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Jachman-Kapułka J, Zińczuk A, Szymański W, Simon K, Rorat M. Complexity and Diversity of the Neurological Spectrum of SARS-CoV-2 over Three Waves of COVID-19. J Clin Med 2024; 13:3477. [PMID: 38930003 PMCID: PMC11204600 DOI: 10.3390/jcm13123477] [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: 04/10/2024] [Revised: 05/27/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024] Open
Abstract
Background/Objectives: SARS-CoV-2 continually mutates, with five identified variants. Many neurological manifestations were observed during the COVID-19 pandemic, with differences between virus variants. The aim of this study is to assess the frequency and characteristics of neurological manifestations during COVID-19 in hospitalized patients over three waves in Poland with comparison and analysis correlation with the course of infection. Methods: This retrospective single-center study included 600 consecutive adults with confirmed COVID-19, hospitalized during 3 waves (pre-Delta, Delta and Omicron) in Poland. Demographic and clinical information and neurological manifestations were collected and compared across three periods. Results: The median age of the study group was 68, lower during the Delta wave. In the Omicron period, the disease severity at admission and inflammatory markers concentration were the lowest. Neurological manifestations were observed in 49%. The most common were altered mentation, headache, myalgia, mood disorder, ischemic stroke and encephalopathy. Smell and taste disturbances (STDs) were less frequent in the Omicron period. Neurological complications were predominant in the pre-Delta and Omicron periods. Ischemic stroke was observed more often in pre-Delta period. Altered mentation was related to higher severity at admission, worse lab test results, higher admission to ICU and mortality, while headache reduced mortality. Pre-existing dementia was related to higher mortality. Conclusions: Neurological manifestations of COVID-19 are frequent, with a lower rate of STDs in the Omicron period and more often cerebrovascular diseases in the pre-Delta period. Headache improves the course of COVID-19, while altered mentation, stroke and neurological comorbidities increase severity and mortality.
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Affiliation(s)
- Justyna Jachman-Kapułka
- 6th Department of Internal Medicine and Rheumatology, J. Gromkowski Specialist Regional Hospital, 51-149 Wroclaw, Poland
| | - Aleksander Zińczuk
- 1st Department of Infectious Diseases, J. Gromkowski Specialist Regional Hospital, 51-149 Wroclaw, Poland; (A.Z.); (W.S.); (K.S.)
| | - Wojciech Szymański
- 1st Department of Infectious Diseases, J. Gromkowski Specialist Regional Hospital, 51-149 Wroclaw, Poland; (A.Z.); (W.S.); (K.S.)
- Clinical Department of Infectious Diseases and Hepatology, Wroclaw Medical University, 50-369 Wroclaw, Poland
| | - Krzysztof Simon
- 1st Department of Infectious Diseases, J. Gromkowski Specialist Regional Hospital, 51-149 Wroclaw, Poland; (A.Z.); (W.S.); (K.S.)
- Clinical Department of Infectious Diseases and Hepatology, Wroclaw Medical University, 50-369 Wroclaw, Poland
| | - Marta Rorat
- Department of Social Sciences and Infectious Diseases, Medical Faculty, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland;
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Mahin A, Soman SP, Modi PK, Raju R, Keshava Prasad TS, Abhinand CS. Meta-analysis of the serum/plasma proteome identifies significant associations between COVID-19 with Alzheimer's/Parkinson's diseases. J Neurovirol 2024; 30:57-70. [PMID: 38167982 DOI: 10.1007/s13365-023-01191-7] [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: 10/14/2023] [Revised: 11/22/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024]
Abstract
In recent years, we have seen the widespread devastations and serious health complications manifested by COVID-19 globally. Although we have effectively controlled the pandemic, uncertainties persist regarding its potential long-term effects, including prolonged neurological issues. To gain comprehensive insights, we conducted a meta-analysis of mass spectrometry-based proteomics data retrieved from different studies with a total of 538 COVID-19 patients and 523 healthy controls. The meta-analysis revealed that top-enriched pathways were associated with neurological disorders, including Alzheimer's (AD) and Parkinson's disease (PD). Further analysis confirmed a direct correlation in the expression patterns of 24 proteins involved in Alzheimer's and 23 proteins in Parkinson's disease with COVID-19. Protein-protein interaction network and cluster analysis identified SNCA as a hub protein, a known biomarker for Parkinson's disease, in both AD and PD. To the best of our knowledge, this is the first meta-analysis study providing proteomic profiling evidence linking COVID-19 to neurological complications.
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Affiliation(s)
- Althaf Mahin
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to Be University), Mangalore, 575018, India
| | - Sreelakshmi Pathappillil Soman
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to Be University), Mangalore, 575018, India
| | - Prashant Kumar Modi
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to Be University), Mangalore, 575018, India
| | - Rajesh Raju
- Centre for Integrative Omics Data Science, Yenepoya (Deemed to Be University), Mangalore, Karnataka, 575018, India.
| | | | - Chandran S Abhinand
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to Be University), Mangalore, 575018, India.
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Smadi M, Kaburis M, Schnapper Y, Reina G, Molero P, Molendijk ML. SARS-CoV-2 susceptibility and COVID-19 illness course and outcome in people with pre-existing neurodegenerative disorders: systematic review with frequentist and Bayesian meta-analyses. Br J Psychiatry 2023:1-14. [PMID: 37183681 DOI: 10.1192/bjp.2023.43] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND People with neurodegenerative disease and mild cognitive impairment (MCI) may have an elevated risk of acquiring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and may be disproportionally affected by coronavirus disease 2019 (COVID-19) once infected. AIMS To review all eligible studies and quantify the strength of associations between various pre-existing neurodegenerative disorders and both SARS-CoV-2 susceptibility and COVID-19 illness course and outcome. METHOD Pre-registered systematic review with frequentist and Bayesian meta-analyses. Systematic searches were executed in PubMed, Web of Science and preprint servers. The final search date was 9 January 2023. Odds ratios (ORs) were used as measures of effect. RESULTS In total, 136 primary studies (total sample size n = 97 643 494), reporting on 268 effect-size estimates, met the inclusion criteria. The odds for a positive SARS-CoV-2 test result were increased for people with pre-existing dementia (OR = 1.83, 95% CI 1.16-2.87), Alzheimer's disease (OR = 2.86, 95% CI 1.44-5.66) and Parkinson's disease (OR = 1.65, 95% CI 1.34-2.04). People with pre-existing dementia were more likely to experience a relatively severe COVID-19 course, once infected (OR = 1.43, 95% CI 1.00-2.03). People with pre-existing dementia or Alzheimer's disease were at increased risk for COVID-19-related hospital admission (pooled OR range: 1.60-3.72). Intensive care unit admission rates were relatively low for people with dementia (OR = 0.54, 95% CI 0.40-0.74). All neurodegenerative disorders, including MCI, were at higher risk for COVID-19-related mortality (pooled OR range: 1.56-2.27). CONCLUSIONS Our findings confirm that, in general, people with neurodegenerative disease and MCI are at a disproportionally high risk of contracting COVID-19 and have a poor outcome once infected.
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Affiliation(s)
- Muhannad Smadi
- Institute of Psychology, Department of Clinical Psychology, Leiden University, Leiden, The Netherlands
| | - Melina Kaburis
- Institute of Psychology, Department of Clinical Psychology, Leiden University, Leiden, The Netherlands
| | - Youval Schnapper
- Institute of Psychology, Department of Clinical Psychology, Leiden University, Leiden, The Netherlands
| | - Gabriel Reina
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain; and Clínica Universidad de Navarra, Department of Microbiology, Pamplona, Spain
| | - Patricio Molero
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain; and Clínica Universidad de Navarra, Department of Psychiatry and Medical Psychology, Pamplona, Spain
| | - Marc L Molendijk
- Institute of Psychology, Department of Clinical Psychology, Leiden University, Leiden, The Netherlands; and Leiden Institute for Brain and Cognition, Leiden University Medical Centre, Leiden, The Netherlands
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Kwiatkowska A, Granicka LH. Anti-Viral Surfaces in the Fight against the Spread of Coronaviruses. MEMBRANES 2023; 13:membranes13050464. [PMID: 37233525 DOI: 10.3390/membranes13050464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 04/22/2023] [Accepted: 04/24/2023] [Indexed: 05/27/2023]
Abstract
This review is conducted against the background of nanotechnology, which provides us with a chance to effectively combat the spread of coronaviruses, and which primarily concerns polyelectrolytes and their usability for obtaining protective function against viruses and as carriers for anti-viral agents, vaccine adjuvants, and, in particular, direct anti-viral activity. This review covers nanomembranes in the form of nano-coatings or nanoparticles built of natural or synthetic polyelectrolytes--either alone or else as nanocomposites for creating an interface with viruses. There are not a wide variety of polyelectrolytes with direct activity against SARS-CoV-2, but materials that are effective in virucidal evaluations against HIV, SARS-CoV, and MERS-CoV are taken into account as potentially active against SARS-CoV-2. Developing new approaches to materials as interfaces with viruses will continue to be relevant in the future.
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Affiliation(s)
- Angelika Kwiatkowska
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4 St., 02-109 Warsaw, Poland
| | - Ludomira H Granicka
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4 St., 02-109 Warsaw, Poland
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Zsichla L, Müller V. Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors. Viruses 2023; 15:175. [PMID: 36680215 PMCID: PMC9863423 DOI: 10.3390/v15010175] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 01/04/2023] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.
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Affiliation(s)
- Levente Zsichla
- Institute of Biology, Eötvös Loránd University, 1117 Budapest, Hungary
- National Laboratory for Health Security, Eötvös Loránd University, 1117 Budapest, Hungary
| | - Viktor Müller
- Institute of Biology, Eötvös Loránd University, 1117 Budapest, Hungary
- National Laboratory for Health Security, Eötvös Loránd University, 1117 Budapest, Hungary
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Mavragani A, Hardy F, Tucker K, Hopper A, Marchã MJM, Navaratnam AV, Briggs TWR, Yates J, Day J, Wheeler A, Eve-Jones S, Gray WK. Frailty, Comorbidity, and Associations With In-Hospital Mortality in Older COVID-19 Patients: Exploratory Study of Administrative Data. Interact J Med Res 2022; 11:e41520. [PMID: 36423306 PMCID: PMC9746678 DOI: 10.2196/41520] [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: 07/29/2022] [Revised: 11/22/2022] [Accepted: 11/24/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Older adults have worse outcomes following hospitalization with COVID-19, but within this group there is substantial variation. Although frailty and comorbidity are key determinants of mortality, it is less clear which specific manifestations of frailty and comorbidity are associated with the worst outcomes. OBJECTIVE We aimed to identify the key comorbidities and domains of frailty that were associated with in-hospital mortality in older patients with COVID-19 using models developed for machine learning algorithms. METHODS This was a retrospective study that used the Hospital Episode Statistics administrative data set from March 1, 2020, to February 28, 2021, for hospitalized patients in England aged 65 years or older. The data set was split into separate training (70%), test (15%), and validation (15%) data sets during model development. Global frailty was assessed using the Hospital Frailty Risk Score (HFRS) and specific domains of frailty were identified using the Global Frailty Scale (GFS). Comorbidity was assessed using the Charlson Comorbidity Index (CCI). Additional features employed in the random forest algorithms included age, sex, deprivation, ethnicity, discharge month and year, geographical region, hospital trust, disease severity, and International Statistical Classification of Disease, 10th Edition codes recorded during the admission. Features were selected, preprocessed, and input into a series of random forest classification algorithms developed to identify factors strongly associated with in-hospital mortality. Two models were developed; the first model included the demographic, hospital-related, and disease-related items described above, as well as individual GFS domains and CCI items. The second model was similar to the first but replaced the GFS domains and CCI items with the HFRS as a global measure of frailty. Model performance was assessed using the area under the receiver operating characteristic (AUROC) curve and measures of model accuracy. RESULTS In total, 215,831 patients were included. The model using the individual GFS domains and CCI items had an AUROC curve for in-hospital mortality of 90% and a predictive accuracy of 83%. The model using the HFRS had similar performance (AUROC curve 90%, predictive accuracy 82%). The most important frailty items in the GFS were dementia/delirium, falls/fractures, and pressure ulcers/weight loss. The most important comorbidity items in the CCI were cancer, heart failure, and renal disease. CONCLUSIONS The physical manifestations of frailty and comorbidity, particularly a history of cognitive impairment and falls, may be useful in identification of patients who need additional support during hospitalization with COVID-19.
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Affiliation(s)
| | - Flavien Hardy
- Getting It Right First Time programme, National Health Service England and National Health Service Improvement, London, United Kingdom
| | - Katie Tucker
- Innovation and Intelligent Automation Unit, Royal Free London National Health Service Foundation Trust, London, United Kingdom
| | - Adrian Hopper
- Getting It Right First Time programme, National Health Service England and National Health Service Improvement, London, United Kingdom.,Guy's and St Thomas' National Health Service Foundation Trust, London, United Kingdom
| | - Maria J M Marchã
- Science and Technology Facilities Council Distributed Research Utilising Advanced Computing High Performance Computing Facility, University College London, London, United Kingdom
| | - Annakan V Navaratnam
- University College London Hospitals National Health Service Foundation Trust, London, United Kingdom
| | - Tim W R Briggs
- Getting It Right First Time programme, National Health Service England and National Health Service Improvement, London, United Kingdom.,Royal National Orthopaedic Hospital National Health Service Trust, London, United Kingdom
| | - Jeremy Yates
- Department of Computer Science, University College London, London, United Kingdom
| | - Jamie Day
- Getting It Right First Time programme, National Health Service England and National Health Service Improvement, London, United Kingdom
| | - Andrew Wheeler
- Getting It Right First Time programme, National Health Service England and National Health Service Improvement, London, United Kingdom
| | - Sue Eve-Jones
- Getting It Right First Time programme, National Health Service England and National Health Service Improvement, London, United Kingdom
| | - William K Gray
- Getting It Right First Time programme, National Health Service England and National Health Service Improvement, London, United Kingdom
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Cascini S, Agabiti N, Marino C, Acampora A, Balducci M, Calandrini E, Davoli M, Bargagli AM. Incidence and Outcomes of SARS-CoV-2 Infection in Older Adults Living with Dementia: A Population-Based Cohort Study. J Alzheimers Dis 2022; 89:681-693. [PMID: 35912744 PMCID: PMC9535569 DOI: 10.3233/jad-220369] [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] [Indexed: 01/10/2023]
Abstract
Background: The identification of risk factors for SARS-CoV-2 infection and mortality in patients with dementia is a key aspect to support clinical decisions and public health interventions. Objective: To assess the incidence of SARS-CoV-2 infection and COVID-19 related death in a cohort of patients with dementia residing in the Lazio region and to investigate predicting factors for both infection and mortality. Methods: This population-based study used information from administrative databases and the SARS-CoV-2 infection surveillance system. Patients with dementia (age ≥65) were enrolled as of December 31, 2019 and followed-up until February 28, 2021. Cumulative risk of infection and death within 60 days of infection onset, and age-standardized incidence (SIR) and mortality (SMR) ratios were calculated. Logistic regression models were applied to identify factors associated with infection and mortality. Results: Among 37,729 dementia patients, 2,548 had a diagnosis of SARS-CoV-2 infection. The crude risk of infection was 6.7%. An increase in risk of infection was observed both in women (SIR 1.72; 95% CI 1.64–1.80) and men (SIR 1.43; 95% CI 1.33–1.54). Pneumonia, cerebrovascular and blood diseases, femur fracture, anxiety, antipsychotic and antithrombotic use were associated with an increased risk of infection. The crude risk of death was 31.0%, the SMRs 2.32 (95% CI 2.05–2.65) for men, and 2.82 (95% CI 2.55–3.11) for women. Factors associated with mortality included: male gender, age ≥85, symptoms at the diagnosis, antipsychotic and systemic antibiotics treatment. Conclusion: These findings emphasize the need of close and tailored monitoring of dementia patients to reduce the impact of COVID-19 on this fragile population.
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Affiliation(s)
- Silvia Cascini
- Department of Epidemiology of the Regional HealthService-Lazio, Rome, Italy
| | - Nera Agabiti
- Department of Epidemiology of the Regional HealthService-Lazio, Rome, Italy
| | - Claudia Marino
- Department of Epidemiology of the Regional HealthService-Lazio, Rome, Italy
| | - Anna Acampora
- Department of Epidemiology of the Regional HealthService-Lazio, Rome, Italy
| | - Maria Balducci
- Department of Epidemiology of the Regional HealthService-Lazio, Rome, Italy
| | - Enrico Calandrini
- Department of Epidemiology of the Regional HealthService-Lazio, Rome, Italy
| | - Marina Davoli
- Department of Epidemiology of the Regional HealthService-Lazio, Rome, Italy
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Morales Chacón LM, Galán García L, Cruz Hernández TM, Pavón Fuentes N, Maragoto Rizo C, Morales Suarez I, Morales Chacón O, Abad Molina E, Rocha Arrieta L. Clinical Phenotypes and Mortality Biomarkers: A Study Focused on COVID-19 Patients with Neurological Diseases in Intensive Care Units. Behav Sci (Basel) 2022; 12:234. [PMID: 35877304 PMCID: PMC9312189 DOI: 10.3390/bs12070234] [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: 06/01/2022] [Revised: 06/30/2022] [Accepted: 07/05/2022] [Indexed: 12/10/2022] Open
Abstract
Purpose: To identify clinical phenotypes and biomarkers for best mortality prediction considering age, symptoms and comorbidities in COVID-19 patients with chronic neurological diseases in intensive care units (ICUs). Subjects and Methods: Data included 1252 COVID-19 patients admitted to ICUs in Cuba between January and August 2021. A k-means algorithm based on unsupervised learning was used to identify clinical patterns related to symptoms, comorbidities and age. The Stable Sparse Classifiers procedure (SSC) was employed for predicting mortality. The classification performance was assessed using the area under the receiver operating curve (AUC). Results: Six phenotypes using a modified v-fold cross validation for the k-means algorithm were identified: phenotype class 1, mean age 72.3 years (ys)-hypertension and coronary artery disease, alongside typical COVID-19 symptoms; class 2, mean age 63 ys-asthma, cough and fever; class 3, mean age 74.5 ys-hypertension, diabetes and cough; class 4, mean age 67.8 ys-hypertension and no symptoms; class 5, mean age 53 ys-cough and no comorbidities; class 6, mean age 60 ys-without symptoms or comorbidities. The chronic neurological disease (CND) percentage was distributed in the six phenotypes, predominantly in phenotypes of classes 3 (24.72%) and 4 (35,39%); χ² (5) 11.0129 p = 0.051134. The cerebrovascular disease was concentrated in classes 3 and 4; χ² (5) = 36.63, p = 0.000001. The mortality rate totaled 325 (25.79%), of which 56 (17.23%) had chronic neurological diseases. The highest in-hospital mortality rates were found in phenotypes 1 (37.22%) and 3 (33.98%). The SSC revealed that a neurological symptom (ageusia), together with two neurological diseases (cerebrovascular disease and Parkinson's disease), and in addition to ICU days, age and specific symptoms (fever, cough, dyspnea and chilliness) as well as particular comorbidities (hypertension, diabetes and asthma) indicated the best prediction performance (AUC = 0.67). Conclusions: The identification of clinical phenotypes and mortality biomarkers using practical variables and robust statistical methodologies make several noteworthy contributions to basic and experimental investigations for distinguishing the COVID-19 clinical spectrum and predicting mortality.
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Affiliation(s)
| | | | | | - Nancy Pavón Fuentes
- International Center for Neurological Restoration, Havana 11300, Cuba; (N.P.F.); (C.M.R.); (E.A.M.)
| | - Carlos Maragoto Rizo
- International Center for Neurological Restoration, Havana 11300, Cuba; (N.P.F.); (C.M.R.); (E.A.M.)
| | | | - Odalys Morales Chacón
- Languages Center, Technological University of Havana Jose Antonio Echeverria, La Habana 3H3M+XJ6, Cuba;
| | - Elianne Abad Molina
- International Center for Neurological Restoration, Havana 11300, Cuba; (N.P.F.); (C.M.R.); (E.A.M.)
| | - Luisa Rocha Arrieta
- Center for Research and Advanced Studies México, Ciudad de México 14330, Mexico;
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Laudanski K, Hajj J, Restrepo M, Siddiq K, Okeke T, Rader DJ. Dynamic Changes in Central and Peripheral Neuro-Injury vs. Neuroprotective Serum Markers in COVID-19 Are Modulated by Different Types of Anti-Viral Treatments but Do Not Affect the Incidence of Late and Early Strokes. Biomedicines 2021; 9:1791. [PMID: 34944606 PMCID: PMC8698659 DOI: 10.3390/biomedicines9121791] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/15/2021] [Accepted: 11/19/2021] [Indexed: 01/07/2023] Open
Abstract
The balance between neurodegeneration, neuroinflammation, neuroprotection, and COVID-19-directed therapy may underly the heterogeneity of SARS-CoV-2's neurological outcomes. A total of 105 patients hospitalized with a diagnosis of COVID-19 had serum collected over a 6 month period to assess neuroinflammatory (MIF, CCL23, MCP-1), neuro-injury (NFL, NCAM-1), neurodegenerative (KLK6, τ, phospho τ, amyloids, TDP43, YKL40), and neuroprotective (clusterin, fetuin, TREM-2) proteins. These were compared to markers of nonspecific inflammatory responses (IL-6, D-dimer, CRP) and of the overall viral burden (spike protein). Data regarding treatment (steroids, convalescent plasma, remdasavir), pre-existing conditions, and incidences of strokes were collected. Amyloid β42, TDP43, NF-L, and KLK6 serum levels declined 2-3 days post-admission, yet recovered to admission baseline levels by 7 days. YKL-40 and NCAM-1 levels remained elevated over time, with clusters of differential responses identified among TREM-2, TDP43, and YKL40. Fetuin was elevated after the onset of COVID-19 while TREM-2 initially declined before significantly increasing over time. MIF serum level was increased 3-7 days after admission. Ferritin correlated with TDP-43 and KLK6. No treatment with remdesivir coincided with elevations in Amyloid-β40. A lack of convalescent plasma resulted in increased NCAM-1 and total tau, and steroidal treatments did not significantly affect any markers. A total of 11 incidences of stroke were registered up to six months after initial admission for COVID-19. Elevated D-dimer, platelet counts, IL-6, and leukopenia were observed. Variable MIF serum levels differentiated patients with CVA from those who did not have a stroke during the acute phase of COVID-19. This study demonstrated concomitant and opposite changes in neurodegenerative and neuroprotective markers persisting well into recovery.
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Affiliation(s)
- Krzysztof Laudanski
- The Department of Anesthesiology and Critical Care Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jihane Hajj
- School of Nursing, Widener University, Philadelphia, PA 19013, USA;
| | - Mariana Restrepo
- College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Kumal Siddiq
- College of Arts and Sciences, Drexel University, Philadelphia, PA 19104, USA;
| | - Tony Okeke
- School of Biomedical Engineering, Drexel University, Philadelphia, PA 19104, USA;
| | - Daniel J. Rader
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA;
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