A novel protein glycan biomarker and LCAT activity in metabolic syndrome

Associations among NMR-measured inflammatory and metabolic biomarkers and accelerated aging in cardiac catheterization patients

Research into aging has grown substantially with the creation of molecular biomarkers of biological age that can be used to determine age acceleration. Concurrently, nuclear magnetic resonance (NMR) assessment of biomarkers of inflammation and metabolism provides researchers with new ways to examine intermediate risk factors for chronic disease. We used data from a cardiac catheterization cohort to examine associations between biomarkers of cardiometabolic health and accelerated aging assessed using both gene expression (Transcriptomic Age) and DNA methylation (Hannum Age, GrimAge, Horvath Age, and Phenotypic Age). Linear regression models were used to associate accelerated aging with each outcome (cardiometabolic health biomarkers) while adjusting for chronological age, sex, race, and neighborhood socioeconomic status. Our study shows a robust association between GlycA and GrimAge (5.71, 95% CI = 4.36, 7.05, P = 7.94 × 10-16), Hannum Age (1.81, 95% CI = 0.65, 2.98, P = 2.30 × 10-3), and Phenotypic Age (2.88, 95% CI = 1.91, 3.87, P = 1.21 × 10-8). We also saw inverse associations between apolipoprotein A-1 and aging biomarkers. These associations provide insight into the relationship between aging and cardiometabolic health that may be informative for vulnerable populations.

Gradual Increase in Inflammation-Linked Glycoproteins and a Proatherogenic Lipoprotein Profile in the Early Stages of Psychosis as Characterized by 1H NMR Blood Analysis

Minimally invasive prognostic markers of inflammation and dyslipidemia in individuals with a risk of psychosis, also called "at-risk mental state" (ARMS), or in the first episode of psychosis (FEP) are of utmost clinical importance to prevent cardiovascular disorders. We analyzed the plasma concentration of inflammation-linked glycoproteins (Glycs) and lipoprotein subclasses by proton nuclear magnetic resonance (¹H NMR) in a single acquisition. Study participants were healthy controls (HCs, N = 67) and patients with ARMS (N = 58), FEP (N = 110), or early psychosis diagnosis with ≥2 episodes (critical period (CP), N = 53). Clinical biomarkers such as high-sensitivity C-reactive protein, interleukin 6, fibrinogen, insulin, and lipoproteins were also measured. Although all participants had normal lipoprotein profiles and no inflammation according to conventional biomarkers, a gradual increase in the Glyc ¹H NMR levels was observed from HCs to CP patients; this increase was statistically significant for GlycA (CP vs HC). In parallel, a progressive and significant proatherogenic ¹H NMR lipoprotein profile was also identified across stages of psychosis (ARMS and CP vs HC). These findings highlight the potential of using ¹H NMR Glyc and lipoprotein profiling to identify blood changes in individuals with ARMS or FEP and pave the way for applications using this technology to monitor metabolic and cardiovascular risks in clinical psychiatry.

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.

Early life infection and proinflammatory, atherogenic metabolomic and lipidomic profiles in infancy: a population-based cohort study

Background:

The risk of adult onset cardiovascular and metabolic (cardiometabolic) disease accrues from early life. Infection is ubiquitous in infancy and induces inflammation, a key cardiometabolic risk factor, but the relationship between infection, inflammation, and metabolic profiles in early childhood remains unexplored. We investigated relationships between infection and plasma metabolomic and lipidomic profiles at age 6 and 12 months, and mediation of these associations by inflammation.

Methods:

Matched infection, metabolomics, and lipidomics data were generated from 555 infants in a pre-birth longitudinal cohort. Infection data from birth to 12 months were parent-reported (total infections at age 1, 3, 6, 9, and 12 months), inflammation markers (high-sensitivity C-reactive protein [hsCRP]; glycoprotein acetyls [GlycA]) were quantified at 12 months. Metabolic profiles were 12-month plasma nuclear magnetic resonance metabolomics (228 metabolites) and liquid chromatography/mass spectrometry lipidomics (776 lipids). Associations were evaluated with multivariable linear regression models. In secondary analyses, corresponding inflammation and metabolic data from birth (serum) and 6-month (plasma) time points were used.

Results:

At 12 months, more frequent infant infections were associated with adverse metabolomic (elevated inflammation markers, triglycerides and phenylalanine, and lower high-density lipoprotein [HDL] cholesterol and apolipoprotein A1) and lipidomic profiles (elevated phosphatidylethanolamines and lower trihexosylceramides, dehydrocholesteryl esters, and plasmalogens). Similar, more marked, profiles were observed with higher GlycA, but not hsCRP. GlycA mediated a substantial proportion of the relationship between infection and metabolome/lipidome, with hsCRP generally mediating a lower proportion. Analogous relationships were observed between infection and 6-month inflammation, HDL cholesterol, and apolipoprotein A1.

Conclusions:

Infants with a greater infection burden in the first year of life had proinflammatory and proatherogenic plasma metabolomic/lipidomic profiles at 12 months of age that in adults are indicative of heightened risk of cardiovascular disease, obesity, and type 2 diabetes. These findings suggest potentially modifiable pathways linking early life infection and inflammation with subsequent cardiometabolic risk.

Funding:

The establishment work and infrastructure for the BIS was provided by the Murdoch Children’s Research Institute (MCRI), Deakin University, and Barwon Health. Subsequent funding was secured from National Health and Medical Research Council of Australia (NHMRC), The Shepherd Foundation, The Jack Brockhoff Foundation, the Scobie & Claire McKinnon Trust, the Shane O’Brien Memorial Asthma Foundation, the Our Women’s Our Children’s Fund Raising Committee Barwon Health, the Rotary Club of Geelong, the Minderoo Foundation, the Ilhan Food Allergy Foundation, GMHBA, Vanguard Investments Australia Ltd, and the Percy Baxter Charitable Trust, Perpetual Trustees. In-kind support was provided by the Cotton On Foundation and CreativeForce. The study sponsors were not involved in the collection, analysis, and interpretation of data; writing of the report; or the decision to submit the report for publication. Research at MCRI is supported by the Victorian Government’s Operational Infrastructure Support Program. This work was also supported by NHMRC Senior Research Fellowships to ALP (1008396); DB (1064629); and RS (1045161) , NHMRC Investigator Grants to ALP (1110200) and DB (1175744), NHMRC-A*STAR project grant (1149047). TM is supported by an MCRI ECR Fellowship. SB is supported by the Dutch Research Council (452173113).

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.

Genetic and Metabolic Determinants of Atrial Fibrillation in a General Population Sample: The CHRIS Study

Atrial fibrillation (AF) is a supraventricular arrhythmia deriving from uncoordinated electrical activation with considerable associated morbidity and mortality. To expand the limited understanding of AF biological mechanisms, we performed two screenings, investigating the genetic and metabolic determinants of AF in the Cooperative Health Research in South Tyrol study. We found 110 AF cases out of 10,509 general population individuals. A genome-wide association scan (GWAS) identified two novel loci (p-value < 5 × 10⁻⁸) around SNPs rs745582874, next to gene PBX1, and rs768476991, within gene PCCA, with genotype calling confirmed by Sanger sequencing. Risk alleles at both SNPs were enriched in a family detected through familial aggregation analysis of the phenotype, and both rare alleles co-segregated with AF. The metabolic screening of 175 metabolites, in a subset of individuals, revealed a 41% lower concentration of lysophosphatidylcholine lysoPC a C20:3 in AF cases compared to controls (p-adj = 0.005). The genetic findings, combined with previous evidence, indicate that the two identified GWAS loci may be considered novel genetic rare determinants for AF. Considering additionally the association of lysoPC a C20:3 with AF by metabolic screening, our results demonstrate the valuable contribution of the combined genomic and metabolomic approach in studying AF in large-scale population studies.

Inflammatory metabolic profile of South African patients with prostate cancer

Background

Men with African ancestry are more likely to develop aggressive prostate cancer (PCa) and to die from this disease. The study of PCa in the South African population represents an opportunity for biomedical research due to the high prevalence of aggressive PCa. While inflammation is known to play a significant role in PCa progression, its association with tumor stage in populations of African descent has not been explored in detail. Identification of new metabolic biomarkers of inflammation may improve diagnosis of patients with aggressive PCa.

Methods

Plasma samples were profiled from 41 South African men with PCa using nuclear magnetic resonance (NMR) spectroscopy. A total of 41 features, including metabolites, lipid classes, total protein, and the inflammatory NMR markers, GlycA, and GlycB, were quantified from each NMR spectrum. The Bruker’s B.I.-LISA protocols were used to characterize 114 parameters related to the lipoproteins. The unsupervised KODAMA method was used to stratify the patients of our cohort based on their metabolic profile.

Results

We found that the plasma of patients with very high risk, aggressive PCa and high level of C-reactive protein have a peculiar metabolic phenotype (metabotype) characterized by extremely high levels of GlycA and GlycB. The inflammatory processes linked to the higher level of GlycA and GlycB are characterized by a deep change of the plasma metabolome that may be used to improve the stratification of patients with PCa. We also identified a not previously known relationship between high values of VLDL and low level of GlycB in a different metabotype of patients characterized by lower-risk PCa.

Conclusions

For the first time, a portrait of the metabolic changes in African men with PCa has been delineated indicating a strong association between inflammation and metabolic profiles. Our findings indicate how the metabolic profile could be used to identify those patients with high level of inflammation, characterized by aggressive PCa and short life expectancy. Integrating a metabolomic analysis as a tool for patient stratification could be important for opening the door to the development of new therapies. Further investigations are needed to understand the prevalence of an inflammatory metabotype in patients with aggressive PCa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-021-00265-6.

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.

Elevated serum alpha-1 antitrypsin is a major component of GlycA-associated risk for future morbidity and mortality

Background

GlycA is a nuclear magnetic resonance (NMR) spectroscopy biomarker that predicts risk of disease from myriad causes. It is heterogeneous; arising from five circulating glycoproteins with dynamic concentrations: alpha-1 antitrypsin (AAT), alpha-1-acid glycoprotein (AGP), haptoglobin (HP), transferrin (TF), and alpha-1-antichymotrypsin (AACT). The contributions of each glycoprotein to the disease and mortality risks predicted by GlycA remain unknown.

Methods

We trained imputation models for AAT, AGP, HP, and TF from NMR metabolite measurements in 626 adults from a population cohort with matched NMR and immunoassay data. Levels of AAT, AGP, and HP were estimated in 11,861 adults from two population cohorts with eight years of follow-up, then each biomarker was tested for association with all common endpoints. Whole blood gene expression data was used to identify cellular processes associated with elevated AAT.

Results

Accurate imputation models were obtained for AAT, AGP, and HP but not for TF. While AGP had the strongest correlation with GlycA, our analysis revealed variation in imputed AAT levels was the most predictive of morbidity and mortality for the widest range of diseases over the eight year follow-up period, including heart failure (meta-analysis hazard ratio = 1.60 per standard deviation increase of AAT, P-value = 1×10⁻¹⁰), influenza and pneumonia (HR = 1.37, P = 6×10⁻¹⁰), and liver diseases (HR = 1.81, P = 1×10⁻⁶). Transcriptional analyses revealed association of elevated AAT with diverse inflammatory immune pathways.

Conclusions

This study clarifies the molecular underpinnings of the GlycA biomarker’s associated disease risk, and indicates a previously unrecognised association between elevated AAT and severe disease onset and mortality.

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 (¹H-NMR)-derived glycoprotein profiles have emerged as potential biomarkers that reflect systemic inflammation in type 2 diabetes, obesity, and other pathological processes. The aim of this work is to study plasma glycoprotein profiles as metabolic/inflammatory biomarkers underlying PCOS and its association with inflammation and obesity. We used ¹H-NMR spectroscopy to study five glycoprotein variables, namely GlycA, GlycB, and GlycF and the height-to-width (H/W) ratio of GlycA and GlycB, in 17 women with PCOS (9 non-obese and 8 obese), 17 control women (9 non-obese and 8 obese), and 19 healthy men (10 non-obese and 9 obese). H/W ratios of GlycA and GlycB, but not glycoprotein areas, were specifically associated with PCOS independently of obesity. When considered as a whole, obese subjects presented higher GlycA, GlycB, and GlycF areas and higher H/W GlycA and GlycB ratios than their non-obese counterparts. All glycoprotein variables were associated with hsCRP, IL-6, and TNF-α, showing different correlations among PCOS, women, and men. Our present exploratory results suggest that ¹H-NMR-derived glycoprotein profiles might serve as novel diagnostic markers of low-grade chronic inflammation in women with PCOS.

The association between lecithin-cholesterol acyltransferase activity and fatty liver index

Background

Non-alcoholic fatty liver disease is a frequent ailment with known complications, including those within the cardiovascular system. Associations between several indicators of high-density lipoprotein metabolism and function with clinical and laboratory parameters for the assessment of fatty liver index, a surrogate marker of non-alcoholic fatty liver disease, were evaluated.

Methods

The study comprised 130 patients classified according to fatty liver index values: fatty liver index < 30, fatty liver index 30–59 (the intermediate group) and fatty liver index ⩾ 60. Lecithin–cholesterol acyltransferase and cholesteryl ester transfer protein activities were determined. Paraoxonase 1 concentration and its activity, paraoxonase 3 concentration and high-density lipoprotein subclass distribution were assessed.

Results

Increased lecithin–cholesterol acyltransferase activity correlated with increased fatty liver index ( P < 0.001). Paraoxonase 3 concentration was lower in the fatty liver index ⩾ 60 group compared with the fatty liver index < 30 group ( P < 0.05). Cholesteryl ester transfer protein activity, paraoxonase 1 concentration and its activity did not significantly differ across the fatty liver index groups. The relative proportion of small-sized high-density lipoprotein 3 subclass was higher in the fatty liver index ⩾ 60 group compared with the other two fatty liver index groups ( P < 0.01). Lecithin–cholesterol acyltransferase activity positively associated with the fatty liver index ⩾ 60 group and remained significant after adjustment for other potential confounders. Only the triglyceride concentration remained significantly associated with lecithin–cholesterol acyltransferase activity when the parameters that constitute the fatty liver index equation were examined.

Conclusions

Higher lecithin–cholesterol acyltransferase activity is associated with elevated fatty liver index values. Significant independent association between triglycerides and lecithin–cholesterol acyltransferase activity might indicate a role of hypertriglyceridaemia in alterations of lecithin–cholesterol acyltransferase activity in individuals with elevated fatty liver index.

Primary aldosteronism is associated with decreased low-density and high-density lipoprotein particle concentrations and increased GlycA, a pro-inflammatory glycoprotein biomarker

BACKGROUND

Primary aldosteronism (PA) may confer increased cardiovascular risk beyond effects on systemic blood pressure, but contributing mechanisms remain incompletely understood. We compared plasma (apo)lipoproteins and lipoprotein particle characteristics, GlycA, a pro-inflammatory glycoprotein biomarker of enhanced chronic inflammation, and plasma total branched-chain amino acids (BCAA), measured using nuclear magnetic resonance (NMR) spectroscopy, between patients with PA, control subjects without hypertension, subjects with untreated hypertension and subjects with treated hypertension.

METHODS

Twenty PA patients were individually matched with 2819 control subjects without hypertension, 501 subjects with untreated hypertension and 878 subjects with treated hypertension participating in the PREVEND (Prevention of Renal and Vascular End-Stage Disease) cohort study with respect to age, sex, body mass index, smoking and statin use. The Vantera® Clinical Analyzer was used to determine NMR-based laboratory parameters.

RESULTS

Total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein (apo) B, apolipoprotein A-I (apoA-I), LDL particle and HDL particle concentrations were all decreased in PA subjects vs control subjects and subjects with untreated hypertension (P < 0.016). Triglycerides (TG) and triglyceride-rich lipoprotein (TRL) concentrations were lower in PA subjects vs subjects with (untreated) hypertension. GlycA was increased in PA vs the three comparator groups (P < 0.016). Total BCAA concentrations were unaltered in PA.

CONCLUSIONS

Primary aldosteronism is associated with lower concentrations of LDL and HDL particles and to some extent also with lower TG and TRL particle concentrations. PA is also characterized by increased GlycA levels, indicating enhanced low-grade chronic inflammation. Low HDL particle concentrations and increased GlycA could contribute to accelerated cardiovascular disease development in PA.

Effects of regular endurance exercise on GlycA: Combined analysis of 14 exercise interventions

BACKGROUND AND AIMS

GlycA is a relatively new biomarker for inflammation as well as cardiometabolic disease risk. However, the effect of exercise on GlycA is largely unknown. Therefore, the purpose of this study was to examine the effects of regular exercise on the inflammatory marker GlycA across seven studies and 14 exercise interventions.

METHODS

Nuclear magnetic resonance spectroscopy, specifically signal amplitudes originating from the N-acetyl methyl group protons of the N-acetylglucosamine residues on the glycan branches of glycoproteins, was used to quantify GlycA concentrations. GlycA was measured before and after completion of an exercise intervention in 1568 individuals across seven studies and 14 exercise interventions. Random effects inverse variance weighting models were used to pool effects across interventions.

RESULTS

Combined analysis of unadjusted data showed that regular exercise significantly (p = 2 × 10-6) reduced plasma GlycA (-8.26 ± 1.8 μmol/L). This reduction remained significant (-9.12 ± 1.9 μmol/L, p = 1.22 × 10-6) following adjustment for age, sex, race, baseline BMI, and baseline GlycA. Changes in GlycA were correlated with changes in traditional inflammatory markers, C-reactive protein, interleukin-6, and fibrinogen, however, these correlations were relatively weak (range r: 0.21-0.38, p < 0.0001).

CONCLUSIONS

Regular exercise significantly reduced plasma GlycA across 14 different exercise interventions despite differences in exercise programs and study populations. The current study provides a greater understanding of the use of exercise as a potential therapy for the reduction of systemic inflammation. Further research is needed to understand the mechanisms behind the exercise-related reductions in GlycA.

Plasma lecithin:cholesterol acyltransferase and phospholipid transfer protein activity independently associate with nonalcoholic fatty liver disease

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is a highly prevalent condition which contributes to atherogenic apolipoprotein B dyslipoproteinemias. Lecithin:cholesterol acyltransferase (LCAT) and phospholipid transfer protein (PLTP) are both synthesized by the liver and are important in lipid metabolism. Here, we interrogated the impact of NAFLD on plasma LCAT and PLTP activities.

METHODS

Plasma LCAT activity (exogenous substrate assay) and PLTP activity (phospholipid vesicles-HDL assay) were determined in 348 subjects (279 men; 81 subjects with type 2 diabetes (T2DM); 123 with metabolic syndrome (MetS)). A Fatty Liver Index (FLI) ≥60 was used as a proxy of NAFLD. Insulin resistance was determined by homoeostasis model assessment (HOMA-IR).

RESULTS

A total of 147 participants had an FLI ≥60 coinciding with T2DM and MetS (P < 0.001 for each). Plasma LCAT activity and PLTP activity were on average 12% and 5% higher, respectively, in subjects with an FLI ≥ 60 (P < 0.001 for each). In age- and sex-adjusted partial linear regression analysis, LCAT activity and PLTP activity were positively related to various obesity measures and HOMA-IR (P < 0.001 for each). In multivariable linear regression analyses adjusted for age and sex, LCAT activity was associated with an FLI ≥ 60 independent of T2DM and MetS, the waist/hip ratio, or HOMA-IR (β = 0.307 to 0.366, P < 0001 for all models). PLTP activity was also associated with an FLI ≥ 60 independent of these variables (β = 0.151 to 0223, P = 0.013 to 0.001).

CONCLUSION

NAFLD, as inferred from an FLI≥60, confers higher plasma LCAT and to a lesser extent PLTP activity, even when taking account of T2DM, MetS, central obesity and insulin resistance.

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.

Applications of high-resolution magic angle spinning MRS in biomedical studies I-cell line and animal models

High-resolution magic angle spinning (HRMAS) MRS allows for direct measurements of non-liquid tissue and cell specimens to present valuable insights into the cellular metabolisms of physiological and pathological processes. HRMAS produces high-resolution spectra comparable to those obtained from solutions of specimen extracts but without complex metabolite extraction processes, and preserves the tissue cellular structure in a form suitable for pathological examinations following spectroscopic analysis. The technique has been applied in a wide variety of biomedical and biochemical studies and become one of the major platforms of metabolomic studies. By quantifying single metabolites, metabolite ratios, or metabolic profiles in their entirety, HRMAS presents promising possibilities for diagnosis and prediction of clinical outcomes for various diseases, as well as deciphering of metabolic changes resulting from drug therapies or xenobiotic interactions. In this review, we evaluate HRMAS MRS results on animal models and cell lines reported in the literature, and present the diverse applications of the method for the understanding of pathological processes and the effectiveness of therapies, development of disease animal models, and new progress in HRMAS methodology.

Association of N-Linked Glycoprotein Acetyls and Colorectal Cancer Incidence and Mortality

Background

Acute phase proteins highlight the dynamic interaction between inflammation and oncogenesis. GlycA, a novel nuclear magnetic resonance (NMR) inflammatory marker that identifies primarily circulating N-acetyl glycan groups attached to acute phase proteins, may be a future CRC risk biomarker.

Methods

We examined the association between GlycA and incident CRC and mortality in two prospective cohorts (N = 34,320); Discovery cohort: 27,495 participants from Women's Health Study (WHS); Replication cohort: 6,784 participants from Multi-Ethnic Study of Atherosclerosis (MESA). Multivariable Cox models were adjusted for clinical risk factors and compared GlycA to acute phase proteins (high-sensitivity C-reactive protein [hsCRP], fibrinogen, and soluble intercellular adhesion molecule-1 [sICAM-1]).

Results

In WHS (median follow-up 19 years, 337 cases, 103 deaths), adjusted HRs (95% CIs) per SD increment of GlycA for CRC incidence and mortality were 1.19 (1.06–1.35; p = 0.004) and 1.24 (1.00–1.55; p = 0.05), respectively. We replicated findings in MESA (median follow-up 11 years, 70 cases, 23 deaths); HRs (95% CIs) per SD of GlycA for CRC incidence and mortality were 1.32 (1.06–1.65; p = 0.01) and 1.54 (1.06–2.23; p = 0.02), respectively, adjusting for age, sex, and race. Pooled analysis, adjusted HR (95% CI) per SD of GlycA for CRC incidence and mortality was 1.26 (1.15–1.39; p = 1 x 10⁻⁶). Other acute phase proteins (hsCRP, fibrinogen, and sICAM-1) had weaker or no association with CRC incidence, while only fibrinogen and GlycA were associated with CRC mortality.

Conclusions

The clinical utility of GlycA to personalize CRC therapies or prevention warrants further study.

Trial Registration

ClinicalTrials.gov: WHS NCT00000479, MESA NCT00005487

gFinder: A Web-Based Bioinformatics Tool for the Analysis of N-Glycopeptides

Glycoproteins influence numerous indispensable biological functions, and changes in protein glycosylation have been observed in various diseases. The identification and characterization of glycoprotein and glycosylation sites by mass spectrometry (MS) remain challenging tasks, and great efforts have been devoted to the development of proteome informatics tools that facilitate the MS analysis of glycans and glycopeptides. Here we report on the development of gFinder, a web-based bioinformatics tool that analyzes mixtures of native N-glycopeptides that have been profiled by tandem MS. gFinder not only enables the simultaneous integration of collision-induced dissociation (CID) and high-energy collisional dissociation (HCD) fragmentation but also merges the spectra for high-throughput analysis. These merged spectra expedite the identification of both glycans and N-glycopeptide backbones in tandem MS data using the glycan database and a proteomic search tool (e.g., Mascot). These data can be used to simultaneously characterize peptide backbone sequences and possible N-glycan structures using assigned scores. gFinder also provides many convenient functions that make it easy to perform manual calculations while viewing the spectrum on-screen. We used gFinder to detect an additional protein (Q8N9B8) that was missed from the previously published data set containing N-linked glycosylation. For N-glycan analysis, we used the GlycomeDB glycan structure database, which integrates the structural and taxonomic data from all of the major carbohydrate databases available in the public domain. Thus, gFinder is a convenient, high-throughput analytical tool for interpreting the tandem mass spectra of N-glycopeptides, which can then be used for identification of potential missing proteins having glycans. gFinder is available publicly at http://gFinder.proteomix.org/ .

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.

Higher circulating GlycA, a pro-inflammatory glycoprotein biomarker, relates to lipoprotein-associated phospholipase A2 mass in nondiabetic subjects but not in diabetic or metabolic syndrome subjects

BACKGROUND

Lipoprotein-associated phospholipase A2 (Lp-PLA2) is a cardiovascular risk marker, which is in part complexed to low-density lipoproteins, where it exerts pro-inflammatory properties. GlycA is a pro-inflammatory proton nuclear magnetic resonance spectroscopy biomarker whose signal originates from a subset of N-acetylglucosamine residues on the most abundant glycosylated acute-phase proteins.

OBJECTIVE

We compared plasma GlycA and Lp-PLA2 mass between subjects without type 2 diabetes mellitus (T2DM) or the metabolic syndrome (MetS) and subjects with T2DM and/or MetS. We also tested the relationship of GlycA with Lp-PLA2 in each group.

METHODS

Plasma GlycA, Lp-PLA2 mass, high-sensitivity C-reactivity protein (hsCRP) and lipids were measured in 40 subjects with neither T2DM nor MetS (group 1) and in 58 subjects with T2DM and/or MetS (group 2).

RESULTS

GlycA and hsCRP were higher (P < .01 for each), whereas Lp-PLA2 was lower in group 2 vs group 1 (P < .001). GlycA was positively related to hsCRP in each group (P < .001). In contrast, GlycA was correlated positively with Lp-PLA2 in group 1 (r = 0.384, P = .015), but not in group 2 (r = 0.045; P = .74; interaction term for difference: P = .059). Although Lp-PLA2 was correlated positively with non-high-density lipoprotein cholesterol and low-density lipoprotein cholesterol in each group (P ≤ .02), its inverse relationship with high-density lipoprotein cholesterol in group 1 (r = -0.381, P = .013) was absent in group 2 (r = -0.101, P = .42).

CONCLUSIONS

A pro-inflammatory glycoprotein biomarker, GlycA, is higher in subjects with either T2DM, MetS, or both. The normally present positive relationship of GlycA with Lp-PLA2 is blunted in subjects with T2DM and/or MetS.

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.