Declined serum high density lipoprotein cholesterol is associated with the severity of COVID-19 infection

Establishment and validation of a prognostic model based on common laboratory indicators for SARS-CoV-2 infection in Chinese population

BACKGROUND

At the beginning of December 2022, the Chinese government made major adjustments to the epidemic prevention and control measures. The epidemic infection data and laboratory makers for infected patients based on this period may help with the management and prognostication of COVID-19 patients.

METHODS

The COVID-19 patients hospitalized during December 2022 were enrolled. Logistic regression analysis was used to screen significant factors associated with mortality in patients with COVID-19. Candidate variables were screened by LASSO and stepwise logistic regression methods and were used to construct logistic regression as the prognostic model. The performance of the models was evaluated by discrimination, calibration, and net benefit.

RESULTS

888 patients were eligible, consisting of 715 survivors and 173 all-cause deaths. Factors significantly associated with mortality in COVID-19 patients were: lactate dehydrogenase (LDH), albumin (ALB), procalcitonin (PCT), age, smoking history, malignancy history, high density lipoprotein cholesterol (HDL-C), lactate, vaccine status and urea. 335 of the 888 eligible patients were defined as ICU cases. Seven predictors, including neutrophil to lymphocyte ratio, D-dimer, PCT, C-reactive protein, ALB, bicarbonate, and LDH, were finally selected to establish the prognostic model and generate a nomogram. The area under the curve of the receiver operating curve in the training and validation cohorts were respectively 0.842 and 0.853. In terms of calibration, predicted probabilities and observed proportions displayed high agreements. Decision curve analysis showed high clinical net benefit in the risk threshold of 0.10-0.85. A cutoff value of 81.220 was determined to predict the outcome of COVID-19 patients via this nomogram.

CONCLUSIONS

The laboratory model established in this study showed high discrimination, calibration, and net benefit. It may be used for early identification of severe patients with COVID-19.

Mass spectrometric approaches in discovering lipid biomarkers for COVID-19 by lipidomics: Future challenges and perspectives

Coronavirus disease 2019 (COVID-19) has emerged as a global health threat and has rapidly spread worldwide. Significant changes in the lipid profile before and after COVID-19 confirmed the significance of lipid metabolism in regulating the response to viral infection. Therefore, understanding the role of lipid metabolism may facilitate the development of new therapeutics for COVID-19. Owing to their high sensitivity and accuracy, mass spectrometry (MS)-based methods are widely used for rapidly identifying and quantifying of thousands of lipid species present in a small amount of sample. To enhance the capabilities of MS for the qualitative and quantitative analysis of lipids, different platforms have been combined to cover a wide range of lipidomes with high sensitivity, specificity, and accuracy. Currently, MS-based technologies are being established as efficient methods for discovering potential diagnostic biomarkers for COVID-19 and related diseases. As the lipidome of the host cell is drastically affected by the viral replication process, investigating lipid profile alterations in patients with COVID-19 and targeting lipid metabolism pathways are considered to be crucial steps in host-directed drug targeting to develop better therapeutic strategies. This review summarizes various MS-based strategies that have been developed for lipidomic analyzes and biomarker discoveries to combat COVID-19 by integrating various other potential approaches using different human samples. Furthermore, this review discusses the challenges in using MS technologies and future perspectives in terms of drug discovery and diagnosis of COVID-19.

Post-Acute Sequelae and Mitochondrial Aberration in SARS-CoV-2 Infection

This review investigates links between post-acute sequelae of SARS-CoV-2 infection (PASC), post-infection viral persistence, mitochondrial involvement and aberrant innate immune response and cellular metabolism during SARS-CoV-2 infection. Advancement of proteomic and metabolomic studies now allows deeper investigation of alterations to cellular metabolism, autophagic processes and mitochondrial dysfunction caused by SARS-CoV-2 infection, while computational biology and machine learning have advanced methodologies of predicting virus-host gene and protein interactions. Particular focus is given to the interaction between viral genes and proteins with mitochondrial function and that of the innate immune system. Finally, the authors hypothesise that viral persistence may be a function of mitochondrial involvement in the sequestration of viral genetic material. While further work is necessary to understand the mechanisms definitively, a number of studies now point to the resolution of questions regarding the pathogenesis of PASC.

The biogenesis and transport of triglyceride-rich lipoproteins

Triglyceride-rich lipoproteins (TRLs) play essential roles in human health and disease by transporting bulk lipids into the circulation. This review summarizes the fundamental mechanisms and diverse factors governing lipoprotein production, secretion, and regulation. Emphasizing the broader implications for human health, we outline the intricate landscape of lipoprotein research and highlight the potential coordination between the biogenesis and transport of TRLs in physiology, particularly the unexpected coupling of metabolic enzymes and transport machineries. Challenges and opportunities in lipoprotein biology with respect to inherited diseases and viral infections are also discussed. Further characterization of the biogenesis and transport of TRLs will advance both basic research in lipid biology and translational medicine for metabolic diseases.

HDL-based therapeutics: A promising frontier in combating viral and bacterial infections

Low levels of high-density lipoprotein (HDL) and impaired HDL functionality have been consistently associated with increased susceptibility to infection and its serious consequences. This has been attributed to the critical role of HDL in maintaining cellular lipid homeostasis, which is essential for the proper functioning of immune and structural cells. HDL, a multifunctional particle, exerts pleiotropic effects in host defense against pathogens. It functions as a natural nanoparticle, capable of sequestering and neutralizing potentially harmful substances like bacterial lipopolysaccharides. HDL possesses antiviral activity, preventing viruses from entering or fusing with host cells, thereby halting their replication cycle. Understanding the complex relationship between HDL and the immune system may reveal innovative targets for developing new treatments to combat infectious diseases and improve patient outcomes. This review aims to emphasize the role of HDL in influencing the course of bacterial and viral infections and its and its therapeutic potential.

Effect of IL-6R blockade on plasma lipids and clinical outcomes among hospitalized patients with COVID-19 infection

Plasma lipid levels are modulated by systemic infection and inflammation; it is unknown whether these changes reflect inflammatory responses or caused directly by pathogen presence. We explored the hypothesis that anti-inflammatory intervention via interleukin 6 receptor (IL-6R) blockade would influence plasma lipid levels during severe infection and evaluated the association of plasma lipid changes with clinical outcomes. Sarilumab (monoclonal antibody blocking IL-6R) efficacy was previously assessed in patients with coronavirus disease 2019 (COVID-19) (NCT04315298). This analysis determined whether strong inflammatory reduction by sarilumab in patients with COVID-19 pneumonia of increasing severity (severe, critical, multisystem organ dysfunction) affected plasma lipid changes between day 1 and day 7 of study therapy. Baseline lipid levels reflected the presence of acute systemic infection, characterized by very low HDL-C, low LDL-C, and moderately elevated triglycerides (TGs). Disease severity was associated with progressively more abnormal lipid levels. At day 7, median lipid levels increased more in the sarilumab versus placebo group (HDL-C +10.3%, LDL-C +54.7%, TG +32% vs. HDL-C +1.7%, LDL-C +15.4%, TG +8.8%, respectively). No significant association between lipid changes and clinical outcomes was observed. In conclusion, severe-to-critical COVID-19 pneumonia causes profound HDL-C depression that is only modestly responsive to strong anti-IL-6R inflammatory intervention. Conversely, LDL-C depression is strongly responsive to IL-6R blockade, with LDL-C levels likely returning to the predisease set point. These results advance our understanding of the complex relationship between serum lipids and infection/inflammation and suggest that HDL-C depression during acute contagious disease is driven by infection and not IL-6-mediated inflammation.

Reduced HDL-cholesterol in long COVID-19: A key metabolic risk factor tied to disease severity

This controlled study investigated metabolic changes in non-vaccinated individuals with Long-COVID-19, along with their connection to the severity of the disease. The study involved 88 patients who experienced varying levels of initial disease severity (mild, moderate, and severe), and a control group of 29 healthy individuals. Metabolic risk markers from fasting blood samples were analyzed, and data regarding disease severity indicators were collected. Findings indicated significant metabolic shifts in severe Long-COVID-19 cases, mainly a marked drop in HDL-C levels and a doubled increase in ferritin levels and insulin resistance compared to the mild cases and controls. HDL-C and ferritin were identified as the leading factors predicted by disease severity. In conclusion, the decline in HDL-C levels and rise in ferritin levels seen in Long-COVID-19 individuals, largely influenced by the severity of the initial infection, could potentially play a role in the persistence and progression of Long-COVID-19. Hence, these markers could be considered as possible therapeutic targets, and help shape preventive strategies to reduce the long-term impacts of the disease.

SARS-CoV-2 nucleocapsid protein promotes TMAO-induced NLRP3 inflammasome activation by SCAP-SREBP signaling pathway

The sterol regulatory element-binding protein (SREBP) activation and cytokine level were significantly increased in coronavirus disease-19. The NLRP3 inflammasome is an amplifier for cellular inflammation. This study aimed to elucidate the modulatory effect of SARS-CoV-2 nucleocapsid protein (SARS-CoV-2 NP) on trimethylamine N-oxide (TMAO)-induced lipogenesis and NLRP3 inflammasome activation and the underlying mechanisms in vascular smooth muscle cells (VSMCs). Our data indicated that SARS-CoV-2 NP activates the dissociation of the SREBP cleavage activating protein (SCAP) from the endoplasmic reticulum, resulting in SREBP activation, increased lipogenic gene expression, and NLRP3 inflammasome activation. TMAO was applied to VSMC-induced NLRP3 inflammasome by promoting the SCAP-SREBP complex endoplasmic reticulum-to-Golgi translocation, which facilitates directly binding of SARS-CoV-2 NP to the NLRP3 protein for NLRP3 inflammasome assembly. SARS-CoV-2 NP amplified the TMAO-induced lipogenic gene expression and NLRP3 inflammasome. Knockdown of SCAP-SREBP2 can effectively reduce lipogenic gene expression and alleviate NLRP3 inflammasome-mediated systemic inflammation in VSMCs stimulated with TMAO and SARS-CoV-2 NP. These results reveal that SARS-CoV-2 NP amplified TMAO-induced lipogenesis and NLRP3 inflammasome activation via priming the SCAP-SREBP signaling pathway.

B. Comparison of Different Vascular Biomarkers for Predicting In-Hospital Mortality in Severe SARS-CoV-2 Infection

Severe SARS-CoV-2 elicits a hyper-inflammatory response that results in intravascular inflammation with endothelial injury, which contributes to increased mortality in COVID-19. To predict the outcome of severe SARS-CoV-2 infection, we analyzed the baseline level of different biomarkers of vascular disorders in COVID-19 subjects upon intensive care unit (ICU) admission and prior to any vaccination. A total of 70 severe COVID-19 patients (37 survivors and 33 non-survivors) were included with 16 age- and sex-matched controls. Vascular dysfunction was monitored via soluble VCAM-1, E-selectin, ACE2 and Lp-PLA2, while abnormal platelet activation was evaluated by soluble P-selectin and CD40L in parallel. These results were correlated with routine laboratory parameters and disease outcomes. Among these parameters, VCAM-1 and ACE2 showed significantly higher serum levels in COVID-19 patients with early death vs. convalescent subjects. VCAM-1 was significantly correlated with the Horowitz index (r = 0.3115) and IL-6 (r = 0.4599), while ACE2 was related to E-selectin (r = 0.4143) and CD40L (r = 0.2948). Lp-PLA2 was altered in none of these COVID-19 subcohorts and showed no relationship with the other parameters. Finally, the pre-treatment level of VCAM-1 (≥1420 ng/mL) and ACE2 activity (≥45.2 μU/mL) predicted a larger risk for mortality (Log-Rank p = 0.0031 and p = 0.0117, respectively). Vascular dysfunction with endothelial cell activation is linked to lethal COVID-19, and highly elevated soluble VCAM-1 and ACE2 at admission to ICU may predict unfavorable outcomes.

Retrospective cohort study to evaluate the continuous use of anticholesterolemics and diuretics in patients with COVID-19

Purpose

The purpose of this study is to evaluate the interference of the continuous use of drug classes in the expression of biomarkers during the first week of hospitalization and in the prognosis of patients with COVID-19.

Methods

The patients diagnosed with COVID-19 and confirmed with SARS-CoV-2 by RT-qPCR assay underwent the collection of fasting whole blood samples for further analysis. Other data also extracted for this study included age, sex, clinical symptoms, related comorbidities, smoking status, and classes of continuous use. Routine serum biochemical parameters, including alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, C-reactive protein, N-terminal fragment of B-type natriuretic peptide, and cardiac troponin, were measured.

Results

In this cross-sectional study, a total of 176 patients with COVID-19 hospitalizations were included. Among them, 155 patients were discharged (88.5%), and 21 patients died (12%). Among the drug classes evaluated, we verified that the continuous use of diuretic 4.800 (1.853-11.67) (p = 0.0007) and antihypercholesterolemic 3.188 (1.215-7.997) (p = 0.0171) drug classes presented a significant relative risk of death as an outcome when compared to the group of patients who were discharged. We evaluated biomarkers in patients who used continuous antihypercholesterolemic and diuretic drug classes in the first week of hospitalization. We observed significant positive correlations between the levels of CRP with cardiac troponin (r = 0.714), IL-6 (r = 0.600), and IL-10 (r = 0.900) in patients who used continuous anticholesterolemic and diuretic drug classes and were deceased. In these patients, we also evaluated the possible correlations between the biomarkers AST, NT-ProBNP, cardiac troponin, IL-6, IL-8, and IL-10. We observed a significantly negative correlations in AST levels with NT-ProBNP (r = -0.500), cardiac troponin (r = -1.00), IL-6 (r = -1.00), and IL-10 (r = -1.00) and a positive correlation with IL-8 (r = 0.500). We also observed significant negative correlation in the levels of NT-ProBNP with IL-10 (r = -0.800) and a positive correlation with cardiac troponin (r = 0.800). IL-6 levels exhibited positive correlations with cardiac troponin (r = 0.800) and IL-10 (r = 0.700).

Conclusion

In this study, we observed that hospitalized COVID-19 patients who continued using anticholesterolemic and diuretic medications showed a higher number of correlations between biomarkers, indicating a poorer clinical prognosis. These correlations suggest an imbalanced immune response to injuries caused by SARS-CoV-2.

Oxylipin transport by lipoprotein particles and its functional implications for cardiometabolic and neurological disorders

Lipoprotein metabolism is critical to inflammation. While the periphery and central nervous system (CNS) have separate yet connected lipoprotein systems, impaired lipoprotein metabolism is implicated in both cardiometabolic and neurological disorders. Despite the substantial investigation into the composition, structure and function of lipoproteins, the lipoprotein oxylipin profiles, their influence on lipoprotein functions, and their potential biological implications are unclear. Lipoproteins carry most of the circulating oxylipins. Importantly, lipoprotein-mediated oxylipin transport allows for endocrine signaling by these lipid mediators, long considered to have only autocrine and paracrine functions. Alterations in plasma lipoprotein oxylipin composition can directly impact inflammatory responses of lipoprotein metabolizing cells. Similar investigations of CNS lipoprotein oxylipins are non-existent to date. However, as APOE4 is associated with Alzheimer's disease-related microglia dysfunction and oxylipin dysregulation, ApoE4-dependent lipoprotein oxylipin modulation in neurological pathologies is suggested. Such investigations are crucial to bridge knowledge gaps linking oxylipin- and lipoprotein-related disorders in both periphery and CNS. Here, after providing a summary of existent literatures on lipoprotein oxylipin analysis methods, we emphasize the importance of lipoproteins in oxylipin transport and argue that understanding the compartmentalization and distribution of lipoprotein oxylipins may fundamentally alter our consideration of the roles of lipoprotein in cardiometabolic and neurological disorders.

Association between biochemical and hematologic factors with COVID-19 using data mining methods

BACKGROUND AND AIM

Coronavirus disease (COVID-19) is an infectious disease that can spread very rapidly with important public health impacts. The prediction of the important factors related to the patient's infectious diseases is helpful to health care workers. The aim of this research was to select the critical feature of the relationship between demographic, biochemical, and hematological characteristics, in patients with and without COVID-19 infection.

METHOD

A total of 13,170 participants in the age range of 35-65 years were recruited. Decision Tree (DT), Logistic Regression (LR), and Bootstrap Forest (BF) techniques were fitted into data. Three models were considered in this study, in model I, the biochemical features, in model II, the hematological features, and in model II, both biochemical and homological features were studied.

RESULTS

In Model I, the BF, DT, and LR algorithms identified creatine phosphokinase (CPK), blood urea nitrogen (BUN), fasting blood glucose (FBG), total bilirubin, body mass index (BMI), sex, and age, as important predictors for COVID-19. In Model II, our BF, DT, and LR algorithms identified BMI, sex, mean platelet volume (MPV), and age as important predictors. In Model III, our BF, DT, and LR algorithms identified CPK, BMI, MPV, BUN, FBG, sex, creatinine (Cr), age, and total bilirubin as important predictors.

CONCLUSION

The proposed BF, DT, and LR models appear to be able to predict and classify infected and non-infected people based on CPK, BUN, BMI, MPV, FBG, Sex, Cr, and Age which had a high association with COVID-19.

Adsorption of pulmonary and exogeneous surfactants on SARS-CoV-2 spike protein

COVID-19 is transmitted by airborne particles containing virions of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus virions represent nanoparticles enveloped by a lipid bilayer decorated by a "crown" of Spike protein protrusions. Virus transmission into the cells is induced by binding of Spike proteins with ACE2 receptors of alveolar epithelial cells. Active clinical search is ongoing for exogenous surfactants and biologically active chemicals capable of hindering virion-receptor binding. Here, we explore by using coarse-grained molecular dynamics simulations the physico-chemical mechanisms of adsorption of selected pulmonary surfactants, zwitterionic dipalmitoyl phosphatidyl choline and cholesterol, and exogeneous anionic surfactant, sodium dodecyl sulfate, on the S1-domain of the Spike protein. We show that surfactants form micellar aggregates that selectively adhere to the specific regions of the S1-domain that are responsible for binding with ACE2 receptors. We find distinctly higher cholesterol adsorption and stronger cholesterol-S1 interactions in comparison with other surfactants, that is consistent with the experimental observations of the effects of cholesterol on COVID-19 infection. Distribution of adsorbed surfactant along the protein residue chain is highly specific and inhomogeneous with preferential adsorption around specific amino acid sequences. We observe preferential adsorption of surfactants on cationic arginine and lysine residues in the receptor-binding domain (RBD) that play an important role in ACE2 binding and are present in higher amounts in Delta and Omicron variants, which may lead to blocking direct Spike-ACE2 interactions. Our findings of strong selective adhesion of surfactant aggregates to Spike proteins have important implications for informing clinical search for therapeutic surfactants for curing and preventing COVID-19 caused by SARS-CoV-2 and its variants.

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.

Metabolic Syndrome Is Associated with Poor Omicron Infection Prognosis While Inactivated Vaccine Improves the Outcome of Coronavirus Disease 2019 among Chinese Inhabitants: A Retrospective Observational Study from a Chinese Municipality

Coronavirus disease 2019 (COVID-19) and metabolic syndrome (MetS) are currently highly prevalent diseases worldwide. Studies on clinical outcomes of patients with Omicron and MetS, especially after vaccination with an inactivated vaccine are limited. Herein, we explored the relationship between MetS and the outcome of Omicron infection.

STUDY DESIGN

This was a retrospective observational study.

METHODS

This study recruited 316 individuals with Omicron infection. The inpatient data from between 8 January and 7 February 2022 were obtained from designated isolation hospitals in Tianjin, China. Hierarchical and multivariable analysis was conducted on age, gender, number of complications, and vaccination status.

RESULTS

Among the 316 study participants, 35.1% were diagnosed with MetS. The results showed that MetS was strongly associated with Intensive Unit Care (ICU) admission, Polymerase Chain Reaction (PCR) re-positivity, and severe COVID-19. The ICU admission rates of the unvaccinated individuals, those who received two-dose and full vaccination (3 doses), were 66.7%, 19.2%, and 0, respectively (p < 0.01). Two-dose and three-dose vaccinations significantly reduced PCR re-positivity.

CONCLUSIONS

In summary, MetS increases the risk of ICU admission, PCR re-positivity, and severe COVID-19. MetS is a composite predictor of poor outcomes of Omicron infection. Two shots of inactivated vaccine, specifically three doses, effectively protect against Omicron even in the high-risk group.

The bidirectional interaction of COVID-19 infections and lipoproteins

COVID-19 infections decrease total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I, A-II, and B levels while triglyceride levels may be increased or inappropriately normal for the poor nutritional status. The degree of reduction in total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I are predictive of mortality. With recovery lipid/lipoprotein levels return towards pre-infection levels and studies have even suggested an increased risk of dyslipidemia post-COVID-19 infection. The potential mechanisms for these changes in lipid and lipoprotein levels are discussed. Decreased HDL-C and apolipoprotein A-I levels measured many years prior to COVID-19 infections are associated with an increased risk of severe COVID-19 infections while LDL-C, apolipoprotein B, Lp (a), and triglyceride levels were not consistently associated with an increased risk. Finally, data suggest that omega-3-fatty acids and PCSK9 inhibitors may reduce the severity of COVID-19 infections. Thus, COVID-19 infections alter lipid/lipoprotein levels and HDL-C levels may affect the risk of developing COVID-19 infections.

The Association of the Levels of High-Density Lipoprotein and Apolipoprotein A1 with SARS-CoV-2 Infection and COVID-19 Severity: An Analysis of the N3C Database

This study analyzed data from the National COVID Cohort Collaborative (N3C) database to investigate whether high-density lipoprotein (HDL) and its major protein component, apolipoprotein A1 (apoA1), are associated with severe COVID-19 sequelae, specifically acute kidney injury (AKI) and severe COVID-19 disease as defined by the infection resulting in hospitalization, extracorporeal membrane oxygenation (ECMO), invasive ventilation, or death. Our study included a total of 1,415,302 subjects with HDL values and 3589 subjects with apoA1 values. Higher levels of both HDL and apoA1 were associated with a lower incidence of infection as well as a lower incidence of severe disease. Higher HDL levels were also associated with a lower incidence of developing AKI. Most comorbidities were negatively correlated with SARS-CoV-2 infection, presumably due to the behavioral changes that occurred as a result of the precautions taken by individuals with underlying comorbidities. The presence of comorbidities, however, was associated with developing severe COVID-19 disease and AKI. African American and Hispanic populations experienced worse outcomes, including a higher incidence of infection and the development of severe disease, as well as AKI. Smoking and being male were associated with a lower incidence of infection, while they were risk factors for the development of severe disease and AKI. The results on cholesterol and diabetes drugs warrant further research, given that the database included multiple drugs in each category impeding for analysis of specific medications. Despite the current limitations in the N3C data, this study is the first to investigate the roles of HDL and apoA1 on the outcomes of COVID-19 using the US population data.

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.

Low HDL-c levels at admission are associated with greater severity and worse clinical outcomes in patients with COVID-19 disease

Background and aims

HDL particles may act to buffer host cells from excessive inflammatory mediators. The aim of this study is to investigate if the lipid profile provides a prognostic biomarker for COVID-19 outcomes.

Methods

This was a prospective study of the characteristics of 125 adult COVID-19 patients with a lipid profile performed on the day of admission analyzed with regard to clinical outcomes.

Results

Seventy-seven patients (61.2%) were men, with a mean age of 66.3 (15.6) years. 54.1% had bilateral pneumonia. The all-cause mortality rate during hospitalization was 20.8%. We found a direct association between more severe disease assessed by the WHO classification, admission to the ICU and death with more pronounced lymphopenia, higher levels of CRP, ferritin (p < 0.001), D-dímer and lactate dehydrogenase (LDH) all statistically significant. Lower leves of HDL-c and LDL-c were also associated with a worse WHO classification, ICU admission, and death,. HDL-c levels were inversely correlated with inflammatory markers CRP (r = -0.333; p < 0.001), ferritin (r = -0.354; p < 0.001), D-dímer (r = -0.214; p < 0.001), LDH (r = -0.209; p < 0.001. LDL-c levels were significantly associated with CRP (r = -0.320; p < 0.001) and LDH (r = -0.269; p < 0.001). ROC curves showed that HDL [AUC = 0.737(0.586-0.887), p = 0.005] and lymphocytes [AUC = 0.672(0.497-0.847], p < 0.043] had the best prognostic accuracy to predict death. In a multivariate analysis, HDL-c (β = -0.146(0.770-0.971), p = 0.014) and urea (β = 0.029(1.003-1.057), p = 0.027) predicted mortality.

Conclusion

Hypolipidemia including HDL levels at admission identifies patients with a higher risk of death and worse clinical manifestations who may require more intensive care.

The potential role of scavenger receptor B type I (SR-BI) in SARS-CoV-2 infection

Scavenger receptor type B I (SR-BI), the major receptor for high-density lipoprotein (HDL) mediates the delivery of cholesterol ester and cholesterol from HDL to the cell membrane. SR-BI is implicated as a receptor for entry of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). SR-BI is colocalized with the angiotensin-converting enzyme 2 (ACE2) increasing the binding and affinity of SARS-CoV-2 to ACE2 with subsequent viral internalization. SR-BI regulates lymphocyte proliferation and the release of pro-inflammatory cytokines from activated macrophages and lymphocytes. SR-BI is reduced during COVID-19 due to consumption by SARS-CoV-2 infection. COVID-19-associated inflammatory changes and high angiotensin II (AngII) might be possible causes of repression of SR-BI in SARS-CoV-2 infection. In conclusion, the downregulation of SR-BI in COVID-19 could be due to direct invasion by SARS-CoV-2 or through upregulation of pro-inflammatory cytokines, inflammatory signaling pathways, and high circulating AngII. Reduction of SR-BI in COVID-19 look like ACE2 may provoke COVID-19 severity through exaggeration of the immune response. Further studies are invoked to clarify the potential role of SR-BI in the pathogenesis of COVID-19 that could be protective rather than detrimental.

Plasma Apolipoprotein Concentrations Are Highly Altered in Severe Intensive Care Unit COVID-19 Patients: Preliminary Results from the LIPICOR Cohort Study

SARS-CoV-2 infection goes beyond acute pneumonia, as it also impacts lipid metabolism. Decreased HDL-C and LDL-C levels have been reported in patients with COVID-19. The lipid profile is a less robust biochemical marker than apolipoproteins, components of lipoproteins. However, the association of apolipoprotein levels during COVID-19 is not well described and understood. The objective of our study is to measure plasma levels of 14 apolipoproteins in patients with COVID-19 and to evaluate the relationships between apolipoprotein levels, severity factors and patient outcomes. From November to March 2021, 44 patients were recruited on admission to the intensive care unit because of COVID-19. Fourteen apolipoproteins and LCAT were measured by LC-MS/MS in plasma of 44 COVID-19 patients on admission to the ICU and 44 healthy control subjects. Absolute apolipoprotein concentrations were compared between COVID-19 patients and controls. Plasma apolipoproteins (Apo) A (I, II, IV), C(I, II), D, H, J and M and LCAT were lower in COVID-19 patients, whereas Apo E was higher. COVID-19 severity factors such as PaO2/FiO2 ratio, SO-FA score and CRP were correlated with certain apolipoproteins. Lower Apo B100 and LCAT levels were observed in non-survivors of COVID-19 versus survivors. To conclude, in this study, lipid and apolipoprotein profiles are altered in COVID-19 patients. Low Apo B100 and LCAT levels may be predictive of non-survival in COVID-19 patients.

Fraction of plasma exomeres and low-density lipoprotein cholesterol as a predictor of fatal outcome of COVID-19

Transcriptomic analysis conducted by us previously revealed upregulation of genes involved in low-density lipoprotein particle receptor (LDLR) activity pathway in lethal COVID-19 caused by SARS-CoV-2 virus (severe acute respiratory syndrome coronavirus 2). Last data suggested the possible role of extracellular vesicles in COVID-19 pathogenesis. The aim of the present study was to retrospectively evaluate parameters of cholesterol metabolism and newly identified EVs, exomeres, as possible predictors of fatal outcome of COVID-19 patients infected by the Alpha and the Delta variants of SARS-CoV-2 virus. Blood from 67 patients with severe COVID-19 were collected at the time of admission to the intensive care unit (ICU) and 7 days after admission to the ICU. After 30 days patients were divided into two subgroups according to outcome-34 non-survivors and 33 survivors. This study demonstrated that plasma low- and high-density lipoprotein cholesterol levels (LDL-C and HDL-C) were decreased in non-survivors compared to controls at the time of admission to the ICU. The conjoint fraction of exomeres and LDL particles measured by dynamic light scattering (DLS) was decreased in non-survivors infected by the Alpha and the Delta variants compared to survivors at the time of admission to the ICU. We first showed that reduction of exomeres fraction may be critical in fatal outcome of COVID-19.

Potential antiviral effects of pantethine against SARS-CoV-2

SARS-CoV-2 interacts with cellular cholesterol during many stages of its replication cycle. Pantethine was reported to reduce total cholesterol levels and fatty acid synthesis and potentially alter different processes that might be involved in the SARS-CoV-2 replication cycle. Here, we explored the potential antiviral effects of pantethine in two in vitro experimental models of SARS-CoV-2 infection, in Vero E6 cells and in Calu-3a cells. Pantethine reduced the infection of cells by SARS-CoV-2 in both preinfection and postinfection treatment regimens. Accordingly, cellular expression of the viral spike and nucleocapsid proteins was substantially reduced, and we observed a significant reduction in viral copy numbers in the supernatant of cells treated with pantethine. In addition, pantethine inhibited the infection-induced increase in TMPRSS2 and HECT E3 ligase expression in infected cells as well as the increase in antiviral interferon-beta response and inflammatory gene expression in Calu-3a cells. Our results demonstrate that pantethine, which is well tolerated in humans, was very effective in controlling SARS-CoV-2 infection and might represent a new therapeutic drug that can be repurposed for the prevention or treatment of COVID-19 and long COVID syndrome.

Angiotensin Converting Enzyme 1 Polymorphisms and Lipid Profile in Mexican Patients With COVID-19

BACKGROUND/AIM

Renin-angiotensin system (RAS) is present in a diverse type of cells and plays an important role in lung physiology and pathophysiology. Angiotensin converting enzymes (ACE) are part of the RAS system. There are still controversies about the association of I/D polymorphisms of ACE1 with COVID-19 severity. The goal of the study was to determine whether there is an association of the I/D polymorphism with severity of COVID-19 in Mexican patients.

PATIENTS AND METHODS

The study included voluntary participants: 53 healthy individuals negative to RT-PCR COVID-19 (control), and 165 patients positive to COVID-19. Severity was defined by the need of hospitalization, invasive ventilation, shock, or multiple organ failure. The patient group consisted of 28 asymptomatic, 82 with mild, and 55 with severe COVID-19. I/D polymorphism was determined by PCR. Rutinary laboratory tests were performed in all the participants.

RESULTS

DD polymorphism was significantly associated with severe COVID-19, independently of comorbidities, or any other variable. Receiver operator characteristic curves demonstrated association of low total cholesterol, low high-density lipoproteins, and high c-reactive protein with severity of COVID-19.

CONCLUSION

The DD polymorphism was associated with the course of the infection and severity of COVID-19 in a sample of Mexican patients.

Low HDL Cholesterol Efflux Capacity Indicates a Fatal Course of COVID-19

Plasma membrane cholesterol is required for proper trafficking and localization of receptors that facilitate severe acute respiratory syndrome coronavirus 2 infection. High-density lipoproteins (HDL) mobilize plasma membrane cholesterol, and HDL-cholesterol levels are associated with the severity of COVID-19 disease and mortality. However, HDL-cholesterol levels poorly reflect the function of this complex family of particles, and a detailed assessment of COVID-19-associated changes in HDL functionality and its prognostic value is lacking. In the present study, we assessed HDL cholesterol efflux capacity, HDL anti-inflammatory and antioxidant properties, and changes in HDL composition and metabolism in COVID-19 (n = 48) and non-COVID pneumonia patients (n = 32). COVID-19 infection markedly reduced the activity of lecithin-cholesteryl-acyltransferase and functional parameters of HDL, such as the cholesterol efflux capacity, arylesterase activity of paraoxonase 1, and anti-oxidative capacity of apoB-depleted serum when compared to non-COVID pneumonia at baseline, paralleled by markedly reduced levels of HDL-cholesterol. Of particular interest, low HDL cholesterol efflux capacity was associated with increased mortality risk in COVID-19 patients, independent of HDL-C levels. Our results highlight profound effects of COVID-19 infection on HDL function, metabolism, and composition. Low HDL cholesterol efflux capacity indicates a fatal course of COVID-19, independent of HDL-cholesterol levels.

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.

Relationship between Metabolic Syndrome Components and COVID-19 Disease Severity in Hospitalized Patients: A Pilot Study

Background

Preliminary data suggest that patients with comorbidities are more susceptible to severe COVID-19 infection. However, data regarding the presence of metabolic syndrome (MetS) in patients with COVID-19 are scarce.

Aim

In the present study, we aim to investigate the association between MetS components and disease severity in hospitalized COVID-19 patients.

Methods

We conducted a prospective observational study of 90 hospitalized patients with COVID-19 pneumonia at a tertiary hospital. The study population consisted of inpatients who tested positive by the reverse transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2. Patients with critical COVID-19 disease on admission were excluded. Adult Treatment Panel III of the National Cholesterol Education Program (NCEP-ATP III) criteria were used to define MetS. Laboratory analysis and thorax CT were performed on admission.

Results

90 patients, 60 moderate and 30 severe COVID-19 patients, included in the study. The percentage of MetS cases was higher among severe COVID-19 patients (p=0.018). Of the MetS criteria fasting blood glucose (p=0.004), triglycerides (p=0.007) were significantly higher in patients with severe COVID-19 disease with no statistical significance found in waist circumference (WC) (p=0.348), systolic blood pressure (p=0.429), and HDL-C levels (p=0.263) between two groups. Body mass index (BMI) values were similar in both severe and moderate cases (p=0.854). In logistic regression analysis, serum triglycerides (p=0.024), HDL-C (p=0.006), and WC (p=0.004) were found as independent prognostic factor for severe COVID-19 infection.

Conclusion

Severe COVID-19 patients have higher rates of MetS. Serum triglycerides, HDL-C, and WC have an impact on disease severity in COVID-19.

High-density lipoproteins may play a crucial role in COVID-19

Background

Lipids play a central role in the virus life cycle and are a crucial target to develop antiviral therapeutics. Importantly, among the other lipoproteins, the ‘good cholesterol’ high-density lipoprotein (HDL) has been widely studied for its role in not only cardiovascular but several infectious diseases as well. Studies have suggested a role of serum lipids and lipoproteins including HDL, total cholesterol (TC), triglycerides (TG), and low-density lipoproteins (LDL) in several viral infections including COVID-19. This disease is currently a major public health problem and there is a need to explore the role of these host lipids/lipoproteins in virus pathogenesis.

Methodology

A total of 75 retrospective COVID-19 positive serum samples and 10 COVID-19 negative controls were studied for their lipid profiles including TC, HDL, LDL, and very-low-density lipoproteins (VLDL), and TG.

Results

Systematic literature search on dyslipidemia status in India shows that low HDL is the most common dyslipidemia. In this cohort, 65% (49) of COVID-19 patients had severely low HDL levels whereas 35% (26) had moderately low HDL and none had normal HDL levels. On the other hand, ~ 96% of samples had normal TC (72) and LDL (72) levels. VLDL and TG levels were also variable. In the controls, 100% of samples had moderately low HDL but none severely low HDL levels.

Conclusion

HDL likely plays a crucial role in COVID-19 infection and outcomes. The causal relationships between HDL levels and COVID-19 need to be studied extensively for an understanding of disease pathogenesis and management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-022-01865-4.

Sosa S, Mateu-Rogell P, Ortega-Castillo V, Tolentino-Dolores M, Perichart-Perera O, Franco-Gallardo JO, Carranco-Martínez JA, Prieto-Rodríguez S, Guzmán-Huerta M, Missirlis F, Estrada-Gutierrez G. Inflammatory-Metal Profile as a Hallmark for COVID-19 Severity During Pregnancy

Pregnancy makes women more susceptible to infectious agents; however, available data on the effect of SARS-CoV-2 on pregnant women are limited. To date, inflammatory responses and changes in serum metal concentration have been reported in COVID-19 patients, but few associations between metal ions and cytokines have been described. The aim of this study was to evaluate correlations between inflammatory markers and serum metal ions in third-trimester pregnant women with varying COVID-19 disease severity. Patients with severe symptoms had increased concentrations of serum magnesium, copper, and calcium ions and decreased concentrations of iron, zinc, and sodium ions. Potassium ions were unaffected. Pro-inflammatory cytokines IL-6, TNF-α, IL-8, IL-1α, anti-inflammatory cytokine IL-4, and the IP-10 chemokine were induced in the severe presentation of COVID-19 during pregnancy. Robust negative correlations between iron/magnesium and zinc/IL-6, and a positive correlation between copper/IP-10 were observed in pregnant women with the severe form of the disease. Thus, coordinated alterations of serum metal ions and inflammatory markers – suggestive of underlying pathophysiological interactions—occur during SARS-CoV-2 infection in pregnancy.

COVID-19 and Lipid Disorders

An elevated cholesterol concentration has been suspected to increase the susceptibility for SARS-COV-2 infection. Cholesterol plays a central role in the mechanisms of the SARS-COV-2 infection. In contrast, higher HDL-cholesterol levels seem to be protective. During COVID-19 disease, LDL-cholesterol and HDL-cholesterol appear to be decreased. On the other hand, triglycerides (also in different lipoprotein fractions) were elevated. Lipoprotein(a) may increase during this disease and is most probably responsible for thromboembolic events. This lipoprotein can induce a progression of atherosclerotic lesion formation. The same is suspected for the SARS-COV-2 infection itself. COVID-19 patients are at increased risk of incident cardiovascular diseases, including cerebrovascular disorders, dysrhythmias, ischemic and non-ischemic heart disease, pericarditis, myocarditis, heart failure, and thromboembolic disorders. An ongoing lipid-lowering therapy, including lipoprotein apheresis, is recommended to be continued during the COVID-19 disease, though the impact of lipid-lowering drugs or the extracorporeal therapy on prognosis should be studied in further investigations.

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.

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.

Neural Network Training with Highly Incomplete Medical Datasets

Neural network training and validation rely on the availability of large high-quality datasets. However, in many cases only incomplete datasets are available, particularly in health care applications, where each patient typically undergoes different clinical procedures or can drop out of a study. Since the data to train the neural networks need to be complete, most studies discard the incomplete datapoints, which reduces the size of the training data, or impute the missing features, which can lead to artefacts. Alas, both approaches are inadequate when a large portion of the data is missing. Here, we introduce GapNet, an alternative deep-learning training approach that can use highly incomplete datasets without overfitting or introducing artefacts. First, the dataset is split into subsets of samples containing all values for a certain cluster of features. Then, these subsets are used to train individual neural networks. Finally, this ensemble of neural networks is combined into a single neural network whose training is fine-tuned using all complete datapoints. Using two highly incomplete real-world medical datasets, we show that GapNet improves the identification of patients with underlying Alzheimer’s disease pathology and of patients at risk of hospitalization due to Covid-19. Compared to commonly used imputation methods, this improvement suggests that GapNet can become a general tool to handle incomplete medical datasets.

Changes in the Blood Viscosity in Patients With SARS-CoV-2 Infection

Coronavirus disease 2019 (COVID-19) is caused by a novel virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2-induced hyperinflammation together with alteration of plasma proteins, erythrocyte deformability, and platelet activation, may affect blood viscosity. Thus, this review aimed to study the link between SARS-CoV-2 infection and alteration of blood viscosity in COVID-19 patients. In order to review findings related to hyperviscosity in COVID-19, we suggested a protocol for narrative review of related published COVID-19 articles. Hyperviscosity syndrome is developed in different hematological disorders including multiple myeloma, sickle cell anemia, Waldenstorm macroglobulinemia, polycythemia, and leukemia. In COVID-19, SARS-CoV-2 may affect erythrocyte morphology via binding of membrane cluster of differentiation 147 (CD147) receptors, and B and 3 proteins on the erythrocyte membrane. Variations in erythrocyte fragility and deformability with endothelial dysfunction and oxidative stress in SARS-CoV-2 infection may cause hyperviscosity syndrome in COVID-19. Of interest, hyperviscosity syndrome in COVID-19 may cause poor tissue perfusion, peripheral vascular resistance, and thrombosis. Most of the COVID-19 patients with a blood viscosity more than 3.5 cp may develop coagulation disorders. Of interest, hyperviscosity syndrome is more commonly developed in vaccine recipients who had formerly received the COVID-19 vaccine due to higher underlying immunoglobulin concentrations, and only infrequently in those who have not received the COVID-19 vaccine. Taken together, these observations are untimely too early to give a final connotation between COVID-19 vaccination and the risk for development of hyperviscosity syndrome, consequently prospective and retrospective studies are necessary in this regard.

Effect of COVID-19 on lipid profile parameters and its correlation with acute phase reactants: A single-center retrospective analysis

Background and objective

The development and correlation of dyslipidemia is unknown in COVID-19. This investigation was performed to assess the pathological alterations in lipid profile and their association in COVID-19.

Methods

This was a retrospective study performed on real-world patients to assess serum levels of LDL-C, HDL, TG, TC on COVID-19 patients (mild: 319; moderate: 391; critical: 357). Age- and gender-matched controls who had their lipid profiles in the same period were included as the control group.

Results

LDL-C, HDL, TG, and TC levels were significantly lower in COVID-19 patients when compared with the control group (P < 0.001, 0.047, 0.045, <0.001, respectively). All parameters decreased gradually with COVID-19 disease severity (LDL-C: median (IQR), mild: 98 (91,134); moderate: 97 (81,113); critical: 68 (68,83); HDL: mild: 45 (37,50); moderate: 46 (41,50); critical: 40 (37,46); TG: mild: 186 (150,245); moderate: 156 (109,198); critical: 111 (98,154); TC: mild: 224 (212,238); moderate: 212 (203,213); critical: 154 (125,187)). Logistic regression demonstrated lipid profile as predictor of severity of COVID-19 disease.

Conclusion

Hypolipidemia develops in increasing frequency with severe COVID-19 disease. It inversely correlates with levels of acute-phase reactants, indicating SARS-COV-2 as the causative agent for alteration in lipid and thyroid levels.

Is there any association between plasma lipid profile and severity of COVID-19?

BACKGROUND

COVID-19 is an infectious disease which caused a pandemic with many diseases and fatalities. This new variant of coronavirus called SARS-CoV-2 and is primarily characterized by respiratory symptoms. There are some data indicating that LDL-cholesterol (LDL-C) as well as HDL-cholesterol (HDL-C) levels are inversely correlated to disease severity and could act as a predictor for disease progression and unfavorable prognosis. However, the results of some other studies do not confirm this. This current study aimed to provide an answer to this question.

METHODS

This prospective, single-center study analyzed 367 confirmed COVID-19 patients to find whether there are any differences in plasma lipoproteins between survivors and non-survivors patients or between the patients with a "duration of ≤10 days intensive unit care (ICU) stay" and patients with a "duration of >10 days ICU stay".

RESULTS

No association between any lipid/lipoprotein parameter and the severity of COVID-19 could be found but survivors and non-survivors did differ concerning total cholesterol and LDL-C levels.

CONCLUSION

Multivariate cox regression analysis could not prove any association between lipids/lipoproteins and severe events in COVID-19 patients. Significantly less non-survivors with COVID-19 were taking atorvastatin than survivors which is consistent with the majority of previous findings.

Hyperviscosity syndrome in COVID-19 and related vaccines: exploring of uncertainties

Hyperviscosity syndrome (HVS) recently emerged as a complication of coronavirus disease 2019 (COVID-19) and COVID-19 vaccines. Therefore, the objectives of this critical review are to establish the association between COVID-19 and COVID-19 vaccines with the development of HVS. HVS may develop in various viral infections due to impairment of humoral and cellular immunity with elevation of immunoglobulins. COVID-19 can increase blood viscosity (BV) through modulation of fibrinogen, albumin, lipoproteins, and red blood cell (RBC) indices. HVS can cause cardiovascular and neurological complications in COVID-19 like myocardial infarction (MI) and stroke. HVS with or without abnormal RBCs function in COVID-19 participates in the reduction of tissue oxygenation with the development of cardio-metabolic complications and long COVID-19. Besides, HVS may develop in vaccine recipients with previous COVID-19 due to higher underlying Ig concentrations and rarely without previous COVID-19. Similarly, patients with metabolic syndrome are at the highest risk for propagation of HVS after COVID-19 vaccination. In conclusion, COVID-19 and related vaccines are linked with the development of HVS, mainly in patients with previous COVID-19 and underlying metabolic derangements. The possible mechanism of HVS in COVID-19 and related vaccines is increasing levels of fibrinogen and immunoglobulins. However, dehydration, oxidative stress, and inflammatory reactions are regarded as additional contributing factors in the pathogenesis of HVS in COVID-19. However, this critical review cannot determine the final causal relationship between COVID-19 and related vaccines and the development of HVS. Prospective and retrospective studies are warranted in this field.

Altered Lipid Profile in COVID-19 Patients and Metabolic Reprogramming

Background

Coronavirus disease 2019 (COVID-19) is a global pandemic. Previous studies have reported dyslipidemia in patients with COVID-19. Herein, we conducted a retrospective study and a bioinformatics analysis to evaluate the essential data of the lipid profile as well as the possible mechanism in patients with COVID-19.

Methods

First of all, the retrospective study included three cohorts: patients with COVID-19, a healthy population, and patients with chronic obstructive pulmonary disease (COPD). For each subject, serum lipid profiles in the biochemical data were compared, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Furthermore, bioinformatics analyses were performed for exploring the biological or immunological mechanisms.

Results

In line with the biochemical data of the three cohorts, the statistical result displayed that patients with COVID-19 were more likely to have lower levels of TC and HDL-C as compared with healthy individuals. The differential proteins associated with COVID-19 are involved in the lipid pathway and can target and regulate cytokines and immune cells. Additionally, a heatmap revealed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections were possibly involved in lipid metabolic reprogramming. The viral proteins, such as spike (S) and non-structural protein 2 (Nsp2) of SARS-CoV-2, may be involved in metabolic reprogramming.

Conclusion

The metabolic reprogramming after SARS-CoV-2 infections is probably associated with the immune and clinical phenotype of patients. Hence, metabolic reprogramming may be targeted for developing antivirals against COVID-19.

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.

Plasma Metabolomic Alterations Induced by COVID-19 Vaccination Reveal Putative Biomarkers Reflecting the Immune Response

Vaccination is currently the most effective strategy for the mitigation of the COVID-19 pandemic. mRNA vaccines trigger the immune system to produce neutralizing antibodies (NAbs) against SARS-CoV-2 spike proteins. However, the underlying molecular processes affecting immune response after vaccination remain poorly understood, while there is significant heterogeneity in the immune response among individuals. Metabolomics have often been used to provide a deeper understanding of immune cell responses, but in the context of COVID-19 vaccination such data are scarce. Mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR)-based metabolomics were used to provide insights based on the baseline metabolic profile and metabolic alterations induced after mRNA vaccination in paired blood plasma samples collected and analysed before the first and second vaccination and at 3 months post first dose. Based on the level of NAbs just before the second dose, two groups, "low" and "high" responders, were defined. Distinct plasma metabolic profiles were observed in relation to the level of immune response, highlighting the role of amino acid metabolism and the lipid profile as predictive markers of response to vaccination. Furthermore, levels of plasma ceramides along with certain amino acids could emerge as predictive biomarkers of response and severity of inflammation.

First Recombinant High-Density Lipoprotein Particles Administration in a Severe ICU COVID-19 Patient, a Multi-Omics Exploratory Investigation

High-density lipoproteins (HDLs) have multiple endothelioprotective properties. During SARS-CoV-2 infection, HDL-cholesterol (HDL-C) concentration is markedly reduced, and studies have described severe impairment of the functionality of HDL particles. Here, we report a multi-omic investigation of the first administration of recombinant HDL (rHDL) particles in a severe COVID-19 patient in an intensive care unit. Plasma ApoA1 increased and HDL-C decreased after each recombinant HDL injection, suggesting that these particles were functional in terms of reverse cholesterol transport. The proportion of large HDL particles also increased after injection of recombinant HDL. Shotgun proteomics performed on HDLs isolated by ultracentrifugation indicated that ApoA1 was more abundant after injections whereas most of the pro-inflammatory proteins identified were less abundant. Assessment of Serum amyloid A-1, inflammatory markers, and cytokines showed a significant decrease for most of them during recombinant HDL infusion. Our results suggest that recombinant HDL infusion is feasible and a potential therapeutic strategy to be explored in COVID-19 patients.

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.

Cellular metabolic basis of altered immunity in the lungs of patients with COVID-19

Metabolic pathways drive cellular behavior. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes lung tissue damage directly by targeting cells or indirectly by producing inflammatory cytokines. However, whether functional alterations are related to metabolic changes in lung cells after SARS-CoV-2 infection remains unknown. Here, we analyzed the lung single-nucleus RNA-sequencing (snRNA-seq) data of several deceased COVID-19 patients and focused on changes in transcripts associated with cellular metabolism. We observed upregulated glycolysis and oxidative phosphorylation in alveolar type 2 progenitor cells, which may block alveolar epithelial differentiation and surfactant secretion. Elevated inositol phosphate metabolism in airway progenitor cells may promote neutrophil infiltration and damage the lung barrier. Further, multiple metabolic alterations in the airway goblet cells are associated with impaired muco-ciliary clearance. Increased glycolysis, oxidative phosphorylation, and inositol phosphate metabolism not only enhance macrophage activation but also contribute to SARS-CoV-2 induced lung injury. The cytotoxicity of natural killer cells and CD8⁺ T cells may be enhanced by glycerolipid and inositol phosphate metabolism. Glycolytic activation in fibroblasts is related to myofibroblast differentiation and fibrogenesis. Glycolysis, oxidative phosphorylation, and glutathione metabolism may also boost the aging, apoptosis and proliferation of vascular smooth muscle cells, resulting in pulmonary arterial hypertension. In conclusion, this preliminary study revealed a possible cellular metabolic basis for the altered innate immunity, adaptive immunity, and niche cell function in the lung after SARS-CoV-2 infection. Therefore, patients with COVID-19 may benefit from therapeutic strategies targeting cellular metabolism in future.

Alteration of the gut microbiota following SARS-CoV-2 infection correlates with disease severity in hamsters

Mounting evidence suggests that the gut-to-lung axis is critical during respiratory viral infections. We herein hypothesized that disruption of gut homeostasis during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may associate with early disease outcomes. To address this question, we took advantage of the Syrian hamster model. Our data confirmed that this model recapitulates some hallmark features of the human disease in the lungs. We further showed that SARS-CoV-2 infection associated with mild intestinal inflammation, relative alteration in intestinal barrier property and liver inflammation and altered lipid metabolism. These changes occurred concomitantly with an alteration of the gut microbiota composition over the course of infection, notably characterized by a higher relative abundance of deleterious bacterial taxa such as Enterobacteriaceae and Desulfovibrionaceae. Conversely, several members of the Ruminococcaceae and Lachnospiraceae families, including bacteria known to produce the fermentative products short-chain fatty acids (SCFAs), had a reduced relative proportion compared to non-infected controls. Accordingly, infection led to a transient decrease in systemic SCFA amounts. SCFA supplementation during infection had no effect on clinical and inflammatory parameters. Lastly, a strong correlation between some gut microbiota taxa and clinical and inflammation indices of SARS-CoV-2 infection severity was evidenced. Collectively, alteration of the gut microbiota correlates with disease severity in hamsters making this experimental model valuable for the design of interventional, gut microbiota-targeted, approaches for the control of COVID-19.Abbreviations: SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; COVID-19, coronavirus disease 2019; SCFAs, short-chain fatty acids; dpi, day post-infection; RT-PCR, reverse transcription polymerase chain reaction; IL, interleukin. ACE2, angiotensin converting enzyme 2; TMPRSS2, transmembrane serine protease 2.

Body composition, physical capacity, and immuno-metabolic profile in community-acquired pneumonia caused by COVID-19, influenza, and bacteria: a prospective cohort study

BACKGROUND

Different pathogens can cause community-acquired pneumonia (CAP); however, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has re-emphasized the vital role of respiratory viruses as a cause of CAP. The aim was to explore differences in metabolic profile, body composition, physical capacity, and inflammation between patients hospitalized with CAP caused by different etiology.

METHODS

A prospective study of Danish patients hospitalized with CAP caused by SARS-CoV-2, influenza, or bacteria. Fat (FM) and fat-free mass (FFM) were assessed with bioelectrical impedance analysis. Physical activity and capacity were assessed using questionnaires and handgrip strength. Plasma (p)-glucose, p-lipids, hemoglobin A1c (HbA1c), p-adiponectin, and cytokines were measured.

RESULTS

Among 164 patients with CAP, etiology did not affect admission levels of glucose, HbA1c, adiponectin, or lipids. Overall, 15.2% had known diabetes, 6.1% had undiagnosed diabetes, 51.3% had pre-diabetes, 81% had hyperglycemia, and 60% had low HDL-cholesterol, with no difference between groups. Body mass index, FM, and FFM were similar between groups, with 73% of the patients being characterized with abdominal obesity, although waist circumference was lower in patients with COVID-19. Physical capacity was similar between groups. More than 80% had low handgrip strength and low physical activity levels. Compared to patients with influenza, patients with COVID-19 had increased levels of interferon (IFN)-γ (mean difference (MD) 4.14; 95% CI 1.36-12.58; p = 0.008), interleukin (IL)-4 (MD 1.82; 95% CI 1.12-2.97; p = 0.012), IL-5 (MD 2.22; 95% CI 1.09-4.52; p = 0.024), and IL-6 (MD 2.41; 95% CI 1.02-5.68; p = 0.044) and increased IFN-γ (MD 6.10; 95% CI 2.53-14.71; p < 0.001) and IL-10 (MD 2.68; 95% CI 1.53-4.69; p < 0.001) compared to patients with bacterial CAP, but no difference in IL-1β, tumor necrosis factor-α, IL-8, IL-18, IL-12p70, C-reactive protein, and adiponectin.

CONCLUSION

Despite higher inflammatory response in patients with COVID-19, metabolic profile, body composition, and physical capacity were similar to patients with influenza and bacterial CAP.

Impact of Metabolic Risk Factors on COVID-19 Clinical Outcomes: An Extensive Review

BACKGROUND

Cardiovascular (CV) risk factors, particularly cardiometabolic, seem to be associated with heightened severity and increased morbimortality in patients infected with the novel Coronavirus disease-2019 (COVID-19).

METHODS

A thorough scoping review was conducted to elucidate and summarize the latest evidence for the effects of adverse cardiac metabolic profiles on the severity, morbidity, and prognosis of COVID-19 infection.

RESULTS

The pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is complex, being characterized by viral-induced immune dysregulation and hypercytokinemia, particularly in patients with critical disease, evolving with profound endothelial dysfunction, systemic inflammation, and prothrombotic state. Moreover, cardiovascular comorbidities such as diabetes are the most prevalent amongst individuals requiring hospitalization, raising concerns towards the clinical evolution and prognosis of these patients. The chronic proinflammatory state observed in patients with cardiovascular risk factors may contribute to the immune dysregulation mediated by SARS-CoV-2, favoring more adverse clinical outcomes and increased severity. Cardiometabolism is defined as a combination of interrelated risk factors and metabolic dysfunctions such as dyslipidemia, insulin resistance, impaired glucose tolerance, and central adiposity, which increase the likelihood of vascular events, being imperative to specifically analyze its clinical association with COVID-19 outcomes.

CONCLUSION

DM and obesity appears to be important risk factors for severe COVID-19. The chronic proinflammatory state observed in patients with excess visceral adipose tissue (VAT) possibly augments COVID-19 immune hyperactivity leading to more adverse clinical outcomes in these patients.

APOA1 Level is Negatively Correlated with the Severity of COVID-19

Objective

We used public data to analyze the proteomics, metabolomics and transcriptomics characteristics of COVID-19 patients to identify potential therapeutic targets. More importantly, we also collected clinical data for verification to make the analysis results more reliable.

Methods

Download the serum proteomics and metabolomics data of COVID-19 patients and describe their changes in serum proteins and metabolites, and use bioinformatics analysis methods to identify potential biomarkers and therapeutic targets. Finally, clinical data and experimental data of cell infection were combined for verification.

Results

It was found that the serum apolipoprotein A1 (APOA1) protein level in COVID-19 patients was down-regulated (log2FC = −0.39, false discovery rate (FDR) < 0.001), and the degree of reduction in the severe group was more significant (kruskal-test p = 2.5e-05). What is more, APOA1 was not only expressed lower in male patients (Wilcox-test p = 0.012), but also negatively correlated with C-reactive protein (CRP, r = −0.37, p = 0.019). The experiment data from SARS-CoV-2 infected cells further showed that the protein and transcript level of APOA1 gradually decreased as the infection time increased, and the transcription level (log₂FC = −8.3, FDR = 0.0015) was more down-regulated than protein level (log2FC = −0.95, FDR = 0.0014). More importantly, the collected clinical data also confirmed that APOA1 was down-regulated in COVID-19 patients (kruskal-test p = 0.001), and APOA1 levels are negatively correlated with IL6 (r = −0.396, p = 2.22e-07), D-dimers (DD, r = −0.262, p = 8.19e-04), prothrombin time (PT, r = −0.464, p = 6.68e-10) and thrombin time (TT, r = −0.279, p = 3.46e-04).

Conclusion

The degree of down-regulation of APOA1 is positively correlated with the severity of COVID-19, and the expression level of APOA1 is negatively correlated with CRP, IL6, DD, PT, TT, and positively correlated with HD and LDL. This indicates that APOA1 may be a key molecule in tandem acute inflammatory response, coagulation abnormalities and cholesterol metabolism disorder in COVID-19, and could be a potential therapeutic target.

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.