Low-density lipoprotein cholesterol levels are associated with poor clinical outcomes in COVID-19

High-density lipoproteins and COVID-19: preparing the next pandemic

High-density lipoproteins (HDLs) are heterogeneous particles with pleiotropic functions including anti-inflammatory and anti-infectious effects. In clinical studies, lower HDL-associated cholesterol (HDL-C) concentration has been associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, severity, and mortality. A reduction in the number of HDL particles, particularly small ones has been observed with alterations in their protein and lipid composition impairing their functions. These observations have supported HDL supplementation with promising results in small preliminary studies. This review summarizes available evidence to better understand the two-way interaction between HDLs and Coronavirus disease 2019 (COVID-19) and guide future HDL-based therapies for preparing for the next pandemic.

Dyslipidemia in severe fever with thrombocytopenia syndrome patients: A retrospective cohort study

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is a rapidly progressive infectious disease triggered by a novel bunyavirus (SFTSV). Despite the critical role of host lipid metabolism in viral infections, research on dyslipidemia in SFTS remains limited.

METHODS

This retrospective study included 433 SFTS patients, who were stratified into survival group (n = 365) and death group (n = 68) and who were treated at the Shandong Public Health Clinical Center from September 2021 to December 2023. Additionally, 96 healthy controls with matching baseline characteristics were included from Shandong Provincial Hospital. Cross-sectional analysis based on admission data and longitudinal analysis over time were employed to survey the correlation between serum lipid profiles and mortality in SFTS patients.

RESULTS

SFTS patients exhibited elevated triglyceride (TG) levels and reduced total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels compared to healthy individuals. Cross-sectional analysis demonstrated that lower LDL-C and apolipoprotein-B (ApoB) levels were related to elevated mortality risk in SFTS patients. Longitudinal analysis demonstrated that LDL-C and ApoB levels remained consistently lower in the death group, while TG levels gradually declined, and HDL-C levels gradually increased as the disease progressed.

CONCLUSION

SFTS patients exhibit significant dyslipidemia compared to healthy individuals. Lower LDL-C and ApoB levels may independently influence mortality in SFTS patients. Elevated TG and reduced HDL-C levels may associate with disease progression.

Hospitalization for SARS-CoV-2 and the risk of self-harm readmission: a French nationwide retrospective cohort study

AIMS

The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the risk of self-harming behaviours warrants further investigation. Here, we hypothesized that people with a history of hospitalization for self-harm may be particularly at risk of readmission in case of SARS-CoV-2 hospitalization.

METHODS

We conducted a retrospective analysis based on the French national hospitalization database. We identified all patients hospitalized for deliberate self-harm (10th edition of the International Classification of Diseases codes X60-X84) between March 2020 and March 2021. To study the effect of SARS-CoV-2 hospitalization on the risk of readmission for self-harm at 1-year of the inclusion, we performed a multivariable Fine and Gray model considering hospital death as a competing event.

RESULTS

A total of 61,782 individuals were hospitalized for self-harm. During the 1-year follow-up, 9,403 (15.22%) were readmitted for self-harm. Between inclusion and self-harm readmission or the end of follow-up, 1,214 (1.96% of the study cohort) were hospitalized with SARS-CoV-2 (mean age 60 years, 52.9% women) while 60,568 were not (mean age 45 years, 57% women). Multivariate models revealed that the factors independently associated with self-harm readmission were: hospitalization with SARS-CoV-2 (adjusted hazard ratio (aHR) = 3.04 [2.73-3.37]), psychiatric disorders (aHR = 1.61 [1.53-1.69]), self-harm history (aHR = 2.00 [1.88-2.04]), intensive care and age above 80.

CONCLUSIONS

In hospitalized people with a personal history of self-harm, infection with SARS-CoV-2 increased the risk of readmission of self-harm, with an effect that seemed to add to the effect of a history of mental disorders, with an equally significant magnitude. Infection may be a significantly stressful condition that precipitates self-harming acts in vulnerable individuals. Clinicians should pay particular attention to the emergence of suicidal ideation in these patients in the aftermath of SARS-CoV-2 infection.

Lower serum LDL-C levels are associated with poor prognosis in severe fever with thrombocytopenia syndrome: a single-center retrospective cohort study

Background

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease triggered by a novel bunyavirus (SFTSV). Characterized by fever, thrombocytopenia, leukocytopenia, and multiple organ dysfunction manifestations, its primary mode of transmission is through tick bites. Despite the critical role of lipid metabolism in viral infections, the role of lipids in SFTS remains unclear.

Methods

This retrospective study analyzed 602 patients with SFTS treated at the Shandong Public Health Clinical Center from January 2021 to December 2023. Based on the endpoint events, patients were classified into survival (S) and death (D) groups. The S group was further classified into non-critical (non-C) and critical (C) groups based on symptoms. All patients were followed up for at least 28 days after admission. Propensity score matching, multivariable logistic regression, survival analysis, time trend analysis, and mediation analysis were conducted to assess the association between LDL-C levels and prognosis in SFTS.

Results

The serum LDL-C levels on admission were significantly lower in the D and C groups than in the S and non-C groups. The logistic regression models indicated a potential association between LDL-C levels and a poor prognosis in SFTS. The restricted cubic spline showed a unidirectional trend between LDL-C levels and mortality, with a cutoff value of 1.59 mmol/L. The survival analysis revealed higher and earlier mortality in the low-LDL-C group than in the high-LDL-C group. The trends over 28 days post-admission showed that the serum LDL-C levels gradually increased in SFTS, with a favorable prognosis. Finally, the mediation analysis indicated that low LDL-C levels are associated with mortality through poor hepatic, cardiac, and coagulation functions.

Conclusion

Low LDL-C levels are potentially associated with a poor prognosis in SFTS.

Causal relationship between blood traits and severe influenza A(H1N1)pdm09 infection in East Asian: A Mendelian randomization study

Although a range of blood traits have been reported to be associated with influenza A(H1N1)pdm09 (H1N1pdm09) disease severity, their underlying causal relationships and biological mechanisms have remained unclear. This study aimed to investigate the causal relationship between blood traits and H1N1pdm09 using a two-sample Mendelian randomization analysis. Based on the data from our in-house genome-wide association study (GWAS) on H1N1pdm09 disease severity (Ncase [severe] = 70, Ncontrol [mild] = 95) and GWAS summaries of 44 blood traits from Biobank Japan (N = 12 303-143 658), we identified the potential causal effect of blood traits on severe H1N1pdm09. The inverse variance weighted method analysis revealed significant causal effects of lower aspartate aminotransferase (AST, β = -3.212, p = 0.019), low-density-lipoprotein cholesterol (LDL-C, β = -1.372, p = 0.045), and basophil counts (Baso, β = -1.638, p = 0.047) on severe H1N1pdm09 disease. Additionally, polygenic risk score analysis further confirmed genetic overlap between these blood traits and severe H1N1pdm09 disease. This study provided evidence linking the lower level of AST, LDL-C, and lower count of Baso with severe H1N1pdm09 disease, potentially identifying new therapeutic targets for patients with severe influenza.

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

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

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.

The bidirectional interaction of COVID-19 infections and lipoproteins

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

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.

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

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

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

Background

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

Methods

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

Result

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

Conclusion

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

Dyslipidemia and Inflammation as Hallmarks of Oxidative Stress in COVID-19: A Follow-Up Study

Recent works have demonstrated a significant reduction in cholesterol levels and increased oxidative stress in patients with coronavirus disease 2019 (COVID-19). The cause of this alteration is not well known. This study aimed to comprehensively evaluate their possible association during the evolution of COVID-19. This is an observational prospective study. The primary endpoint was to analyze the association between lipid peroxidation, lipid, and inflammatory profiles in COVID-19 patients. A multivariate regression analysis was employed. The secondary endpoint included the long-term follow-up of lipid profiles. COVID-19 patients presented significantly lower values in their lipid profile (total, low, and high-density lipoprotein cholesterol) with greater oxidative stress and inflammatory response compared to the healthy controls. Lipid peroxidation was the unique oxidative parameter with a significant association with the total cholesterol (OR: 0.982; 95% CI: 0.969-0.996; p = 0.012), IL1-RA (OR: 0.999; 95% CI: 0.998-0.999; p = 0.021) IL-6 (OR: 1.062; 95% CI: 1.017-1.110; p = 0.007), IL-7 (OR: 0.653; 95% CI: 0.433-0.986; p = 0.042) and IL-17 (OR: 1.098; 95% CI: 1.010-1.193; p = 0.028). Lipid abnormalities recovered after the initial insult during long-term follow-up (IQR 514 days); however, those with high LPO levels at hospital admission had, during long-term follow-up, an atherogenic lipid profile. Our study suggests that oxidative stress in COVID-19 is associated with derangements of the lipid profile and inflammation. Survivors experienced a recovery in their lipid profiles during long-term follow-up, but those with stronger oxidative responses had an atherogenic lipid profile.

Remnant cholesterol levels are associated with severity and death in COVID-19 patients

Coronavirus disease-19 (COVID-19) patients with severe complications present comorbidities like cardiovascular-disease, hypertension and type-2 diabetes mellitus (DM), sharing metabolic alterations like insulin resistance (IR) and dyslipidemia. Our objective was to evaluate the association among different components of the lipid-lipoprotein profile, such as remnant lipoprotein (RLP)-cholesterol, in patients with COVID-19, and to analyze their associations with the severity of the disease and death. We studied 193 patients (68 (29-96) years; 49.7% male) hospitalized for COVID-19 and 200 controls (46 (18-79) years; 52.5% male). Lipoprotein profile, glucose and procalcitonin were assessed. Patients presented higher glucose, TG, TG/HDL-cholesterol and RLP-cholesterol levels, but lower total, LDL, HDL and no-HDL-cholesterol levels (p < 0.001). When a binary logistic regression was performed, age, non-HDL-cholesterol, and RLP-cholesterol were associated with death (p = 0.005). As the COVID-19 condition worsened, according to procalcitonin tertiles, a decrease in all the cholesterol fractions (p < 0.03) was observed with no differences in TG, while levels of RLP-cholesterol and TG/HDL-cholesterol increased (p < 0.001). Lower levels of all the cholesterol fractions were related with the presence and severity of COVID-19, except for RLP-cholesterol levels and TG/HDL-cholesterol index. These alterations indicate a lipid metabolic disorder, characteristic of IR states in COVID-19 patients. RLP-cholesterol levels predicted severity and death in these patients.

A Review of Routine Laboratory Biomarkers for the Detection of Severe COVID-19 Disease

As the COVID-19 pandemic continues, there is an urgent need to identify clinical and laboratory predictors of disease severity and prognosis. Once the coronavirus enters the cell, it triggers additional events via different signaling pathways. Cellular and molecular deregulation evoked by coronavirus infection can manifest as changes in laboratory findings. Understanding the relationship between laboratory biomarkers and COVID-19 outcomes would help in developing a risk-stratified approach to the treatment of patients with this disease. The purpose of this review is to investigate the role of hematological (white blood cell (WBC), lymphocyte, and neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet, and red blood cell (RBC) count), inflammatory (C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and lactate dehydrogenase (LDH)), and biochemical (Albumin, aspartate aminotransferase (AST) and alanine aminotransferase (ALT), blood urea nitrogen (BUN), creatinine, D-dimer, total Cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL)) biomarkers in the pathogenesis of COVID-19 disease and how their levels vary according to disease severity.

MAGI1 inhibits interferon signaling to promote influenza A infection

We have shown that membrane-associated guanylate kinase with inverted domain structure-1 (MAGI1), a scaffold protein with six PSD95/DiscLarge/ZO-1 (PDZ) domains, is involved in the regulation of endothelial cell (EC) activation and atherogenesis in mice. In addition to causing acute respiratory disease, influenza A virus (IAV) infection plays an important role in atherogenesis and triggers acute coronary syndromes and fatal myocardial infarction. Therefore, the aim of this study is to investigate the function and regulation of MAGI1 in IAV-induced EC activation. Whereas, EC infection by IAV increases MAGI1 expression, MAGI1 depletion suppresses IAV infection, suggesting that the induction of MAGI1 may promote IAV infection. Treatment of ECs with oxidized low-density lipoprotein (OxLDL) increases MAGI1 expression and IAV infection, suggesting that MAGI1 is part of the mechanistic link between serum lipid levels and patient prognosis following IAV infection. Our microarray studies suggest that MAGI1-depleted ECs increase protein expression and signaling networks involve in interferon (IFN) production. Specifically, infection of MAGI1-null ECs with IAV upregulates expression of signal transducer and activator of transcription 1 (STAT1), interferon b1 (IFNb1), myxovirus resistance protein 1 (MX1) and 2'-5'-oligoadenylate synthetase 2 (OAS2), and activate STAT5. By contrast, MAGI1 overexpression inhibits Ifnb1 mRNA and MX1 expression, again supporting the pro-viral response mediated by MAGI1. MAGI1 depletion induces the expression of MX1 and virus suppression. The data suggests that IAV suppression by MAGI1 depletion may, in part, be due to MX1 induction. Lastly, interferon regulatory factor 3 (IRF3) translocates to the nucleus in the absence of IRF3 phosphorylation, and IRF3 SUMOylation is abolished in MAGI1-depleted ECs. The data suggests that MAGI1 inhibits IRF3 activation by maintaining IRF3 SUMOylation. In summary, IAV infection occurs in ECs in a MAGI1 expression-dependent manner by inhibiting anti-viral responses including STATs and IRF3 activation and subsequent MX1 induction, and MAGI1 plays a role in EC activation, and in upregulating a pro-viral response. Therefore, the inhibition of MAGI1 is a potential therapeutic target for IAV-induced cardiovascular disease.

COVID-19 and Lipid Disorders

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

Thyroid-Stimulating Hormone Predicts Total Cholesterol and Low-Density Lipoprotein Cholesterol Reduction during the Acute Phase of COVID-19

A complex dysregulation of lipid metabolism occurs in COVID-19, leading to reduced total cholesterol (TC), LDL-cholesterol (LDL-C), and HDL-cholesterol (HDL-C) levels, along with a derangement of thyroid function, leading to reduced thyroid-stimulating hormone (TSH) levels. This study aimed to explore the association between TSH levels during COVID-19 and the variation (Δ) of lipid profile parameters in the period preceding (from 1 month up to 1 year) hospital admission due to COVID-19. Clinical data of 324 patients (mean age 76 ± 15 years, 54% males) hospitalized due to COVID-19 between March 2020 and March 2022 were retrospectively analyzed. The association between TSH levels at hospital admission and either Δ-TC, Δ-LDL-C, or Δ-HDL-C over the selected time frame was assessed through univariable and multivariable analyses. TSH levels were below the lower reference limit of 0.340 μUI/mL in 14% of COVID-19 patients. A significant reduction of plasma TC, LDL-C, and HDL-C was recorded between the two time points (p < 0.001 for all the comparisons). TSH was directly associated with Δ-TC (rho = 0.193, p = 0.001), Δ-LDL-C (rho = 0.201, p = 0.001), and Δ-HDL-C (rho = 0.160, p = 0.008), and inversely associated with C-reactive protein (CRP) (rho = −0.175, p = 0.004). Moreover, TSH decreased with increasing COVID-19 severity (p < 0.001). CRP and COVID-19 severity were inversely associated with Δ-TC, Δ-LDL-C, and Δ-HDL-C (p < 0.05 for all associations). A significant independent association was found between TSH and either Δ-TC (β = 0.125, p = 0.044) or Δ-LDL-C (β = 0.131, p = 0.036) after adjusting for multiple confounders including CRP and COVID-19 severity. In conclusion, lower levels of TSH may contribute to explain TC and LDL-C reduction in the acute phase of COVID-19.

Dietary Cholesterol Causes Inflammatory Imbalance and Exacerbates Morbidity in Mice Infected with Influenza A Virus

Influenza is a common cause of pneumonia-induced hospitalization and death, but how host factors function to influence disease susceptibility or severity has not been fully elucidated. Cellular cholesterol levels may affect the pathogenesis of influenza infection, as cholesterol is crucial for viral entry and replication, as well as immune cell proliferation and function. However, there is still conflicting evidence on the extent to which dietary cholesterol influences cholesterol metabolism. In this study, we examined the effects of a high-cholesterol diet in modulating the immune response to influenza A virus (IAV) infection in mice. Mice were fed a standard or a high-cholesterol diet for 5 wk before inoculation with mouse-adapted human IAV (Puerto Rico/8/1934), and tissues were collected at days 0, 4, 8, and 16 postinfection. Cholesterol-fed mice exhibited dyslipidemia characterized by increased levels of total serum cholesterol prior to infection and decreased triglycerides postinfection. Cholesterol-fed mice also displayed increased morbidity compared with control-fed mice, which was neither a result of immunosuppression nor changes in viral load. Instead, transcriptomic analysis of the lungs revealed that dietary cholesterol caused upregulation of genes involved in viral-response pathways and leukocyte trafficking, which coincided with increased numbers of cytokine-producing CD4⁺ and CD8⁺ T cells and infiltrating dendritic cells. Morbidity as determined by percent weight loss was highly correlated with numbers of cytokine-producing CD4⁺ and CD8⁺ T cells as well as granulocytes. Taken together, dietary cholesterol promoted IAV morbidity via exaggerated cellular immune responses that were independent of viral load.

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

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

Investigation of systemic immune-inflammation index, neutrophil/high-density lipoprotein ratio, lymphocyte/high-density lipoprotein ratio, and monocyte/high-density lipoprotein ratio as indicators of inflammation in patients with schizophrenia and bipolar disorder

BACKGROUND

The systemic immune-inflammation index (SII), system inflammation response index (SIRI), neutrophil/high-density lipoprotein (HDL) ratio (NHR), lymphocyte/HDL ratio (LHR), monocyte/HDL ratio (MHR), and platelet/HDL ratio (PHR) have been recently investigated as new markers for inflammation. The purpose of this research is to use large-scale clinical data to discuss and compare the predictive ability of the SII, SIRI, NHR, LHR, MHR, and PHR in patients with schizophrenia (SCZ) and bipolar disorder (BD), to investigate potential biomarkers.

MATERIALS AND METHODS

In this retrospective, naturalistic, cross-sectional study, we collected the hematological parameter data of 13,329 patients with SCZ, 4,061 patients with BD manic episodes (BD-M), and 1,944 patients with BD depressive episodes (BD-D), and 5,810 healthy subjects served as the healthy control (HC) group. The differences in the SII, SIRI, NHR, LHR, MHR, and PHR were analyzed, and a receiver operating characteristic (ROC) curve was used to analyze the diagnostic potential of these parameters.

RESULTS

Compared with the HC group, the values of the SII, SIRI, NHR, LHR, MHR, and PHR and the levels of neutrophils, monocytes, and triglycerides (TG) were higher in SCZ and BD groups, and levels of platelets, cholesterol (CHO), HDL, low-density lipoprotein (LDL), and apoprotein B (Apo B) were lower in SCZ and BD groups. Compared to the BD group, the values of the SIRI, lymphocytes, monocytes, and HDL were lower and the values of the SII, NHR, PHR, and platelet were higher in the SCZ group. In contrast to the BD-D group, the values of the SII; SIRI; NHR; and MHR; and levels of neutrophils, monocytes, and platelets were higher in the BD-M group, and the levels of CHO, TG, LDL, and Apo B were lower in the BD-M group. The MHR and NHR were predictors for differentiating the SCZ group from the HC group; the SIRI, NHR, and MHR were predictors for differentiating the BD-M group from the HC group; and the MHR was a predictor for differentiating the BD-D group from the HC group. The combination model of the indicators improved diagnostic effectiveness.

CONCLUSION

Our study highlights the role of systemic inflammation in the pathophysiology of SCZ, BD-M, and BD-D, the association between inflammation and lipid metabolism, and these inflammation and lipid metabolism indicators showed different variation patterns in SCZ, BD-D, and BD-M.

Strong relationship between cholesterol, low-density lipoprotein receptor, Na+/H+ exchanger, and SARS-COV-2: this association may be the cause of death in the patient with COVID-19

Lipids have a wide variety and vital functions. Lipids play roles in energy metabolism, intracellular and extracellular signal traffic, and transport of fat-soluble vitamins. Also, they form the structure of the cell membrane. SARS-CoV-2 interacts with lipids since its genetic material contains lipid-enveloped ribonucleic acid (RNA). Previous studies have shown that total cholesterol, high-density lipoprotein, and low-density lipoprotein (LDL) levels are lower in patients with severe novel coronavirus disease 2019 (COVID-19) compared to patients with non-severe COVID-19.Na+/H+ Exchanger (NHE) is an important antiport that keeps the intracellular pH value within physiological limits. When the intracellular pH falls, NHE is activated and pumps H+ ions outward. However, prolonged NHE activation causes cell damage and atherosclerosis. Prolonged NHE activation may increase susceptibility to SARS-CoV-2 infection and severity of COVID-19.In COVID-19, increased angiotensin II (Ang II) due to angiotensin-converting enzyme-2 (ACE2) dysfunction stimulates NHE. Lipids are in close association with the NHE pump. Prolonged NHE activity increases the influx of H+ ions and free fatty acid (FFA) inward. Ang II also causes increased low-density lipoprotein receptor (LDLR) levels by inhibiting proprotein convertase subtilisin/kexin type 9 (PCSK9). Thus, intracellular atheroma plaque formation is accelerated.Besides, SARS-CoV-2 may replicate more rapidly as intracellular cholesterol increases. SARS-CoV-2 swiftly infects the cell whose intracellular pH decreases with NHE activation and FFA movement. Novel treatment regimens based on NHE and lipids should be explored for the treatment of COVID-19.

Strong relationship between cholesterol, low-density lipoprotein receptor, Na+/H+ exchanger, and SARS-COV-2: this association may be the cause of death in the patient with COVID-19

Lipids have a wide variety and vital functions. Lipids play roles in energy metabolism, intracellular and extracellular signal traffic, and transport of fat-soluble vitamins. Also, they form the structure of the cell membrane. SARS-CoV-2 interacts with lipids since its genetic material contains lipid-enveloped ribonucleic acid (RNA). Previous studies have shown that total cholesterol, high-density lipoprotein, and low-density lipoprotein (LDL) levels are lower in patients with severe novel coronavirus disease 2019 (COVID-19) compared to patients with non-severe COVID-19.Na⁺/H⁺ Exchanger (NHE) is an important antiport that keeps the intracellular pH value within physiological limits. When the intracellular pH falls, NHE is activated and pumps H⁺ ions outward. However, prolonged NHE activation causes cell damage and atherosclerosis. Prolonged NHE activation may increase susceptibility to SARS-CoV-2 infection and severity of COVID-19.In COVID-19, increased angiotensin II (Ang II) due to angiotensin-converting enzyme-2 (ACE2) dysfunction stimulates NHE. Lipids are in close association with the NHE pump. Prolonged NHE activity increases the influx of H⁺ ions and free fatty acid (FFA) inward. Ang II also causes increased low-density lipoprotein receptor (LDLR) levels by inhibiting proprotein convertase subtilisin/kexin type 9 (PCSK9). Thus, intracellular atheroma plaque formation is accelerated.Besides, SARS-CoV-2 may replicate more rapidly as intracellular cholesterol increases. SARS-CoV-2 swiftly infects the cell whose intracellular pH decreases with NHE activation and FFA movement. Novel treatment regimens based on NHE and lipids should be explored for the treatment of COVID-19.

Estimating causal effects of atherogenic lipid-related traits on COVID-19 susceptibility and severity using a two-sample Mendelian randomization approach

BACKGROUND

As the number of COVID-19 deaths continues to rise worldwide, the identification of risk factors for the disease is an urgent issue, and it remains controversial whether atherogenic lipid-related traits including serum apolipoprotein B, low-density lipoprotein (LDL)-cholesterol, and triglyceride levels, are risk factors. The aim of this study was to estimate causal effects of lipid-related traits on COVID-19 risk in the European population using a two-sample Mendelian randomization (MR) approach.

METHODS

We used summary statistics from a genome-wide association study (GWAS) that included 441,016 participants from the UK Biobank as the exposure dataset of lipid-related traits and from COVID-19 Host Genetics Initiative GWAS meta-analyses of European ancestry as the outcome dataset for COVID-19 susceptibility (32,494 cases and 1,316,207 controls), hospitalization (8316 cases and 1,549,095 controls), and severity (4792 cases and 1,054,664 controls). We performed two-sample MR analyses using the inverse variance weighted (IVW) method. As sensitivity analyses, the MR-Egger regression, weighted median, and weighted mode methods were conducted as were leave-one-out sensitivity analysis, the MR-PRESSO global test, PhenoScanner searches, and IVW multivariable MR analyses. A P value below 0.0055 with Bonferroni correction was considered statistically significant.

RESULTS

This MR study suggested that serum apolipoprotein B or LDL-cholesterol levels were not significantly associated with COVID-19 risk. On the other hand, we inferred that higher serum triglyceride levels were suggestively associated with higher risks of COVID-19 susceptibility (odds ratio [OR] per standard deviation increase in lifelong triglyceride levels, 1.065; 95% confidence interval [CI], 1.001-1.13; P = 0.045) and hospitalization (OR, 1.174; 95% CI, 1.04-1.33; P = 0.012), and were significantly associated with COVID-19 severity (OR, 1.274; 95% CI, 1.08-1.50; P = 0.004). Sensitivity and bidirectional MR analyses suggested that horizontal pleiotropy and reverse causation were unlikely.

CONCLUSIONS

Our MR study indicates a causal effect of higher serum triglyceride levels on a greater risk of COVID-19 severity in the European population using the latest and largest GWAS datasets to date. However, as the underlying mechanisms remain unclear and our study might be still biased due to possible horizontal pleiotropy, further studies are warranted to validate our findings and investigate underlying mechanisms.

Lipid profile as an indicator of COVID-19 severity: A systematic review and meta-analysis

Background

Coronavirus disease-2019 (COVID-19) is a global pandemic. Studies reported dyslipidemia in patients with COVID-19. Herein, we conducted a systematic review and meta-analysis of published articles to evaluate the association of the lipid profile with the severity and mortality in COVID-19 patients.

Methods

PubMed/Medline, Europe PMC, and Google Scholar were searched for studies published between January 1, 2020 and January 13, 2021. Random or Fixed effects models were used to calculate the mean difference (MD) and 95% confidence intervals (CIs). Statistical heterogeneity was assessed using Cochran's Q test and I² statistics.

Results

This meta-analysis included 19 studies. Of which, 12 studies were categorized by severity, 04 studies by mortality, and 03 studies by both severity and mortality. Our findings revealed significantly decreased levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in the severe group when compared with the non-severe group in a random effect model. Similarly, random effect model results demonstrated significantly lower levels of HDL-C and LDL-C in the non-survivor group when compared with the survivor group. The level of TC was also found to be decreased in the non-survivor group when compared to the survivor group in a fixed-effect model.

Conclusion

In conclusion, the lipid profile is associated with both the severity and mortality in COVID-19 patients. Hence, the lipid profile may be used for assessing the severity and prognosis of COVID-19.

Prospero registration number

CRD42021216316.

Possible mechanisms of cholesterol elevation aggravating COVID-19

Importance: Despite the availability of a vaccine against the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), humans will have to live with this virus and the after-effects of the coronavirus disease 2019 (COVID-19) infection for a long time. Cholesterol plays an important role in the infection and prognosis of SARS-CoV-2, and the study of its mechanism is of great significance not only for the treatment of COVID-19 but also for research on generic antiviral drugs. Observations: Cholesterol promotes the development of atherosclerosis by activating NLR family pyrin domain containing 3 (NLRP3), and the resulting inflammatory environment indirectly contributes to COVID-19 infection and subsequent deterioration. In in vitro studies, membrane cholesterol increased the number of viral entry sites on the host cell membrane and the number of angiotensin-converting enzyme 2 (ACE2) receptors in the membrane fusion site. Previous studies have shown that the fusion protein of the virus interacts with cholesterol, and the spike protein of SARS-CoV-2 also requires cholesterol to enter the host cells. Cholesterol in blood interacts with the spike protein to promote the entry of spike cells, wherein the scavenger receptor class B type 1 (SR-B1) plays an important role. Because of the cardiovascular protective effects of lipid-lowering therapy and the additional anti-inflammatory effects of lipid-lowering drugs, it is currently recommended to continue lipid-lowering therapy for patients with COVID-19, but the safety of extremely low LDL-C is questionable. Conclusions and Relevance: Cholesterol can indirectly increase the susceptibility of patients to SARS-CoV-2 and increase the risk of death from COVID-19, which are mediated by NLRP3 and atherosclerotic plaques, respectively. Cholesterol present in the host cell membrane, virus, and blood may also directly participate in the virus cell entry process, but the specific mechanism still needs further study. Patients with COVID-19 are recommended to continue lipid-lowering therapy.