Screening novel biomarkers for metabolic syndrome by profiling human plasma N-glycans in Chinese Han and Croatian populations

Human complement component C3 N-glycome changes in type 1 diabetes complications

Aim

Changes in N-glycosylation have been described in numerous diseases and are being considered as biomarkers of ongoing pathological condition. Previous studies demonstrated the interrelation of N-glycosylation and type 1 diabetes (T1D), particularly linking serum N-glycan changes with complications accompanying the disease. Moreover, the role of complement component C3 in diabetic nephropathy and retinopathy has been implicated, and C3 N-glycome was found to be altered in young T1D patients. Therefore, we investigated associations between C3 N-glycan profiles and albuminuria and retinopathy accompanying T1D, as well as glycosylation connection with other known T1D complication risk factors.

Research design and methods

Complement component C3 N-glycosylation profiles have been analyzed from 189 serum samples of T1D patients (median age 46) recruited at a Croatian hospital centre. Using our recently developed high-throughput method, relative abundances of all six of the C3 glycopeptides have been determined. Assessment of C3 N-glycome interconnection with T1D complications, hypertension, smoking status, estimated glomerular filtration rate (eGFR), glycaemic control and duration of the disease was done using linear modelling.

Results

Significant changes of C3 N-glycome in severe albuminuria accompanying type 1 diabetes were observed, as well as in T1D subjects with hypertension. All except one of the C3 glycopeptides proved to be associated with measured HbA1c levels. One of the glycoforms was shown to be changed in non-proliferative T1D retinopathy. Smoking and eGFR showed no effect on C3 N-glycome. Furthermore, C3 N-glycosylation profile was shown to be independent of disease duration.

Conclusion

This study empowered the role of C3 N-glycosylation in T1D, showing value in distinguishing subjects with different diabetic complications. Being independent of the disease duration, these changes may be associated with the disease onset, making C3 N-glycome a potential novel marker of the disease progression and severity.

Not-So-Sweet Dreams: Plasma and IgG N-Glycome in the Severe Form of the Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a prevalent disease associated with increased risk for cardiovascular and metabolic diseases and shortened lifespan. The aim of this study was to explore the possibility of using N-glycome as a biomarker for the severe form of OSA. Seventy subjects who underwent a whole-night polysomnography/polygraphy and had apnea-hypopnea index (AHI) over 30 were compared to 23 controls (AHI under 5). Plasma samples were used to extract 39 glycan peaks using ultra-high-performance liquid chromatography (UPLC) and 27 IgG peaks using capillary gel electrophoresis (CGE). We also measured glycan age, a molecular proxy for biological aging. Three plasma and one IgG peaks were significant in a multivariate model controlling for the effects of age, sex, and body mass index. These included decreased GP24 (disialylated triantennary glycans as major structure) and GP28 (trigalactosylated, triantennary, disialylated, and trisialylated glycans), and increased GP32 (trisialylated triantennary glycan). Only one IgG glycan peak was significantly increased (P26), which contains biantennary digalactosylated glycans with core fucose. Patients with severe OSA exhibited accelerated biological aging, with a median of 6.9 years more than their chronological age (p < 0.001). Plasma N-glycome can be used as a biomarker for severe OSA.

Identification and validation of IgG N-glycosylation biomarkers of esophageal carcinoma

Introduction

Altered Immunoglobulin G (IgG) N-glycosylation is associated with aging, inflammation, and diseases status, while its effect on esophageal squamous cell carcinoma (ESCC) remains unknown. As far as we know, this is the first study to explore and validate the association of IgG N-glycosylation and the carcinogenesis progression of ESCC, providing innovative biomarkers for the predictive identification and targeted prevention of ESCC.

Methods

In total, 496 individuals of ESCC (n=114), precancerosis (n=187) and controls (n=195) from the discovery population (n=348) and validation population (n=148) were recruited in the study. IgG N-glycosylation profile was analyzed and an ESCC-related glycan score was composed by a stepwise ordinal logistic model in the discovery population. The receiver operating characteristic (ROC) curve with the bootstrapping procedure was used to assess the performance of the glycan score.

Results

In the discovery population, the adjusted OR of GP20 (digalactosylated monosialylated biantennary with core and antennary fucose), IGP33 (the ratio of all fucosylated monosyalilated and disialylated structures), IGP44 (the proportion of high mannose glycan structures in total neutral IgG glycans), IGP58 (the percentage of all fucosylated structures in total neutral IgG glycans), IGP75 (the incidence of bisecting GlcNAc in all fucosylated digalactosylated structures in total neutral IgG glycans), and the glycan score are 4.03 (95% CI: 3.03-5.36, P&lt;0.001), 0.69 (95% CI: 0.55-0.87, P&lt;0.001), 0.56 (95% CI: 0.45-0.69, P&lt;0.001), 0.52 (95% CI: 0.41-0.65, P&lt;0.001), 7.17 (95% CI: 4.77-10.79, P&lt;0.001), and 2.86 (95% CI: 2.33-3.53, P&lt;0.001), respectively. Individuals in the highest tertile of the glycan score own an increased risk (OR: 11.41), compared with those in the lowest. The average multi-class AUC are 0.822 (95% CI: 0.786-0.849). Findings are verified in the validation population, with an average AUC of 0.807 (95% CI: 0.758-0.864).

Discussion

Our study demonstrated that IgG N-glycans and the proposed glycan score appear to be promising predictive markers for ESCC, contributing to the early prevention of esophageal cancer. From the perspective of biological mechanism, IgG fucosylation and mannosylation might involve in the carcinogenesis progression of ESCC, and provide potential therapeutic targets for personalized interventions of cancer progression.

Association of IgG N-glycomics with prevalent and incident type 2 diabetes mellitus from the paradigm of predictive, preventive, and personalized medicine standpoint

Objectives

Type 2 diabetes mellitus (T2DM), a major metabolic disorder, is expanding at a rapidly rising worldwide prevalence and has emerged as one of the most common chronic diseases. Suboptimal health status (SHS) is considered a reversible intermediate state between health and diagnosable disease. We hypothesized that the time frame between the onset of SHS and the clinical manifestation of T2DM is the operational area for the application of reliable risk assessment tools, such as immunoglobulin G (IgG) N-glycans. From the viewpoint of predictive, preventive, and personalized medicine (PPPM/3PM), the early detection of SHS and dynamic monitoring by glycan biomarkers could provide a window of opportunity for targeted prevention and personalized treatment of T2DM.

Methods

Case-control and nested case-control studies were performed and consisted of 138 and 308 participants, respectively. The IgG N-glycan profiles of all plasma samples were detected by an ultra-performance liquid chromatography instrument.

Results

After adjustment for confounders, 22, five, and three IgG N-glycan traits were significantly associated with T2DM in the case-control setting, baseline SHS, and baseline optimal health participants from the nested case-control setting, respectively. Adding the IgG N-glycans to the clinical trait models, the average area under the receiver operating characteristic curves (AUCs) of the combined models based on repeated 400 times fivefold cross-validation differentiating T2DM from healthy individuals were 0.807 in the case-control setting and 0.563, 0.645, and 0.604 in the pooled samples, baseline SHS, and baseline optimal health samples of nested case-control setting, respectively, which presented moderate discriminative ability and were generally better than models with either glycans or clinical features alone.

Conclusions

This study comprehensively illustrated that the observed altered IgG N-glycosylation, i.e., decreased galactosylation and fucosylation/sialylation without bisecting GlcNAc, as well as increased galactosylation and fucosylation/sialylation with bisecting GlcNAc, reflects a pro-inflammatory state of T2DM. SHS is an important window period of early intervention for individuals at risk for T2DM; glycomic biosignatures as dynamic biomarkers have the ability to identify populations at risk for T2DM early, and the combination of evidence could provide suggestive ideas and valuable insight for the PPPM of T2DM.

Supplementary information

The online version contains supplementary material available at 10.1007/s13167-022-00311-3.

High-Throughput Glycomic Methods

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Changes in Serum IgG Glycosylation Patterns for Abdominal Aortic Aneurysm Patients

Background: B cells and autoantibodies play an important role in the pathogenesis of abdominal aortic aneurysm (AAA). IgG glycosylations are highly valued as potential disease biomarkers and therapeutic targets. Methods: Lectin microarray was applied to analyze the expression profile of serum IgG glycosylation in 75 patients with AAA, 68 autoimmune disease controls, and 100 healthy controls. Lectin blots were performed to validate the differences. The clinical relevance of lectins binding from the microarray results was explored in AAA patients. Results: Significantly lower binding level of SBA (preferred GalNAc) was observed for the AAA group compared with DCs (p < 0.001) and HCs (p = 0.049). A significantly lower binding level of ConA (preferred mannose) was observed in patients with aneurysm diameter >5 cm. Significantly higher binding of CSA (preferred GalNAc) was present for dyslipidemia patients, whereas a lower binding level of AAL (preferred fucose) was observed for hypertensive patients. Patients with diabetes had lower binding levels of IRA (preferred GalNAc) and HPA (preferred GalNAc) compared with those not with DM. PTL-L (R = 0.36, p = 0.0015, preferred GalNAc) was positively associated with aneurysm diameters, whereas DSL (R = 0.28, p = 0.014, preferred (GlcNAc)2-4) was positively associated with patients’ age. Symptomatic patients had a lower binding level of ConA (p = 0.032), and patients with coronary heart disease had higher binding levels of STL (p = 0.0029, preferred GlcNAc). Patients with ILT bound less with black bean crude (p = 0.04, preferred GalNAc). Conclusions: AAA was associated with a decreased IgG binding level of SBA (recognizing glycan GalNAc). Symptomatic patients with aneurysm <5 cm had a higher binding level of ConA (preferred mannose). Coronary heart disease and elder age were associated with increased IgG bisecting GlcNAc. IgG O-glycosylation (GalNAc) may play an important role in AAA pathogenesis and progression.

All around suboptimal health - a joint position paper of the Suboptimal Health Study Consortium and European Association for Predictive, Preventive and Personalised Medicine

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person. This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions:Stress overload associated pathologiesMale and female healthPlanned pregnanciesPeriodontal healthEye disordersInflammatory disorders, wound healing and pain management with associated complicationsMetabolic disorders and suboptimal body weightCardiovascular pathologiesCancersStroke, particularly of unknown aetiology and in young individualsSleep medicineSports medicineImproved individual outcomes under pandemic conditions such as COVID-19.

The Rapidly Expanding Nexus of Immunoglobulin G N-Glycomics, Suboptimal Health Status, and Precision Medicine

Immunoglobulin G is a prevalent glycoprotein, whose downstream immune responses are partially mediated by the N-glycans within the fragment crystallisable domain. Collectively termed the N-glycome, it is considered a complex intermediate phenotype: an amalgamation of genetic predisposition, environmental exposure, and health behaviours over the life-course. Thus, the immunoglobulin G N-glycome may provide an indication of health status on the spectrum from health to disease and infirmary. Although variability exists within and between populations, composition of the immunoglobulin G N-glycome remains stable over short periods of time. This underscores the potential of harnessing the immunoglobulin G N-glycome as an ideal tool for preclinical disease risk prediction, stratification, and prognosis through the development of precise dynamic biomarkers.

Plasma protein N-glycosylation is associated with cardiovascular disease, nephropathy, and retinopathy in type 2 diabetes

INTRODUCTION

Although associations of total plasma N-glycome (TPNG) with type 2 diabetes have been reported, little is known on the role of TPNG in type 2 diabetes complications, a major cause of type 2 diabetes-related morbidity and mortality. Here, we assessed TPNG in relation to type 2 diabetes complications in subsamples of two Dutch cohorts using mass spectrometry (n=1815 in DiaGene and n=1518 in Hoorn Diabetes Care System).

RESEARCH DESIGN AND METHODS

Blood plasma samples and technical replicates were pipetted into 96-well plates in a randomized manner. Peptide:N-glycosidase F (PNGase F) was used to release N-glycans, whereafter sialic acids were derivatized for stabilization and linkage differentiation. After total area normalization, 68 individual glycan compositions were quantified in total and were used to calculate 45 derived traits which reflect structural features of glycosylation. Associations of glycan features with prevalent and incident microvascular or macrovascular complications were tested in logistic and Cox regression in both independent cohorts and the results were meta-analyzed.

RESULTS

Our results demonstrated similarities between incident and prevalent complications. The strongest association for prevalent cardiovascular disease was a high level of bisection on a group of diantennary glycans (A2FS0B; OR=1.38, p=1.34×10^-11), while for prevalent nephropathy the increase in 2,6-sialylation on triantennary glycans was most pronounced (A3E; OR=1.28, p=9.70×10^-6). Several other TPNG features, including fucosylation, galactosylation, and sialylation, firmly demonstrated associations with prevalent and incident complications of type 2 diabetes.

CONCLUSIONS

These findings may provide a glance on how TPNG patterns change before complications emerge, paving the way for future studies on prediction biomarkers and potentially disease mechanisms.

Glycosylation of IgG Associates with Hypertension and Type 2 Diabetes Mellitus Comorbidity in the Chinese Muslim Ethnic Minorities and the Han Chinese

Objectives: Hypertension and type 2 diabetes mellitus comorbidity (HDC) is common, which confers a higher risk of cardiovascular disease than the presence of either condition alone. Describing the underlying glycomic changes of immunoglobulin G (IgG) that predispose individuals to HDC may help develop novel protective immune-targeted and anti-inflammatory therapies. Therefore, we investigated glycosylation changes of IgG associated with HDC. Methods: The IgG N-glycan profiles of 883 plasma samples from the three northwestern Chinese Muslim ethnic minorities and the Han Chinese were analyzed by ultra-performance liquid chromatography instrument. Results: We found that 12 and six IgG N-glycan traits showed significant associations with HDC in the Chinese Muslim ethnic minorities and the Han Chinese, respectively, after adjustment for potential confounders and false discovery rate. Adding the IgG N-glycan traits to the baseline models, the area under the receiver operating characteristic curves (AUCs) of the combined models differentiating HDC from hypertension (HTN), type 2 diabetes mellitus (T2DM), and healthy individuals were 0.717, 0.747, and 0.786 in the pooled samples of Chinese Muslim ethnic minorities, and 0.828, 0.689, and 0.901 in the Han Chinese, respectively, showing improved discriminating performance than both the baseline models and the glycan-based models. Conclusion: Altered IgG N-glycan profiles were shown to associate with HDC, suggesting the involvement of inflammatory processes of IgG glycosylation. The alterations of IgG N-glycome, illustrated here for the first time in HDC, demonstrate a biomarker potential, which may shed light on future studies investigating their potential for monitoring or preventing the progression from HTN or T2DM towards HDC.

Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis

Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.

Serum Bile Acid Profiles Improve Clinical Prediction of Nonalcoholic Fatty Liver in T2DM patients

Background: The present study aimed to assess the ability of serum bile acid profiles to predict the development of nonalcoholic fatty liver (NAFL) in type 2 diabetes mellitus (T2DM) patients. Methods: Using targeted ultraperformance liquid chromatography (UPLC) coupled with triple quadrupole mass spectrometry (TQ/MS), we compared serum bile acid levels in T2DM patients with NAFL (n = 30) and age- and sex-matched T2DM patients without NAFL (n = 36) at the first time. Second, an independent cohort study of T2DM patients with NAFL (n = 17) and age- and sex-matched T2DM patients without NAFL (n = 20) was used to validate the results. The incremental benefits of serum biomarkers, clinical variables alone, or with biomarkers were then evaluated using receiver operating characteristic (ROC) curves and decision curve analysis. The area under the curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used to evaluate the biomarker predictive abilities. Results: The serum bile acid profiles in T2DM patients with NAFL were significantly different from T2DM patients without NAFL, as characterized by the significant elevation of LCA, TLCA, TUDCA, CDCA-24G, and TCDCA, which may be potential biomarkers for the identification of NAFL in T2DM patients. Based on the improvement in AUC, IDI, and NRI, the addition of 5 bile acids to a model with clinical variables statistically improved its predictive value. Similar results were found in the validation cohort. Conclusions: These results highlight that the detected biomarkers may contribute to the progression of NAFL in T2DM patients, and these biomarkers particularly in combination may help in the diagnosis of NAFL and allow earlier intervention in T2DM patients.

A Rapidly Aging World in the 21st Century: Hopes from Glycomics and Unraveling the Biomarkers of Aging with the Sugar Code

A global rise in life expectancy comes with an increased burden of serious life-long health issues and the need for useful real-time measures of the aging processes. Studies have shown the value of biochemical signatures of immunoglobulin G (IgG) N-glycosylation as clinically relevant biomarkers to differentiate healthy from accelerated aging. Most human biological processes rely on glycosylation of proteins to regulate their function, but these events appear sensitive to environmental changes, age, and the presence of disease. Specifically, variations in N-glycosylation of IgG can adversely affect inflammatory pathways underpinning unhealthy aging and chronic disease pathogenesis. This expert review highlights the discrepancies between an organism's age in years of life (chronological age) versus age in terms of health status (biological age). The article examines and synthesizes the studies on IgG N-glycan profiles and the third alphabet of life, the sugar code, in relation to their relevance as dynamic indicators of aging, and to differentiate between normal and accelerated aging. The levels of N-glycan structures change with aging, suggesting that monitoring the alterations of serum glycan biosignatures with glycomics might allow real-time studies of human aging in the near future. Glycomics brings in yet another systems science technology platform to strengthen the emerging multiomics studies of aging and aging-related diseases.

The Repertoire of Glycan Alterations and Glycoproteins in Human Cancers

Cancer as the leading cause of death worldwide has many issues that still need to be addressed. Since the alterations on the glycan compositions or/and structures (i.e., glycosylation, sialylation, and fucosylation) are common features of tumorigenesis, glycomics becomes an emerging field examining the structure and function of glycans. In the past, cancer studies heavily relied on genomics and transcriptomics with relatively little exploration of the glycan alterations and glycoprotein biomarkers among individuals and populations. Since glycosylation of proteins increases their structural complexity by several orders of magnitude, glycome studies resulted in highly dynamic biomarkers that can be evaluated for cancer diagnosis, prognosis, and therapy. Glycome not only integrates our genetic background with past and present environmental factors but also offers a promise of more efficient patient stratification compared with genetic variations. Therefore, studying glycans holds great potential for better diagnostic markers as well as developing more efficient treatment strategies in human cancers. While recent developments in glycomics and associated technologies now offer new possibilities to achieve a high-throughput profiling of glycan diversity, we aim to give an overview of the current status of glycan research and the potential applications of the glycans in the scope of the personalized medicine strategies for cancer.

Glycosylation Profiling as a Biomarker of Suboptimal Health Status for Chronic Disease Stratification

WHO defines health as "a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity." We coined and defined suboptimal health status (SHS) as a subclinical, reversible stage of the pre-chronic disease. SHS is a physical state between health and disease, characterized by health complaints, general weakness, chronic fatigue, and low energy levels. We have developed an instrument to measure SHS, Suboptimal Health Status Questionnaire-25 (SHSQ-25), a self-reported survey assessing five health components that has been validated in various ethnical populations. Our studies suggest that SHS is associated with the major components of cardiovascular health and the early onset of metabolic diseases. Besides subjective measure of health (SHS), glycans are conceived as objective biomarkers of SHS. Glycans are complex and branching carbohydrate moieties attached to proteins, participating in inflammatory regulation and chronic disease pathogenesis. We have been investigating the role of glycans and SHS in multiple cardiometabolic diseases in different ethnical populations (African, Chinese, and Caucasian). Here we present case studies to prove that a combination of subjective health measure (SHS) with objective health measure (glycans) represents a window of opportunity to halt or reverse the progression of chronic diseases.

Glycosylation and Aging

Human lifespan has increased significantly in the last 200 years, emphasizing our need to age healthily. Insights into molecular mechanisms of aging might allow us to slow down its rate or even revert it. Similar to aging, glycosylation is regulated by an intricate interplay of genetic and environmental factors. The dynamics of glycopattern variation during aging has been mostly explored for plasma/serum and immunoglobulin G (IgG) N-glycome, as we describe thoroughly in this chapter. In addition, we discuss the potential functional role of agalactosylated IgG glycans in aging, through modulation of inflammation level, as proposed by the concept of inflammaging. We also comment on the potential to use the plasma/serum and IgG N-glycome as a biomarker of healthy aging and on the interventions that modulate the IgG glycopattern. Finally, we discuss the current knowledge about animal models for human plasma/serum and IgG glycosylation and mention other, less explored, instances of glycopattern changes during organismal aging and cellular senescence.

Serum N-Glycome analysis reveals pancreatic cancer disease signatures

Background &Aims

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer type with loco‐regional spread that makes the tumor surgically unresectable. Novel diagnostic tools are needed to improve detection of PDAC and increase patient survival. In this study we explore serum protein N‐glycan profiles from PDAC patients with regard to their applicability to serve as a disease biomarker panel.

Methods

Total serum N‐glycome analysis was applied to a discovery set (86 PDAC cases/84 controls) followed by independent validation (26 cases/26 controls) using in‐house collected serum specimens. Protein N‐glycan profiles were obtained using ultrahigh resolution mass spectrometry and included linkage‐specific sialic acid information. N‐glycans were relatively quantified and case‐control classification performance was evaluated based on glycosylation traits such as branching, fucosylation, and sialylation.

Results

In PDAC patients a higher level of branching (OR 6.19, P‐value 9.21 × 10⁻¹¹) and (antenna)fucosylation (OR 13.27, P‐value 2.31 × 10⁻⁹) of N‐glycans was found. Furthermore, the ratio of α2,6‐ vs α2,3‐linked sialylation was higher in patients compared to healthy controls. A classification model built with three glycosylation traits was used for discovery (AUC 0.88) and independent validation (AUC 0.81), with sensitivity and specificity values of 0.85 and 0.71 for the discovery set and 0.75 and 0.72 for the validation set.

Conclusion

Serum N‐glycome analysis revealed glycosylation differences that allow classification of PDAC patients from healthy controls. It was demonstrated that glycosylation traits rather than single N‐glycan structures obtained in this clinical glycomics study can serve as a basis for further development of a blood‐based diagnostic test.

A Predictive Model Using N-Glycan Biosignatures for Clinical Diagnosis of Early Hepatocellular Carcinoma Related to Hepatitis B Virus

Early diagnosis of hepatic cancer is a major public health challenge. While changes in serum N-glycans have been observed as patients progress from liver fibrosis/cirrhosis to hepatocellular carcinoma (HCC), the predictive performance of N-glycans is yet to be determined for HCC early diagnosis as well as differential diagnosis from liver fibrosis/cirrhosis. In a total sample of 247 patients with hepatitis B virus-related liver disease, we characterized and compared the serum N-glycans in very early/early and intermediate/advanced stages of HCC and those with liver fibrosis/cirrhosis. Additionally, we performed a retrospective timeline analysis of the serum N-glycans 6 and 12 months before a diagnosis of the very early/early stage of HCC (EHCC). A predictive model was built, named hereafter as Glycomics-EHCC, incorporating the glycan peaks (GPs) 1, 2, and 4. The model showed a larger area under the receiver operating characteristic curve compared with a traditional model with the α-fetoprotein (0.936 vs. 0.731, respectively). The Glycomics-EHCC model had a sensitivity of 84.6% and specificity of 85.0% at a cutoff value of -0.39 to distinguish EHCC from liver fibrosis/cirrhosis. Moreover, the Glycomics-EHCC model was able to forecast a future EHCC diagnosis with a sensitivity and specificity over 90% and 85%, respectively, using the serum N-glycan biosignatures 6 or 12 months earlier when the patients were suffering from liver fibrosis/cirrhosis before being diagnosed with EHCC. This serum glycomic biosignature model warrants further clinical studies in independent population samples and offers promise to forecast EHCC and its differential diagnosis from liver fibrosis/cirrhosis.

Next-Generation (Glycomic) Biomarkers for Cardiometabolic Health: A Community-Based Study of Immunoglobulin G N-Glycans in a Chinese Han Population

Cardiovascular disease is a common complex trait that calls for next-generation biomarkers for precision diagnostics and therapeutics. The most common type of post-translational protein modification involves glycosylation. Glycans participate in key intercellular and intracellular functions, such as protein quality control, cell adhesion, cell-cell recognition, signal transduction, cell proliferation, and cell differentiation. In this context, immunoglobulin G (IgG) N-glycans affect the anti-inflammatory and proinflammatory responses of IgG, and are associated with cardiometabolic risk factors such as aging, central obesity, dyslipidemia, and hyperglycemia. Yet, the role of such glycomic biomarkers requires evaluation in diverse world populations. We report here original observations on association of IgG N-glycan biosignatures with 15 cardiometabolic risk factors in a community-based cross-sectional study conducted in 701 Chinese Han participants. After controlling for age and sex, we found that the 16, 21, and 18 IgG N-glycan traits were significantly different in participants with and without metabolic syndrome, hypertriglyceridemic waist phenotype, or abdominal obesity, respectively. The canonical correlation analysis showed that IgG N-glycan profiles were significantly associated with cardiometabolic risk factors (r = 0.469, p < 0.001). Classification models based on IgG N-glycan traits were able to differentiate participants with (1) metabolic syndrome, (2) hypertriglyceridemic waist phenotype, or (3) abdominal obesity from controls, with an area under receiver operating characteristic curves (AUC) of 0.632 (95% confidence interval [CI], 0.574-0.691, p < 0.001), 0.659 (95% CI, 0.587-0.730, p < 0.001), and 0.610 (95% CI, 0.565-0.656, p < 0.001), respectively. These new data suggest that IgG N-glycans may play an important role in cardiometabolic disease pathogenesis by regulating the proinflammatory or anti-inflammatory responses of IgG. Looking into the future, IgG N-glycan biosignatures warrant further research in other world population samples with a view to applications in clinical cardiology and public health practice.

Type 2 Diabetes Mellitus is Associated with the Immunoglobulin G N-Glycome through Putative Proinflammatory Mechanisms in an Australian Population

Type 2 diabetes mellitus (T2DM) is a common complex trait arising from interactions among multiple environmental, genomic, and postgenomic factors. We report here the first attempt to investigate the association between immunoglobulin G (IgG) N-glycan patterns, T2DM, and their clinical risk factors in an Australian population. N-glycosylation of proteins is one of the most frequently observed co- and post-translational modifications, reflecting, importantly, the real-time status of the interplay between the genomic and postgenomic factors. In a community-based case-control study, 849 participants (217 cases and 632 controls) were recruited from an urban community in Busselton, Western Australia. We applied the ultraperformance liquid chromatography method to analyze the composition of IgG N-glycans. We then conducted Spearman's correlation analyses to explore the association between glycan biomarker candidates and clinical risk factors. We performed area under the curve (AUC) analysis of the receiver operating characteristic curves by fivefold cross-validation for clinical risk factors, IgG glycans, and their combination. Two directly measured and four derived glycan peaks were significantly associated with T2DM, after correction for extensive clinical confounders and false discovery rate, thus suggesting that IgG N-glycan traits are highly correlated with T2DM clinical risk factors. Moreover, adding the IgG glycan profiles to fasting blood glucose in the logistic regression model increased the AUC from 0.799 to 0.859. The AUC for IgG glycans alone was 0.623 with a 95% confidence interval 0.580-0.666. In addition, our study provided new evidence of diversity in T2DM complex trait by IgG N-glycan stratification. Six IgG glycan traits were firmly associated with T2DM, which reflects an increased proinflammatory and biological aging status. In summary, our study reports novel associations between the IgG N-glycome and T2DM in an Australian population and the putative role of proinflammatory mechanisms. Furthermore, IgG N-glycomic alterations offer future prospects as inflammatory biomarker candidates for T2DM diagnosis, and monitoring of T2DM progression to cardiovascular disease or renal failure.

Utilization of N-glycosylation profiles as risk stratification biomarkers for suboptimal health status and metabolic syndrome in a Ghanaian population

Aim: The study sought to apply N-glycosylation profiles to understand the interplay between suboptimal health status (SHS) and metabolic syndrome (MetS). Materials & methods: In this study, 262 Ghanaians were recruited from May to July 2016. After completing a health survey, plasma samples were collected for clinical assessments while ultra performance liquid chromatography was used to measure plasma N-glycans. Results: Four glycan peaks were found to predict case status (MetS and SHS) using a step-wise Akaike’s information criterion logistic regression model selection. This model yielded an area under the curve of MetS: 83.1% (95% CI: 78.0–88.1%) and SHS: 67.1% (60.6–73.7%). Conclusion: Our results show that SHS is a significant, albeit modest, risk factor for MetS and N-glycan complexity was associated with MetS.

Glycomics for Type 2 Diabetes Biomarker Discovery: Promise of Immunoglobulin G Subclass-Specific Fragment Crystallizable N-glycosylation in the Uyghur Population

Aberrant immunoglobulin G (IgG) N-glycosylation offers new prospects to detect changes in cell metabolism and by extension, for biomarker discovery in type 2 diabetes mellitus (T2DM). However, past studies did not analyze the individual IgG subclasses in relation to T2DM pathophysiology. We report here original findings through a comparison of the IgG subclass-specific fragment crystallizable (Fc) glycan biosignatures in 115 T2DM patients with 122 healthy controls within the Uyghur population in China. IgG Fc glycosylation profiles were analyzed using nano-liquid chromatography-mass spectrometry to exclude changes attributed to fragment antigen binding N-glycosylation. After correction for clinical covariates, 27 directly measured and 4 derived glycan traits of the IgG subclass-specific N-glycopeptides were significantly associated with T2DM. Furthermore, we observed in T2DM a decrease in bisecting N-acetylglucosamine of IgG2 and agalactosylation of IgG4, and an increase in sialylation of IgG4 and digalactosylation of IgG2. Classification model based on IgG subclass-specific N-glycan traits was able to distinguish patients with T2DM from controls with an area under the receiver operating characteristic curve of 0.927 (95% confidence interval 0.894-0.960, p < 0.001). In conclusion, a robust association between the IgG subclass-specific Fc N-glycomes and T2DM was observed in the Uyghur population sample in China, suggesting a potential for the IgG Fc glycosylation as a biomarker candidate for type 2 diabetes. The integration of glycomics with other system science biomarkers might offer further hope for innovation in diagnosis and treatment of T2DM in the future. Finally, it is noteworthy that "Population Glycomics" is an emerging approach to biomarker discovery for common complex diseases.

Polybrominated Diphenyl Ethers and Gut Microbiome Modulate Metabolic Syndrome-Related Aqueous Metabolites in Mice

Polybrominated diphenyl ethers (PBDEs) are persistent environmental toxicants associated with increased risk for metabolic syndrome. Intermediary metabolism is influenced by the intestinal microbiome. To test the hypothesis that PBDEs reduce host-beneficial intermediary metabolites in an intestinal microbiome-dependent manner, 9-week old male conventional (CV) and germ-free (GF) C57BL/6 mice were orally gavaged once daily with vehicle, BDE-47, or BDE-99 (100 μmol/kg) for 4 days. Intestinal microbiome (16S rDNA sequencing), liver transcriptome (RNA-Seq), and intermediary metabolites in serum, liver, as well as small and large intestinal contents (SIC and LIC; LC-MS) were examined. Changes in intermediary metabolite abundances in serum, liver, and SIC, were observed under basal conditions (CV vs. GF mice) and by PBDE exposure. PBDEs altered the largest number of metabolites in the LIC; most were regulated by PBDEs in GF conditions. Importantly, intestinal microbiome was necessary for PBDE-mediated decreases in branched-chain and aromatic amino acid metabolites, including 3-indolepropionic acid, a tryptophan metabolite recently shown to be protective against inflammation and diabetes. Gene-metabolite networks revealed a positive association between the hepatic glycan synthesis gene α-1,6-mannosyltransferase (Alg12) mRNA and mannose, which are important for protein glycosylation. Glycome changes have been observed in patients with metabolic syndrome. In LIC of CV mice, 23 bacterial taxa were regulated by PBDEs. Correlations of certain taxa with distinct serum metabolites further highlight a modulatory role of the microbiome in mediating PBDE effects. In summary, PBDEs impact intermediary metabolism in an intestinal microbiome-dependent manner, suggesting that dysbiosis may contribute to PBDE-mediated toxicities that include metabolic syndrome.

Type 2 Diabetes Mellitus: Integrative Analysis of Multiomics Data for Biomarker Discovery

Increased fasting plasma glucose (FPG) is an independent risk factor for type 2 diabetes mellitus (T2DM). The development of systems biology technologies for integration of multiomics data is crucial for predicting increased FPG levels. In this case-control study, immunoglobulin (Ig) G glycosylation profiling and genome-wide association analyses were performed on 511 participants, and among them 76 had increased FPG (aged 47.6 ± 6.14 years), and 435 had decreased or fluctuant FPG (aged 47.9 ± 6.08 years). We identified nine single nucleotide polymorphisms (SNPs) in five genes (RPL7AP27, SNX30, SLC39A12, BACE2, and IGFL2) that were significantly associated with increased FPG (odds ratios 1.937-2.393). Moreover, of the 24 glycan peaks (GPs), GPs 3, 8, and 11 presented positive trends with increased FPG levels, whereas GPs 4 and 14 presented negative trends. A significant improvement of predictive power was observed when adding 24 IgG GPs to 9 SNPs with the area under the curve increased from 0.75 to 0.81. This report shows that the combination of candidate SNPs with IgG glycomics offers biomarker potentials for T2DM. The substantial predictive power obtained from integrating genomics and glycomics biomarkers suggests the feasibility of applying such multiomics strategies to enable predictive, preventive, and personalized medicine for T2DM.

Healthy human serum N-glycan profiling reveals the influence of ethnic variation on the identified cancer-relevant glycan biomarkers

Background

Most glycomics studies have focused on understanding disease mechanisms and proposing serum markers for various diseases, yet the influence of ethnic variation on the identified glyco-biomarker remains poorly addressed. This study aimed to investigate the inter-ethnic serum N-glycan variation among US origin control, Japanese, Indian, and Ethiopian healthy volunteers.

Methods

Human serum from 54 healthy subjects of various ethnicity and 11 Japanese hepatocellular carcinoma (HCC) patients were included in the study. We employed a comprehensive glycoblotting-assisted MALDI-TOF/MS-based quantitative analysis of serum N-glycome and fluorescence HPLC-based quantification of sialic acid species. Data representing serum N-glycan or sialic acid levels were compared among the ethnic groups using SPSS software.

Results

Total of 51 N-glycans released from whole serum glycoproteins could be reproducibly quantified within which 33 glycoforms were detected in all ethnicities. The remaining N-glycans were detected weakly but exclusively either in the Ethiopians (13 glycans) or in all the other ethnic groups (5 glycans). Highest abundance (p < 0.001) of high mannose, core-fucosylated, hyperbranched/hypersialylated N-glycans was demonstrated in Ethiopians. In contrast, only one glycan (m/z 2118) significantly differed among all ethnicities being highest in Indians and lowest in Ethiopians. Glycan abundance trend in Ethiopians was generally close to that of Japanese HCC patients. Glycotyping analysis further revealed ethnic-based disparities mainly in the branched and sialylated structures. Surprisingly, some of the glycoforms greatly elevated in the Ethiopian subjects have been identified as serum biomarkers of various cancers. Sialic acid level was significantly increased primarily in Ethiopians, compared to the other ethnicities.

Conclusion

The study revealed ethnic-specific differences in healthy human serum N-glycome with highest abundance of most glycoforms in the Ethiopian ethnicity. The results strongly emphasized the need to consider ethnicity matching for accurate glyco-biomarker identification. Further large-scale study employing various ethnic compositions is needed to verify the current result.

The association between subclass-specific IgG Fc N-glycosylation profiles and hypertension in the Uygur, Kazak, Kirgiz, and Tajik populations

Hypertension results from the interaction of genetic and acquired factors. IgG occurs in the form of different subclasses, of which the effector functions show significant variation. The detailed differences between the glycosylation profiles of the individual IgG subclasses may be lost in a profiling method for total IgG N-glycosylation. In this study, subclass-specific IgG Fc glycosylation profile was investigated in the four northwestern Chinese minority populations, namely, Uygur (UIG), Kazak (KZK), Kirgiz (KGZ), and Tajik (TJK), composed of 274 hypertensive patients and 356 healthy controls. The results showed that ten directly measured IgG N-glycan traits (i.e., IgG1G0F, IgG2G0F, IgG2G1FN, IgG2G1FS, IgG2G2S, IgG4G0F, IgG4G1FS, IgG4G1S, IgG4G2FS, and IgG4G2N) representing galactosylation and sialylation are significantly associated with hypertension, with IgG4 consistently showing weaker associations of its sialylation, across the four ethnic groups. We observed a modest improvement on the AUC of ROC curve when the IgG Fc N-glycan traits are added into the glycan-based model (difference between AUCs, 0.044, 95% CI: 0.016-0.072, P = 0.002). The AUC of the diagnostic model indicated that the subclass-specific IgG Fc N-glycan profiles provide more information reinforcing current models utilizing age, gender, BMI, and ethnicity, and demonstrate the potential of subclass-specific IgG Fc N-glycosylation profiles to serve as a biomarker for hypertension. Further research is however required to determine the additive value of subclass-specific IgG Fc N-glycosylation on top of biomarkers, which are currently used.

Pathways from epigenomics and glycobiology towards novel biomarkers of addiction and its radical cure

The recent demonstration that addiction-relevant neuronal ensembles defined by known master transcription factors and their connectome is networked throughout mesocorticolimbic reward circuits and resonates harmonically at known frequencies implies that single-cell pan-omics techniques can improve our understanding of Substance Use Disorders (SUD's). Application of machine learning algorithms to such data could find diagnostic utility as biomarkers both to define the presence of the disorder and to quantitate its severity and find myriad applications in a developmental pipeline towards therapeutics and cure. Recent epigenomic studies have uncovered a wealth of clinically important data relating to synapse-nucleus signalling, memory storage, lineage-fate determination and cellular control and are contributing greatly to our understanding of all SUD's. Epigenetics interacts extensively with glycobiology. Glycans decorate DNA, RNA and many circulating critical proteins particularly immunoglobulins. Glycosylation is emerging as a major information-laden post-translational protein modification with documented application for biomarker development. The integration of these two emerging cutting-edge technologies provides a powerful and fertile algorithmic-bioinformatic space for the development both of SUD biomarkers and novel cutting edge therapeutics.

HYPOTHESES

These lines of evidence provide fertile ground for hypotheses relating to both diagnosis and treatment. They suggest that biomarkers derived from epigenomics complemented by glycobiology may potentially provide a bedside diagnostic tool which could be developed into a clinically useful biomarker to gauge both the presence and the severity of SUD's. Moreover they suggest that modern information-based therapeutics acting on the epigenome, via RNA interference or by DNA antisense oligonucleotides may provide a novel 21st century therapeutic development pipeline towards the radical cure of addictive disorders. Such techniques could be focussed and potentiated by neurotrophic vectors or the application of interfering electric or magnetic fields deep in the medial temporal lobes of the brain.

Characteristic glycopeptides associated with extreme human longevity identified through plasma glycoproteomics

BACKGROUND

Glycosylation is highly susceptible to changes of the physiological conditions, and accordingly, is a potential biomarker associated with several diseases and/or longevity. Semi-supercentenarians (SSCs; older than 105 years) are thought to be a model of human longevity. Thus, we performed glycoproteomics using plasma samples of SSCs, and identified proteins and conjugated N-glycans that are characteristic of extreme human longevity.

METHODS

Plasma proteins from Japanese semi-supercentenarians (SSCs, 106-109 years), aged controls (70-88 years), and young controls (20-38 years) were analysed by using lectin microarrays and liquid chromatography/mass spectrometry (LC/MS). Peak area ratios of glycopeptides to corresponding normalising peptides were subjected to orthogonal projections to latent structures discriminant analysis (OPLS-DA). Furthermore, plasma levels of clinical biomarkers were measured.

RESULTS

We found two lectins such as Phaseolus vulgaris, and Erythrina cristagalli (ECA), of which protein binding were characteristically increased in SSCs. Peak area ratios of ECA-enriched glycopeptides were successfully discriminated between SSCs and controls using OPLS-DA, and indicated that tri-antennary and sialylated N-glycans of haptoglobin at Asn207 and Asn211 sites were characterized in SSCs. Sialylated glycans of haptoglobin are a potential biomarker of several diseases, such as hepatocellular carcinoma, liver cirrhosis, and IgA-nephritis. However, the SSCs analysed here did not suffer from these diseases.

CONCLUSIONS

Tri-antennary and sialylated N-glycans on haptoglobin at the Asn207 and Asn211 sites were abundant in SSCs and characteristic of extreme human longevity.

GENERAL SIGNIFICANCE

We found abundant glycans in SSCs, which may be associated with human longevity.

Incorporation of suboptimal health status as a potential risk assessment for type II diabetes mellitus: a case-control study in a Ghanaian population

Due to a paradigm shift in lifestyles, there is growing concern that type 2 diabetes mellitus (T2DM) will reach epidemic proportions in Ghana. However, specific characteristics of the disease are under explored in this region. More challenging are those yet to be diagnosed or who complain of poor health in the absence of a diagnosed disease-suboptimal health status (SHS). We conducted a study to examine various factors that characterise SHS and T2DM. Using a cross-sectional design, we recruited 264 people as controls and 241 T2DM patients from January to June 2016. The controls were categorised into high and low SHS based on how they rated on an SHS questionnaire-25 (SHSQ-25). Anthropometric and biochemical parameters: body mass index (BMI); blood pressure (BP); fasting plasma glucose (FPG); glycated haemoglobin (HbA1c); serum lipids [(total cholesterol, triglycerides (TG), high- and low-density lipoprotein-cholesterol (HDL-c and LDL-c)] were measured. The male to female ratio for T2DM and controls were 99:142 and 98:166, respectively, whilst the mean ages were 55.89 and 51.52 years. Compared to controls, T2DM patients had higher FPG (8.96 ± 4.18 vs. 6.08 ± 1.79; p < 0.0001) and HbA1c (8.23 ± 2.09 vs. 5.45 ± 1.00; p < 0.0001). Primarily sedentary [adjusted odds ratio (aOR) = 2.97 (1.38-6.39); p = 0.034)], systolic blood pressure (SBP) (p = 0.001) and diastolic blood pressure (DBP) (p = 0.001) significantly correlated with high SHS. After adjusting for age and gender, central adiposity [aOR = 1.74 (1.06-2.83); p = 0.027)], underweight [aOR = 5.82 (1.23-27.52); p = 0.018)], high SBP [aOR = 1.86 (1.14-3.05); p = 0.012)], high DBP [aOR = 2.39 (1.40-4.07); p = 0.001)] and high TG [aOR = 2.17 (1.09-4.33); p = 0.029)] were found to be independent risk factors associated with high SHS. The management of T2DM in Ghana is suboptimal and undiagnosed risk factors remain prevalent. The SHSQ-25 can be translated and applied as a practical tool to screen at-risk individuals and hence prove useful for the purpose of predictive, preventive and personalised medicine.

Glycan Biomarkers for Rheumatoid Arthritis and Its Remission Status in Han Chinese Patients

Rheumatoid arthritis (RA), a systemic, chronic, and progressive inflammatory autoimmune disease, affects up to 1.0% of the world population doubling mortality rate of patients and is a major global health burden. Worrisomely, we lack robust diagnostics of RA and its remission status. Research with the next-generation biomarker technology platforms such as glycomics offers new promises in this context. We report here a clinical case-control study comprising 128 patients suffering from chronic RA (80.22% in remission, 19.78% active clinically) and 195 gender- and age-matched controls, with a view to the putative glycan biomarkers of RA as well as its activity or remission status in Han Chinese RA patients. Hydrophilic interaction liquid chromatography-ultra-performance liquid chromatography (HILIC-UPLC) was used for the analysis of IgG glycans. The regression model identified the glycans that predict RA status, while a receiver operating characteristic (ROC) curve analysis validated the sensitivity and prediction power. Among the total 24 glycan peaks (GP1-GP24), ROC analysis showed only GP1 prediction to be highly sensitive with an area under the curve (AUC) = 0.881. Even though GP21 and GP22 could predict active status among the RA cases (p < 0.05), they had lower sensitivity of prediction with an AUC = 0.658. Taken together, these observations suggest that GP1 might have potential as a putative biomarker for RA in the Han Chinese population, while the change in IgG glycosylation shows association with the RA active and remission states. To the best of our knowledge, this is the first glycomics study with respect to disease activity and remission states in RA.

Human Plasma N-glycosylation as Analyzed by Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance-MS Associates with Markers of Inflammation and Metabolic Health

Glycosylation is an abundant co- and post-translational protein modification of importance to protein processing and activity. Although not template-defined, glycosylation does reflect the biological state of an organism and is a high-potential biomarker for disease and patient stratification. However, to interpret a complex but informative sample like the total plasma N-glycome, it is important to establish its baseline association with plasma protein levels and systemic processes. Thus far, large-scale studies (n >200) of the total plasma N-glycome have been performed with methods of chromatographic and electrophoretic separation, which, although being informative, are limited in resolving the structural complexity of plasma N-glycans. MS has the opportunity to contribute additional information on, among others, antennarity, sialylation, and the identity of high-mannose type species.Here, we have used matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance (FTICR)-MS to study the total plasma N-glycome of 2144 healthy middle-aged individuals from the Leiden Longevity Study, to allow association analysis with markers of metabolic health and inflammation. To achieve this, N-glycans were enzymatically released from their protein backbones, labeled at the reducing end with 2-aminobenzoic acid, and following purification analyzed by negative ion mode intermediate pressure MALDI-FTICR-MS. In doing so, we achieved the relative quantification of 61 glycan compositions, ranging from Hex₄HexNAc₂ to Hex₇HexNAc₆dHex₁Neu5Ac₄, as well as that of 39 glycosylation traits derived thereof. Next to confirming known associations of glycosylation with age and sex by MALDI-FTICR-MS, we report novel associations with C-reactive protein (CRP), interleukin 6 (IL-6), body mass index (BMI), leptin, adiponectin, HDL cholesterol, triglycerides (TG), insulin, gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), and smoking. Overall, the bisection, galactosylation, and sialylation of diantennary species, the sialylation of tetraantennary species, and the size of high-mannose species proved to be important plasma characteristics associated with inflammation and metabolic health.

'Omics' biomarkers associated with chronic low back pain: protocol of a retrospective longitudinal study

INTRODUCTION

Chronic low back pain (CLBP) produces considerable direct costs as well as indirect burdens for society, industry and health systems. CLBP is characterised by heterogeneity, inclusion of several pain syndromes, different underlying molecular pathologies and interaction with psychosocial factors that leads to a range of clinical manifestations. There is still much to understand in the underlying pathological processes and the non-psychosocial factors which account for differences in outcomes. Biomarkers that may be objectively used for diagnosis and personalised, targeted and cost-effective treatment are still lacking. Therefore, any data that may be obtained at the '-omics' level (glycomics, Activomics and genome-wide association studies-GWAS) may be helpful to use as dynamic biomarkers for elucidating CLBP pathogenesis and may ultimately provide prognostic information too. By means of a retrospective, observational, case-cohort, multicentre study, we aim to investigate new promising biomarkers potentially able to solve some of the issues related to CLBP.

METHODS AND ANALYSIS

The study follows a two-phase, 1:2 case-control model. A total of 12 000 individuals (4000 cases and 8000 controls) will be enrolled; clinical data will be registered, with particular attention to pain characteristics and outcomes of pain treatments. Blood samples will be collected to perform -omics studies. The primary objective is to recognise genetic variants associated with CLBP; secondary objectives are to study glycomics and Activomics profiles associated with CLBP.

ETHICS AND DISSEMINATION

The study is part of the PainOMICS project funded by European Community in the Seventh Framework Programme. The study has been approved from competent ethical bodies and copies of approvals were provided to the European Commission before starting the study. Results of the study will be reviewed by the Scientific Board and Ethical Committee of the PainOMICS Consortium. The scientific results will be disseminated through peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT02037789; Pre-results.

China suboptimal health cohort study: rationale, design and baseline characteristics

BACKGROUND

Suboptimal health status (SHS) is a physical state between health and disease, characterized by the perception of health complaints, general weakness, chronic fatigue and low energy levels. SHS is proposed by the ancient concept of traditional Chinese medicine (TCM) from the perspective of preservative, predictive and personalized (precision) medicine. We previously created the suboptimal health status questionnaire 25 (SHSQ-25), a novel instrument to measure SHS, validated in various populations. SHSQ-25 thus affords a window of opportunity for early detection and intervention, contributing to the reduction of chronic disease burdens.

METHODS/DESIGN

To investigate the causative effect of SHS in non-communicable chronic diseases (NCD), we initiated the China suboptimal health cohort study (COACS), a longitudinal study starting from 2013. Phase I of the study involved a cross-sectional survey aimed at identifying the risk/protective factors associated with SHS; and Phase II: a longitudinal yearly follow-up study investigating how SHS contributes to the incidence and pattern of NCD.

RESULTS

(1) Cross-sectional survey: in total, 4313 participants (53.8 % women) aged from 18 to 65 years were included in the cohort. The prevalence of SHS was 9.0 % using SHS score of 35 as threshold. Women showed a significantly higher prevalence of SHS (10.6 % in the female vs. 7.2 % in the male, P < 0.001). Risk factors for chronic diseases such as socioeconomic status, marital status, highest education completed, physical activity, salt intake, blood pressure and triglycerides differed significantly between subjects of SHS (SHS score ≥35) and those of ideal health (SHS score <35). (2) Follow up: the primary and secondary outcomes will be monitored from 2015 to 2024.

CONCLUSIONS

The sex-specific difference in prevalence of SHS might partly explain the gender difference of incidence of certain chronic diseases. The COACS will enable a thorough characterization of SHS and establish a cohort that will be used for longitudinal analyses of the interaction between the genetic, lifestyle and environmental factors that contribute to the onset and etiology of targeted chronic diseases. The study together with the designed prospective cohort provides a chance to characterize and evaluate the effect of SHS systemically, and it thus generates an unprecedented opportunity for the early detection and prevention of chronic disease.

Murine Plasma N-Glycosylation Traits Associated with Sex and Strain

Glycosylation is an abundant and important protein modification with large influence on the properties and interactions of glycoconjugates. Human plasma N-glycosylation has been the subject of frequent investigation, revealing strong associations with physiological and pathological conditions. Less well-characterized is the plasma N-glycosylation of the mouse, the most commonly used animal model for studying human diseases, particularly with regard to differences between strains and sexes. For this reason, we used MALDI-TOF(/TOF)-MS(/MS) assisted by linkage-specific derivatization of the sialic acids to comparatively analyze the plasma N-glycosylation of both male and female mice originating from BALB/c, CD57BL/6, CD-1, and Swiss Webster strains. The combined use of this analytical method and the recently developed data processing software named MassyTools allowed the relative quantification of the N-glycan species within plasma, the distinction between α2,3- and α2,6-linked N-glycolylneuraminic acids (due to respective lactonization and ethyl esterification), the detection of sialic acid O-acetylation, as well as the characterization of branching sialylation (Neu5Gcα2,3-Hex-[Neu5Gcα2,6-]HexNAc). When analyzing the glycosylation according to mouse sex, we found that female mice present a considerably higher degree of core fucosylation (2-4-fold depending on the strain), galactosylation, α2,6-linked sialylation, and larger high-mannose type glycan species compared with their male counterparts. Male mice, on the contrary, showed on average higher α2,3-linked sialylation, branching sialylation, and putative bisection. These differences together with sialic acid acetylation proved to be strain-specific as well. Interestingly, the outbred strains CD-1 and Swiss Webster displayed considerably larger interindividual variation than inbred strains BALB/c and CD57BL/6, suggesting a strong hereditable component of the observed plasma N-glycome.

The Uyghur population and genetic susceptibility to type 2 diabetes: potential role for variants in CAPN10, APM1 and FUT6 genes

Genome‐wide association studies have successfully identified over 70 loci associated with the risk of type 2 diabetes mellitus (T2DM) in multiple populations of European ancestry. However, the risk attributable to an individual variant is modest and does not yet provide convincing evidence for clinical utility. Association between these established genetic variants and T2DM in general populations is hitherto understudied in the isolated populations, such as the Uyghurs, resident in Hetian, far southern Xinjiang Uyghur Autonomous Region, China. In this case–control study, we genotyped 13 single‐nucleotide polymorphisms (SNPs) at 10 genes associated with diabetes in 130 cases with T2DM and 135 healthy controls of Uyghur, a Chinese minority ethnic group. Three of the 13 SNPs demonstrated significant association with T2DM in the Uyghur population. There were significant differences between the T2DM patients and controls in the risk allele distributions of rs3792267 (CAPN10) (P = 0.002), rs1501299 (APM1) (P = 0.017), and rs3760776 (FUT6) (P = 0.031). Allelic carriers of rs3792267‐A, rs1501299‐T, and rs3760776‐T had a 2.24‐fold [OR (95% CI): 1.35–3.71], 0.59‐fold [OR (95% CI): 0.39–0.91], 0.57‐fold [OR (95% CI): 0.34–0.95] increased risk for T2DM respectively. We further confirmed that the cumulative risk allelic scores calculated from the 13 susceptibility loci for T2DM differed significantly between the T2DM patients and controls (P = 0.001), and the effect of obesity/overweight on T2DM was only observed in the subjects with a combined risk allelic score under a value of 17. This study observed that the SNPs rs3792267 in CAPN10, rs1501299 in APM1, and rs3760776 in FUT6 might serve as potential susceptible biomarkers for T2DM in Uyghurs. The cumulative risk allelic scores of multiple loci with modest individual effects are also significant risk factors in Uyghurs for T2DM, particularly among non‐obese individuals. This is the first investigation having observed/found genetic variations on genetic loci functionally linked with glycosylation associated with the risk of T2DM in a Uyghur population.

Profiling IgG N-glycans as potential biomarker of chronological and biological ages: A community-based study in a Han Chinese population

As an important post-translation modifying process, glycosylation significantly affects the structure and function of immunoglobulin G (IgG) molecules and is essential in many steps of the inflammatory cascade. Studies have demonstrated the potential of using glycosylation features of IgG as a component of predictive biomarkers for chronological age in several European populations, whereas no study has been reported in Chinese. Herein, we report various patterns of changes in IgG glycosylation associated with age by analyzing IgG glycosylation in 701 community-based Han Chinese (244 males, 457 females; 23-68 years old). Eleven IgG glycans, including FA2B, A2G1, FA2[6]G1, FA2[3]G1, FA2[6]BG1, FA2[3]BG1, A2G2, A2BG2, FA2G2, FA2G2S1, and FA2G2S2, change considerably with age and specific combinations of these glycan features can explain 23.3% to 45.4% of the variance in chronological age in this population. This indicates that these combinations of glycan features provide more predictive information than other single markers of biological age such as telomere length. In addition, the clinical traits such as fasting plasma glucose and aspartate aminotransferase associated with biological age are strongly correlated with the combined glycan features. We conclude that IgG glycosylation appears to correlate with both chronological and biological ages, and thus its possible role in the aging process merits further study.

The Association Between Glycosylation of Immunoglobulin G and Hypertension: A Multiple Ethnic Cross-Sectional Study

More than half of all known proteins, and almost all membrane and extra-cellular proteins have oligosaccharide structures or glycans attached to them. Defects in glycosylation pathways are directly involved in at least 30 severe human diseases.A multiple center cross-sectional study (China, Croatia, and Scotland) was carried out to investigate the possible association between hypertension and IgG glycosylation. A hydrophilic interaction chromatography of fluorescently labeled glycans was used to analyze N-glycans attached to IgG in plasma samples from a total of 4757 individuals of Chinese Han, Croatian, and Scottish ethnicity.Five glycans (IgG with digalactosylated glycans) significantly differed in participants with prehypertension or hypertension compared to those with normal blood pressure, while additional 17 glycan traits were only significantly differed in participants with hypertension compared to those of normal blood pressure. These glycans were also significant correlated with systolic blood pressure (SBP) or diastolic blood pressure (DBP).The present study demonstrated for the 1st time an association between hypertension and IgG glycome composition. These findings suggest that the individual variation in N-glycosylation of IgG contributes to pathogenesis of hypertension, presumably via its effect on pro- and/or anti-inflammatory pathways.

Physical and mental health conditions of young college students with different Traditional Chinese Medicine constitutions in Zhejiang Province of China

OBJECTIVE

To investigate Traditional Chinese Medicine (TCM) constitutions of youths in colleges, and their physical and mental health conditions of different TCM constitutions, so as to provide a theoretical basis for the TCM way to improve young people's physical and mental health.

METHODS

The Standard TCM Constitutions' Classification and Determination Questionnaire was used to measure the body health condition, and the Symptom Checklist 90 Questionnaire and the Questionnaire of the National Student Physical Health Standards were used to determine mental and physical health conditions respectively in 1421 young participants validly answering the questionnaires in Zhejiang Province.

RESULTS

The participants had a mean age of 19.96 years (SD = 0.95 years) with the majority of females (55.10%). One fourth of the 1421 participants were the Ping-he constitution and others were the tendency constitutions. Participants with Pinghe module (which has characteristics of moderate posture, rosy, energetic and is a healthy condition in TCM) were healthier than those with tendency constitutions in physical and mental health, with 65.81 ± 7.83 (men) and 77.99 ± 7.24 (women) scores in the physical test and around 1.25 scores in the mental health test. College students with combined biased constitutions were more likely suffer force, sensitive, depression and anxiety.

CONCLUSION

Most of college students have a tendency or biased constitution which could be more likely to suffer suboptimal health status and diseases. Youths in college themselves and health providers should pay more attention to their potential health issues and make proper healthcare plan according to their own TCM constitution.

Glycomics and glycoproteomics focused on aging and age-related diseases--Glycans as a potential biomarker for physiological alterations

BACKGROUND

Since glycosylation depends on glycosyltransferases, glycosidases, and sugar nucleotide donors, it is susceptible to the changes associated with physiological and pathological conditions. Therefore, alterations in glycan structures may be good targets and biomarkers for monitoring health conditions. Since human aging and longevity are affected by genetic and environmental factors such as diseases, lifestyle, and social factors, a scale that reflects various environmental factors is required in the study of human aging and longevity.

SCOPE OF REVIEW

We herein focus on glycosylation changes elucidated by glycomic and glycoproteomic studies on aging, longevity, and age-related diseases including cognitive impairment, diabetes mellitus, and frailty. We also consider the potential of glycan structures as biomarkers and/or targets for monitoring physiological and pathophysiological changes.

MAJOR CONCLUSIONS

Glycan structures are altered in age-related diseases. These glycans and glycoproteins may be involved in the pathophysiology of these diseases and, thus, be useful diagnostic markers. Age-dependent changes in N-glycans have been reported previously in cohort studies, and characteristic N-glycans in extreme longevity have been proposed. These findings may lead to a deeper understanding of the mechanisms underlying aging as well as the factors influencing longevity.

GENERAL SIGNIFICANCE

Alterations in glycosylation may be good targets and biomarkers for monitoring health conditions, and be applicable to studies on age-related diseases and healthy aging. This article is part of a Special Issue entitled "Glycans in personalised medicine" Guest Editor: Professor Gordan Lauc.