Glycosylation of Acute Phase Proteins: A Promising Disease Biomarker

Common and Novel Markers for Measuring Inflammation and Oxidative Stress Ex Vivo in Research and Clinical Practice-Which to Use Regarding Disease Outcomes?

Many chronic conditions such as cancer, chronic obstructive pulmonary disease, type-2 diabetes, obesity, peripheral/coronary artery disease and auto-immune diseases are associated with low-grade inflammation. Closely related to inflammation is oxidative stress (OS), which can be either causal or secondary to inflammation. While a low level of OS is physiological, chronically increased OS is deleterious. Therefore, valid biomarkers of these signalling pathways may enable detection and following progression of OS/inflammation as well as to evaluate treatment efficacy. Such biomarkers should be stable and obtainable through non-invasive methods and their determination should be affordable and easy. The most frequently used inflammatory markers include acute-phase proteins, essentially CRP, serum amyloid A, fibrinogen and procalcitonin, and cytokines, predominantly TNFα, interleukins 1β, 6, 8, 10 and 12 and their receptors and IFNγ. Some cytokines appear to be disease-specific. Conversely, OS-being ubiquitous-and its biomarkers appear less disease or tissue-specific. These include lipid peroxidation products, e.g., F2-isoprostanes and malondialdehyde, DNA breakdown products (e.g., 8-OH-dG), protein adducts (e.g., carbonylated proteins), or antioxidant status. More novel markers include also -omics related ones, as well as non-invasive, questionnaire-based measures, such as the dietary inflammatory-index (DII), but their link to biological responses may be variable. Nevertheless, many of these markers have been clearly related to a number of diseases. However, their use in clinical practice is often limited, due to lacking analytical or clinical validation, or technical challenges. In this review, we strive to highlight frequently employed and useful markers of inflammation-related OS, including novel promising markers.

Glycoproteins as diagnostic and prognostic biomarkers for neurodegenerative diseases: A glycoproteomic approach

Neurodegenerative diseases (NDs) are incurable and can develop progressively debilitating disorders, including dementia and ataxias. Alzheimer's disease and Parkinson's disease are the most common NDs that mainly affect the elderly people. There is an urgent need to develop new diagnostic tools so that patients can be accurately stratified at an early stage. As a common post-translational modification, protein glycosylation plays a key role in physiological and pathological processes. The abnormal changes in glycosylation are associated with the altered biological pathways in NDs. The pathogenesis-related proteins, like amyloid-β and microtubule-associated protein tau, have altered glycosylation. Importantly, specific glycosylation changes in cerebrospinal fluid, blood and urine are valuable for revealing neurodegeneration in the early stages. This review describes the emerging biomarkers based on glycoproteomics in NDs, highlighting the potential applications of glycoprotein biomarkers in the early detection of diseases, monitoring of the disease progression, and measurement of the therapeutic responses. The mass spectrometry-based strategies for characterizing glycoprotein biomarkers are also introduced.

Mass spectrometry-based glycomic profiling of the total IgG and total proteome N-glycomes isolated from follicular fluid

Couples with infertility issues have been assisted by in vitro fertilization reproduction technologies with high success rates of 50-80%. However, complications associated with ovarian stimulation remain, such as ovarian hyperstimulation. Oocyte quality is a significant factor impacting the outcome of in vitro fertilization procedures, but other processes are also critical for fertilization success. Increasing evidence points to aberrant inflammation as one of these critical processes reflected in molecular changes, including glycosylation of proteins. Here we report results from a MALDI-TOF-MS-based glycomic profiling of the total IgG and total proteome N-glycomes isolated from the follicular fluid obtained from patients undergoing fertilization through either (1) assisted reproduction by modified natural cycle or (2) controlled ovarian stimulation (GnRH antagonist, GnRH Ant) protocols. Significant inflammatory-related differences between analyzed N-glycomes were observed from samples and correlated with the ovarian stimulation protocol used in patients.

Title: Human Serum/Plasma Glycoprotein Analysis by 1H-NMR, an Emerging Method of Inflammatory Assessment

Several studies suggest that variations in the concentration of plasma glycoproteins can influence cellular changes in a large number of diseases. In recent years, proton nuclear magnetic resonance (1H-NMR) has played a major role as an analytical tool for serum and plasma samples. In recent years, there is an increasing interest in the characterization of glycoproteins through 1H-NMR in order to search for reliable and robust biomarkers of disease. The objective of this review was to examine the existing studies in the literature related to the study of glycoproteins from an analytical and clinical point of view. There are currently several techniques to characterize circulating glycoproteins in serum or plasma, but in this review, we focus on 1H-NMR due to its great robustness and recent interest in its translation to the clinical setting. In fact, there is already a marker in H-NMR representing the acetyl groups of the glycoproteins, GlycA, which has been increasingly studied in clinical studies. A broad search of the literature was performed showing a general consensus that GlycA is a robust marker of systemic inflammation. The results also suggested that GlycA better captures systemic inflammation even more than C-reactive protein (CRP), a widely used classical inflammatory marker. The applications reviewed here demonstrated that GlycA was potentially a key biomarker in a wide range of diseases such as cancer, metabolic diseases, cardiovascular risk, and chronic inflammatory diseases among others. The profiling of glycoproteins through 1H-NMR launches an encouraging new paradigm for its future incorporation in clinical diagnosis.

Quantitative N-glycoproteomics reveals altered glycosylation levels of various plasma proteins in bloodstream infected patients

Bloodstream infections are associated with high morbidity and mortality with rates varying from 10-25% and higher. Appropriate and timely onset of antibiotic therapy influences the prognosis of these patients. It requires the diagnostic accuracy which is not afforded by current gold standards such as blood culture. Moreover, the time from blood sampling to blood culture results is a key determinant of reducing mortality. No established biomarkers exist which can differentiate bloodstream infections from other systemic inflammatory conditions. This calls for studies on biomarkers potential of molecular profiling of plasma as it is affected most by the molecular changes accompanying bloodstream infections. N-glycosylation is a post-translational modification which is very sensitive to changes in physiology. Here we have performed targeted quantitative N-glycoproteomics from plasma samples of patients with confirmed positive blood culture together with age and sex matched febrile controls with negative blood culture reports. Three hundred and sixty eight potential N-glycopeptides were quantified by mass spectrometry and 149 were further selected for identification. Twenty four N-glycopeptides were identified with high confidence together with elucidation of the peptide sequence, N-glycosylation site, glycan composition and proposed glycan structures. Principal component analysis, orthogonal projections to latent structures-discriminant analysis (S-Plot) and self-organizing maps clustering among other statistical methods were employed to analyze the data. These methods gave us clear separation of the two patient classes. We propose high-confidence N-glycopeptides which have the power to separate the bloodstream infections from blood culture negative febrile patients and shed light on host response during bacteremia. Data are available via ProteomeXchange with identifier PXD009048.

Improving Blood Plasma Glycoproteome Coverage by Coupling Ultracentrifugation Fractionation to Electrostatic Repulsion-Hydrophilic Interaction Chromatography Enrichment

Blood plasma is considered to be an excellent source of disease biomarkers because it contains proteins, lipids, metabolites, cell, and cell-derived extracellular vesicles from different cellular origins including diseased tissues. Most secretory and membranous proteins that can be found in plasma are glycoproteins; therefore, the plasma glycoproteome is one of the major subproteomes that is highly enriched with disease biomarkers. As a result, the glycoproteome has attracted much attention in clinical proteomic research. The modification of proteins with glycans regulates a wide range of functions in biology, but profiling plasma glycoproteins on a global scale has been hampered by the presence of low stoichiometry of glycoproteins in a complex high abundance plasma proteome background and lack of effective analytical technique. This study aims to improve plasma glycoproteome coverage using pig plasma as a model sample with a two-step strategy. The first step involves fractionation of the plasma proteins using ultracentrifugation into supernatant and pellet that is believed to contain low abundant glycoproteins. In the second step, further enrichment of glycopeptides was achieved in both fractions by adopting electrostatic repulsion hydrophilic interaction chromatography (ERLIC) coupled to tandem mass spectrometry (LC-MS/MS) analysis. The coverage of enriched glycoproteins in supernatant, pellet, and whole plasma sample as control was compared. Using this simple sample fractionation approach by ultracentrifugation and further ERLIC enrichment technique, sample complexity was reduced and glycoproteome coverage was significantly enhanced in supernatant and pellet fractions (by >50%) compared with whole plasma sample. This study showed that when ultracentrifugation is coupled to ERLIC glycopeptides enrichment and glycoproteome identification are significantly improved. This study demonstrates the combination of ultracentrifugation and ERLIC as a useful method for discovering plasma glycoprotein disease biomarkers.