Cholesterol and Triglyceride Concentrations, COVID-19 Severity, and Mortality: A Systematic Review and Meta-Analysis With Meta-Regression

Impact of the triglyceride-glucose index on 28-day mortality in non-diabetic critically Ill patients with sepsis: a retrospective cohort analysis

INTRODUCTION

Sepsis is a life-threatening condition that poses a globally high mortality rate. Identifying risk factors is crucial. Insulin resistance and the TYG index, associated with metabolic disorders, may play a role. This study explores their correlation with mortality in non-diabetic septic patients.

METHODS

This retrospective cohort study used data from the MIMIC-IV (version 2.1) database, which includes over 50,000 ICU admissions from 2008 to 2019 at Beth Israel Deaconess Medical Center in Boston. We included adult patients with sepsis who were admitted to the intensive care unit in the study. The primary outcome was to evaluate the ability of TYG to predict death at 28-day of hospital admission in patients with sepsis.

RESULTS

The study included 2213 patients with sepsis, among whom 549 (24.8%) died within 28 days of hospital admission. We observed a non-linear association between TYG and the risk of mortality. Compared to the reference group (lower TYG subgroup), the 28-day mortality increased in the higher TYG subgroup, with a fully adjusted hazard ratio of 2.68 (95% CI: 2.14 to 3.36). The area under the curve (AUC) for TYG was 67.7%, higher than for triglycerides alone (AUC = 64.1%), blood glucose (AUC = 62.4%), and GCS (AUC = 63.6%), and comparable to SOFA (AUC = 69.3%). The final subgroup analysis showed no significant interaction between TYG and each subgroup except for the COPD subgroup (interaction P-values: 0.076-0.548).

CONCLUSION

In our study, TYG can be used as an independent predictor for all-cause mortality due to sepsis within 28 days of hospitalization.

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.

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.

The Triglycerides and Glucose Index Is an Independent Risk Factor for Acute Respiratory Distress Syndrome in Patients with COVID-19

Introduction: Although it has been observed that the triglycerides and glucose (TyG) index, a biomarker of insulin resistance, is associated with severity and morbidity by COVID-19, evidence is still scarce. Therefore, the objective of this study was to determine whether the TyG index is associated with both the degree of severity and mortality by acute respiratory distress syndrome (ARDS) in patients with COVID-19. Methods: Men and women aged 20 years or more with diagnosis of COVID-19 were included in a case-control study. Exclusion criteria were pregnancy, cancer, autoimmune diseases, autoimmune treatment, and incomplete data. Patients with severe COVID-19 ARDS were allocated into the case group, and those with mild or moderate COVID-19 ARDS in the control group. COVID-19 was defined by a positive reverse transcriptase-polymerase chain reaction test for SARS-CoV-2, and ARDS was defined according to the Berlin criteria. Results: A total of 206 patients were included and allocated into the case (n = 103) and control (n = 103) groups. The logistic regression analysis adjusted by age, sex, and body mass index showed that the TyG index is significantly associated with moderate [odds ratio (OR) = 6.0; 95% confidence interval (CI): 1.1-30.6] and severe (OR = 9.5; 95% CI: 2.4-37.5) COVID-19 ARDS, and death (OR = 10.1; 95% CI: 2.2-46.5). Conclusion: The results of our study show a significant and independent association of the TyG index with ARDS and mortality in patients with COVID-19.

Limited efficacy of low-dose dexamethasone for the treatment of severe COVID-19 pneumonia: A retrospective study

BACKGROUND

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2. Its symptoms range from mild to severe, with the latter often being life-threatening. This study aims to assess the effects of low-dose dexamethasone (DEX) in mild-to-severe COVID-19 pneumonia and examine the final clinical outcomes to identify the optimal therapeutic dose.

METHODS

Clinical data from 132 patients hospitalized for COVID-19 pneumonia between January and October 2021 at Yamato Municipal Hospital were retrospectively analyzed. Based on the ratio of peripheral arterial oxygen saturation (SpO2) to inspired fraction of oxygen (FiO2), patients were categorized into the mild (>450, n = 65), moderate (315-450, n = 55), and severe (<315, n = 12) pneumonia groups. The event of interest was defined as the worsening of the patient's condition during treatment (need to increase FiO2 > 0.1). Patients were treated with low-dose DEX (6.6 mg/day) for 10 days.

RESULTS

The event-free survival rate decreased significantly in patients with severe pneumonia compared with in those with mild and moderate pneumonia (Bonferroni-adjusted p < 0.02). A total of 16 patients were treated with high-dose corticosteroids because of severe hypoxia. Recovery was observed in all discharged patients with respiratory condition improvement. Low SpO2/FiO2 at admission was significantly associated with serum C-reactive protein levels.

CONCLUSIONS

For Japanese patients with COVID-19, severe pneumonia, and SpO2/FiO2 of <315, it may be necessary to administer a dose of corticosteroids of >6.6 mg DEX.

Host metabolome predicts the severity and onset of acute toxicities induced by CAR T-cell therapy

Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy is a highly effective treatment option for patients with relapsed/refractory large B-cell lymphoma. However, widespread use is deterred by the development of clinically significant acute inflammatory toxicities, including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), that induce significant morbidity and require close monitoring. Identification of host biochemical signatures that predict the severity and time-to-onset of CRS and ICANS may assist patient stratification to enable timely mitigation strategies. Here, we report pretreatment host metabolites that are associated with CRS and ICANS induced by axicabtagene ciloleucel or tisagenlecleucel therapy. Both untargeted metabolomics analysis and validation using targeted assays revealed a significant association between the abundance of specific pretreatment biochemical entities and an increased risk and/or onset of clinically significant CRS (q < .1) and ICANS (q < .25). Higher pretreatment levels of plasma glucose and lower levels of cholesterol and glutamate were associated with a faster onset of CRS. In contrast, low baseline levels of the amino acids proline and glycine and the secondary bile acid isoursodeoxycholate were significantly correlated with clinically significant CRS. Lower concentration of the amino acid hydroxyproline was associated with higher grade and faster onset of ICANS, whereas low glutamine was negatively correlated with faster development of ICANS. Overall, our data indicate that the pretreatment host metabolome has biomarker potential in determining the risk of clinically significant CRS and ICANS, and may be useful in risk stratification of patients before anti-CD19 CAR T-cell therapy.

The Lasting Effects of COVID-19 on the Progression of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)

It is estimated that around 30% of the population living in Western countries has metabolic dysfunction-associated steatotic liver disease (MASLD), a spectrum of pathology (not attributed to alcohol/substance intake) initiated by steatosis and progression toward inflammation and irreversible fibrosis metabolic dysfunction-associated steatohepatitis (MASH). With inflammation being a key component of the transition to MASH, it raises the question of whether the ongoing COVID-19 pandemic, which has notoriously induced hyperinflammatory states, may influence the progression of MASLD. Specifically, it remains unclear if the potential chronic sequelae of COVID-19 in patients who recovered from it may increase the predisposition for MASH. Since MASH maintains a high risk for hepatocellular carcinoma, liver failure, and the need for a liver transplant, the potential additive effects of COVID-19 could prove critical to study. Thus, the objective of this study was to conduct a literature review to examine if COVID-19 could have chronic sequelae that affect the progression of MASLD pathogenesis. It was hypothesized that severe cases of COVID-19 could induce systemic inflammation, metabolic changes, and lasting gut microbiome alterations that lead to inflammatory and fibrotic changes in the liver, similar to those seen in MASH. A scoping review of the literature was conducted utilizing the PubMed database. Studies that examined hepatobiliary pathology, gut microbiome, systemic inflammation, metabolic changes, drug-induced liver injury (DILI), and hypoxia seen in COVID-19 were included. Human studies of adult cohorts, animal models, and in vitro experiments were included. Genetic components of MASLD were not examined. Exclusion criteria also encompassed any studies not referencing the hepatobiliary, gastrointestinal tract, portal system, or systemic circulation. Findings indicated a frequent trend of elevated liver enzymes, mild steatosis, Kupffer cell hyperplasia, and hepatobiliary congestion. It was found that direct cytopathic effects on hepatocytes were unlikely, but the direct viral insult of cholangiocytes was a potential complication. High serum levels of IL-1, TNF-a, and MCP-1, in COVID-19 were found as potential risk factors for MASH development. Hypoxia, altered lipid metabolism, and iatrogenic DILI were also proposed as potential precipitators of MASH development. Notably, lasting changes in gut microbiome were also frequently observed and correlated closely with those seen in MASH.

Biomarkers of glucose homeostasis as mediators of the relationship of body mass index and waist circumference with COVID-19 outcomes among postmenopausal women: The Women's Health Initiative

BACKGROUND & AIMS

Systematic reviews, meta-analyses and Mendelian randomization studies suggest that cardiometabolic diseases may be associated with COVID-19 risk and prognosis, with evidence implicating insulin resistance (IR) as a common biological mechanism. As driving factors for IR, we examined body mass index (BMI) and waist circumference (WC) among postmenopausal women in association with COVID-19 outcomes (positivity and hospitalization), and the role of glucose homeostasis as a mediator of this relationship.

METHODS

Associations of BMI and WC at baseline (1993-1998) with COVID-19 outcomes collected at Survey 1 (June-December, 2020) and/or Survey 2 (September-December, 2021) were evaluated among 42,770 Women's Health Initiative (WHI) participants (baseline age: 59.36 years) of whom 16,526 self-reported having taken ≥1 COVID-19 test, with 1242 reporting ≥1 positive COVID-19 test and 362 reporting ≥1 COVID-19 hospitalization. We applied logistic regression and causal mediation analyses to sub-samples with available fasting biomarkers of glucose homeostasis (glucose, insulin, Homeostatic Model Assessment for Insulin Resistance, Homeostasis Model Assessment for β-cell function, Quantitative Insulin-sensitivity Check Index, Triglyceride-Glucose index (TyG)) at baseline, whereby 57 of 759 reported COVID-19 test positivity and 23 of 1896 reported COVID-19 hospitalization.

RESULTS

In fully adjusted models, higher BMI, WC and TyG were associated with COVID-19 test positivity and hospitalization. Glucose concentrations mediated associations of BMI and WC with COVID-19 positivity, whereas TyG mediated BMI and WC's associations with COVID-19 hospitalization.

CONCLUSIONS

Obesity and central obesity markers collected an average of 24 years prior were associated with COVID-19 outcomes among postmenopausal women. Glucose concentration and TyG partly mediated these associations.

Association between cyclin-dependent kinase inhibitor 2B antisense RNA 1 and zinc finger homeobox 3 gene polymorphisms and COVID-19 severity

BACKGROUND

There is no doubt about the cardiovascular complications of coronavirus disease 2019 (COVID-19). Several genetic studies have demonstrated an association between genetic variants in a region on chromosome 9p21 and in a region on chromosome 16q22 with myocardial infarction (MI) and atrial fibrillation (AF) accompanied by cerebral infarction (CI), respectively.

OBJECTIVES

MI and CI susceptibility in patients with CDKN2B-AS1 and ZFHX3 polymorphisms, respectively, may have an effect on COVID-19 severity. We aimed to investigate whether there is an association between the cyclin-dependent kinase inhibitor 2B antisense RNA 1 (CDKN2B-AS1) rs1333049 and zinc finger homeobox 3 (ZFHX3) rs2106261 single nucleotide polymorphisms (SNPs) and the degree of COVID-19 severity.

SUBJECTS AND METHODS

This current work was carried out on 360 subjects. They were classified into three groups: 90 severe COVID-19 cases, 90 moderate COVID-19 cases and 180 age- and gender-matched healthy controls. All subjects underwent genotyping of CDKN2B-AS1 (rs1333049) and ZFHX3 (rs2106261) by real-time PCR.

RESULTS

The frequency of G/C in CDKN2B-AS1 (rs1333049) was higher in severe and moderate COVID-19 patients than in controls (71.1% and 53.3% vs. 37.8%). The frequency of the C/C of CDKN2B-AS1 (rs1333049) was higher in moderate COVID-19 patients than in controls (26.7% vs. 13.3%). There were no significant differences regarding genotype frequency and allelic distribution of ZFHX3 (rs2106261) between COVID-19 patients and healthy controls.

CONCLUSION

CDKN2B-AS1 (rs1333049) gene polymorphism may play a role in determining the degree of COVID-19 severity. Further studies on its effect on cyclins and cyclin-dependent kinases (CDKs) [not measured in our study] may shed light on new treatment options for COVID-19.

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.

Cytokine response and damages in the lungs of aging Syrian hamsters on a high-fat diet infected with the SARS-CoV-2 virus

Hypertriglyceridemia, obesity, and aging are among the key risk factors for severe COVID-19 with acute respiratory distress syndrome (ARDS). One of the main prognostic biomarkers of ARDS is the level of cytokines IL-6 and TNF-α in the blood. In our study, we modeled hyperglyceridemia and hypercholesterolemia on 18-month-old Syrian hamsters (Mesocricetus auratus). By 18 months, the animals showed such markers of aging as weight stabilization with a tendency to reduce it, polycystic liver disease, decreased motor activity, and foci of alopecia. The high-fat diet caused an increase in triglycerides and cholesterol, as well as fatty changes in the liver. On the third day after infection with the SARS-CoV-2 virus, animals showed a decrease in weight in the groups with a high-fat diet. In the lungs of males on both diets, there was an increase in the concentration of IFN-α, as well as IL-6 in both males and females, regardless of the type of diet. At the same time, the levels of TNF-α and IFN-γ did not change in infected animals. Morphological studies of the lungs of hamsters with SARS-CoV-2 showed the presence of a pathological process characteristic of ARDS. These included bronchointerstitial pneumonia and diffuse alveolar damages. These observations suggest that in aging hamsters, the immune response to pro-inflammatory cytokines may be delayed to a later period. Hypertriglyceridemia, age, and gender affect the severity of COVID-19. These results will help to understand the pathogenesis of COVID-19 associated with age, gender, and disorders of fat metabolism in humans.

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.

COVID-19 and metabolic syndrome

Convergence of the two pandemics: metabolic syndrome and COVID-19 over last two years has posed unprecedented challenges to individuals as well as healthcare systems. Epidemiological data suggest a close association between metabolic syndrome and COVID-19 while variety of possible pathogenic connections have been proposed while some have been proven. Despite the evidence of high risk for adverse COVID-19 outcomes in people with metabolic syndrome, little is known about the differences in efficacy and safety among people with metabolic syndrome and without. It is important to recognize that among people with metabolic syndrome This review summarizes the current knowledge and epidemiological evidence on the association between metabolic syndrome and adverse COVID-19 outcomes, pathogenic interrelationships, management considerations for acute COVID-19 and post-COVID sequalae and sustaining care of people living with metabolic syndrome with appraisal of evidence and gaps in knowledge.

Using system biology and bioinformatics to identify the influences of COVID-19 co-infection with influenza virus on COPD

Coronavirus disease 2019 (COVID-19) has speedily increased mortality globally. Although they are risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), less is known about the common molecular mechanisms behind COVID-19, influenza virus A (IAV), and chronic obstructive pulmonary disease (COPD). This research used bioinformatics and systems biology to find possible medications for treating COVID-19, IAV, and COPD via identifying differentially expressed genes (DEGs) from gene expression datasets (GSE171110, GSE76925, GSE106986, and GSE185576). A total of 78 DEGs were subjected to functional enrichment, pathway analysis, protein-protein interaction (PPI) network construct, hub gene extraction, and other potentially relevant disorders. Then, DEGs were discovered in networks including transcription factor (TF)-gene connections, protein-drug interactions, and DEG-microRNA (miRNA) coregulatory networks by using NetworkAnalyst. The top 12 hub genes were MPO, MMP9, CD8A, HP, ELANE, CD5, CR2, PLA2G7, PIK3R1, SLAMF1, PEX3, and TNFRSF17. We found that 44 TFs-genes, as well as 118 miRNAs, are directly linked to hub genes. Additionally, we searched the Drug Signatures Database (DSigDB) and identified 10 drugs that could potentially treat COVID-19, IAV, and COPD. Therefore, we evaluated the top 12 hub genes that could be promising DEGs for targeted therapy for SARS-CoV-2 and identified several prospective medications that may benefit COPD patients with COVID-19 and IAV co-infection.

Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis

Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman's correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission. IMPORTANCE Previous reports on the associations between COVID-19 and gut microbiome have been constrained by taxonomic-level analysis and overlook the interaction between microbes. By applying a genome-resolved, reference-free, guild-based metagenomic analysis, we demonstrated that the relationship between gut microbiota and COVID-19 is genome-specific instead of taxon-specific or even species-specific. Moreover, the COVID-19-associated genomes were not independent but formed two competing guilds, with Guild 1 potentially beneficial and Guild 2 potentially more detrimental to the host based on comparative genomic analysis. The dominance of Guild 2 over Guild 1 at time of admission was associated with hospitalized COVID-19 patients at high risk for more severe outcomes. Moreover, the guild-level microbiome signature is not only correlated with the symptom severity of COVID-19 patients, but also differentiates COVID-19 patients from pneumonia controls and healthy subjects across different studies. Here, we showed the possibility of using genome-resolved and guild-level microbiome signatures to identify hospitalized COVID-19 patients with a high risk of more severe outcomes at the time of admission.

Phenotypic changes in low-density lipoprotein particles as markers of adverse clinical outcomes in COVID-19

BACKGROUND AND AIMS

Low-density lipoprotein (LDL) plasma concentration decline is a biomarker for acute inflammatory diseases, including coronavirus disease-2019 (COVID-19). Phenotypic changes in LDL during COVID-19 may be equally related to adverse clinical outcomes.

METHODS

Individuals hospitalized due to COVID-19 (n = 40) were enrolled. Blood samples were collected on days 0, 2, 4, 6, and 30 (D0, D2, D4, D6, and D30). Oxidized LDL (ox-LDL), and lipoprotein-associated phospholipase A2 (Lp-PLA2) activity were measured. In a consecutive series of cases (n = 13), LDL was isolated by gradient ultracentrifugation from D0 and D6 and was quantified by lipidomic analysis. Association between clinical outcomes and LDL phenotypic changes was investigated.

RESULTS

In the first 30 days, 42.5% of participants died due to Covid-19. The serum ox-LDL increased from D0 to D6 (p < 0.005) and decreased at D30. Moreover, individuals who had an ox-LDL increase from D0 to D6 to over the 90th percentile died. The plasma Lp-PLA2 activity also increased progressively from D0 to D30 (p < 0.005), and the change from D0 to D6 in Lp-PLA2 and ox-LDL were positively correlated (r = 0.65, p < 0.0001). An exploratory untargeted lipidomic analysis uncovered 308 individual lipids in isolated LDL particles. Paired-test analysis from D0 and D6 revealed higher concentrations of 32 lipid species during disease progression, mainly represented by lysophosphatidyl choline and phosphatidylinositol. In addition, 69 lipid species were exclusively modulated in the LDL particles from non-survivors as compared to survivors.

CONCLUSIONS

Phenotypic changes in LDL particles are associated with disease progression and adverse clinical outcomes in COVID-19 patients and could serve as a potential prognostic biomarker.

SARS-CoV-2 infection-related deregulation of blood lipids in a patient with -/-LDLR familial homozygous hypercholesterolemia: A case report

BACKGROUND

The effect of SARS-CoV-2 infection in blood lipids of homozygous familial hypercholesterolemia (HoFH) has not been explored.

CASE SUMMARY

We report a case of a 43-year-old male patient with -/-LDLR HoFH with previous history of premature coronary artery disease, coronary artery bypass graft (CABG) and surgical repair of aortic valve stenosis. He presented with an abrupt decrease of his blood lipid levels during acute infection with SARS-CoV2 and subsequently a rebound increase above pre-infection levels, refractory to treatment including LDL-apheresis, statin, ezetimibe and lomitapide up-titration to maximum tolerated doses. Markers of liver stiffness were closely monitored, increased at 9 months and decreased at 18 months after the infection. Potential interactions of hypolipidemic treatment with the viral replication process during the acute phase, as well as therapeutic dilemmas occurring in the post infection period are discussed.

Detection of Porcine Deltacoronavirus RNA in the Upper and Lower Respiratory Tract and Biliary Fluid and the Effect of Infection on Serum Cholesterol Levels and Blood T Cell Population Frequencies in Gnotobiotic Piglets

Porcine deltacoronavirus (PDCoV) was first identified approximately a decade ago, but much is still obscure in terms of its pathogenesis. We aimed to further characterize PDCoV infection by investigating the presence of virus in respiratory and biliary tissues or fluids; T cell population frequencies in blood; and altered serum cholesterol levels. Twelve, 6-day-old, gnotobiotic piglets were inoculated oronasally with PDCoV OH-FD22 (2.6 × 10⁷ FFU/pig). Six control piglets were not inoculated. Rectal swab (RS), nasal swab (NS), nasal wash (NW), bronchoalveolar lavage (BAL), and biliary fluid (BF) samples were collected at 2, 4, and 7 days post-inoculation (DPI) and tested for PDCoV RNA by RT-qPCR. Blood T cell populations and serum cholesterol levels were determined by flow cytometry and a colorimetric assay, respectively. Moderate to high, and low to moderate titers of PDCoV RNA were detected in RS and in NS, NW, BAL, and BF samples, respectively, of inoculated piglets. There were trends toward decreased CD4+CD8-, CD4-CD8+, and CD4+CD8+ blood T cell frequencies in inoculated piglets. Furthermore, serum cholesterol levels were increased in inoculated piglets. Overall, we found that PDCoV infection does not exclusively involve the intestine, since the respiratory and biliary systems and cholesterol metabolism also can be affected.

Association Between Hypocholesterolemia and Mortality in Critically Ill Patients With Sepsis: A Systematic Review and Meta-Analysis

To ascertain the association between cholesterol and triglyceride levels on ICU admission and mortality in patients with sepsis.

DATA SOURCES

Systematic review and meta-analysis of published studies on PubMed and Embase.

STUDY SELECTION

All observational studies reporting ICU admission cholesterol and triglyceride levels in critically ill patients with sepsis were included. Authors were contacted for further data.

DATA EXTRACTION

Eighteen observational studies were identified, including 1,283 patients with a crude overall mortality of 33.3%. Data were assessed using Revman (Version 5.1, Cochrane Collaboration, Oxford, United Kingdom) and presented as mean difference (MD) with 95% CIs, p values, and I ² values.

DATA SYNTHESIS

Admission levels of total cholesterol (17 studies, 1,204 patients; MD = 0.52 mmol/L [0.27-0.77 mmol/L]; p < 0.001; I ² = 91%), high-density lipoprotein (HDL)-cholesterol (14 studies, 991 patients; MD = 0.08 mmol/L [0.01-0.15 mmol/L]; p = 0.02; I ² = 61%), and low-density lipoprotein (LDL)-cholesterol (15 studies, 1,017 patients; MD = 0.18 mmol/L [0.04-0.32 mmol/L]; p = 0.01; I ² = 71%) were significantly lower in eventual nonsurvivors compared with survivors. No association was seen between admission triglyceride levels and mortality (15 studies, 1,070 patients; MD = 0.00 mmol/L [-0.16 to 0.15 mmol/L]; p = -0.95; I ² = 79%).

CONCLUSIONS

Mortality was associated with lower levels of total cholesterol, HDL-cholesterol, and LDL-cholesterol, but not triglyceride levels, in patients admitted to ICU with sepsis. The impact of cholesterol replacement on patient outcomes in sepsis, particularly in at-risk groups, merits investigation.

Autoimmune Reaction Associated With Long COVID Syndrome and Cardiovascular Disease: A Genetic Case Report

A 35-year-old woman with history of cardiovascular disease presented with shortness of breath, lightheadedness, fatigue, chest pain, and premature ventricular contractions 3 weeks after her second COVID-19 vaccine. Symptoms subsided following catheter ablation and ibuprofen except for chest pain and fatigue, which persisted following ablation and subsequent SARS-CoV-2 infection. The case suggests causal associations between COVID-19 vaccine/infection and recurrence of cardiovascular disease, including long-COVID-like symptoms. (Level of Difficulty: Advanced.).

Sex differences in factors influencing hospital-acquired pneumonia in schizophrenia patients receiving modified electroconvulsive therapy

BACKGROUND

Sex differences may be presented in the clinical features or symptoms of schizophrenia patients but also affect the occurrence of hospital-acquired pneumonia (HAP). Modified electroconvulsive therapy (mECT) is a common treatment method for schizophrenia, used in combination with antipsychotics. This retrospective research explores the sex difference in HAP affecting patients with schizophrenia who have received mECT treatment during hospitalization.

METHODS

We included schizophrenia inpatients treated with mECT and antipsychotics between January 2015 and April 2022. Blood-related and demographic data collected on admission were analyzed. Influencing factors of HAP in male and female groups were assessed separately.

RESULTS

A total of 951 schizophrenia patients treated with mECT were enrolled in the study, including 375 males and 576 females, of which 62 patients experienced HAP during hospitalization. The risk period of HAP in these patients was found to be the first day after each mECT treatment and the first three sessions of mECT treatment. Statistically significant differences in the incidence of HAP were identified in male vs. female groups, with an incidence in men about 2.3 times higher than that in women (P < 0.001). Lower total cholesterol (Z = -2.147, P = 0.032) and the use of anti-parkinsonian drugs (χ² = 17.973, P < 0.001) were found to be independent risk factors of HAP in male patients, while lower lymphocyte count (Z = -2.408, P = 0.016), hypertension (χ² = 9.096, P = 0.003), and use of sedative-hypnotic drugs (χ² = 13.636, P < 0.001) were identified in female patients.

CONCLUSION

Influencing factors of HAP in schizophrenia patients treated with mECT have gender differences. The first day after each mECT treatment and the first three sessions of mECT treatment were identified to have the greatest risk for HAP development. Therefore, it would be imperative to monitor clinical management and medications during this period according to these gender differences.

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

Background

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

Methods

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

Results

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

Conclusion

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

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.

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.

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.

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.

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

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

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.

Comparison of Intracellular Transcriptional Response of NHBE Cells to Infection with SARS-CoV-2 Washington and New York Strains

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan, China in December 2019 and caused a global pandemic resulting in millions of deaths and tens of millions of patients positive tests. While studies have shown a D614G mutation in the viral spike protein are more transmissible, the effects of this and other mutations on the host response, especially at the cellular level, are yet to be fully elucidated. In this experiment we infected normal human bronchial epithelial (NHBE) cells with the Washington (D614) strain or the New York (G614) strains of SARS-CoV-2. We generated RNA sequencing data at 6, 12, and 24 hours post-infection (hpi) to improve our understanding of how the intracellular host response differs between infections with these two strains. We analyzed these data with a bioinformatics pipeline that identifies differentially expressed genes (DEGs), enriched Gene Ontology (GO) terms and dysregulated signaling pathways. We detected over 2,000 DEGs, over 600 GO terms, and 29 affected pathways between the two infections. Many of these entities play a role in immune signaling and response. A comparison between strains and time points showed a higher similarity between matched time points than across different time points with the same strain in DEGs and affected pathways, but found more similarity between strains across different time points when looking at GO terms. A comparison of the affected pathways showed that the 24hpi samples of the New York strain were more similar to the 12hpi samples of the Washington strain, with a large number of pathways related to translation being inhibited in both strains. These results suggest that the various mutations contained in the genome of these two viral isolates may cause distinct effects on the host transcriptional response in infected host cells, especially relating to how quickly translation is dysregulated after infection. This comparison of the intracellular host response to infection with these two SARS-CoV-2 isolates suggest that some of the mechanisms associated with more severe disease from these viruses could include virus replication, metal ion usage, host translation shutoff, host transcript stability, and immune inhibition.

Tissue-specific pathway activities: A retrospective analysis in COVID-19 patients

The ACE2 receptors essential for SARS-CoV-2 infections are expressed not only in the lung but also in many other tissues in the human body. To better understand the disease mechanisms and progression, it is essential to understand how the virus affects and alters molecular pathways in the different affected tissues. In this study, we mapped the proteomics data obtained from Nie X. et al. (2021) to the pathway models of the COVID-19 Disease Map project and WikiPathways. The differences in pathway activities between COVID-19 and non-COVID-19 patients were calculated using the Wilcoxon test. As a result, 46% (5,235) of the detected proteins were found to be present in at least one pathway. Only a few pathways were altered in multiple tissues. As an example, the Kinin-Kallikrein pathway, an important inflammation regulatory pathway, was found to be less active in the lung, spleen, testis, and thyroid. We can confirm previously reported changes in COVID-19 patients such as the change in cholesterol, linolenic acid, and arachidonic acid metabolism, complement, and coagulation pathways in most tissues. Of all the tissues, we found the thyroid to be the organ with the most changed pathways. In this tissue, lipid pathways, energy pathways, and many COVID-19 specific pathways such as RAS and bradykinin pathways, thrombosis, and anticoagulation have altered activities in COVID-19 patients. Concluding, our results highlight the systemic nature of COVID-19 and the effect on other tissues besides the lung.

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

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

COVID-19 and Lipid Disorders

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

Are lipid ratios and triglyceride-glucose index associated with critical care outcomes in COVID-19 patients?

Lipid ratios and the triglyceride and glucose index (TyG) could be a simple biochemical marker of insulin resistance (IR). The current study was carried out to examine the correlation between triglyceride to high-density lipoprotein-cholesterol (TG/HDL-C), total cholesterol to HDL-C (TC/HDL-C), low-density lipoprotein-cholesterol to HDL-C ratio (LDL-C/HDL-C), as well as TyG index with the severity and mortality of severe coronavirus disease 2019 (COVID-19). A total of 1228 confirmed COVID-19 patients were included in the current research. Regression models were performed to evaluate the correlation between the lipid index and severity and mortality of COVID-19. The TyG index and TG/HDL-C levels were significantly higher in the severe patients (P<0.05). TG/HDL-C, LDL-C/HDL-C, TC/HDL-C ratios, and TyG index were significantly lower in survivor cases (P<0.05). Multivariate logistic regression analysis demonstrated that predictors of the severity adjusted for age, sex and BMI were TyG index, TG/HDL-C ratio (OR = 1.42 CI:1.10–1.82, OR = 1.06 CI: 1.02–1.11, respectively). This analysis showed that TG/HDL-C, TC/HDL-C, LDL-C/HDL-C ratios, and TyG index statistically are correlated with COVID-19 mortality (OR = 1.12 CI:1.06–1.18, OR = 1.24 CI:1.05–1.48, OR = 1.47 CI:1.19–1.80, OR = 1.52 CI:1.01–2.31, respectively). In summary, the TyG index and lipid ratios such as TC/HDL-C, TG/HDL-C, LDL-C/HDL-C could be used as an early indicator of COVID-19 mortality. Furthermore, the study revealed that TyG index and TG/HDL-C indices are biochemical markers of COVID-19 severe prognosis.

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.

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

Introduction

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

Methods

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

Results

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

Conclusion

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

Integration of omics data to generate and analyse COVID-19 specific genome-scale metabolic models

COVID-19 presents a complex disease that needs to be addressed using systems medicine approaches that include genome-scale metabolic models (GEMs). Previous studies have used a single model extraction method (MEM) and/or a single transcriptomic dataset to reconstruct context-specific models, which proved to be insufficient for the broader biological contexts. We have applied four MEMs in combination with five COVID-19 datasets. Models produced by GIMME were separated by infection, while tINIT preserved the biological variability in the data and enabled the best prediction of the enrichment of metabolic subsystems. Vitamin D3 metabolism was predicted to be down-regulated in one dataset by GIMME, and in all by tINIT. Models generated by tINIT and GIMME predicted downregulation of retinol metabolism in different datasets, while downregulated cholesterol metabolism was predicted only by tINIT-generated models. Predictions are in line with the observations in COVID-19 patients. Our data indicated that GIMME and tINIT models provided the most biologically relevant results and should have a larger emphasis in further analyses. Particularly tINIT models identified the metabolic pathways that are a part of the host response and are potential antiviral targets. The code and the results of the analyses are available to download from https://github.com/CompBioLj/COVID_GEMs_and_MEMs.

Plasma lipid profile: a predictive marker of disease severity among COVID-19 patients—an opportunity for low-income countries

Objective

This study aimed to assess the correlation between body mass index (BMI) and plasma lipid profile levels in mild and severe COVID-19 patients.

Method

This was a prospective, observational, cohort study, conducted in a medical referral center specializing in management of COVID-19 cases. Patients were divided into two groups according to infection severity (mild and severe). Blood samples were obtained from all patients who tested positive to a PCR test for measuring biochemical and inflammatory markers such as lactate dehydrogenase, ferritin, C-reactive protein, and d-dimer, as well as lipid profile, including total cholesterol, triacylglycerols, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), which were analyzed and compared between the two groups. Pearson’s correlation was used to assess the correlation between BMI and plasma lipid profile among mild and severe cases.

Results

The levels of plasma triacylglycerols, d-dimer, lactate dehydrogenase, ferritin, and C-reactive protein with severe infection were significantly different between patients with mild and severe COVID-19 symptoms (p = 0.036, 0.03, 0.001, 0.014, and 0.006, respectively). A positive correlation between BMI and triglyceride levels was observed only in the severe infection group. However, HDL-C was negatively correlated with BMI.

Conclusion

A routine lipid profile test might help as a marker of inflammation and risk stratification in patients with COVID-19. Especially in middle- or low-income countries, the test can rapidly help clinicians to delineate prognostic measures and hence management and treatment plans for this disease as the levels of the lipid profile were correlated with the patients’ BMI and infection severity.

Transcriptional Effects of Candidate COVID-19 Treatments on Cardiac Myocytes

Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) has emerged as a major cause of morbidity and mortality worldwide, placing unprecedented pressure on healthcare. Cardiomyopathy is described in patients with severe COVID-19 and increasing evidence suggests that cardiovascular involvement portends a high mortality. To facilitate fast development of antiviral interventions, drugs initially developed to treat other diseases are currently being repurposed as COVID-19 treatments. While it has been shown that SARS-CoV-2 invades cells through the angiotensin-converting enzyme 2 receptor (ACE2), the effect of drugs currently repurposed to treat COVID-19 on the heart requires further investigation.

Methods

Human induced pluripotent stem cell-derived cardiac myocytes (hiPSC-CMs) were treated with five repurposed drugs (remdesivir, lopinavir/ritonavir, lopinavir/ritonavir/interferon beta (INF-β), hydroxychloroquine, and chloroquine) and compared with DMSO controls. Transcriptional profiling was performed to identify global changes in gene expression programs.

Results

RNA sequencing of hiPSC-CMs revealed significant changes in gene programs related to calcium handling and the endoplasmic reticulum stress response, most prominently for lopinavir/ritonavir and lopinavir/ritonavir/interferon-beta. The results of the differential gene expression analysis are available for interactive access at https://covid19drugs.jakobilab.org.

Conclusion

Transcriptional profiling in hiPSC-CMs treated with COVID-19 drugs identified unfavorable changes with lopinavir/ritonavir and lopinavir/ritonavir/INF-β in key cardiac gene programs that may negatively affect heart function.

Association of Lipid Levels With COVID-19 Infection, Disease Severity and Mortality: A Systematic Review and Meta-Analysis

Background

Coronavirus disease 2019 (COVID-19) ranges from asymptomatic infection to severe illness. Cholesterol in the host cell plasma membrane plays an important role in the SARS-CoV-2 virus entry into cells. Serum lipids, especially low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C), are in constant interaction with the lipid rafts in the host cell membranes and can modify the interaction of virus with host cells and the resultant disease severity. Recent studies on serum lipid levels and COVID-19 disease severity lack consistency.

Objectives

Our systematic review and meta-analysis compared the serum levels of total cholesterol (TC), LDL-C, HDL-C, and triglycerides (TG) between (1) COVID-19 patients vs. healthy controls; (2) severe vs. non-severe COVID-19 disease; (3) deceased vs. surviving COVID-19 patients.

Methods

PRISMA guidelines were followed. We included peer-reviewed articles on observational (case-control and cohort) studies from PubMed and Embase published from the database inception until September 1, 2021. We used random-effects meta-analysis for pooled mean-differences (pMD) in lipid levels (mg/dL) for the above groups.

Results

Among 441 articles identified, 29 articles (26 retrospective and 3 prospective cohorts), with an aggregate of 256,721 participants, were included. COVID-19 patients had lower TC (pMD-14.9, 95%CI-21.6 to -8.3) and HDL-C (pMD-6.9, 95%CI -10.2 to -3.7) levels (mg/dL). Severe COVID-19 patients had lower TC (pMD-10.4, 95%CI -18.7 to -2.2), LDL-C (pMD-4.4, 95%CI -8.4 to -0.42), and HDL-C (pMD-4.4, 95%CI -6.9 to -1.8) at admission compared to patients with non-severe disease. Deceased patients had lower TC (pMD-14.9, 95%CI -21.6 to -8.3), LDL-C (pMD-10.6, 95%CI -16.5 to -4.6) and HDL-C (pMD-2.5, 95%CI -3.9 to -1.0) at admission. TG levels did not differ based on COVID-19 severity or mortality. No publication bias was noted.

Conclusion

We demonstrated lower lipid levels in patients with COVID-19 infection and an association with disease severity and mortality. Their potential role in COVID-19 pathogenesis and their utility as prognostic factors require further investigation.

Aberrant Cholesterol Metabolic Genes Regulation in a Negative Feedback Loop Induced by an Alphacoronavirus

Porcine epidemic diarrhea virus (PEDV) is an alphacoronavirus that causes acute inflammation and severe diarrhea in newborn piglets with a high mortality rate. Given that cholesterol is required for coronavirus infection in vitro, the role of endogenous cholesterol metabolism in regulating coronavirus infection and the mechanism behind it ought to be elucidated. In this study, we found that the levels of cholesterol and bile acids were both elevated in the livers of PEDV-infected piglets compared to those of the control group. Consistently, in the livers of PEDV-infected piglets, the expression of key genes involved in cholesterol metabolism was significantly increased. Transcriptomic analysis indicated that the cholesterol homeostasis pathway was among the most enriched pathways in the livers of PEDV-infected piglets. Unexpectedly, the expression of key genes in the cholesterol metabolic pathway was downregulated at the messenger RNA (mRNA) level, but upregulated at the protein level. While the primary transcriptional factors (TFs) of cholesterol metabolism, including SREBP2 and FXR, were upregulated at both mRNA and protein levels in response to PEDV infection. Further Chromatin Immunoprecipitation Quantitative Real-time PCR (ChIP-qPCR) analysis demonstrated that the binding of these TFs to the locus of key genes in the cholesterol metabolic pathway was remarkably inhibited by PEDV infection. It was also observed that the occupancies of histone H3K27ac and H3K4me1, at the locus of the cholesterol metabolic genes HMGCR and HMGCS1, in the livers of PEDV-infected piglets, were suppressed. Together, the PEDV triggers an aberrant regulation of cholesterol metabolic genes via epigenetic inhibition of SREBP2/FXR-mediated transcription, which provides a novel antiviral target against PEDV and other coronaviruses.

HDL maturation and remodelling

Cholesterol in the circulation is mostly transported in an esterified form as a component of lipoproteins. The majority of these cholesteryl esters are produced in nascent, discoidal high density lipoproteins (HDLs) by the enzyme, lecithin:cholesterol acyltransferase (LCAT). Discoidal HDLs are discrete populations of particles that consist of a phospholipid bilayer, the hydrophobic acyl chains of which are shielded from the aqueous environment by apolipoproteins that also confer water solubility on the particles. The progressive LCAT-mediated accumulation of cholesteryl esters in discoidal HDLs generates the spherical HDLs that predominate in normal human plasma. Spherical HDLs contain a core of water insoluble, neutral lipids (cholesteryl esters and triglycerides) that is surrounded by a surface monolayer of phospholipids with which apolipoproteins associate. Although spherical HDLs all have the same basic structure, they are extremely diverse in size, composition, and function. This review is concerned with how the biogenesis of discoidal and spherical HDLs is regulated and the mechanistic basis of their size and compositional heterogeneity. Current understanding of the impact of this heterogeneity on the therapeutic potential of HDLs of varying size and composition is also addressed in the context of several disease states.

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.