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Kori M, Kasavi C, Arga KY. Exploring COVID-19 Pandemic Disparities with Transcriptomic Meta-analysis from the Perspective of Personalized Medicine. J Microbiol 2024:10.1007/s12275-024-00154-9. [PMID: 38980578 DOI: 10.1007/s12275-024-00154-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 06/06/2024] [Accepted: 06/17/2024] [Indexed: 07/10/2024]
Abstract
Infection with SARS-CoV2, which is responsible for COVID-19, can lead to differences in disease development, severity and mortality rates depending on gender, age or the presence of certain diseases. Considering that existing studies ignore these differences, this study aims to uncover potential differences attributable to gender, age and source of sampling as well as viral load using bioinformatics and multi-omics approaches. Differential gene expression analyses were used to analyse the phenotypic differences between SARS-CoV-2 patients and controls at the mRNA level. Pathway enrichment analyses were performed at the gene set level to identify the activated pathways corresponding to the differences in the samples. Drug repurposing analysis was performed at the protein level, focusing on host-mediated drug candidates to uncover potential therapeutic differences. Significant differences (i.e. the number of differentially expressed genes and their characteristics) were observed for COVID-19 at the mRNA level depending on the sample source, gender and age of the samples. The results of the pathway enrichment show that SARS-CoV-2 can be combated more effectively in the respiratory tract than in the blood samples. Taking into account the different sample sources and their characteristics, different drug candidates were identified. Evaluating disease prediction, prevention and/or treatment strategies from a personalised perspective is crucial. In this study, we not only evaluated the differences in COVID-19 from a personalised perspective, but also provided valuable data for further experimental and clinical efforts. Our findings could shed light on potential pandemics.
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Affiliation(s)
- Medi Kori
- Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, 34752, Istanbul, Turkey.
- Faculty of Health Sciences, Acibadem Mehmet Ali Aydinlar University, 34752, Istanbul, Turkey.
| | - Ceyda Kasavi
- Department of Bioengineering, Marmara University, 34722, Istanbul, Turkey
| | - Kazim Yalcin Arga
- Department of Bioengineering, Marmara University, 34722, Istanbul, Turkey
- Genetic and Metabolic Diseases Research and Investigation Center, Marmara University, 34722, Istanbul, Turkey
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2
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Li Y, Tao X, Ye S, Tai Q, You YA, Huang X, Liang M, Wang K, Wen H, You C, Zhang Y, Zhou X. A T-Cell-Derived 3-Gene Signature Distinguishes SARS-CoV-2 from Common Respiratory Viruses. Viruses 2024; 16:1029. [PMID: 39066192 PMCID: PMC11281602 DOI: 10.3390/v16071029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 06/06/2024] [Accepted: 06/21/2024] [Indexed: 07/28/2024] Open
Abstract
Research on the host responses to respiratory viruses could help develop effective interventions and therapies against the current and future pandemics from the host perspective. To explore the pathogenesis that distinguishes SARS-CoV-2 infections from other respiratory viruses, we performed a multi-cohort analysis with integrated bioinformatics and machine learning. We collected 3730 blood samples from both asymptomatic and symptomatic individuals infected with SARS-CoV-2, seasonal human coronavirus (sHCoVs), influenza virus (IFV), respiratory syncytial virus (RSV), or human rhinovirus (HRV) across 15 cohorts. First, we identified an enhanced cellular immune response but limited interferon activities in SARS-CoV-2 infection, especially in asymptomatic cases. Second, we identified a SARS-CoV-2-specific 3-gene signature (CLSPN, RBBP6, CCDC91) that was predominantly expressed by T cells, could distinguish SARS-CoV-2 infection, including Omicron, from other common respiratory viruses regardless of symptoms, and was predictive of SARS-CoV-2 infection before detectable viral RNA on RT-PCR testing in a longitude follow-up study. Thereafter, a user-friendly online tool, based on datasets collected here, was developed for querying a gene of interest across multiple viral infections. Our results not only identify a unique host response to the viral pathogenesis in SARS-CoV-2 but also provide insights into developing effective tools against viral pandemics from the host perspective.
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Affiliation(s)
- Yang Li
- Beijing International Center for Mathematical Research, Peking University, Beijing 100871, China;
- Chongqing Research Institute of Big Data, Peking University, Chongqing 400041, China; (X.T.); (X.H.)
| | - Xinya Tao
- Chongqing Research Institute of Big Data, Peking University, Chongqing 400041, China; (X.T.); (X.H.)
| | - Sheng Ye
- Chongqing Center for Disease Control and Prevention, Chongqing 400707, China;
| | - Qianchen Tai
- Department of Probability and Statistics, School of Mathematical Sciences, Peking University, Beijing 100091, China;
| | - Yu-Ang You
- Institute of Pharmaceutical Science, King’s College London, London WC2R 2LS, UK;
| | - Xinting Huang
- Chongqing Research Institute of Big Data, Peking University, Chongqing 400041, China; (X.T.); (X.H.)
| | - Mifang Liang
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China;
| | - Kai Wang
- Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Department of Infectious Diseases, Institute for Viral Hepatitis, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China;
| | - Haiyan Wen
- Chongqing International Travel Health Care Center, Chongqing 401120, China;
| | - Chong You
- Beijing International Center for Mathematical Research, Peking University, Beijing 100871, China;
- Chongqing Research Institute of Big Data, Peking University, Chongqing 400041, China; (X.T.); (X.H.)
- Shanghai Institute for Mathematics and Interdisciplinary Sciences, Fudan University, Shanghai 200433, China
| | - Yan Zhang
- Sports & Medicine Integration Research Center (SMIRC), Capital University of Physical Education and Sports, Beijing 100088, China
| | - Xiaohua Zhou
- Beijing International Center for Mathematical Research, Peking University, Beijing 100871, China;
- Chongqing Research Institute of Big Data, Peking University, Chongqing 400041, China; (X.T.); (X.H.)
- Department of Probability and Statistics, School of Mathematical Sciences, Peking University, Beijing 100091, China;
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3
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Lee SG, Furth PA, Hennighausen L, Lee HK. Variant- and vaccination-specific alternative splicing profiles in SARS-CoV-2 infections. iScience 2024; 27:109177. [PMID: 38414855 PMCID: PMC10897911 DOI: 10.1016/j.isci.2024.109177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/28/2023] [Accepted: 02/06/2024] [Indexed: 02/29/2024] Open
Abstract
The COVID-19 pandemic, driven by the SARS-CoV-2 virus and its variants, highlights the important role of understanding host-viral molecular interactions influencing infection outcomes. Alternative splicing post-infection can impact both host responses and viral replication. We analyzed RNA splicing patterns in immune cells across various SARS-CoV-2 variants, considering immunization status. Using a dataset of 190 RNA-seq samples from our prior studies, we observed a substantial deactivation of alternative splicing and RNA splicing-related genes in COVID-19 patients. The alterations varied significantly depending on the infecting variant and immunization history. Notably, Alpha or Beta-infected patients differed from controls, while Omicron-infected patients displayed a splicing profile closer to controls. Particularly, vaccinated Omicron-infected individuals showed a distinct dynamic in alternative splicing patterns not widely shared among other groups. Our findings underscore the intricate interplay between SARS-CoV-2 variants, vaccination-induced immunity, and alternative splicing, emphasizing the need for further investigations to deepen understanding and guide therapeutic development.
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Affiliation(s)
- Sung-Gwon Lee
- Section of Genetics and Physiology, Laboratory of Molecular and Cellular Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Priscilla A Furth
- Section of Genetics and Physiology, Laboratory of Molecular and Cellular Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Lothar Hennighausen
- Section of Genetics and Physiology, Laboratory of Molecular and Cellular Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Hye Kyung Lee
- Section of Genetics and Physiology, Laboratory of Molecular and Cellular Biology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA
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Kyriazopoulou E, Hasin-Brumshtein Y, Midic U, Poulakou G, Milionis H, Metallidis S, Astriti M, Fragkou A, Rapti A, Taddei E, Kalomenidis I, Chrysos G, Angheben A, Kainis I, Alexiou Z, Castelli F, Serino FS, Bakakos P, Nicastri E, Tzavara V, Ioannou S, Dagna L, Dimakou K, Tzatzagou G, Chini M, Bassetti M, Kotsis V, Tsoukalas DG, Selmi C, Konstantinou A, Samarkos M, Doumas M, Masgala A, Pagkratis K, Argyraki A, Akinosoglou K, Symbardi S, Netea MG, Panagopoulos P, Dalekos GN, Liesenfeld O, Sweeney TE, Khatri P, Giamarellos-Bourboulis EJ. Transitions of blood immune endotypes and improved outcome by anakinra in COVID-19 pneumonia: an analysis of the SAVE-MORE randomized controlled trial. Crit Care 2024; 28:73. [PMID: 38475786 PMCID: PMC10935809 DOI: 10.1186/s13054-024-04852-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Endotype classification may guide immunomodulatory management of patients with bacterial and viral sepsis. We aimed to identify immune endotypes and transitions associated with response to anakinra (human interleukin 1 receptor antagonist) in participants in the SAVE-MORE trial. METHODS Adult patients hospitalized with radiological findings of PCR-confirmed severe pneumonia caused by SARS-CoV-2 and plasma-soluble urokinase plasminogen activator receptor levels of ≥ 6 ng/ml in the SAVE-MORE trial (NCT04680949) were characterized at baseline and days 4 and 7 of treatment using a previously defined 33-messenger RNA classifier to assign an immunological endotype in blood. Endpoints were changes in endotypes and progression to severe respiratory failure (SRF) associated with anakinra treatment. RESULTS At baseline, 23.2% of 393 patients were designated as inflammopathic, 41.1% as adaptive, and 35.7% as coagulopathic. Only 23.9% were designated as the same endotype at days 4 and 7 compared to baseline, while all other patients transitioned between endotypes. Anakinra-treated patients were more likely to remain in the adaptive endotype during 7-day treatment (24.4% vs. 9.9%; p < 0.001). Anakinra also protected patients with coagulopathic endotype at day 7 against SRF compared to placebo (27.8% vs. 55.9%; p = 0.013). CONCLUSION We identify an association between endotypes defined using blood transcriptome and anakinra therapy for COVID-19 pneumonia, with anakinra-treated patients shifting toward endotypes associated with a better outcome, mainly the adaptive endotype. Trial registration ClinicalTrials.gov, NCT04680949, December 23, 2020.
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Affiliation(s)
- Evdoxia Kyriazopoulou
- 4th Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | | | | | - Garyfallia Poulakou
- 3rd Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Haralampos Milionis
- 1st Department of Internal Medicine, Medical School, University of Ioannina, Ioannina, Greece
| | - Simeon Metallidis
- 1st Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Myrto Astriti
- 1st Department of Internal Medicine, G. Gennimatas General Hospital of Athens, Athens, Greece
| | | | - Aggeliki Rapti
- 2nd Department of Pulmonary Medicine, Sotiria General Hospital of Chest Diseases, Athens, Greece
| | - Eleonora Taddei
- Dipartimento Scienze di Laboratorio e Infettivologiche, Fondazione Policlinico Gemelli IRCCS, Rome, Italy
| | - Ioannis Kalomenidis
- 1st Department of Critical Care and Pulmonary Medicine, Medical School, National and Kapodistrian University of Athens, Evangelismos General Hospital, Athens, Greece
| | - Georgios Chrysos
- 2nd Department of Internal Medicine, Tzaneio General Hospital of Piraeus, Athens, Greece
| | - Andrea Angheben
- Department of Infectious - Tropical Diseases and Microbiology, IRCSS Sacro Cuore Hospital, Negrar, Verona, Italy
| | - Ilias Kainis
- 10th Department of Pulmonary Medicine, Sotiria General Hospital of Chest Diseases of Athens, Athens, Greece
| | - Zoi Alexiou
- 2nd Department of Internal Medicine, Thriasio General Hospital of Eleusis, Athens, Greece
| | - Francesco Castelli
- Spedali Civili, Brescia ASST Spedali Civili Hospital, University of Brescia, Brescia, Italy
| | | | - Petros Bakakos
- 1st Department of Chest Medicine, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Emanuele Nicastri
- Department of Internal Medicine, Spallanzani Institute of Rome, Rome, Italy
| | - Vasiliki Tzavara
- 1st Department of Internal Medicine, Korgialeneion-Benakeion General Hospital, Athens, Greece
| | - Sofia Ioannou
- Department of Therapeutics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Lorenzo Dagna
- Unit of Immunology, Rheumatology, Allergy and Rare Diseases (UnIRAR), IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milan, Italy
| | - Katerina Dimakou
- 5th Department of Pulmonary Medicine, Sotiria General Hospital of Chest Diseases, Athens, Athens, Greece
| | - Glykeria Tzatzagou
- 1st Department of Internal Medicine, Papageorgiou General Hospital of Thessaloniki, Thessaloniki, Greece
| | - Maria Chini
- 3rd Department of Internal Medicine and Infectious Diseases Unit, Korgialeneion-Benakeion General Hospital, Athens, Greece
| | - Matteo Bassetti
- Infectious Diseases Clinic, Ospedale Policlinico San Martino IRCCS and Department of Health Sciences, University of Genova, Genova, Italy
| | - Vasileios Kotsis
- 3rd Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Dionysios G Tsoukalas
- 4th Department of Pulmonary Medicine, Sotiria General Hospital of Chest Diseases, Athens, Greece
| | - Carlo Selmi
- Department of Biomedical Sciences, Humanitas University and IRCCS Humanitas Research Hospital, Milan, Italy
| | - Alexandra Konstantinou
- 1st Department of Internal Medicine, Asklepieio General Hospital of Voula, Voula, Greece
| | - Michael Samarkos
- 1st Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Michael Doumas
- 2nd Department of Propedeutic Medicine, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Aikaterini Masgala
- 2nd Department of Internal Medicine, Konstantopouleio General Hospital, Athens, Greece
| | | | - Aikaterini Argyraki
- Department of Internal Medicine, Sotiria General Hospital of Chest Diseases, Athens, Greece
| | | | - Styliani Symbardi
- 1st Department of Internal Medicine, Thriasio General Hospital of Eleusis, Athens, Greece
| | - Mihai G Netea
- Department of Internal Medicine and Center for Infectious Diseases, Radboud University, Nijmegen, The Netherlands
- Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, Bonn, Germany
| | - Periklis Panagopoulos
- 2nd Department of Internal Medicine, Medical School, Democritus University of Thrace, Alexandroupolis, Greece
| | - George N Dalekos
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, European Reference Network on Hepatological Diseases (ERN RARE-LIVER), General University Hospital of Larissa, Larissa, Greece
| | | | | | - Purvesh Khatri
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA, USA
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Evangelos J Giamarellos-Bourboulis
- 4th Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
- 4th Department of Internal Medicine, ATTIKON University Hospital, 1 Rimini Street, 124 62, Athens, Greece.
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5
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Krupka S, Hoffmann A, Jasaszwili M, Dietrich A, Guiu-Jurado E, Klöting N, Blüher M. Consequences of COVID-19 on Adipose Tissue Signatures. Int J Mol Sci 2024; 25:2908. [PMID: 38474155 DOI: 10.3390/ijms25052908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 02/26/2024] [Accepted: 02/29/2024] [Indexed: 03/14/2024] Open
Abstract
Since the emergence of coronavirus disease-19 (COVID-19) in 2019, it has been crucial to investigate the causes of severe cases, particularly the higher rates of hospitalization and mortality in individuals with obesity. Previous findings suggest that adipocytes may play a role in adverse COVID-19 outcomes in people with obesity. The impact of COVID-19 vaccination and infection on adipose tissue (AT) is currently unclear. We therefore analyzed 27 paired biopsies of visceral and subcutaneous AT from donors of the Leipzig Obesity BioBank that have been categorized into three groups (1: no infection/no vaccination; 2: no infection but vaccinated; 3: infected and vaccinated) based on COVID-19 antibodies to spike (indicating vaccination) and/or nucleocapsid proteins. We provide additional insights into the impact of COVID-19 on AT biology through a comprehensive histological transcriptome and serum proteome analysis. This study demonstrates that COVID-19 infection is associated with smaller average adipocyte size. The impact of infection on gene expression was significantly more pronounced in subcutaneous than in visceral AT and mainly due to immune system-related processes. Serum proteome analysis revealed the effects of the infection on circulating adiponectin, interleukin 6 (IL-6), and carbonic anhydrase 5A (CA5A), which are all related to obesity and blood glucose abnormalities.
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Affiliation(s)
- Sontje Krupka
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG), Helmholtz Zentrum München, University of Leipzig and University Hospital Leipzig, 04103 Leipzig, Germany
| | - Anne Hoffmann
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG), Helmholtz Zentrum München, University of Leipzig and University Hospital Leipzig, 04103 Leipzig, Germany
| | - Mariami Jasaszwili
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Arne Dietrich
- Clinic for Visceral, Transplantation and Thorax and Vascular Surgery, University Hospital Leipzig, 04103 Leipzig, Germany
| | - Esther Guiu-Jurado
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Nora Klöting
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG), Helmholtz Zentrum München, University of Leipzig and University Hospital Leipzig, 04103 Leipzig, Germany
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG), Helmholtz Zentrum München, University of Leipzig and University Hospital Leipzig, 04103 Leipzig, Germany
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
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Ratnasiri K, Zheng H, Toh J, Yao Z, Duran V, Donato M, Roederer M, Kamath M, Todd JPM, Gagne M, Foulds KE, Francica JR, Corbett KS, Douek DC, Seder RA, Einav S, Blish CA, Khatri P. Systems immunology of transcriptional responses to viral infection identifies conserved antiviral pathways across macaques and humans. Cell Rep 2024; 43:113706. [PMID: 38294906 PMCID: PMC10915397 DOI: 10.1016/j.celrep.2024.113706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 11/02/2023] [Accepted: 01/09/2024] [Indexed: 02/02/2024] Open
Abstract
Viral pandemics and epidemics pose a significant global threat. While macaque models of viral disease are routinely used, it remains unclear how conserved antiviral responses are between macaques and humans. Therefore, we conducted a cross-species analysis of transcriptomic data from over 6,088 blood samples from macaques and humans infected with one of 31 viruses. Our findings demonstrate that irrespective of primate or viral species, there are conserved antiviral responses that are consistent across infection phase (acute, chronic, or latent) and viral genome type (DNA or RNA viruses). Leveraging longitudinal data from experimental challenges, we identify virus-specific response kinetics such as host responses to Coronaviridae and Orthomyxoviridae infections peaking 1-3 days earlier than responses to Filoviridae and Arenaviridae viral infections. Our results underscore macaque studies as a powerful tool for understanding viral pathogenesis and immune responses that translate to humans, with implications for viral therapeutic development and pandemic preparedness.
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Affiliation(s)
- Kalani Ratnasiri
- Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Epidemiology and Population Health, Stanford University, Stanford, CA 94305, USA
| | - Hong Zheng
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA; Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jiaying Toh
- Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Surgery, Division of Abdominal Transplantation, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA; Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Zhiyuan Yao
- Department of Microbiology and Immunology, Stanford University, CA 94305, USA
| | - Veronica Duran
- Department of Microbiology and Immunology, Stanford University, CA 94305, USA
| | - Michele Donato
- Department of Surgery, Division of Abdominal Transplantation, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Mario Roederer
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Megha Kamath
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - John-Paul M Todd
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Matthew Gagne
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kathryn E Foulds
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joseph R Francica
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kizzmekia S Corbett
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel C Douek
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Robert A Seder
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shirit Einav
- Department of Microbiology and Immunology, Stanford University, CA 94305, USA; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Catherine A Blish
- Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA; Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Purvesh Khatri
- Department of Surgery, Division of Abdominal Transplantation, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA; Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA.
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7
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Chang YY, Wei AC. Transcriptome and machine learning analysis of the impact of COVID-19 on mitochondria and multiorgan damage. PLoS One 2024; 19:e0297664. [PMID: 38295140 PMCID: PMC10830027 DOI: 10.1371/journal.pone.0297664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/09/2024] [Indexed: 02/02/2024] Open
Abstract
The effects of coronavirus disease 2019 (COVID-19) primarily concern the respiratory tract and lungs; however, studies have shown that all organs are susceptible to infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 may involve multiorgan damage from direct viral invasion through angiotensin-converting enzyme 2 (ACE2), through inflammatory cytokine storms, or through other secondary pathways. This study involved the analysis of publicly accessible transcriptome data from the Gene Expression Omnibus (GEO) database for identifying significant differentially expressed genes related to COVID-19 and an investigation relating to the pathways associated with mitochondrial, cardiac, hepatic, and renal toxicity in COVID-19. Significant differentially expressed genes were identified and ranked by statistical approaches, and the genes derived by biological meaning were ranked by feature importance; both were utilized as machine learning features for verification. Sample set selection for machine learning was based on the performance, sample size, imbalanced data state, and overfitting assessment. Machine learning served as a verification tool by facilitating the testing of biological hypotheses by incorporating gene list adjustment. A subsequent in-depth study for gene and pathway network analysis was conducted to explore whether COVID-19 is associated with cardiac, hepatic, and renal impairments via mitochondrial infection. The analysis showed that potential cardiac, hepatic, and renal impairments in COVID-19 are associated with ACE2, inflammatory cytokine storms, and mitochondrial pathways, suggesting potential medical interventions for COVID-19-induced multiorgan damage.
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Affiliation(s)
- Yu-Yu Chang
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - An-Chi Wei
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
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8
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Lei H. Hypoxia and Activation of Neutrophil Degranulation-Related Genes in the Peripheral Blood of COVID-19 Patients. Viruses 2024; 16:201. [PMID: 38399976 PMCID: PMC10891603 DOI: 10.3390/v16020201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 01/20/2024] [Accepted: 01/21/2024] [Indexed: 02/25/2024] Open
Abstract
Severe COVID-19 is characterized by systematic hyper-inflammation and subsequent damage to various organs. Therefore, it is critical to trace this cascade of hyper-inflammation. Blood transcriptome has been routinely utilized in the interrogation of host immune response in COVID-19 and other infectious conditions. In this study, consensus gene dysregulation in the blood was obtained from 13 independent transcriptome studies on COVID-19. Among the up-regulated genes, the most prominent functional categories were neutrophil degranulation and cell cycle, which is clearly different from the classical activation of interferon signaling pathway in seasonal flu. As for the potential upstream causal factors of the atypical gene dysregulation, systemic hypoxia was further examined because it is much more widely reported in COVID-19 than that in seasonal flu. It was found that both physiological and pathological hypoxia can induce activation of neutrophil degranulation-related genes in the blood. Furthermore, COVID-19 patients with different requirement for oxygen intervention showed distinctive levels of gene expression related to neutrophil degranulation in the whole blood, which was validated in isolated neutrophils. Thus, activation of neutrophil degranulation-related genes in the blood of COVID-19 could be partially attributed to hypoxia. Interestingly, similar pattern was also observed in H1N1 infection (the cause of Spanish flu) and several other severe respiratory viral infections. As for the molecular mechanism, both HIF-dependent and HIF-independent pathways have been examined. Since the activation of neutrophil degranulation-related genes is highly correlated with disease severity in COVID-19, early detection of hypoxia and active intervention may prevent further activation of neutrophil degranulation-related genes and other harmful downstream hyper-inflammation. This common mechanism is applicable to current and future pandemic as well as the severe form of common respiratory infection.
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Affiliation(s)
- Hongxing Lei
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing 100101, China; ; Tel.: +86-010-84097276
- Cunji Medical School, University of Chinese Academy of Sciences, Beijing 101408, China
- Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing 100069, China
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9
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Zhang Y, Zhao L, Zhang J, Zhang X, Han S, Sun Q, Yao M, Pang B, Duan Q, Jiang X. Antibody and transcription landscape in peripheral blood mononuclear cells of elderly adults over 70 years of age with third dose of COVID-19 BBIBP-CorV and ZF2001 booster vaccine. Immun Ageing 2024; 21:11. [PMID: 38280989 PMCID: PMC10821575 DOI: 10.1186/s12979-023-00408-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 12/20/2023] [Indexed: 01/29/2024]
Abstract
BACKGROUND In the context of the COVID-19 pandemic and extensive vaccination, it is important to explore the immune response of elderly adults to homologous and heterologous booster vaccines of COVID-19. At this point, we detected serum IgG antibodies and PBMC sample transcriptome profiles in 46 participants under 70 years old and 25 participants over 70 years old who received the third dose of the BBIBP-CorV and ZF2001 vaccines. RESULTS On day 7, the antibody levels of people over 70 years old after the third dose of booster vaccine were lower than those of young people, and the transcriptional responses of innate and adaptive immunity were also weak. The age of the participants showed a significant negative correlation with functions related to T-cell differentiation and costimulation. Nevertheless, 28 days after the third dose, the IgG antibodies of elderly adults reached equivalence to those of younger adults, and immune-related transcriptional regulation was significantly improved. The age showed a significant positive correlation with functions related to "chemokine receptor binding", "chemokine activity", and "chemokine-mediated signaling pathway". CONCLUSIONS Our results document that the response of elderly adults to the third dose of the vaccine was delayed, but still able to achieve comparable immune effects compared to younger adults, in regard to antibody responses as well as at the transcript level.
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Affiliation(s)
- Yuwei Zhang
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, Shandong Province, China
| | - Lianxiang Zhao
- School of Public Health and Management, Binzhou Medical University, Yantai , Shandong Province, China
| | - Jinzhong Zhang
- Liaocheng Center for Disease Control and Prevention, Liaocheng, Shandong Province, China
| | - Xiaomei Zhang
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, Shandong Province, China
| | - Shanshan Han
- School of Public Health and Health Management, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong Province, China
| | - Qingshuai Sun
- School of Public Health and Health Management, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong Province, China
| | - Mingxiao Yao
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, Shandong Province, China
| | - Bo Pang
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, Shandong Province, China
| | - Qing Duan
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, Shandong Province, China
| | - Xiaolin Jiang
- School of Public Health and Management, Binzhou Medical University, Yantai , Shandong Province, China.
- School of Public Health and Health Management, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong Province, China.
- Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, 16992 Jingshi Road , Jinan, 250014, Shandong Province, China.
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10
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Huang B, Huang J, Chiang NH, Chen Z, Lui G, Ling L, Kwan MYW, Wong JSC, Mak PQ, Ling JWH, Lam ICS, Ng RWY, Wang X, Gao R, Hui DSC, Ma SL, Chan PKS, Tang NLS. Interferon response and profiling of interferon response genes in peripheral blood of vaccine-naive COVID-19 patients. Front Immunol 2024; 14:1315602. [PMID: 38268924 PMCID: PMC10806211 DOI: 10.3389/fimmu.2023.1315602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/18/2023] [Indexed: 01/26/2024] Open
Abstract
Introduction There is insufficient understanding on systemic interferon (IFN) responses during COVID-19 infection. Early reports indicated that interferon responses were suppressed by the coronavirus (SARS-CoV-2) and clinical trials of administration of various kinds of interferons had been disappointing. Expression of interferon-stimulated genes (ISGs) in peripheral blood (better known as interferon score) has been a well-established bioassay marker of systemic IFN responses in autoimmune diseases. Therefore, with archival samples of a cohort of COVID-19 patients collected before the availability of vaccination, we aimed to better understand this innate immune response by studying the IFN score and related ISGs expression in bulk and single cell RNAs sequencing expression datasets. Methods In this study, we recruited 105 patients with COVID-19 and 30 healthy controls in Hong Kong. Clinical risk factors, disease course, and blood sampling times were recovered. Based on a set of five commonly used ISGs (IFIT1, IFIT2, IFI27, SIGLEC1, IFI44L), the IFN score was determined in blood leukocytes collected within 10 days after onset. The analysis was confined to those blood samples collected within 10 days after disease onset. Additional public datasets of bulk gene and single cell RNA sequencing of blood samples were used for the validation of IFN score results. Results Compared to the healthy controls, we showed that ISGs expression and IFN score were significantly increased during the first 10 days after COVID infection in majority of patients (71%). Among those low IFN responders, they were more commonly asymptomatic patients (71% vs 25%). 22 patients did not mount an overall significant IFN response and were classified as low IFN responders (IFN score < 1). However, early IFN score or ISGs level was not a prognostic biomarker and could not predict subsequent disease severity. Both IFI27 and SIGLEC1 were monocyte-predominant expressing ISGs and IFI27 were activated even among those low IFN responders as defined by IFN score. In conclusion, a substantial IFN response was documented in this cohort of COVID-19 patients who experience a natural infection before the vaccination era. Like innate immunity towards other virus, the ISGs activation was observed largely during the early course of infection (before day 10). Single-cell RNA sequencing data suggested monocytes were the cell-type that primarily accounted for the activation of two highly responsive ISGs (IFI44L and IFI27). Discussion As sampling time and age were two major confounders of ISG expression, they may account for contradicting observations among previous studies. On the other hand, the IFN score was not associated with the severity of the disease.
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Affiliation(s)
- Baozhen Huang
- Department of Chemical Pathology, and Li Ka Shing Institute of Health Science, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Jinghan Huang
- Department of Chemical Pathology, and Li Ka Shing Institute of Health Science, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Nim Hang Chiang
- Department of Chemical Pathology, and Li Ka Shing Institute of Health Science, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Zigui Chen
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Grace Lui
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Lowell Ling
- Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Mike Yat Wah Kwan
- Paediatric Infectious Disease Unit, Department of Paediatrics and Adolescent Medicine, Princess Margaret Hospital, Hong Kong, Hong Kong SAR, China
| | - Joshua Sung Chih Wong
- Paediatric Infectious Disease Unit, Department of Paediatrics and Adolescent Medicine, Princess Margaret Hospital, Hong Kong, Hong Kong SAR, China
| | - Phoebe Qiaozhen Mak
- Paediatric Infectious Disease Unit, Department of Paediatrics and Adolescent Medicine, Princess Margaret Hospital, Hong Kong, Hong Kong SAR, China
| | - Janet Wan Hei Ling
- Paediatric Infectious Disease Unit, Department of Paediatrics and Adolescent Medicine, Princess Margaret Hospital, Hong Kong, Hong Kong SAR, China
| | - Ivan Cheuk San Lam
- Paediatric Infectious Disease Unit, Department of Paediatrics and Adolescent Medicine, Princess Margaret Hospital, Hong Kong, Hong Kong SAR, China
| | - Rita Wai Yin Ng
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Xingyan Wang
- Department of Chemical Pathology, and Li Ka Shing Institute of Health Science, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Ruonan Gao
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - David Shu-Cheong Hui
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Suk Ling Ma
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Paul K. S. Chan
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Nelson Leung Sang Tang
- Department of Chemical Pathology, and Li Ka Shing Institute of Health Science, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
- Hong Kong Branch of CAS Center for Excellence in Animal Evolution and Genetics and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Hong Kong, Hong Kong SAR, China
- Functional Genomics and Biostatistical Computing Laboratory, CUHK Shenzhen Research Institute, Shenzhen, China
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11
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Fan Y, Liu X, Guan F, Hang X, He X, Jin J. Investigating the Potential Shared Molecular Mechanisms between COVID-19 and Alzheimer's Disease via Transcriptomic Analysis. Viruses 2024; 16:100. [PMID: 38257800 PMCID: PMC10821526 DOI: 10.3390/v16010100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/29/2023] [Accepted: 01/03/2024] [Indexed: 01/24/2024] Open
Abstract
SARS-CoV-2 caused the COVID-19 pandemic. COVID-19 may elevate the risk of cognitive impairment and even cause dementia in infected individuals; it may accelerate cognitive decline in elderly patients with dementia, possibly in Alzheimer's disease (AD) patients. However, the mechanisms underlying the interplay between AD and COVID-19 are still unclear. To investigate the underlying mechanisms and associations between AD progression and SARS-CoV-2 infection, we conducted a series of bioinformatics research into SARS-CoV-2-infected cells, COVID-19 patients, AD patients, and SARS-CoV-2-infected AD patients. We identified the common differentially expressed genes (DEGs) in COVID-19 patients, AD patients, and SARS-CoV-2-infected cells, and these DEGs are enriched in certain pathways, such as immune responses and cytokine storms. We constructed the gene interaction network with the signaling transduction module in the center and identified IRF7, STAT1, STAT2, and OAS1 as the hub genes. We also checked the correlations between several key transcription factors and the SARS-CoV-2 and COVID-19 pathway-related genes. We observed that ACE2 expression is positively correlated with IRF7 expression in AD and coronavirus infections, and interestingly, IRF7 is significantly upregulated in response to different RNA virus infections. Further snRNA-seq analysis indicates that NRGN neurons or endothelial cells may be responsible for the increase in ACE2 and IRF7 expression after SARS-CoV-2 infection. The positive correlation between ACE2 and IRF7 expressions is confirmed in the hippocampal formation (HF) of SARS-CoV-2-infected AD patients. Our findings could contribute to the investigation of the molecular mechanisms underlying the interplay between AD and COVID-19 and to the development of effective therapeutic strategies for AD patients with COVID-19.
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Affiliation(s)
- Yixian Fan
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Center for Genomics and Proteomics Research, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Key Laboratory of Vascular Aging of the Ministry of Education, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic Evaluation, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiaozhao Liu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Center for Genomics and Proteomics Research, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Key Laboratory of Vascular Aging of the Ministry of Education, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic Evaluation, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Fei Guan
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Center for Genomics and Proteomics Research, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Key Laboratory of Vascular Aging of the Ministry of Education, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic Evaluation, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiaoyi Hang
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Center for Genomics and Proteomics Research, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Key Laboratory of Vascular Aging of the Ministry of Education, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic Evaluation, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ximiao He
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Center for Genomics and Proteomics Research, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Key Laboratory of Vascular Aging of the Ministry of Education, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic Evaluation, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jing Jin
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Center for Genomics and Proteomics Research, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Key Laboratory of Vascular Aging of the Ministry of Education, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic Evaluation, Huazhong University of Science and Technology, Wuhan 430030, China
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12
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Zhang K, Chen F, Shen HY, Zhang PP, Gao H, Peng H, Luo YS, Cheng ZS. Regulatory variants of APOBEC3 genes potentially associate with COVID-19 severity in populations with African ancestry. Sci Rep 2023; 13:22435. [PMID: 38105291 PMCID: PMC10725877 DOI: 10.1038/s41598-023-49791-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 12/12/2023] [Indexed: 12/19/2023] Open
Abstract
Since November 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused the worldwide pandemic of the coronavirus disease 2019 (COVID-19), the impact of which is huge to the lives of world populations. Many studies suggested that such situation will continue due to the endless mutations in SARS-CoV-2 genome that result in complexity of the efforts for the control of SARS-CoV-2, since the special enrichment of nucleotide substitution C>U in SARS-CoV-2 sequences were discovered mainly due to the editing by human host factors APOBEC3 genes. The observation of SARS-CoV-2 variants Beta (B.1.351) and Omicron (B.1.1.529) firstly spreading in South Africa promoted us to hypothesize that genetic variants of APOBEC3 special in African populations may be attributed to the higher mutation rate of SARS-CoV-2 variants in Africa. Current study was conducted to search for functional variants of APOBEC3 genes associate with COVID-19 hospitalization in African population. By integrating data from the 1000 Genomes Project, Genotype-Tissue Expression (GTEx), and Host Genetics Initiative (HGI) of COVID-19, we identified potential functional SNPs close to APOBEC3 genes that are associated with COVID-19 hospitalization in African but not with other populations. Our study provides new insights on the potential contribution of APOBEC3 genes on the evolution of SARS-CoV-2 mutations in African population, but further replication is needed to confirm our results.
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Affiliation(s)
- Ke Zhang
- The Key and Characteristic Laboratory of Modern Pathogenicity Biology, School of Basic Medical Sciences, Guizhou Medical University, Guiyang, 561113, China
| | - Fang Chen
- The Key and Characteristic Laboratory of Modern Pathogenicity Biology, School of Basic Medical Sciences, Guizhou Medical University, Guiyang, 561113, China
| | - Hu-Yan Shen
- The Key and Characteristic Laboratory of Modern Pathogenicity Biology, School of Basic Medical Sciences, Guizhou Medical University, Guiyang, 561113, China
| | - Ping-Ping Zhang
- The Key and Characteristic Laboratory of Modern Pathogenicity Biology, School of Basic Medical Sciences, Guizhou Medical University, Guiyang, 561113, China
| | - Han Gao
- The Department of Emergency ICU, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China
| | - Hong Peng
- The Department of Emergency ICU, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China
| | - Yu-Si Luo
- The Department of Emergency ICU, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China.
- The Department of Emergency, Liupanshui Hospital of The Affiliated Hospital of Guizhou Medical University, Liupanshui, 553000, China.
| | - Zhong-Shan Cheng
- Center for Applied Bioinformatics, St. Jude Children's Research Hospital, 262 Danny Thomas Hospital, MS1122, Memphis, TN, 38105, USA.
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13
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Li L, Hu L, Qiao X, Mo R, Liu G, Hu L. Integrative Analysis of DNA Methylation and Gene Expression Data Identifies Potential Biomarkers and Functional Epigenetic Modules for SARS-CoV-2. Biochem Genet 2023; 61:2318-2329. [PMID: 37017853 PMCID: PMC10075172 DOI: 10.1007/s10528-023-10373-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 03/27/2023] [Indexed: 04/06/2023]
Abstract
To integrate gene expression and DNA methylation data and find the potential role of DNA methylation in the invasion and replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We first conducted differential expression and methylation analysis between the coronavirus disease of 2019 (COVID-19) and healthy controls. FEM was employed to identify functional epigenetic modules, from which a diagnostic model for COVID-19 was built. SKA1 and WSB1 modules were identified, with SKA1 module enriched in COVID-19 replication and transcription, and WSB1 module related to ubiquitin-protein activity. The differentially expressed or differentially methylated genes in these two modules could be used to distinguish COVID-19 from healthy controls, with AUC reaching 1 and 0.98 for SKA1 and WSB1 modules, respectively. Two epigenetically activated genes (CENPM and KNL1) from the SKA1 module were upregulated in HPV- or HBV-positive tumor samples and were found to be significantly associated with the survival of tumor patients. In conclusion, the identified FEM modules and potential signatures play an essential role in the replication and transcription of coronavirus.
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Affiliation(s)
- Lu Li
- Department of Radiology and Interventional Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430023, Hubei, China
| | - Lingli Hu
- Department of Infectious Diseases, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430023, Hubei, China
| | - Xueli Qiao
- Office of Hospital Infection Management, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430023, Hubei, China
| | - Ruo Mo
- Office of Hospital Infection Management, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430023, Hubei, China
| | - Guangya Liu
- Outpatient Office, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430023, Hubei, China.
| | - Lingyan Hu
- Office of Hospital Infection Management, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430023, Hubei, China.
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14
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Lee SG, Furth PA, Hennighausen L, Lee HK. Variant- and Vaccination-Specific Alternative Splicing Profiles in SARS-CoV-2 Infections. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.24.568603. [PMID: 38076812 PMCID: PMC10705549 DOI: 10.1101/2023.11.24.568603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, and its subsequent variants has underscored the importance of understanding the host-viral molecular interactions to devise effective therapeutic strategies. A significant aspect of these interactions is the role of alternative splicing in modulating host responses and viral replication mechanisms. Our study sought to delineate the patterns of alternative splicing of RNAs from immune cells across different SARS-CoV-2 variants and vaccination statuses, utilizing a robust dataset of 190 RNA-seq samples from our previous studies, encompassing an average of 212 million reads per sample. We identified a dynamic alteration in alternative splicing and genes related to RNA splicing were highly deactivated in COVID-19 patients and showed variant- and vaccination-specific expression profiles. Overall, Omicron-infected patients exhibited a gene expression profile akin to healthy controls, unlike the Alpha or Beta variants. However, significantly, we found identified a subset of infected individuals, most pronounced in vaccinated patients infected with Omicron variant, that exhibited a specific dynamic in their alternative splicing patterns that was not widely shared amongst the other groups. Our findings underscore the complex interplay between SARS-CoV-2 variants, vaccination-induced immune responses, and alternative splicing, emphasizing the necessity for further investigations into these molecular cross-talks to foster deeper understanding and guide strategic therapeutic development.
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Affiliation(s)
- Sung-Gwon Lee
- Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, USA
| | - Priscilla A. Furth
- Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, USA
| | - Lothar Hennighausen
- Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, USA
| | - Hye Kyung Lee
- Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, USA
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15
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Pereira EPV, da Silva Felipe SM, de Freitas RM, da Cruz Freire JE, Oliveira AER, Canabrava N, Soares PM, van Tilburg MF, Guedes MIF, Grueter CE, Ceccatto VM. Transcriptional Profiling of SARS-CoV-2-Infected Calu-3 Cells Reveals Immune-Related Signaling Pathways. Pathogens 2023; 12:1373. [PMID: 38003837 PMCID: PMC10674242 DOI: 10.3390/pathogens12111373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 11/11/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
The COVID-19 disease, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), emerged in late 2019 and rapidly spread worldwide, becoming a pandemic that infected millions of people and caused significant deaths. COVID-19 continues to be a major threat, and there is a need to deepen our understanding of the virus and its mechanisms of infection. To study the cellular responses to SARS-CoV-2 infection, we performed an RNA sequencing of infected vs. uninfected Calu-3 cells. Total RNA was extracted from infected (0.5 MOI) and control Calu-3 cells and converted to cDNA. Sequencing was performed, and the obtained reads were quality-analyzed and pre-processed. Differential expression was assessed with the EdgeR package, and functional enrichment was performed in EnrichR for Gene Ontology, KEGG pathways, and WikiPathways. A total of 1040 differentially expressed genes were found in infected vs. uninfected Calu-3 cells, of which 695 were up-regulated and 345 were down-regulated. Functional enrichment analyses revealed the predominant up-regulation of genes related to innate immune response, response to virus, inflammation, cell proliferation, and apoptosis. These transcriptional changes following SARS-CoV-2 infection may reflect a cellular response to the infection and help to elucidate COVID-19 pathogenesis, in addition to revealing potential biomarkers and drug targets.
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Affiliation(s)
- Eric Petterson Viana Pereira
- Superior Institute of Biomedical Sciences, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (S.M.d.S.F.); (R.M.d.F.); (J.E.d.C.F.); (P.M.S.)
| | - Stela Mirla da Silva Felipe
- Superior Institute of Biomedical Sciences, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (S.M.d.S.F.); (R.M.d.F.); (J.E.d.C.F.); (P.M.S.)
| | - Raquel Martins de Freitas
- Superior Institute of Biomedical Sciences, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (S.M.d.S.F.); (R.M.d.F.); (J.E.d.C.F.); (P.M.S.)
| | - José Ednésio da Cruz Freire
- Superior Institute of Biomedical Sciences, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (S.M.d.S.F.); (R.M.d.F.); (J.E.d.C.F.); (P.M.S.)
| | | | - Natália Canabrava
- Biotechnology and Molecular Biology Laboratory, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (N.C.); (M.F.v.T.); (M.I.F.G.)
| | - Paula Matias Soares
- Superior Institute of Biomedical Sciences, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (S.M.d.S.F.); (R.M.d.F.); (J.E.d.C.F.); (P.M.S.)
| | - Mauricio Fraga van Tilburg
- Biotechnology and Molecular Biology Laboratory, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (N.C.); (M.F.v.T.); (M.I.F.G.)
| | - Maria Izabel Florindo Guedes
- Biotechnology and Molecular Biology Laboratory, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (N.C.); (M.F.v.T.); (M.I.F.G.)
| | - Chad Eric Grueter
- Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA;
| | - Vânia Marilande Ceccatto
- Superior Institute of Biomedical Sciences, State University of Ceará, Fortaleza 60714-903, CE, Brazil; (S.M.d.S.F.); (R.M.d.F.); (J.E.d.C.F.); (P.M.S.)
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16
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Wimmers F, Burrell AR, Feng Y, Zheng H, Arunachalam PS, Hu M, Spranger S, Nyhoff LE, Joshi D, Trisal M, Awasthi M, Bellusci L, Ashraf U, Kowli S, Konvinse KC, Yang E, Blanco M, Pellegrini K, Tharp G, Hagan T, Chinthrajah RS, Nguyen TT, Grifoni A, Sette A, Nadeau KC, Haslam DB, Bosinger SE, Wrammert J, Maecker HT, Utz PJ, Wang TT, Khurana S, Khatri P, Staat MA, Pulendran B. Multi-omics analysis of mucosal and systemic immunity to SARS-CoV-2 after birth. Cell 2023; 186:4632-4651.e23. [PMID: 37776858 PMCID: PMC10724861 DOI: 10.1016/j.cell.2023.08.044] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 06/18/2023] [Accepted: 08/31/2023] [Indexed: 10/02/2023]
Abstract
The dynamics of immunity to infection in infants remain obscure. Here, we used a multi-omics approach to perform a longitudinal analysis of immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in infants and young children by analyzing blood samples and weekly nasal swabs collected before, during, and after infection with Omicron and non-Omicron variants. Infection stimulated robust antibody titers that, unlike in adults, showed no sign of decay for up to 300 days. Infants mounted a robust mucosal immune response characterized by inflammatory cytokines, interferon (IFN) α, and T helper (Th) 17 and neutrophil markers (interleukin [IL]-17, IL-8, and CXCL1). The immune response in blood was characterized by upregulation of activation markers on innate cells, no inflammatory cytokines, but several chemokines and IFNα. The latter correlated with viral load and expression of interferon-stimulated genes (ISGs) in myeloid cells measured by single-cell multi-omics. Together, these data provide a snapshot of immunity to infection during the initial weeks and months of life.
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Affiliation(s)
- Florian Wimmers
- Department of Molecular Medicine, Interfaculty Institute for Biochemistry, University of Tuebingen, 72076 Tuebingen, Baden-Wuerttemberg, Germany; DFG Cluster of Excellence 2180 "Image-guided and Functional Instructed Tumor Therapy" (iFIT), University of Tuebingen, 72076 Tuebingen, Baden-Wuerttemberg, Germany; German Consortium for Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), 69120 Heidelberg, Baden-Wuerttemberg, Germany
| | - Allison R Burrell
- Department of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Environmental and Public Health Sciences, Division of Epidemiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Yupeng Feng
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA
| | - Hong Zheng
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Prabhu S Arunachalam
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA
| | - Mengyun Hu
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA
| | - Sara Spranger
- Department of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Lindsay E Nyhoff
- Department of Pediatrics, Division of Infectious Disease, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Devyani Joshi
- Department of Pediatrics, Division of Infectious Disease, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Meera Trisal
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA
| | - Mayanka Awasthi
- Division of Viral Products, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD 20993, USA
| | - Lorenza Bellusci
- Division of Viral Products, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD 20993, USA
| | - Usama Ashraf
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA
| | - Sangeeta Kowli
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Katherine C Konvinse
- Department of Pediatrics, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Emily Yang
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Michael Blanco
- Stanford Genomics Service Center, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | - Gregory Tharp
- Yerkes National Primate Research Center, Atlanta, GA 30024, USA
| | - Thomas Hagan
- Department of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - R Sharon Chinthrajah
- Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research, Stanford, CA 94305, USA
| | - Tran T Nguyen
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Alba Grifoni
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA
| | - Alessandro Sette
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA; Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego, La Jolla, CA 92037, USA
| | - Kari C Nadeau
- Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research, Stanford, CA 94305, USA
| | - David B Haslam
- Department of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Steven E Bosinger
- Yerkes National Primate Research Center, Atlanta, GA 30024, USA; Department of Pathology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jens Wrammert
- Department of Pediatrics, Division of Infectious Disease, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Holden T Maecker
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Paul J Utz
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Taia T Wang
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Surender Khurana
- Division of Viral Products, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD 20993, USA
| | - Purvesh Khatri
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Mary A Staat
- Department of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Bali Pulendran
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA.
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17
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Pandya R, He YD, Sweeney TE, Hasin-Brumshtein Y, Khatri P. A machine learning classifier using 33 host immune response mRNAs accurately distinguishes viral and non-viral acute respiratory illnesses in nasal swab samples. Genome Med 2023; 15:64. [PMID: 37641125 PMCID: PMC10463681 DOI: 10.1186/s13073-023-01216-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 07/27/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Viral acute respiratory illnesses (viral ARIs) contribute significantly to human morbidity and mortality worldwide, but their successful treatment requires timely diagnosis of viral etiology, which is complicated by overlap in clinical presentation with the non-viral ARIs. Multiple pandemics in the twenty-first century to date have further highlighted the unmet need for effective monitoring of clinically relevant emerging viruses. Recent studies have identified conserved host response to viral infections in the blood. METHODS We hypothesize that a similarly conserved host response in nasal samples can be utilized for diagnosis and to rule out viral infection in symptomatic patients when current diagnostic tests are negative. Using a multi-cohort analysis framework, we analyzed 1555 nasal samples across 10 independent cohorts dividing them into training and validation. RESULTS Using six of the datasets for training, we identified 119 genes that are consistently differentially expressed in viral ARI patients (N = 236) compared to healthy controls (N = 146) and further down-selected 33 genes for classifier development. The resulting locked logistic regression-based classifier using the 33-mRNAs had AUC of 0.94 and 0.89 in the six training and four validation datasets, respectively. Furthermore, we found that although trained on healthy controls only, in the four validation datasets, the 33-mRNA classifier distinguished viral ARI from both healthy or non-viral ARI samples with > 80% specificity and sensitivity, irrespective of age, viral type, and viral load. Single-cell RNA-sequencing data showed that the 33-mRNA signature is dominated by macrophages and neutrophils in nasal samples. CONCLUSION This proof-of-concept signature has potential to be adapted as a clinical point-of-care test ('RespVerity') to improve the diagnosis of viral ARIs.
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Affiliation(s)
| | - Yudong D. He
- Inflammatix Inc., CA 94085 Sunnyvale, USA
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA 94305 USA
- Allen Institute of Immunology, Seattle, WA USA
| | | | | | - Purvesh Khatri
- Inflammatix Inc., CA 94085 Sunnyvale, USA
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA 94305 USA
- Department of Medicine, Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA 94305 USA
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18
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Bakaros E, Voulgaridi I, Paliatsa V, Gatselis N, Germanidis G, Asvestopoulou E, Alexiou S, Botsfari E, Lygoura V, Tsachouridou O, Mimtsoudis I, Tseroni M, Sarrou S, Mouchtouri VA, Dadouli K, Kalala F, Metallidis S, Dalekos G, Hadjichristodoulou C, Speletas M. Innate Immune Gene Polymorphisms and COVID-19 Prognosis. Viruses 2023; 15:1784. [PMID: 37766191 PMCID: PMC10537595 DOI: 10.3390/v15091784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 08/19/2023] [Accepted: 08/19/2023] [Indexed: 09/29/2023] Open
Abstract
COVID-19 is characterized by a heterogeneous clinical presentation and prognosis. Risk factors contributing to the development of severe disease include old age and the presence of comorbidities. However, the genetic background of the host has also been recognized as an important determinant of disease prognosis. Considering the pivotal role of innate immunity in the control of SARS-CoV-2 infection, we analyzed the possible contribution of several innate immune gene polymorphisms (including TLR2-rs5743708, TLR4-rs4986790, TLR4-rs4986791, CD14-rs2569190, CARD8-rs1834481, IL18-rs2043211, and CD40-rs1883832) in disease severity and prognosis. A total of 249 individuals were enrolled and further divided into five (5) groups, according to the clinical progression scale provided by the World Health Organization (WHO) (asymptomatic, mild, moderate, severe, and critical). We identified that elderly patients with obesity and/or diabetes mellitus were more susceptible to developing pneumonia and respiratory distress syndrome after SARS-CoV-2 infection, while the IL18-rs1834481 polymorphism was an independent risk factor for developing pneumonia. Moreover, individuals carrying either the TLR2-rs5743708 or the TLR4-rs4986791 polymorphisms exhibited a 3.6- and 2.5-fold increased probability for developing pneumonia and a more severe disease, respectively. Our data support the notion that the host's genetic background can significantly affect COVID-19 clinical phenotype, also suggesting that the IL18-rs1834481, TLR2-rs5743708, and TLR4-rs4986791 polymorphisms may be used as molecular predictors of COVID-19 clinical phenotype.
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Affiliation(s)
- Evangelos Bakaros
- Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece; (E.B.); (V.P.); (E.A.); (S.A.); (E.B.); (S.S.); (F.K.)
| | - Ioanna Voulgaridi
- Laboratory of Hygiene and Epidemiology, Faculty of Medicine, University of Thessaly, 41222 Larissa, Greece; (I.V.); (V.A.M.); (K.D.); (C.H.)
| | - Vassiliki Paliatsa
- Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece; (E.B.); (V.P.); (E.A.); (S.A.); (E.B.); (S.S.); (F.K.)
| | - Nikolaos Gatselis
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, Full Member of the European Reference Network on Hepatological Diseases (ERN RARE-LIVER), General University Hospital of Larissa, 41110 Larissa, Greece; (N.G.); (V.L.); (G.D.)
| | - Georgios Germanidis
- First Internal Medicine Department, Infectious Diseases Division, AHEPA Hospital, Medical School, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (G.G.); (O.T.); (I.M.); (S.M.)
| | - Evangelia Asvestopoulou
- Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece; (E.B.); (V.P.); (E.A.); (S.A.); (E.B.); (S.S.); (F.K.)
| | - Stamatia Alexiou
- Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece; (E.B.); (V.P.); (E.A.); (S.A.); (E.B.); (S.S.); (F.K.)
| | - Elli Botsfari
- Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece; (E.B.); (V.P.); (E.A.); (S.A.); (E.B.); (S.S.); (F.K.)
| | - Vasiliki Lygoura
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, Full Member of the European Reference Network on Hepatological Diseases (ERN RARE-LIVER), General University Hospital of Larissa, 41110 Larissa, Greece; (N.G.); (V.L.); (G.D.)
| | - Olga Tsachouridou
- First Internal Medicine Department, Infectious Diseases Division, AHEPA Hospital, Medical School, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (G.G.); (O.T.); (I.M.); (S.M.)
| | - Iordanis Mimtsoudis
- First Internal Medicine Department, Infectious Diseases Division, AHEPA Hospital, Medical School, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (G.G.); (O.T.); (I.M.); (S.M.)
| | - Maria Tseroni
- National Public Health Organization, 15123 Athens, Greece;
| | - Styliani Sarrou
- Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece; (E.B.); (V.P.); (E.A.); (S.A.); (E.B.); (S.S.); (F.K.)
| | - Varvara A. Mouchtouri
- Laboratory of Hygiene and Epidemiology, Faculty of Medicine, University of Thessaly, 41222 Larissa, Greece; (I.V.); (V.A.M.); (K.D.); (C.H.)
| | - Katerina Dadouli
- Laboratory of Hygiene and Epidemiology, Faculty of Medicine, University of Thessaly, 41222 Larissa, Greece; (I.V.); (V.A.M.); (K.D.); (C.H.)
| | - Fani Kalala
- Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece; (E.B.); (V.P.); (E.A.); (S.A.); (E.B.); (S.S.); (F.K.)
| | - Simeon Metallidis
- First Internal Medicine Department, Infectious Diseases Division, AHEPA Hospital, Medical School, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (G.G.); (O.T.); (I.M.); (S.M.)
| | - George Dalekos
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, Full Member of the European Reference Network on Hepatological Diseases (ERN RARE-LIVER), General University Hospital of Larissa, 41110 Larissa, Greece; (N.G.); (V.L.); (G.D.)
| | - Christos Hadjichristodoulou
- Laboratory of Hygiene and Epidemiology, Faculty of Medicine, University of Thessaly, 41222 Larissa, Greece; (I.V.); (V.A.M.); (K.D.); (C.H.)
| | - Matthaios Speletas
- Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece; (E.B.); (V.P.); (E.A.); (S.A.); (E.B.); (S.S.); (F.K.)
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19
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Quach HQ, Goergen KM, Grill DE, Haralambieva IH, Ovsyannikova IG, Poland GA, Kennedy RB. Virus-specific and shared gene expression signatures in immune cells after vaccination in response to influenza and vaccinia stimulation. Front Immunol 2023; 14:1168784. [PMID: 37600811 PMCID: PMC10436507 DOI: 10.3389/fimmu.2023.1168784] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 07/18/2023] [Indexed: 08/22/2023] Open
Abstract
Background In the vaccine era, individuals receive multiple vaccines in their lifetime. Host gene expression in response to antigenic stimulation is usually virus-specific; however, identifying shared pathways of host response across a wide spectrum of vaccine pathogens can shed light on the molecular mechanisms/components which can be targeted for the development of broad/universal therapeutics and vaccines. Method We isolated PBMCs, monocytes, B cells, and CD8+ T cells from the peripheral blood of healthy donors, who received both seasonal influenza vaccine (within <1 year) and smallpox vaccine (within 1 - 4 years). Each of the purified cell populations was stimulated with either influenza virus or vaccinia virus. Differentially expressed genes (DEGs) relative to unstimulated controls were identified for each in vitro viral infection, as well as for both viral infections (shared DEGs). Pathway enrichment analysis was performed to associate identified DEGs with KEGG/biological pathways. Results We identified 2,906, 3,888, 681, and 446 DEGs in PBMCs, monocytes, B cells, and CD8+ T cells, respectively, in response to influenza stimulation. Meanwhile, 97, 120, 20, and 10 DEGs were identified as gene signatures in PBMCs, monocytes, B cells, and CD8+ T cells, respectively, upon vaccinia stimulation. The majority of DEGs identified in PBMCs were also found in monocytes after either viral stimulation. Of the virus-specific DEGs, 55, 63, and 9 DEGs occurred in common in PBMCs, monocytes, and B cells, respectively, while no DEGs were shared in infected CD8+ T cells after influenza and vaccinia. Gene set enrichment analysis demonstrated that these shared DEGs were over-represented in innate signaling pathways, including cytokine-cytokine receptor interaction, viral protein interaction with cytokine and cytokine receptor, Toll-like receptor signaling, RIG-I-like receptor signaling pathways, cytosolic DNA-sensing pathways, and natural killer cell mediated cytotoxicity. Conclusion Our results provide insights into virus-host interactions in different immune cells, as well as host defense mechanisms against viral stimulation. Our data also highlights the role of monocytes as a major cell population driving gene expression in ex vivo PBMCs in response to viral stimulation. The immune response signaling pathways identified in this study may provide specific targets for the development of novel virus-specific therapeutics and improved vaccines for vaccinia and influenza. Although influenza and vaccinia viruses have been selected in this study as pathogen models, this approach could be applicable to other pathogens.
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Affiliation(s)
- Huy Quang Quach
- Mayo Clinic Vaccine Research Group, Division of General Internal Medicine, Mayo Clinic, Rochester, MN, United States
| | - Krista M. Goergen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
| | - Diane E. Grill
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
| | - Iana H. Haralambieva
- Mayo Clinic Vaccine Research Group, Division of General Internal Medicine, Mayo Clinic, Rochester, MN, United States
| | - Inna G. Ovsyannikova
- Mayo Clinic Vaccine Research Group, Division of General Internal Medicine, Mayo Clinic, Rochester, MN, United States
| | - Gregory A. Poland
- Mayo Clinic Vaccine Research Group, Division of General Internal Medicine, Mayo Clinic, Rochester, MN, United States
| | - Richard B. Kennedy
- Mayo Clinic Vaccine Research Group, Division of General Internal Medicine, Mayo Clinic, Rochester, MN, United States
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20
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Sasson J, Moreau GB, Petri WA. The role of interleukin 13 and the type 2 immune pathway in COVID-19: A review. Ann Allergy Asthma Immunol 2023; 130:727-732. [PMID: 36924937 PMCID: PMC10014128 DOI: 10.1016/j.anai.2023.03.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 02/23/2023] [Accepted: 03/06/2023] [Indexed: 03/16/2023]
Abstract
Although much has been learned about severe acute respiratory syndrome coronavirus 2 since December 2019, uneven global vaccine distribution, rapid viral spread, and variant evasion of preventative measures have led to its persistence in the population for the foreseeable future. Additional therapies are needed to support patients through their acute, immune-mediated disease process that continues to lead to considerable morbidity and mortality. Data revealing the involvement of type 2 immune pathway in acute coronavirus disease 2019 and post-recovery conditions represent a potential additional area for intervention. Herein, we review the current understanding of interleukin 13 in acute severe acute respiratory syndrome coronavirus 2 infection, the clinical outcomes associated with type 2 immune processes, and the impact of type 2 blockade on acute and long-term coronavirus disease 2019 conditions.
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Affiliation(s)
- Jennifer Sasson
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - G Brett Moreau
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
| | - William A Petri
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia; Department of Microbiology, Immunology and Cancer Biology, University of Virginia School of Medicine, Charlottesville, Virginia; Department of Pathology, University of Virginia Health System, Charlottesville, Virginia.
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21
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Forst CV, Zeng L, Wang Q, Zhou X, Vatansever S, Xu P, Song W, Tu Z, Zhang B. Multiscale network analysis identifies potential receptors for SARS-CoV-2 and reveals their tissue-specific and age-dependent expression. FEBS Lett 2023; 597:1384-1402. [PMID: 36951513 PMCID: PMC10294276 DOI: 10.1002/1873-3468.14613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 02/13/2023] [Accepted: 02/27/2023] [Indexed: 03/24/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has affected tens of millions of individuals and caused hundreds of thousands of deaths worldwide. Here, we present a comprehensive, multiscale network analysis of the transcriptional response to the virus. In particular, we focused on key regulators, cell receptors, and host processes that were hijacked by the virus for its advantage. ACE2-controlled processes involved CD300e (a TYROBP receptor) as a key regulator and the activation of IL-2 pro-inflammatory cytokine signaling. We further investigated the age dependency of such receptors in different tissues. In summary, this study provides novel insights into the gene regulatory organization during the SARS-CoV-2 infection and the tissue-specific, age-dependent expression of the cell receptors involved in COVID-19.
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Affiliation(s)
- Christian V. Forst
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Department of MicrobiologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Lu Zeng
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Qian Wang
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Xianxiao Zhou
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Sezen Vatansever
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Peng Xu
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Won‐Min Song
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Zhidong Tu
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Bin Zhang
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
- Department of Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
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22
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Barh D, Aburjaile FF, Tavares TS, da Silva ME, Bretz GPM, Rocha IFM, Dey A, de Souza RP, Góes-Neto A, Ribeiro SP, Alzahrani KJ, Alghamdi AA, Alzahrani FM, Halawani IF, Tiwari S, Aljabali AAA, Lundstrom K, Azevedo V, Ganguly NK. Indian food habit & food ingredients may have a role in lowering the severity & high death rate from COVID-19 in Indians: findings from the first nutrigenomic analysis. Indian J Med Res 2023; 157:293-303. [PMID: 37102510 PMCID: PMC10438415 DOI: 10.4103/ijmr.ijmr_1701_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Indexed: 04/28/2023] Open
Abstract
Background & objectives During the COVID-19 pandemic, the death rate was reportedly 5-8 fold lower in India which is densely populated as compared to less populated western countries. The aim of this study was to investigate whether dietary habits were associated with the variations in COVID-19 severity and deaths between western and Indian population at the nutrigenomics level. Methods In this study nutrigenomics approach was applied. Blood transcriptome of severe COVID-19 patients from three western countries (showing high fatality) and two datasets from Indian patients were used. Gene set enrichment analyses were performed for pathways, metabolites, nutrients, etc., and compared for western and Indian samples to identify the food- and nutrient-related factors, which may be associated with COVID-19 severity. Data on the daily consumption of twelve key food components across four countries were collected and a correlation between nutrigenomics analyses and per capita daily dietary intake was investigated. Results Distinct dietary habits of Indians were observed, which may be associated with low death rate from COVID-19. Increased consumption of red meat, dairy products and processed foods by western populations may increase the severity and death rate by activating cytokine storm-related pathways, intussusceptive angiogenesis, hypercapnia and enhancing blood glucose levels due to high contents of sphingolipids, palmitic acid and byproducts such as CO2 and lipopolysaccharide (LPS). Palmitic acid also induces ACE2 expression and increases the infection rate. Coffee and alcohol that are highly consumed in western countries may increase the severity and death rates from COVID-19 by deregulating blood iron, zinc and triglyceride levels. The components of Indian diets maintain high iron and zinc concentrations in blood and rich fibre in their foods may prevent CO2 and LPS-mediated COVID-19 severity. Regular consumption of tea by Indians maintains high high-density lipoprotein (HDL) and low triglyceride in blood as catechins in tea act as natural atorvastatin. Importantly, regular consumption of turmeric in daily food by Indians maintains strong immunity and curcumin in turmeric may prevent pathways and mechanisms associated with SARS-CoV-2 infection and COVID-19 severity and lowered the death rate. Interpretation & conclusions Our results suggest that Indian food components suppress cytokine storm and various other severity related pathways of COVID-19 and may have a role in lowering severity and death rates from COVID-19 in India as compared to western populations. However, large multi-centered case-control studies are required to support our current findings.
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Affiliation(s)
- Debmalya Barh
- Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics & Applied Biotechnology, Purba Medinipur, West Bengal, India
- Department of Genetics, Ecology & Evolution, Institute of Biological Sciences, Belo Horizonte, Brazil
| | - Flávia Figueira Aburjaile
- Department of Preventative Veterinary Medicine, School of Veterinary Medicine, Belo Horizonte, Brazil
| | - Thais Silva Tavares
- Department of Laboratory of Algorithms in Biology, Institute of Biological Sciences, Belo Horizonte, Brazil
| | | | | | - Igor Fernando Martins Rocha
- Department of Centre of Research on Health Vulnerability, Faculty of Medicine, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Annesha Dey
- Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics & Applied Biotechnology, Purba Medinipur, West Bengal, India
| | - Renan Pedra de Souza
- Department of Laboratory of Integrative Biology, Institute of Biological Sciences, Belo Horizonte, Brazil
| | - Aristóteles Góes-Neto
- Department of Genetics, Ecology & Evolution, Institute of Biological Sciences, Belo Horizonte, Brazil
| | - Sérvio Pontes Ribeiro
- Department of Laboratory of Ecology of Diseases & Forests, Nucleus of Biological Research, Universidade Federal de Ouro Preto, Ouro Preto, MG, Brazil
| | - Khalid J. Alzahrani
- Department of Clinical Laboratories Sciences, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Ahmad A. Alghamdi
- Department of Clinical Laboratories Sciences, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Fuad M. Alzahrani
- Department of Clinical Laboratories Sciences, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Ibrahim Faisal Halawani
- Department of Clinical Laboratories Sciences, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Sandeep Tiwari
- Department of Post-Graduation Programs in Microbiology and Immunology, Institute of Biology and Health Sciences, Federal University of Bahia, Salvador, BA, Brazil
| | - Alaa A. A. Aljabali
- Department of Pharmaceutics & Pharmaceutical Technology, Faculty of Pharmacy, Yarmouk University, Irbid, Jordan
| | | | - Vasco Azevedo
- Department of Genetics, Ecology & Evolution, Institute of Biological Sciences, Belo Horizonte, Brazil
| | - Nirmal Kumar Ganguly
- Policy Center for Biomedical Research, Translational Health Science & Technology Institute, Faridabad, Haryana, India
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23
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Mucosal Gene Expression in Response to SARS-CoV-2 Is Associated with Viral Load. J Virol 2023; 97:e0147822. [PMID: 36656015 PMCID: PMC9973040 DOI: 10.1128/jvi.01478-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Little is known about the relationships between symptomatic early severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and upper airway mucosal gene expression and immune response. To examine the association of symptomatic SARS-CoV-2 early viral load with upper airway mucosal gene expression, we profiled the host mucosal transcriptome from nasopharyngeal swab samples from 68 adults with symptomatic, mild-to-moderate coronavirus disease 19 (COVID-19). We measured SARS-CoV-2 viral load using reverse transcription-quantitative PCR (RT-qPCR). We then examined the association of SARS-CoV-2 viral load with upper airway mucosal immune response. We detected SARS-CoV-2 in all samples and recovered >80% of the genome from 95% of the samples from symptomatic COVID-19 adults. The respiratory virome was dominated by SARS-CoV-2, with limited codetection of other respiratory viruses, with the human Rhinovirus C being identified in 4 (6%) samples. This limited codetection of other respiratory viral pathogens may be due to the implementation of public health measures, like social distancing and masking practices. We observed a significant positive correlation between SARS-CoV-2 viral load and interferon signaling (OAS2, OAS3, IFIT1, UPS18, ISG15, ISG20, IFITM1, and OASL), chemokine signaling (CXCL10 and CXCL11), and adaptive immune system (IFITM1, CD300E, and SIGLEC1) genes in symptomatic, mild-to-moderate COVID-19 adults, when adjusting for age, sex, and race. Interestingly, the expression levels of most of these genes plateaued at a cycle threshold (CT) value of ~25. Overall, our data show that the early nasal mucosal immune response to SARS-CoV-2 infection is viral load dependent, potentially modifying COVID-19 outcomes. IMPORTANCE Several prior studies have shown that SARS-CoV-2 viral load can predict the likelihood of disease spread and severity. A higher detectable SARS-CoV-2 plasma viral load was associated with worse respiratory disease severity. However, the relationship between SARS-CoV-2 viral load, airway mucosal gene expression, and immune response remains elusive. We profiled the nasal mucosal transcriptome from nasal samples collected from adults infected with SARS-CoV-2 during spring 2020 with mild-to-moderate symptoms using a comprehensive metatranscriptomics method. We observed a positive correlation between SARS-CoV-2 viral load, interferon signaling, chemokine signaling, and adaptive immune system in adults with COVID-19. Our data suggest that early nasal mucosal immune response to SARS-CoV-2 infection was viral load dependent and may modify COVID-19 outcomes.
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24
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Zhang Z, Sauerwald N, Cappuccio A, Ramos I, Nair VD, Nudelman G, Zaslavsky E, Ge Y, Gaitas A, Ren H, Brockman J, Geis J, Ramalingam N, King D, McClain MT, Woods CW, Henao R, Burke TW, Tsalik EL, Goforth CW, Lizewski RA, Lizewski SE, Weir DL, Letizia AG, Sealfon SC, Troyanskaya OG. Blood RNA alternative splicing events as diagnostic biomarkers for infectious disease. CELL REPORTS METHODS 2023; 3:100395. [PMID: 36936082 PMCID: PMC10014279 DOI: 10.1016/j.crmeth.2023.100395] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 10/31/2022] [Accepted: 01/09/2023] [Indexed: 01/13/2023]
Abstract
Assays detecting blood transcriptome changes are studied for infectious disease diagnosis. Blood-based RNA alternative splicing (AS) events, which have not been well characterized in pathogen infection, have potential normalization and assay platform stability advantages over gene expression for diagnosis. Here, we present a computational framework for developing AS diagnostic biomarkers. Leveraging a large prospective cohort of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whole-blood RNA sequencing (RNA-seq) data, we identify a major functional AS program switch upon viral infection. Using an independent cohort, we demonstrate the improved accuracy of AS biomarkers for SARS-CoV-2 diagnosis compared with six reported transcriptome signatures. We then optimize a subset of AS-based biomarkers to develop microfluidic PCR diagnostic assays. This assay achieves nearly perfect test accuracy (61/62 = 98.4%) using a naive principal component classifier, significantly more accurate than a gene expression PCR assay in the same cohort. Therefore, our RNA splicing computational framework enables a promising avenue for host-response diagnosis of infection.
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Affiliation(s)
- Zijun Zhang
- Center for Computational Biology, Flatiron Institute, New York, NY 10010, USA
- Division of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Natalie Sauerwald
- Center for Computational Biology, Flatiron Institute, New York, NY 10010, USA
| | - Antonio Cappuccio
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Irene Ramos
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Venugopalan D. Nair
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - German Nudelman
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yongchao Ge
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Angelo Gaitas
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hui Ren
- Fluidigm Corporation, South San Francisco, CA 94080, USA
| | - Joel Brockman
- Fluidigm Corporation, South San Francisco, CA 94080, USA
| | - Jennifer Geis
- Fluidigm Corporation, South San Francisco, CA 94080, USA
| | | | - David King
- Fluidigm Corporation, South San Francisco, CA 94080, USA
| | - Micah T. McClain
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | - Christopher W. Woods
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | - Ricardo Henao
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | - Thomas W. Burke
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | - Ephraim L. Tsalik
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | | | | | | | - Dawn L. Weir
- Naval Medical Research Center, Silver Spring, MD, USA
| | | | - Stuart C. Sealfon
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Olga G. Troyanskaya
- Center for Computational Biology, Flatiron Institute, New York, NY 10010, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
- Department of Computer Science, Princeton University, Princeton, NJ 08544, USA
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25
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del Molino del Barrio I, Hayday TS, Laing AG, Hayday AC, Di Rosa F. COVID-19: Using high-throughput flow cytometry to dissect clinical heterogeneity. Cytometry A 2023; 103:117-126. [PMID: 34811890 PMCID: PMC9011838 DOI: 10.1002/cyto.a.24516] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/18/2021] [Accepted: 11/11/2021] [Indexed: 12/22/2022]
Abstract
Here we consider how high-content flow cytometric methodology at appropriate scale and throughput rapidly provided meaningful biological data in our recent studies of COVID-19, which we discuss in the context of other similar investigations. In our work, high-throughput flow cytometry was instrumental to identify a consensus immune signature in COVID-19 patients, and to investigate the impact of SARS-CoV-2 exposure on patients with either solid or hematological cancers. We provide here some examples of our 'holistic' approach, in which flow cytometry data generated by lymphocyte and myelomonocyte panels were integrated with other analytical metrics, including SARS-CoV-2-specific serum antibody titers, plasma cytokine/chemokine levels, and in-depth clinical annotation. We report how selective differences between T cell subsets were revealed by a newly described flow cytometric TDS assay to distinguish actively cycling T cells in the peripheral blood. By such approaches, our and others' high-content flow cytometry studies collectively identified overt abnormalities and subtle but critical changes that discriminate the immuno-signature of COVID-19 patients from those of healthy donors and patients with non-COVID respiratory infections. Thereby, these studies offered several meaningful biomarkers of COVID-19 severity that have the potential to improve the management of patients and of hospital resources. In sum, flow cytometry provides an important means for rapidly obtaining data that can guide clinical decision-making without requiring highly expensive, sophisticated equipment, and/or "-omics" capabilities. We consider how this approach might be further developed.
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Affiliation(s)
- Irene del Molino del Barrio
- Peter Gorer Department of ImmunobiologyKing's College LondonLondonUK
- University College LondonLondonUK
- Cancer Research UK Cancer Immunotherapy AcceleratorLondonUK
| | - Thomas S. Hayday
- Peter Gorer Department of ImmunobiologyKing's College LondonLondonUK
| | - Adam G. Laing
- Peter Gorer Department of ImmunobiologyKing's College LondonLondonUK
| | - Adrian C. Hayday
- Peter Gorer Department of ImmunobiologyKing's College LondonLondonUK
- Cancer Research UK Cancer Immunotherapy AcceleratorLondonUK
- Immunosurveillance LaboratoryThe Francis Crick InstituteLondonUK
| | - Francesca Di Rosa
- Institute of Molecular Biology and PathologyNational Research Council of ItalyRomeItaly
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26
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Krishnamoorthy P, Raj AS, Kumar H. Machine learning-driven blood transcriptome-based discovery of SARS-CoV-2 specific severity biomarkers. J Med Virol 2023; 95:e28488. [PMID: 36625381 DOI: 10.1002/jmv.28488] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 12/13/2022] [Accepted: 01/05/2023] [Indexed: 01/11/2023]
Abstract
The Coronavirus disease 2019 (COVID-19) pandemic, caused by rapidly evolving variants of severe acute respiratory syndrome coronavirus (SARS-CoV-2), continues to be a global health threat. SARS-CoV-2 infection symptoms often intersect with other nonsevere respiratory infections, making early diagnosis challenging. There is an urgent need for early diagnostic and prognostic biomarkers to predict severity and reduce mortality when a sudden outbreak occurs. This study implemented a novel approach of integrating bioinformatics and machine learning algorithms over publicly available clinical COVID-19 transcriptome data sets. The robust 7-gene biomarker identified through this analysis can not only discriminate SARS-CoV-2 associated acute respiratory illness (ARI) from other types of ARIs but also can discriminate severe COVID-19 patients from nonsevere COVID-19 patients. Validation of the 7-gene biomarker in an independent blood transcriptome data set of longitudinal analysis of COVID-19 patients across various stages of the disease showed that the dysregulation of the identified biomarkers during severe disease is restored during recovery, showing their prognostic potential. The blood biomarkers identified in this study can serve as potential diagnostic candidates and help reduce COVID-19-associated mortality.
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Affiliation(s)
- Pandikannan Krishnamoorthy
- Laboratory of Immunology and Infectious Disease Biology, Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Bhopal, Bhopal, Madhya Pradesh, India
| | - Athira S Raj
- Laboratory of Immunology and Infectious Disease Biology, Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Bhopal, Bhopal, Madhya Pradesh, India
| | - Himanshu Kumar
- Laboratory of Immunology and Infectious Disease Biology, Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Bhopal, Bhopal, Madhya Pradesh, India.,Laboratory of Host Defense, WPI Immunology, Frontier Research Centre, Osaka University, Osaka, Japan
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27
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Wang Z, Wang P, Lu X, Song C, Jiang S, Li L, Lu Y. Uncovering the potential pathological mechanism of acute pancreatitis in patients with COVID-19 by bioinformatics methods. World J Emerg Med 2023; 14:397-401. [PMID: 37908802 PMCID: PMC10613788 DOI: 10.5847/wjem.j.1920-8642.2023.099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 08/02/2023] [Indexed: 11/02/2023] Open
Affiliation(s)
- Zhaodi Wang
- Department of Nursing, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
- Department of Geriatric and Emergency medicine, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
- Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases of Zhejiang Province, Hangzhou 310003, China
| | - Ping Wang
- Department of Geriatric and Emergency medicine, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
- Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases of Zhejiang Province, Hangzhou 310003, China
| | - Xuan Lu
- Department of Geriatric and Emergency medicine, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
- Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases of Zhejiang Province, Hangzhou 310003, China
| | - Congying Song
- Department of Geriatric and Emergency medicine, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
- Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases of Zhejiang Province, Hangzhou 310003, China
| | - Shuai Jiang
- Department of Geriatric and Emergency medicine, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
- Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases of Zhejiang Province, Hangzhou 310003, China
| | - Li Li
- Department of Geriatric and Emergency medicine, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
- Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases of Zhejiang Province, Hangzhou 310003, China
| | - Yuanqiang Lu
- Department of Geriatric and Emergency medicine, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
- Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases of Zhejiang Province, Hangzhou 310003, China
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28
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A two-gene marker for the two-tiered innate immune response in COVID-19 patients. PLoS One 2023; 18:e0280392. [PMID: 36649304 PMCID: PMC9844909 DOI: 10.1371/journal.pone.0280392] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 12/28/2022] [Indexed: 01/18/2023] Open
Abstract
For coronavirus disease 2019 (COVID-19), a pandemic disease characterized by strong immune dysregulation in severe patients, convenient and efficient monitoring of the host immune response is critical. Human hosts respond to viral and bacterial infections in different ways, the former is characterized by the activation of interferon stimulated genes (ISGs) such as IFI27, while the latter is characterized by the activation of anti-bacterial associated genes (ABGs) such as S100A12. This two-tiered innate immune response has not been examined in COVID-19. In this study, the activation patterns of this two-tiered innate immune response represented by IFI27 and S100A12 were explored based on 1421 samples from 17 transcriptome datasets derived from the blood of COVID-19 patients and relevant controls. It was found that IFI27 activation occurred in most of the symptomatic patients and displayed no correlation with disease severity, while S100A12 activation was more restricted to patients under severe and critical conditions with a stepwise activation pattern. In addition, most of the S100A12 activation was accompanied by IFI27 activation. Furthermore, the activation of IFI27 was most pronounced within the first week of symptom onset, but generally waned after 2-3 weeks. On the other hand, the activation of S100A12 displayed no apparent correlation with disease duration and could last for several months in certain patients. These features of the two-tiered innate immune response can further our understanding on the disease mechanism of COVID-19 and may have implications to the clinical triage. Development of a convenient two-gene protocol for the routine serial monitoring of this two-tiered immune response will be a valuable addition to the existing laboratory tests.
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29
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Multi-objective optimization identifies a specific and interpretable COVID-19 host response signature. Cell Syst 2022; 13:989-1001.e8. [PMID: 36549275 DOI: 10.1016/j.cels.2022.11.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 08/05/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022]
Abstract
The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature's robustness in multiple independent COVID-19 cohorts. Using public data from 8,630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, or confounders. In contrast, previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature's interpretation, based on cell-type deconvolution and single-cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. Although the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts. A record of this paper's transparent peer review process is included in the supplemental information.
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30
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Zarei Ghobadi M, Emamzadeh R, Teymoori-Rad M, Afsaneh E. Exploration of blood−derived coding and non-coding RNA diagnostic immunological panels for COVID-19 through a co-expressed-based machine learning procedure. Front Immunol 2022; 13:1001070. [DOI: 10.3389/fimmu.2022.1001070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) is the causative virus of the pandemic coronavirus disease 2019 (COVID-19). Evaluating the immunological factors and other implicated processes underlying the progression of COVID-19 is essential for the recognition and then the design of efficacious therapies. Therefore, we analyzed RNAseq data obtained from PBMCs of the COVID-19 patients to explore coding and non-coding RNA diagnostic immunological panels. For this purpose, we integrated multiple RNAseq data and analyzed them overall as well as by considering the state of disease including severe and non-severe conditions. Afterward, we utilized a co-expressed-based machine learning procedure comprising weighted-gene co-expression analysis and differential expression gene as filter phase and recursive feature elimination-support vector machine as wrapper phase. This procedure led to the identification of two modules containing 5 and 84 genes which are mostly involved in cell dysregulation and innate immune suppression, respectively. Moreover, the role of vitamin D in regulating some classifiers was highlighted. Further analysis disclosed the role of discriminant miRNAs including miR-197-3p, miR-150-5p, miR-340-5p, miR-122-5p, miR-1307-3p, miR-34a-5p, miR-98-5p and their target genes comprising GAN, VWC2, TNFRSF6B, and CHST3 in the metabolic pathways. These classifiers differentiate the final fate of infection toward severe or non-severe COVID-19. The identified classifier genes and miRNAs may help in the proper design of therapeutic procedures considering their involvement in the immune and metabolic pathways.
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31
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Jin Q, Li W, Yu W, Zeng M, Liu J, Xu P. Analysis and identification of potential type II helper T cell (Th2)-Related key genes and therapeutic agents for COVID-19. Comput Biol Med 2022; 150:106134. [PMID: 36201886 PMCID: PMC9528635 DOI: 10.1016/j.compbiomed.2022.106134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 08/30/2022] [Accepted: 09/18/2022] [Indexed: 11/19/2022]
Abstract
COVID-19 pandemic poses a severe threat to public health. However, so far, there are no effective drugs for COVID-19. Transcriptomic changes and key genes related to Th2 cells in COVID-19 have not been reported. These genes play an important role in host interactions with SARS-COV-2 and may be used as promising target. We analyzed five COVID-19-associated GEO datasets (GSE157103, GSE152641, GSE171110, GSE152418, and GSE179627) using the xCell algorithm and weighted gene co-expression network analysis (WGCNA). Results showed that 5 closely correlated modular genes to COVID-19 and Th2 cell enrichment levels, including purple, blue, pink, tan and turquoise, were intersected with differentially expressed genes (DEGs) and 648 shared genes were obtained. GO and KEGG pathway enrichment analyses revealed that they were enriched in cell proliferation, differentiation, and immune responses after virus infection. The most significantly enriched pathway involved the regulation of viral life cycle. Three key genes, namely CCNB1, BUB1, and UBE2C, may clarify the pathogenesis of COVID-19 associated with Th2 cells. 11 drug candidates were identified that could down-regulate three key genes using the cMAP database and demonstrated strong drugs binding energies aganist the three keygenes using molecular docking methods. BUB1, CCNB1 and UBE2C were identified key genes for COVID-19 and could be promising therapeutic targets.
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Affiliation(s)
- Qiying Jin
- Institute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, PR China
| | - Wanxi Li
- Institute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, PR China
| | - Wendi Yu
- Institute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, PR China
| | - Maosen Zeng
- Institute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, PR China
| | - Jinyuan Liu
- Basic Medical College, Guangzhou University of Chinese Medicine, Guangzhou, PR China
| | - Peiping Xu
- Institute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, PR China.
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32
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Leligdowicz A, Harhay MO, Calfee CS. Immune Modulation in Sepsis, ARDS, and Covid-19 - The Road Traveled and the Road Ahead. NEJM EVIDENCE 2022; 1:EVIDra2200118. [PMID: 38319856 DOI: 10.1056/evidra2200118] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Immune Modulation in Sepsis, ARDS, and Covid-19Leligdowicz et al. consider the history and future of immunomodulating therapies in sepsis and ARDS, including ARDS due to Covid-19, and remark on the larger challenge of clinical research on therapies for syndromes with profound clinical and biologic heterogeneity.
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Affiliation(s)
- Aleksandra Leligdowicz
- Department of Medicine, Division of Critical Care Medicine, Western University, London, ON, Canada
- Robarts Research Institute, Western University, London, ON, Canada
| | - Michael O Harhay
- Clinical Trials Methods and Outcomes Lab, Palliative and Advanced Illness Research (PAIR) Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Carolyn S Calfee
- Department of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco
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Luo YS, Li W, Cai Y, Zhang J, Gui H, Zhang K, Cheng ZS. Genome-wide screening of sex-biased genetic variants potentially associated with COVID-19 hospitalization. Front Genet 2022; 13:1014191. [DOI: 10.3389/fgene.2022.1014191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 09/29/2022] [Indexed: 11/13/2022] Open
Abstract
Sex-biased difference in coronavirus disease 2019 (COVID-19) hospitalization has been observed as that male patients tend to be more likely to be hospitalized than female patients. However, due to the insufficient sample size and existed studies that more prioritized to sex-stratified COVID-19 genome-wide association study (GWAS), the searching for sex-biased genetic variants showing differential association signals between sexes with COVID-19 hospitalization was severely hindered. We hypothesized genetic variants would show potentially sex-biased genetic effects on COVID-19 hospitalization if they display significant differential association effect sizes between male and female COVID-19 patients. By integrating two COVID-19 GWASs, including hospitalized COVID-19 patients vs. general population separated into males (case = 1,917 and control = 221,174) and females (case = 1,343 and control = 262,886), we differentiated the association effect sizes of each common single nucleotide polymorphism (SNP) within the two GWASs. Twelve SNPs were suggested to show differential COVID-19 associations between sexes. Further investigation of genes (n = 58) close to these 12 SNPs resulted in the identification of 34 genes demonstrating sex-biased differential expression in at least one GTEx tissue. Finally, 5 SNPs are mapped to 8 genes, including rs1134004 (GADD45G), rs140657166 (TRIM29 and PVRL1), rs148143613 (KNDC1 and STK32C), rs2443615 (PGAP2 and TRIM21), and rs2924725 (CSMD1). The 8 genes display significantly differential gene expression in blood samples derived from COVID-19 patients compared to healthy controls. These genes are potential genetic factors contributing to sex differences in COVID-19 hospitalization and warranted for further functional studies.
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Development of Single-Cell Transcriptomics and Its Application in COVID-19. Viruses 2022; 14:v14102271. [PMID: 36298825 PMCID: PMC9611071 DOI: 10.3390/v14102271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 09/30/2022] [Accepted: 10/11/2022] [Indexed: 11/07/2022] Open
Abstract
Over the last three years, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related health crisis has claimed over six million lives and caused USD 12 trillion losses to the global economy. SARS-CoV-2 continuously mutates and evolves with a high basic reproduction number (R0), resulting in a variety of clinical manifestations ranging from asymptomatic infection to acute respiratory distress syndrome (ARDS) and even death. To gain a better understanding of coronavirus disease 2019 (COVID-19), it is critical to investigate the components that cause various clinical manifestations. Single-cell sequencing has substantial advantages in terms of identifying differentially expressed genes among individual cells, which can provide a better understanding of the various physiological and pathological processes. This article reviewed the use of single-cell transcriptomics in COVID-19 research, examined the immune response disparities generated by SARS-CoV-2, and offered insights regarding how to improve COVID-19 diagnosis and treatment plans.
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Wang J, Liu J, Luo M, Cui H, Zhang W, Zhao K, Dai H, Song F, Chen K, Yu Y, Zhou D, Li MJ, Yang H. Rational drug repositioning for coronavirus-associated diseases using directional mapping and side-effect inference. iScience 2022; 25:105348. [PMID: 36267550 PMCID: PMC9556799 DOI: 10.1016/j.isci.2022.105348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 09/02/2022] [Accepted: 10/11/2022] [Indexed: 02/08/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen of coronavirus disease 2019 (COVID-19), has infected hundreds of millions of people and caused millions of deaths. Looking for valid druggable targets with minimal side effects for the treatment of COVID-19 remains critical. After discovering host genes from multiscale omics data, we developed an end-to-end network method to investigate drug-host gene(s)-coronavirus (CoV) paths and the mechanism of action between the drug and the host factor in a directional network. We also inspected the potential side effect of the candidate drug on several common comorbidities. We established a catalog of host genes associated with three CoVs. Rule-based prioritization yielded 29 Food and Drug Administration (FDA)-approved drugs via accounting for the effects of drugs on CoVs, comorbidities, and drug-target confidence information. Seven drugs are currently undergoing clinical trials as COVID-19 treatment. This catalog of druggable host genes associated with CoVs and the prioritized repurposed drugs will provide a new sight in therapeutics discovery for severe COVID-19 patients.
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Affiliation(s)
- Jianhua Wang
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China,Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jiaojiao Liu
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Menghan Luo
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hui Cui
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Wenwen Zhang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Ke Zhao
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Fangfang Song
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Ying Yu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Dongming Zhou
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Corresponding author
| | - Mulin Jun Li
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China,Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Corresponding author
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Corresponding author
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Zhang Z. Genomic Biomarker Heterogeneities between SARS-CoV-2 and COVID-19. Vaccines (Basel) 2022; 10:vaccines10101657. [PMID: 36298522 PMCID: PMC9608907 DOI: 10.3390/vaccines10101657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 09/27/2022] [Accepted: 09/29/2022] [Indexed: 11/06/2022] Open
Abstract
Genes functionally associated with SARS-CoV-2 infection and genes functionally related to the COVID-19 disease can be different, whose distinction will become the first essential step for successfully fighting against the COVID-19 pandemic. Unfortunately, this first step has not been completed in all biological and medical research. Using a newly developed max-competing logistic classifier, two genes, ATP6V1B2 and IFI27, stand out to be critical in the transcriptional response to SARS-CoV-2 infection with differential expressions derived from NP/OP swab PCR. This finding is evidenced by combining these two genes with another gene in predicting disease status to achieve better-indicating accuracy than existing classifiers with the same number of genes. In addition, combining these two genes with three other genes to form a five-gene classifier outperforms existing classifiers with ten or more genes. These two genes can be critical in fighting against the COVID-19 pandemic as a new focus and direction with their exceptional predicting accuracy. Comparing the functional effects of these genes with a five-gene classifier with 100% accuracy identified and tested from blood samples in our earlier work, the genes and their transcriptional response and functional effects on SARS-CoV-2 infection, and the genes and their functional signature patterns on COVID-19 antibodies, are significantly different. We will use a total of fourteen cohort studies (including breakthrough infections and omicron variants) with 1481 samples to justify our results. Such significant findings can help explore the causal and pathological links between SARS-CoV-2 infection and the COVID-19 disease, and fight against the disease with more targeted genes, vaccines, antiviral drugs, and therapies.
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Affiliation(s)
- Zhengjun Zhang
- Department of Statistics, School of Computer, Data & Information Sciences, University of Wisconsin, Madison, WI 53706, USA
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Laurence J, Nuovo G, Racine-Brzostek SE, Seshadri M, Elhadad S, Crowson AN, Mulvey JJ, Harp J, Ahamed J, Magro C. Premortem Skin Biopsy Assessing Microthrombi, Interferon Type I Antiviral and Regulatory Proteins, and Complement Deposition Correlates with Coronavirus Disease 2019 Clinical Stage. THE AMERICAN JOURNAL OF PATHOLOGY 2022; 192:1282-1294. [PMID: 35640675 PMCID: PMC9144849 DOI: 10.1016/j.ajpath.2022.05.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/20/2022] [Accepted: 05/23/2022] [Indexed: 01/08/2023]
Abstract
Apart from autopsy, tissue correlates of coronavirus disease 2019 (COVID-19) clinical stage are lacking. In the current study, cutaneous punch biopsy specimens of 15 individuals with severe/critical COVID-19 and six with mild/moderate COVID-19 were examined. Evidence for arterial and venous microthrombi, deposition of C5b-9 and MASP2 (representative of alternative and lectin complement pathways, respectively), and differential expression of interferon type I-driven antiviral protein MxA (myxovirus resistance A) versus SIN3A, a promoter of interferon type I-based proinflammatory signaling, were assessed. Control subjects included nine patients with sepsis-related acute respiratory distress syndrome (ARDS) and/or acute kidney injury (AKI) pre-COVID-19. Microthrombi were detected in 13 (87%) of 15 patients with severe/critical COVID-19 versus zero of six patients with mild/moderate COVID-19 (P < 0.001) and none of the nine patients with pre-COVID-19 ARDS/AKI (P < 0.001). Cells lining the microvasculature staining for spike protein of severe acute respiratory syndrome coronavirus 2, the etiologic agent of COVID-19, also expressed tissue factor. C5b-9 deposition occurred in 13 (87%) of 15 patients with severe/critical COVID-19 versus zero of six patients with mild/moderate COVID-19 (P < 0.001) and none of the nine patients with pre-COVID-19 ARDS/AKI (P < 0.001). MASP2 deposition was also restricted to severe/critical COVID-19 cases. MxA expression occurred in all six mild/moderate versus two (15%) of 13 severe/critical cases (P < 0.001) of COVID-19. In contrast, SIN3A was restricted to severe/critical COVID-19 cases co-localizing with severe acute respiratory syndrome coronavirus 2 spike protein. SIN3A was also elevated in plasma of patients with severe/critical COVID-19 versus control subjects (P ≤ 0.02). In conclusion, the study identified premortem tissue correlates of COVID-19 clinical stage using skin. If validated in a longitudinal cohort, this approach could identify individuals at risk for disease progression and enable targeted interventions.
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Affiliation(s)
- Jeffrey Laurence
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, New York.
| | - Gerard Nuovo
- The Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Discovery Life Sciences, Inc., Powell, Ohio
| | | | - Madhav Seshadri
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Sonia Elhadad
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, New York
| | - A Neil Crowson
- Department of Pathology, Regional Medical Laboratories, Tulsa, Oklahoma
| | - J Justin Mulvey
- Department of Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Joanna Harp
- Department of Dermatology, Weill Cornell Medicine, New York, New York
| | - Jasimuddin Ahamed
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma
| | - Cynthia Magro
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York
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Rajagopala SV, Strickland BA, Pakala SB, Kimura KS, Shilts MH, Rosas-Salazar C, Brown HM, Freeman MH, Wessinger BC, Gupta V, Phillips E, Mallal SA, Turner JH, Das SR. Mucosal gene expression in response to SARS-CoV-2 is associated with early viral load. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.08.23.504908. [PMID: 36052371 PMCID: PMC9435401 DOI: 10.1101/2022.08.23.504908] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Little is known about the relationships between symptomatic early-time SARS-CoV-2 viral load and upper airway mucosal gene expression and immune response. To examine the association of symptomatic SARS-CoV-2 early viral load with upper airway mucosal gene expression, we profiled the host mucosal transcriptome from nasopharyngeal swab samples from 68 adults with symptomatic, mild-to-moderate COVID-19. We measured SARS-CoV-2 viral load using qRT-PCR. We then examined the association of SARS-CoV-2 viral load with upper airway mucosal immune response. We detected SARS-CoV-2 in all samples and recovered >80% of the genome from 85% of the samples from symptomatic COVID-19 adults. The respiratory virome was dominated by SARS-CoV-2, with limited co-detection of common respiratory viruses i.e., only the human Rhinovirus (HRV) being identified in 6% of the samples. We observed a significant positive correlation between SARS-CoV-2 viral load and interferon signaling (OAS2, OAS3, IFIT1, UPS18, ISG15, ISG20, IFITM1, and OASL), chemokine signaling (CXCL10 and CXCL11), and adaptive immune system (IFITM1, CD300E, and SIGLEC1) genes in symptomatic, mild-to-moderate COVID-19 adults, when adjusted for age, sex and race. Interestingly, the expression levels of most of these genes plateaued at a CT value of ~25. Overall, our data shows that early nasal mucosal immune response to SARS-CoV-2 infection is viral load dependent, which potentially could modify COVID-19 outcomes. AUTHOR SUMMARY Several prior studies have shown that SARS-CoV-2 viral load can predict the likelihood of disease spread and severity. A higher detectable SARS-CoV-2 plasma viral load was associated with worse respiratory disease severity. However, the relationship between SARS-CoV-2 viral load and airway mucosal gene expression and immune response remains elusive. We profiled the nasal mucosal transcriptome from nasal samples collected from adults infected with SARS-CoV-2 during Spring 2020 with mild-to-moderate symptoms using a comprehensive metatranscriptomics method. We observed a positive correlation between SARS-CoV-2 viral load with interferon signaling, chemokine signaling, and adaptive immune system in adults with COVID-19. Our data suggest that early nasal mucosal immune response to SARS-CoV-2 infection was viral load-dependent and may modify COVID-19 outcomes.
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Affiliation(s)
| | - Britton A. Strickland
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN,Pathology Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Suman B. Pakala
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Kyle S. Kimura
- Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN
| | - Meghan H. Shilts
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | | | - Hunter M. Brown
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Michael H. Freeman
- Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN
| | | | - Veerain Gupta
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
| | - Elizabeth Phillips
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Simon A. Mallal
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Justin H. Turner
- Pathology Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Suman R. Das
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN,Pathology Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA,Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN
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Maleknia S, Tavassolifar MJ, Mottaghitalab F, Zali MR, Meyfour A. Identifying novel host-based diagnostic biomarker panels for COVID-19: a whole-blood/nasopharyngeal transcriptome meta-analysis. Mol Med 2022; 28:86. [PMID: 35922752 PMCID: PMC9347150 DOI: 10.1186/s10020-022-00513-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/27/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Regardless of improvements in controlling the COVID-19 pandemic, the lack of comprehensive insight into SARS-COV-2 pathogenesis is still a sophisticated challenge. In order to deal with this challenge, we utilized advanced bioinformatics and machine learning algorithms to reveal more characteristics of SARS-COV-2 pathogenesis and introduce novel host response-based diagnostic biomarker panels. METHODS In the present study, eight published RNA-Seq datasets related to whole-blood (WB) and nasopharyngeal (NP) swab samples of patients with COVID-19, other viral and non-viral acute respiratory illnesses (ARIs), and healthy controls (HCs) were integrated. To define COVID-19 meta-signatures, Gene Ontology and pathway enrichment analyses were applied to compare COVID-19 with other similar diseases. Additionally, CIBERSORTx was executed in WB samples to detect the immune cell landscape. Furthermore, the optimum WB- and NP-based diagnostic biomarkers were identified via all the combinations of 3 to 9 selected features and the 2-phases machine learning (ML) method which implemented k-fold cross validation and independent test set validation. RESULTS The host gene meta-signatures obtained for SARS-COV-2 infection were different in the WB and NP samples. The gene ontology and enrichment results of the WB dataset represented the enhancement in inflammatory host response, cell cycle, and interferon signature in COVID-19 patients. Furthermore, NP samples of COVID-19 in comparison with HC and non-viral ARIs showed the significant upregulation of genes associated with cytokine production and defense response to the virus. In contrast, these pathways in COVID-19 compared to other viral ARIs were strikingly attenuated. Notably, immune cell proportions of WB samples altered in COVID-19 versus HC. Moreover, the optimum WB- and NP-based diagnostic panels after two phases of ML-based validation included 6 and 8 markers with an accuracy of 97% and 88%, respectively. CONCLUSIONS Based on the distinct gene expression profiles of WB and NP, our results indicated that SARS-COV-2 function is body-site-specific, although according to the common signature in WB and NP COVID-19 samples versus controls, this virus also induces a global and systematic host response to some extent. We also introduced and validated WB- and NP-based diagnostic biomarkers using ML methods which can be applied as a complementary tool to diagnose the COVID-19 infection from non-COVID cases.
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Affiliation(s)
- Samaneh Maleknia
- Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Javad Tavassolifar
- Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Faezeh Mottaghitalab
- Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Zali
- Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Anna Meyfour
- Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Iqbal N, Kumar P. Integrated COVID-19 Predictor: Differential expression analysis to reveal potential biomarkers and prediction of coronavirus using RNA-Seq profile data. Comput Biol Med 2022; 147:105684. [PMID: 35687925 PMCID: PMC9162937 DOI: 10.1016/j.compbiomed.2022.105684] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 05/27/2022] [Accepted: 05/30/2022] [Indexed: 02/01/2023]
Abstract
Background The world has been battling the continuous COVID-19 pandemic spread by the SARS-CoV-2 virus for last two years. The issue of viral disease prediction is constantly a matter of interest in virology and the study of disease transmission over the long years. Objective In this study, we aimed to implement genome association studies using RNA-Seq of COVID-19 and reveal highly expressed gene biomarkers and prediction based on the machine learning model of COVID-19 analysis to combat this pandemic. Method We collected RNA-Seq gene count data for both healthy (Control) and non-healthy (Treated) COVID-19 cases. In this experiment, a sequence of bioinformatics strategies and statistical techniques, such as fold-change and adjusted p-value, were processed to identify differentially expressed genes (DEGs). We filtered biomarker sets of high DEGs, moderate DEGs, and low DEGs using DESeq2, Limma Trend, and Limma Voom methods based on intersection and union operations and applied machine learning techniques to predict COVID-19. Result Through experimental analysis, 67 potential biomarkers were extracted, comprising 49 up-regulated and 18 down-regulated genes, using statistical techniques and a set-theory consensus strategy. We trained the machine learning models on 12 different biomarker sets and found that the SVM model performed better than the other classifiers with 99.07% classification accuracy for moderate DEGs. Conclusion Our study revealed that identified differentially expressed genes of the moderate DEGs biomarker set, |log2FC| ≥ 2 with adjusted p-value < 0.05, work significantly as input features to implement a machine learning model using a kernel-based SVM technique to predict COVID-19.
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Tveita A, Murphy SL, Holter JC, Kildal AB, Michelsen AE, Lerum TV, Kaarbø M, Heggelund L, Holten AR, Finbråten AK, Müller KE, Mathiessen A, Bøe S, Fevang B, Granerud BK, Tonby K, Lind A, Dudman SG, Henriksen KN, Müller F, Skjønsberg OH, Trøseid M, Barratt-Due A, Dyrhol-Riise AM, Aukrust P, Halvorsen B, Dahl TB, Ueland T. High Circulating Levels of the Homeostatic Chemokines CCL19 and CCL21 Predict Mortality and Disease Severity in COVID-19. J Infect Dis 2022; 226:2150-2160. [PMID: 35876699 PMCID: PMC9384496 DOI: 10.1093/infdis/jiac313] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 07/12/2022] [Accepted: 07/28/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Immune dysregulation is a major factor in the development of severe coronavirus disease 2019 (COVID-19). The homeostatic chemokines CCL19 and CCL21 have been implicated as mediators of tissue inflammation, but data on their regulation in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is limited. We thus investigated the levels of these chemokines in COVID-19 patients. METHODS Serial blood samples were obtained from patients hospitalized with COVID-19 (n = 414). Circulating CCL19 and CCL21 levels during hospitalization and 3-month follow-up were analyzed. In vitro assays and analysis of RNAseq data from public repositories were performed to further explore possible regulatory mechanisms. RESULTS A consistent increase in circulating levels of CCL19 and CCL21 was observed, with high levels correlating with disease severity measures, including respiratory failure, need for intensive care, and 60-day all-cause mortality. High levels of CCL21 at admission were associated with persisting impairment of pulmonary function at the 3-month follow-up. CONCLUSIONS Our findings highlight CCL19 and CCL21 as markers of immune dysregulation in COVID-19. This may reflect aberrant regulation triggered by tissue inflammation, as observed in other chronic inflammatory and autoimmune conditions. Determination of the source and regulation of these chemokines and their effects on lung tissue is warranted to further clarify their role in COVID-19. CLINICAL TRIALS REGISTRATION NCT04321616 and NCT04381819.
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Affiliation(s)
- Anders Tveita
- Correspondence: Anders Tveita, MD, PhD, Department of Internal Medicine, Bærum Hospital, Vestre Viken Hospital Trust, 1346 Gjettum, Norway ()
| | | | | | - Anders Benjamin Kildal
- Department of Anesthesiology and Intensive Care, University Hospital of North Norway, Tromsø, Norway
| | - Annika E Michelsen
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Tøri Vigeland Lerum
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Pulmonary Medicine, Oslo University Hospital Ullevål, Oslo, Norway
| | - Mari Kaarbø
- Department of Microbiology, Oslo University Hospital, Oslo, Norway
| | - Lars Heggelund
- Department of Internal Medicine, Drammen Hospital, Vestre Viken Hospital Trust, Drammen, Norway,Department of Clinical Science, Faculty of Medicine, University of Bergen, Bergen, Norway
| | - Aleksander Rygh Holten
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Acute Medicine, Oslo University Hospital, Oslo, Norway
| | | | - Karl Erik Müller
- Department of Internal Medicine, Drammen Hospital, Vestre Viken Hospital Trust, Drammen, Norway
| | | | - Simen Bøe
- Department of Anesthesiology and Intensive Care, Hammerfest County Hospital, Hammerfest, Norway
| | - Børre Fevang
- Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway,Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Beathe Kiland Granerud
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Microbiology, Oslo University Hospital, Oslo, Norway
| | - Kristian Tonby
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Infectious Diseases, Oslo University Hospital Ullevål, Oslo, Norway
| | - Andreas Lind
- Department of Microbiology, Oslo University Hospital, Oslo, Norway
| | - Susanne Gjeruldsen Dudman
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Microbiology, Oslo University Hospital, Oslo, Norway
| | - Katerina Nezvalova Henriksen
- Department of Hematology, Oslo University Hospital, Oslo, Norway,Hospital Pharmacies, South-Eastern Norway Enterprise, Oslo, Norway
| | - Fredrik Müller
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Microbiology, Oslo University Hospital, Oslo, Norway
| | - Ole Henning Skjønsberg
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Pulmonary Medicine, Oslo University Hospital Ullevål, Oslo, Norway
| | - Marius Trøseid
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway,Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Andreas Barratt-Due
- Division of Laboratory Medicine, Department of Immunology, Oslo University Hospital, Oslo, Norway,Department of Anesthesia and Intensive Care Medicine, Oslo University Hospital, Oslo, Norway
| | - Anne Ma Dyrhol-Riise
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Infectious Diseases, Oslo University Hospital Ullevål, Oslo, Norway
| | - Pål Aukrust
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway,Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Bente Halvorsen
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway
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Gao K, Wang R, Chen J, Cheng L, Frishcosy J, Huzumi Y, Qiu Y, Schluckbier T, Wei X, Wei GW. Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2. Chem Rev 2022; 122:11287-11368. [PMID: 35594413 PMCID: PMC9159519 DOI: 10.1021/acs.chemrev.1c00965] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.
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Affiliation(s)
- Kaifu Gao
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Rui Wang
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jiahui Chen
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Limei Cheng
- Clinical
Pharmacology and Pharmacometrics, Bristol
Myers Squibb, Princeton, New Jersey 08536, United States
| | - Jaclyn Frishcosy
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuta Huzumi
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuchi Qiu
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Tom Schluckbier
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Xiaoqi Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Guo-Wei Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biochemistry and Molecular Biology, Michigan
State University, East Lansing, Michigan 48824, United States
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Gómez-Carballa A, Rivero-Calle I, Pardo-Seco J, Gómez-Rial J, Rivero-Velasco C, Rodríguez-Núñez N, Barbeito-Castiñeiras G, Pérez-Freixo H, Cebey-López M, Barral-Arca R, Rodriguez-Tenreiro C, Dacosta-Urbieta A, Bello X, Pischedda S, Currás-Tuala MJ, Viz-Lasheras S, Martinón-Torres F, Salas A. A multi-tissue study of immune gene expression profiling highlights the key role of the nasal epithelium in COVID-19 severity. ENVIRONMENTAL RESEARCH 2022; 210:112890. [PMID: 35202626 PMCID: PMC8861187 DOI: 10.1016/j.envres.2022.112890] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/11/2022] [Accepted: 02/02/2022] [Indexed: 05/08/2023]
Abstract
Coronavirus Disease-19 (COVID-19) symptoms range from mild to severe illness; the cause for this differential response to infection remains unknown. Unravelling the immune mechanisms acting at different levels of the colonization process might be key to understand these differences. We carried out a multi-tissue (nasal, buccal and blood; n = 156) gene expression analysis of immune-related genes from patients affected by different COVID-19 severities, and healthy controls through the nCounter technology. Mild and asymptomatic cases showed a powerful innate antiviral response in nasal epithelium, characterized by activation of interferon (IFN) pathway and downstream cascades, successfully controlling the infection at local level. In contrast, weak macrophage/monocyte driven innate antiviral response and lack of IFN signalling activity were present in severe cases. Consequently, oral mucosa from severe patients showed signals of viral activity, cell arresting and viral dissemination to the lower respiratory tract, which ultimately could explain the exacerbated innate immune response and impaired adaptative immune responses observed at systemic level. Results from saliva transcriptome suggest that the buccal cavity might play a key role in SARS-CoV-2 infection and dissemination in patients with worse prognosis. Co-expression network analysis adds further support to these findings, by detecting modules specifically correlated with severity involved in the abovementioned biological routes; this analysis also provides new candidate genes that might be tested as biomarkers in future studies. We also found tissue specific severity-related signatures mainly represented by genes involved in the innate immune system and cytokine/chemokine signalling. Local immune response could be key to determine the course of the systemic response and thus COVID-19 severity. Our findings provide a framework to investigate severity host gene biomarkers and pathways that might be relevant to diagnosis, prognosis, and therapy.
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Affiliation(s)
- Alberto Gómez-Carballa
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Irene Rivero-Calle
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Jacobo Pardo-Seco
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - José Gómez-Rial
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Laboratorio de Inmunología. Servicio de Análisis Clínicos. Hospital Clínico Universitario (SERGAS), Galicia, Spain
| | - Carmen Rivero-Velasco
- Intensive Medicine Department, Hospital Clìnico Universitario de Santiago de Compostela, Galicia, Spain
| | - Nuria Rodríguez-Núñez
- Pneumology Department, Hospital Clìnico Universitario de Santiago de Compostela, Galicia, Spain
| | - Gema Barbeito-Castiñeiras
- Clinical Microbiology Unit, Complexo Hospitalario Universitario de Santiago Santiago de Compostela, Spain; Instituto de Investigación Sanitaria de Santiago, Santiago de Compostela, Spain
| | - Hugo Pérez-Freixo
- Preventive Medicine Department, Hospital Clínico Universitario de Santiago de Compostela, Spain
| | - Miriam Cebey-López
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Ruth Barral-Arca
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Carmen Rodriguez-Tenreiro
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Ana Dacosta-Urbieta
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Xabier Bello
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Sara Pischedda
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - María José Currás-Tuala
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Sandra Viz-Lasheras
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Federico Martinón-Torres
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Antonio Salas
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain.
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44
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Agrawal P, Sambaturu N, Olgun G, Hannenhalli S. A Path-Based Analysis of Infected Cell Line and COVID-19 Patient Transcriptome Reveals Novel Potential Targets and Drugs Against SARS-CoV-2. Front Immunol 2022; 13:918817. [PMID: 35844595 PMCID: PMC9284228 DOI: 10.3389/fimmu.2022.918817] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 06/07/2022] [Indexed: 11/13/2022] Open
Abstract
Most transcriptomic studies of SARS-CoV-2 infection have focused on differentially expressed genes, which do not necessarily reveal the genes mediating the transcriptomic changes. In contrast, exploiting curated biological network, our PathExt tool identifies central genes from the differentially active paths mediating global transcriptomic response. Here we apply PathExt to multiple cell line infection models of SARS-CoV-2 and other viruses, as well as to COVID-19 patient-derived PBMCs. The central genes mediating SARS-CoV-2 response in cell lines were uniquely enriched for ATP metabolic process, G1/S transition, leukocyte activation and migration. In contrast, PBMC response reveals dysregulated cell-cycle processes. In PBMC, the most frequently central genes are associated with COVID-19 severity. Importantly, relative to differential genes, PathExt-identified genes show greater concordance with several benchmark anti-COVID-19 target gene sets. We propose six novel anti-SARS-CoV-2 targets ADCY2, ADSL, OCRL, TIAM1, PBK, and BUB1, and potential drugs targeting these genes, such as Bemcentinib, Phthalocyanine, and Conivaptan.
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Affiliation(s)
- Piyush Agrawal
- Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Narmada Sambaturu
- IISc Mathematics Initiative, Indian Institute of Science, Bangalore, India
| | - Gulden Olgun
- Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Sridhar Hannenhalli
- Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
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45
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Ward B, Yombi JC, Balligand JL, Cani PD, Collet JF, de Greef J, Dewulf JP, Gatto L, Haufroid V, Jodogne S, Kabamba B, Pyr dit Ruys S, Vertommen D, Elens L, Belkhir L. HYGIEIA: HYpothesizing the Genesis of Infectious Diseases and Epidemics through an Integrated Systems Biology Approach. Viruses 2022; 14:v14071373. [PMID: 35891354 PMCID: PMC9318602 DOI: 10.3390/v14071373] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/13/2022] [Accepted: 06/21/2022] [Indexed: 12/13/2022] Open
Abstract
More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care.
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Affiliation(s)
- Bradley Ward
- Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics Group (PMGK), Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (B.W.); (S.P.d.R.)
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
| | - Jean Cyr Yombi
- Department of Internal Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Jean-Luc Balligand
- WELBIO (Walloon Excellence in Life Sciences and Biotechnology), Pole of Pharmacology and Therapeutics (FATH), Institut de Recherche Experimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Patrice D. Cani
- WELBIO (Walloon Excellence in Life Sciences and Biotechnology), Metabolism and Nutrition Research Group, Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Jean-François Collet
- WELBIO (Walloon Excellence in Life Sciences and Biotechnology), de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Julien de Greef
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Department of Internal Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Joseph P. Dewulf
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Department of Laboratory Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
- Department of Biochemistry, de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium
| | - Laurent Gatto
- Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Vincent Haufroid
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Department of Laboratory Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Sébastien Jodogne
- Computer Science and Engineering Department (INGI), Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), UCLouvain, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium;
| | - Benoît Kabamba
- Department of Laboratory Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
- Pôle de Microbiologie, Institut de Recherche Expérimentale et Clinique, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium
| | - Sébastien Pyr dit Ruys
- Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics Group (PMGK), Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (B.W.); (S.P.d.R.)
| | - Didier Vertommen
- De Duve Institute, and MASSPROT Platform, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Laure Elens
- Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics Group (PMGK), Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (B.W.); (S.P.d.R.)
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Correspondence: (L.E.); (L.B.)
| | - Leïla Belkhir
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Department of Internal Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
- Correspondence: (L.E.); (L.B.)
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Schimke LF, Marques AHC, Baiocchi GC, de Souza Prado CA, Fonseca DLM, Freire PP, Rodrigues Plaça D, Salerno Filgueiras I, Coelho Salgado R, Jansen-Marques G, Rocha Oliveira AE, Peron JPS, Cabral-Miranda G, Barbuto JAM, Camara NOS, Calich VLG, Ochs HD, Condino-Neto A, Overmyer KA, Coon JJ, Balnis J, Jaitovich A, Schulte-Schrepping J, Ulas T, Schultze JL, Nakaya HI, Jurisica I, Cabral-Marques O. Severe COVID-19 Shares a Common Neutrophil Activation Signature with Other Acute Inflammatory States. Cells 2022; 11:cells11050847. [PMID: 35269470 PMCID: PMC8909161 DOI: 10.3390/cells11050847] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 02/24/2022] [Accepted: 02/25/2022] [Indexed: 02/06/2023] Open
Abstract
Severe COVID-19 patients present a clinical and laboratory overlap with other hyperinflammatory conditions such as hemophagocytic lymphohistiocytosis (HLH). However, the underlying mechanisms of these conditions remain to be explored. Here, we investigated the transcriptome of 1596 individuals, including patients with COVID-19 in comparison to healthy controls, other acute inflammatory states (HLH, multisystem inflammatory syndrome in children [MIS-C], Kawasaki disease [KD]), and different respiratory infections (seasonal coronavirus, influenza, bacterial pneumonia). We observed that COVID-19 and HLH share immunological pathways (cytokine/chemokine signaling and neutrophil-mediated immune responses), including gene signatures that stratify COVID-19 patients admitted to the intensive care unit (ICU) and COVID-19_nonICU patients. Of note, among the common differentially expressed genes (DEG), there is a cluster of neutrophil-associated genes that reflects a generalized hyperinflammatory state since it is also dysregulated in patients with KD and bacterial pneumonia. These genes are dysregulated at the protein level across several COVID-19 studies and form an interconnected network with differentially expressed plasma proteins that point to neutrophil hyperactivation in COVID-19 patients admitted to the intensive care unit. scRNAseq analysis indicated that these genes are specifically upregulated across different leukocyte populations, including lymphocyte subsets and immature neutrophils. Artificial intelligence modeling confirmed the strong association of these genes with COVID-19 severity. Thus, our work indicates putative therapeutic pathways for intervention.
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Affiliation(s)
- Lena F. Schimke
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
- Correspondence: (L.F.S.); (O.C.-M.); Tel.: +55-11-943661555 (L.F.S.); +55-11-974642022 (O.C.-M.)
| | - Alexandre H. C. Marques
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Gabriela Crispim Baiocchi
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Caroline Aliane de Souza Prado
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (C.A.d.S.P.); (D.L.M.F.); (D.R.P.); (A.E.R.O.); (H.I.N.)
| | - Dennyson Leandro M. Fonseca
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (C.A.d.S.P.); (D.L.M.F.); (D.R.P.); (A.E.R.O.); (H.I.N.)
| | - Paula Paccielli Freire
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Desirée Rodrigues Plaça
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (C.A.d.S.P.); (D.L.M.F.); (D.R.P.); (A.E.R.O.); (H.I.N.)
| | - Igor Salerno Filgueiras
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Ranieri Coelho Salgado
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Gabriel Jansen-Marques
- Information Systems, School of Arts, Sciences and Humanities, University of Sao Paulo, São Paulo 03828-000, Brazil;
| | - Antonio Edson Rocha Oliveira
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (C.A.d.S.P.); (D.L.M.F.); (D.R.P.); (A.E.R.O.); (H.I.N.)
| | - Jean Pierre Schatzmann Peron
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Gustavo Cabral-Miranda
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - José Alexandre Marzagão Barbuto
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
- Laboratory of Medical Investigation in Pathogenesis, Targeted Therapy in Onco-Immuno-Hematology (LIM-31), Department of Hematology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo 05403-000, Brazil
| | - Niels Olsen Saraiva Camara
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Vera Lúcia Garcia Calich
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Hans D. Ochs
- Department of Pediatrics, Seattle Children’s Research Institute, University of Washington School of Medicine, Seattle, WA 98101, USA;
| | - Antonio Condino-Neto
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
| | - Katherine A. Overmyer
- National Center for Quantitative Biology of Complex Systems, Madison, WI 53562, USA; (K.A.O.); (J.J.C.)
- Morgridge Institute for Research, Madison, WI 53562, USA
| | - Joshua J. Coon
- National Center for Quantitative Biology of Complex Systems, Madison, WI 53562, USA; (K.A.O.); (J.J.C.)
- Morgridge Institute for Research, Madison, WI 53562, USA
- Department of Biomolecular Chemistry, University of Wisconsin, Madison, WI 53506, USA
- Department of Chemistry, University of Wisconsin, Madison, WI 53506, USA
| | - Joseph Balnis
- Division of Pulmonary and Critical Care Medicine, Albany Medical Center, Albany, NY 12208, USA; (J.B.); (A.J.)
- Department of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA
| | - Ariel Jaitovich
- Division of Pulmonary and Critical Care Medicine, Albany Medical Center, Albany, NY 12208, USA; (J.B.); (A.J.)
- Department of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA
| | - Jonas Schulte-Schrepping
- Life and Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; (J.S.-S.); (J.L.S.)
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), University of Bonn, 53127 Bonn, Germany;
| | - Thomas Ulas
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), University of Bonn, 53127 Bonn, Germany;
- German Center for Neurodegenerative Diseases (DZNE), PRECISE Platform for Genomics and Epigenomics at DZNE, University of Bonn, 53127 Bonn, Germany
| | - Joachim L. Schultze
- Life and Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; (J.S.-S.); (J.L.S.)
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), University of Bonn, 53127 Bonn, Germany;
- German Center for Neurodegenerative Diseases (DZNE), PRECISE Platform for Genomics and Epigenomics at DZNE, University of Bonn, 53127 Bonn, Germany
| | - Helder I. Nakaya
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (C.A.d.S.P.); (D.L.M.F.); (D.R.P.); (A.E.R.O.); (H.I.N.)
- Hospital Israelita Albert Einstein, São Paulo 05652-900, Brazil
- Scientific Platform Pasteur, University of São Paulo, São Paulo 05508-020, Brazil
| | - Igor Jurisica
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada;
- Departments of Medical Biophysics and Computer Science, Faculty of Dentistry, University of Toronto, Toronto, ON M5G 1L7, Canada
- Institute of Neuroimmunology, Slovak Academy of Sciences, 845 10 Bratislava, Slovakia
| | - Otávio Cabral-Marques
- Department of Imunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (A.H.C.M.); (G.C.B.); (P.P.F.); (I.S.F.); (R.C.S.); (J.P.S.P.); (G.C.-M.); (J.A.M.B.); (N.O.S.C.); (V.L.G.C.); (A.C.-N.)
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo 05508-000, Brazil; (C.A.d.S.P.); (D.L.M.F.); (D.R.P.); (A.E.R.O.); (H.I.N.)
- Network of Immunity in Infection, Malignancy, Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), São Paulo 05508-000, Brazil
- Correspondence: (L.F.S.); (O.C.-M.); Tel.: +55-11-943661555 (L.F.S.); +55-11-974642022 (O.C.-M.)
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Hasin-Brumshtein Y, Sakaram S, Khatri P, He YD, Sweeney TE. A robust gene expression signature for NASH in liver expression data. Sci Rep 2022; 12:2571. [PMID: 35173224 PMCID: PMC8850484 DOI: 10.1038/s41598-022-06512-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 01/31/2022] [Indexed: 02/06/2023] Open
Abstract
Non-Alcoholic Fatty Liver Disease (NAFLD) is a progressive liver disease that affects up to 30% of worldwide population, of which up to 25% progress to Non-Alcoholic SteatoHepatitis (NASH), a severe form of the disease that involves inflammation and predisposes the patient to liver cirrhosis. Despite its epidemic proportions, there is no reliable diagnostics that generalizes to global patient population for distinguishing NASH from NAFLD. We performed a comprehensive multicohort analysis of publicly available transcriptome data of liver biopsies from Healthy Controls (HC), NAFLD and NASH patients. Altogether we analyzed 812 samples from 12 different datasets across 7 countries, encompassing real world patient heterogeneity. We used 7 datasets for discovery and 5 datasets were held-out for independent validation. Altogether we identified 130 genes significantly differentially expressed in NASH versus a mixed group of NAFLD and HC. We show that our signature is not driven by one particular group (NAFLD or HC) and reflects true biological signal. Using a forward search we were able to downselect to a parsimonious set of 19 mRNA signature with mean AUROC of 0.98 in discovery and 0.79 in independent validation. Methods for consistent diagnosis of NASH relative to NAFLD are urgently needed. We showed that gene expression data combined with advanced statistical methodology holds the potential to serve basis for development of such diagnostic tests for the unmet clinical need.
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Affiliation(s)
| | - Suraj Sakaram
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA
| | - Purvesh Khatri
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Palo Alto, CA, 94305, USA.,Department of Medicine, Center for Biomedical Informatics Research, Stanford University, Stanford, CA, 94305, USA
| | - Yudong D He
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA.
| | - Timothy E Sweeney
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA.
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Alqutami F, Senok A, Hachim M. COVID-19 Transcriptomic Atlas: A Comprehensive Analysis of COVID-19 Related Transcriptomics Datasets. Front Genet 2022; 12:755222. [PMID: 35003208 PMCID: PMC8727884 DOI: 10.3389/fgene.2021.755222] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 11/17/2021] [Indexed: 01/08/2023] Open
Abstract
Background: To develop anti-viral drugs and vaccines, it is crucial to understand the molecular basis and pathology of COVID-19. An increase in research output is required to generate data and results at a faster rate, therefore bioinformatics plays a crucial role in COVID-19 research. There is an abundance of transcriptomic data from studies carried out on COVID-19, however, their use is limited by the confounding factors pertaining to each study. The reanalysis of all these datasets in a unified approach should help in understanding the molecular basis of COVID-19. This should allow for the identification of COVID-19 biomarkers expressed in patients and the presence of markers specific to disease severity and condition. Aim: In this study, we aim to use the multiple publicly available transcriptomic datasets retrieved from the Gene Expression Omnibus (GEO) database to identify consistently differential expressed genes in different tissues and clinical settings. Materials and Methods: A list of datasets was generated from NCBI’s GEO using the GEOmetadb package through R software. Search keywords included SARS-COV-2 and COVID-19. Datasets in human tissues containing more than ten samples were selected for this study. Differentially expressed genes (DEGs) in each dataset were identified. Then the common DEGs between different datasets, conditions, tissues and clinical settings were shortlisted. Results: Using a unified approach, we were able to identify common DEGs based on the disease conditions, samples source and clinical settings. For each indication, a different set of genes have been identified, revealing that a multitude of factors play a role in the level of gene expression. Conclusion: Unified reanalysis of publically available transcriptomic data showed promising potential in identifying core targets that can explain the molecular pathology and be used as biomarkers for COVID-19.
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Affiliation(s)
- Fatma Alqutami
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | - Abiola Senok
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | - Mahmood Hachim
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.,Center for Genomic Discovery, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
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Immunothrombosis Biomarkers for Distinguishing Coronavirus Disease 2019 Patients From Noncoronavirus Disease Septic Patients With Pneumonia and for Predicting ICU Mortality. Crit Care Explor 2022; 3:e0588. [PMID: 34984340 PMCID: PMC8718216 DOI: 10.1097/cce.0000000000000588] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Supplemental Digital Content is available in the text. IMPORTANCE: Coronavirus disease 2019 patients have an increased risk of thrombotic complications that may reflect immunothrombosis, a process characterized by blood clotting, endothelial dysfunction, and the release of neutrophil extracellular traps. To date, few studies have investigated longitudinal changes in immunothrombosis biomarkers in these patients. Furthermore, how these longitudinal changes differ between coronavirus disease 2019 patients and noncoronavirus disease septic patients with pneumonia are unknown. OBJECTIVES: In this pilot observational study, we investigated the utility of immunothrombosis biomarkers for distinguishing between coronavirus disease 2019 patients and noncoronavirus disease septic patients with pneumonia. We also evaluated the utility of the biomarkers for predicting ICU mortality in these patients. DESIGN, SETTING, AND PARTICIPANTS: The participants were ICU patients with coronavirus disease 2019 (n = 14), noncoronavirus disease septic patients with pneumonia (n = 19), and healthy age-matched controls (n = 14). MAIN OUTCOMES AND MEASURES: Nine biomarkers were measured from plasma samples (on days 1, 2, 4, 7, 10, and/or 14). Analysis was based on binomial logit models and receiver operating characteristic analyses. RESULTS: Cell-free DNA, d-dimer, soluble endothelial protein C receptor, protein C, soluble thrombomodulin, fibrinogen, citrullinated histones, and thrombin-antithrombin complexes have significant powers for distinguishing coronavirus disease 2019 patients from healthy individuals. In comparison, fibrinogen, soluble endothelial protein C receptor, antithrombin, and cell-free DNA have significant powers for distinguishing coronavirus disease 2019 from pneumonia patients. The predictors of ICU mortality differ between the two patient groups: soluble thrombomodulin and citrullinated histones for coronavirus disease 2019 patients, and protein C and cell-free DNA or fibrinogen for pneumonia patients. In both patient groups, the most recent biomarker values have stronger prognostic value than their ICU day 1 values. CONCLUSIONS AND RELEVANCE: Fibrinogen, soluble endothelial protein C receptor, antithrombin, and cell-free DNA have utility for distinguishing coronavirus disease 2019 patients from noncoronavirus disease septic patients with pneumonia. The most important predictors of ICU mortality are soluble thrombomodulin/citrullinated histones for coronavirus disease 2019 patients, and protein C/cell-free DNA for noncoronavirus disease pneumonia patients. This hypothesis-generating study suggests that the pathophysiology of immunothrombosis differs between the two patient groups.
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Genome-wide bidirectional CRISPR screens identify mucins as host factors modulating SARS-CoV-2 infection. Nat Genet 2022; 54:1078-1089. [PMID: 35879412 PMCID: PMC9355872 DOI: 10.1038/s41588-022-01131-x] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 06/10/2022] [Indexed: 01/08/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a range of symptoms in infected individuals, from mild respiratory illness to acute respiratory distress syndrome. A systematic understanding of host factors influencing viral infection is critical to elucidate SARS-CoV-2-host interactions and the progression of Coronavirus disease 2019 (COVID-19). Here, we conducted genome-wide CRISPR knockout and activation screens in human lung epithelial cells with endogenous expression of the SARS-CoV-2 entry factors ACE2 and TMPRSS2. We uncovered proviral and antiviral factors across highly interconnected host pathways, including clathrin transport, inflammatory signaling, cell-cycle regulation, and transcriptional and epigenetic regulation. We further identified mucins, a family of high molecular weight glycoproteins, as a prominent viral restriction network that inhibits SARS-CoV-2 infection in vitro and in murine models. These mucins also inhibit infection of diverse respiratory viruses. This functional landscape of SARS-CoV-2 host factors provides a physiologically relevant starting point for new host-directed therapeutics and highlights airway mucins as a host defense mechanism.
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