Cholesterol, lipoproteins, and COVID-19: Basic concepts and clinical applications

Associations of Temporal Cardiometabolic Patterns and Incident SARS-CoV-2 Infection Among U.S. Blood Donors With Serologic Evidence of Vaccination

Introduction

Cardiometabolic diseases are associated with greater COVID-19 severity; however, the influences of cardiometabolic health on SARS-CoV-2 infections after vaccination remain unclear. Our objective was to investigate the associations between temporal blood pressure and total cholesterol patterns and incident SARS-CoV-2 infections among those with serologic evidence of vaccination.

Methods

In this prospective cohort of blood donors, blood samples were collected in 2020-2021 and assayed for binding antibodies of SARS-CoV-2 nucleocapsid protein antibody seropositivity. We categorized participants into intraindividual pattern subgroups of blood pressure and total cholesterol (persistently, intermittently, or not elevated [systolic blood pressure <130 mmHg, diastolic blood pressure <80 mmHg, total cholesterol <200 mg/dL]) across the study time points.

Results

Among 13,930 donors with 39,736 donations representing 1,127,071 person-days, there were 221 incident SARS-CoV-2 infections among those with serologic evidence of vaccination (1.6%). Intermittent hypertension was associated with greater SARS-CoV-2 infections among those with serologic evidence of vaccination risk (adjusted incidence rate ratio=2.07; 95% CI=1.44, 2.96; p<0.01) than among participants with consistent normotension on the basis of a multivariable Poisson regression. Among men, intermittently elevated total cholesterol (adjusted incidence rate ratio=1.90; 95% CI=1.32, 2.74; p<0.01) and higher BMI at baseline (adjusted hazard ratio=1.44; 95% CI=1.07, 1.93; p=0.01; per 10 units) were associated with greater SARS-CoV-2 infections among those with serologic evidence of vaccination probability; these associations were null among women (both p>0.05).

Conclusions

Our findings underscore that the benefits of cardiometabolic health, particularly blood pressure, include a lower risk of SARS-CoV-2 infection after vaccination.

Novel COVID-19 biomarkers identified through multi-omics data analysis: N-acetyl-4-O-acetylneuraminic acid, N-acetyl-L-alanine, N-acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate

This study aims to apply machine learning models to identify new biomarkers associated with the early diagnosis and prognosis of SARS-CoV-2 infection.Plasma and serum samples from COVID-19 patients (mild, moderate, and severe), patients with other pneumonia (but with negative COVID-19 RT-PCR), and healthy volunteers (control) from hospitals in four different countries (China, Spain, France, and Italy) were analyzed by GC-MS, LC-MS, and NMR. Machine learning models (PCA and PLS-DA) were developed to predict the diagnosis and prognosis of COVID-19 and identify biomarkers associated with these outcomes.A total of 1410 patient samples were analyzed. The PLS-DA model presented a diagnostic and prognostic accuracy of around 95% of all analyzed data. A total of 23 biomarkers (e.g., spermidine, taurine, L-aspartic, L-glutamic, L-phenylalanine and xanthine, ornithine, and ribothimidine) have been identified as being associated with the diagnosis and prognosis of COVID-19. Additionally, we also identified for the first time five new biomarkers (N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate) that are also associated with the severity and diagnosis of COVID-19. These five new biomarkers were elevated in severe COVID-19 patients compared to patients with mild disease or healthy volunteers.The PLS-DA model was able to predict the diagnosis and prognosis of COVID-19 around 95%. Additionally, our investigation pinpointed five novel potential biomarkers linked to the diagnosis and prognosis of COVID-19: N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate. These biomarkers exhibited heightened levels in severe COVID-19 patients compared to those with mild COVID-19 or healthy volunteers.

Cholesterol: A friend to viruses

Cholesterol is a key life-sustaining molecule which regulates membrane fluidity and serves as a signaling mediator. Cholesterol homeostasis is closely related to various pathological conditions including tumor, obesity, atherosclerosis, Alzheimer's disease and viral infection. Viral infection disrupts host cholesterol homeostasis, facilitating their own survival. Meanwhile, the host cells strive to reduce cholesterol accessibility to limit viral infection. This review focuses on the regulation of cholesterol metabolism and the role of cholesterol in viral infection, specifically providing an overview of cholesterol as a friend to promote viral entry, replication, assembly, release and immune evasion, which might inspire valuable thinking for pathogenesis and intervention of viral infection.

Identifying diseases associated with Post-COVID syndrome through an integrated network biology approach

A growing body of research shows that COVID-19 is now recognized as a multi-organ disease with a wide range of manifestations that can have long-lasting repercussions, referred to as post-COVID-19 syndrome. It is unknown why the vast majority of COVID-19 patients develop post-COVID-19 syndrome, or why patients with pre-existing disorders are more likely to experience severe COVID-19. This study used an integrated network biology approach to obtain a comprehensive understanding of the relationship between COVID-19 and other disorders. The approach involved building a PPI network with COVID-19 genes and identifying highly interconnected regions. The molecular information contained within these subnetworks, as well as the pathway annotations, were used to reveal the link between COVID-19 and other disorders. Using Fisher's exact test and disease-specific gene information, significant COVID-19-disease associations were discovered. The study discovered diseases that affect multiple organs and organ systems, thus proving the theory of multiple organ damage caused by COVID-19. Cancers, neurological disorders, hepatic diseases, cardiac disorders, pulmonary diseases, and hypertensive diseases are just a few of the conditions linked to COVID-19. Pathway enrichment analysis of shared proteins revealed the shared molecular mechanism of COVID-19 and these diseases. The findings of the study shed new light on the major COVID-19-associated disease conditions and how their molecular mechanisms interact with COVID-19. The novelty of studying disease associations in the context of COVID-19 provides new insights into the management of rapidly evolving long-COVID and post-COVID syndromes, which have significant global implications.Communicated by Ramaswamy H. Sarma.

Research Advances on the Role of Lipids in the Life Cycle of Human Coronaviruses

Coronaviruses (CoVs) are emerging pathogens with a significant potential to cause life-threatening harm to human health. Since the beginning of the 21st century, three highly pathogenic and transmissible human CoVs have emerged, triggering epidemics and posing major threats to global public health. CoVs are enveloped viruses encased in a lipid bilayer. As fundamental components of cells, lipids can play an integral role in many physiological processes, which have been reported to play important roles in the life cycle of CoVs, including viral entry, uncoating, replication, assembly, and release. Therefore, research on the role of lipids in the CoV life cycle can provide a basis for a better understanding of the infection mechanism of CoVs and provide lipid targets for the development of new antiviral strategies. In this review, research advances on the role of lipids in different stages of viral infection and the possible targets of lipids that interfere with the viral life cycle are discussed.

An overview of the role of Niemann-pick C1 (NPC1) in viral infections and inhibition of viral infections through NPC1 inhibitor

Viruses communicate with their hosts through interactions with proteins, lipids, and carbohydrate moieties on the plasma membrane (PM), often resulting in viral absorption via receptor-mediated endocytosis. Many viruses cannot multiply unless the host's cholesterol level remains steady. The large endo/lysosomal membrane protein (MP) Niemann-Pick C1 (NPC1), which is involved in cellular cholesterol transport, is a crucial intracellular receptor for viral infection. NPC1 is a ubiquitous housekeeping protein essential for the controlled cholesterol efflux from lysosomes. Its human absence results in Niemann-Pick type C disease, a deadly lysosomal storage disorder. NPC1 is a crucial viral receptor and an essential host component for filovirus entrance, infection, and pathogenesis. For filovirus entrance, NPC1's cellular function is unnecessary. Furthermore, blocking NPC1 limits the entry and replication of the African swine fever virus by disrupting cholesterol homeostasis. Cell entrance of quasi-enveloped variants of hepatitis A virus and hepatitis E virus has also been linked to NPC1. By controlling cholesterol levels, NPC1 is also necessary for the effective release of reovirus cores into the cytoplasm. Drugs that limit NPC1's activity are effective against several viruses, including SARS-CoV and Type I Feline Coronavirus (F-CoV). These findings reveal NPC1 as a potential therapeutic target for treating viral illnesses and demonstrate its significance for several viral infections. This article provides a synopsis of NPC1's function in viral infections and a review of NPC1 inhibitors that may be used to counteract viral infections. Video Abstract.

Deep phenotyping of the lipidomic response in COVID-19 and non-COVID-19 sepsis

BACKGROUND

Lipids may influence cellular penetrance by viral pathogens and the immune response that they evoke. We deeply phenotyped the lipidomic response to SARs-CoV-2 and compared that with infection with other pathogens in patients admitted with acute respiratory distress syndrome to an intensive care unit (ICU).

METHODS

Mass spectrometry was used to characterise lipids and relate them to proteins, peripheral cell immunotypes and disease severity.

RESULTS

Circulating phospholipases (sPLA2, cPLA2 (PLA2G4A) and PLA2G2D) were elevated on admission in all ICU groups. Cyclooxygenase, lipoxygenase and epoxygenase products of arachidonic acid (AA) were elevated in all ICU groups compared with controls. sPLA2 predicted severity in COVID-19 and correlated with TxA2, LTE4 and the isoprostane, iPF2α-III, while PLA2G2D correlated with LTE4. The elevation in PGD2, like PGI2 and 12-HETE, exhibited relative specificity for COVID-19 and correlated with sPLA2 and the interleukin-13 receptor to drive lymphopenia, a marker of disease severity. Pro-inflammatory eicosanoids remained correlated with severity in COVID-19 28 days after admission. Amongst non-COVID ICU patients, elevations in 5- and 15-HETE and 9- and 13-HODE reflected viral rather than bacterial disease. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflected disease severity in COVID-19. In healthy marines, these lipids rose with seroconversion. Eicosanoids linked variably to the peripheral cellular immune response. PGE2, TxA2 and LTE4 correlated with T cell activation, as did PGD2 with non-B non-T cell activation. In COVID-19, LPS stimulated peripheral blood mononuclear cell PGF2α correlated with memory T cells, dendritic and NK cells while LA and DiHOMEs correlated with exhausted T cells. Three high abundance lipids - ChoE 18:3, LPC-O-16:0 and PC-O-30:0 - were altered specifically in COVID. LPC-O-16:0 was strongly correlated with T helper follicular cell activation and all three negatively correlated with multi-omic inflammatory pathways and disease severity.

CONCLUSIONS

A broad based lipidomic storm is a predictor of poor prognosis in ARDS. Alterations in sPLA2, PGD2 and 12-HETE and the high abundance lipids, ChoE 18:3, LPC-O-16:0 and PC-O-30:0 exhibit relative specificity for COVID-19 amongst such patients and correlate with the inflammatory response to link to disease severity.

Mitochondrial dysfunction, lipids metabolism, and amino acid biosynthesis are key pathways for COVID-19 recovery

The metabolic alterations caused by SARS-CoV-2 infection reflect disease progression. To analyze molecules involved in these metabolic changes, a multiomics study was performed using plasma from 103 patients with different degrees of COVID-19 severity during the evolution of the infection. With the increased severity of COVID-19, changes in circulating proteomic, metabolomic, and lipidomic profiles increased. Notably, the group of severe and critical patients with high HRG and ChoE (20:3) and low alpha-ketoglutaric acid levels had a high chance of unfavorable disease evolution (AUC = 0.925). Consequently, patients with the worst prognosis presented alterations in the TCA cycle (mitochondrial dysfunction), lipid metabolism, amino acid biosynthesis, and coagulation. Our findings increase knowledge regarding how SARS-CoV-2 infection affects different metabolic pathways and help in understanding the future consequences of COVID-19 to identify potential therapeutic targets.

COVID-19 and cholesterol biosynthesis: Towards innovative decision support systems

With COVID-19 becoming endemic, there is a continuing need to find biomarkers characterizing the disease and aiding in patient stratification. We studied the relation between COVID-19 and cholesterol biosynthesis by comparing 10 intermediates of cholesterol biosynthesis during the hospitalization of 164 patients (admission, disease deterioration, discharge) admitted to the University Medical Center of Ljubljana. The concentrations of zymosterol, 24-dehydrolathosterol, desmosterol, and zymostenol were significantly altered in COVID-19 patients. We further developed a predictive model for disease severity based on clinical parameters alone and their combination with a subset of sterols. Our machine learning models applying 8 clinical parameters predicted disease severity with excellent accuracy (AUC = 0.96), showing substantial improvement over current clinical risk scores. After including sterols, model performance remained better than COVID-GRAM. This is the first study to examine cholesterol biosynthesis during COVID-19 and shows that a subset of cholesterol-related sterols is associated with the severity of COVID-19.

Hyperlipidemia in immune thrombocytopenia: a retrospective study

BACKGROUND

Immune thrombocytopenia (ITP) is an autoimmune hemorrhagic disease characterized by low platelet count and bleeding manifestations. However, some patients also suffered from atherosclerosis or even infarction. Apart from activated platelets, lipid metabolism takes a large part in the formation of atherosclerosis and metabolic syndrome. The lipid metabolic state in ITP patients is still unknown.

METHODS

We retrospectively reviewed 302 hospitalized ITP patients in our cohort, comparing their blood lipids, bleeding symptoms, metabolic diseases and treatment responses.

RESULTS

We found a high proportion of ITP patients suffered from hyperlipidemia, and other metabolic diseases including cardiovascular or cerebral atherosclerosis or infarction, hypertension, and type 2 diabetes. Hyperlipidemia was associated with severe bleeding and treatment refractoriness in ITP. Statins could alleviate thrombocytopenia and bleeding severity, and facilitate ITP treatment, while improving hyperlipidemia in ITP patients.

CONCLUSIONS

Our present study demonstrated that lipid metabolism might play an indispensable role in ITP pathogenesis and development.

Proteomics analysis of lung tissue reveals protein makers for the lung injury of adjuvant arthritis rats

Lung injury is one of the common extra‑articular lesions in rheumatoid arthritis (RA). Due to its insidious onset and no obvious clinical symptoms, it can be easily dismissed in the early stage of diagnosis, which is one of the reasons that leads to a decline of the quality of life and subsequent death of patients with RA. However, its pathogenesis is still unclear and there is a lack of effective therapeutic targets. In the present study, tandem mass tag‑labeled proteomics was used to research the lung tissue proteins in RA model (adjuvant arthritis, AA) rats that had secondary lung injury. The aim of the present study was to identify the differentially expressed proteins related to RA‑lung injury, determine their potential role in the pathogenesis of RA‑lung injury and provide potential targets for clinical treatment. Lung tissue samples were collected from AA‑lung injury and normal rats. The differentially expressed proteins (DEPs) were identified by tandem mass spectrometry. Bioinformatic analysis was used to assess the biological processes and signaling pathways associated with these DEPs. A total of 310 DEPs were found, of which 244 were upregulated and 66 were downregulated. KEGG anlysis showed that 'fatty acid degradation', 'fatty acid metabolism', 'fatty acid elongation', 'complement and coagulation cascades', 'peroxisome proliferator‑activated receptor signaling pathway' and 'hypoxia‑inducible factor signaling pathway' were significantly upregulated in the lung tissues of AA‑lung injury. Immunofluorescence staining confirmed the increased expression of clusterin, serine protease inhibitors and complement 1qc in lung tissue of rats with AA lung injury. In the present study, the results revealed the significance of certain DEPs (for example, C9, C1qc and Clu) in the occurrence and development of RA‑lung injury and provided support through experiments to identify potential biomarkers for the early diagnosis and prevention of RA‑lung injury.

Association of dietary intake of polyphenols, lignans, and phytosterols with immune-stimulating microbiota and COVID-19 risk in a group of Polish men and women

Objectives

Devastating consequences of COVID-19 disease enhanced the role of promoting prevention-focused practices. Among targeted efforts, diet is regarded as one of the potential factors which can affect immune function and optimal nutrition is postulated as the method of augmentation of people's viral resistance. As epidemiological evidence is scarce, the present study aimed to explore the association between dietary intake of total polyphenols, lignans and plant sterols and the abundance of immunomodulatory gut microbiota such as Enterococcus spp. and Escherichia coli and the risk of developing COVID-19 disease.

Methods

Demographic data, dietary habits, physical activity as well as the composition of body and gut microbiota were analyzed in a sample of 95 young healthy individuals. Dietary polyphenol, lignan and plant sterol intakes have been retrieved based on the amount of food consumed by the participants, the phytochemical content was assessed in laboratory analysis and using available databases.

Results

For all investigated polyphenols and phytosterols, except campesterol, every unit increase in the tertile of intake category was associated with a decrease in the odds of contracting COVID-19. The risk reduction ranged from several dozen percent to 70 %, depending on the individual plant-based chemical, and after controlling for basic covariates it was statistically significant for secoisolariciresinol (OR = 0.28, 95% CI: 0.11-0.61), total phytosterols (OR = 0.47, 95% CI: 0.22-0.95) and for stigmasterols (OR = 0.34, 95% CI: 0.14-0.72). We found an inverse association between increased β-sitosterol intake and phytosterols in total and the occurrence of Escherichia coli in stool samples outside reference values, with 72% (OR = 0.28, 95% CI: 0.08-0.86) and 66% (OR = 0.34, 95% CI: 0.10-1.08) reduced odds of abnormal level of bacteria for the highest compared with the lowest tertile of phytochemical consumption. Additionally, there was a trend of more frequent presence of Enterococcus spp. at relevant level in people with a higher intake of lariciresinol.

Conclusion

The beneficial effects of polyphenols and phytosterols should be emphasized and these plant-based compounds should be regarded in the context of their utility as antiviral agents preventing influenza-type infections.

ABO Blood Type and Metabolic Markers in COVID-19 Susceptibility and Severity: A Cross-Sectional Study

Background and Aims: To evaluate the effect of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus on the function and metabolic changes, as well as the relationship of the virus with blood groups. Methods and Results: This cross-sectional study included a matched sample of adult individuals with coronavirus disease 2019 (COVID-19) (n = 114) or without (controls; n = 236). Blood samples were collected and processed for triglycerides (TGs), total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, and blood typing analysis. The results showed that subjects with COVID-19 had higher TG and lower HDL-C levels compared with the control group. As for blood typing, the risk of COVID-19 was higher in subjects with blood group A than in those with blood group B and in those with other blood groups. In addition, an association of COVID-19 with blood type and Rh A- was observed. When related to the severity of COVID-19 symptoms, blood type A was more protective against moderate/severe symptoms compared with blood type O. In addition, individuals with blood type O were 2.90 times more likely to have symptoms moderate/severe symptoms of COVID-19 than those with other blood groups and individuals with type A blood were less likely to have severe/moderate symptoms of COVID-19 compared with individuals without type A blood. Conclusion: The results suggest that blood type may play a role in susceptibility to SARS-CoV-2 infection and add evidence that infection with the novel coronavirus may be associated with changes in lipid metabolism.

Outpatient atorvastatin use and severe COVID-19 outcomes: A population-based study

Evidence of the effect of statins on patients with coronavirus disease (2019) COVID-19 is inconsistent. The aim of this study was to evaluate the association between chronic use of statins-both overall and by active ingredient-and severe outcomes of COVID-19 (risk of hospitalization and mortality), progression to severe outcomes, and susceptibility to the virus. We conducted a population-based case-control study with data from electronic records to assess the risk of (1) hospitalization: cases were patients admitted due to COVID-19 and controls were subjects without COVID-19; (2) mortality: cases were hospitalized patients who died due to COVID-19 and controls were subjects without COVID-19; (3) progression: cases were hospitalized COVID-19 subjects and controls were nonhospitalized COVID-19 patients; and (4) susceptibility: cases were patients with COVID-19 (both hospitalized and nonhospitalized) and controls were subjects without COVID-19. We collected data on 2821 hospitalized cases, 26 996 nonhospitalized cases, and 52 318 controls. Chronic use of atorvastatin was associated with a decreased risk of hospitalization (adjusted odds ratios [aOR] = 0.83; 95% confidence interval [CI]: 0.74-0.92) and mortality (aOR = 0.70; 95% CI: 0.53-0.93), attributable in part to a lower risk of susceptibility to the virus (aOR = 0.91; 95% CI: 0.86-0.96). Simvastatin was associated with a reduced risk of mortality (aOR = 0.59; 95% CI: 0.40-0.87). The wide degree of heterogeneity observed in the estimated odds ratios (ORs) of the different statins suggests that there is no class effect. The results of this real-world study suggest that chronic use of atorvastatin (and to a lesser degree, of simvastatin) is associated with a decrease in risk of severe COVID-19 outcomes.

The Impact of the Serum Extraction Protocol on Metabolomic Profiling Using UPLC-MS/MS and FTIR Spectroscopy

Biofluid metabolomics is a very appealing tool to increase the knowledge associated with pathophysiological mechanisms leading to better and new therapies and biomarkers for disease diagnosis and prognosis. However, due to the complex process of metabolome analysis, including the metabolome isolation method and the platform used to analyze it, there are diverse factors that affect metabolomics output. In the present work, the impact of two protocols to extract the serum metabolome, one using methanol and another using a mixture of methanol, acetonitrile, and water, was evaluated. The metabolome was analyzed by ultraperformance liquid chromatography associated with tandem mass spectrometry (UPLC-MS/MS), based on reverse-phase and hydrophobic chromatographic separations, and Fourier transform infrared (FTIR) spectroscopy. The two extraction protocols of the metabolome were compared over the analytical platforms (UPLC-MS/MS and FTIR spectroscopy) concerning the number of features, the type of features, common features, and the reproducibility of extraction replicas and analytical replicas. The ability of the extraction protocols to predict the survivability of critically ill patients hospitalized at an intensive care unit was also evaluated. The FTIR spectroscopy platform was compared to the UPLC-MS/MS platform and, despite not identifying metabolites and consequently not contributing as much as UPLC-MS/MS in terms of information concerning metabolic information, it enabled the comparison of the two extraction protocols as well as the development of very good predictive models of patient's survivability, such as the UPLC-MS/MS platform. Furthermore, FTIR spectroscopy is based on much simpler procedures and is rapid, economic, and applicable in the high-throughput mode, i.e., enabling the simultaneous analysis of hundreds of samples in the microliter range in a couple of hours. Therefore, FTIR spectroscopy represents a very interesting complementary technique not only to optimize processes as the metabolome isolation but also for obtaining biomarkers such as those for disease prognosis.

Use of data mining approaches to explore the association between type 2 diabetes mellitus with SARS-CoV-2

BACKGROUND AND OBJECTIVE

Corona virus causes respiratory tract infections in mammals. The latest type of Severe Acute Respiratory Syndrome Corona-viruses 2 (SARS-CoV-2), Corona virus spread in humans in December 2019 in Wuhan, China. The purpose of this study was to investigate the relationship between type 2 diabetes mellitus (T2DM), and their biochemical and hematological factors with the level of infection with COVID-19 to improve the treatment and management of the disease.

MATERIAL AND METHOD

This study was conducted on a population of 13,170 including 5780 subjects with SARS-COV-2 and 7390 subjects without SARS-COV-2, in the age range of 35-65 years. Also, the associations between biochemical factors, hematological factors, physical activity level (PAL), age, sex, and smoking status were investigated with the COVID-19 infection.

RESULT

Data mining techniques such as logistic regression (LR) and decision tree (DT) algorithms were used to analyze the data. The results using the LR model showed that in biochemical factors (Model I) creatine phosphokinase (CPK) (OR: 1.006 CI 95% (1.006,1.007)), blood urea nitrogen (BUN) (OR: 1.039 CI 95% (1.033, 1.047)) and in hematological factors (Model II) mean platelet volume (MVP) (OR: 1.546 CI 95% (1.470, 1.628)) were significant factors associated with COVID-19 infection. Using the DT model, CPK, BUN, and MPV were the most important variables. Also, after adjustment for confounding factors, subjects with T2DM had higher risk for COVID-19 infection.

CONCLUSION

There was a significant association between CPK, BUN, MPV and T2DM with COVID-19 infection and T2DM appears to be important in the development of COVID-19 infection.

Post-COVID-19 effect on biochemical parameters in children: Should we take heed?

The aim of this research is to analyze the potential impact of the COVID-19 infection on the serum biochemical concentration of children 6 months after recovery from the infection. The study included 72 children with a median age of 11 years. The case group consisted of 37 children who had contracted COVID-19 6 months prior to the analysis. They reported no other pre- or post-covid chronic or systemic diseases. The control group consisted of 35 children who had no prior record of COVID-19 infection. The analysis showed a substantial variation (P = 0.026) in the mean urea values (mmol/L) between the case group (4.513 ± 0.839) and the control group (5.425 ± 1.173). However, both groups' urea levels were within the normal range of their age group. No statistical differences were found analyzing the variations between the two groups in the levels of LDH, AST, ALT, BiliT, GGT, AlbBCG2, CRP, CK, AlKP, UA, Phos, Crea2, Gluc, Ca, Na, K, Cl, TP, TC, TG, and HDL (P > 0.05). The DMFT score was substantially greater (P < 0.002) in the infected team (5.38 ± 2.841) in comparison to the non-infected group (2.6 ± 2.257). The study indicates that COVID-19 infection does not leave biochemical alterations among children who did not have pre-existing conditions. The biochemical analysis suggests that children recover better than adults from COVID-19. Furthermore, it calls for investigating non-lethal COVID-19 infection as a tool to discover underlying conditions. The DMFT score shows a correlation between COVID-19 infection and caries. However, the nature of the correlation is yet to be investigated.

Effect of Cholesterol on Biomimetic Membrane Curvature and Coronavirus Fusion Peptide Encapsulation

Biomimetic cubic phases can be used for protein encapsulation in a variety of applications such as biosensors and drug delivery. Cubic phases with a high concentration of cholesterol and phospholipids were obtained herein. It is shown that the cubic phase structure can be maintained with a higher concentration of biomimetic membrane additives than has been reported previously. Opposing effects on the curvature of the membrane were observed upon the addition of phospholipids and cholesterol. Furthermore, the coronavirus fusion peptide significantly increased the negative curvature of the biomimetic membrane with cholesterol. We show that the viral fusion peptide can undergo structural changes leading to the formation of hydrophobic α-helices that insert into the lipid bilayer. This is of high importance, as a fusion peptide that induces increased negative curvature as shown by the formation of inverse hexagonal phases allows for greater contact area between two membranes, which is required for viral fusion to occur. The cytotoxicity assay showed that the toxicity toward HeLa cells was dramatically decreased when the cholesterol or peptide level in the nanoparticles increased. This suggests that the addition of cholesterol can improve the biocompatibility of the cubic phase nanoparticles, making them safer for use in biomedical applications. As the results, this work improves the potential for the biomedical end-use applications of the nonlamellar lipid nanoparticles and shows the need of systematic formulation studies due to the complex interplay of all components.

Toward Understanding the Subcellular Distributions of Cholesterol and Sphingolipids Using High-Resolution NanoSIMS Imaging

ConspectusCharacterizing the subcellular distributions of biomolecules of interest is a basic inquiry that helps inform on the potential roles of these molecules in biological functions. Presently, the functions of specific lipid species and cholesterol are not well understood, partially because cholesterol and lipid species of interest are difficult to image with high spatial resolution but without perturbing them. Because cholesterol and lipids are relatively small and their distributions are influenced by noncovalent interactions with other biomolecules, functionalizing them with relatively large labels that permit their detection may alter their distributions in membranes and between organelles. This challenge has been surmounted by exploiting rare stable isotopes as labels that may be metabolically incorporated into cholesterol and lipids without altering their chemical compositions, and the Cameca NanoSIMS 50 instrument's ability to image rare stable isotope labels with high spatial resolution. This Account covers the use of secondary ion mass spectrometry (SIMS) performed with a Cameca NanoSIMS 50 instrument for imaging cholesterol and sphingolipids in the membranes of mammalian cells. The NanoSIMS 50 detects monatomic and diatomic secondary ions ejected from the sample to map the elemental and isotopic composition at the surface of the sample with better than 50 nm lateral resolution and 5 nm depth resolution. Much effort has focused on using NanoSIMS imaging of rare isotope-labeled cholesterol and sphingolipids for testing the long-standing hypothesis that cholesterol and sphingolipids colocalize within distinct domains in the plasma membrane. By using a NanoSIMS 50 to image rare isotope-labeled cholesterol and sphingolipids in parallel with affinity-labeled proteins of interest, a hypothesis regarding the colocalization of specific membrane proteins with cholesterol and sphingolipids in distinct plasma membrane domains has been tested. NanoSIMS performed in a depth profiling mode has enabled imaging the intracellular distributions of cholesterol and sphingolipids. Important progress has also been made in developing a computational depth correction strategy for constructing more accurate three-dimensional (3D) NanoSIMS depth profiling images of intracellular component distribution without requiring additional measurements with complementary techniques or signal collection. This Account provides an overview of this exciting progress, focusing on the studies from our laboratory that shifted understanding of plasma membrane organization, and the development of enabling tools for visualizing intracellular lipids.

Ectopic expression of SARS-CoV-2 S and ORF-9B proteins alters metabolic profiles and impairs contractile function in cardiomyocytes

Coronavirus disease 2019 (COVID-19) is associated with adverse impacts in the cardiovascular system, but the mechanisms driving this response remain unclear. In this study, we conducted "pseudoviral infection" of SARS-CoV-2 subunits to evaluate their toxic effects in cardiomyocytes (CMs), that were derived from human induced pluripotent stem cells (hiPSCs). We found that the ectopic expression of S and ORF-9B subunits significantly impaired the contractile function and altered the metabolic profiles in human cardiomyocytes. Further mechanistic study has shown that the mitochondrial oxidative phosphorylation (OXPHOS), membrane potential, and ATP production were significantly decreased two days after the overexpression of S and ORF-9B subunits, while S subunits induced higher level of reactive oxygen species (ROS). Two weeks after overexpression, glycolysis was elevated in the ORF-9B group. Based on the transcriptomic analysis, both S and ORF-9B subunits dysregulated signaling pathways associated with metabolism and cardiomyopathy, including upregulated genes involved in HIF-signaling and downregulated genes involved in cholesterol biosynthetic processes. The ORF-9B subunit also enhanced glycolysis in the CMs. Our results collectively provide an insight into the molecular mechanisms underlying SARS-CoV-2 subunits-induced metabolic alterations and cardiac dysfunctions in the hearts of COVID-19 patients.

In silico investigation of the interactions of certain drugs proposed for the treatment of Covid-19 with the paraoxonase-1

Coronavirus disease 2019 (Covid-19) has caused one of the biggest pandemics of modern times, infected over 240 million people and killed over 4.9 million people, and continues to do so. Although many drugs are widely recommended in the treatment of this disease, the interactions of these drugs with an anti-atherosclerotic enzyme, paraoxonase-1 (PON1), are not well known. In our study, we investigated the interactions of 18 different drugs, which are claimed to be effective against covid-19, with the PON1 enzyme and its genetics variants L55M and Q192R with molecular docking, molecular dynamics simulation and free energy calculation method MM/PBSA. We found that ruxolitinib, dexamethasone, colchicine; dexamethasone, sitagliptin, baricitinib and galidesivir, ruxolitinib, hydroxychloroquine were the most effective compounds in binding PON1-w, PON1L55M and PON1Q192R respectively. Mainly, sitagliptin, galidesivir and hydroxychloroquine have attracted attention by showing very high affinity (<-300 kJ/mol) according to the MM/PBSA method. We concluded that the drug interactions should be considered and more attention should be paid in the use of these drugs.Communicated by Ramaswamy H. Sarma.

Detecting the most critical clinical variables of COVID-19 breakthrough infection in vaccinated persons using machine learning

Background

COVID-19 vaccines offer different levels of immune protection but do not provide 100% protection. Vaccinated persons with pre-existing comorbidities may be at an increased risk of SARS-CoV-2 breakthrough infection or reinfection. The aim of this study is to identify the critical variables associated with a higher probability of SARS-CoV-2 breakthrough infection using machine learning.

Methods

A dataset comprising symptoms and feedback from 257 persons, of whom 203 were vaccinated and 54 unvaccinated, was used for the investigation. Three machine learning algorithms - Deep Multilayer Perceptron (Deep MLP), XGBoost, and Logistic Regression - were trained with the original (imbalanced) dataset and the balanced dataset created by using the Random Oversampling Technique (ROT), and the Synthetic Minority Oversampling Technique (SMOTE). We compared the performance of the classification algorithms when the features highly correlated with breakthrough infection were used and when all features in the dataset were used.

Result

The results show that when highly correlated features were considered as predictors, with Random Oversampling to address data imbalance, the XGBoost classifier has the best performance (F1 = 0.96; accuracy = 0.96; AUC = 0.98; G-Mean = 0.98; MCC = 0.88). The Deep MLP had the second best performance (F1 = 0.94; accuracy = 0.94; AUC = 0.92; G-Mean = 0.70; MCC = 0.42), while Logistic Regression had less accurate performance (F1 = 0.89; accuracy = 0.88; AUC = 0.89; G-Mean = 0.89; MCC = 0.68). We also used Shapley Additive Explanations (SHAP) to investigate the interpretability of the models. We found that body temperature, total cholesterol, glucose level, blood pressure, waist circumference, body weight, body mass index (BMI), haemoglobin level, and physical activity per week are the most critical variables indicating a higher risk of breakthrough infection.

Conclusion

These results, evident from our unique data source derived from apparently healthy volunteers with cardiovascular risk factors, follow the expected pattern of positive or negative correlations previously reported in the literature. This information strengthens the body of knowledge currently applied in public health guidelines and may also be used by medical practitioners in the future to reduce the risk of SARS-CoV-2 breakthrough infection.

Role of Lipid Profile and Its Relative Ratios (Cholesterol/HDL-C, Triglyceride/HDL-C, LDL-C/HDL-C, WBC/HDL-C, and FBG/HDL-C) on Admission Predicts In-Hospital Mortality COVID-19

Background

Lipid profile and its related ratios such as total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), triglyceride (TG), high-density lipoprotein-cholesterol (HDL-C), TG/HDL-C ratio, TC/HDL-C ratio, LDL-C/HDL-C ratio, white blood cell (WBC)/HDL-C ratio, and fasting blood glucose (FBG)/HDL-C ratio are valuable indicators that have been studied in various disorders to predict mortality. The present study was conducted with the aim of investigating the role of lipid profile ratios in predicting mortality in COVID-19 patients.

Methods

At the beginning of hospitalization, laboratory tests were taken from all patients (n = 300). The ability of lipid profile ratios to determine the COVID-19 severity was evaluated using receiver-operating characteristic (ROC). In addition, survival probability was determined with the average of Kaplan-Meier curves, so that the end point was death.

Results

In deceased patients, TG, TC, LDL-C, HDL-C, TC/HDL-C, TG/HDL-C, and LDL-C/HDL-C parameters were significantly lower than those of surviving patients, while WBC/HDL-C and FBG/HDL-C were significantly higher. TC (HR = 3.178, 95%CI = 1.064 to 9.491, P < 0.05), TG (HR = 3.276, 95%CI = 1.111 to 9.655, P < 0.05), LDL-C (HR = 3.207, 95%CI = 1.104 to 9.316, P < 0.05), and HDL-C (HR = 3.690, 95%CI = 1.290 to 10.554, P < 0.05), as well as TC/HDL-C (HR = 3.860, 95%CI = 1.289 to 11.558, P < 0.05), TG/HDL-C (HR = 3.860, 95%CI = 1.289 to 11.558, P < 0.05), LDL-C/HDL-C (HR = 3.915, 95%CI = 1.305 to 11.739, P < 0.05), WBC/HDL-C (HR = 3.232, 95%CI = 1.176 to 8.885, P < 0.05), and FBG/HDL-C ratios (HR = 4.474, 95%CI = 1.567 to 12.777, P < 0.01), were detectably related to survival. The multivariate Cox regression models showed that only FBG/HDL-C ratio (HR = 5.477, 95%CI = 1.488 to 20.153, P < 0.01) was significantly related to survival.

Conclusion

The results suggested that FBG/HDL-C ratio in hospital-admitted COVID-19 patients was a reliable predictor of mortality.

Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection

BACKGROUND

The majority of those infected by ancestral Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) during the UK first wave (starting March 2020) did not require hospitalisation. Most had a short-lived mild or asymptomatic infection, while others had symptoms that persisted for weeks or months. We hypothesized that the plasma proteome at the time of first infection would reflect differences in the inflammatory response that linked to symptom severity and duration.

METHODS

We performed a nested longitudinal case-control study and targeted analysis of the plasma proteome of 156 healthcare workers (HCW) with and without lab confirmed SARS-CoV-2 infection. Targeted proteomic multiple-reaction monitoring analysis of 91 pre-selected proteins was undertaken in uninfected healthcare workers at baseline, and in infected healthcare workers serially, from 1 week prior to 6 weeks after their first confirmed SARS-CoV-2 infection. Symptom severity and antibody responses were also tracked. Questionnaires at 6 and 12 months collected data on persistent symptoms.

FINDINGS

Within this cohort (median age 39 years, interquartile range 30-47 years), 54 healthcare workers (44% male) had PCR or antibody confirmed infection, with the remaining 102 (38% male) serving as uninfected controls. Following the first confirmed SARS-CoV-2 infection, perturbation of the plasma proteome persisted for up to 6 weeks, tracking symptom severity and antibody responses. Differentially abundant proteins were mostly coordinated around lipid, atherosclerosis and cholesterol metabolism pathways, complement and coagulation cascades, autophagy, and lysosomal function. The proteomic profile at the time of seroconversion associated with persistent symptoms out to 12 months. Data are available via ProteomeXchange with identifier PXD036590.

INTERPRETATION

Our findings show that non-severe SARS-CoV-2 infection perturbs the plasma proteome for at least 6 weeks. The plasma proteomic signature at the time of seroconversion has the potential to identify which individuals are more likely to suffer from persistent symptoms related to SARS-CoV-2 infection.

FUNDING INFORMATION

The COVIDsortium is supported by funding donated by individuals, charitable Trusts, and corporations including Goldman Sachs, Citadel and Citadel Securities, The Guy Foundation, GW Pharmaceuticals, Kusuma Trust, and Jagclif Charitable Trust, and enabled by Barts Charity with support from University College London Hospitals (UCLH) Charity. This work was additionally supported by the Translational Mass Spectrometry Research Group and the Biomedical Research Center (BRC) at Great Ormond Street Hospital.

Depth Correction of 3D NanoSIMS Images Shows Intracellular Lipid and Cholesterol Distributions while Capturing the Effects of Differential Sputter Rate

Knowledge of the distributions of drugs, metabolites, and drug carriers within cells is a prerequisite for the development of effective disease treatments. Intracellular component distribution may be imaged with high sensitivity and spatial resolution by using a NanoSIMS in the depth profiling mode. Depth correction strategies that capture the effects of differential sputtering without requiring additional measurements could enable producing accurate 3D NanoSIMS depth profiling images of intracellular component distributions. Here we describe an approach for depth correcting 3D NanoSIMS depth profiling images of cells that accounts for differential sputter rates. Our approach uses the secondary ion and secondary electron depth profiling images to reconstruct the cell's morphology at every raster plane. These cell morphology reconstructions are used to adjust the z-positions and heights of the voxels in the component-specific 3D NanoSIMS images. We validated this strategy using AFM topography data and reconstructions created from depth profiling images acquired with focused ion beam-secondary electron microscopy. Good agreement was found for the shapes and relative heights of the reconstructed morphologies. Application of this depth correction strategy to 3D NanoSIMS depth profiling images of a metabolically labeled cell better resolved the transport vesicles, organelles, and organellar membranes containing ¹⁸O-cholesterol and ¹⁵N-sphingolipids. Accurate 3D NanoSIMS images of intracellular component distributions may now be produced without requiring correlated analyses with separate instruments or the assumption of a constant sputter rate. This will allow visualization of the subcellular distributions of lipids, metabolites, drugs, and nanoparticles in 3D, information pivotal to understanding and treating disease.

Biofunctional roles of estrogen in coronavirus disease 2019: Beyond a steroid hormone

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), epidemic poses a major global public health threat with more than one million daily new infections and hundreds of deaths. To combat this global pandemic, efficient prevention and management strategies are urgently needed. Together with the main characteristics of COVID-19, impaired coagulation with dysfunctions of the immune response in COVID-19 pathophysiology causes high mortality and morbidity. From recent clinical observations, increased expression of specific types of estrogen appears to protect patients from SARS-CoV-2 infection, thereby, reducing mortality. COVID-19 severity is less common in women than in men, particularly in menopausal women. Furthermore, estrogen levels are negatively correlated with COVID-19 severity and mortality. These findings suggest that estrogen plays a protective role in the pathophysiology of COVID-19. In this review, we discuss the potential roles of estrogen in blocking the SARS-CoV-2 from invading alveolar cells and replicating, and summarize the potential mechanisms of anti-inflammation, immune modulation, reactive oxygen species resistance, anti-thrombosis, vascular dilation, and vascular endothelium protection. Finally, the potential therapeutic effects of estrogen against COVID-19 are reviewed. This review provides insights into the role of estrogen and its use as a potential strategy to reduce the mortality associated with COVID-19, and possibly other viral infections and discusses the possible challenges and pertinent questions.

Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application

Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet of Things (IoT). In particular, machine learning (ML) sensors for the prompt diagnosis of COVID-19 are an important option for IoT application in healthcare and ambient assisted living (AAL). Determining a COVID-19 infected status with various diagnostic tests and imaging results is costly and time-consuming. This study provides a fast, reliable and cost-effective alternative tool for the diagnosis of COVID-19 based on the routine blood values (RBVs) measured at admission. The dataset of the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 test results and 51 routine blood values. In this study, 13 popular classifier machine learning models and the LogNNet neural network model were exanimated. The most successful classifier model in terms of time and accuracy in the detection of the disease was the histogram-based gradient boosting (HGB) (accuracy: 100%, time: 6.39 sec). The HGB classifier identified the 11 most important features (LDL, cholesterol, HDL-C, MCHC, triglyceride, amylase, UA, LDH, CK-MB, ALP and MCH) to detect the disease with 100% accuracy. In addition, the importance of single, double and triple combinations of these features in the diagnosis of the disease was discussed. We propose to use these 11 features and their binary combinations as important biomarkers for ML sensors in the diagnosis of the disease, supporting edge computing on Arduino and cloud IoT service.

The Influence of SARS-CoV-2 Infection on Lipid Metabolism—The Potential Use of Lipid-Lowering Agents in COVID-19 Management

Several studies have indicated lipid metabolism alterations during COVID-19 infection, specifically a decrease in high-density lipoprotein (HDL) and low-density lipoprotein (LDL) concentrations and an increase in triglyceride (TG) levels during the infection. However, a decline in triglycerides can also be observed in critical cases. A direct correlation can be observed between a decrease in serum cholesterol, HDL-C, LDL-C and TGs, and the severity of the disease; these laboratory findings can serve as potential markers for patient outcomes. The transmission of coronavirus increases proportionally with rising levels of cholesterol in the cell membrane. This is due to the fact that cholesterol increases the number of viral entry spots and the concentration of angiotensin-converting enzyme 2 (ACE2) receptor, crucial for viral penetration. Studies have found that lower HDL-C levels correspond with a higher susceptibility to SARS-CoV-2 infection and infections in general, while higher HDL-C levels were related to a lower risk of developing them. However, extremely high HDL-C levels in serum increase the risk of infectious diseases and is associated with a higher risk of cardiovascular events. Low HDL-C levels are already accepted as a marker for risk stratification in critical illnesses, and higher HDL-C levels prior to the infection is associated with a lower risk of death in older patients. The correlation between LDL-C levels and disease severity is still unclear. However, TG levels were significantly higher in non-surviving severe patients compared to those that survived; therefore, elevated TG-C levels in COVID-19 patients may be considered an indicator of uncontrolled inflammation and an increased risk of death.

The Bovine Seminal Plasma Protein PDC-109 Possesses Pan-Antiviral Activity

Mammalian seminal plasma contains a multitude of bioactive components, including lipids, glucose, mineral elements, metabolites, proteins, cytokines, and growth factors, with various functions during insemination and fertilization. The seminal plasma protein PDC-109 is one of the major soluble components of the bovine ejaculate and is crucially important for sperm motility, capacitation, and acrosome reaction. A hitherto underappreciated function of seminal plasma is its anti-microbial and antiviral activity, which may limit the sexual transmission of infectious diseases during intercourse. We have recently discovered that PDC-109 inhibits the membrane fusion activity of influenza virus particles and significantly impairs viral infections at micromolar concentrations. Here we investigated whether the antiviral activity of PDC-109 is restricted to Influenza or if other mammalian viruses are similarly affected. We focused on Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 19 (COVID-19), thoroughly assessing PDC-109 inhibition with SARS-CoV-2 Spike (S)-pseudotyped reporter virus particles, but also live-virus infections. Consistent with our previous publications, we found significant virus inhibition, albeit accompanied by substantial cytotoxicity. However, using time-of-addition experiments we discovered a treatment regimen that enables virus suppression without affecting cell viability. We furthermore demonstrated that PDC-109 is also able to impair infections mediated by the VSV glycoprotein (VSVg), thus indicating a broad pan-antiviral activity against multiple virus species and families.

Singularity and Commonality in Response to SARS-CoV-2 in Lung and Colon Cell Models

The systemic nature of COVID-19 with multiple extrapulmonary manifestations of disease, largely due to the wide tissue expression of SARS-CoV-2 major entry factors, as well as the patient-specific features of COVID-19 pathobiology, determine important directions for basic and translational research. In the current study, we addressed the questions of singularities and commonalities in cellular responses to SARS-CoV-2 and related SARS-CoV on the basis of compendium-wide analysis of publicly available transcriptomic datasets as part of the herein implemented multi-modular UNCOVIDING approach. We focused on cellular models attributed to the epithelial cells of the respiratory system, the Calu-3 cell line, and epithelial cells of the gastrointestinal tract, the Caco-2 cell line, infected with either SARS-CoV-2 or SARS-CoV. Here, we report the outcome of a comparative analysis based on differentially expressed genes in terms of perturbations and diseases, Canonical pathways, and Upstream Regulators. We furthermore performed compendium-wide analysis across more than 19,000 mRNASeq datasets and dissected the condition-specific gene signatures. Information was gained with respect to common and unique cellular responses and molecular events. We identified that in cell lines of colon or lung origin, both viruses show similarities in cellular responses; by contrast, there are cell type-specific regulators that differed for Calu-3 and Caco-2 cells. Among the major findings is the impact of the interferon system for lung Calu-3 cells and novel links to the liver- and lipid-metabolism-associated responses for colon Caco-2 cells as part of the extrapulmonary pathomechanisms in the course of COVID-19. Among differently expressed genes, we specifically dissected the expression pattern of the APOBEC family members and propose APOBEC3G as a promising intrinsic antiviral factor of the host response to SARS-CoV-2. Overall, our study provides gene expression level evidence for the cellular responses attributed to pulmonary and gastrointestinal manifestations of COVID-19.

On the relationship between tripartite motif-containing 22 single-nucleotide polymorphisms and COVID-19 infection severity

Background

The tripartite motif containing (TRIM)-22 participates in innate immune responses and exhibits antiviral activities. The present study aimed to assess of the relationship between TRIM22 single-nucleotide polymorphisms and clinical parameters with the coronavirus disease 2019 (COVID-19) infection severity.

Methods

TRIM22 polymorphisms (rs7113258, rs7935564, and rs1063303) were genotyped using TaqMan polymerase chain reaction (PCR) assay in 495 dead and 497 improved severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patients.

Results

In this study, the frequencies of TRIM22 rs1063303 GG, rs7935564 GG, and rs7113258 TT were significantly higher in dead patients than in improved patients, and higher viral load with low PCR Ct value was noticed in dead patients. The multivariate logistic regression analysis revealed that the lower levels of low-density lipoprotein (LDL), cholesterol, PCR Ct value, and lower 25-hydroxyvitamin D, and also higher levels of erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and TRIM22 rs1063303 GG, rs7113258 TT, and rs3824949 GG genotypes were related to the COVID-19 infection severity.

Conclusion

Our finding proved the probable relationship between the COVID-19 infection severity with the genotypes of TRIM22 SNPs and clinical parameters. More research is required worldwide to show the association between the COVID-19 infection severity and host genetic factors.

Neurological aspects of SARS-CoV-2 infection: lipoproteins and exosomes as Trojan horses

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primarily targets lipid-producing cells for viral tropism. In this review, we connect systemic lipid couriers, particularly high-density lipoproteins (HDLs) and exosomes, with the neurological facets of SARS-CoV-2 infection. We discuss how SARS-CoV-2 preferentially targets lipid-secreting cells and usurps host cell lipid metabolism for efficient replication and systemic spreading. Besides providing natural veils for viral materials against host immunity, the inherent properties of some of these endogenous lipid particles to traverse the blood-brain barrier (BBB) also offer alternative routes for SARS-CoV-2 neurotropism. Importantly, virus-driven neurological aberrations mediated by HDLs and exosomes are fueled by lipid rafts, which are implicated in the production and transmigration of these lipid particles across the BBB. Finally, we discuss how repurposing existing drugs targeting lipid rafts and cholesterol homeostasis may be beneficial toward alleviating the global coronavirus disease 2019 (COVID-19) disease burden.

Factors Modulating COVID-19: A Mechanistic Understanding Based on the Adverse Outcome Pathway Framework

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues.

The constellation of cholesterol-dependent processes associated with SARS-CoV-2 infection

The role of cholesterol in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other coronavirus-host cell interactions is currently being discussed in the context of two main scenarios: i) the presence of the neutral lipid in cholesterol-rich lipid domains involved in different steps of the viral infection and ii) the alteration of metabolic pathways by the virus over the course of infection. Cholesterol-enriched lipid domains have been reported to occur in the lipid envelope membrane of the virus, in the host-cell plasma membrane, as well as in endosomal and other intracellular membrane cellular compartments. These membrane subdomains, whose chemical and physical properties distinguish them from the bulk lipid bilayer, have been purported to participate in diverse phenomena, from virus-host cell fusion to intracellular trafficking and exit of the virions from the infected cell. SARS-CoV-2 recruits many key proteins that participate under physiological conditions in cholesterol and lipid metabolism in general. This review analyses the status of cholesterol and lipidome proteins in SARS-CoV-2 infection and the new horizons they open for therapeutic intervention.

Association between Atherogenic Index and Cholesterol to HDL Ratio in COVID-19 Patients During the Initial Phase of Infection

This case-control study aimed to assess pathologic alteration in the serum levels of the atherogenic index, cholesterol to high-density lipoprotein (HDL) ratio, HDL cholesterol, total cholesterol, triglyceride, HbA1c, and glucose in 158 COVID-19 patients who were hospitalized in Erbil international hospital, Erbil, Iraq, between January and May 2020, in the early stage of infection. The patients were confirmed for SARS-CoV-2 on admission. The laboratory test results were compared between this group and a group of healthy individuals (n=158). A statistically significant difference was found between the studied factors in healthy controls and COVID-19 patients, except for low-density lipoprotein (LDL) cholesterol (P=0.13). In the case of COVID-19 patients, total levels of cholesterol and HDL cholesterol were significantly lower than controls (P<0.003). Triglyceride, VLDL cholesterol, atherogenic index, and total cholesterol to HDL ratio were found to be significantly higher in COVID-19 patients, compared to controls (P<0.005). Atherogenic index were found to be positively correlated with triglyceride (r=0.88, P=0.00), HbA1C (r=0.6, P=0.05), and glucose index (r= 0.62, P= 0.05), and the ratio of cholesterol to HDL (r=0.64, P=0.04). In contrast, no correlation was found between atherogenic index and cholesterol to HDL ratio in controls. The results of the current study indicated that risk factors for the cardiovascular disease increased in patients with COVID-19 infection, which included atherogenic index, cholesterol to HDL ratio, as well as the association between atherogenic index, and all were organized in one cluster. Therefore, lipids can perform a vital physiological function in patients infected with COVID-19.

Roles of the ACE/Ang II/AT1R pathway, cytokine release, and alteration of tight junctions in COVID-19 pathogenesis

This paper shows how SARS-CoV-2 alters tight junctions (TJs) in human organs. The effect of SARS-CoV-2 on the ACE/Ang II/AT1R pathway and immune cells culminates in the release of numerous pro-inflammatory mediators, leading to the presence of certain symptoms in COVID-19, such as acute lung injury (ALI), pulmonary hypertension, and pulmonary fibrosis. Furthermore, the cytokines released alter different TJs components. The study shows how the irregular release of pro-inflammatory cytokines leads to claudin disruption in various tissues of the body, resulting in different symptoms, such as alveolar fibrosis, pulmonary edema, conjunctivitis, altered fertility in males, gastrointestinal symptoms, Covid toes, and others. SARS-CoV-2 also alters occludin expression in the endothelial and blood-testis barriers (BTB) resulting in edema and altered fertility. Viral disruption of JAM-A leads to activation of the RhoA GTPase, which leads to ALI. Taken together, these results define ACE/Ang II/AT1R pathway receptors and tight junctional components as potential therapeutic targets in COVID-19.

The Evaluation of Relationship Between Monocyte/High-Density Lipoprotein Ratio (MHR) and COVID-19

Objective: Early diagnosis is important for severe diseases in COVID-19. Monocyte/high dansity lipoprotein ratio (MHR) is a new prognostic marker indicating inflammation. We aimed to investigate the relationship between MHR and diseases severity in COVID-19. Materials and Methods: Patients with laboratory confirmed COVID-19, were retrospectively analyzed. Clinical symptoms, signs and laboratory data on the first day of hospitalization were obtained from medical records of hospital. The clinical data of 301 patients were included in study. Cases were diagnosed on the basis of interim guidance of World Health Organization (WHO). Patients were classified into two groups as non-severe COVID-19 and severe COVID-19. MHR were calculated with laboratory data on the first day of hospitalization. The relationship between MHR level and COVID-19 severity was evaluated. Statistical analysis of the data was performed by using SPSS 25 (SPSS Inc., Chicago, IL, USA) package program. Statistical significance level was accepted as p

Noncommunicable diseases risk factors and the risk of COVID-19 among university employees in Indonesia

Introduction

Noncommunicable diseases (NCDs) are still a major public health problem in Indonesia. Studies have shown that risk factors of NCDs are associated with coronavirus disease 2019 (COVID-19) severity and mortality. However, it is unclear whether NCD risk factors are also risks for new COVID-19 cases. This study aimed to obtain an NCD risk profile among university employees and its associations with contracting COVID-19.

Methods

A cross-sectional study was conducted in October 2021. Participants were administrative employees of Universitas Indonesia (UI), Depok City, West Java. Assessment of NCD risk factors was based on the World Health Organization STEPwise approach to NCD risk factor surveillance (WHO STEPS). Demographic, working, and medical-history data were obtained electronically by using a Google Form. Physical and laboratory examinations were done in the Integrated Post for NCDs. Risks were expressed as adjusted odds ratio (OR_adj) and 95% confidence interval (CI) in multivariate analyses.

Results

A total of 613 employees were enrolled. Men were predominant (54.8%), and about 36% of them work in shift as security personnel. About 66.7% were overweight or obese and 77.8% had hypertension. There were 138 (22.8%) employees who had COVID-19. Nearly all (95.6%) had been fully vaccinated against COVID-19. At-risk waist circumference (OR_adj 1.72, 95% CI 1.15–2.56, p = 0.008) and total cholesterol level of 200–239 mg/dL (OR_adj 2.30, 95% CI 1.19–4.44, p = 0.013) were independent risk factors, but shift work (OR_adj 0.52, 95% CI 0.34–0.80, p = 0.003) was protective against COVID-19.

Conclusion

The prevalence of NCD risk factors among university administrative employees was high, increasing the risk of contracting COVID-19. A behavioral intervention program to manage NCD risk factors at the university level is urgently needed according to the Health Promoting University framework.

Immunometabolic analysis shows a distinct cyto-metabotype in Covid-19 compared to sepsis from other causes

Background

In Covid-19, profound systemic inflammatory responses are accompanied by both metabolic risk factors for severity and, separately, metabolic mechanisms have been shown to underly disease progression. It is unknown whether this reflects similar situations in sepsis or is a unique characteristic of Covid-19.

Aims

Define the immunometabolic signature of Covid-19.

Methods

65 patients with Covid-19,19 patients with sepsis and 14 healthy controls were recruited and sampled for plasma, serum and peripheral blood mononuclear cells (PBMCs) through 10 days of critical illness. Metabotyping was performed using the Biocrates p180 kit and multiplex cytokine profiling undertaken. PBMCs underwent phenotyping by flow cytometry. Immune and metabolic readouts were integrated and underwent pathway analysis.

Results

Phopsphatidylcholines (PC) are reduced in Covid-19 but greater than in sepsis. Compared to controls, tryptophan is reduced in Covid-19 and inversely correlated with the severity of the disease and IFN-ɣ concentrations, conversely the kyneurine and kyneurine/tryptophan ratio increased in the most severe cases. These metabolic changes were consistent through 2 pandemic waves in our centre. PD-L1 expression in CD8+ T cells, Tregs and CD14+ monocytes was increased in Covid-19 compared to controls.

Conclusions

In our cohort, Covid-19 is associated with monocytopenia, increased CD14+ and Treg PD-L1 expression correlating with IFN-ɣ plasma concentration and disease severity (SOFA score). The latter is also associated with metabolic derangements of Tryptophan, LPC 16:0 and PCs. Lipid metabolism, in particular phosphatidylcholines and lysophosphatidylcolines, seems strictly linked to immune response in Covid-19. Our results support the hypothesis that IFN-ɣ -PD-L1 axis might be involved in the cytokine release syndrome typical of severe Covid-19 and the phenomenon persisted through multiple pandemic waves despite use of immunomodulation.

Metabolomics Analysis of PK-15 Cells with Pseudorabies Virus Infection Based on UHPLC-QE-MS

Viruses depend on the metabolic mechanisms of the host to support viral replication. We utilize an approach based on ultra-high-performance liquid chromatography/Q Exactive HF-X Hybrid Quadrupole-Orbitrap Mass (UHPLC-QE-MS) to analyze the metabolic changes in PK-15 cells induced by the infections of the pseudorabies virus (PRV) variant strain and Bartha K61 strain. Infections with PRV markedly changed lots of metabolites, when compared to the uninfected cell group. Additionally, most of the differentially expressed metabolites belonged to glycerophospholipid metabolism, sphingolipid metabolism, purine metabolism, and pyrimidine metabolism. Lipid metabolites account for the highest proportion (around 35%). The results suggest that those alterations may be in favor of virion formation and genome amplification to promote PRV replication. Different PRV strains showed similar results. An understanding of PRV-induced metabolic reprogramming will provide valuable information for further studies on PRV pathogenesis and the development of antiviral therapy strategies.

Coronavirus Infection and Cholesterol Metabolism

Host cholesterol metabolism remodeling is significantly associated with the spread of human pathogenic coronaviruses, suggesting virus-host relationships could be affected by cholesterol-modifying drugs. Cholesterol has an important role in coronavirus entry, membrane fusion, and pathological syncytia formation, therefore cholesterol metabolic mechanisms may be promising drug targets for coronavirus infections. Moreover, cholesterol and its metabolizing enzymes or corresponding natural products exert antiviral effects which are closely associated with individual viral steps during coronavirus replication. Furthermore, the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 infections are associated with clinically significant low cholesterol levels, suggesting cholesterol could function as a potential marker for monitoring viral infection status. Therefore, weaponizing cholesterol dysregulation against viral infection could be an effective antiviral strategy. In this review, we comprehensively review the literature to clarify how coronaviruses exploit host cholesterol metabolism to accommodate viral replication requirements and interfere with host immune responses. We also focus on targeting cholesterol homeostasis to interfere with critical steps during coronavirus infection.

Melatonin and REGN-CoV2 combination as a vaccine adjuvant for Omicron variant of SARS-CoV-2

The omicron variant (B.529) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged in late 2021, caused panic worldwide due to its contagiousness and multiple mutations in the spike protein compared to the Delta variant (B.617.2). There is currently no specific antiviral available to treat Coronavirus disease 2019 (COVID-19). However, studies on neutralizing monoclonal antibodies (mAb) developed to fight COVID-19 are growing and gaining traction. REGN-COV2 (Regeneron or imdevimab-casirivimab combination), which has been shown in recent studies to be less affected by Omicron's RBD (receptor binding domain) mutations among other mAb cocktails, plays an important role in adjuvant therapy against COVID-19. On the other hand, it is known that melatonin, which has antioxidant and immunomodulatory effects, can prevent a possible cytokine storm, and other severe symptoms that may develop in the event of viral invasion. Along with all these findings, we believe it is crucial to evaluate the use of melatonin with REGN-COV2, a cocktail of mAbs, as an adjuvant in the treatment and prevention of COVID-19, particularly in immunocompromised and elderly patients.

Potential plants for inflammatory dysfunction in the SARS-CoV-2 infection

The inflammatory process is a biological response of the organism to remove injurious stimuli and initiate homeostasis. It has been recognized as a key player in the most severe forms of SARS-CoV-2, characterized by significantly increased pro-inflammatory cytokine levels, the so-called "cytokine storm" that appears to play a pivotal role in this disease. Therefore, the aim of this systematic review was to select clinical trials with anti-inflammatory plants and relate the activity of these plants to inflammatory markers of SARS-CoV-2 infection. PRISMA guidelines are followed, and studies of interest are indexed in PubMed and ClinicalTrials.gov databases. As a result, 32 clinical trials encompassing 22 plants were selected. The main anti-inflammatory mechanisms described in the studies are the inhibition of inflammatory cytokines, such as IL-6, TNF-a, IFN-γ, and IL-1; decreased CRP and oxidative marker levels; increased endogenous antioxidant levels; modulation of cardiovascular risk markers. The data found are not directly related to SARS-CoV-2 infection. However, they provide possibilities for new studies as plants have a wide array of phytochemicals, and detecting which ones are responsible for anti-inflammatory effects can provide invaluable contribution to studies aiming to evaluate efficacy in scenarios of SARS-CoV-2 infection.

Intracellular Cholesterol Synthesis and Transport

Cholesterol homeostasis is related to multiple diseases in humans, including cardiovascular disease, cancer, and neurodegenerative and hepatic diseases. The cholesterol levels in cells are balanced dynamically by uptake, biosynthesis, transport, distribution, esterification, and export. In this review, we focus on de novo cholesterol synthesis, cholesterol synthesis regulation, and intracellular cholesterol trafficking. In addition, the progression of lipid transfer proteins (LTPs) at multiple contact sites between organelles is considered.

Alterations of Lipid Profile in COVID-19: A Narrative Review

The COVID-19 pandemic has led to over 100 million infections and over 3 million deaths worldwide. Understanding its pathogenesis is crucial to guide prognostic and therapeutic implications. Viral infections are known to alter the lipid profile and metabolism of their host cells, similar to the case with MERS and SARS-CoV-2002. Since lipids play various metabolic roles, studying lipid profile alterations in COVID-19 is an inevitable step as an attempt to achieve better therapeutic strategies, as well as a potential prognostic factor in the course of this disease. Several studies have reported changes in lipid profile associated with COVID-19. The most frequently reported changes are a decline in serum cholesterol and ApoA1 levels and elevated triglycerides. The hyper-inflammatory state mediated by the Cytokine storm disturbs several fundamental lipid biosynthesis pathways. Virus replication is a process that drastically changes the host cell's lipid metabolism program and overuses cell lipid resources. Lower HDL-C and ApoA1 levels are associated with higher severity and mortality rates and with higher levels of inflammatory markers. Studies suggest that arachidonic acid omega-3 derivatives might help modulate hyper-inflammation and cytokine storm resulting from pulmonary involvement. Also, statins have been shown to be beneficial when administered after COVID-19 diagnosis via unclear mechanisms probably associated with anti-inflammatory effects and HDL-C rising effects.

Dynamic Changes of the Blood Chemistry in Syrian Hamsters Post-Acute COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that causes coronavirus disease 2019 (COVID-19). However, the long-term health consequences of COVID-19 are not fully understood. We aimed to determine the long-term lung pathology and blood chemistry changes in Syrian hamsters infected with SARS-CoV-2. Syrian hamsters (Mesocricetus auratus) were inoculated with 10⁵ PFU of SARS-CoV-2, and changes post-infection (pi) were observed for 20 days. On days 5 and 20 pi, the lungs were harvested and processed for pathology and viral load count. Multiple blood samples were collected every 3 to 5 days to observe dynamic changes in blood chemistry. Infected hamsters showed consistent weight loss until day 7 pi At day 5 pi, histopathology of the lungs showed moderate to severe inflammation and the virus could be detected. These results indicate that SARS-CoV-2 has an acute onset and recovery course in the hamster infection model. During the acute onset, blood triglyceride levels increased significantly at day 3 pi During the recovery course, uric acid and low-density lipoprotein levels increased significantly, but the total protein and albumin levels decreased. Together, our study suggests that SARS-CoV-2 infection in hamsters not only causes lung damage but also causes long-term changes in blood biochemistry during the recovery process.

IMPORTANCE COVID-19 is now considered a multiorgan disease with a wide range of manifestations. There are increasing reports of persistent and long-term effects after acute COVID-19, but the long-term health consequences of COVID-19 are not fully understood. This study reported for the first time the use of blood samples collected continuously in a SARS-CoV-2-infected hamster model, which provides more information about the dynamic changes in blood biochemistry during the acute and recovery phases of SARS-CoV-2 infection. Our study suggests that SARS-CoV-2 infection in hamsters not only causes lung damage but also causes long-term changes in blood biochemistry during the recovery process. The study may be used by several researchers and clinicians, especially those who are studying potential treatments for patients with post-acute COVID-19 syndrome.

COVIDomics: The Proteomic and Metabolomic Signatures of COVID-19

Omics-based technologies have been largely adopted during this unprecedented global COVID-19 pandemic, allowing the scientific community to perform research on a large scale to understand the pathobiology of the SARS-CoV-2 infection and its replication into human cells. The application of omics techniques has been addressed to every level of application, from the detection of mutations, methods of diagnosis or monitoring, drug target discovery, and vaccine generation, to the basic definition of the pathophysiological processes and the biochemical mechanisms behind the infection and spread of SARS-CoV-2. Thus, the term COVIDomics wants to include those efforts provided by omics-scale investigations with application to the current COVID-19 research. This review summarizes the diverse pieces of knowledge acquired with the application of COVIDomics techniques, with the main focus on proteomics and metabolomics studies, in order to capture a common signature in terms of proteins, metabolites, and pathways dysregulated in COVID-19 disease. Exploring the multiomics perspective and the concurrent data integration may provide new suitable therapeutic solutions to combat the COVID-19 pandemic.

The “Invisible Enemy” SARS-CoV-2: Viral Spread and Drug Treatment

Nowadays, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has become the main subject of the scientific medical world and all World Organizations, causing millions of deaths worldwide. In this review, we have highlighted the context of the Coronavirus disease 2019 (COVID-19) pandemic, how the virus spreads, the symptoms and complications that may occur, and, especially, the drug treatment of viral infection, with emphasis on monoclonal antibodies. While well-known strains such as Alpha, Beta, Gamma, and, especially, Delta have shown an accelerated transmission among the population, the new Omicron variant (discovered on 24 November 2021) indicates more significant infectiousness and the poor efficacy of monoclonal antibody therapy due to mutations on the spike protein receptor-binding domain. With these discoveries, the experiments began, the first being in silico and in vitro, but these are not enough, and in vivo experiments are needed to see exactly the cause of neutralization of the action of these drugs. Following the documentation of the latest medical and scientific research, it has been concluded that there are many chemical molecules that have the potential to treat SARS-CoV-2 infection, but more detailed clinical trials are needed for their use in therapy. In addition, it is important to consider the structure of the viral strain in the administration of treatment.

SARS-CoV-2-Specific Immune Response and the Pathogenesis of COVID-19

The review aims to consolidate research findings on the molecular mechanisms and virulence and pathogenicity characteristics of coronavirus disease (COVID-19) causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and their relevance to four typical stages in the development of acute viral infection. These four stages are invasion; primary blockade of antiviral innate immunity; engagement of the virus's protection mechanisms against the factors of adaptive immunity; and acute, long-term complications of COVID-19. The invasion stage entails the recognition of the spike protein (S) of SARS-CoV-2 target cell receptors, namely, the main receptor (angiotensin-converting enzyme 2, ACE2), its coreceptors, and potential alternative receptors. The presence of a diverse repertoire of receptors allows SARS-CoV-2 to infect various types of cells, including those not expressing ACE2. During the second stage, the majority of the polyfunctional structural, non-structural, and extra proteins SARS-CoV-2 synthesizes in infected cells are involved in the primary blockage of antiviral innate immunity. A high degree of redundancy and systemic action characterizing these pathogenic factors allows SARS-CoV-2 to overcome antiviral mechanisms at the initial stages of invasion. The third stage includes passive and active protection of the virus from factors of adaptive immunity, overcoming of the barrier function at the focus of inflammation, and generalization of SARS-CoV-2 in the body. The fourth stage is associated with the deployment of variants of acute and long-term complications of COVID-19. SARS-CoV-2's ability to induce autoimmune and autoinflammatory pathways of tissue invasion and development of both immunosuppressive and hyperergic mechanisms of systemic inflammation is critical at this stage of infection.

COVID-19 and diabetes-Two giants colliding: From pathophysiology to management

Since December 2019, a new coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread around the world, causing the coronavirus 2019 (COVID-19) pandemic. From the beginning, SARS-CoV-2 has put a strain on the health system. In fact, many patients have had severe forms of the disease with the need for hospitalization due to respiratory failure. To contain the pandemic, the most widely used approach has been lockdowns. Social restrictions have been reduced thanks to the development of vaccines and targeted therapies. However, fatal events still occur among people at high risk of serious infection, such as patients with concomitant diabetes. Different mechanisms have been proposed to explain the poor prognosis of patients with diabetes and COVID-19, but the specific cause is unclear. It is now known that insulin resistance, inflammation, and cytokine storm are involved. Moreover, SARS-CoV-2 uses the angiotensin-converting enzyme 2 receptors to enter cells. This receptor is expressed on pancreatic beta cells and, during infection, it appears that receptor involvement may induce hyperglycemia in patients with or without diabetes. In this study, we discuss the mechanisms underlying the poor prognosis in people with COVID-19 and diabetes and what may improve the outcome in these patients.