GlycA, a Nuclear Magnetic Resonance Spectroscopy Measure for Protein Glycosylation, is a Viable Biomarker for Disease Activity in IBD

Peripheral inflammation is associated with brain atrophy and cognitive decline linked to mild cognitive impairment and Alzheimer's disease

Inflammation is an important factor in Alzheimer's disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD. However, the associations between GlycA and these brain changes have not been fully evaluated. Here, we performed Spearman's correlation analyses to evaluate these associations cross-sectionally and determined whether GlycA can inform AD-relevant longitudinal measurements among participants in the Alzheimer's Disease Neuroimaging Initiative (n = 1506), with additional linear models and stratification analyses to evaluate the influences of sex or diagnosis status and confirm findings from Spearman's correlation analyses. We found that GlycA was elevated in AD patients compared to cognitively normal participants. GlycA correlated negatively with multiple concurrent regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD. Baseline GlycA level was associated with executive function decline at 3-9 year follow-up in participants diagnosed with LMCI at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. Results here indicated that GlycA is an inflammatory biomarker relevant to AD pathogenesis and that the stage of LMCI might be relevant to inflammation-related intervention.

Explainable AI-prioritized plasma and fecal metabolites in inflammatory bowel disease and their dietary associations

Fecal metabolites effectively discriminate inflammatory bowel disease (IBD) and show differential associations with diet. Metabolomics and AI-based models, including explainable AI (XAI), play crucial roles in understanding IBD. Using datasets from the UK Biobank and the Human Microbiome Project Phase II IBD Multi'omics Database (HMP2 IBDMDB), this study uses multiple machine learning (ML) classifiers and Shapley additive explanations (SHAP)-based XAI to prioritize plasma and fecal metabolites and analyze their diet correlations. Key findings include the identification of discriminative metabolites like glycoprotein acetyl and albumin in plasma, as well as nicotinic acid metabolites andurobilin in feces. Fecal metabolites provided a more robust disease predictor model (AUC [95%]: 0.93 [0.87-0.99]) compared to plasma metabolites (AUC [95%]: 0.74 [0.69-0.79]), with stronger and more group-differential diet-metabolite associations in feces. The study validates known metabolite associations and highlights the impact of IBD on the interplay between gut microbial metabolites and diet.

Challenges in IBD Research 2024: Precision Medicine

Precision medicine is part of 5 focus areas of the Challenges in IBD Research 2024 research document, which also includes preclinical human IBD mechanisms, environmental triggers, novel technologies, and pragmatic clinical research. Building on Challenges in IBD Research 2019, the current Challenges aims to provide a comprehensive overview of current gaps in inflammatory bowel diseases (IBDs) research and deliver actionable approaches to address them with a focus on how these gaps can lead to advancements in interception, remission, and restoration for these diseases. The document is the result of multidisciplinary input from scientists, clinicians, patients, and funders, and represents a valuable resource for patient-centric research prioritization. In particular, the precision medicine section is focused on the main research gaps in elucidating how to bring the best care to the individual patient in IBD. Research gaps were identified in biomarker discovery and validation for predicting disease progression and choosing the most appropriate treatment for each patient. Other gaps were identified in making the best use of existing patient biosamples and clinical data, developing new technologies to analyze large datasets, and overcoming regulatory and payer hurdles to enable clinical use of biomarkers. To address these gaps, the Workgroup suggests focusing on thoroughly validating existing candidate biomarkers, using best-in-class data generation and analysis tools, and establishing cross-disciplinary teams to tackle regulatory hurdles as early as possible. Altogether, the precision medicine group recognizes the importance of bringing basic scientific biomarker discovery and translating it into the clinic to help improve the lives of IBD patients.

GlycA: Evaluation of a New Biomarker of Acute Pancreatitis

BACKGROUND

Acute pancreatitis (AP) is a leading cause of gastrointestinal hospital admissions, with up to 40% mortality in patients with moderate-severe AP. Glycoprotein acetylation (GlycA) is measured as a nuclear magnetic resonance signal (NMR) of the post-translational modification of glycosylated acute-phase proteins released during inflammation. We aimed to investigate the role of GlycA as an inflammatory biomarker of AP.

METHODS

We prospectively enrolled 20 AP patients and 22 healthy controls and collected EDTA plasma samples at admission and discharge. NMR spectra were acquired from these samples using a 400 MHz Vantera® Clinical Analyzer, and GlycA concentrations were calculated (normal = 400 μmol/L). The GlycA NMR signal, at 2.00 ± 0.01 ppm in the NMR spectrum, is derived from the N-acetyl methyl group protons within the carbohydrate side chains of circulating glycoproteins such as α1-acid glycoprotein, haptoglobin, α1-antitrypsin, α1-antichymotrypsin, and transferrin. GlycA levels were then compared between AP patients and controls, as well as within the AP group, based on etiology and severity.

RESULTS

Demographic comparisons were similar, except for a higher BMI in AP patients compared to healthy controls (29.9 vs. 24.8 kg/m2; p < 0.001). AP was mild in 10 patients, moderate in 7, and severe in 3. GlycA levels were higher in AP patients than healthy controls on admission (578 vs. 376 μmol/L, p < 0.001) and at discharge (655 vs. 376 μmol/L, p < 0.001). GlycA levels were significantly higher in patients with moderate-severe AP than in those with mild AP at discharge (533 vs. 757 μmol/L, p = 0.023) but not at admission. After adjusting for BMI, multivariable regression indicated that patients with GlycA levels > 400 μmol/L had significantly higher odds of having AP of any severity (OR = 6.88; 95% CI, 2.07-32.2; p = 0.004) and mild AP (OR = 6.12; 95% CI, 1.48-42.0; p = 0.025) than controls.

CONCLUSION

Our pilot study highlights the use of GlycA as a novel diagnostic biomarker of inflammation in patients with AP. Our study shows that GlycA levels were significantly higher in hospitalized AP patients compared to healthy controls. Patients with moderate-to-severe AP had higher GlycA levels compared to patients with mild AP at the time of their hospital discharge, suggesting persistent inflammation in patients with severe disease.

Choosing the Right Therapy at the Right Time for Pediatric Inflammatory Bowel Disease: Does Sequence Matter

Despite the enlarging therapeutic armamentarium, IBD is still plagued by a therapeutic ceiling. Precision medicine, with the selection of the "rights," may present a solution, and this review will discuss the critical process of pairing the right patient with right therapy at the right time. Firstly, the review will discuss the shift to and evidence behind early effective therapy. Then, it delves into promising future strategies of patient profiling to identify a patients' biological pathway(s) and prognosis. Finally, the review lays out practical considerations that drive treatment selection, particularly the impact of the therapeutic sequence.

Plasma protein N-glycome composition associates with postprandial lipaemic response

BACKGROUND

A dysregulated postprandial metabolic response is a risk factor for chronic diseases, including type 2 diabetes mellitus (T2DM). The plasma protein N-glycome is implicated in both lipid metabolism and T2DM risk. Hence, we first investigate the relationship between the N-glycome and postprandial metabolism and then explore the mediatory role of the plasma N-glycome in the relationship between postprandial lipaemia and T2DM.

METHODS

We included 995 individuals from the ZOE-PREDICT 1 study with plasma N-glycans measured by ultra-performance liquid chromatography at fasting and triglyceride, insulin, and glucose levels measured at fasting and following a mixed-meal challenge. Linear mixed models were used to investigate the associations between plasma protein N-glycosylation and metabolic response (fasting, postprandial (Cmax), or change from fasting). A mediation analysis was used to further explore the relationship of the N-glycome in the prediabetes (HbA1c = 39-47 mmol/mol (5.7-6.5%))-postprandial lipaemia association.

RESULTS

We identified 36 out of 55 glycans significantly associated with postprandial triglycerides (Cmax β ranging from -0.28 for low-branched glycans to 0.30 for GP26) after adjusting for covariates and multiple testing (padjusted < 0.05). N-glycome composition explained 12.6% of the variance in postprandial triglycerides not already explained by traditional risk factors. Twenty-seven glycans were also associated with postprandial glucose and 12 with postprandial insulin. Additionally, 3 of the postprandial triglyceride-associated glycans (GP9, GP11, and GP32) also correlate with prediabetes and partially mediate the relationship between prediabetes and postprandial triglycerides.

CONCLUSIONS

This study provides a comprehensive overview of the interconnections between plasma protein N-glycosylation and postprandial responses, demonstrating the incremental predictive benefit of N-glycans. We also suggest a considerable proportion of the effect of prediabetes on postprandial triglycerides is mediated by some plasma N-glycans.

Glycoprotein Serum Concentrations Assessed By 1H-NMR are Increased in Patients With High Blood Pressure

BACKGROUND

Patients with hypertension present a permanent state of low-grade inflammation, as the disease activates several pro-inflammatory cells and inflammatory pathways. Glycoproteins A, B, and F, determined by proton nuclear magnetic resonance, provide a highly sensitive method for determining a group of liver-derived pro-inflammatory proteins, and their role has not yet been explored in patients with hypertension. In this study, we evaluated the impact of plasma concentrations of these glycoproteins in patients with hypertension.

METHODS

This cross-sectional study involved 340 patients attending our vascular and metabolism medicine unit. Of them, 129 were normotensive and 211 were hypertensive. Standard biochemistry and carotid ultrasound measures were performed. Serum concentrations of glycoproteins A, B, and F were determined by proton nuclear magnetic resonance.

RESULTS

Hypertensive patients presented a higher prevalence of obesity, metabolic syndrome, and diabetes and higher glycoprotein A, B, and F concentrations. Glycoproteins A, B, and F were positively correlated with systolic and diastolic blood pressure. Multivariate logistic models showed that glycoproteins A, B, and F were associated with higher odds of being hypertensive. Machine learning methods corroborated the relationship between glycoproteins and high blood pressure. The higher prevalence of carotid plaques in patients with high blood pressure was partially mediated by glycoproteins A and F.

CONCLUSIONS

Patients with hypertension present systemic, subclinical inflammation as assessed by liver-derived glycoprotein A, B, and F serum levels. These results support the effect of hypertension on the mechanisms of systemic inflammation. Hypertension-associated systemic inflammation plays a role in hypertension-associated vascular injury and probably in hypertension-induced damage to other organs.

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.

Systemic cytokines and GlycA discriminate disease status and predict corticosteroid response in HTLV-1-associated neuroinflammation

BACKGROUND

HTLV-1-Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP) is an incapacitating neuroinflammatory disorder for which no disease-modifying therapy is available, but corticosteroids provide some clinical benefit. Although HAM/TSP pathogenesis is not fully elucidated, older age, female sex and higher proviral load are established risk factors. We investigated systemic cytokines and a novel chronic inflammatory marker, GlycA, as possible biomarkers of immunopathogenesis and therapeutic response in HAM/TSP, and examined their interaction with established risk factors.

PATIENTS AND METHODS

We recruited 110 People living with HTLV-1 (PLHTLV-1, 67 asymptomatic individuals and 43 HAM/TSP patients) with a total of 946 person-years of clinical follow-up. Plasma cytokine levels (IL-2, IL-4, IL-6, IL-10, IL-17A, IFN-γ, TNF) and GlycA were quantified by Cytometric Bead Array and 1NMR, respectively. Cytokine signaling and prednisolone response were validated in an independent cohort by nCounter digital transcriptomics. We used multivariable regression, machine learning algorithms and Bayesian network learning for biomarker identification.

RESULTS

We found that systemic IL-6 was positively correlated with both age (r = 0.50, p < 0.001) and GlycA (r = 0.45, p = 0.00049) in asymptomatics, revealing an 'inflammaging" signature which was absent in HAM/TSP. GlycA levels were higher in women (p = 0.0069), but cytokine levels did not differ between the sexes. IFN-γ (p = 0.007) and IL-17A (p = 0.0001) levels were increased in untreated HAM/TSP Multivariable logistic regression identified IL-17A and proviral load as independent determinants of clinical status, resulting in modest accuracy of predicting HAM/TSP status (64.1%), while a machine learning-derived decision tree classified HAM/TSP patients with 90.7% accuracy. Pre-treatment GlycA and TNF levels significantly predicted clinical worsening (measured by Osame Motor Disability Scale), independent of proviral load. In addition, a poor prednisolone response was significantly correlated with higher post-treatment IFN-γ levels. Likewise, a transcriptomic IFN signaling score, significantly correlated with previously proposed HAM/TSP biomarkers (CASP5/CXCL10/FCGR1A/STAT1), was efficiently blunted by in vitro prednisolone treatment of PBMC from PLHTLV-1 and incident HAM/TSP.

CONCLUSIONS

An age-related increase in systemic IL-6/GlycA levels reveals inflammaging in PLHTLV-1, in the absence of neurological disease. IFN-γ and IL-17A are biomarkers of untreated HAM/TSP, while pre-treatment GlycA and TNF predict therapeutic response to prednisolone pulse therapy, paving the way for a precision medicine approach in HAM/TSP.

Prognostication in inflammatory bowel disease

Personalized care in inflammatory bowel diseases (IBD) hinges on parsing the heterogeneity of IBD patients through prognostication of their disease course and therapeutic response to allow for tailor-made treatment and monitoring strategies to optimize care. Herein we review the currently available predictors of outcomes in IBD and those on the both near and far horizons. We additionally discuss the importance of worldwide collaborative efforts and tools to support clinical use of these prognostication tools.

Evidence of a genetically driven metabolomic signature in actively inflamed Crohn's disease

Crohn's disease (CD) is characterised by chronic inflammation. We aimed to identify a relationship between plasma inflammatory metabolomic signature and genomic data in CD using blood plasma metabolic profiles. Proton NMR spectroscopy were achieved for 228 paediatric CD patients. Regression (OPLS) modelling and machine learning (ML) approaches were independently applied to establish the metabolic inflammatory signature, which was correlated against gene-level pathogenicity scores generated for all patients and functional enrichment was analysed. OPLS modelling of metabolomic spectra from unfasted patients revealed distinctive shifts in plasma metabolites corresponding to regions of the spectrum assigned to N-acetyl glycoprotein, glycerol and phenylalanine that were highly correlated (R² = 0.62) with C-reactive protein levels. The same metabolomic signature was independently identified using ML to predict patient inflammation status. Correlation of the individual peaks comprising this metabolomic signature of inflammation with pathogenic burden across 15,854 unselected genes identified significant enrichment for genes functioning within 'intrinsic component of membrane' (p = 0.003) and 'inflammatory bowel disease (IBD)' (p = 0.003). The seven genes contributing IBD enrichment are critical regulators of pro-inflammatory signaling. Overall, a metabolomic signature of inflammation can be detected from blood plasma in CD. This signal is correlated with pathogenic mutation in pro-inflammatory immune response genes.

Emerging role of protein modification in inflammatory bowel disease

The onset of inflammatory bowel disease (IBD) involves many factors, including environmental parameters, microorganisms, and the immune system. Although research on IBD continues to expand, the specific pathogenesis mechanism is still unclear. Protein modification refers to chemical modification after protein biosynthesis, also known as post-translational modification (PTM), which causes changes in the properties and functions of proteins. Since proteins can be modified in different ways, such as acetylation, methylation, and phosphorylation, the functions of proteins in different modified states will also be different. Transitions between different states of protein or changes in modification sites can regulate protein properties and functions. Such modifications like neddylation, sumoylation, glycosylation, and acetylation can activate or inhibit various signaling pathways (e.g., nuclear factor-‍κB (NF-‍κB), extracellular signal-regulated kinase (ERK), and protein kinase B (AKT)) by changing the intestinal flora, regulating immune cells, modulating the release of cytokines such as interleukin-1β (IL-‍‍1β), tumor necrosis factor-α (TNF‍-‍α), and interferon-‍γ (IFN-‍γ), and ultimately leading to the maintenance of the stability of the intestinal epithelial barrier. In this review, we focus on the current understanding of PTM and describe its regulatory role in the pathogenesis of IBD.

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.

An Overview of Glycosylation and its Impact on Cardiovascular Health and Disease

The cardiovascular system is a complex and well-organized system in which glycosylation plays a vital role. The heart and vascular wall cells are constituted by an array of specific receptors; most of them are N- glycosylated and mucin-type O-glycosylated. There are also intracellular signaling pathways regulated by different post-translational modifications, including O-GlcNAcylation, which promote adequate responses to extracellular stimuli and signaling transduction. Herein, we provide an overview of N-glycosylation and O-glycosylation, including O-GlcNAcylation, and their role at different levels such as reception of signal, signal transduction, and exogenous molecules or agonists, which stimulate the heart and vascular wall cells with effects in different conditions, like the physiological status, ischemia/reperfusion, exercise, or during low-grade inflammation in diabetes and aging. Furthermore, mutations of glycosyltransferases and receptors are associated with development of cardiovascular diseases. The knowledge on glycosylation and its effects could be considered biochemical markers and might be useful as a therapeutic tool to control cardiovascular diseases.

Randomized Trial: D-Glyceric Acid Activates Mitochondrial Metabolism in 50–60-Year-Old Healthy Humans

Background: Based on earlier studies, natural metabolite D-glyceric acid (DGA) does not seem to play any role in whole-body metabolism. Nevertheless, one ethanol oxidation-related rat study with controversial results raised our interest. According to preparatory studies for the regulatory approval of DGA, some highly conserved mechanism seems to subtly activate the cellular energy metabolism. Therefore, the present 25-days double-blind human study with placebo control was initiated.

Purpose: The main target in the present study with 27 healthy 50–60-year-old human volunteers was to find out whether an “acute” 4-days and a longer 21-days exogenous DGA regimen caused moderate activation of the mitochondrial energy metabolism. The simultaneous target was to find out whether a halved dose of DGA continued to be an effective regimen.

Main Findings: The results revealed the following statistically significant findings: 1) plasma concentrations of metabolites related to aerobic energy production, especially lactate, were strongly reduced, 2) systemic inflammation was lowered both in 4- and 21-days, 3) mitochondria-related mRNA expressions in circulating immune cells were noticeably modulated at Day4, 4) cellular membrane integrity seemed to be sharply enhanced, and 5) cellular NADH/NAD⁺ -ratio was upregulated.

Conclusion: Mitochondrial metabolism was clearly upregulated at the whole-body level in both 4- and 21 days. At the same time, the effect of DGA was very well tolerated. Based on received solid results, the DGA regimen may alleviate acute and chronic energy metabolic challenges in main organs like the liver, CNS, and skeletal muscles. Enhanced membrane integrity combined with lower systemic inflammation and activated metabolic flows by the DGA regimen may be beneficial especially for the aging population.

Quantification of glycoproteins by nuclear magnetic resonance associated with preclinical carotid atherosclerosis in patients with type 1 diabetes

BACKGROUND AND AIMS

Glycoproteins play a key role in inflammatory and cardiometabolic processes. Their implication in atherosclerosis in type 1 diabetes (T1D) is unknown. We assessed the relationships between classic inflammatory markers, glycoproteins measured by nuclear magnetic resonance (¹H-NMR), and preclinical atherosclerosis in these patients.

METHODS AND RESULTS

We selected patients with T1D, without cardiovascular disease (CVD), with: age ≥40 years, nephropathy (micro/macroalbuminuria), or ≥10 years of evolution with another risk factor. The presence of plaque (intima-media thickness >1.5 mm) was determined by ultrasonography. Concentrations of high-sensitive C-reactive protein (hsCRP), circulating leukocytes (classical inflammation markers) and ¹H-NMR-glycoproteins (GlycA, GlycB, GlycF, and the height/width [H/W] ratios of GlycA and GlycB) were determined. We included 189 patients (58% male, age 47.0 [40.7-55.2] years). Thirty-five percent presented plaques (22%, ≥2 plaques). There was no association between hsCRP or leukocytes and atherosclerosis. However, in age- and sex-adjusted models, GlycA, GlycF, and the H/W ratios of GlycA and GlycB gradually increased with the number of plaques (0, 1, ≥2 plaques) only in patients without statins (p < 0.05), with no association in patients receiving this drug (p for interaction <0.05; in ≥2 plaques). Finally, in models adjusted for other classical and T1D-specific risk factors, GlycA and GlycB H/W ratios remained associated with carotid plaque (OR 1.39 [1.12-1.90] and OR 6.89 [1.85-25.62], respectively).

CONCLUSION

In T1D individuals without lipid-lowering treatment, ¹H-NMR-glycoproteins were independently associated with the presence and amount of carotid atherosclerosis, unlike other classical inflammatory markers. Further studies are needed to ascertain their utility as CVD biomarkers.

Surrogate markers of mucosal healing in inflammatory bowel disease: A systematic review

BACKGROUND

Mucosal healing (MH) has emerged as a key therapeutic target in inflammatory bowel disease (IBD), and achievement of this goal is documented by endoscopy with biopsy. However, colonoscopy is burdensome and invasive, and substitution with an accurate noninvasive biomarker is desirable.

AIM

To summarize published data regarding the performance of noninvasive biomarkers in assessing MH in IBD patients.

METHODS

We conducted a systematic review of studies that reported the performance of biomarkers in diagnosing MH in patients with IBD. The main outcome measure was to review the diagnostic accuracy of serum and fecal markers that showed promising utility in assessing MH.

RESULTS

We screened 1301 articles, retrieved 46 manuscripts and included 23 articles for full-text analysis. The majority of the included manuscripts referred to fecal markers (12/23), followed by circulatory markers (8/23); only 3/23 of the included manuscripts investigated combined markers (serum and/or fecal markers). Fecal calprotectin (FC) was the most investigated fecal marker for assessing MH. In ulcerative colitis, for cutoff levels ranging between 58 mcg/g and 490 mcg/g, the sensitivity was 89.7%-100% and the specificity was 62%-93.3%. For Crohn’s disease, the cutoff levels of FC ranged from 71 mcg/g to 918 mcg/g (sensitivity 50%-95.9% and specificity 52.3%-100%). The best performance for a serum marker was observed for the endoscopic healing index, which showed a comparable accuracy to the measurement of FC and a higher accuracy than the measurement of serum C-reactive protein.

CONCLUSION

Several promising biomarkers of MH are emerging but cannot yet substitute for endoscopy with biopsy due to issues with reproducibility and standardization.

Metabolomic profiling reveals plasma GlycA and GlycB as a potential biomarkers for treatment efficiency in rheumatoid arthritis

In this pilot study, we carried out metabolic profiling of patients with rheumatoid arthritis (RA) starting therapy with biological disease-modifying antirheumatic drugs (bDMARDs). The main aim of the study was to assess the occurring metabolic changes associated with therapy success and metabolic pathways involved. In particular, the potential of the metabolomics profiles was evaluated as therapeutically valuable prognostic indicators of the effectiveness of bDMARD treatment to identify responders versus non-responders prior to implementing treatment. Plasma metabolomic profiles of twenty-five patients with RA prior bDMARD treatment and after three months of therapy were obtained by ¹H NMR, liquid chromatography - mass spectrometry, and gas chromatography - mass spectrometry and evaluated by statistical and multivariate analyses. In the group of responders, significant differences in their metabolic patterns were seen after three months of the bDMARD therapy compared with profiles prior to treatment. We identified 24 metabolites that differed significantly between these two-time points mainly belonging to amino acid metabolism, peptides, lipids, cofactors, and vitamins and xenobiotics. Eleven metabolites differentiated responders versus non-responders before treatment. Additionally, N-acetylglucosamine and N-acetylgalactosamine (GlycA) and N-acetylneuraminic acid (GlycB) persisted significant in comparison responders to non-responders after three months of therapy. Moreover, those two metabolites indicated prediction of response potential by results of receiver-operating characteristic (ROC) curve analysis. The applied analysis provides novel insights into the metabolic pathways involved in RA patient's response to bDMARD and therapy effectiveness. GlycA and GlycB are promising biomarkers to identify responding patients prior onset of bDMARD therapy.

NMR Spectroscopic Windows on the Systemic Effects of SARS-CoV-2 Infection on Plasma Lipoproteins and Metabolites in Relation to Circulating Cytokines

To investigate the systemic metabolic effects of SARS-CoV-2 infection, we analyzed 1H NMR spectroscopic data on human blood plasma and co-modeled with multiple plasma cytokines and chemokines (measured in parallel). Thus, 600 MHz 1H solvent-suppressed single-pulse, spin-echo, and 2D J-resolved spectra were collected on plasma recorded from SARS-CoV-2 rRT-PCR-positive patients (n = 15, with multiple sampling timepoints) and age-matched healthy controls (n = 34, confirmed rRT-PCR negative), together with patients with COVID-19/influenza-like clinical symptoms who tested SARS-CoV-2 negative (n = 35). We compared the single-pulse NMR spectral data with in vitro diagnostic research (IVDr) information on quantitative lipoprotein profiles (112 parameters) extracted from the raw 1D NMR data. All NMR methods gave highly significant discrimination of SARS-CoV-2 positive patients from controls and SARS-CoV-2 negative patients with individual NMR methods, giving different diagnostic information windows on disease-induced phenoconversion. Longitudinal trajectory analysis in selected patients indicated that metabolic recovery was incomplete in individuals without detectable virus in the recovery phase. We observed four plasma cytokine clusters that expressed complex differential statistical relationships with multiple lipoproteins and metabolites. These included the following: cluster 1, comprising MIP-1β, SDF-1α, IL-22, and IL-1α, which correlated with multiple increased LDL and VLDL subfractions; cluster 2, including IL-10 and IL-17A, which was only weakly linked to the lipoprotein profile; cluster 3, which included IL-8 and MCP-1 and were inversely correlated with multiple lipoproteins. IL-18, IL-6, and IFN-γ together with IP-10 and RANTES exhibited strong positive correlations with LDL1-4 subfractions and negative correlations with multiple HDL subfractions. Collectively, these data show a distinct pattern indicative of a multilevel cellular immune response to SARS CoV-2 infection interacting with the plasma lipoproteome giving a strong and characteristic immunometabolic phenotype of the disease. We observed that some patients in the respiratory recovery phase and testing virus-free were still metabolically highly abnormal, which indicates a new role for these technologies in assessing full systemic recovery.

The Role of Glycosylation in Inflammatory Diseases

The diversity of glycan presentation in a cell, tissue and organism is enormous, which reflects the huge amount of important biological information encoded by the glycome which has not been fully understood. A compelling body of evidence has been highlighting the fundamental role of glycans in immunity, such as in development, and in major inflammatory processes such as inflammatory bowel disease, systemic lupus erythematosus and other autoimmune disorders. Glycans play an instrumental role in the immune response, integrating the canonical circuits that regulate innate and adaptive immune responses. The relevance of glycosylation in immunity is demonstrated by the role of glycans as important danger-associated molecular patterns and pathogen-associated molecular patterns associated with the discrimination between self and non-self; also as important regulators of the threshold of T cell activation, modulating receptors signalling and the activity of both T and other immune cells. In addition, glycans are important determinants that regulate the dynamic crosstalk between the microbiome and immune response. In this chapter, the essential role of glycans in the immunopathogenesis of inflammatory disorders will be presented and its potential clinical applications (diagnosis, prognosis and therapeutics) will be highlighted.

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.

Probabilistic identification of saccharide moieties in biomolecules and their protein complexes

The chemical composition of saccharide complexes underlies their biomedical activities as biomarkers for cardiometabolic disease, various types of cancer, and other conditions. However, because these molecules may undergo major structural modifications, distinguishing between compounds of saccharide and non-saccharide origin becomes a challenging computational problem that hinders the aggregation of information about their bioactive moieties. We have developed an algorithm and software package called "Cheminformatics Tool for Probabilistic Identification of Carbohydrates" (CTPIC) that analyzes the covalent structure of a compound to yield a probabilistic measure for distinguishing saccharides and saccharide-derivatives from non-saccharides. CTPIC analysis of the RCSB Ligand Expo (database of small molecules found to bind proteins in the Protein Data Bank) led to a substantial increase in the number of ligands characterized as saccharides. CTPIC analysis of Protein Data Bank identified 7.7% of the proteins as saccharide-binding. CTPIC is freely available as a webservice at (http://ctpic.nmrfam.wisc.edu).

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.

Serum GlycA Level is Elevated in Active Systemic Lupus Erythematosus and Correlates to Disease Activity and Lupus Nephritis Severity

Objective: Reliable non-invasive biomarkers are needed to assess disease activity and prognosis in patients with systemic lupus erythematosus (SLE). Glycoprotein acetylation (GlycA), a novel biomarker for chronic inflammation, has been reported to be increased in several inflammatory diseases. We investigated the relevance of serum GlycA in SLE patients exhibiting various levels of activity and severity, especially with regards to renal involvement. Methods: Serum GlycA was measured by nuclear magnetic resonance spectroscopy in samples from well characterized SLE patients and from both healthy controls and patients with other kidney diseases (KD). Disease activity was evaluated using the Systemic Lupus Erythematosus Activity Index 2000 (SLEDAI-2K). Renal severity was assessed by kidney biopsy. Results: Serum GlycA was elevated in active (n = 105) compared to quiescent SLE patients (n = 39, p < 10⁻⁶), healthy controls (n = 20, p = 0.009) and KD controls (n = 21, p = 0.04), despite a more severely altered renal function in the latter. GlycA level was correlated to disease activity (SLEDAI-2K, ρ = 0.37, p < 10⁻⁴), C-reactive protein, neutrophil count, triglyceride levels, proteinuria and inversely to serum albumin. In patients with biopsy-proven lupus nephritis (LN), GlycA levels were higher in proliferative (n = 26) than non-proliferative LN (n = 10) in univariate analysis (p = 0.04), and was shown to predict proliferative LN independently of renal parameters, immunological activity, neutrophil count and daily corticosteroid dosage by multivariate analysis (p < 5 × 10⁻³ for all models). In LN patients with repeated longitudinal GlycA measurement (n = 11), GlycA varied over time and seemed to peak at the time of the flare. Conclusions: GlycA, as a summary measure for different inflammatory processes, could be a valuable biomarker of disease activity in patients with SLE, and a non-invasive biomarker of pathological severity in the context of LN.

Precision medicine in inflammatory bowel disease: concept, progress and challenges

Crohn's disease and ulcerative colitis are increasingly prevalent, relapsing and remitting inflammatory bowel diseases (IBDs) with variable disease courses and complications. Their aetiology remains unclear but current evidence shows an increasingly complex pathophysiology broadly centring on the genome, exposome, microbiome and immunome. Our increased understanding of disease pathogenesis is providing an ever-expanding arsenal of therapeutic options, but these can be expensive and patients can lose response or never respond to certain therapies. Therefore, there is now a growing need to personalise therapies on the basis of the underlying disease biology and a desire to shift our approach from "reactive" management driven by disease complications to "proactive" care with an aim to prevent disease sequelae. Precision medicine is the tailoring of medical treatment to the individual patient, encompassing a multitude of data-driven (and multi-omic) approaches to foster accurate clinical decision-making. In IBD, precision medicine would have significant benefits, enabling timely therapy that is both effective and appropriate for the individual. In this review, we summarise some of the key areas of progress towards precision medicine, including predicting disease susceptibility and its course, personalising therapies in IBD and monitoring response to therapy. We also highlight some of the challenges to be overcome in order to deliver this approach.

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.

Decreased expression of MUC2 due to a decrease in the expression of lectins and apoptotic defects in colitis patients

INTRODUCTION

The involvement of mucin, lectin, and apoptosis in colitis is still unclear. This study aimed to investigate changes in MUC2 expression, inflammation, and changes in lectin expression in colitis patients.

METHODS

A total of 17 patients were divided into two groups including 11 hemorrhoid patients as a control group and 6 colitis patients. MUC2 mutation analysis was carried out using immunofluorescent and FISH techniques. Assessment of caspase-3, Ki-67, NF-kB, and lectin expressions was also carried out by immunofluorescent technique then analyzed by confocal laser scanning microscope.

RESULTS

The MUC2, caspase-3, and lectin expressions were significantly lower in the colitis group than in the control group (p < 0.05).

CONCLUSIONS

It was concluded that in colitis there was a change in MUC2 expression due to changes in lectins accompanied by apoptotic defects.conclusion.

Inflammatory bowel disease - glycomics perspective

BACKGROUND

Inflammatory bowel disease (IBD) pathogenesis is still not well understood. It is considered to result from genetic susceptibility, environment, microbiota composition and aberrant immune response. Crohn's disease (CD) and ulcerative colitis (UC), forms of IBD, are sometimes indistinguishable by typical laboratory and clinical characteristics making timely diagnosis and subsequent therapy hit-and-miss. Glycosylation has shown a promising biomarker potential for early IBD diagnosis and effective response to treatment prediction.

SCOPE OF REVIEW

This mini-review briefly covers present knowledge of IBD pathophysiology, with a focus on recent research on the role of glycosylation in IBD pathogenesis and disease progression.

MAJOR CONCLUSIONS

Aberrant glycosylation significantly changes functionality of key proteins in intestinal niche and is involved in IBD etiology.

GENERAL SIGNIFICANCE

Elucidating mechanisms of IBD development is one of critical goals in managing this disease. Glycans are important for fine-tuning of intestinal processes that ensure homeostatic conditions which, if disrupted, lead to IBD.