Proteomic analysis detects deregulated reverse cholesterol transport in human subjects with ST-segment elevation myocardial infarction

Application of proteomics for novel drug discovery and risk prediction optimisation in stroke and myocardial infarction: a review of in-human studies

The use of proteomics in human studies investigating stroke and myocardial infarction (MI) has been increasing, prompting a review of the literature. This revealed proteinaceous biomarkers of stroke from thrombi, brain tissue, cells, and particles, some of which cross the blood-brain barrier (BBB). Several proteins were also implicated in coronary artery disease (CAD), which often underlies MI, cholesterol transportation, and inflammation. Furthermore, the platelet proteome revealed itself as a potential therapeutic target, along with differentially expressed proteins associated with MI progression. Moreover, proteomic data enhanced the performance of conventional risk scores and causal protein discovery has improved interventions and drug development for patients with MI and other conditions. These findings suggest that proteomics holds much promise for future stroke and MI research.

Identification of ABCA5 among ATP-Binding Cassette Transporter Family as a New Biomarker for Colorectal Cancer

Background

The increasing incidence and mortality of colorectal cancer (CRC) urgently requires updated biomarkers. The ABC transporter family is a widespread family of membrane-bound proteins involved in the transportation of substrates associated with ATP hydrolysis, including metabolites, amino acids, peptides and proteins, sterols and lipids, organic and inorganic ions, sugars, metals, and drugs. They play an important role in the maintenance of homeostasis in the body.

Purpose

This study aims to search for new markers in the ABC transporter gene family for diagnostic and prognostic purposes through data mining of The Cancer Genome Atlas (TCGA) and GEO (Gene Expression Omnibus) datasets.

Methods

A total of 980 samples, including 684 CRC patients and 296 controls from five different datasets, were included for analysis. The construction of the PPI (protein-protein interaction) network and pathway analysis were performed in STRING database and DAVID (database for annotation, visualization, and integrated discovery), respectively. In addition, GSEA (gene set enrichment analysis) and WGCNA (weighted gene co-expression network analysis) were also used for functional analysis.

Results

After several rounds of screening and validation, only the ABCB5 gene was retained among the 49 genes.

Conclusions

The results demonstrated that ABCA5 expression is reduced in CRC and patients with high ABCA5 expression have better OS, which can provide guidance for better management and treatment of CRC in the future.

Proteomic Studies of Blood and Vascular Wall in Atherosclerosis

The review is devoted to the analysis of literature data related to the role of proteomic studies in the study of atherosclerotic cardiovascular diseases. Diagnosis of patients with atherosclerotic plaques before clinical manifestations is an arduous task. The review presents the results of research on the new proteomic potential biomarkers of coronary heart disease, coronary atherosclerosis, acute coronary syndrome, myocardial infarction, carotid artery atherosclerosis. Also, the analysis of literature data on proteomic studies of the vascular wall was carried out. To assess the involvement of proteins in the pathological process of atherosclerosis, it is important to investigate the specific relationships between proteins in the arteries, expression and concentration of proteins. The development of proteomic technologies has made it possible to analyse the number of proteins associated with the development of the disease. Analysis of the proteomic profile of the vascular wall in atherosclerosis can help to detect possible diagnostically significant protein structures or potential biomarkers of the disease and develop novel approaches to the diagnosis of atherosclerosis and its complications.

PGLYRP2 as a novel biomarker for the activity and lipid metabolism of systemic lupus erythematosus

Background

To assess the value of peptidoglycan recognition protein 2 (PGLYRP2) in assessing the disease activity and lipid metabolism in patients with systemic lupus erythematosus (SLE).

Methods

SLE patients with stable disease (n = 15), active lupus nephritis (LN) (n = 15) and neuropsychiatric systemic lupus erythematosus (NP-SLE) (n = 15) admitted to Northern Jiangsu People’s Hospital (Jiangsu, China) in 2019–2020 were recruited. In addition, volunteers with matched age and sex (n = 15) were enrolled as controls. The level of PGLYRP2 in the serum and its expression in peripheral blood mononuclear cells (PBMCs) were measured. The link between PGLYRP2 level and clinical parameters (including lipid profile) was described.

Results

Serum PGLYRP2 level in SLE cases exceeded that in healthy volunteers (3938.56 ± 576.07 pg/mL), and significantly higher in active LN (5152.93 ± 446.13 pg/mL) and NP-SLE patients (5141.52 ± 579.61 pg/mL). As shown by quantitative real-time PCR results, the expression of PGLYRP2 in PBMCs of SLE patients with active LN and NP-SLE surpassed that in healthy volunteers (P < 0.01). Receiver operating characteristic (ROC) curves demonstrated that PGLYRP2 was capable of distinguishing stable SLE from active LN (AUC = 0.841, 95%CI = 0.722–0.960, P = 0.000). PGLYRP2 level positively correlated with SLEDAI of SLE patients (r = 0.5783, P < 0.01). Moreover, its level varied with serological and renal function parameters (complement 3, complement 4, estimated glomerular filtration rate and 24-h urine protein) and immunoglobulin A (IgA) of SLE. A potential correlation between PGLYRP2 level and lipid profile (HLD-c, Apo-A1 and Apo B/A1) was determined in SLE patients. The linear regression analysis indicated SLEDAI as an independent factor of PGLYRP2 level, with a positive correlation in between (P < 0.05).

Conclusions

Serum PGLYRP2 level significantly increases in SLE patients, and is positively correlated to SLEDAI. Moreover, serum PGLYRP2 level is correlated with renal damage parameters and the abnormal lipid profile of SLE. PGLYRP2 could be used to predict SLE activity, dyslipidemia and cardiovascular disease risks in SLE patients.