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All Studies   Meta Analysis    Recent:   

Network-based multi-omics-disease-drug associations reveal drug repurposing candidates for COVID-19 disease phases

Agamah et al., ScienceOpen, doi:10.58647/DRUGARXIV.PR000010.v1
Apr 2024  
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Metformin for COVID-19
3rd treatment shown to reduce risk in July 2020
 
*, now known with p < 0.00000000001 from 89 studies.
No treatment is 100% effective. Protocols combine complementary and synergistic treatments. * >10% efficacy in meta analysis with ≥3 clinical studies.
4,100+ studies for 60+ treatments. c19early.org
In Silico study identifying potential drugs beneficial for COVID-19 by integrating transcriptomics, proteomics, metabolomics, lipidomics, and drug data. Authors explore interactions between drugs, molecular features, and disease severity. Hypothesis-driven analysis, using IL-6 and IL-6R as seeds, highlighted immunosuppressants, corticosteroids, and IL-6 inhibitors as promising candidates, while data-driven analysis, using STAT1, SOD2, and lipid/metabolite markers as seeds, identified antioxidants, kinase inhibitors, and protein synthesis inhibitors. Network analysis revealed key hubs like CCL2, CCL4, NFKB1, and HGF that interact with drug candidates and influence disease progression. Treatments identified in the top 20 lists include ivermectin, zinc, azithromycin, indomethacin, curcumin, vitamin C, metformin, and acetylcysteine.
8 preclinical studies support the efficacy of metformin for COVID-19:
A systematic review and meta-analysis of 15 non-COVID-19 preclinical studies showed that metformin inhibits pulmonary inflammation and oxidative stress, minimizes lung injury, and improves survival in animal models of acute respiratory distress syndrome (ARDS) or acute lung injury (ALI) Wang. Metformin inhibits SARS-CoV-2 in vitro Parthasarathy, Ventura-López, minimizes LPS-induced cytokine storm in a mouse model Taher, minimizes lung damage and fibrosis in a mouse model of LPS-induced ARDS Miguel, may protect against SARS-CoV-2-induced neurological disorders Yang, may be beneficial via inhibitory effects on ORF3a-mediated inflammasome activation Zhang, reduces UUO and FAN-induced kidney fibrosis Miguel, increases mitochondrial function and decreases TGF-β-induced fibrosis, apoptosis, and inflammation markers in lung epithelial cells Miguel, and may improve outcomes via modulation of immune responses with increased anti-inflammatory T lymphocyte gene expression and via enhanced gut microbiota diversity Petakh.
Study covers ivermectin, zinc, indomethacin, curcumin, vitamin C, metformin, and N-acetylcysteine.
Agamah et al., 16 Apr 2024, preprint, 6 authors. Contact: francisagamahh@gmail.com, peter-bram.thoen@radboudumc.nl, emile.chimusa@northumbria.ac.uk.
In Silico studies are an important part of preclinical research, however results may be very different in vivo.
This PaperMetforminAll
Network-based multi-omics-disease-drug associations reveal drug repurposing candidates for
Francis Edem Agamah, Thomas H A Ederveen, Michelle Skelton, Darren P Martin, MSc Emile R Chimusa, Peter A C 't Hoen 't Hoen, PhD Peter A C 't Hoen
Background: The development and roll-out of vaccines, and the use of various drugs have contributed to controlling the COVID-19 pandemic. Nevertheless, challenges such as the inequitable distribution of vaccines, the influence of emerging viral lineages and immune evasive variants on vaccine efficacy, and the inadequate immune defense in subgroups of the population continue to motivate the development of new drugs to combat the disease. Aim: In this study, we sought to identify, prioritize, and characterize drug repurposing candidates appropriate for treating mild, moderate, or severe COVID-19 using a network-based integrative approach that systematically integrates drug-related data and multi-omics datasets. Methods: We leveraged drug data, and multi-omics data, and used a random walk restart algorithm to explore an integrated knowledge graph comprised of three subgraphs: (i) a COVID-19 knowledge graph, (ii) a drug repurposing knowledge graph, and (iii) a COVID-19 disease-state specific omics graph. Results: We prioritized twenty FDA-approved agents as potential candidate drugs for mild, moderate, and severe COVID-19 disease phases. Specifically, drugs that could stimulate immune cell recruitment and activation including histamine, curcumin, and paclitaxel have potential utility in mild disease states to mitigate disease progression. Drugs like omacetaxine, crizotinib, and vorinostat that exhibit antiviral properties and have the potential to inhibit viral replication can be considered for mild to moderate COVID-19 disease states. Also, given the association between antioxidant deficiency and high inflammatory factors that trigger cytokine storms, antioxidants like glutathione can be considered for moderate disease states. Drugs that exhibit potent antiinflammatory effects like (i) anti-inflammatory drugs (sarilumab and tocilizumab), (ii) corticosteroids (dexamethasone and hydrocortisone), and (iii) immunosuppressives (sirolimus and cyclosporine) are potential candidates for moderate to severe disease states that trigger a hyperinflammatory cascade of COVID-19. Conclusion: Our study demonstrates that the multi-omics data-driven integrative analysis within the drug data enables prioritizing drug candidates for COVID-19 disease phases, offering a comprehensive basis for therapeutic strategies that can be brought to market quickly given their established safety profiles. Importantly, the multi-omics data-driven integrative analysis within the drug data approach implemented here can be used to prioritize drug repurposing candidates appropriate for other diseases.
Declarations Ethics approval and consent to participate Not applicable Consent for publication The authors have consented for the work to be published. Supplementary Files Supplementary data Supplementary file 1 Supplementary file 2 Supplementary file 3 Supplementary file 4 Supplementary file 5 Next, we prioritized and characterized candidate drugs followed by drug prediction robustness analysis. Finally, we concluded the analysis by validating the predicted drug candidates. Figure legends
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{ 'DOI': '10.58647/drugarxiv.pr000010.v1', 'URL': 'http://dx.doi.org/10.58647/DRUGARXIV.PR000010.v1', 'abstract': '<jats:p> \n' ' <jats:bold>Background:</jats:bold>The development and roll-out of ' 'vaccines, and the use of various drugs have contributed to controlling the COVID-19 pandemic. ' 'Nevertheless, challenges such as the inequitable distribution of vaccines, the influence of ' 'emerging viral lineages and immune evasive variants on vaccine efficacy, and the inadequate ' 'immune defense in subgroups of the population continue to motivate the development of new ' 'drugs to combat the disease.</jats:p>\n' ' <jats:p> \n' ' <jats:bold>Aim:</jats:bold>In this study, we sought to identify, ' 'prioritize, and characterize drug repurposing candidates appropriate for treating mild, ' 'moderate, or severe COVID-19 using a network-based integrative approach that systematically ' 'integrates drug-related data and multi-omics datasets.</jats:p>\n' ' <jats:p> \n' ' <jats:bold>Methods</jats:bold>: We leveraged drug data, and multi-omics ' 'data, and used a random walk restart algorithm to explore an integrated knowledge graph ' 'comprised of three sub-graphs: (i) a COVID-19 knowledge graph, (ii) a drug repurposing ' 'knowledge graph, and (iii) a COVID-19 disease-state specific omics graph.</jats:p>\n' ' <jats:p> \n' ' <jats:bold>Results:</jats:bold>We prioritized twenty FDA-approved agents ' 'as potential candidate drugs for mild, moderate, and severe COVID-19 disease phases. ' 'Specifically, drugs that could stimulate immune cell recruitment and activation including ' 'histamine, curcumin, and paclitaxel have potential utility in mild disease states to mitigate ' 'disease progression. Drugs like omacetaxine, crizotinib, and vorinostat that exhibit ' 'antiviral properties and have the potential to inhibit viral replication can be considered ' 'for mild to moderate COVID-19 disease states. Also, given the association between antioxidant ' 'deficiency and high inflammatory factors that trigger cytokine storms, antioxidants like ' 'glutathione can be considered for moderate disease states. Drugs that exhibit potent ' 'anti-inflammatory effects like (i) anti-inflammatory drugs (sarilumab and tocilizumab), (ii) ' 'corticosteroids (dexamethasone and hydrocortisone), and (iii) immunosuppressives (sirolimus ' 'and cyclosporine) are potential candidates for moderate to severe disease states that trigger ' 'a hyperinflammatory cascade of COVID-19.</jats:p>\n' ' <jats:p> \n' ' <jats:bold>Conclusion:</jats:bold>Our study demonstrates that the ' 'multi-omics data-driven integrative analysis within the drug data enables prioritizing drug ' 'candidates for COVID-19 disease phases, offering a comprehensive basis for therapeutic ' 'strategies that can be brought to market quickly given their established safety profiles. ' 'Importantly, the multi-omics data-driven integrative analysis within the drug data approach ' 'implemented here can be used to prioritize drug repurposing candidates appropriate for other ' 'diseases.</jats:p>', 'author': [ { 'ORCID': 'http://orcid.org/0000-0002-2980-1392', 'affiliation': [ { 'id': [ { 'asserted-by': 'publisher', 'id': 'https://ror.org/03p74gp79', 'id-type': 'ROR'}], 'name': 'Computational Biology Division, Department of Integrative ' 'Biomedical Sciences, Institute of Infectious Disease and ' 'Molecular Medicine, Faculty of Health Sciences, University of ' 'Cape Town, Cape Town, South Africa'}], 'authenticated-orcid': False, 'family': 'Agamah', 'given': 'Francis Edem', 'sequence': 'first'}, { 'affiliation': [ { 'id': [ { 'asserted-by': 'publisher', 'id': 'https://ror.org/05wg1m734', 'id-type': 'ROR'}], 'name': 'Department of Medical BioSciences, Radboud University Medical ' 'Center Nijmegen, The Netherlands'}], 'family': 'Ederveen', 'given': 'Thomas H.A.', 'sequence': 'additional'}, { 'affiliation': [ { 'id': [ { 'asserted-by': 'publisher', 'id': 'https://ror.org/03p74gp79', 'id-type': 'ROR'}], 'name': 'Computational Biology Division, Department of Integrative ' 'Biomedical Sciences, Institute of Infectious Disease and ' 'Molecular Medicine, Faculty of Health Sciences, University of ' 'Cape Town, Cape Town, South Africa'}], 'family': 'Skelton', 'given': 'Michelle', 'sequence': 'additional'}, { 'affiliation': [ { 'id': [ { 'asserted-by': 'publisher', 'id': 'https://ror.org/03p74gp79', 'id-type': 'ROR'}], 'name': 'Computational Biology Division, Department of Integrative ' 'Biomedical Sciences, Institute of Infectious Disease and ' 'Molecular Medicine, Faculty of Health Sciences, University of ' 'Cape Town, Cape Town, South Africa'}], 'family': 'Martin', 'given': 'Darren P.', 'sequence': 'additional'}, { 'affiliation': [ { 'id': [ { 'asserted-by': 'publisher', 'id': 'https://ror.org/049e6bc10', 'id-type': 'ROR'}], 'name': 'Department of Applied Science, Faculty of Health and Life ' 'Sciences, Northumbria University, Newcastle, Tyne and Wear, NE1 ' '8ST, UK'}], 'family': 'Chimusa', 'given': 'Emile R.', 'sequence': 'additional'}, { 'affiliation': [ { 'id': [ { 'asserted-by': 'publisher', 'id': 'https://ror.org/05wg1m734', 'id-type': 'ROR'}], 'name': 'Department of Medical BioSciences, Radboud University Medical ' 'Center Nijmegen, The Netherlands'}], 'family': "'t Hoen", 'given': "Peter A.C. 't Hoen", 'sequence': 'additional'}], 'container-title': [], 'content-domain': {'crossmark-restriction': False, 'domain': []}, 'created': {'date-parts': [[2024, 4, 17]], 'date-time': '2024-04-17T13:50:17Z', 'timestamp': 1713361817000}, 'deposited': { 'date-parts': [[2024, 4, 17]], 'date-time': '2024-04-17T13:50:18Z', 'timestamp': 1713361818000}, 'funder': [ {'award': ['184.034.019'], 'name': 'Dutch Organization of Scientific Research'}, {'award': ['871096'], 'name': 'European Union to the EATRIS-Plus infrastructure project'}], 'indexed': {'date-parts': [[2024, 4, 18]], 'date-time': '2024-04-18T02:13:26Z', 'timestamp': 1713406406464}, 'institution': [{'name': 'ScienceOpen'}], 'is-referenced-by-count': 0, 'issued': {'date-parts': [[2024, 4, 16]]}, 'license': [ { 'URL': 'http://creativecommons.org/licenses/by/4.0/', 'content-version': 'unspecified', 'delay-in-days': 0, 'start': { 'date-parts': [[2024, 4, 16]], 'date-time': '2024-04-16T00:00:00Z', 'timestamp': 1713225600000}}], 'link': [ { 'URL': 'https://drugrepocentral.scienceopen.com/hosted-document?doi=10.58647/DRUGARXIV.PR000010.v1', 'content-type': 'unspecified', 'content-version': 'vor', 'intended-application': 'similarity-checking'}], 'member': '5403', 'original-title': [], 'posted': {'date-parts': [[2024, 4, 16]]}, 'prefix': '10.58647', 'published': {'date-parts': [[2024, 4, 16]]}, 'publisher': 'ScienceOpen', 'reference-count': 0, 'references-count': 0, 'relation': {}, 'resource': { 'primary': { 'URL': 'https://drugrepocentral.scienceopen.com/hosted-document?doi=10.58647/DRUGARXIV.PR000010.v1'}}, 'score': 1, 'short-title': [], 'source': 'Crossref', 'subject': [], 'subtitle': [], 'subtype': 'preprint', 'title': 'Network-based multi-omics-disease-drug associations reveal drug repurposing candidates for ' 'COVID-19 disease phases', 'type': 'posted-content'}
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