Cognitive impairment in COVID‐19 Survivors: Analysis and Extensions on Population Studies in Greece

Background The aim of our study was to investigate the prevalence and associations of cognitive impairment in COVID‐19 survivors in the post‐acute setting. Method Our study is conducted in three post‐COVID‐19 outpatient clinics in tertiary hospitals in Greece. Eligible subjects included previously hospitalized COVID‐19 survivors with mild to moderate disease, returning for follow‐up at least two months post‐discharge. Exclusion criteria included intensive care unit admission, intubation, a history of neurodegenerative disease and other significant comorbidities. Study measurements included demographics, clinical evaluation, medical, family history, anthropometrics, 6‐minute walk test (6MWT), 30 seconds sit‐to‐stand (30STS), handgrip strength, spirometry, Pittsburgh Sleep Quality Index (PSQI), the Montreal Cognitive Assessment (MoCA), reactive oxygen metabolites (dROMs) and plasma antioxidant capacity (PAT). Cognitive impairment was considered on MoCA ≤24. Result 142 COVID‐19 survivors were included in the study (110 Male, 32 Female;Mean age of 56.16±10.92). A total of 47.2% presented with cognitive decline (CD) as indicated by a MoCA score ≤24. Cognitive decline prevalence by SARS‐CoV‐2 variant of concern (VOC) was 39.5%, 50% and 62.5% for Alpha, Beta and Delta, correspondingly. A binary logistic regression model controlling for age, gender and VOC indicated that the diffusing capacity for carbon monoxide (DLCO) was independently associated with MoCA ≤24 (p = 0.014, OR = 0.669, 95%CI: 0.484‐0.923). Compared to severe untreated OSAS (n = 28), distinct domains but similar prevalence of cognitive impairment was noted. Conclusion Diffusion capacity abnormalities for carbon monoxide in COVID‐19 survivors as noted in other studies, may be implicated in the development of cognitive impairment.

Post-COVID-19 Parkinsonism and Parkinson's Disease Pathogenesis: The Exosomal Cargo Hypothesis.

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.

COVID-19 Phenotypes and Comorbidity: A Data-Driven, Pattern Recognition Approach Using National Representative Data from the United States.

The aim of our study was to determine COVID-19 syndromic phenotypes in a data-driven manner using the survey results based on survey results from Carnegie Mellon University's Delphi Group. Monthly survey results (>1 million responders per month; 320,326 responders with a certain COVID-19 test status and disease duration <30 days were included in this study) were used sequentially in identifying and validating COVID-19 syndromic phenotypes. Logistic Regression-weighted multiple correspondence analysis (LRW-MCA) was used as a preprocessing procedure, in order to weigh and transform symptoms recorded by the survey to eigenspace coordinates, capturing a total variance of >75%. These scores, along with symptom duration, were subsequently used by the Two Step Clustering algorithm to produce symptom clusters. Post-hoc logistic regression models adjusting for age, gender, and comorbidities and confirmatory linear principal components analyses were used to further explore the data. Model creation, based on August's 66,165 included responders, was subsequently validated in data from March-December 2020. Five validated COVID-19 syndromes were identified in August: 1. Afebrile (0%), Non-Coughing (0%), Oligosymptomatic (ANCOS); 2. Febrile (100%) Multisymptomatic (FMS); 3. Afebrile (0%) Coughing (100%) Oligosymptomatic (ACOS); 4. Oligosymptomatic with additional self-described symptoms (100%; OSDS); 5. Olfaction/Gustatory Impairment Predominant (100%; OGIP). Our findings indicate that the COVID-19 spectrum may be undetectable when applying current disease definitions focusing on respiratory symptoms alone.

PM2.5 Pollution Strongly Predicted COVID-19 Incidence in Four High-Polluted Urbanized Italian Cities during the Pre-Lockdown and Lockdown Periods.

BACKGROUND: The coronavirus disease in 2019 (COVID-19) heavily hit Italy, one of Europe's most polluted countries. The extent to which PM pollution contributed to COVID-19 diffusion is needing further clarification. We aimed to investigate the particular matter (PM) pollution and its correlation with COVID-19 incidence across four Italian cities: Milan, Rome, Naples, and Salerno, during the pre-lockdown and lockdown periods. METHODS: We performed a comparative analysis followed by correlation and regression analyses of the daily average PM10, PM2.5 concentrations, and COVID-19 incidence across four cities from 1 January 2020 to 8 April 2020, adjusting for several factors, taking a two-week time lag into account. RESULTS: Milan had significantly higher average daily PM10 and PM2.5 levels than Rome, Naples, and Salerno. Rome, Naples, and Salerno maintained safe PM10 levels. The daily PM2.5 levels exceeded the legislative standards in all cities during the entire period. PM2.5 pollution was related to COVID-19 incidence. The PM2.5 levels and sampling rate were strong predictors of COVID-19 incidence during the pre-lockdown period. The PM2.5 levels, population's age, and density strongly predicted COVID-19 incidence during lockdown. CONCLUSIONS: Italy serves as a noteworthy paradigm illustrating that PM2.5 pollution impacts COVID-19 spread. Even in lockdown, PM2.5 levels negatively impacted COVID-19 incidence.

In silico investigation of the viroporin E as a vaccine target against SARS-CoV-2.

Viroporins, integral viral membrane ion channel proteins, interact with host-cell proteins deregulating physiological processes and activating inflammasomes. Severity of COVID-19 might be associated with hyperinflammation, thus we aimed at the complete immunoinformatic analysis of the SARS-CoV-2 viroporin E, P0DTC4. We also identified the human proteins interacting with P0DTC4 and the enriched molecular functions of the corresponding genes. The complete sequence of P0DTC4 in FASTA format was processed in 10 databases relative to secondary and tertiary protein structure analyses and prediction of optimal vaccine epitopes. Three more databases were accessed for the retrieval and the molecular functional characterization of the P0DTC4 human interactors. The immunoinformatics analysis resulted in the identification of 4 discontinuous B-cell epitopes along with 1 linear B-cell epitope and 11 T-cell epitopes which were found to be antigenic, immunogenic, nonallergen, nontoxin, and unable to induce autoimmunity thus fulfilling prerequisites for vaccine design. The functional enrichment analysis showed that the predicted host interactors of P0DTC4 target the cellular acetylation network. Two of the identified host-cell proteins - BRD2 and BRD4 - have been shown to be promising targets for antiviral therapy. Thus, our findings have implications for COVID-19 therapy and indicate that viroporin E could serve as a promising vaccine target against SARS-CoV-2. Validation experiments are required to complement these in silico results.

Outside-in induction of the IFITM3 trafficking system by infections, including SARS-CoV-2, in the pathobiology of Alzheimer's disease.

BACKGROUND: IFITM3 is a viral restriction protein that enables sequestration of viral particles and subsequent trafficking to lysosomes. Recently, IFITM3 upregulation was found to induce gamma - secretase activity and the production of amyloid beta. The purpose of this study was to determine whether dysregulation of IFITM3-dependent pathways was present in neurons and peripheral immune cells donated by AD patients. As a secondary aim, we sought to determine whether these perturbations could be induced by viruses, including SARS-CoV-2. METHODS: Gene set enrichment analyses (GSEA) previously performed on publicly available transcriptomic data from tissues donated by AD patients were screened for enriched pathways containing IFITM3. Subsequently, signature containing IFITM3, derived from entorhinal cortex (EC) neurons containing neurofibrillary tangles (NFT) was screened for overlap with curated, publicly available, viral infection-induced gene signatures (including SARS-CoV-2). RESULTS: GSEA determined that IFITM3 gene networks are significantly enriched both in CNS sites (entorhinal and hippocampal cortices) and in peripheral blood mononuclear cells (PBMCs) donated by AD patients. Overlap screening revealed that IFITM3 signatures are induced by several viruses, including SARS-CoV, MERS-CoV, SARS-CoV-2 and HIV-1 (adjusted p-value <0.001; Enrichr Database). DISCUSSION: A data-driven analysis of AD tissues revealed IFITM3 gene signatures both in the CNS and in peripheral immune cells. GSEA revealed that an IFITM3 derived gene signature extracted from EC/NFT neurons overlapped with those extracted from publicly available viral infection datasets, including SARS-CoV-2. Our results are in line with currently emerging evidence on IFITM3's role in AD, and SARS-CoV-2's potential contribution in the setting of an expanded antimicrobial protection hypothesis.