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Loucera C, Carmona R, Esteban-Medina M, Bostelmann G, Muñoyerro-Muñiz D, Villegas R, Peña-Chilet M, Dopazo J. Real-world evidence with a retrospective cohort of 15,968 COVID-19 hospitalized patients suggests 21 new effective treatments. Virol J 2023; 20:226. [PMID: 37803348 PMCID: PMC10559601 DOI: 10.1186/s12985-023-02195-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 09/27/2023] [Indexed: 10/08/2023] Open
Abstract
PURPOSE Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19. METHODS Using data from a central registry of electronic health records (the Andalusian Population Health Database), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient outcomes, including survival and lymphocyte progression, was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. RESULTS Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality. CONCLUSIONS In this study we have taken advantage of the availability of a regional clinical database to study the effect of drugs, which patients were taking for other indications, on their survival. The large size of the database allowed us to control covariates effectively.
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Affiliation(s)
- Carlos Loucera
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain
| | - Rosario Carmona
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS. Hospital Virgen del Rocio, Sevilla, Spain
| | - Marina Esteban-Medina
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain
| | - Gerrit Bostelmann
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
| | - Dolores Muñoyerro-Muñiz
- Subdirección Técnica Asesora de Gestión de la Información. Servicio Andaluz de Salud, Sevilla, Spain
| | - Román Villegas
- Subdirección Técnica Asesora de Gestión de la Información. Servicio Andaluz de Salud, Sevilla, Spain
| | - María Peña-Chilet
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS. Hospital Virgen del Rocio, Sevilla, Spain
| | - Joaquín Dopazo
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain.
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS. Hospital Virgen del Rocio, Sevilla, Spain.
- FPS/ELIXIR-ES, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, Sevilla, Spain.
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Foresta A, Ojeda-Fernandez L, Macaluso G, Roncaglioni MC, Tettamanti M, Fortino I, Leoni O, Genovese S, Baviera M. Dipeptidyl Peptidase-4 Inhibitors, Glucagon-like Peptide-1 Receptor Agonists, and Sodium-Glucose Cotransporter-2 Inhibitors and COVID-19 Outcomes. Clin Ther 2023; 45:e115-e126. [PMID: 36933975 PMCID: PMC9974363 DOI: 10.1016/j.clinthera.2023.02.007] [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: 10/26/2022] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/05/2023]
Abstract
PURPOSE It has been reported that dipeptidyl peptidase-4 inhibitors (DPP-4i), glucagon-like peptide-1 receptor agonists (GLP-1 RA), and sodium-glucose cotransporter-2 inhibitors (SGLT-2i) have a role in modulation of inflammation associated with coronavirus disease 2019 (COVID-19). This study assessed the effect of these drug classes on COVID-19-related outcomes. METHODS Using a COVID-19 linkable administrative database, we selected patients aged ≥40 years with at least 2 prescriptions of DPP-4i, GLP-1 RA, or SGLT-2i or any other antihyperglycemic drug and a diagnosis of COVID-19 from February 15, 2020, to March 15, 2021. Adjusted odds ratios (ORs) with 95% CIs were used to calculate the association between treatments and all-cause and in-hospital mortality and COVID-19-related hospitalization. A sensitivity analysis was performed by using inverse probability treatment weighting. FINDINGS Overall, 32,853 subjects were included in the analysis. Multivariable models showed a reduction of the risk for COVID-19 outcomes for users of DPP-4i, GLP-1 RA, and SGLT-2i compared with nonusers, although statistical significance was reached only in DPP-4i users for total mortality (OR, 0.89; 95% CI, 0.82-0.97). The sensitivity analysis confirmed the main results reaching a significant reduction for hospital admission in GLP-1 RA users and in-hospital mortality in SGLT-2i users compared with nonusers. IMPLICATIONS This study found a beneficial effect in the risk reduction of COVID-19 total mortality in DPP-4i users compared with nonusers. A positive trend was also observed in users of GLP-1 RA and SGLT-2i compared with nonusers. Randomized clinical trials are needed to confirm the effect of these drug classes as potential therapy for the treatment of COVID-19.
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Affiliation(s)
- Andreana Foresta
- Laboratory of Cardiovascular Prevention, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
| | - Luisa Ojeda-Fernandez
- Laboratory of Cardiovascular Prevention, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Giulia Macaluso
- Laboratory of Cardiovascular Prevention, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Maria Carla Roncaglioni
- Laboratory of Cardiovascular Prevention, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Mauro Tettamanti
- Laboratory of Geriatric Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Ida Fortino
- Unità Organizzativa Osservatorio Epidemiologico Regionale, Lombardy Region, Milan, Italy
| | - Olivia Leoni
- Unità Organizzativa Osservatorio Epidemiologico Regionale, Lombardy Region, Milan, Italy
| | | | - Marta Baviera
- Laboratory of Cardiovascular Prevention, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
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Cao JF, Yang X, Xiong L, Wu M, Chen S, Xiong C, He P, Zong Y, Zhang L, Fu H, Qi Y, Ying X, Liu D, Hu X, Zhang X. Mechanism of N-0385 blocking SARS-CoV-2 to treat COVID-19 based on molecular docking and molecular dynamics. Front Microbiol 2022; 13:1013911. [PMID: 36329841 PMCID: PMC9622768 DOI: 10.3389/fmicb.2022.1013911] [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: 08/08/2022] [Accepted: 09/26/2022] [Indexed: 11/21/2023] Open
Abstract
PURPOSE 2019 Coronavirus disease (COVID-19) has caused millions of confirmed cases and deaths worldwide. TMPRSS2-mediated hydrolysis and maturation of spike protein is essential for SARS-CoV-2 infection in vivo. The latest research found that a TMPRSS2 inhibitor called N-0385 could effectively prevent the infection of the SARS-CoV-2 and its variants. However, it is not clear about the mechanism of N-0385 treatment COVID-19. Therefore, this study used computer simulations to investigate the mechanism of N-0385 treatment COVID-19 by impeding SARS-CoV-2 infection. METHODS The GeneCards database was used to search disease gene targets, core targets were analyzed by PPI, GO and KEGG. Molecular docking and molecular dynamics were used to validate and analyze the binding stability of small molecule N-0385 to target proteins. The supercomputer platform was used to simulate and analyze the number of hydrogen bonds, binding free energy, stability of protein targets at the residue level, radius of gyration and solvent accessible surface area. RESULTS There were 4,600 COVID-19 gene targets from GeneCards database. PPI, GO and KEGG analysis indicated that signaling pathways of immune response and inflammation played crucial roles in COVID-19. Molecular docking showed that N-0385 could block SARS-CoV-2 infection and treat COVID-19 by acting on ACE2, TMPRSS2 and NLRP3. Molecular dynamics was used to demonstrate that the small molecule N-0385 could form very stable bindings with TMPRSS2 and TLR7. CONCLUSION The mechanism of N-0385 treatment COVID-19 was investigated by molecular docking and molecular dynamics simulation. We speculated that N-0385 may not only inhibit SARS-CoV-2 invasion directly by acting on TMPRSS2, ACE2 and DPP4, but also inhibit the immune recognition process and inflammatory response by regulating TLR7, NLRP3 and IL-10 to prevent SARS-CoV-2 invasion. Therefore, these results suggested that N-0385 may act through multiple targets to reduce SARS-CoV-2 infection and damage caused by inflammatory responses.
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Affiliation(s)
- Jun-Feng Cao
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Xingyu Yang
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Li Xiong
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Mei Wu
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Shengyan Chen
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Chenyang Xiong
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Peiyong He
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | | | - Lixin Zhang
- Yunnan Academy of Forestry Sciences, Kunming, Yunnan, China
| | - Hongjiao Fu
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Yue Qi
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Xiran Ying
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Dengxin Liu
- Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Xiaosong Hu
- Chengdu Medical College of Basic Medical Sciences, Chengdu, China
| | - Xiao Zhang
- Chengdu Medical College of Basic Medical Sciences, Chengdu, China
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Schöning V, Hammann F. Drug-Disease Severity and Target-Disease Severity Interaction Networks in COVID-19 Patients. Pharmaceutics 2022; 14:pharmaceutics14091828. [PMID: 36145576 PMCID: PMC9504398 DOI: 10.3390/pharmaceutics14091828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/18/2022] [Accepted: 08/27/2022] [Indexed: 11/25/2022] Open
Abstract
Drug interactions with other drugs are a well-known phenomenon. Similarly, however, pre-existing drug therapy can alter the course of diseases for which it has not been prescribed. We performed network analysis on drugs and their respective targets to investigate whether there are drugs or targets with protective effects in COVID-19, making them candidates for repurposing. These networks of drug-disease interactions (DDSIs) and target-disease interactions (TDSIs) revealed a greater share of patients with diabetes and cardiac co-morbidities in the non-severe cohort treated with dipeptidyl peptidase-4 (DPP4) inhibitors. A possible protective effect of DPP4 inhibitors is also plausible on pathophysiological grounds, and our results support repositioning efforts of DPP4 inhibitors against SARS-CoV-2. At target level, we observed that the target location might have an influence on disease progression. This could potentially be attributed to disruption of functional membrane micro-domains (lipid rafts), which in turn could decrease viral entry and thus disease severity.
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