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

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

Contributing to the management of viral infections through simple immunosensing of the arachidonic acid serum level.

A trendsetting direct competitive-based biosensing tool has been developed and implemented for the determination of the polyunsaturated fatty acid arachidonic acid (ARA), a highly significant biological regulator with decisive roles in viral infections. The designed methodology involves a competitive reaction between the target endogenous ARA and a biotin-ARA competitor for the recognition sites of anti-ARA antibodies covalently attached to the surface of carboxylic acid-coated magnetic microbeads (HOOC-MµBs), followed by the enzymatic label of the biotin-ARA residues with streptavidin-horseradish peroxidase (Strep-HRP) conjugate. The resulting bioconjugates were magnetically trapped onto the sensing surface of disposable screen-printed carbon transducers (SPCEs) to monitor the extent of the biorecognition reaction through amperometry. The operational functioning of the exhaustively optimized and characterized immunosensing bioplatform was highly convenient for the quantitative determination of ARA in serum samples from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2-) and respiratory syncytial virus (RSV)-infected individuals in a rapid, affordable, trustful, and sensitive manner.

Low-density lipoprotein from active SLE patients is more atherogenic to endothelial cells than low-density lipoprotein from the same patients during remission.

OBJECTIVES: SLE patients have an enhanced risk of atherosclerosis and cardiovascular disease. However, the increased prevalence of cardiovascular disease is not fully explained by traditional Framingham cardiovascular risk factors. Specific features of low-density lipoprotein (LDL) particles, other than plasma concentration, may induce accelerated atherosclerosis at early stages in these patients. Thus, we aimed to explore the impact of LDL from both active and inactive SLE patients on human aortic endothelial cells. METHODS: Human aortic endothelial cells were stimulated with the same concentration of LDL particles isolated from pooled serum that was collected from 13 SLE patients during both active and inactive states. Gene expression and cell migration assays were performed. RESULTS: Circulating LDL particles obtained from healthy volunteers and SLE patients in both remission and flare states were comparable in terms of number, cholesterol and triglyceride content, and net electric charge. Stimulation of cells with LDL from active SLE patients induced the expression of vascular cell adhesion molecule 1 (∼2.0-fold, P < 0.05), monocyte chemoattractant protein 1 (∼2.0-fold, P < 0.05) and matrix metallopeptidase 2 (∼1.6-fold, P < 0.01) compared with cells stimulated with LDL from inactive SLE patients. Additionally, LDL extracted from active patients increased cell migration in a wound-healing assay (1.4-fold, P < 0.05). CONCLUSION: Our data show that, at the same LDL concentration, LDL from active SLE patients had increased proatherogenic effects on endothelial cells compared with LDL from the same patients when in an inactive or remission state.

Gelsolin: a new biomarker of disease activity in SLE patients associated with HDL-c.

OBJECTIVES: To identify potential biomarkers of disease activity analysing the proteome of high-density lipoprotein (HDL) particles from SLE patients in clinical remission and when they develop a flare compared with a healthy control group. METHODS: Quantitative proteomic analyses of purified HDL were performed using Tandem Mass Tag isobaric tag-labelling and nanoLC-Orbitrap (nLC-MS/MS) from nine SLE patients in clinical remission when they developed a flare and from nine healthy controls (9-9-9). We verified the identified proteins by Western blot and ELISA in a cohort of 104 SLE women patients, 46 healthy women and 14 SLE patients when a flare developed. RESULTS: We found 17 proteins with a significant fold-change (>1.1) compared with the control group. In lupus patients experiencing a flare compared with those in remission, we identified four proteins with a significant fold-change (C4, Indian Hedgehog protein, S100A8 and gelsolin). Plasma gelsolin (pGSN) levels were decreased in the 104 SLE patients (176.02(74.9) mcg/l) compared with the control group (217.13(86.7) mcg/l); P=0.005 and when they developed a clinical flare (104.84(41.7) mcg/l); P=0.002). pGSN levels were associated with HDL cholesterol levels (r = 0.316, P<0.001). Antimalarial treated patients showed significant higher levels of pGSN (214.56(88.94) mcg/l regarding 170.35(66.36) mcg/l); P = 0.017. CONCLUSION: Decreased pGSN are associated with clinical disease activity in SLE patients. Antimalarial treatment and HDL cholesterol are associated with higher levels of pGSN.

Effectiveness of a network of automatically activated trained volunteers on the reduction of cardiopulmonary resuscitation manoueuvers initiation time: study protocol.

BACKGROUND: Cardiorespiratory arrest (CRA) is a health emergency with high mortality. Mortality depends on time of initiation and quality of cardiopulmonary resuscitation (CPR) manoeuvres and the use of the automated external defibrillator (AED). METHODS: The aim of the study is to determine the effectiveness of an automatically activated network of volunteers using smartwatch and smartphone applications on the reduction of time of initiation of cardiopulmonary resuscitation manoeuvres. The protocol will be developed in four phases: 1) validation of an application (App) for smartwatch that automatically generates a health alert in case of out-of-hospital cardiorespiratory arrest (OHCA); 2) training course for laypersons on CPR manoeuvres and AED use; 3) creation of a network of volunteers trained in CPR and AED use that covers our city; and 4) simulation in which the network of volunteers is automatically activated via smartphone to attend simulated OHCAs. A total of 134 health alerts will be generated; on 67 occasions the alert will be directed to the emergency health services and to the network of trained volunteers (Intervention Group) and on 67 occasions the alert will be solely directed to the emergency health services (Control Group). The arrival time of the first rescuer, category of first rescuer (emergency services versus network of volunteers), initiation time of manoeuvres and competence will be recorded. DISCUSSION: CPR training for laypersons is advised, especially for relatives and people close to patients with heart disease, to reduce time of initiation of CPR and to improve OHCA survival rates. This study aims to verify that the initiation time of CPR manoeuvres and AED use is shorter in the intervention than in the control group. TRIAL REGISTRATION: Clinicaltrials.gov ID NCT03828305 . Trial registered on February 1, 2019 (retrospective register).

Serum Levels of Arachidonic Acid, Interleukin-6, and C-Reactive Protein as Potential Indicators of Pulmonary Viral Infections: Comparative Analysis of Influenza A, Respiratory Syncytial Virus Infection, and COVID-19.

Acute respiratory tract infections, including influenza A (FluA), respiratory syncytial virus (RSV) infection, and COVID-19, can aggravate to levels requiring hospitalization, increasing morbidity and mortality. Identifying biomarkers for an accurate diagnosis and prognosis of these infections is a clinical need. We performed a cross-sectional study aimed to investigate the changes in circulating levels of arachidonic acid, interleukin 6 (IL-6), and C-reactive protein (CRP) in patients with FluA, RSV, or COVID-19, and to analyze the potential of these parameters as diagnosis or prognosis biomarkers. We analyzed serum samples from 172 FluA, 80 RSV, and 217 COVID-19 patients, and 104 healthy volunteers. Individuals with lung viral diseases showed reduced arachidonic acid concentrations compared to healthy people, with these differences being most pronounced in the order COVID-19 > RSV > FluA. Conversely, IL-6 and CRP levels were elevated across diseases, with IL-6 emerging as the most promising diagnostic biomarker, with areas under the curve (AUC) of the receiver operating characteristics plot higher than 0.85 and surpassing arachidonic acid and CRP. Moreover, IL-6 displayed notable efficacy in distinguishing between FluA patients who survived and those who did not (AUC = 0.80). These findings may provide useful tools for diagnosing and monitoring the severity of acute viral respiratory tract infections, ultimately improving patient outcomes.

Retrospective Analysis of Clostridioides difficile Infection Rates and Outcomes in Hospitalized Patients during the COVID-19 Pandemic: A Unicenter Study in Reus, Spain.

Background:Clostridioides difficile infections (CDI) vary in severity from mild diarrhea to life-threatening conditions like pseudomembranous colitis or toxic megacolon, often leading to sepsis and death. The COVID-19 pandemic prompted changes in healthcare practices, potentially affecting CDI incidence, though reported data are inconclusive. We studied factors influencing CDI incidence and outcomes at a university hospital throughout the COVID-19 pandemic years. Methods: We conducted a retrospective study on all adult hospitalized CDI cases from 1 January 2020 to 31 December 2022 in Hospital Universitari de Sant Joan in Reus. We collected demographic information, comorbid conditions, and concurrent infections. Results: While overall CDI and COVID-19 rates decreased in 2022, a notable increase in CDI infections was observed among oncological patients and those undergoing some aggressive treatments, such as colonoscopies or gastroscopies. The prevalence of comorbidities remained unmodified, and there were declines in prior gastrointestinal surgeries and proton pump inhibitor prescriptions. Factors associated with patient fatality or prolonged hospitalization included older age, cancer, chronic kidney disease, higher Charlson and McCabe indices, elevated C-reactive protein, and low albumin concentrations. Conclusions: Our study shows the evolving landscape of CDI during the COVID-19 pandemic and emphasizes the impact of delayed diagnoses and treatments exacerbated by telemedicine adoption. Identified risk factors for CDI-related mortality or prolonged hospital stays underscore the importance of targeted interventions in high-risk populations.

Differential analysis of lipoprotein and glycoprotein profiles in bacterial infections and COVID-19 using proton nuclear magnetic resonance and machine learning.

Background: We scrutinized variations in the proton nuclear magnetic resonance (1H NMR) lipoprotein and glycoprotein profiles among hospitalized individuals with infectious diseases. Methods: We obtained sera from 124 patients with COVID-19, 50 patients with catheter-related bacterial infections, and 50 healthy volunteers. Results were interpreted using machine learning. Results: COVID-19 patients had bigger and more abundant VLDL particles than the control group and higher VLDL-cholesterol and VLDL-triglyceride concentrations. Patients with bacterial infections showed similar trends, but differences often did not reach statistical significance. Both types of patients showed lower LDL-cholesterol concentrations than the controls. LDL were larger, and the number of particles was lower than that of the healthy individuals. HDL particles had decreased cholesterol and increased triglycerides. Small particles were reduced. Glycoproteins were increased in both groups of patients. All these alterations were more pronounced in COVID-19 patients than those with bacterial infections. The diagnostic accuracy of these profiles exceeded 90 % when distinguishing between healthy individuals and patients, and 85 % when differentiating between the two patient groups. Conclusion: Our findings highlight the potential of 1H NMR analysis for lipoproteins and glycoproteins as infection biomarkers. Additionally, they reveal differences between viral and bacterial infections, shedding light on an area with promising clinical significance.

Omicron XBB.1.16-Adapted Vaccine for COVID-19: Interim Immunogenicity and Safety Clinical Trial Results.

(1) Background: The global coronavirus disease 2019 vaccination adapts to protect populations from emerging variants. This communication presents interim findings from the new Omicron XBB.1.16-adapted PHH-1V81 protein-based vaccine compared to an XBB.1.5-adapted mRNA vaccine against various acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains. (2) Methods: In a Phase IIb/III pivotal trial, adults previously vaccinated with a primary scheme and at least one booster dose of an EU-approved mRNA vaccine randomly received either the PHH-1V81 or BNT162b2 XBB.1.5 vaccine booster as a single dose. The primary efficacy endpoint assessed neutralization titers against the Omicron XBB.1.16 variant at day 14. Secondary endpoints evaluated neutralization titers and cellular immunity against different variants. Safety endpoints comprised solicited reactions up to day 7 post-vaccination and serious adverse events until the cut-off date of the interim analysis. Changes in humoral responses were assessed by pseudovirion-based or virus neutralization assays. (3) Results: At the cut-off date, immunogenicity assessments included 599 participants. Both boosters elicited neutralizing antibodies against XBB.1.16, XBB.1.5, and JN.1, with PHH-1V81 inducing a higher response for all variants. The PHH-1V8 booster triggers a superior neutralizing antibody response against XBB variants compared to the mRNA vaccine. A subgroup analysis consistently revealed higher neutralizing antibody responses with PHH-1V81 across age groups, SARS-CoV-2 infection history, and the number of prior vaccination shots. A safety analysis (n = 607) at the day 14 visit revealed favorable safety profiles without any serious vaccine-related adverse events. (4) Conclusions: PHH-1V81 demonstrates superiority on humoral immunogenicity compared to the mRNA vaccine against XBB variants and non-inferiority against JN.1 with a favorable safety profile and lower reactogenicity, confirming its potential as a vaccine candidate.

Paraoxonase-1: How a xenobiotic detoxifying enzyme has become an actor in the pathophysiology of infectious diseases and cancer.

Both infectious and non-infectious diseases can share common molecular mechanisms, including oxidative stress and inflammation. External factors, such as bacterial or viral infections, excessive calorie intake, inadequate nutrients, or environmental factors, can cause metabolic disorders, resulting in an imbalance between free radical production and natural antioxidant systems. These factors may lead to the production of free radicals that can oxidize lipids, proteins, and nucleic acids, causing metabolic alterations that influence the pathogenesis of the disease. The relationship between oxidation and inflammation is crucial, as they both contribute to the development of cellular pathology. Paraoxonase 1 (PON1) is a vital enzyme in regulating these processes. PON1 is an enzyme that is bound to high-density lipoproteins and protects the organism against oxidative stress and toxic substances. It breaks down lipid peroxides in lipoproteins and cells, enhances the protection of high-density lipoproteins against different infectious agents, and is a critical component of the innate immune system. Impaired PON1 function can affect cellular homeostasis pathways and cause metabolically driven chronic inflammatory states. Therefore, understanding these relationships can help to improve treatments and identify new therapeutic targets. This review also examines the advantages and disadvantages of measuring serum PON1 levels in clinical settings, providing insight into the potential clinical use of this enzyme.

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

Background and aims: HDL particles may act to buffer host cells from excessive inflammatory mediators. The aim of this study is to investigate if the lipid profile provides a prognostic biomarker for COVID-19 outcomes. Methods: This was a prospective study of the characteristics of 125 adult COVID-19 patients with a lipid profile performed on the day of admission analyzed with regard to clinical outcomes. Results: Seventy-seven patients (61.2%) were men, with a mean age of 66.3 (15.6) years. 54.1% had bilateral pneumonia. The all-cause mortality rate during hospitalization was 20.8%. We found a direct association between more severe disease assessed by the WHO classification, admission to the ICU and death with more pronounced lymphopenia, higher levels of CRP, ferritin (p < 0.001), D-dímer and lactate dehydrogenase (LDH) all statistically significant. Lower leves of HDL-c and LDL-c were also associated with a worse WHO classification, ICU admission, and death,. HDL-c levels were inversely correlated with inflammatory markers CRP (r = -0.333; p < 0.001), ferritin (r = -0.354; p < 0.001), D-dímer (r = -0.214; p < 0.001), LDH (r = -0.209; p < 0.001. LDL-c levels were significantly associated with CRP (r = -0.320; p < 0.001) and LDH (r = -0.269; p < 0.001). ROC curves showed that HDL [AUC = 0.737(0.586-0.887), p = 0.005] and lymphocytes [AUC = 0.672(0.497-0.847], p < 0.043] had the best prognostic accuracy to predict death. In a multivariate analysis, HDL-c (ß = -0.146(0.770-0.971), p = 0.014) and urea (ß = 0.029(1.003-1.057), p = 0.027) predicted mortality. Conclusion: Hypolipidemia including HDL levels at admission identifies patients with a higher risk of death and worse clinical manifestations who may require more intensive care.

Combining Semi-Targeted Metabolomics and Machine Learning to Identify Metabolic Alterations in the Serum and Urine of Hospitalized Patients with COVID-19.

Viral infections cause metabolic dysregulation in the infected organism. The present study used metabolomics techniques and machine learning algorithms to retrospectively analyze the alterations of a broad panel of metabolites in the serum and urine of a cohort of 126 patients hospitalized with COVID-19. Results were compared with those of 50 healthy subjects and 45 COVID-19-negative patients but with bacterial infectious diseases. Metabolites were analyzed by gas chromatography coupled to quadrupole time-of-flight mass spectrometry. The main metabolites altered in the sera of COVID-19 patients were those of pentose glucuronate interconversion, ascorbate and fructose metabolism, nucleotide sugars, and nucleotide and amino acid metabolism. Alterations in serum maltose, mannonic acid, xylitol, or glyceric acid metabolites segregated positive patients from the control group with high diagnostic accuracy, while succinic acid segregated positive patients from those with other disparate infectious diseases. Increased lauric acid concentrations were associated with the severity of infection and death. Urine analyses could not discriminate between groups. Targeted metabolomics and machine learning algorithms facilitated the exploration of the metabolic alterations underlying COVID-19 infection, and to identify the potential biomarkers for the diagnosis and prognosis of the disease.

Retrospective Analysis of Vaccination Status and Predominant Viral Variants in Patients Hospitalized with COVID-19 in Reus, Spain.

SARS-CoV-2 infection in already-vaccinated individuals is still possible and may require hospitalization. The aim of the present study was to evaluate the clinical evolution of patients with COVID-19 admitted to a public hospital. The outcomes were assessed in relation to the predominant viral variant and the vaccination status. This retrospective study was performed on 1295 COVID-19-positive patients who attended a 352-bed university hospital between 2021 and 2022. Clinical variables and vaccination status were recorded. Of the patients, 799 had not been vaccinated (NV, 61.7%), 449 were partially vaccinated (PV, 34.7%), and 47 were completely vaccinated (CV, 3.6%). The mean age of the CV patients was significantly higher than that of PV and NV. Additionally, they had higher percentages of chronic diseases. The outcomes depended on age but not on vaccination status. There were 209 patients admitted during the Omicron-infection period, of whom 70 (33.5%) were NV, 135 (64.6%) were PV, and 4 (1.9%) were CV. In conclusion, correct vaccination greatly reduces the risk of acquiring severe COVID-19. Partial vaccination does not guarantee protection of the population. This highlights the need for continuous vaccination promotion with all recommended doses, while also investigating alternative treatments for those patients who do not respond to the vaccines.

Leptin and adiponectin, but not IL18, are related with insulin resistance in treated HIV-1-infected patients with lipodystrophy.

Leptin, adiponectin and IL18 are adipokines related with obesity, insulin resistance and dyslipidemia in the general population. Treated HIV-1-infected patients with lipodystrophy may develop insulin resistance and proatherogenic dyslipidemia. We assessed the relationship between plasma adipokine levels, adipokine genetics, lipodystrophy and metabolic disturbances. Plasma leptin, adiponectin and IL18 levels were assessed in 446 individuals: 282 HIV-1-infected patients treated with antiretroviral drugs (132 with lipodystrophy and 150 without) and 164 uninfected controls (UC). The LEP2410A>G, LEPRQ223R, ADIPQ276G>T, ADIPOR2-Intron5A>G and IL18-607C>A polymorphisms were validated by sequencing. Leptin levels were higher in UC than in HIV-1-infected, either with or without lipodystrophy (p<0.001 for both comparisons) and were lower in patients with lipodystrophy compared with those without lipodystrophy (p=0.006). In patients with lipodystrophy, leptin had a positive correlation with insulin and with HOMA-IR. Adiponectin levels were non-significantly different in UC and HIV-1-infected patients. Patients with lipodystrophy had lower adiponectin levels than non-lipodystrophy subjects (p<0.001). In patients with lipodystrophy, adiponectin was negatively correlated with insulin, HOMA-IR and triglycerides. Plasma IL18 levels were higher in HIV-1-infected patients compared with UC (p<0.001), and no differences were found according to the presence of lipodystrophy. In patients with lipodystrophy there was a negative correlation between IL18 levels and LDLc. Genetic analyses indicated no significant associations with lipodystrophy nor with insulin resistance or with lipid abnormalities. In conclusion, HIV-1-infected patients have reduced plasma leptin levels. This reduction is magnified in patients with lipodystrophy whose adiponectin levels were lower than that of non-lipodystrophy subjects. Plasma IL18 levels are increased in infected patients irrespective of the presence of lipodystrophy. The polymorphisms assessed are not associated with lipodystrophy or metabolic disturbances in treated HIV-1-infected patients.

Characteristics of hospitalized patients with SARS-CoV-2 infection during successive waves of the COVID-19 pandemic in a reference hospital in Spain.

Since the beginning of the COVID-19 pandemic and until September 2021, Spain suffered five waves of infection, the latter being related to the expansion of the Delta variant and with a high incidence. A vaccination campaign began in December 2020 and by the end of the fifth wave 77.3% of people had been fully vaccinated. Examining the changing dynamics of COVID-19 pandemic and its impact on outcomes among those hospitalized is essential. Our objective was to ascertain any differences in the characteristics and outcomes of hospitalized patients during that period compared to previous waves. We prospectively enrolled 200 consecutively admitted hospital patients from each wave and collected their clinical and demographic data from the medical records, including symptoms, comorbidities, deaths and whether they needed to be admitted to the Intensive Care Unit to receive assisted ventilation. We found that patients in the fifth wave were considerably younger than before, and the mortality rate fell from 22.5 to 2.0%. Admissions to the Intensive Care Unit decreased from 10 to 2%. Patients in the fifth wave had fewer comorbidities, and the age of the patients who died was higher than those who survived. Our results show a marked improvement in patient outcomes in the fifth wave, suggesting success of the vaccination campaign despite the explosion in cases due to the Delta variant.

Measurement of Plasma Galectin-3 Concentrations in Patients with Catheter Infections: A Post Hoc Retrospective Cohort Study.

Catheter-related infections (CRIs) include catheter-associated urinary tract infections (CAUTIs) and central line-associated bloodstream infections (CLABSIs), and they are associated with high morbidity, mortality, and healthcare costs. The diagnosis of a CRI is made difficult by its non-specific symptoms. We aimed to investigate the factors influencing the plasma concentration of galectin-3 in catheter-bearing patients and to explore its potential usefulness as an index for CRIs. Circulating the concentrations of galectin-3, we measured the chemokine (C-C) motif ligand 2, procalcitonin, and C-reactive protein in 110 patients with a central catheter, in 165 patients with a urinary catheter, and in 72 control subjects. Catheter-bearing patients had higher concentrations (p < 0.001) of galectin-3 than the control group [central catheter: 19.1 (14.0−23.4) µg/L; urinary catheter: 17.1 (12.7−25.4) µg/L; control group: 6.1 (5.0−8.7) µg/L]. We identified chronic kidney disease as an independent determinant of galectin-3 concentrations in patients with a central catheter, and serum creatinine, cardiovascular disease, and number of days that the catheter was indwelling were identified as determinants in urinary catheter patients. We found that measuring galectin-3 concentrations in urinary catheter patients with a CRI was more accurate for diagnosis than the other parameters. We conclude that the measurement of galectin-3 concentration may be useful for assessing the inflammatory status of catheter-bearing patients and may contribute to the diagnosis of CRIs in those with a urinary catheter.

Machine learning and semi-targeted lipidomics identify distinct serum lipid signatures in hospitalized COVID-19-positive and COVID-19-negative patients.

BACKGROUND: Lipids are involved in the interaction between viral infection and the host metabolic and immunological responses. Several studies comparing the lipidome of COVID-19-positive hospitalized patients vs. healthy subjects have already been reported. It is largely unknown, however, whether these differences are specific to this disease. The present study compared the lipidomic signature of hospitalized COVID-19-positive patients with that of healthy subjects, as well as with COVID-19-negative patients hospitalized for other infectious/inflammatory diseases. METHODS: We analyzed the lipidomic signature of 126 COVID-19-positive patients, 45 COVID-19-negative patients hospitalized with other infectious/inflammatory diseases and 50 healthy volunteers. A semi-targeted lipidomics analysis was performed using liquid chromatography coupled to mass spectrometry. Two-hundred and eighty-three lipid species were identified and quantified. Results were interpreted by machine learning tools. RESULTS: We identified acylcarnitines, lysophosphatidylethanolamines, arachidonic acid and oxylipins as the most altered species in COVID-19-positive patients compared to healthy volunteers. However, we found similar alterations in COVID-19-negative patients who had other causes of inflammation. Conversely, lysophosphatidylcholine 22:6-sn2, phosphatidylcholine 36:1 and secondary bile acids were the parameters that had the greatest capacity to discriminate between COVID-19-positive and COVID-19-negative patients. CONCLUSION: This study shows that COVID-19 infection shares many lipid alterations with other infectious/inflammatory diseases, and which differentiate them from the healthy population. The most notable alterations were observed in oxylipins, while alterations in bile acids and glycerophospholipis best distinguished between COVID-19-positive and COVID-19-negative patients. Our results highlight the value of integrating lipidomics with machine learning algorithms to explore the pathophysiology of COVID-19 and, consequently, improve clinical decision making.

Usefulness of the Measurement of Serum Paraoxonase-1 Arylesterase Activity in the Diagnoses of COVID-19.

The development of inexpensive, fast, and reliable screening tests for COVID-19 is, as yet, an unmet need. The present study was aimed at evaluating the usefulness of serum arylesterase activity of paraoxonase-1 (PON1) measurement as a screening test in patients with different severity levels of COVID-19 infection. We included 615 COVID-19-positive patients who were classified as asymptomatic, mildly symptomatic, severely symptomatic, or fatally symptomatic. Results were compared with 50 healthy volunteers, 330 patients with cancer, and 343 with morbid obesity. Results showed PON1 activity greatly decreased in COVID-19 compared to healthy volunteers; a receiver operating characteristics plot showed a high diagnostic accuracy. The degree of COVID-19 severity did not influence PON1 levels. Our results indicated that PON1 determination was efficient for disease diagnosis, but not for prognosis. Furthermore, patients with obesity or cancer presented alterations similar to those of COVID-19 patients. As such, elevated levels of PON1 indicate the absence of COVID-19, but low levels may be present in various other chronic diseases. The assay is fast and inexpensive. We suggest that PON1 measurement could be used as an initial, high cut-off point screening method, while lower values should be confirmed with the more expensive nucleic acid amplification test.

Clinical Performance of Paraoxonase-1-Related Variables and Novel Markers of Inflammation in Coronavirus Disease-19. A Machine Learning Approach.

SARS-CoV-2 infection produces a response of the innate immune system causing oxidative stress and a strong inflammatory reaction termed 'cytokine storm' that is one of the leading causes of death. Paraoxonase-1 (PON1) protects against oxidative stress by hydrolyzing lipoperoxides. Alterations in PON1 activity have been associated with pro-inflammatory mediators such as the chemokine (C-C motif) ligand 2 (CCL2), and the glycoprotein galectin-3. We aimed to investigate the alterations in the circulating levels of PON1, CCL2, and galectin-3 in 126 patients with COVID-19 and their interactions with clinical variables and analytical parameters. A machine learning approach was used to identify predictive markers of the disease. For comparisons, we recruited 45 COVID-19 negative patients and 50 healthy individuals. Our approach identified a synergy between oxidative stress, inflammation, and fibrogenesis in positive patients that is not observed in negative patients. PON1 activity was the parameter with the greatest power to discriminate between patients who were either positive or negative for COVID-19, while their levels of CCL2 and galectin-3 were similar. We suggest that the measurement of serum PON1 activity may be a useful marker for the diagnosis of COVID-19.

Characterization of the LPS and 3OHFA Contents in the Lipoprotein Fractions and Lipoprotein Particles of Healthy Men.

Atherosclerosis is a chronic inflammatory disease that is caused by the accumulation of LDL particles in the intima, causing the activation of immune cells and triggering an inflammatory response. LPS is a potent activator of the innate immune response and it can be transported by lipoproteins. Since humans are much more sensitive to LPS than other mammals, and very low amounts of LPS can elicit an immune response, the aim of this study is to characterize the distribution of LPS and its immunogenic portion (3OHFAs) among lipoprotein types of healthy men. We separated lipoprotein fractions by ultracentrifugation and the amount of each 3OHFA was measured by MS in each lipoprotein fraction to calculate LPS concentration. Lipoprotein particle concentration was measured by NMR. LDL and HDL fractions transported the highest concentration of LPS (35.7% and 31.5%, respectively), but VLDL particles carried more LPS molecules per particle (0.55 molecules/particle) than LDL or HDL (p < 0.01). The distribution of LPS and all 3OHFAs among lipoprotein fractions showed high interindividual variability, suggesting that they may be studied as a potential biomarker. This may help understand the role of LPS in atherosclerosis in those cases where the disease cannot be explained by traditional risk factors.