients With Coronavirus Disease 2019 in Wuhan, China

            The outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, is serious and has the potential to become an epidemic worldwide. Several studies have described typical clinical manifestations including fever, cough, diarrhea, and fatigue. However, to our knowledge, it has not been reported that patients with COVID-19 had any neurologic manifestations.
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              Causal analysis approaches in Ingenuity Pathway Analysis

              Motivation: Prior biological knowledge greatly facilitates the meaningful interpretation of gene-expression data. Causal networks constructed from individual relationships curated from the literature are particularly suited for this task, since they create mechanistic hypotheses that explain the expression changes observed in datasets. Results: We present and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene-expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base. We extend the method to predict downstream effects on biological functions and diseases and demonstrate the validity of our approach by applying it to example datasets. Availability: The causal analytics tools ‘Upstream Regulator Analysis', ‘Mechanistic Networks', ‘Causal Network Analysis' and ‘Downstream Effects Analysis' are implemented and available within Ingenuity Pathway Analysis (IPA, http://www.ingenuity.com). Supplementary information: Supplementary material is available at Bioinformatics online.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Cells
                Cells
                cells
                Cells
                MDPI
                2073-4409
                13 February 2021
                February 2021
                : 10
                : 2
                : 386
                Affiliations
                [1 ]Department of Laboratory Medicine, San Francisco VA Health Care System, San Francisco, CA 94121, USA; Bing.sun@ 123456va.gov (B.S.); Norina.Tang@ 123456va.gov (N.T.)
                [2 ]Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California at San Francisco, San Francisco, CA 94110, USA; Michael.peluso@ 123456ucsf.edu (M.J.P.); Rachel.rutishauser@ 123456ucsf.edu (R.L.R.); Isabel.rodriguez@ 123456ucsf.edu (I.R.-B.); Bryan.greenhouse@ 123456ucsf.edu (B.G.); Steven.deeks@ 123456ucsf.edu (S.G.D.)
                [3 ]Division of Experimental Medicine, Department of Medicine, University of California at San Francisco, San Francisco, CA 94110, USA; nikita.iyer@ 123456ucsf.edu (N.S.I.); Leonel.Torres@ 123456ucsf.edu (L.T.); Joanna.donatelli@ 123456ucsf.edu (J.L.D.); Sadie.munter@ 123456ucsf.edu (S.E.M.); Christopher.nixon@ 123456ucsf.edu (C.C.N.); Timothy.henrich@ 123456ucsf.edu (T.J.H.)
                [4 ]Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA 94158, USA; Dan.kelly@ 123456ucsf.edu (J.D.K.); Jeffrey.martin@ 123456ucsf.edu (J.N.M.)
                [5 ]Department of Laboratory Medicine and Medicine, University of California at San Francisco, San Francisco, CA 94143, USA
                Author notes
                [* ]Correspondence: Lynn.pulliam@ 123456ucsf.edu
                Article
                cells-10-00386
                10.3390/cells10020386
                7918597
                33668514
                003239c6-bbc7-4336-8c70-358dcc18e80b
                © 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 ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 January 2021
                : 10 February 2021
                Categories
                Article

                sars-cov-2,neurodegeneration,exosome,cytokines,comorbidities

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