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Su C, Hou Y, Xu J, Xu Z, Zhou M, Ke A, Li H, Xu J, Brendel M, Maasch JRMA, Bai Z, Zhang H, Zhu Y, Cincotta MC, Shi X, Henchcliffe C, Leverenz JB, Cummings J, Okun MS, Bian J, Cheng F, Wang F. Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data. NPJ Digit Med 2024; 7:184. [PMID: 38982243 PMCID: PMC11233682 DOI: 10.1038/s41746-024-01175-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Accepted: 06/21/2024] [Indexed: 07/11/2024] Open
Abstract
Parkinson's disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals' phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.
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Grants
- R21 AG083003 NIA NIH HHS
- R01 AG082118 NIA NIH HHS
- R56 AG074001 NIA NIH HHS
- R01AG076448 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- RF1AG072449 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- MJFF-023081 Michael J. Fox Foundation for Parkinson's Research (Michael J. Fox Foundation)
- R01AG080991 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- P30 AG072959 NIA NIH HHS
- 3R01AG066707-01S1 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R21AG083003 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R01AG066707 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R35 AG071476 NIA NIH HHS
- RF1 AG082211 NIA NIH HHS
- R56AG074001 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R01AG082118 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R25 AG083721 NIA NIH HHS
- RF1AG082211 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- U01 NS093334 NINDS NIH HHS
- AG083721-01 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- RF1NS133812 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- P20GM109025 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- RF1 NS133812 NINDS NIH HHS
- R35AG71476 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- U01 AG073323 NIA NIH HHS
- R01 AG066707 NIA NIH HHS
- R01AG053798 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R01AG076234 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R01 AG076448 NIA NIH HHS
- R01 AG080991 NIA NIH HHS
- R01 AG076234 NIA NIH HHS
- U01NS093334 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- P20 GM109025 NIGMS NIH HHS
- P30AG072959 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- RF1 AG072449 NIA NIH HHS
- R01 AG053798 NIA NIH HHS
- 3R01AG066707-02S1 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- U01AG073323 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- ALZDISCOVERY-1051936 Alzheimer's Association
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Affiliation(s)
- Chang Su
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Yu Hou
- Department of Surgery, University of Minnesota, Minneapolis, MN, USA
| | - Jielin Xu
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Zhenxing Xu
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Manqi Zhou
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Alison Ke
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Haoyang Li
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Jie Xu
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Matthew Brendel
- Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Jacqueline R M A Maasch
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Department of Computer Science, Cornell Tech, Cornell University, New York, NY, USA
| | - Zilong Bai
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Haotan Zhang
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Yingying Zhu
- Department of Computer Science, University of Texas at Arlington, Arlington, TX, USA
| | - Molly C Cincotta
- Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA
| | - Xinghua Shi
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Claire Henchcliffe
- Department of Neurology, University of California Irvine, Irvine, CA, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Michael S Okun
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Fei Wang
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA.
- Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, Cornell University, New York, NY, USA.
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2
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Vavougios GD, Mavridis T, Doskas T, Papaggeli O, Foka P, Hadjigeorgiou G. SARS-CoV-2-Induced Type I Interferon Signaling Dysregulation in Olfactory Networks Implications for Alzheimer's Disease. Curr Issues Mol Biol 2024; 46:4565-4579. [PMID: 38785545 PMCID: PMC11119810 DOI: 10.3390/cimb46050277] [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: 01/10/2024] [Revised: 04/15/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
Type I interferon signaling (IFN-I) perturbations are major drivers of COVID-19. Dysregulated IFN-I in the brain, however, has been linked to both reduced cognitive resilience and neurodegenerative diseases such as Alzheimer's. Previous works from our group have proposed a model where peripheral induction of IFN-I may be relayed to the CNS, even in the absence of fulminant infection. The aim of our study was to identify significantly enriched IFN-I signatures and genes along the transolfactory route, utilizing published datasets of the nasal mucosa and olfactory bulb amygdala transcriptomes of COVID-19 patients. We furthermore sought to identify these IFN-I signature gene networks associated with Alzheimer's disease pathology and risk. Gene expression data involving the nasal epithelium, olfactory bulb, and amygdala of COVID-19 patients and transcriptomic data from Alzheimer's disease patients were scrutinized for enriched Type I interferon pathways. Gene set enrichment analyses and gene-Venn approaches were used to determine genes in IFN-I enriched signatures. The Agora web resource was used to identify genes in IFN-I signatures associated with Alzheimer's disease risk based on its aggregated multi-omic data. For all analyses, false discovery rates (FDR) <0.05 were considered statistically significant. Pathways associated with type I interferon signaling were found in all samples tested. Each type I interferon signature was enriched by IFITM and OAS family genes. A 14-gene signature was associated with COVID-19 CNS and the response to Alzheimer's disease pathology, whereas nine genes were associated with increased risk for Alzheimer's disease based on Agora. Our study provides further support to a type I interferon signaling dysregulation along the extended olfactory network as reconstructed herein, ranging from the nasal epithelium and extending to the amygdala. We furthermore identify the 14 genes implicated in this dysregulated pathway with Alzheimer's disease pathology, among which HLA-C, HLA-B, HLA-A, PSMB8, IFITM3, HLA-E, IFITM1, OAS2, and MX1 as genes with associated conferring increased risk for the latter. Further research into its druggability by IFNb therapeutics may be warranted.
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Affiliation(s)
- George D. Vavougios
- Department of Neurology, Medical School, University of Cyprus, Nicosia 1678, Cyprus
| | - Theodoros Mavridis
- Department of Neurology, Tallaght University Hospital (TUH)/The Adelaide and Meath Hospital, Dublin, Incorporating the National Children’s Hospital (AMNCH), D24 NR0A Dublin, Ireland;
| | | | - Olga Papaggeli
- Molecular Virology Laboratory, Hellenic Pasteur Institute, 115 21 Athens, Greece; (O.P.); (P.F.)
| | - Pelagia Foka
- Molecular Virology Laboratory, Hellenic Pasteur Institute, 115 21 Athens, Greece; (O.P.); (P.F.)
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3
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Vavougios GD, Tseriotis VS, Liampas A, Mavridis T, de Erausquin GA, Hadjigeorgiou G. Type I interferon signaling, cognition and neurodegeneration following COVID-19: update on a mechanistic pathogenetic model with implications for Alzheimer's disease. Front Hum Neurosci 2024; 18:1352118. [PMID: 38562226 PMCID: PMC10982434 DOI: 10.3389/fnhum.2024.1352118] [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] [Received: 12/07/2023] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
COVID-19's effects on the human brain reveal a multifactorial impact on cognition and the potential to inflict lasting neuronal damage. Type I interferon signaling, a pathway that represents our defense against pathogens, is primarily affected by COVID-19. Type I interferon signaling, however, is known to mediate cognitive dysfunction upon its dysregulation following synaptopathy, microgliosis and neuronal damage. In previous studies, we proposed a model of outside-in dysregulation of tonic IFN-I signaling in the brain following a COVID-19. This disruption would be mediated by the crosstalk between central and peripheral immunity, and could potentially establish feed-forward IFN-I dysregulation leading to neuroinflammation and potentially, neurodegeneration. We proposed that for the CNS, the second-order mediators would be intrinsic disease-associated molecular patterns (DAMPs) such as proteopathic seeds, without the requirement of neuroinvasion to sustain inflammation. Selective vulnerability of neurogenesis sites to IFN-I dysregulation would then lead to clinical manifestations such as anosmia and cognitive impairment. Since the inception of our model at the beginning of the pandemic, a growing body of studies has provided further evidence for the effects of SARS-CoV-2 infection on the human CNS and cognition. Several preclinical and clinical studies have displayed IFN-I dysregulation and tauopathy in gene expression and neuropathological data in new cases, correspondingly. Furthermore, neurodegeneration identified with a predilection for the extended olfactory network furthermore supports the neuroanatomical concept of our model, and its independence from fulminant neuroinvasion and encephalitis as a cause of CNS damage. In this perspective, we summarize the data on IFN-I as a plausible mechanism of cognitive impairment in this setting, and its potential contribution to Alzheimer's disease and its interplay with COVID-19.
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Affiliation(s)
- George D. Vavougios
- Department of Neurology, Medical School, University of Cyprus, Lefkosia, Cyprus
| | | | - Andreas Liampas
- Department of Neurology, Medical School, University of Cyprus, Lefkosia, Cyprus
| | - Theodore Mavridis
- Tallaght University Hospital (TUH)/The Adelaide and Meath Hospital Dublin, Incorporating the National Children's Hospital (AMNCH), Dublin, Ireland
| | - Gabriel A. de Erausquin
- Laboratory of Brain Development, Modulation and Repair, The Glenn Biggs Institute of Alzheimer's and Neurodegenerative Disorders, Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
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4
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Razzaq A, Disoma C, Zhou Y, Tao S, Chen Z, Liu S, Zheng R, Zhang Y, Liao Y, Chen X, Liu S, Dong Z, Xu L, Deng X, Li S, Xia Z. Targeting epidermal growth factor receptor signalling pathway: A promising therapeutic option for COVID-19. Rev Med Virol 2024; 34:e2500. [PMID: 38126937 DOI: 10.1002/rmv.2500] [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: 08/14/2023] [Revised: 11/20/2023] [Accepted: 12/10/2023] [Indexed: 12/23/2023]
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously producing new variants, necessitating effective therapeutics. Patients are not only confronted by the immediate symptoms of infection but also by the long-term health issues linked to long COVID-19. Activation of epidermal growth factor receptor (EGFR) signalling during SARS-CoV-2 infection promotes virus propagation, mucus hyperproduction, and pulmonary fibrosis, and suppresses the host's antiviral response. Over the long term, EGFR activation in COVID-19, particularly in COVID-19-induced pulmonary fibrosis, may be linked to the development of lung cancer. In this review, we have summarised the significance of EGFR signalling in the context of SARS-CoV-2 infection. We also discussed the targeting of EGFR signalling as a promising strategy for COVID-19 treatment and highlighted erlotinib as a superior option among EGFR inhibitors. Erlotinib effectively blocks EGFR and AAK1, thereby preventing SARS-CoV-2 replication, reducing mucus hyperproduction, TNF-α expression, and enhancing the host's antiviral response. Nevertheless, to evaluate the antiviral efficacy of erlotinib, relevant clinical trials involving an appropriate patient population should be designed.
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Affiliation(s)
- Aroona Razzaq
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Cyrollah Disoma
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
- Department of Biology, College of Natural Sciences and Mathematics, Mindanao State University, Marawi City, Philippines
| | - Yuzheng Zhou
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
- Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, China
| | - Siyi Tao
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Zongpeng Chen
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Sixu Liu
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Rong Zheng
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Yongxing Zhang
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Yujie Liao
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Xuan Chen
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Sijie Liu
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Zijun Dong
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Liangtao Xu
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Xu Deng
- Xiangya School of Pharmaceutical Science, Central South University, Changsha, China
| | - Shanni Li
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
| | - Zanxian Xia
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, China
- Hunan Key Laboratory of Animal Models for Human Diseases, School of Life Sciences, Central South University, Changsha, China
- Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China
- Centre for Medical Genetics, School of Life Sciences, Central South University, Changsha, China
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5
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Olivera E, Sáez A, Carniglia L, Caruso C, Lasaga M, Durand D. Alzheimer's disease risk after COVID-19: a view from the perspective of the infectious hypothesis of neurodegeneration. Neural Regen Res 2023; 18:1404-1410. [PMID: 36571334 PMCID: PMC10075115 DOI: 10.4103/1673-5374.360273] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
In light of the rising evidence of the association between viral and bacterial infections and neurodegeneration, we aimed at revisiting the infectious hypothesis of Alzheimer's disease and analyzing the possible implications of COVID-19 neurological sequelae in long-term neurodegeneration. We wondered how SARS-CoV-2 could be related to the amyloid-β cascade and how it could lead to the pathological hallmarks of the disease. We also predict a paradigm change in clinical medicine, which now has a great opportunity to conduct prospective surveillance of cognitive sequelae and progression to dementia in people who suffered severe infections together with other risk factors for Alzheimer's disease.
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Affiliation(s)
- Eugenia Olivera
- Instituto de Investigaciones Biomédicas INBIOMED UBA-CONICET, Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - Albany Sáez
- Instituto de Investigaciones Biomédicas INBIOMED UBA-CONICET, Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - Lila Carniglia
- Instituto de Investigaciones Biomédicas INBIOMED UBA-CONICET, Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - Carla Caruso
- Instituto de Investigaciones Biomédicas INBIOMED UBA-CONICET, Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - Mercedes Lasaga
- Instituto de Investigaciones Biomédicas INBIOMED UBA-CONICET, Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - Daniela Durand
- Instituto de Investigaciones Biomédicas INBIOMED UBA-CONICET, Facultad de Medicina, Universidad de Buenos Aires, Argentina
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Al-Kuraishy HM, Al-Gareeb AI, Kaushik A, Kujawska M, Ahmed EA, Batiha GES. SARS-COV-2 infection and Parkinson's disease: Possible links and perspectives. J Neurosci Res 2023; 101:952-975. [PMID: 36717481 DOI: 10.1002/jnr.25171] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 01/13/2023] [Accepted: 01/15/2023] [Indexed: 02/01/2023]
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by the progressive loss of dopaminergic neurons in the substantia nigra. The hallmarks are the presence of Lewy bodies composed mainly of aggregated α-synuclein and immune activation and inflammation in the brain. The neurotropism of SARS-CoV-2 with induction of cytokine storm and neuroinflammation can contribute to the development of PD. Interestingly, overexpression of α-synuclein in PD patients may limit SARS-CoV-2 neuroinvasion and degeneration of dopaminergic neurons; however, on the other hand, this virus can speed up the α-synuclein aggregation. The review aims to discuss the potential link between COVID-19 and the risk of PD, highlighting the need for further studies to authenticate the potential association. We have also overviewed the influence of SARS-CoV-2 infection on the PD course and management. In this context, we presented the prospects for controlling the COVID-19 pandemic and related PD cases that, beyond global vaccination and novel anti-SARS-CoV-2 agents, may include the development of graphene-based nanoscale platforms offering antiviral and anti-amyloid strategies against PD.
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Affiliation(s)
- Hayder M Al-Kuraishy
- Department of Clinical Pharmacology and Medicine, College of Medicine, Al-Mustansiriyia University, Baghdad, Iraq
| | - Ali I Al-Gareeb
- Department of Clinical Pharmacology and Medicine, College of Medicine, Al-Mustansiriyia University, Baghdad, Iraq
| | - Ajeet Kaushik
- NanoBioTech Laboratory, Department of Environmental Engineering, Florida Polytechnic University, Lakeland, Florida, USA
| | - Małgorzata Kujawska
- Department of Toxicology, Poznan University of Medical Sciences, Poznan, Poland
| | - Eman A Ahmed
- Department of Pharmacology, Faculty of Veterinary Medicine, Suez Canal University, Ismailia, Egypt
| | - Gaber El-Saber Batiha
- Department of Pharmacology and Therapeutics, Faculty of Veterinary Medicine, Damanhour University, Damanhour, Egypt
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7
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Wang Z, Zhan J, Gao H. Computer-aided drug design combined network pharmacology to explore anti-SARS-CoV-2 or anti-inflammatory targets and mechanisms of Qingfei Paidu Decoction for COVID-19. Front Immunol 2022; 13:1015271. [PMID: 36618410 PMCID: PMC9816407 DOI: 10.3389/fimmu.2022.1015271] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
Introduction Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by SARS-CoV-2. Severe cases of COVID-19 are characterized by an intense inflammatory process that may ultimately lead to organ failure and patient death. Qingfei Paidu Decoction (QFPD), a traditional Chines e medicine (TCM) formula, is widely used in China as anti-SARS-CoV-2 and anti-inflammatory. However, the potential targets and mechanisms for QFPD to exert anti-SARS-CoV-2 or anti-inflammatory effects remain unclear. Methods In this study, Computer-Aided Drug Design was performed to identify the antiviral or anti-inflammatory components in QFPD and their targets using Discovery Studio 2020 software. We then investigated the mechanisms associated with QFPD for treating COVID-19 with the help of multiple network pharmacology approaches. Results and discussion By overlapping the targets of QFPD and COVID-19, we discovered 8 common targets (RBP4, IL1RN, TTR, FYN, SFTPD, TP53, SRPK1, and AKT1) of 62 active components in QFPD. These may represent potential targets for QFPD to exert anti-SARS-CoV-2 or anti-inflammatory effects. The result showed that QFPD might have therapeutic effects on COVID-19 by regulating viral infection, immune and inflammation-related pathways. Our work will promote the development of new drugs for COVID-19.
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Vavougios GD, de Erausquin GA, Snyder HM. Type I interferon signaling in SARS-CoV-2 associated neurocognitive disorder (SAND): Mapping host-virus interactions to an etiopathogenesis. Front Neurol 2022; 13:1063298. [PMID: 36570454 PMCID: PMC9771386 DOI: 10.3389/fneur.2022.1063298] [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: 10/06/2022] [Accepted: 11/09/2022] [Indexed: 12/12/2022] Open
Abstract
Epidemiological, clinical, and radiological studies have provided insights into the phenomenology and biological basis of cognitive impairment in COVID-19 survivors. Furthermore, its association with biomarkers associated with neuroinflammation and neurodegeneration supports the notion that it is a distinct aspect of LongCOVID syndrome with specific underlying biology. Accounting for the latter, translational studies on SARS-CoV-2's interactions with its hosts have provided evidence on type I interferon dysregulation, which is seen in neuroinflammatory and neurodegenerative diseases. To date, studies attempting to describe this overlap have only described common mechanisms. In this manuscript, we attempt to propose a mechanistic model based on the host-virus interaction hypothesis. We discuss the molecular basis for a SARS-CoV-2-associated neurocognitive disorder (SAND) focusing on specific genes and pathways with potential mechanistic implications, several of which have been predicted by Vavougios and their research group. Furthermore, our hypothesis links translational evidence on interferon-responsive gene perturbations introduced by SARS-CoV-2 and known dysregulated pathways in dementia. Discussion emphasizes the crosstalk between central and peripheral immunity via danger-associated molecular patterns in inducing SAND's emergence in the absence of neuroinfection. Finally, we outline approaches to identifying targets that are both testable and druggable, and could serve in the design of future clinical and translational studies.
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Affiliation(s)
- George D. Vavougios
- Department of Neurology, University of Cyprus, Lefkosia, Cyprus,Department of Respiratory Medicine, University of Thessaly, Larisa, Greece,*Correspondence: George D. Vavougios ;
| | - Gabriel A. de Erausquin
- The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UTHSA, San Antonio, TX, United States
| | - Heather M. Snyder
- Division of Medical and Scientific Relations, Alzheimer's Association, Chicago, IL, United States
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Post-COVID-19 Parkinsonism and Parkinson’s Disease Pathogenesis: The Exosomal Cargo Hypothesis. Int J Mol Sci 2022; 23:ijms23179739. [PMID: 36077138 PMCID: PMC9456372 DOI: 10.3390/ijms23179739] [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: 08/09/2022] [Revised: 08/21/2022] [Accepted: 08/26/2022] [Indexed: 11/16/2022] Open
Abstract
Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease after Alzheimer’s disease, globally. Dopaminergic neuron degeneration in substantia nigra pars compacta and aggregation of misfolded alpha-synuclein are the PD hallmarks, accompanied by motor and non-motor symptoms. Several viruses have been linked to the appearance of a post-infection parkinsonian phenotype. Coronavirus disease 2019 (COVID-19), caused by emerging severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, has evolved from a novel pneumonia to a multifaceted syndrome with multiple clinical manifestations, among which neurological sequalae appear insidious and potentially long-lasting. Exosomes are extracellular nanovesicles bearing a complex cargo of active biomolecules and playing crucial roles in intercellular communication under pathophysiological conditions. Exosomes constitute a reliable route for misfolded protein transmission, contributing to PD pathogenesis and diagnosis. Herein, we summarize recent evidence suggesting that SARS-CoV-2 infection shares numerous clinical manifestations and inflammatory and molecular pathways with PD. We carry on hypothesizing that these similarities may be reflected in exosomal cargo modulated by the virus in correlation with disease severity. Travelling from the periphery to the brain, SARS-CoV-2-related exosomal cargo contains SARS-CoV-2 RNA, viral proteins, inflammatory mediators, and modified host proteins that could operate as promoters of neurodegenerative and neuroinflammatory cascades, potentially leading to a future parkinsonism and PD development.
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Alegría-Arcos M, Barbosa T, Sepúlveda F, Combariza G, González J, Gil C, Martínez A, Ramírez D. Network pharmacology reveals multitarget mechanism of action of drugs to be repurposed for COVID-19. Front Pharmacol 2022; 13:952192. [PMID: 36052135 PMCID: PMC9424758 DOI: 10.3389/fphar.2022.952192] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/06/2022] [Indexed: 12/03/2022] Open
Abstract
The coronavirus disease 2019 pandemic accelerated drug/vaccine development processes, integrating scientists all over the globe to create therapeutic alternatives against this virus. In this work, we have collected information regarding proteins from SARS-CoV-2 and humans and how these proteins interact. We have also collected information from public databases on protein–drug interactions. We represent this data as networks that allow us to gain insights into protein–protein interactions between both organisms. With the collected data, we have obtained statistical metrics of the networks. This data analysis has allowed us to find relevant information on which proteins and drugs are the most relevant from the network pharmacology perspective. This method not only allows us to focus on viral proteins as the main targets for COVID-19 but also reveals that some human proteins could be also important in drug repurposing campaigns. As a result of the analysis of the SARS-CoV-2–human interactome, we have identified some old drugs, such as disulfiram, auranofin, gefitinib, suloctidil, and bromhexine as potential therapies for the treatment of COVID-19 deciphering their potential complex mechanism of action.
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Affiliation(s)
- Melissa Alegría-Arcos
- Facultad de Ingeniería y Negocios, Universidad de Las Américas, Sede Providencia, Santiago, Chile
| | - Tábata Barbosa
- Departamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Sede Bogotá, Bogotá, Colombia
| | - Felipe Sepúlveda
- Department of Molecular Genetics and Microbiology, Biological Sciences Faculty, Pontifical Catholic University of Chile, Santiago, Chile
| | - German Combariza
- Universidad Externado de Colombia, Departamento de Matemáticas, Bogotá, Colombia
| | - Janneth González
- Departamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Sede Bogotá, Bogotá, Colombia
| | - Carmen Gil
- Centro de Investigaciones Biológicas Margarita Salas (CIB-CSIC), Madrid, Spain
| | - Ana Martínez
- Centro de Investigaciones Biológicas Margarita Salas (CIB-CSIC), Madrid, Spain
| | - David Ramírez
- Instituto de Ciencias Biomédicas, Universidad Autónoma de Chile, Santiago, Chile
- Research Center for the Development of Novel Therapeutic Alternatives for Alcohol Use Disorders, Santiago, Chile
- *Correspondence: David Ramírez,
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Vavougios GD, Mavridis T, Artemiadis A, Krogfelt KA, Hadjigeorgiou G. Trained immunity in viral infections, Alzheimer's disease and multiple sclerosis: A convergence in type I interferon signalling and IFNβ-1a. Biochim Biophys Acta Mol Basis Dis 2022; 1868:166430. [DOI: 10.1016/j.bbadis.2022.166430] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/02/2022] [Accepted: 05/02/2022] [Indexed: 12/14/2022]
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