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      NOX5-induced uncoupling of endothelial NO synthase is a causal mechanism and theragnostic target of an age-related hypertension endotype

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          Abstract

          Hypertension is the most important cause of death and disability in the elderly. In 9 out of 10 cases, the molecular cause, however, is unknown. One mechanistic hypothesis involves impaired endothelium-dependent vasodilation through reactive oxygen species (ROS) formation. Indeed, ROS forming NADPH oxidase ( Nox) genes associate with hypertension, yet target validation has been negative. We re-investigate this association by molecular network analysis and identify NOX5, not present in rodents, as a sole neighbor to human vasodilatory endothelial nitric oxide (NO) signaling. In hypertensive patients, endothelial microparticles indeed contained higher levels of NOX5—but not NOX1, NOX2, or NOX4—with a bimodal distribution correlating with disease severity. Mechanistically, mice expressing human Nox5 in endothelial cells developed—upon aging—severe systolic hypertension and impaired endothelium-dependent vasodilation due to uncoupled NO synthase (NOS). We conclude that NOX5-induced uncoupling of endothelial NOS is a causal mechanism and theragnostic target of an age-related hypertension endotype. Nox5 knock-in (KI) mice represent the first mechanism-based animal model of hypertension.

          Abstract

          The causes of hypertension are not understood; treatments are symptomatic and prevent only few of the associated risks. This study applies network medicine to identify a subgroup of patients with NADPH oxidase 5-induced uncoupling of nitric oxide synthase as the cause of age-related hypertension, enabling a first-in-class mechanism-based treatment of hypertension.

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          The obligatory role of endothelial cells in the relaxation of arterial smooth muscle by acetylcholine.

          Despite its very potent vasodilating action in vivo, acetylcholine (ACh) does not always produce relaxation of isolated preparations of blood vessels in vitro. For example, in the helical strip of the rabbit descending thoracic aorta, the only reported response to ACh has been graded contractions, occurring at concentrations above 0.1 muM and mediated by muscarinic receptors. Recently, we observed that in a ring preparation from the rabbit thoracic aorta, ACh produced marked relaxation at concentrations lower than those required to produce contraction (confirming an earlier report by Jelliffe). In investigating this apparent discrepancy, we discovered that the loss of relaxation of ACh in the case of the strip was the result of unintentional rubbing of its intimal surface against foreign surfaces during its preparation. If care was taken to avoid rubbing of the intimal surface during preparation, the tissue, whether ring, transverse strip or helical strip, always exhibited relaxation to ACh, and the possibility was considered that rubbing of the intimal surface had removed endothelial cells. We demonstrate here that relaxation of isolated preparations of rabbit thoracic aorta and other blood vessels by ACh requires the presence of endothelial cells, and that ACh, acting on muscarinic receptors of these cells, stimulates release of a substance(s) that causes relaxation of the vascular smooth muscle. We propose that this may be one of the principal mechanisms for ACh-induced vasodilation in vivo. Preliminary reports on some aspects of the work have been reported elsewhere.
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            Network medicine: a network-based approach to human disease.

            Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.
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              Architecture of the human interactome defines protein communities and disease networks

              The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidation of how genome variation contributes to disease 1–3 . Here, we present BioPlex 2.0 (Biophysical Interactions of ORFEOME-derived complexes), which employs robust affinity purification-mass spectrometry (AP-MS) methodology 4 to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein coding genes from the human genome, and constitutes the largest such network to date. With >56,000 candidate interactions, BioPlex 2.0 contains >29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering (MCL) 5 of interacting proteins identified more than 1300 protein communities representing diverse cellular activities. Genes essential for cell fitness 6,7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Software
                Role: Formal analysisRole: MethodologyRole: Software
                Role: ConceptualizationRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: MethodologyRole: SoftwareRole: Visualization
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: ResourcesRole: Validation
                Role: Formal analysisRole: MethodologyRole: ResourcesRole: Validation
                Role: MethodologyRole: Resources
                Role: MethodologyRole: Resources
                Role: Formal analysisRole: Methodology
                Role: InvestigationRole: Software
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                10 November 2020
                November 2020
                10 November 2020
                : 18
                : 11
                : e3000885
                Affiliations
                [1 ] Department of Pharmacology and Personalised Medicine, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands
                [2 ] Department of Pharmacology and Toxicology, School of Pharmacy, Zagazig University, Zagazig, Egypt
                [3 ] Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
                [4 ] School of Computing, Newcastle University, Newcastle, United Kingdom
                [5 ] Research Programme on Biomedical Informatics, The Hospital del Mar Medical Research Institute and Pompeu Fabra University, Barcelona, Spain
                [6 ] Division of Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Brunswick, Germany
                [7 ] Central Animal Facility, CPV, Maastricht University, Maastricht, the Netherlands
                [8 ] Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan
                [9 ] Department of Critical Care Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
                [10 ] Division of Cardiology and Cardiovascular Research Center, Taipei Medical University Hospital, Taipei, Taiwan
                [11 ] Taipei Heart Institute, Division of Cardiology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
                [12 ] Department of Pharmacology and Toxicology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
                [13 ] Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
                University of Pittsburgh, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-2437-1773
                https://orcid.org/0000-0002-8701-2295
                https://orcid.org/0000-0002-3466-6535
                https://orcid.org/0000-0001-7535-0417
                https://orcid.org/0000-0002-5393-2413
                https://orcid.org/0000-0002-9725-2794
                https://orcid.org/0000-0002-4963-7219
                https://orcid.org/0000-0001-7310-4191
                https://orcid.org/0000-0003-0419-5549
                Article
                PBIOLOGY-D-20-00252
                10.1371/journal.pbio.3000885
                7654809
                33170835
                49efec6e-03c6-4387-8096-5a6e65c3f4f5
                © 2020 Elbatreek et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 February 2020
                : 18 September 2020
                Page count
                Figures: 3, Tables: 1, Pages: 25
                Funding
                Funded by: H2020 European Research Council (AdG RadMed)
                Award ID: 294683
                Award Recipient :
                Funded by: H2020 European Research Council (PoC SAVEBRAIN)
                Award ID: 737586
                Award Recipient :
                Funded by: Horizon 2020 (REPO-TRIAL)
                Award ID: 777111
                Award Recipient :
                Funded by: VILLUM Young Investigator grant.
                Award ID: 13154
                Award Recipient :
                J.B. is grateful for financial support of his VILLUM Young Investigator grant (no. 13154). Financial support to H.H.H.W.S. by the ERC (AdG RadMed '294683' and PoC SAVEBRAIN '737586') and the Horizon 2020 programme (REPO-TRIAL '777111') is gratefully acknowledged. This reflects only the author's view and the European Commission is not responsible for any use that may be made of the information it contains. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Vascular Medicine
                Blood Pressure
                Hypertension
                Biology and Life Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Arteries
                Femoral Arteries
                Medicine and Health Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Arteries
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                Medicine and Health Sciences
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                Research and Analysis Methods
                Animal Studies
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                Anatomy
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                Biology and Life Sciences
                Biochemistry
                Neurochemistry
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                Nitric Oxide
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                Custom metadata
                All relevant data are within the paper and its Supporting Information files. For in silico data, we used the interactome from IID database which is available at http://ophid.utoronto.ca/iid. For computational data analysis, the MONET tool ( https://github.com/BergmannLab/MONET) and SPICi tool ( https://compbio.cs.princeton.edu/spici/) were used.

                Life sciences
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