GlycA is a Novel Marker of Inflammation Among Non-Critically Ill Hospitalized Patients with Type 2 Diabetes

A, Sarma DK, Verma V, Nagpal R, Mohania D, Tiwari R, Kumar M. Deciphering the complex interplay of risk factors in type 2 diabetes mellitus: A comprehensive review

The complex and multidimensional landscape of type 2 diabetes mellitus (T2D) is a major global concern. Despite several years of extensive research, the precise underlying causes of T2D remain elusive, but evidence suggests that it is influenced by a myriad of interconnected risk factors such as epigenetics, genetics, gut microbiome, environmental factors, organelle stress, and dietary habits. The number of factors influencing the pathogenesis is increasing day by day which worsens the scenario; meanwhile, the interconnections shoot up the frame. By gaining deeper insights into the contributing factors, we may pave the way for the development of personalized medicine, which could unlock more precise and impactful treatment pathways for individuals with T2D. This review summarizes the state of knowledge about T2D pathogenesis, focusing on the interplay between various risk factors and their implications for future therapeutic strategies. Understanding these factors could lead to tailored treatments targeting specific risk factors and inform prevention efforts on a population level, ultimately improving outcomes for individuals with T2D and reducing its burden globally.

Glycoprotein Acetyls Associate With Intraglomerular Hemodynamic Dysfunction, Albuminuria, Central Adiposity, and Insulin Resistance in Youth With Type 1 Diabetes

OBJECTIVES

Glycoprotein acetyls (GlycA's) are biomarkers of systemic inflammation and cardiovascular disease, yet little is known about their role in type 1 diabetes (T1D). In this study we examined the associations among GlycA's, central adiposity, insulin resistance, and early kidney injury in youth with T1D.

METHODS

Glomerular filtration rate and renal plasma flow by iohexol and p-aminohippurate clearance, urine albumin-to-creatinine ratio (UACR), central adiposity by dual-energy x-ray absorptiometry, and estimated insulin sensitivity were assessed in 50 youth with T1D (16±3.0 years of age, 50% female, glycated hemoglobin 8.7%±1.3%, T1D duration 5.7±2.6 years). Concentrations of GlycA were quantified by targeted nuclear magnetic resonance spectroscopy. Correlation and multivariable linear regression analyses were performed.

RESULTS

GlycA's were higher in girls vs boys (1.05±0.26 vs 0.84±0.15 mmol/L, p=0.001) and in participants living with overweight/obesity vs normal weight (1.12±0.23 vs 0.87±0.20 mmol/L, p=0.0004). GlycA's correlated positively with estimated intraglomerular pressure (r=0.52, p=0.001), UACR (r=0.53, p<0.0001), and trunk mass (r=0.45, p=0.001), and inversely with estimated insulin sensitivity (r=-0.36, p=0.01). All relationships remained significant after adjustment for age, sex, and glycated hemoglobin.

CONCLUSIONS

As biomarkers of inflammation, GlycA's were higher in girls and those with overweight or obese body habitus in T1D. GlycA's associated with parameters of early kidney dysfunction, central adiposity, and insulin resistance.

Towards clinical application of GlycA and GlycB for early detection of inflammation associated with (pre)diabetes and cardiovascular disease: recent evidence and updates

Cardiometabolic diseases are associated with low-grade inflammation early in life and persists into old age. The long latency period presents opportunities for early detection, lifestyle modification and intervention. However, the performance of conventional biomarker assays to detect low-grade inflammation has been variable, particularly for early-stage cardiometabolic disorder including prediabetes and subclinical atherosclerotic vascular inflammation. During the last decade, the application of nuclear magnetic resonance (NMR) spectroscopy for metabolic profiling of biofluids in translational and epidemiological research has advanced to a stage approaching clinical application. Proton (1H)-NMR profiling induces no destructible physical changes to specimens, and generates quantitative signals from deconvoluted spectra that are highly repeatable and reproducible. Apart from quantitative analysis of amino acids, lipids/lipoproteins, metabolic intermediates and small proteins, 1H-NMR technology is unique in being able to detect composite signals of acute-phase and low-grade inflammation indicated by glycosylated acetyls (GlycA) and N-acetylneuraminic acid (sialic acid) moieties (GlycB). Different from conventional immunoassays that target epitopes and are susceptible to conformational variation in protein structure and binding, GlycA and GlycB signals are stable over time, and maybe complementary as well as superior to high-sensitivity C-reactive protein and other inflammatory cytokines. Here we review the physicochemical principles behind 1H-NMR profiling of GlycA and GlycB, and the available evidence supporting their potential clinical application for the prediction of incident (pre)diabetes, cardiovascular disease, and adverse outcomes.

Quantitative Serum NMR Spectroscopy Stratifies COVID-19 Patients and Sheds Light on Interfaces of Host Metabolism and the Immune Response with Cytokines and Clinical Parameters

The complex manifestations of COVID-19 are still not fully decoded on the molecular level. We combined quantitative the nuclear magnetic resonance (NMR) spectroscopy serum analysis of metabolites, lipoproteins and inflammation markers with clinical parameters and a targeted cytokine panel to characterize COVID-19 in a large (534 patient samples, 305 controls) outpatient cohort of recently tested PCR-positive patients. The COVID-19 cohort consisted of patients who were predominantly in the initial phase of the disease and mostly exhibited a milder disease course. Concerning the metabolic profiles of SARS-CoV-2-infected patients, we identified markers of oxidative stress and a severe dysregulation of energy metabolism. NMR markers, such as phenylalanine, inflammatory glycoproteins (Glyc) and their ratio with the previously reported supramolecular phospholipid composite (Glyc/SPC), showed a predictive power comparable to laboratory parameters such as C-reactive protein (CRP) or ferritin. We demonstrated interfaces between the metabolism and the immune system, e.g., we could trace an interleukin (IL-6)-induced transformation of a high-density lipoprotein (HDL) to a pro-inflammatory actor. Finally, we showed that metadata such as age, sex and constitution (e.g., body mass index, BMI) need to be considered when exploring new biomarkers and that adding NMR parameters to existing diagnoses expands the diagnostic toolbox for patient stratification and personalized medicine.

Metabolomic serum abnormalities in dogs with hepatopathies

Hepatopathies can cause major metabolic abnormalities in humans and animals. This study examined differences in serum metabolomic parameters and patterns in left-over serum samples from dogs with either congenital portosystemic shunts (cPSS, n = 24) or high serum liver enzyme activities (HLEA, n = 25) compared to control dogs (n = 64). A validated targeted proton nuclear magnetic resonance spectroscopy platform was used to assess 123 parameters. Principal component analysis of the serum metabolome demonstrated distinct clustering among individuals in each group, with the cluster of HLEA being broader compared to the other groups, presumably due to the wider spectrum of hepatic diseases represented in these samples. While younger and older adult control dogs had very similar metabolomic patterns and clusters, there were changes in many metabolites in the hepatopathy groups. Higher phenylalanine and tyrosine concentrations, lower branched-chained amino acids (BCAAs) concentrations, and altered fatty acid parameters were seen in cPSS dogs compared to controls. In contrast, dogs with HLEA had increased concentrations of BCAAs, phenylalanine, and various lipoproteins. Machine learning based solely on the metabolomics data showed excellent group classification, potentially identifying a novel tool to differentiate hepatopathies. The observed changes in metabolic parameters could provide invaluable insight into the pathophysiology, diagnosis, and prognosis of hepatopathies.

Glycoprotein Profile Measured by a 1H-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 ¹H-NMR. We quantified the two peaks associated with the concentration of plasma glycoproteins (GlycA and GlycB) and their height/width ratios (H/W GlycA and H/W GlycB), as higher and narrower signals have been related to inflammation. We also quantified GlycF, the signal of which is proportional to the concentration of the acetyl groups of free N-acetylglucosamine, N-acetylgalactosamine, and N-acetylneuraminic in the samples. The lipoprotein profile was also determined (Liposcale^®). Standard clinical and anthropometric measurements were taken. Multivariate classification models were developed to study the differences between the study groups. Reduced HDL-C levels, increased small dense LDL and HDL particles, and elevated TG levels were significantly associated with glycoprotein variables. Glycoprotein values in the diagnostic groups were significantly different from those in the CT groups. AD and DM conditions together contribute to a positive and significant synergetic effect on the GlycA area (<0.05) and the H/W ratios of GlycA (<0.01) and GlycB (<0.05). By adding the new glycoprotein variables to the traditionally used marker of inflammation C-reactive protein (CRP), the AUC increased sharply for classification models between the CT group and the rest (0.68 to 0.84), patients with and without dyslipidemia (0.54 to 0.86), and between patients with and without diabetes (0.55 to 0.75). ¹H-NMR-derived glycoproteins can be used as possible markers of the degree of inflammation associated with T2DM and AD.

Meal-induced inflammation: postprandial insights from the Personalised REsponses to DIetary Composition Trial (PREDICT) study in 1000 participants

BACKGROUND

Meal-induced metabolic changes trigger an acute inflammatory response, contributing to chronic inflammation and associated diseases.

OBJECTIVES

We aimed to characterize variability in postprandial inflammatory responses using traditional (IL-6) and novel [glycoprotein acetylation (GlycA)] biomarkers of inflammation and dissect their biological determinants with a focus on postprandial glycemia and lipemia.

METHODS

Postprandial (0-6 h) glucose, triglyceride (TG), IL-6, and GlycA responses were measured at multiple intervals after sequential mixed-nutrient meals (0 h and 4 h) in 1002 healthy adults aged 18-65 y from the PREDICT (Personalised REsponses to DIetary Composition Trial) 1 study, a single-arm dietary intervention study. Measures of habitual diet, blood biochemistry, gut microbiome composition, and visceral fat mass (VFM) were also collected.

RESULTS

The postprandial changes in GlycA and IL-6 concentrations were highly variable between individuals. Participants eliciting an increase in GlycA and IL-6 (60% and 94% of the total participants, respectively) had mean 6-h increases of 11% and 190%, respectively. Peak postprandial TG and glucose concentrations were significantly associated with 6-h GlycA (r = 0.83 and r = 0.24, respectively; both P < 0.001) but not with 6-h IL-6 (both P > 0.26). A random forest model revealed the maximum TG concentration was the strongest postprandial TG predictor of postprandial GlycA and structural equation modeling revealed that VFM and fasting TG were most strongly associated with fasting and postprandial GlycA. Network Mendelian randomization demonstrated a causal link between VFM and fasting GlycA, mediated (28%) by fasting TG. Individuals eliciting enhanced GlycA responses had higher predicted cardiovascular disease risk (using the atherosclerotic disease risk score) than the rest of the cohort.

CONCLUSIONS

The variable postprandial increases in GlycA and their associations with TG metabolism highlight the importance of modulating TG in concert with obesity to reduce GlycA and associated low-grade inflammation-related diseases.This trial was registered at clinicaltrials.gov as NCT03479866.

Association Between GlycA and Cognitive Function: Cross-Sectional Results From the ELSA-Brasil Study

Inflammation is associated with poor cognitive performance. GlycA is a novel marker of systemic inflammation, but information on GlycA and cognition is scarce. We aimed to evaluate the association between GlycA and cognitive performance in a large sample from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). In this cross-sectional study, participants with GlycA measured at baseline were included. Cognitive function was evaluated using the word list test, the trail-making test, and the semantic and phonemic verbal fluency tests. The association of GlycA with cognitive performance was investigated using linear regression models adjusted for sociodemographic and clinical variables. A total of 4327 participants were analyzed (mean age=51.5±9.0 y old, 54% were female, 60% white). The mean GlycA was 414.9±69.8 µmol/L. Higher GlycA levels were associated with lower global cognitive performance, even after adjustments for confounders and C-reactive protein. Higher GlycA levels were associated with lower performance in language and executive function domains (language: β=-0.005, 95% confidence interval CI=-0.010, -0.001, P=0.01; and executive function: β=-0.005, 95% confidence interval=0.009, -0.001, P=0.02]. GlycA was associated with worse cognitive performance in the ELSA-Brasil study, independent of C-reactive protein levels. GlycA may be a potential biomarker for cognitive impairment.

Integrative Modeling of Quantitative Plasma Lipoprotein, Metabolic, and Amino Acid Data Reveals a Multiorgan Pathological Signature of SARS-CoV-2 Infection

The metabolic effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on human blood plasma were characterized using multiplatform metabolic phenotyping with nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Quantitative measurements of lipoprotein subfractions, α-1-acid glycoprotein, glucose, and biogenic amines were made on samples from symptomatic coronavirus disease 19 (COVID-19) patients who had tested positive for the SARS-CoV-2 virus (n = 17) and from age- and gender-matched controls (n = 25). Data were analyzed using an orthogonal-projections to latent structures (OPLS) method and used to construct an exceptionally strong (AUROC = 1) hybrid NMR-MS model that enabled detailed metabolic discrimination between the groups and their biochemical relationships. Key discriminant metabolites included markers of inflammation including elevated α-1-acid glycoprotein and an increased kynurenine/tryptophan ratio. There was also an abnormal lipoprotein, glucose, and amino acid signature consistent with diabetes and coronary artery disease (low total and HDL Apolipoprotein A1, low HDL triglycerides, high LDL and VLDL triglycerides), plus multiple highly significant amino acid markers of liver dysfunction (including the elevated glutamine/glutamate and Fischer's ratios) that present themselves as part of a distinct SARS-CoV-2 infection pattern. A multivariate training-test set model was validated using independent samples from additional SARS-CoV-2 positive patients and controls. The predictive model showed a sensitivity of 100% for SARS-CoV-2 positivity. The breadth of the disturbed pathways indicates a systemic signature of SARS-CoV-2 positivity that includes elements of liver dysfunction, dyslipidemia, diabetes, and coronary heart disease risk that are consistent with recent reports that COVID-19 is a systemic disease affecting multiple organs and systems. Metabolights study reference: MTBLS2014.

GlycA: A New Biomarker for Systemic Inflammation and Cardiovascular Disease (CVD) Risk Assessment

The GlycA test is a recently developed proton nuclear magnetic resonance (¹H-NMR) spectroscopy-based assay that has been gaining increased interest as a serum biomarker for systemic inflammation, and consequently, as a potential biomarker for cardiovascular disease (CVD) risk assessment. The test has undergone investigation in several large cohort studies, since its development, to assess its predictive value for incident CVD events, CVD-associated mortality, and all-cause mortality. Despite variation in the generated estimates by these studies, they have all consistently demonstrated moderate-strength positive correlations between baseline GlycA levels, and incident CVD event rates and associated mortality. These correlations withheld testing even after adjusting for several other established CVD risk factors, including notable inflammatory biomarkers such as high-sensitivity C-reactive protein (hsCRP) and interleukin-6 (IL-6). Compared with hsCRP, which is a well-known inflammatory biomarker for CVD risk assessment, GlycA has a comparable predictive value for future CVD-related events. However, the indications to pursue GlycA testing, and its clinical utility in patient care management, are yet to be determined. In this review, we define the GlycA test and what it "measures", and provide a brief summary of the findings of studies showing its association with incident CVD rates, and CVD-related mortality, as well as its correlation with other inflammatory biomarkers, namely hsCRP. Finally, we highlight the analytical advantages of the GlycA test, compared with "traditional" inflammatory biomarkers, while also mentioning its current limitations.

Glycoprotein A as a biomarker of pulmonary infection and inflammation in children with cystic fibrosis

BACKGROUND

Serum Glycoprotein A (GlycA) levels are increased in a variety of inflammatory disease states. However, GlycA has not been previously evaluated in children with cystic fibrosis (CF). We assessed the relationship between GlycA and pulmonary infection, inflammation, bronchial wall thickening (BWT) and bronchiectasis in young children with CF.

METHODS

From 95 patients, we obtained 311 paired serum and bronchoalveolar lavage (BAL) samples at multiple timepoints, with concurrent chest computed tomography on 168 occasions. Quantitative GlycA was determined using high-throughput nuclear magnetic resonance metabolomic testing. Participants were considered to be infected if ≥1 significant proinflammatory organism was isolated from their BAL. The presence of free neutrophil elastase (NE) above the limit of detection was considered evidence of inflammation. The relationships between GlycA levels and infection state, inflammation, and bronchiectasis were examined using a generalized estimating equation approach.

RESULTS

There was a positive relationship between GlycA (mean 1.01 mmol/L, range 0.68-1.92 mmol/L) and being infected with one or more proinflammatory organisms, even after adjusting for age and gender (odds ratio [OR], 1.2 per 0.1 mmol/L, 95% confidence interval [CI], 1.02, 1.4, P = .03). There was also a positive relationship between GlycA and NE (unadjusted OR, 1.2 95% CI, 1.01, 1.4, P = .04), not significant after adjustment. GlycA concentration was associated with BWT but not bronchiectasis.

CONCLUSIONS

Although GlycA levels were higher on average in those who had an infection or neutrophilic inflammation, there was also considerable variability, limiting the clinical utility of this biomarker alone in determining early disease status in CF.

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.

The Exercise Training Modulatory Effects on the Obesity-Induced Immunometabolic Dysfunctions

Reduced physical activity rate in people's lifestyle is a global concern associated with the prevalence of health disorders such as obesity and metabolic disturbance. Ample evidence has indicated a critical role of the immune system in the aggravation of obesity. The type, duration, and production of adipose tissue-released mediators may change subsequent inactive lifestyle-induced obesity, leading to the chronic systematic inflammation and monocyte/macrophage (MON/MФ) phenotype polarization. Preliminary adipose tissue expansion can be inhibited by changing the lifestyle. In this context, exercise training is widely recommended due to a definite improvement of energy balance and the potential impacts on the inflammatory signaling cascades. How exercise training affects the immune system has not yet been fully elucidated, because its anti-inflammatory, pro-inflammatory, or even immunosuppressive impacts have been indicated in the literature. A thorough understanding of the mechanisms triggered by exercise can suggest a new approach to combat meta-inflammation-induced metabolic diseases. In this review, we summarized the obesity-induced inflammatory pathways, the roles of MON/MФ polarization in adipose tissue and systemic inflammation, and the underlying inflammatory mechanisms triggered by exercise during obesity.

Increased glycoprotein acetylation is associated with high cardiac event rates: Analysis using coronary computed tomography angiography

Objective:

Glycoprotein acetylation (GlycA), an emerging inflammatory biomarker, has been used as an indicator of cardiovascular disease. Our research aimed to evaluate the correlation between GlycA and coronary artery disease (CAD) using coronary computed tomography angiography (CCTA).

Methods:

In the present study, a total of 342 patients were enrolled, and each of them underwent CCTA. The correlation between GlycA and major adverse cardiac events (MACE) was detected via Cox’s proportional hazards models. Based on differences in the GlycA level, patients were categorized into three groups (T1, T2, and T3).

Results:

Compared with the group with the lowest GlycA level (T1), the group with the highest GlycA level (T3) exhibited stronger atherosclerotic pressure involving the extent of atherosclerotic plaque and risk of obstructive CAD. In addition, the patients in the T3 group had a greater chance of experiencing MACE and higher all-cause mortality than those in the T1 group. Among patients without CAD who underwent CCTA, those with high GlycA levels experienced elevated atherosclerotic stress and heightened risk of MACE compared with those with low GlycA levels.

Conclusion:

These results suggest that serum GlycA is significantly associated with the long-term clinical results of patients with no known CAD undergoing CCTA. The risks of death and experiencing MACE increase among patients with high GlycA levels.

Effects of hepato-preferential basal insulin peglispro on nuclear magnetic resonance biomarkers lipoprotein insulin resistance index and GlycA in patients with diabetes

AIM

To characterize the effects of hepato-preferential basal insulin peglispro (BIL) and insulin glargine on insulin resistance (lipoprotein insulin resistance index [LP-IR]) and inflammation (GlycA), and to explore the biological implications.

METHODS

This substudy included 847 patients with Type 1 diabetes (T1D) or Type 2 diabetes (T2D) in four cohorts of the BIL development program. LP-IR and GlycA were measured before and after insulin treatment. Correlations between LP-IR, GlycA, clinical parameters and liver biomarkers were assessed.

RESULTS

LP-IR and GlycA were higher in T2D than T1D. LP-IR increased in patients switched from basal insulins to BIL but not in insulin-naive patients. GlycA decreased in T2D patients treated with BIL and T1D patients treated with glargine.

CONCLUSION

These exploratory analyses help to characterize differences in biological effects between BIL and glargine treatment.

GlycA, a marker of protein glycosylation, is related to albuminuria and estimated glomerular filtration rate: the ELSA-Brasil study

Background

Systemic inflammation has been implicated in several chronic diseases. GlycA is a new nuclear mass resonance (NMR) spectroscopy-derived biomarker of systemic inflammation that reflects protein glycosylation. We evaluated the association of GlycA with albuminuria and eGFR in the ELSA-Brasil Study.

Methods

The cross-sectional association between GlycA (automated NMR LipoProfile(®) test spectra, LabCorp, Raleigh, NC), and overnight 12 h–albuminuria and CKD-EPI eGFR was evaluated among 5050 participants.

Results

GlycA was higher among older, women, smokers, alcohol abstemious, obese and in those with diabetes, hypertension or dyslipidemia. In addition, both eGFR and albuminuria were associated to GlycA. In linear regression, GlycA was independently associated with log albuminuria (B 0.03; 95%CI 0.02–0.04, P < 0.0001, per 1sd increase) and inversely related to eGFR (B -0.53; 95%CI -0.99 – -0.07, P < 0.02), even after adjustments including hsCRP. In logistic regression, GlycA was independently related to the risk of A2 or A3 albuminuria (OR 1.42, 95%CI 1.27–1.57, p < 0.0001, per 1sd increase), of having an eGFR < 60 ml/min/1.73m² (OR 1.26, 95%CI 1.12–1.41, p = 0.0003, per 1 sd) or of a combined diagnosis of both conditions (OR 1.35, 95%CI 1.23–1.46, p < 0.0001, per 1 sd). In the ROC curve, GlycA had a higher AUC in comparison to hsCRP (AUC 0.67 vs. 0.62, p = 0.06) for the association with albuminuria A2 or A3.

Conclusions

The present study demonstrates that GlycA is associated with albuminuria and eGFR, independently of major risk factors for CKD progression, including (and with a stronger association than) hsCRP. GlycA should be further evaluated in CKD progression.

GlycA, a novel biomarker of systemic inflammation and cardiovascular disease risk

Background

GlycA is a novel spectroscopic marker of systemic inflammation with low intra-individual variability and other attributes favoring its clinical use in patients with chronic inflammatory and autoimmune diseases. GlycA is unique in its composite nature, reflecting both increased glycan complexity and circulating acute phase protein levels during local and systemic inflammation. Recent studies of GlycA from cross-sectional, observational and interventional studies have been highly informative, demonstrating that GlycA is elevated in acute and chronic inflammation, predicts death in healthy individuals and is associated with disease severity in patients with chronic inflammatory diseases such as rheumatoid arthritis, psoriasis and lupus. Moreover, following treatment with biological therapy in psoriasis, reduction in skin disease severity was accompanied by a decrease in GlycA levels and improvement in vascular inflammation.

Conclusions

Collectively, these findings suggest GlycA is a marker that tracks systemic inflammation and subclinical vascular inflammation. However, larger prospective studies and randomized trials are necessary in order to assess the impact of novel therapies on GlycA in patients with chronic inflammatory conditions, which may be concomitant with cardiovascular benefits.

Association of the Composite Inflammatory Biomarker GlycA, with Exercise-Induced Changes in Body Habitus in Men and Women with Prediabetes

GlycA is a new composite measure of systemic inflammation and a predictor of many inflammatory diseases. GlycA is the nuclear magnetic resonance spectroscopy-derived signal arising from glucosamine residues on acute-phase proteins. This study aimed to evaluate how exercise-based lifestyle interventions modulate GlycA in persons at risk for type 2 diabetes. GlycA, fitness, and body habitus were measured in 169 sedentary adults (45–75 years) with prediabetes randomly assigned to one of four six-month exercise-based lifestyle interventions. Interventions included exercise prescription based on the amount (energy expenditure (kcal/kg weight/week (KKW)) and intensity (%VO_2peak). The groups were (1) low-amount/moderate-intensity (10KKW/50%) exercise; (2) high-amount/moderate-intensity (16KKW/50%) exercise; (3) high-amount/vigorous-intensity (16KKW/75%) exercise; and (4) a Clinical Lifestyle (combined diet plus low-amount/moderate-intensity exercise) intervention. Six months of exercise training and/or diet-reduced GlycA (mean Δ: −6.8 ± 29.2 μmol/L; p = 0.006) and increased VO_2peak (mean Δ: 1.98 ± 2.6 mL/kg/min; p < 0.001). Further, visceral (mean Δ: −21.1 ± 36.6 cm²) and subcutaneous fat (mean Δ: −24.3 ± 41.0 cm²) were reduced, while liver density (mean Δ: +2.3 ± 6.5HU) increased, all p < 0.001. When including individuals in all four interventions, GlycA reductions were associated with reductions in visceral adiposity (p < 0.03). Exercise-based lifestyle interventions reduced GlycA concentrations through mechanisms related to exercise-induced modulations of visceral adiposity. This trial is registered with Clinical Trial Registration Number NCT00962962.

High-density lipoprotein and inflammation in cardiovascular disease

Great advances are being made at the mechanistic level in the understanding of the structural and functional diversity of high-density lipoprotein (HDL). HDL particle subspecies of different sizes are now known to differ in the protein and lipid cargo they transport, conferring on them the ability to perform different functions that in aggregate would be expected to provide protection against the development of atherosclerosis and its downstream clinical consequences. Exacerbating what is already a very complex system is the finding that inflammation, via alteration of the proteomic and lipidomic composition of HDL subspecies, can modulate at least some of their functional activities. In contrast to the progress being made at the mechanistic level, HDL epidemiologic research has lagged behind, largely because the simple HDL biomarkers used (mainly just HDL cholesterol) lack the needed complexity. To address this deficiency, analyses will need to use multiple HDL subspecies and be conducted in such a way as to eliminate potential sources of confounding. To help account for the modulating influence of inflammation, effective use must also be made of inflammatory biomarkers including searching systematically for HDL-inflammation interactions. Using nuclear magnetic resonance (NMR)-measured HDL subclass data and a novel NMR-derived inflammatory biomarker, GlycA, we offer a case study example of the type of analytic approach considered necessary to advance HDL epidemiologic understanding.

Inflammatory glycoproteins in cardiometabolic disorders, autoimmune diseases and cancer

The physiological function initially attributed to the oligosaccharide moieties or glycans on inflammatory glycoproteins was to improve protein stability. However, it is now clear that glycans play a prominent role in glycoprotein structure and function and in some cases contribute to disease states. In fact, glycan processing contributes to pathogenicity not only in autoimmune disorders but also in atherosclerotic cardiovascular disease, diabetes and malignancy. While most clinical laboratory tests measure circulating levels of inflammatory proteins, newly developed diagnostic and prognostic tests are harvesting the information that can be gleaned by measuring the amount or structure of the attached glycans, which may be unique to individuals as well as various diseases. As such, these newer glycan-based tests may provide future means for more personalized approaches to patient stratification and improved patient care. Here we will discuss recent progress in high-throughput laboratory methods for glycomics (i.e. the study of glycan structures) and glycoprotein quantification by methods such as mass spectrometry and nuclear magnetic resonance spectroscopy. We will also review the clinical utility of glycoprotein and glycan measurements in the prediction of common low-grade inflammatory disorders including cardiovascular disease, diabetes and cancer, as well as for monitoring autoimmune disease activity.

GlycA, a marker of acute phase glycoproteins, and the risk of incident type 2 diabetes mellitus: PREVEND study

BACKGROUND

GlycA is a recently developed glycoprotein biomarker of systemic inflammation that may be predictive of incident type 2 diabetes mellitus (T2DM).

METHODS

Analytical performance of the GlycA test, measured on the Vantera® Clinical Analyzer, was evaluated. To test its prospective association with T2DM, GlycA was measured in 4524 individuals from the PREVEND study and a survival analysis was performed with a mean follow-up period of 7.3y.

RESULTS

Imprecision for the GlycA test ranged from 1.3-2.3% and linearity was established between 150 and 1588μmol/l. During the follow-up period, 220 new T2DM cases were ascertained. In analyses adjusted for relevant covariates, GlycA was associated with incident T2DM; hazard ratio (HR) for the highest vs. lowest quartile 1.77 [95% Confidence Interval (CI): 1.10-2.86, P=0.01], whereas the association of high sensitivity C-reactive protein (hsCRP) with T2DM was not significant. GlycA remained associated with incident T2DM after additional adjustment for hsCRP; HR 1.71 [1.00-2.92, P=0.04]. A multivariable adjusted analysis of dichotomized subgroups showed that the hazard for incident T2DM was highest in the subgroup with high GlycA and low hsCRP (P=0.03).

CONCLUSIONS

The performance characteristics of the GlycA test reveal that it is suitable for clinical applications, including assessment of the risk of future T2DM.