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      Dysregulated autoantibodies targeting vaso- and immunoregulatory receptors in Post COVID Syndrome correlate with symptom severity

      research-article
      1 , , 2 , , 1 , 1 , 1 , 1 , 3 , 4 , 5 , 2 , 2 , 6 , 7 , 8 , 7 , 9 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 1 , 17 , 18 , 19 , 1 , 17 , 18 , 19 , 1 , 17 , 18 , 19 , 21 , 22 , 7 , 16 , 2 , 5 , 8 , 23 , 24 , , 1 ,
      Frontiers in Immunology
      Frontiers Media S.A.
      autoantibodies, COVID-19, post COVID syndrome, Chronic Fatigue Syndrome, ME/CFS,, G-protein coupled receptor, autonomic nervous system, renin-angiotensin system

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          Abstract

          Most patients with Post COVID Syndrome (PCS) present with a plethora of symptoms without clear evidence of organ dysfunction. A subset of them fulfills diagnostic criteria of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Symptom severity of ME/CFS correlates with natural regulatory autoantibody (AAB) levels targeting several G-protein coupled receptors (GPCR). In this exploratory study, we analyzed serum AAB levels against vaso- and immunoregulatory receptors, mostly GPCRs, in 80 PCS patients following mild-to-moderate COVID-19, with 40 of them fulfilling diagnostic criteria of ME/CFS. Healthy seronegative (n=38) and asymptomatic post COVID-19 controls (n=40) were also included in the study as control groups. We found lower levels for various AABs in PCS compared to at least one control group, accompanied by alterations in the correlations among AABs. Classification using random forest indicated AABs targeting ADRB2, STAB1, and ADRA2A as the strongest classifiers (AABs stratifying patients according to disease outcomes) of post COVID-19 outcomes. Several AABs correlated with symptom severity in PCS groups. Remarkably, severity of fatigue and vasomotor symptoms were associated with ADRB2 AAB levels in PCS/ME/CFS patients. Our study identified dysregulation of AAB against various receptors involved in the autonomous nervous system (ANS), vaso-, and immunoregulation and their correlation with symptom severity, pointing to their role in the pathogenesis of PCS.

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          Most cited references88

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          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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            clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

            Summary Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life science. It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible. To meet these requirements, we present here an updated version of our popular Bioconductor package, clusterProfiler 4.0. This package has been enhanced considerably compared with its original version published 9 years ago. The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases. It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization. Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists. We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms.
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              Circos: an information aesthetic for comparative genomics.

              We created a visualization tool called Circos to facilitate the identification and analysis of similarities and differences arising from comparisons of genomes. Our tool is effective in displaying variation in genome structure and, generally, any other kind of positional relationships between genomic intervals. Such data are routinely produced by sequence alignments, hybridization arrays, genome mapping, and genotyping studies. Circos uses a circular ideogram layout to facilitate the display of relationships between pairs of positions by the use of ribbons, which encode the position, size, and orientation of related genomic elements. Circos is capable of displaying data as scatter, line, and histogram plots, heat maps, tiles, connectors, and text. Bitmap or vector images can be created from GFF-style data inputs and hierarchical configuration files, which can be easily generated by automated tools, making Circos suitable for rapid deployment in data analysis and reporting pipelines.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                27 September 2022
                2022
                27 September 2022
                : 13
                : 981532
                Affiliations
                [1] 1 Institute for Medical Immunology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin , Berlin, Germany
                [2] 2 Department of Immunology, Institute of Biomedical Sciences, University of São Paulo , São Paulo, Brazil
                [3] 3 Faculty of Mathematics and Information Science, Warsaw University of Technology , Warsaw, Poland
                [4] 4 CEAUL – Centro de Estatística e Aplicações da Universidade de Lisboa , Lisbon, Portugal
                [5] 5 Interunit PostGraduate Program on Bioinformatics, Institute of Mathematics and Statistics (IME), University of Sao Paulo , Sao Paulo, Brazil
                [6] 6 Data Science Initiative, Brown University , Providence, RI, United States
                [7] 7 Department of Rheumatology and Clinical Immunology, University of Lübeck , Lübeck, Germany
                [8] 8 Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo , São Paulo, Brazil
                [9] 9 Department of Psychiatry and Psychotherapy, University of Lübeck , Lübeck, Germany
                [10] 10 Department of Biostatistics and the Data Science Initiative, Brown University , Providence, RI, United States
                [11] 11 Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, University Health Network , Toronto, ON, Canada
                [12] 12 Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network , Toronto, ON, Canada
                [13] 13 Department of Medical Biophysics, University of Toronto , Toronto, ON, Canada
                [14] 14 Department of Computer Science, University of Toronto , Toronto, ON, Canada
                [15] 15 Institute of Neuroimmunology, Slovak Academy of Sciences , Bratislava, Slovakia
                [16] 16 CellTrend GmbH , Luckenwalde, Germany
                [17] 17 Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin Berlin , Berlin, Germany
                [18] 18 Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Experimental and Clinical Research Center , Berlin, Germany
                [19] 19 Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) , Berlin, Germany
                [20] 20 NeuroCure Clinical Research Center, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin , Berlin, Germany
                [21] 21 Zabludowicz Center for Autoimmune Diseases, Sheba Medical Center, Affiliated with the Sackler Faculty of Medicine, Tel-Aviv University , Tel-Hashomer, Israel
                [22] 22 Ariel University , Ariel, Israel
                [23] 23 Network of Immunity in Infection, Malignancy, and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN) , Sao Paulo, Brazil
                [24] 24 Department of Pharmacy, Federal University of Rio Grande do Norte , Natal, RN, Brazil
                Author notes

                Edited by: Maria Giovanna Danieli, Università Politecnica delle Marche, Italy

                Reviewed by: Sarah Jane Annesley, La Trobe University, Australia; Jose L Labandeira-Garcia, University of Santiago de Compostela, Spain

                *Correspondence: Franziska Sotzny, franziska.sotzny@ 123456charite.de ; Igor Salerno Filgueiras, igor.filgueiras@ 123456usp.br ; Otavio Cabral-Marques, otavio.cmarques@ 123456gmail.com ; Carmen Scheibenbogen, carmen.scheibenbogen@ 123456charite.de

                This article was submitted to Autoimmune and Autoinflammatory Disorders, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2022.981532
                9552223
                4088da8d-fabc-429e-8f3d-3fc84edc1f83
                Copyright © 2022 Sotzny, Filgueiras, Kedor, Freitag, Wittke, Bauer, Sepúlveda, Mathias da Fonseca, Baiocchi, Marques, Kim, Lange, Plaça, Luebber, Paulus, De Vito, Jurisica, Schulze-Forster, Paul, Bellmann-Strobl, Rust, Hoppmann, Shoenfeld, Riemekasten, Heidecke, Cabral-Marques and Scheibenbogen

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 June 2022
                : 22 August 2022
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 93, Pages: 17, Words: 7666
                Funding
                Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo , doi 10.13039/501100001807;
                Award ID: 2020/07972-1, 2018/18886-9, 2020/01688-0, 2020/07069-0, 2020/16246-2, 2020/11710-2
                Funded by: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior , doi 10.13039/501100002322;
                Award ID: Financial Code 001
                Funded by: Ontario Research Foundation , doi 10.13039/100012171;
                Award ID: #34876
                Funded by: Natural Sciences and Engineering Research Council of Canada , doi 10.13039/501100000038;
                Award ID: #203475
                Funded by: Canada Foundation for Innovation , doi 10.13039/501100000196;
                Award ID: #29272, #225404, #33536
                Funded by: Narodowa Agencja Wymiany Akademickiej , doi 10.13039/501100014434;
                Award ID: PPN/ULM/2020/1/00069/U/00001
                Categories
                Immunology
                Original Research

                Immunology
                autoantibodies,covid-19,post covid syndrome,chronic fatigue syndrome,me/cfs,,g-protein coupled receptor,autonomic nervous system,renin-angiotensin system

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