Glycoprotein Profile Measured by a H-Nuclear Magnetic Resonance Based on Approach in Patients with Diabetes: A New Robust Method to Assess Inflammation.

Patients with type 2 diabetes mellitus (T2DM) and atherogenic dyslipidemia (AD) are at higher risk of developing cardiovascular diseases (CVDs), so an interest in discovering inflammation biomarkers as indicators of processes related to CVD progression is increasing. This study aims (a) to characterize the plasma glycoprotein profile of a cohort of 504 participants, including patients with and without T2DM and/or AD and controls, and (b) to study the associations between the glycoprotein profile and other lipid and clinical variables in these populations. We characterized the plasma glycoprotein profiles by using H-NMR.

Acute-phase glycoprotein profile responses to different oral macronutrient challenges: Influence of sex, functional hyperandrogenism and obesity.

Acute-phase glycoprotein H-NMR spectroscopy profiles serve as surrogate markers of chronic inflammation in metabolic disorders such as obesity, diabetes and polycystic ovary syndrome (PCOS). The latter is associated with increased height-to-width (H/W) ratios of GlycA and GlycB after fasting, but not to glycoprotein areas, regardless of obesity. We studied the responses to separate glucose, lipid and protein oral challenges of five glycoprotein variables (GlycA, GlycB, and GlycF areas and the GlycA and GlycB H/W ratios) in 17 women with PCOS, 17 control women, and 19 healthy men.

Title: Human Serum/Plasma Glycoprotein Analysis by H-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 (H-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 H-NMR in order to search for reliable and robust biomarkers of disease.

Glycoprotein A and B Height-to-Width Ratios as Obesity-Independent Novel Biomarkers of Low-Grade Chronic Inflammation in Women with Polycystic Ovary Syndrome (PCOS).

The polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting women in reproductive age. Obesity and low-grade chronic inflammation are frequently associated with PCOS. Recently, proton nuclear magnetic resonance (H-NMR)-derived glycoprotein profiles have emerged as potential biomarkers that reflect systemic inflammation in type 2 diabetes, obesity, and other pathological processes.

Characterization of H NMR Plasma Glycoproteins as a New Strategy To Identify Inflammatory Patterns in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease associated with a high index of morbidity and mortality from cardiovascular diseases. We used H NMR to characterize the plasma glycoprotein and lipoprotein profiles of a cohort of patients with RA ( n = 210) versus healthy individuals ( n = 203) to associate them with the RA disease and its severity. Using H NMR, we developed a line-shape method to characterize the two peaks associated with glycoproteins (GlycA and GlycB) and its derived variables: areas of GlycB (Area GlycB) and GlycA (Area GlycA), shape factors of these two peaks (H/W = height/width), and the distance between them (Distance GlycB-GlycA).

Metabolic profiling and targeted lipidomics reveals a disturbed lipid profile in mothers and fetuses with intrauterine growth restriction.

Fetal growth may be impaired by poor placental function or maternal conditions, each of which can influence the transfer of nutrients and oxygen from the mother to the developing fetus. Large-scale studies of metabolites (metabolomics) are key to understand cellular metabolism and pathophysiology of human conditions. Herein, maternal and cord blood plasma samples were used for NMR-based metabolic fingerprinting and profiling, including analysis of the enrichment of circulating lipid classes and subclasses, as well as the number of sub-fraction particles and their size.