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

Proteome analysis develops novel plasma proteins classifier in predicting the mortality of COVID-19

COVID-19 has been a global concern for 3 years, however, consecutive plasma protein changes in the disease course are currently unclear. Setting the mortality within 28 days of admission as the main clinical outcome, plasma samples were collected from patients in discovery and independent validation groups at different time points during the disease course. The whole patients were divided into death and survival groups according to their clinical outcomes. Proteomics and pathway/network analyses were used to find the differentially expressed proteins and pathways. Then, we used machine learning to develop a protein classifier which can predict the clinical outcomes of the patients with COVID-19 and help identify the high-risk patients. Finally, a classifier including C-reactive protein, extracellular matrix protein 1, insulin-like growth factor-binding protein complex acid labile subunit, E3 ubiquitin-protein ligase HECW1 and phosphatidylcholine-sterol acyltransferase was determined. The prediction value of the model was verified with an independent patient cohort. This novel model can realize early prediction of 28-day mortality of patients with COVID-19, with the area under curve 0.88 in discovery group and 0.80 in validation group, superior to 4C mortality and E-CURB65 scores. In total, this work revealed a potential protein classifier which can assist in predicting the outcomes of COVID-19 patients and providing new diagnostic directions.

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.

Cholesterol transport and beyond: Illuminating the versatile functions of HDL apolipoproteins through structural insights and functional implications

High-density lipoproteins (HDLs) play a vital role in lipid metabolism and cardiovascular health, as they are intricately involved in cholesterol transport and inflammation modulation. The proteome of HDL particles is indeed complex and distinct from other components in the bloodstream. Proteomics studies have identified nearly 285 different proteins associated with HDL; however, this review focuses more on the 15 or so traditionally named "apo" lipoproteins. Important lipid metabolizing enzymes closely working with the apolipoproteins are also discussed. Apolipoproteins stand out for their integral role in HDL stability, structure, function, and metabolism. The unique structure and functions of each apolipoprotein influence important processes such as inflammation regulation and lipid metabolism. These interactions also shape the stability and performance of HDL particles. HDLs apolipoproteins have multifaceted roles beyond cardiovascular diseases (CVDs) and are involved in various physiological processes and disease states. Therefore, a detailed exploration of these apolipoproteins can offer valuable insights into potential diagnostic markers and therapeutic targets. This comprehensive review article aims to provide an in-depth understanding of HDL apolipoproteins, highlighting their distinct structures, functions, and contributions to various physiological processes. Exploiting this knowledge holds great potential for improving HDL function, enhancing cholesterol efflux, and modulating inflammatory processes, ultimately benefiting individuals by limiting the risks associated with CVDs and other inflammation-based pathologies. Understanding the nature of all 15 apolipoproteins expands our knowledge of HDL metabolism, sheds light on their pathological implications, and paves the way for advancements in the diagnosis, prevention, and treatment of lipid and inflammatory-related disorders.

Serum Clusterin Concentration and Its Glycosylation Changes as Potential New Diagnostic Markers of SARS-CoV-2 Infection and Recovery Process

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. Glycoprotein clusterin (CLU) has many functions such as phagocyte recruitment, complement system inhibition, apoptosis inhibition, hormone and lipid transport, as well as in the immune response. The study aimed to assess the changes in CLU concentrations and the profile and degree of CLU glycosylation between patients with severe COVID-19, convalescents, and healthy subjects (control). The profile and degree of serum CLU N-glycosylation were analyzed using lectin-ELISA with specific lectins. CLU concentrations were significantly lower and relative reactivities of CLU glycans with SNA (Sambucus nigra agglutinin) were significantly higher in severe COVID-19 patients in comparison to convalescents and the control group. The relative reactivities of CLU glycans with MAA (Maackia amurensis agglutinin), together with relative reactivity with LCA (Lens culinaris agglutinin), were also significantly higher in patients with severe COVID-19 than in convalescents and the control group, but they also significantly differed between convalescents and control. The development of acute inflammation in the course of severe COVID-19 is associated with a decrease in CLU concentration, accompanied by an increase in the expression of α2,3-linked sialic acid, and core fucose. Both of these parameters can be included as useful glycomarkers differentiating patients with severe COVID-19 from convalescents and the control group, as well as convalescents and healthy subjects.

Proteomics Clustering Research of ITRAQ Markers in Plasma of AIDS Patients with Different Chinese Medicine Syndromes

Background

We aimed to distinguish the different Chinese medicine (CM) syndromes of acquired immune deficiency syndrome (AIDS) patients at the proteomics level.

Methods

We collected AIDS patients diagnosed with different CM syndromes from Weishi County, Kaifeng City, Henan Province, China, including Qi-deficiency syndrome (named QD group) and dampness-heat syndrome (named DH group). Healthy people were collected as controls from Weishi County, Kaifeng city, Henan Province, China. The plasma from three groups were labeled with ITRAQ, LC/MC was used for protein quantitative analysis. Finally, sequence search and cluster analysis were performed.

Results

Overall, 27 different proteins were found. Three proteins were up-regulated and 2 proteins down-regulated in the QD group, 11 proteins up-regulated and 13 proteins down-regulated in the DH group. Compared with DH group, there were 7 different proteins in QD group, among which 5 proteins were down-regulated and 2 proteins were up-regulated. When the target protein of DH group was up-regulated, the protein of HC group was down-regulated correspondingly.

Conclusion

The significance analysis and clustering of protein results showed that DH group was significantly different from QD group and HC group at the protein level (P<0.05). However, the QD group could not be effectively distinguished from the HC group. AAT, PF4, C-reactive protein and c4bp may be used as potential biomarkers in DH group. Mass spectrometry based on feature selection can be used to classify different CM syndromes.

ApoA1, ApoB, ApoA1/B for Pathogenic Prediction of Chronic Obstructive Pulmonary Disease Complicated by Acute Lower Respiratory Tract Infection: A Cross-Sectional Study

Purpose

To investigate the value of apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and ApoA1/B ratio in pathogenic diagnosis of chronic obstructive pulmonary disease (COPD) complicated by acute lower respiratory tract infection, assisting comprehensive disease assessment.

Patients and Methods

The study enrolled 171 COPD patients with acute lower respiratory tract infections, 35 COPD patients without acute lower respiratory tract infections, and 41 healthy controls. Correlation analysis and binary logistic regression were used to assess the roles of various factors in COPD with acute lower respiratory tract infections. Receiver operating characteristic (ROC) curves were plotted and area under curves (AUC) values were calculated to evaluate the predictive performance.

Results

Infections were the cause of alterations in ApoA1, ApoB and ApoA1/B index. In correlation analysis for pathogenic diagnosis of COPD complicated by acute lower respiratory infections, age, ApoA1, ApoA1/B ratio, lymphocyte count (LYMPH), neutrophil count (NEUT), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and endotoxin were significantly correlated. For predicting COPD complicated by acute lower respiratory tract bacterial infection, ApoA1 had the highest area under the ROC curve (AUC: 0.889), with sensitivity and specificity of 82.9% and 83.9%, respectively. The combination of NEUT and ApoA1 improved the prediction efficacy (AUC: 0.909; sensitivity/specificity: 85.1%/85.7%).

Conclusion

ApoA1, ApoB, and ApoA1/B ratio are good indicators for predicting pathogens in COPD complicated by acute lower respiratory tract infection, especially ApoA1 which has high predictive value.