Low HDL and high triglycerides predict COVID-19 severity

SARS-CoV-2 infection and vaccination in patients with pituitary diseases: the experience of a Brazilian reference center

PURPOSE

To evaluate the prevalence and characteristics of SARS-CoV-2 infection, and the prevalence, efficacy, and safety of anti-SARS-CoV-2 vaccination in patients with pituitary diseases.

METHODS

Observational, cross-sectional study of adult patients with pituitary diseases followed in a reference center. Clinical data were collected and a questionnaire about SARS-CoV-2 infection, vaccination and its possible adverse effects was applied. COVID-19 disease severity was defined as mild, moderate, and severe according to the WHO classification.

RESULTS

145 patients were studied (79 women; age 50 ± 15.8 years; duration of pituitary disease 16.8 ± 11.5 years), the cause of pituitary disease was tumoral in 74.5%, and 45.9% were on glucocorticoid replacement due to ACTH deficiency. SARS-CoV-2 infection was confirmed in 51 patients (35.2%; 32 women; age 53.8 ± 14.8 years, 22 before vaccination), with 28 (54.9%), 17 (33.3%) and 6 (11.8%) cases of mild, moderate, and severe disease, respectively, and hospitalization was indicated in 7 (14%) cases. One mild case presented pituitary apoplexy after SARS-CoV-2 infection. Advanced age was a risk factor for COVID-19. Patients with moderate and severe forms of COVID-19 had higher prevalence of dyslipidemia and duration of pituitary disease. All but one of the participants were vaccinated against COVID-19, and 60.4% had adverse events, the most common local pain (54.0%), fever (33.3%), and headache (18.4%), with one case of alopecia and two of persistent fatigue.

CONCLUSION

The prevalence of SARS-CoV-2 infection in our cohort was 35.2%, including 14% of moderate and severe cases requiring hospitalization. The vaccination was universal and safe.

Lipidomic and metabolomic changes in community-acquired and COVID-19 pneumonia

This prospective observational study compared the 1H NMR blood lipidomes and metabolomes of 71 patients with community-acquired pneumonia (CAP), 75 patients with COVID-19 pneumonia, and 75 healthy controls (matched by age and sex) to identify potential biomarkers and pathways associated with respiratory infections. Both pneumonia groups had comparable severity indices, including mortality, invasive mechanical ventilation, and intensive care unit admission rates. Patients with COVID-19 pneumonia exhibited more pronounced hypolipidemia, with significantly lower levels of total cholesterol and LDL-c compared to patients with CAP. Atherogenic lipoprotein subclasses (VLDL-cholesterol, IDL-cholesterol, IDL-triglyceride, and LDL-triglyceride/LDL-cholesterol) were significantly increased in severe cases of both pneumonia types, while lower HDL-c and small, dense HDL particles were associated with more severe illness. Both infected groups showed decreased esterified cholesterol and increased triglycerides, along with reduced phosphatidylcholine, lysophosphatidylcholine, PUFA, omega-3 fatty acids, and DHA. Additionally, infected patients had elevated levels of glucose, lactate, 3-hydroxybutyrate, and acetone, which are linked to inflammation, hypoxemia, and sepsis. Increased levels of branched-chain amino acids, alanine, glycine, and creatine, which are involved in energy metabolism and protein catabolism, were also observed. Neurotransmitter synthesis metabolites like histidine and glutamate were higher in infected patients, especially those with COVID-19. Notably, severe infections showed a significant decrease in glutamine, essential for lymphocyte and macrophage energy. The severity of COVID-19 pneumonia was also associated with elevated glycoprotein levels (glycoprotein A, glycoprotein B, and glycoprotein F), indicating an inflammatory state. These findings suggest that metabolomic and lipidomic changes in pneumonia are connected to bioenergetic pathways regulating the immune response.

Pre-hospital oxygen therapy and saturation variability in COVID-19 patients with and without glucose metabolism disorders: part of the COLOS Study

The COVID-19 pandemic has revealed that viruses can have multiple receptor properties, penetrating various tissues and causing mutations in various genes, thus promoting a range of metabolic disorders. The purpose of this study was to investigate the connection between three factors: diabetic status, pre-hospitalization oxygen therapy, and saturation levels, to the values of morphological, inflammatory, and biochemical parameters in the blood serum of COVID-19 patients. The study group consisted of 2139 patients, 1076 women (50.30%) and 1063 men (49.70%), with an average age of 63.73 ± 15.69 years. The population was divided into three groups based on a three-stage scale, taking into account patients with either type 2 diabetes/prediabetes (473 patients), those who received oxygen therapy before hospitalization, and those with a saturation value of below 95% (cut-off value). Among patients who did not receive pre-hospitalization oxygen therapy, those with diabetes and a SpO2 level < 95% had significantly higher levels of D-dimers, procalcitonin, albumin, lymphocytes, RDW-SD ≥ 47, potassium, creatinine, and troponin T when compared to diabetic patients with a SpO2 level ≥ 95%. Similarly, in the same group of patients without pre-hospitalization oxygen therapy, those without diabetes but with a SpO2 level < 95% showed significantly increased levels of IL-6, CRP, albumin, lymphocytes, RDW-SD ≥ 47, glucose, potassium, sodium, creatinine, and ALT, compared to patients without diabetes and with a SpO2 level ≥ 95%. The findings suggest that lower saturation levels may result in increased potassium and glucose levels in patients who did not receive any oxygen therapy before hospitalization due to COVID-19. It is hypothesized that this may be caused by damage to pancreatic β-cells by SARS-CoV-2, and disturbances in the potassium channel, leading to cell membrane depolarization and insulin secretion.

Case-control study on post-COVID-19 conditions reveals severe acute infection and chronic pulmonary disease as potential risk factors

Post-COVID-19 conditions (long COVID) has impacted many individuals, yet risk factors for this condition are poorly understood. This retrospective analysis of 88,943 COVID-19 patients at a multi-state US health system compares phenotypes, laboratory tests, medication orders, and outcomes for 1,086 long-COVID patients and their matched controls. We found that history of chronic pulmonary disease (CPD) (odds ratio: 1.9, 95% CI: [1.5, 2.6]), migraine (OR: 2.2, [1.6, 3.1]), and fibromyalgia (OR: 2.3, [1.3, 3.8]) were more common for long-COVID patients. During the acute infection phase long COVID patients exhibited high triglycerides, low HDL cholesterol, and a high neutrophil-lymphocyte ratio; and were more likely hospitalized (5% vs. 1%). Our findings suggest severity of acute infection and history of CPD, migraine, chronic fatigue syndrome (CFS), or fibromyalgia as risk factors for long COVID. These results suggest that suppressing acute disease severity proactively, especially in patients at high risk, can reduce incidence of long COVID.

Peripheral biomarkers as a predictor of poor prognosis in severe cases of COVID-19

We evaluated glycemia and triglyceride, hepatic, muscular, and renal damage markers, redox profile, and leptin and ghrelin hormone levels in COVID-19 patients. We also conducted statistical analysis to verify the potential of biomarkers to predict poor prognosis and the correlation between them in severe cases. We assessed glycemia and the levels of triglycerides, hepatic, muscular, and renal markers in automatized biochemical analyzer. The leptin and ghrelin hormones were assessed by the ELISA assay. Severe cases presented high glycemia and triglyceride levels. Hepatic, muscular, and renal biomarkers were altered in severe patients. Oxidative stress status was found in severe COVID-19 patients. Severe cases also had increased levels of leptin. The ROC curves indicated many biomarkers as poor prognosis predictors in severe cases. The Spearman analysis showed that biomarkers correlate between themselves. Patients with COVID-19 showed significant dysregulation in the levels of several peripheral biomarkers. We bring to light that a robust panel of peripheral biomarkers and hormones predict poor prognosis in severe cases of COVID-19 and biomarkers correlate with each other. Early monitoring of these biomarkers may lead to appropriate clinical interventions in patients infected by SARS-CoV2.

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.

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.

Integrated network pharmacology, molecular docking, and lipidomics to reveal the regulatory effect of Qingxuan Zhike granules on lipid metabolism in lipopolysaccharide-induced acute lung injury

Qingxuan Zhike granules (QXZKG), a traditional Chinese patent medication, has shown therapeutic potential against acute lung injury (ALI). However, the precise mechanism underlying its lung-protective effects requires further investigation. In this study, integrated network pharmacology, molecular docking, and lipidomics were used to elucidate QXZKG's regulatory effect on lipid metabolism in lipopolysaccharide-induced ALI. Animal experiments were conducted to substantiate the efficacy of QXZKG in reducing pro-inflammatory cytokines and mitigating pulmonary pathology. Network pharmacology analysis identified 145 active compounds that directly targeted 119 primary targets of QXZKG against ALI. Gene Ontology function analysis emphasized the roles of lipid metabolism and mitogen-activated protein kinase (MAPK) cascade as crucial biological processes. The MAPK1 protein exhibited promising affinities for naringenin, luteolin, and kaempferol. Lipidomic analysis revealed that 12 lipids showed significant restoration following QXZKG treatment (p < 0.05, FC >1.2 or <0.83). Specifically, DG 38:4, DG 40:7, PC O-40:8, TG 18:1_18:3_22:6, PI 18:2_20:4, FA 16:3, FA 20:3, FA 20:4, FA 22:5, and FA 24:5 were downregulated, while Cer 18:0;2O/24:0 and SM 36:1;2O/34:5 were upregulated in the QXZKG versus model groups. This study enhances our understanding of the active compounds and targets of QXZKG, as well as the potential of lipid metabolism in the treatment of ALI.

Association between lipid profile and clinical outcomes in COVID-19 patients

High-density lipoprotein cholesterol (HDL-c) removes cholesterol, an essential component in lipid rafts, and this cholesterol removal can regulate protein attachment to lipid rafts, modulating their functionality in the immune cell response. Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can alter the lipid profile, there is little information on the role of HDL-c and other lipids in prognostic of the coronavirus disease 2019 (COVID-19) in Mexican population. This study aims to evaluate the predictive value of HDL-c and lipid profile on severity and survival of 102 patients infected with SARS-CoV-2 during the COVID-19 first wave. Our findings, derived from univariate and multivariate Cox proportional hazards regression models, highlighted age and hypertension as significant predictors of survival (HR = 1.04, p = 0.012; HR = 2.78, p = 0.027), while gender, diabetes, and obesity showed no significant impact. Triglycerides and HDL-c levels notably influenced mortality, with elevated triglycerides and lower HDL-c associated with higher mortality risk (p = 0.032). This study underscores the importance of lipid profiles alongside traditional risk factors in assessing COVID-19 risk and outcomes. It contributes to the understanding of COVID-19 patient management and emphasizes the need for further investigation into the role of dyslipidemia in influencing COVID-19 prognosis, potentially aiding in refined risk stratification and therapeutic strategies.

Association of atherogenic indices with myocardial damage and mortality in COVID-19

BACKGROUND

Lipoproteins in cell membranes are related to membrane stability and play a role against microorganisms. Patients with COVID-19 often experience myocyte membrane damage.

OBJECTIVE

This study aimed to search the relationship of atherogenic indices with myocardial damage and mortality in COVID-19.

METHODS

This was an observational, single-center, retrospective study. The study population was grouped according to in-hospital mortality. C-reactive protein (CRP), CRP to albumin ratio (CAR), monocyte to high density lipoprotein cholesterol ratio (MHR), levels of total cholesterol (TC), triglycerides, high-density lipoprotein cholesterol (HDLc), and low-density lipoprotein cholesterol (LDLc) and cardiac troponin I (cTnI) were recorded. Atherogenic indices (plasma atherogenic index [AIP], atherogenic coefficient [AC], Castelli's risk indices I and II [CRI I and II], triglyceride to HDLc ratio (THR) were calculated.

RESULTS

A total of 783 patients were included. The mortality rate was 15.45% (n = 121). The median age of non-survivor group (NSG) was higher than survivor group (SG) [66.0 years (Q1 -Q3: 55.0-77.5) vs 54.0 years (Q1 -Q3: 43.0-63.0)] (p < 0.001). Study parameters which were measured significantly higher in the NSG were CRP, cTnI, triglyceride, CRI-I, CRI-II, AC, AIP, ferritin, CAR, MHR and THR. LDLc, HDLc, TC and albumin were significantly lower in NSG (p<0.001).

CONCLUSION

THR is positively correlated with myocardial damage and strongly predicts in-hospital mortality in COVID-19.

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.

Connecting impaired fibrinolysis and dyslipidemia

A State of the Art lecture entitled "Connecting Fibrinolysis and Dyslipidemia" was presented at the International Society on Thrombosis and Haemostasis Congress 2023. Hemostasis balances the consequences of blood clotting and bleeding. This balance relies on the proper formation of blood clots, as well as the breakdown of blood clots. The primary mechanism that breaks down blood clots is fibrinolysis, where the fibrin net becomes lysed and the blood clot dissolves. Dyslipidemia is a condition where blood lipid and lipoprotein levels are abnormal. Here, we review studies that observed connections between impaired fibrinolysis and dyslipidemia. We also summarize the different correlations between thrombosis and dyslipidemia in different racial and ethnic groups. Finally, we summarize relevant and new findings on this topic presented during the 2023 International Society on Thrombosis and Haemostasis Congress. More studies are needed to investigate the mechanistic connections between impaired fibrinolysis and dyslipidemia and whether these mechanisms differ in racially and ethnically diverse populations.

Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia

PURPOSE

To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features.

METHODS

Univariate and multivariate logistic regression analyses were used to identify the independent clinical predictors for SAP. Pearson correlation analysis and the least absolute shrinkage and selection operator with ten-fold cross-validation were used to calculate the radiomics score for each feature and identify the predictive radiomics features for SAP. Multivariate logistic regression was used to combine the predictive radiomics features with the independent clinical predictors. The prediction performance of the SAP models was evaluated using receiver operating characteristics (ROC), calibration curves, decision curve analysis, and subgroup analyses.

RESULTS

Triglycerides, the neutrophil-to-lymphocyte ratio, dysphagia, the National Institutes of Health Stroke Scale (NIHSS) score, and internal carotid artery stenosis were identified as clinically independent risk factors for SAP. The radiomics scores in patients with SAP were generally higher than in patients without SAP (P < 0. 05). There was a linear positive correlation between radiomics scores and NIHSS scores, as well as between radiomics scores and infarct volume. Infarct volume showed moderate performance in predicting the occurrence of SAP, with an AUC of 0.635. When compared with the other models, the combined prediction model achieved the best area under the ROC (AUC) in both training (AUC = 0.859, 95% CI 0.759-0.936) and validation (AUC = 0.830, 95% CI 0.758-0.896) cohorts (P < 0.05). The calibration curves and decision curve analysis further confirmed the clinical value of the nomogram. Subgroup analysis showed that this nomogram had potential generalization ability.

CONCLUSION

The addition of the radiomics features to the clinical model improved the prediction of SAP in AIS patients, which verified its feasibility.

Glycemic and lipid profile of patients with COVID-19: Impact on morbidity and mortality

INTRODUCTION

Recent studies have shown that patients with COVID-19, who have underlying diabetes mellitus, develop a severe clinical course and have increased mortality. Similarly, dyslipidemia is a common complication in patients with COVID-19, indicating that there may be a pathophysiological interaction between lipid metabolism and SARS-CoV-2. The main manifestation is hypocholesterolemia, which is associated with severe illness and unfavorable outcome.

AIM

The aim of the present study was to assess the impact of glucose and lipid levels on the progression and outcome of patients with COVID-19 infection.

MATERIAL AND METHODS

The study sample consisted of 301 patients who became ill with SARS-CoV-2 and hospitalized during the calendar year 2021. Data were collected from the patients themselves and from their clinical and laboratory follow-up.

RESULTS

A total of 301 patients were included in the study, 56.8 % were male and 82.4 % of patients were not vaccinated for SARS-CoV-2 at baseline. The mean age was 66.7 years and the body mass index was 28.8. More specifically 27.6 % had diabetes mellitus and 34.2 % reported known dyslipidemia. The comparison of the course of the disease with the laboratory data of patients, on the day of admission, found that death was more frequently observed in the elderly [83.0 ± 11.0 (p < 0.001)], in patients with abnormal glucose values [159.8 ± 51.4 (p = 0.039)], abnormal creatinine values (p < 0.001), low glomerular filtration rate (p < 0.001), lower total cholesterol values (p = 0.044), higher triglycerides values [124 ± 64,8 (p = 0,003)], abnormal CRP values (p < 0.001), cTnT (p = 0.001), D-dimers (p < 0.001), and SatO2 (p < 0.001).

CONCLUSION

The present study showed that death was more frequently observed in subjects with hyperglycemia and hypocholesterolemia, and other pathological findings. It is therefore evident that these patients should be a priority in the development of studies and guidelines.

Paraoxonase 1 rs662 polymorphism, its related variables, and COVID-19 intensity: Considering gender and post-COVID complications

In this study, we aimed to investigate the effect of paraoxonase 1 (PON1) rs662 polymorphism, arylesterase (ARE) activity, and the serum lipid profile in patients with coronavirus disease 2019 (COVID-19) in different stages of the disease considering post-COVID outcomes. A total of 470 COVID-19 patients (235 female and 235 male patients) were recruited into the study, and based on the World Health Organization (WHO) criteria, the patients were divided into three groups: moderate, severe, and critical. PON1 rs662 polymorphism was determined by the Alw 1 enzyme followed by agarose gel electrophoresis. Moreover, serum levels of triglycerides (TG), cholesterol (Chol), high-density lipoprotein-cholesterol (HDL-c), and low-density lipoprotein-cholesterol (LDL-c), as well as the level of the ARE activity of PON1 in the sera of patients were measured at the time of infection and one and three months after hospitalization. There was a significant relationship between the G allele and the severity of the disease. In addition, the probability of death in homozygous individuals (GG) was higher than in heterozygous patients (GA), and it was higher in heterozygous patients than in wild-type individuals (AA). There was also a significant relationship between the decrease in serum lipids and the intensity of COVID-19. On the contrary, at the onset of the disease, the HDL-c level and serum ARE activity were reduced compared to one and three months after COVID-19 infection. The findings of this study indicated the significant impact of PON1 rs662 polymorphism on ARE activity, lipid profiles, disease severity, and mortality in COVID-19 patients.

Multidimensional dynamic prediction model for hospitalized patients with the omicron variant in China

Purpose

To establish dynamic prediction models by machine learning using daily multidimensional data for coronavirus disease 2019 (COVID-19) patients.

Methods

Hospitalized COVID-19 patients at Peking Union Medical College Hospital from Nov 2nd, 2022, to Jan 13th, 2023, were enrolled in this study. The outcome was defined as deterioration or recovery of the patient's condition. Demographics, comorbidities, laboratory test results, vital signs, and treatments were used to train the model. To predict the following days, a separate XGBoost model was trained and validated. The Shapley additive explanations method was used to analyze feature importance.

Results

A total of 995 patients were enrolled, generating 7228 and 3170 observations for each prediction model. In the deterioration prediction model, the minimum area under the receiver operating characteristic curve (AUROC) for the following 7 days was 0.786 (95% CI 0.721-0.851), while the AUROC on the next day was 0.872 (0.831-0.913). In the recovery prediction model, the minimum AUROC for the following 3 days was 0.675 (0.583-0.767), while the AUROC on the next day was 0.823 (0.770-0.876). The top 5 features for deterioration prediction on the 7th day were disease course, length of hospital stay, hypertension, and diastolic blood pressure. Those for recovery prediction on the 3rd day were age, D-dimer levels, disease course, creatinine levels and corticosteroid therapy.

Conclusion

The models could accurately predict the dynamics of Omicron patients' conditions using daily multidimensional variables, revealing important features including comorbidities (e.g., hyperlipidemia), age, disease course, vital signs, D-dimer levels, corticosteroid therapy and oxygen therapy.

HDL-Related Parameters and COVID-19 Mortality: The Importance of HDL Function

COVID-19, caused by the SARS-CoV-2 coronavirus, emerged as a global pandemic in late 2019, resulting in significant global public health challenges. The emerging evidence suggests that diminished high-density lipoprotein (HDL) cholesterol levels are associated with the severity of COVID-19, beyond inflammation and oxidative stress. Here, we used nuclear magnetic resonance spectroscopy to compare the lipoprotein and metabolic profiles of COVID-19-infected patients with non-COVID-19 pneumonia. We compared the control group and the COVID-19 group using inflammatory markers to ensure that the differences in lipoprotein levels were due to COVID-19 infection. Our analyses revealed supramolecular phospholipid composite (SPC), phenylalanine, and HDL-related parameters as key discriminators between COVID-19-positive and non-COVID-19 pneumonia patients. More specifically, the levels of HDL parameters, including apolipoprotein A-I (ApoA-I), ApoA-II, HDL cholesterol, and HDL phospholipids, were significantly different. These findings underscore the potential impact of HDL-related factors in patients with COVID-19. Significantly, among the HDL-related metrics, the cholesterol efflux capacity (CEC) displayed the strongest negative association with COVID-19 mortality. CEC is a measure of how well HDL removes cholesterol from cells, which may affect the way SARS-CoV-2 enters cells. In summary, this study validates previously established markers of COVID-19 infection and further highlights the potential significance of HDL functionality in the context of COVID-19 mortality.

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.

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.

John A, Ling M, Le J, Harris J, Rhoads N, Wang Y, Fu X, Chen J, Fazio S, Lindner JR, López JA. Low-density lipoprotein promotes microvascular thrombosis by enhancing von Willebrand factor self-association

von Willebrand factor (VWF) mediates primary hemostasis and thrombosis in response to hydrodynamic forces. We previously showed that high shear promoted self-association of VWF into hyperadhesive strands, which can be attenuated by high-density lipoprotein (HDL) and apolipoprotein A-I. In this study, we show that low-density lipoprotein (LDL) binds VWF under shear and enhances self-association. Vortexing VWF in tubes resulted in its loss from the solution and deposition onto tube surfaces, which was prevented by HDL. At a stabilizing HDL concentration of 1.2 mg/mL, increasing concentrations of LDL progressively increased VWF loss, the effect correlating with the LDL-to-HDL ratio and not the absolute concentration of the lipoproteins. Similarly, HDL diminished deposition of VWF in a post-in-channel microfluidic device, whereas LDL increased both the rate and extent of strand deposition, with both purified VWF and plasma. Hypercholesterolemic human plasma also displayed accelerated VWF accumulation in the microfluidic device. The initial rate of accumulation correlated linearly with the LDL-to-HDL ratio. In Adamts13-/- and Adamts13-/-LDLR-/- mice, high LDL levels enhanced VWF and platelet adhesion to the myocardial microvasculature, reducing cardiac perfusion, impairing systolic function, and producing early signs of cardiomyopathy. In wild-type mice, high plasma LDL concentrations also increased the size and persistence of VWF-platelet thrombi in ionophore-treated mesenteric microvessels, exceeding the accumulation seen in similarly treated ADAMTS13-deficient mice that did not receive LDL infusion. We propose that targeting the interaction of VWF with itself and with LDL may improve the course of thrombotic microangiopathies, atherosclerosis, and other disorders with defective microvascular circulation.

Association of low HDL-c levels with severe symptoms and poor clinical prognosis in patients with severe fever and thrombocytopenia syndrome

Background

Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease caused by a novel bunyavirus, characterized by high fever, thrombocytopenia, and multiple organ damage. Disturbances in lipid metabolism often occur during viral infections, but the changes and clinical significance of lipid profiles in SFTS patients remain unclear. This study aimed to investigate the alterations in lipid profiles and their clinical significance in SFTS patients.

Methods

A total of 157 SFTS patients and 157 healthy controls were enrolled in this study. Serum lipid levels were collected and analyzed among different groups and prognosis categories. Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of lipid levels in distinguishing between severe and mild cases, as well as surviving and non-surviving patients. Pearson correlation analysis was used to examine the associations between lipid levels and clinical laboratory parameters.

Results

SFTS patients exhibited significantly lower levels of HDL-c, LDL-c, cholesterol, APoAI, and ApoB compared to healthy controls, while triglyceride levels were significantly higher. Serum HDL-c and ApoAI demonstrated good performance as indicators for distinguishing between survivors and non-survivors (AUC of 0.87 and 0.85, respectively). Multivariate regression analysis indicated that HDL-c independently acts as a protective factor in patients with SFTS. HDL-c levels showed decline in non-survivors but recovered in survivors. Moreover, HDL-c exhibited significant correlations with various clinical laboratory parameters (IL-6, CRP, AST, TT, APTT, PLT, ALB, and CD4).

Conclusion

This study identified abnormalities in serum lipid metabolism among SFTS patients. HDL-c and ApoAI levels hold potential as biomarkers for distinguishing survivors from non-survivors. Additionally, HDL-c and ApoAI may serve as therapeutic targets for the management of SFTS patients.

Serum Total Antioxidant Capacity (TAC) and TAC/Lymphocyte Ratio as Promising Predictive Markers in COVID-19

SARS-CoV-2 infection might cause a critical disease, and patients' follow-up is based on multiple parameters. Oxidative stress is one of the key factors in the pathogenesis of COVID-19 suggesting that its level could be a prognostic marker. Therefore, we elucidated the predictive value of the serum non-enzymatic total antioxidant capacity (TAC) and that of the newly introduced TAC/lymphocyte ratio in COVID-19. We included 61 COVID-19 (n = 27 ward, n = 34 intensive care unit, ICU) patients and 29 controls in our study. Serum TAC on admission was measured by an enhanced chemiluminescence (ECL) microplate assay previously validated by our research group. TAC levels were higher (p < 0.01) in ICU (median: 407.88 µmol/L) than in ward patients (315.44 µmol/L) and controls (296.60 µmol/L). Besides the classical parameters, both the TAC/lymphocyte ratio and TAC had significant predictive values regarding the severity (AUC-ROC for the TAC/lymphocyte ratio: 0.811; for TAC: 0.728) and acute kidney injury (AUC-ROC for the TAC/lymphocyte ratio: 0.747; for TAC: 0.733) in COVID-19. Moreover, the TAC/lymphocyte ratio had significant predictive value regarding mortality (AUC-ROC: 0.752). Serum TAC and the TAC/lymphocyte ratio might offer valuable information regarding the severity of COVID-19. TAC measured by our ECL microplate assay serves as a promising marker for the prediction of systemic inflammatory diseases.

Association between Lipid Levels, Anti-SARS-CoV-2 Spike Antibodies and COVID-19 Mortality: A Prospective Cohort Study

BACKGROUND

Recent studies suggest that both lipid levels and anti-severe-acute-respiratory-syndrome-coronavirus-2 (SARS-CoV-2) antibody levels are associated with outcome in coronavirus disease 2019 (COVID-19). While both parameters have separately been implicated in the neutralization and clearance of pathogens during severe infections, it is currently unclear whether the interplay of these parameters affects outcome in COVID-19. We therefore aimed to determine whether there was a relationship between lipoproteins, anti-SARS-CoV-2 antibodies, and COVID-19 mortality.

METHODS

In this prospective, multicenter cohort study, we recruited 1152 hospitalized patients with COVID-19 from five hospitals. Total cholesterol (TC), LDL-C, HDL-C, triglycerides, and anti-SARS-CoV-2 spike antibodies were measured on hospital admission. The investigated endpoint was in-hospital mortality.

RESULTS

LDL-C, HDL-C, and TC were significantly lower in non-survivors than in survivors (mg/dL, 95%CI; 56.1, 50.4-61.8 vs. 72.6, 70.2-75.0, p < 0.001; 34.2, 31.7-36.8 vs. 38.1, 37.2-39.1, p = 0.025; 139.3, 130.9-147.7 vs. 157.4, 54.1-160.6, p = 0.002). Mortality risk increased progressively with lower levels of LDL-C, HDL-C, and TC (aOR 1.73, 1.30-2.31, p < 0.001; 1.44, 1.10-1.88, p = 0.008; 1.49, 1.14-1.94, p < 0.001). Mortality rates varied between 2.1% for high levels of both LDL-C and anti-SARS-CoV-2 antibodies and 16.3% for low levels of LDL-C and anti-SARS-CoV-2 antibodies (aOR 9.14, 95%CI 3.17-26.34, p < 0.001). Accordingly, for total cholesterol and anti-SARS-CoV-2 antibodies, mortality rates varied between 2.1% and 15.0% (aOR 8.01, 95%CI 2.77-23.18, p < 0.001).

CONCLUSION

The combination of serum lipid levels and anti-SARS-CoV-2 antibodies is strongly associated with in-hospital mortality of patients with COVID-19. Patients with low levels of LDL-C and total cholesterol combined with low levels of anti-SARS-CoV-2 antibodies exhibited the highest mortality rates.

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.

Cross-Linking Mass Spectrometry Uncovers Interactions Between High-Density Lipoproteins and the SARS-CoV-2 Spike Glycoprotein

High-density lipoprotein (HDL) levels are reduced in patients with coronavirus disease 2019 (COVID-19), and the extent of this reduction is associated with poor clinical outcomes. While lipoproteins are known to play a key role during the life cycle of the hepatitis C virus, their influence on coronavirus (CoV) infections is poorly understood. In this study, we utilize cross-linking mass spectrometry (XL-MS) to determine circulating protein interactors of the severe acute respiratory syndrome (SARS)-CoV-2 spike glycoprotein. XL-MS of plasma isolated from patients with COVID-19 uncovered HDL protein interaction networks, dominated by acute-phase serum amyloid proteins, whereby serum amyloid A2 was shown to bind to apolipoprotein (Apo) D. XL-MS on isolated HDL confirmed ApoD to interact with SARS-CoV-2 spike but not SARS-CoV-1 spike. Other direct interactions of SARS-CoV-2 spike upon HDL included ApoA1 and ApoC3. The interaction between ApoD and spike was further validated in cells using immunoprecipitation-MS, which uncovered a novel interaction between both ApoD and spike with membrane-associated progesterone receptor component 1. Mechanistically, XL-MS coupled with data-driven structural modeling determined that ApoD may interact within the receptor-binding domain of the spike. However, ApoD overexpression in multiple cell-based assays had no effect upon viral replication or infectivity. Thus, SARS-CoV-2 spike can bind to apolipoproteins on HDL, but these interactions do not appear to alter infectivity.

Circulating ACE2 level and zinc/albumin ratio as potential biomarkers for a precision medicine approach to COVID-19

Highly mutable influenza is successfully countered based on individual susceptibility and similar precision-like medicine approach should be effective against SARS-COV-2. Among predictive markers to bring precision medicine to COVID-19, circulating ACE2 has potential features being upregulated in both severe COVID-19 and predisposing comorbidities. Spike SARS-CoVs were shown to induce ADAM17-mediated shedding of enzymatic active ACE2, thus accounting for its increased activity that has also been suggested to induce positive feedback loops leading to COVID-19-like manifestations. For this reason, pre-existing ACE2 activity and inhibition of ACE2/ADAM17 zinc-metalloproteases through zinc chelating agents have been proposed to predict COVID-19 outcome before infection and to protect from COVID-19, respectively. Since most diagnostic laboratories are not equipped for enzymatic activity determination, other potential predictive markers of disease progression exploitable by diagnostic laboratories were explored. Concentrations of circulating albumin, zinc, ACE2 protein and its activity were investigated in healthy, diabetic (COVID-19-susceptible) and SARS-CoV-2-negative COVID-19 individuals. ACE2 both protein levels and activity significantly increased in COVID-19 and diabetic patients. Abnormal high levels of ACE2 characterised a subgroup (16-19%) of diabetics, while COVID-19 patients were characterised by significantly higher zinc/albumin ratios, pointing to a relative increase of albumin-unbound zinc species, such as free zinc ones. Data on circulating ACE2 levels are in line with the hypothesis that they can drive susceptibility to COVID-19 and elevated zinc/albumin ratios support the therapeutic use of zinc chelating inhibitors of ACE2/ADAM17 zinc-metalloproteases in a targeted therapy for COVID-19.

Serum profiles of pro-inflammatory and anti-inflammatory cytokines in non-hospitalized patients with mild/moderate COVID-19 infection

This study attempted to explore pro-inflammatory and anti-inflammatory responses in patients with mild/moderate coronavirus disease 19 (COVID-19). Eight pro-inflammatory (IL-1α, IL-1β, IL-12, IL-17A, IL-17E, IL-31, IFN-γ and TNF-α) and three anti-inflammatory (IL-1Ra, IL-10 and IL-13) cytokines, as well as two chemokines (CXCL9 and CXCL10), were analyzed in the serum from ninety COVID-19 patients and healthy controls. Cytokine/chemokine levels were measured using enzyme-linked immunosorbent assay kits. Results revealed that IL-1α, IL-1β, IL-10, IL-12, IL-13, IL-17A, IL-31, IFN-γ, TNF-α and CXCL10 were significantly higher in patients than in controls, while IL-1Ra levels were significantly lower in patients. IL-17E and CXCL9 levels showed no significant differences between patients and controls. Seven cytokines/chemokines recorded an area under the curve greater than 0.8: IL-12 (0.945), IL-17A (0.926), CXCL10 (0.909), IFN-γ (0.904), IL-1α (0.869), TNF-α (0.825) and IL-10 (0.821). As indicated by the odds ratio, elevated levels of nine cytokines/chemokines were associated with an increased risk of COVID-19: IL-1α (19.04), IL-10 (5.01), IL-12 (43.66), IL-13 (4.25), IL-17A (16.62), IL-31 (7.38), IFN-γ (13.55), TNF-α (12.00) and CXCL10 (11.18). Only one positive (IL-17E with TNF-α) and six negative (IL-1β, IL-17A and IL-17E with CXCL9, IL-10 with IL-17A, and IL-1β and IL-17A with CXCL10) correlations were found between these cytokines/chemokines. In conclusion, pro-inflammatory (IL-1α, IL-1β, IL-12, IL-13, IL-17A, IL-31, IFN-γ, TNF-α and CXCL10) and anti-inflammatory (IL-10 and IL-13) cytokines/chemokines were up-regulated in the serum of patients with mild/moderate COVID-19. Their potential as biomarkers for diagnosis and prognosis is suggested and the association with COVID-19 risk is indicated to give more insight on COVID-19 immunological responses among non-hospitalized patients.

Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction

An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.

Using cardiovascular risk indices to predict mortality in Covid-19 patients with acute respiratory distress syndrome: a cross sectional study

Covid-19 patients who require admission to an intensive care unit (ICU) have a higher risk of mortality. Several risk factors for severe Covid-19 infection have been identified, including cardiovascular risk factors. Therefore, the aim was to investigate the association between cardiovascular (CV) risk and major adverse cardiovascular events (MACE) and mortality of Covid-19 ARDS patients admitted to an ICU. A prospective cross-sectional study was conducted in a university hospital in Graz, Austria. Covid-19 patients who were admitted to an ICU with a paO2/fiO2 ratio < 300 were included in this study. Standard lipid profile was measured at ICU admission to determine CV risk. 31 patients with a mean age of 68 years were recruited, CV risk was stratified using Framingham-, Procam- and Charlson Comorbidity Index (CCI) score. A total of 10 (32.3%) patients died within 30 days, 8 patients (25.8%) suffered from MACE during ICU stay. CV risk represented by Framingham-, Procam- or CCI score was not associated with higher rates of MACE. Nevertheless, higher CV risk represented by Procam score was significantly associated with 30- day mortality (13.1 vs. 6.8, p = 0.034). These findings suggest that the Procam score might be useful to estimate the prognosis of Covid-19 ARDS patients.

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.

Prognostic Value of Non-HDL Cholesterol in COVID-19 Pneumonia

BACKGROUND

In addition to coronary artery disease, non-high-density lipoprotein(non-HDL-C) provides short and long-term predictive information for many chronic inflammatory diseases such as stroke, hemodialysis, post-renal transplant, non-alcoholic hepatosteatosis, and human immunodeficiency virus.

OBJECTIVES

This study examined the predictive value of non-HDL-C measured before SARS-CoV-2 for mortality in COVID-19 infection.

METHODS

This study retrospectively included 1435 patients diagnosed with COVID-19 and treated in the thoracic diseases ward in a single center between January 2020 and June 2022. All patients included in the study had clinical and radiological features and signs of COVID-19 pneumonia. The COVID-19 diagnosis of all patients was confirmed by a polymerase chain reaction studied from an oropharyngeal swab. Statistical significance was set at p < 0.05.

RESULTS

The study patients, including 1435 subjects, were divided into 712 patients in the non-surviving group and 723 in the surviving group. While there was no difference between the groups regarding gender, there was a statistically significant age difference. The non-surviving group was older. Age, lactate dehydrogenase(LDH), C reactive protein(CRP), triglycerides, D-dimer, and non-HDL-C were independent risk factors for mortality in regression analyses. In correlation analysis, age, CRP, and LDH were positively correlated with non-HDL-C. In the ROC analysis, sensitivity for non-HDL-C was 61.6%, and specificity was 89.2%.

CONCLUSION

We believe that the non-HDL-C level studied before COVID-19 infection can be used as a prognostic biomarker for the disease.

Metabolic alterations upon SARS-CoV-2 infection and potential therapeutic targets against coronavirus infection

The coronavirus disease 2019 (COVID-19) caused by coronavirus SARS-CoV-2 infection has become a global pandemic due to the high viral transmissibility and pathogenesis, bringing enormous burden to our society. Most patients infected by SARS-CoV-2 are asymptomatic or have mild symptoms. Although only a small proportion of patients progressed to severe COVID-19 with symptoms including acute respiratory distress syndrome (ARDS), disseminated coagulopathy, and cardiovascular disorders, severe COVID-19 is accompanied by high mortality rates with near 7 million deaths. Nowadays, effective therapeutic patterns for severe COVID-19 are still lacking. It has been extensively reported that host metabolism plays essential roles in various physiological processes during virus infection. Many viruses manipulate host metabolism to avoid immunity, facilitate their own replication, or to initiate pathological response. Targeting the interaction between SARS-CoV-2 and host metabolism holds promise for developing therapeutic strategies. In this review, we summarize and discuss recent studies dedicated to uncovering the role of host metabolism during the life cycle of SARS-CoV-2 in aspects of entry, replication, assembly, and pathogenesis with an emphasis on glucose metabolism and lipid metabolism. Microbiota and long COVID-19 are also discussed. Ultimately, we recapitulate metabolism-modulating drugs repurposed for COVID-19 including statins, ASM inhibitors, NSAIDs, Montelukast, omega-3 fatty acids, 2-DG, and metformin.

Deep Phenotyping of the Lipidomic Response in COVID and non-COVID Sepsis

Lipids may influence cellular penetrance by pathogens and the immune response that they evoke. Here we find a broad based lipidomic storm driven predominantly by secretory (s) phospholipase A 2 (sPLA 2 ) dependent eicosanoid production occurs in patients with sepsis of viral and bacterial origin and relates to disease severity in COVID-19. Elevations in the cyclooxygenase (COX) products of arachidonic acid (AA), PGD 2 and PGI 2 , and the AA lipoxygenase (LOX) product, 12-HETE, and a reduction in 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, correlate with the inflammatory response and link to disease severity. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflect disease severity in COVID-19. AA and LA metabolites and LPC-O-16:0 linked variably to the immune response. These studies yield prognostic biomarkers and therapeutic targets for patients with sepsis, including COVID-19. An interactive purpose built interactive network analysis tool was developed, allowing the community to interrogate connections across these multiomic data and generate novel hypotheses.

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.

SARS-CoV-2 induced HDL dysfunction may affect the host's response to and recovery from COVID-19

INTRODUCTION

Covid-19 is linked with the development of cardio-metabolic disorders, including dyslipidemia, dysregulation of high-density lipoprotein (HDL), and low-density lipoprotein (LDL). Furthermore, SARS-Co-2 infection is associated with noteworthy changes in lipid profile, which is suggested as a possible biomarker to support the diagnosis and management of Covid-19.

METHODS

This paper adopts the literature review method to obtain information about how Covid-19 affects high-risk group patients and may cause severe and critical effects due to the development of acute lung injury and acute respiratory distress syndrome. A narrative and comprehensive review is presented.

RESULTS

Reducing HDL in Covid-19 is connected to the disease severity and poor clinical outcomes, suggesting that high HDL serum levels could benefit Covid-19. SARS-CoV-2 binds HDL, and this complex is attached to the co-localized receptors, facilitating viral entry. Therefore, SARS-CoV-2 infection may induce the development of dysfunctional HDL through different mechanisms, including induction of inflammatory and oxidative stress with activation of inflammatory signaling pathways. In turn, the induction of dysfunctional HDL induces the activation of inflammatory signaling pathways and oxidative stress, increasing Covid-19 severity.

CONCLUSIONS

Covid-19 is linked with the development of cardio-metabolic disorders, including dyslipidemia in general and dysregulation of high-density lipoprotein and low-density lipoprotein. Therefore, the present study aimed to overview the causal relationship between dysfunctional high-density lipoprotein and Covid-19.

Indian food habit & food ingredients may have a role in lowering the severity & high death rate from COVID-19 in Indians: findings from the first nutrigenomic analysis

Background & objectives

During the COVID-19 pandemic, the death rate was reportedly 5-8 fold lower in India which is densely populated as compared to less populated western countries. The aim of this study was to investigate whether dietary habits were associated with the variations in COVID-19 severity and deaths between western and Indian population at the nutrigenomics level.

Methods

In this study nutrigenomics approach was applied. Blood transcriptome of severe COVID-19 patients from three western countries (showing high fatality) and two datasets from Indian patients were used. Gene set enrichment analyses were performed for pathways, metabolites, nutrients, etc., and compared for western and Indian samples to identify the food- and nutrient-related factors, which may be associated with COVID-19 severity. Data on the daily consumption of twelve key food components across four countries were collected and a correlation between nutrigenomics analyses and per capita daily dietary intake was investigated.

Results

Distinct dietary habits of Indians were observed, which may be associated with low death rate from COVID-19. Increased consumption of red meat, dairy products and processed foods by western populations may increase the severity and death rate by activating cytokine storm-related pathways, intussusceptive angiogenesis, hypercapnia and enhancing blood glucose levels due to high contents of sphingolipids, palmitic acid and byproducts such as CO2 and lipopolysaccharide (LPS). Palmitic acid also induces ACE2 expression and increases the infection rate. Coffee and alcohol that are highly consumed in western countries may increase the severity and death rates from COVID-19 by deregulating blood iron, zinc and triglyceride levels. The components of Indian diets maintain high iron and zinc concentrations in blood and rich fibre in their foods may prevent CO2 and LPS-mediated COVID-19 severity. Regular consumption of tea by Indians maintains high high-density lipoprotein (HDL) and low triglyceride in blood as catechins in tea act as natural atorvastatin. Importantly, regular consumption of turmeric in daily food by Indians maintains strong immunity and curcumin in turmeric may prevent pathways and mechanisms associated with SARS-CoV-2 infection and COVID-19 severity and lowered the death rate.

Interpretation & conclusions

Our results suggest that Indian food components suppress cytokine storm and various other severity related pathways of COVID-19 and may have a role in lowering severity and death rates from COVID-19 in India as compared to western populations. However, large multi-centered case-control studies are required to support our current findings.

Early stages of diffuse idiopathic skeletal hyperostosis (DISH) and chronic inflammation: the Camargo Cohort Study

INTRODUCTION/OBJECTIVES

DISH has traditionally been considered a non-inflammatory rheumatic disorder. Currently, an inflammatory component has been theorized in the early phases of this condition (EDISH). The study is aimed at investigating a possible relationship between EDISH and chronic inflammation.

METHOD

Analytical-observational study: participants from the Camargo Cohort Study were enrolled. We collected clinical, radiological, and laboratory data. C-reactive protein (CRP), albumin-to-globulin ratio (AGR), and triglyceride-glucose (TyG) index were assessed. EDISH was defined by Schlapbach's scale grades I or II. A fuzzy matching with tolerance factor = 0.2 was performed. Subjects without ossification (NDISH), sex- and age-matched with cases (1:4), acted as controls. Definite DISH was an exclusion criterion. Multivariable analyses were performed.

RESULTS

We evaluated 987 persons (mean age 64 ± 8 years; 191 cases with 63.9% women). EDISH subjects presented more frequently obesity, T2DM, MetS, and the lipid pattern [↑TG ↓TC]. TyG index and alkaline phosphatase (ALP) were higher. Trabecular bone score (TBS) was significantly lower (1.310 [0.2] vs. 1.342 [0.1]; p = 0.025). CRP and ALP showed the highest correlation (r = 0.510; p = 0.0001) at lowest TBS level. AGR was lower, and its correlations with ALP (r =  - 0.219; p = 0.0001) and CTX (r =  - 0.153; p = 0.022), were weaker or non-significant in NDISH. After adjustment for potential confounders, estimated CRP means for EDISH and NDISH were 0.52 (95% CI: 0.43-0.62) and 0.41 (95% CI: 0.36-0.46), respectively (p = 0.038).

CONCLUSIONS

EDISH was associated with chronic inflammation. Findings revealed an interplay between inflammation, trabecular impairment, and the onset of ossification. Lipid alterations were similar to those observed in chronic-inflammatory diseases. Key Points • An inflammatory component has been theorized in early stages of DISH (EDISH) • In EDISH group compared to non-DISH, we observed significantly higher correlations between biomarkers and some relevant variables. In particular, with alkaline phosphatase (ALP) and with trabecular bone score (TBS) • EDISH has shown to be associated with chronic inflammation • The lipid alterations observed in the EDISH group were similar to those observed in chronic-inflammatory diseases.

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.

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.

Proteomics Investigation of Diverse Serological Patterns in COVID-19

Serum antibodies IgM and IgG are elevated during Coronavirus Disease 2019 (COVID-19) to defend against viral attacks. Atypical results such as negative and abnormally high antibody expression were frequently observed whereas the underlying molecular mechanisms are elusive. In our cohort of 144 COVID-19 patients, 3.5% were both IgM and IgG negative, whereas 29.2% remained only IgM negative. The remaining patients exhibited positive IgM and IgG expression, with 9.3% of them exhibiting over 20-fold higher titers of IgM than the others at their plateau. IgG titers in all of them were significantly boosted after vaccination in the second year. To investigate the underlying molecular mechanisms, we classed the patients into four groups with diverse serological patterns and analyzed their 2-year clinical indicators. Additionally, we collected 111 serum samples for TMTpro-based longitudinal proteomic profiling and characterized 1494 proteins in total. We found that the continuously negative IgM and IgG expression during COVID-19 were associated with mild inflammatory reactions and high T cell responses. Low levels of serum IgD, inferior complement 1 activation of complement cascades, and insufficient cellular immune responses might collectively lead to compensatory serological responses, causing overexpression of IgM. Serum CD163 was positively correlated with antibody titers during seroconversion. This study suggests that patients with negative serology still developed cellular immunity for viral defense and that high titers of IgM might not be favorable to COVID-19 recovery.

Risks and burdens of incident dyslipidaemia in long COVID: a cohort study

BACKGROUND

Non-clinical evidence and a few human studies with short follow-ups suggest increased risk of dyslipidaemia in the post-acute phase of COVID-19 (ie, >30 days after SARS-CoV-2 infection). However, detailed large-scale controlled studies with longer follow-ups and in-depth assessment of the risks and burdens of incident dyslipidaemia in the post-acute phase of COVID-19 are not yet available. We, therefore, aimed to examine the risks and 1-year burdens of incident dyslipidaemia in the post-acute phase of COVID-19 among people who survive the first 30 days of SARS-CoV-2 infection.

METHODS

In this cohort study, we used the national health-care databases of the US Department of Veterans Affairs to build a cohort of 51 919 participants who had a positive COVID-19 test and survived the first 30 days of infection between March 1, 2020, and Jan 15, 2021; a non-infected contemporary control group (n=2 647 654) that enrolled patients between March 1, 2020, and Jan 15, 2021; and a historical control group (n=2 539 941) that enrolled patients between March 1, 2018, and Jan 15, 2019. Control groups had no evidence of SARS-CoV-2 infection, and participants in all three cohorts were free of dyslipidaemia before cohort enrolment. We then used inverse probability weighting using predefined and algorithmically-selected high dimensional variables to estimate the risks and 1-year burdens of incident dyslipidaemia, lipid-lowering medications use, and a composite of these outcomes. We reported two measures of risk: hazard ratios (HRs) and burden per 1000 people at 12 months. Additionally, we estimated the risks and burdens of incident dyslipidaemia outcomes in mutually exclusive groups based on the care setting of the acute infection (ie, participants who were non-hospitalised, hospitalised, or admitted to intensive care during the acute phase of SARS-CoV-2 infection).

FINDINGS

In the post-acute phase of the SARS-CoV-2 infection, compared with the non-infected contemporary control group, those in the COVID-19 group had higher risks and burdens of incident dyslipidaemia, including total cholesterol greater than 200 mg/dL (hazard ratio [HR] 1·26, 95% CI 1·22-1·29; burden 22·46, 95% CI 19·14-25·87 per 1000 people at 1 year), triglycerides greater than 150 mg/dL (1·27, 1·23-1·31; 22·03, 18·85-25·30), LDL cholesterol greater than 130 mg/dL (1·24, 1·20-1·29; 18·00, 14·98-21·11), and HDL cholesterol lower than 40 mg/dL (1·20, 1·16-1·25; 15·58, 12·52-18·73). The risk and burden of a composite of these abnormal lipid laboratory outcomes were 1·24 (95% CI 1·21-1·27) and 39·19 (95% CI 34·71-43·73), respectively. There was also increased risk and burden of incident lipid-lowering medications use (HR 1·54, 95% CI 1·48-1·61; burden 25·50, 95% CI 22·61-28·50). A composite of any dyslipidaemia outcome (laboratory abnormality or lipid-lowering medications use) yielded an HR of 1·31 (95% CI 1·28-1·34) and a burden of 54·03 (95% CI 49·21-58·92). The risks and burdens of these post-acute outcomes increased in a graded fashion corresponding to the severity of the acute phase of COVID-19 infection (ie, whether patients were non-hospitalised, hospitalised, or admitted to intensive care). The results were consistent in analyses comparing the COVID-19 group to the non-infected historical control group.

INTERPRETATION

Our findings suggest increased risks and 1-year burdens of incident dyslipidaemia and incident lipid-lowering medications use in the post-acute phase of COVID-19 infection. Post-acute care for those with COVID-19 should involve attention to dyslipidaemia as a potential post-acute sequela of SARS-CoV-2 infection.

FUNDING

US Department of Veterans Affairs.

Efficacy and safety of metabolic interventions for the treatment of severe COVID-19: in vitro, observational, and non-randomized open-label interventional study

Background

Viral infection is associated with a significant rewire of the host metabolic pathways, presenting attractive metabolic targets for intervention.

Methods

We chart the metabolic response of lung epithelial cells to SARS-CoV-2 infection in primary cultures and COVID-19 patient samples and perform in vitro metabolism-focused drug screen on primary lung epithelial cells infected with different strains of the virus. We perform observational analysis of Israeli patients hospitalized due to COVID-19 and comparative epidemiological analysis from cohorts in Italy and the Veteran's Health Administration in the United States. In addition, we perform a prospective non-randomized interventional open-label study in which 15 patients hospitalized with severe COVID-19 were given 145 mg/day of nanocrystallized fenofibrate added to the standard of care.

Results

SARS-CoV-2 infection produced transcriptional changes associated with increased glycolysis and lipid accumulation. Metabolism-focused drug screen showed that fenofibrate reversed lipid accumulation and blocked SARS-CoV-2 replication through a PPARα-dependent mechanism in both alpha and delta variants. Analysis of 3233 Israeli patients hospitalized due to COVID-19 supported in vitro findings. Patients taking fibrates showed significantly lower markers of immunoinflammation and faster recovery. Additional corroboration was received by comparative epidemiological analysis from cohorts in Europe and the United States. A subsequent prospective non-randomized interventional open-label study was carried out on 15 patients hospitalized with severe COVID-19. The patients were treated with 145 mg/day of nanocrystallized fenofibrate in addition to standard-of-care. Patients receiving fenofibrate demonstrated a rapid reduction in inflammation and a significantly faster recovery compared to patients admitted during the same period.

Conclusions

Taken together, our data suggest that pharmacological modulation of PPARα should be strongly considered as a potential therapeutic approach for SARS-CoV-2 infection and emphasizes the need to complete the study of fenofibrate in large randomized controlled clinical trials.

Funding

Funding was provided by European Research Council Consolidator Grants OCLD (project no. 681870) and generous gifts from the Nikoh Foundation and the Sam and Rina Frankel Foundation (YN). The interventional study was supported by Abbott (project FENOC0003).

Clinical trial number

NCT04661930.

Untargeted analysis in post-COVID-19 patients reveals dysregulated lipid pathways two years after recovery

Introduction: Similar to what it has been reported with preceding viral epidemics (such as MERS, SARS, or influenza), SARS-CoV-2 infection is also affecting the human immunometabolism with long-term consequences. Even with underreporting, an accumulated of almost 650 million people have been infected and 620 million recovered since the start of the pandemic; therefore, the impact of these long-term consequences in the world population could be significant. Recently, the World Health Organization recognized the post-COVID syndrome as a new entity, and guidelines are being established to manage and treat this new condition. However, there is still uncertainty about the molecular mechanisms behind the large number of symptoms reported worldwide. Aims and Methods: In this study we aimed to evaluate the clinical and lipidomic profiles (using non-targeted lipidomics) of recovered patients who had a mild and severe COVID-19 infection (acute phase, first epidemic wave); the assessment was made two years after the initial infection. Results: Fatigue (59%) and musculoskeletal (50%) symptoms as the most relevant and persistent. Functional analyses revealed that sterols, bile acids, isoprenoids, and fatty esters were the predicted metabolic pathways affected in both COVID-19 and post-COVID-19 patients. Principal Component Analysis showed differences between study groups. Several species of phosphatidylcholines and sphingomyelins were identified and expressed in higher levels in post-COVID-19 patients compared to controls. The paired analysis (comparing patients with an active infection and 2 years after recovery) show 170 dysregulated features. The relationship of such metabolic dysregulations with the clinical symptoms, point to the importance of developing diagnostic and therapeuthic markers based on cell signaling pathways.

Continuation of fibrate therapy in patients with metabolic syndrome and COVID-19: a beneficial regime worth pursuing

Based on separate protective mechanisms related to lipid metabolism, viral cell entry and inflammation, fibrate treatment might be advantageous among patients who have been taking fibrates before SARS-CoV-2 infection and continue taking them during the infection. Based on published data on hospitalized COVID-19 patients, we recommend that the clinicians should ask their patients with metabolic syndrome who are already taking fibrates to continue fibrate treatment during the COVID-19 illness. This recommendation applies to both outpatients and hospitalized patients. However, results from the ongoing randomized controlled trials (RCTs) using fenofibrate treatment for the prevention or treatment of COVID-19 have yet to prove that fenofibrate is clinically significant for this indication.KEY MESSAGESThe role of fibrates as a repurpose to treat SARS-CoV-2 is under investigation in at least three ongoing RCTs.Obesity, diabetes, hypertension and dyslipidaemia, individually or clustered as a discrete phenotype, the metabolic syndrome, typically associate with a more severe course of COVID-19.Fibrate treatment seems to be most advantageous among patients who have been taken fibrates before SARS-CoV-2 infection and are continuing to take them during the infection.We recommend that the clinicians encourage their patients who are already taking fibrate to continue using the drug throughout the COVID-19 illness.

PK, Nadig M, Ross J, Ardhanari S, O’Horo JC, Venkatakrishnan AJ, Rosen CJ, Telenti A, Hurt RT, Soundararajan V. Severe acute infection and chronic pulmonary disease are risk factors for developing post-COVID-19 conditions

Post-COVID-19 conditions, also known as "long COVID", has significantly impacted the lives of many individuals, but the risk factors for this condition are poorly understood. In this study, we performed a retrospective EHR analysis of 89,843 individuals at a multi-state health system in the United States with PCR-confirmed COVID-19, including 1,086 patients diagnosed with long COVID and 1,086 matched controls not diagnosed with long COVID. For these two cohorts, we evaluated a wide range of clinical covariates, including laboratory tests, medication orders, phenotypes recorded in the clinical notes, and outcomes. We found that chronic pulmonary disease (CPD) was significantly more common as a pre-existing condition for the long COVID cohort than the control cohort (odds ratio: 1.9, 95% CI: [1.5, 2.6]). Additionally, long-COVID patients were more likely to have a history of migraine (odds ratio: 2.2, 95% CI: [1.6, 3.1]) and fibromyalgia (odds ratio: 2.3, 95% CI: [1.3, 3.8]). During the acute infection phase, the following lab measurements were abnormal in the long COVID cohort: high triglycerides (meanlongCOVID: 278.5 mg/dL vs. meancontrol: 141.4 mg/dL), low HDL cholesterol levels (meanlongCOVID: 38.4 mg/dL vs. meancontrol: 52.5 mg/dL), and high neutrophil-lymphocyte ratio (meanlongCOVID: 10.7 vs. meancontrol: 7.2). The hospitalization rate during the acute infection phase was also higher in the long COVID cohort compared to the control cohort (ratelongCOVID: 5% vs. ratecontrol: 1%). Overall, this study suggests that the severity of acute infection and a history of CPD, migraine, CFS, or fibromyalgia may be risk factors for long COVID symptoms. Our findings motivate clinical studies to evaluate whether suppressing acute disease severity proactively, especially in patients at high risk, can reduce incidence of long COVID.

Metabolic syndrome and aberrant immune responses to viral infection and vaccination: Insights from small animal models

This review outlines the propensity for metabolic syndrome (MetS) to induce elevated disease severity, higher mortality rates post-infection, and poor vaccination outcomes for viral pathogens. MetS is a cluster of conditions including high blood glucose, an increase in circulating low-density lipoproteins and triglycerides, abdominal obesity, and elevated blood pressure which often overlap in their occurrence. MetS diagnoses are on the rise, as reported cases have increased by greater than 35% since 1988, resulting in one-third of United States adults currently diagnosed as MetS patients. In the aftermath of the 2009 H1N1 pandemic, a link between MetS and disease severity was established. Since then, numerous studies have been conducted to illuminate the impact of MetS on enhancing virally induced morbidity and dysregulation of the host immune response. These correlative studies have emphasized the need for elucidating the mechanisms by which these alterations occur, and animal studies conducted as early as the 1940s have linked the conditions associated with MetS with enhanced viral disease severity and poor vaccine outcomes. In this review, we provide an overview of the importance of considering overall metabolic health in terms of cholesterolemia, glycemia, triglyceridemia, insulin and other metabolic molecules, along with blood pressure levels and obesity when studying the impact of metabolism-related malignancies on immune function. We highlight the novel insights that small animal models have provided for MetS-associated immune dysfunction following viral infection. Such animal models of aberrant metabolism have paved the way for our current understanding of MetS and its impact on viral disease severity, dysregulated immune responses to viral pathogens, poor vaccination outcomes, and contributions to the emergence of viral variants.

Severe COVID-19 in pregnancy has a distinct serum profile, including greater complement activation and dysregulation of serum lipids

Background

Pregnancies complicated by Coronavirus Disease 2019 (COVID-19) are at an increased risk of severe morbidity due to physiologic changes in immunologic, cardiovascular, and respiratory function. There is little is known about how severity of COVID-19 changes protein and metabolite expression in pregnancy.

Objective

This study aims to investigate the pathophysiology behind various clinical trajectories in pregnant patients diagnosed with COVID-19 using multi-omics profiling.

Study design

This is a prospective cohort study of 30 pregnant patients at a single tertiary care center. Participants were categorized by severity of COVID-19 disease (control, asymptomatic, mild/moderate, or severe). Maternal serum samples underwent LC-MS-based multiomics analysis for profiling of proteins, lipids, electrolytes, and metabolites. Linear regression models were used to assess how disease severity related to analyte levels. Reactome pathway enrichment analysis was conducted on differential analytes.

Results

Of 30 participants, 25 had confirmed diagnosis of COVID-19 (6 asymptomatic (one post-infection), 13 mild/moderate (all post-infection), 6 severe), and 5 participants were controls. Severe COVID-19 was associated with distinct profiles demonstrating significant proteomic and lipidomic signatures which were enriched for annotations related to complement and antibody activity. (FDR < 0.05). Downregulated analytes were not significantly enriched but consisted of annotation terms related to lipoprotein activity (FDR > 0.2). Post-infection mild/moderate COVID-19 did not have significantly altered serum protein, metabolite, or lipid metabolite levels compared to controls.

Conclusions

Pregnancies with severe COVID-19 demonstrate greater inflammation and complement activation and dysregulation of serum lipids. This altered multiomic expression provides insight into the pathophysiology of severe COVID-19 in pregnancy and may serve as potential indicators for adverse pregnancy outcomes.

Reduced circulating FABP2 in patients with moderate to severe COVID-19 may indicate enterocyte functional change rather than cell death

The gut is of importance in the pathology of COVID-19 both as a route of infection, and gut dysfunction influencing the severity of disease. Systemic changes caused by SARS-CoV-2 gut infection include alterations in circulating levels of metabolites, nutrients and microbial products which alter immune and inflammatory responses. Circulating plasma markers for gut inflammation and damage such as zonulin, lipopolysaccharide and β-glycan increase in plasma along with severity of disease. However, Intestinal Fatty Acid Binding Protein / Fatty Acid Binding Protein 2 (I-FABP/FABP2), a widely used biomarker for gut cell death, has paradoxically been shown to be reduced in moderate to severe COVID-19. We also found this pattern in a pilot cohort of mild (n = 18) and moderately severe (n = 19) COVID-19 patients in Milan from March to June 2020. These patients were part of the first phase of COVID-19 in Europe and were therefore all unvaccinated. After exclusion of outliers, patients with more severe vs milder disease showed reduced FABP2 levels (median [IQR]) (124 [368] vs. 274 [558] pg/mL, P < 0.01). A reduction in NMR measured plasma relative lipid-CH3 levels approached significance (median [IQR]) (0.081 [0.011] vs. 0.073 [0.024], P = 0.06). Changes in circulating lipid levels are another feature commonly observed in severe COVID-19 and a weak positive correlation was observed in the more severe group between reduced FABP2 and reduced relative lipid-CH3 and lipid-CH2 levels. FABP2 is a key regulator of enterocyte lipid import, a process which is inhibited by gut SARS-CoV-2 infection. We propose that the reduced circulating FABP2 in moderate to severe COVID-19 is a marker of infected enterocyte functional change rather than gut damage, which could also contribute to the development of hypolipidemia in patients with more severe disease.

Electroencephalography spectral edge frequency and suppression rate-guided sedation in patients with COVID-19: A randomized controlled trial

Background

Sedation in coronavirus disease 2019 (COVID-19) patients has been identified as a major challenge. We aimed to investigate whether the use of a multiparameter electroencephalogram (EEG) protocol to guide sedation in COVID-19 patients would increase the 30-day mechanical ventilation-free days (VFD).

Methods

We conducted a double-blind randomized clinical trial. We included patients with severe pneumonia due to COVID-19 who required mechanical ventilation (MV) and deep sedation. We randomized to the control (n = 25) or multiparameter group (n = 25). Sedation in the intervention group was administered following the standard institutional protocols together with a flow chart designed to reduce the propofol administration dose if the EEG suppression rate was over 2% or the spectral edge frequency 95 (SEF95) was below 10 Hz. We performed an intention-to-treat analysis to evaluate our primary outcome (30-day VFD).

Results

There was no difference in VFD at day 30 (median: 11 [IQR 0–20] days in the control group vs. 0 [IQR 0–21] days in the BIS multiparameter group, p = 0.87). Among secondary outcomes, we documented a 17% reduction in the total adjusted propofol administered during the first 5 days of the protocol [median: 2.3 (IQR 1.9–2.8) mg/k/h in the control group vs. 1.9(IQR 1.5–2.2) mg/k/h in the MP group, p = 0.005]. This was accompanied by a higher average BIS value in the intervention group throughout the treatment period.

Conclusion

A sedation protocol guided by multivariate EEG-derived parameters did not increase the 30-day VFD. However, the intervention led to a reduction in total propofol administration.