Systematic Review: Immunoglobulin G N-Glycans as Next-Generation Diagnostic Biomarkers for Common Chronic Diseases

Crosstalk Between Cytokines and IgG N-Glycosylation: Bidirectional Effects and Relevance to Clinical Innovation for Inflammatory Diseases

The crosstalk between cytokines and immunoglobulin G (IgG) N-glycosylation forms a bidirectional regulatory network that significantly impacts inflammation and immune function. This review examines how various cytokines, both pro- and anti-inflammatory, modulate IgG N-glycosylation, shaping antibody activity and influencing inflammatory responses. In addition, we explore how altered IgG N-glycosylation patterns affect cytokine production and immune signaling, either promoting or reducing inflammation. Through a comprehensive analysis of current studies, this review underscores the dynamic relationship between cytokines and IgG N-glycosylation. These insights enhance our understanding of the mechanisms underlying inflammatory diseases and contribute to improved strategies for disease prevention, diagnosis, monitoring, prognosis, and the exploration of novel treatment options. By focusing on this crosstalk, we identify new avenues for developing innovative diagnostic tools and therapies to improve patient outcomes in inflammatory diseases.

LC-MS/MS of isomeric N-and O-glycopeptides on mesoporous graphitized carbon column

BACKGROUND

The study of glycopeptides is associated with challenges regarding the microheterogeneity of different isomeric glycans occupying the same glycosylation sites in glycoproteins. It is immensely valuable to perform both qualitative and quantitative site-specific glycosylation analysis of glycopeptide isomers due to their link to several diseases. Achieving isomeric separation of glycopeptides is particularly challenging due to the low abundance of glycopeptides as well as inefficient ionization. Although some methods have demonstrated the isomeric separation of glycopeptides, a more efficient nanoflow-based stationary phase is needed for the isomeric separation of both N- and O-glycopeptides.

RESULTS

In this study, the separation of N- and O-glycopeptide isomers at 75 °C was achieved with an in-house packed 1 cm long mesoporous graphitized carbon (MGC) column. Different gradient compositions of the optimized mobile phase for separating permethylated glycans on MGC column were tested, and we observed efficient separation of N- and O-glycopeptide isomers at a gradient elution time of 120 min. After achieving the isomeric separation of sialylated glycopeptides from model glycoproteins derived from bovine fetuin, the separation of isomeric glycopeptides derived from asialofetuin, α-1 glycoprotein and human blood serum were also demonstrated. Furthermore, the developed method for the separation of isomeric N- and O-glycopeptide on MGC column showed high reproducibility over three months. We observed an average retention time shift of 1 min and consistent resolution of separated peaks throughout three months.

SIGNIFICANCE AND NOVELTY

MGC column can serve as an efficient tool for obtaining the isomeric separation of N- and O-glycopeptide from complex biological samples in future studies. This will enable a more profound understanding of the roles played by isomeric N- and O-glycopeptide in important biological processes and their correlations to various disease progressions.

Twin Scholarships of Glycomedicine and Precision Medicine in Times of Single-Cell Multiomics

Systems biology and multiomics research expand the prospects of planetary health innovations. In this context, this mini-review unpacks the twin scholarships of glycomedicine and precision medicine in the current era of single-cell multiomics. A significant growth in glycan research has been observed over the past decade, unveiling and establishing co- and post-translational modifications as dynamic indicators of both pathological and physiological conditions. Systems biology technologies have enabled large-scale and high-throughput glycoprofiling and access to data-intensive biological repositories for global research. These advancements have established glycans as a pivotal third code of life, alongside nucleic acids and amino acids. However, challenges persist, particularly in the simultaneous analysis of the glycome and transcriptome in single cells owing to technical limitations. In addition, holistic views of the complex molecular interactions between glycomics and other omics types remain elusive. We underscore and call for a paradigm shift toward the exploration of integrative glycan platforms and analysis methods for single-cell multiomics research and precision medicine biomarker discovery. The integration of multiple datasets from various single-cell omics levels represents a crucial application of systems biology in understanding complex cellular processes and is essential for advancing the twin scholarships of glycomedicine and precision medicine.

Development of an impedance-based biosensor for determination of IgG galactosylation levels

The glycan profile of immunoglobulin G (IgG) molecule and its changes are associated with a number of different diseases. Galactosylation of IgG was recently suggested as a potential biomarker for rheumatoid arthritis, inflammatory bowel disease and many cancers. In this paper, we propose a portable impedance-based biosensor that utilizes lectin array technology to detect glycans in IgG. Biotinylated Griffonia simplicifolia (GSL II) and Ricinus communis agglutinin I (RCA I) lectins were used in our biosensor design for determination of the ratio of N-acetyl glucosamine (GlcNAc) to galactose (Gal) respectively, which is termed agalactosylation factor (AF). Streptavidin gold nanoparticles (GNP) were conjugated to biotinylated lectin bonded to the carbohydrate in the glycoprotein to magnify the change in impedance signal and enhance detection sensitivity. The method was successfully applied to differentiation of the galactosylation levels in human and rat IgG. In addition, we present proof of concept use of our biosensor for differentiation of COVID-19 positive patient samples from negative patients. Consequently, the sensor can be useful in future applications to distinguish between glycan profiles of IgG from healthy and patient samples in disease studies. Our biosensor permits analysis of human serum without conventional time-consuming IgG purification steps or pretreatment using enzyme digestion to cut the sugars from the glycoprotein molecule. The results suggest that the proposed point of care (POC) biosensor can be used for evaluating disease progression and treatment efficacy via monitoring changes in the galactosylation profiles of IgG in patients.

Unravelling the genetic causality of immunoglobulin G N-glycans in ischemic stroke

BACKGROUND

Evidence suggests that immunoglobulin G (IgG) N-glycosylation is associated with ischemic stroke (IS). However, the causality of IgG N-glycosylation for IS remains unknown.

METHODS

Two-sample Mendelian randomization (MR) analyses were performed to investigate the potential causal effects of genetically determined IgG N-glycans on IS using publicly available summarized genetic data from East Asian and European populations. Genetic instruments were used as proxies for IgG N-glycan traits. IgG N-glycans were analysed using ultra-performance liquid chromatography. Four complementary MR methods were performed, including the inverse variance weighted method (IVW), MR‒Egger, weighted median and penalized weighted median. Furthermore, to further test the robustness of the results, MR based on Bayesian model averaging (MR-BMA) was then applied to select and prioritize IgG N-glycan traits as risk factors for IS.

RESULTS

After correcting for multiple testing, in two-sample MR analyses, genetically predicted IgG N-glycans were unrelated to IS in both East Asian and European populations, and the results remained consistent and robust in the sensitivity analysis. Moreover, MR-BMA also showed consistent results in both East Asian and European populations.

CONCLUSIONS

Contrary to observational studies, the study did not provide enough genetic evidence to support the causal associations of genetically predicted IgG N-glycan traits and IS, suggesting that N-glycosylation of IgG might not directly involve in the pathogenesis of IS.

Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples

Alterations of protein glycosylation can serve as sensitive and specific disease biomarkers. Labeling procedures for improved separation and detectability of oligosaccharides have several drawbacks, including incomplete derivatization, side-products, noticeable desialylation/defucosylation, sample loss, and interference with downstream analyses. Here, we develop a label-free workflow based on high sensitivity capillary zone electrophoresis-mass spectrometry (CZE-MS) for profiling of native underivatized released N-glycans. Our workflow provides a >45-fold increase in signal intensity compared to the conventional CZE-MS approaches used for N-glycan analysis. Qualitative and quantitative N-glycan profiling of purified human serum IgG, bovine serum fetuin, bovine pancreas ribonuclease B, blood-derived extracellular vesicle isolates, and total plasma results in the detection of >250, >400, >150, >310, and >520 N-glycans, respectively, using injected amounts equivalent to <25 ng of model protein and nL-levels of plasma-derived samples. Compared to reported results for biological samples of similar amounts and complexity, the number of identified N-glycans is increased up to ~15-fold, enabling highly sensitive analysis of sample amounts as low as sub-0.2 nL of plasma volume equivalents. Furthermore, highly sialylated N-glycans are identified and structurally characterized, and untreated sialic acid-linkage isomers are resolved in a single CZE-MS analysis.

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.

Three Major Gastrointestinal Cancers Could Be Distinguished through Subclass-Specific IgG Glycosylation

Esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC) are three major digestive tract tumors with higher morbidity and mortality due to significant molecular heterogeneity. Altered IgG glycosylation has been observed in inflammatory activities and disease progression, and the IgG glycome profile could be used for disease stratification. However, IgG N-glycome profiles in these three cancers have not been systematically investigated. Herein, subclass-specific IgG glycosylation in CRC, GC, and EC was comprehensively characterized by liquid chromatography-tandem mass spectrometry. It was found that IgG1 sialylation was decreased in all three cancers, and the alterations in CRC and EC may be subclass-specific. IgG4 mono-galactosylation was increased in all three cancers, which was a subclass-specific change in all of them. Additionally, glycopeptides of IgG1-H5N5, IgG2-H4N3F1, and IgG4-H4N4F1 could distinguish all three cancer groups from controls with fair diagnostic performance. Furthermore, bioinformatics verified the differential expression of relevant glycosyltransferase genes in cancer progression. Significantly, those three gastrointestinal cancers could be distinguished from each other using subclass-specific IgG glycans. These findings demonstrated the spatial and temporal diversity of IgG N-glycome among digestive cancers, increasing our understanding of the molecular mechanisms of EC, GC, and CRC pathogenesis.

B-cell-specific ablation of β-1,4-galactosyltransferase 1 prevents aging-related IgG glycans changes and improves aging phenotype in mice

IgG N-glycans levels change with advancing age, making it a potential biomarker of aging. β-1,4-galactosyltransferase (B4GALT) gene expression levels also increase with aging. Ultra performance liquid chromatography (UPLC) was used to examine changes inserum IgG N-glycans at six time points during the aging process. Most serum IgG N-glycans changed with aging in WT but not in CD19-cre B4GALT1 floxed mice. The relative abundance of fucosylated biantennary glycans with or without Neu5Gc structures changed with aging in heterozygous B4GALT1 floxed mice but not in homozygous B4GALT1 floxed mice. Additionally, the aging phenotype was more apparent in WT mice than in B4GALT1 floxed mice. These results demonstrate that fucosylated biantennary glycans and fucosylated biantennary glycans containing N-glycolylneuraminic acid (Neu5Gc)-linked N-acetyllactosamine (LacNAc) were highly associated with aging and were affected by the B4GALT1 floxed mouse genotype. The changing levels of fucosylated monoantennary glycans observed with aging in WT mice was reversed in B4GALT1 floxed mice and was not sex specific. In summary, B-cell-specific ablation of B4GALT1 from a glycoproteomic perspective prevented age-related changes in IgG N-glycans in mice. SIGNIFICANCE: In this study, serum IgG glycoproteomic data in wild-type (WT) and B-cell-specific ablation of β-1,4-galactosyltransferase 1 mice (B4GALT) were analyzed. Results showed that fucosylated biantennary glycans with or without N-glycolylneuraminic acid (Neu5Gc)-linked N-acetyllactosamine (LacNAc) were highly associated with aging and were also affected by the B4GALT1 floxed mouse genotype. In terms of gender-specific information, the trend towards elevated fucosylated monoantennary glycans in WT mice was not seen in CD19-cre B4GALT1 floxed mice in either sex. B-cell-specific ablation of B4GALT1 plays an important role in age-related glycan changes; its specific functions and mechanisms are worthy of in-depth study. Our data suggest that investigating the relationship between galactosylation and aging may help advance the field of glycoproteomics and aging research.

Genome-Wide Mapping of Plasma IgG N-Glycan Quantitative Trait Loci Identifies a Potentially Causal Association between IgG N-Glycans and Rheumatoid Arthritis

Observational studies highlight associations of IgG N-glycosylation with rheumatoid arthritis (RA); however, the causality between these conditions remains to be determined. Standard and multivariable two-sample Mendelian randomization (MR) analyses integrating a summary genome-wide association study for RA and IgG N-glycan quantitative trait loci (IgG N-glycan-QTL) data were performed to explore the potentially causal associations of IgG N-glycosylation with RA. After correcting for multiple testing (p < 2 × 10^-3), the standard MR analysis based on the inverse-variance weighted method showed a significant association of genetically instrumented IgG N-glycan (GP4) with RA (odds ratio_GP4 = 0.906, 95% confidence interval = 0.857-0.958, p = 5.246 × 10^-4). In addition, we identified seven significant associations of genetically instrumented IgG N-glycans with RA by multivariable MR analysis (p < 2 × 10^-3). Results were broadly consistent in sensitivity analyses using MR_Lasso, MR_weighted median, MR_Egger regression, and leave-one-out analysis with different instruments (all p values <0.05). There was limited evidence of pleiotropy bias (all p values > 0.05). In conclusion, our MR analysis incorporating genome-wide association studies and IgG N-glycan-QTL data revealed that IgG N-glycans were potentially causally associated with RA. Our findings shed light on the role of IgG N-glycosylation in the development of RA. Future studies are needed to validate our findings and to explore the underlying physiological mechanisms in the etiology of RA.

N-Glycosylation Patterns across the Age-Related Macular Degeneration Spectrum

The pathogenesis of age-related macular degeneration (AMD) remains elusive, despite numerous research studies. Therefore, we aimed to investigate the changes of plasma and IgG-specific N-glycosylation across the disease severity spectrum. We examined 2835 subjects from the 10.001 Dalmatians project, originating from the isolated Croatian islands of Vis and Korčula. All subjects were classified into four groups, namely (i) bilateral AMD, (ii) unilateral AMD, (iii) early-onset drusen, and (iv) controls. We analysed plasma and IgG N-glycans measured by HPLC and their association with retinal fundus photographs. There were 106 (3.7%) detected cases of AMD; 66 of them were bilateral. In addition, 45 (0.9%) subjects were recorded as having early-onset retinal drusen. We detected several interesting differences across the analysed groups, suggesting that N-glycans can be used as a biomarker for AMD. Multivariate analysis suggested a significant decrease in the immunomodulatory bi-antennary glycan structures in unilateral AMD (adjusted odds ratio 0.43 (95% confidence interval 0.22–0.79)). We also detected a substantial increase in the pro-inflammatory tetra-antennary plasma glycans in bilateral AMD (7.90 (2.94–20.95)). Notably, some of these associations were not identified in the aggregated analysis, where all three disease stages were collapsed into a single category, suggesting the need for better-refined phenotypes and the use of disease severity stages in the analysis of more complex diseases. Age-related macular degeneration progression is characterised by the complex interplay of various mechanisms, some of which can be detected by measuring plasma and IgG N-glycans. As opposed to a simple case-control study, more advanced and refined study designs are needed to understand the pathogenesis of complex diseases.

N-glycosylation of immunoglobulin G predicts incident hypertension

OBJECTIVES

Glycosylation of immunoglobulin G (IgG) is an important regulator of the immune system and has been implicated in prevalent hypertension. The aim of this study is to investigate whether the IgG glycome begins to change prior to hypertension diagnosis by analysing the IgG glycome composition in a large population-based female cohort with two independent replication samples.

METHODS

We included 989 unrelated cases with incident hypertension and 1628 controls from the TwinsUK cohort (mean follow-up time of 6.3 years) with IgG measured at baseline by ultra-performance liquid chromatography and longitudinal BP measurement available. We replicated our findings in 106 individuals from the 10 001 Dalmatians and 729 from KORA S4. Cox regression mixed models were applied to identify changes in glycan traits preincident hypertension, after adjusting for age, mean arterial pressure, BMI, family relatedness and multiple testing (FDR < 0.1). Significant IgG-incident hypertension associations were replicated in the two independent cohorts by leveraging Cox regression mixed models in the 10 001 Dalmatians and logistic regression models in the KORA cohort.

RESULTS

We identified and replicated four glycan traits, incidence of bisecting GlcNAc, GP4, GP9 and GP21, that are predictive of incident hypertension after adjusting for confoundes and multiple testing [hazard ratio (95% CI) ranging from 0.45 (0.24-0.84) for GP21 to 2.9 (1.5-5.68) for GP4]. We then linearly combined the four replicated glycans and found that the glycan score correlated with incident hypertension, SBP and DBP.

CONCLUSION

Our results suggest that the IgG glycome changes prior to the development of hypertension.

IgG N-glycans

Glycosylation, one of the most common post-translational modifications in mammalian cells, impacts many biological processes such as cell adhesion, proliferation and differentiation. As the most abundant glycoprotein in human serum, immunoglobulin G (IgG) plays a vital role in immune response and protection. There is a growing body of evidence suggests that IgG structure and function are modulated by attached glycans, especially N-glycans, and aberrant glycosylation is associated with disease states. In this chapter, we review IgG glycan repertoire and function, strategies for profiling IgG N-glycome and recent studies. Mass spectrometry (MS) based techniques are the most powerful tools for profiling IgG glycome. IgG glycans can be divided into high-mannose, biantennary complex and hybrid types, modified with mannosylation, core-fucosylation, galactosylation, bisecting GlcNAcylation, or sialylation. Glycosylation of IgG affects antibody half-life and their affinity and avidity for antigens, regulates crystallizable fragment (Fc) structure and Fcγ receptor signaling, as well as antibody effector function. Because of their critical roles, IgG N-glycans appear to be promising biomarkers for various disease states. Specific IgG glycosylation can convert a pro-inflammatory response to an anti-inflammatory activity. Accordingly, IgG glycoengineering provides a powerful approach to potentially develop effective drugs and treat disease. Based on the understanding of the functional role of IgG glycans, the development of vaccines with enhanced capacity and long-term protection are possible in the near future.

Variation of IgG N-linked glycosylation profile in diabetic retinopathy

BACKGROUND

The relationship of immunoglobulin G (IgG) glycosylation with diabetes and diabetic nephropathy has been reported, but its role in diabetic retinopathy (DR) remains unclear. We aimed to investigate and validate the association of IgG glycosylation with DR.

METHODS

We analyzed the IgG N-linked glycosylation profile and primarily selected candidate glycans by lasso (least absolute shrinkage and selection operator) regression analysis in the discovery population. The findings were validated in the replication population using a binary logistics model. The association between the significant glycosylation panel and clinical features was illustrated with Spearman's coefficient. The results were confirmed by sensitivity analyses.

RESULTS

Among 16 selected glycan candidates using lasso, two IgG glycans (GP15, GP20) and two derived traits (IGP32, IGP54) were identified and validated to be significantly associated with DR (P < .05), and the combined adjusted odds ratios (ORs) were 0.587, 0.613, 1.970, and 0.593, respectively. The glycosylation panel showed a weak correlation with clinical features, except for age. In addition, the results remained consistent when the subjects with prediabetes were excluded from the controls, and the adjusted ORs were 0.677, 0.738, 1.597, and 0.678 in the whole population. Furthermore, in the 1:3 rematched population, a significant association was observed, apart from GP20.

CONCLUSIONS

The IgG glycosylation profile, reflecting an aging and pro-inflammatory status, was significantly associated with DR. The variation in the IgG glycome deserves more attention in diabetic complications.

Glycoproteins as diagnostic and prognostic biomarkers for neurodegenerative diseases: A glycoproteomic approach

Neurodegenerative diseases (NDs) are incurable and can develop progressively debilitating disorders, including dementia and ataxias. Alzheimer's disease and Parkinson's disease are the most common NDs that mainly affect the elderly people. There is an urgent need to develop new diagnostic tools so that patients can be accurately stratified at an early stage. As a common post-translational modification, protein glycosylation plays a key role in physiological and pathological processes. The abnormal changes in glycosylation are associated with the altered biological pathways in NDs. The pathogenesis-related proteins, like amyloid-β and microtubule-associated protein tau, have altered glycosylation. Importantly, specific glycosylation changes in cerebrospinal fluid, blood and urine are valuable for revealing neurodegeneration in the early stages. This review describes the emerging biomarkers based on glycoproteomics in NDs, highlighting the potential applications of glycoprotein biomarkers in the early detection of diseases, monitoring of the disease progression, and measurement of the therapeutic responses. The mass spectrometry-based strategies for characterizing glycoprotein biomarkers are also introduced.

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.

Automation of Immunoglobulin Glycosylation Analysis

The development of reliable, affordable, high-resolution glycomics technologies that can be used for many samples in a high-throughput manner are essential for both the optimization of glycosylation in the biopharmaceutical industry as well as for the advancement of clinical diagnostics based on glycosylation biomarkers. We will use this chapter to review the sample preparation processes that have been used on liquid-handling robots to obtain high-quality glycomics data for both biopharmaceutical and clinical antibody samples. This will focus on glycoprotein purification, followed by glycan or glycopeptide generation, derivatization and enrichment. The use of liquid-handling robots for glycomics studies on other sample types beyond antibodies will not be discussed here. We will summarize our thoughts on the current status of the field and explore the benefits and challenges associated with developing and using automated platforms for sample preparation. Finally, the future outlook for the automation of glycomics will be discussed along with a projected impact on the field in general.

Association of IgG Glycosylation and Esophageal Precancerosis Beyond Inflammation

This study aimed to investigate the association of IgG glycosylation and esophageal precancerosis for squamous cell carcinoma and determine its role in inflammation. Primary glycans selected by the least absolute shrinkage and selection operator (LASSO) algorithm were validated using univariate and multivariate logistics models plus restricted cubic spline functions. In total, 24 direct glycans and 27 derived traits were detected, among which four glycans and three derived traits were primarily selected. Then, GP5 (adjusted OR: 0.805), GP17 (adjusted OR: 1.305), G12n (adjusted OR: 1.271), Gal_1 (adjusted OR: 0.776) and Fuc (adjusted OR: 0.737) were validated and significantly associated with esophageal precancerosis. In addition, there was a consistent positive association in GP17 and G12n and a negative association in GP5, Gal_1, and Fuc by restricted cubic spline function. Compared with esophageal inflammation, GP17, G12n, and Fuc were still independently associated with precancerosis. In brief, the IgG glycosylation profile was independently associated with esophageal precancerosis beyond inflammation, which could be an early biomarker for esophageal cancer.Prevention Relevance: IgG glycosylation profile is associated with esophageal precancerosis and specific IgG glycans involves in the early stage of esophageal cancer, which is independent of inflammation.

Microbiome and Longevity: High Abundance of Longevity-Linked Muribaculaceae in the Gut of the Long-Living Rodent Spalax leucodon

With a world population living longer as well as marked disparities in life expectancy, understanding the determinants of longevity is one of the priority research agendas in 21st century life sciences. To this end, the blind mole-rat (Spalax leucodon), a subterranean mammalian, has emerged as an exceptional model organism due to its astonishing features such as remarkable longevity, hypoxia and hypercapnia tolerance, and cancer resistance. The microbiome has been found to be a vital parameter for cellular physiology and it is safe to assume that it has an impact on life expectancy. Although the unique characteristics of Spalax make it an ideal experimental model for longevity research, there is limited knowledge of the bacterial composition of Spalax microbiome, which limits its in-depth utilization. In this study, using 16S rRNA amplicon sequencing, we report the gut and skin bacterial structure of Spalax for the first time. The diversity between fecal and skin samples was manifested in the distant clustering, as revealed by beta diversity analysis. Importantly, the longevity-linked Muribaculaceae bacterial family was found to be the dominating bacterial taxa in Spalax fecal samples. These new findings contribute toward further development of Spalax as a model for longevity research and potential linkages between microbiome composition and longevity.

Coronavirus Disease-2019 Treatment Strategies Targeting Interleukin-6 Signaling and Herbal Medicine

Coronavirus disease-2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is evolving across the world and new treatments are urgently needed as with vaccines to prevent the illness and stem the contagion. The virus affects not only the lungs but also other tissues, thus lending support to the idea that COVID-19 is a systemic disease. The current vaccine and treatment development strategies ought to consider such systems medicine perspectives rather than a narrower focus on the lung infection only. COVID-19 is associated with elevated levels of the inflammatory cytokines such as interleukin-6 (IL-6), IL-10, and interferon-gamma (IFN-γ). Elevated levels of cytokines and the cytokine storm have been linked to fatal disease. This suggests new therapeutic strategies through blocking the cytokine storm. IL-6 is one of the major cytokines associated with the cytokine storm. IL-6 is also known to display pleiotropic/diverse pathophysiological effects. We suggest the blockage of IL-6 signaling and its downstream mediators such as Janus kinases (JAKs), and signal transducer and activators of transcription (STATs) offer potential hope for the treatment of severe cases of COVID-19. Thus, repurposing of already approved IL-6-JAK-STAT signaling inhibitors as well as other anti-inflammatory drugs, including dexamethasone, is under development for severe COVID-19 cases. We conclude this expert review by highlighting the potential role of precision herbal medicines, for example, the Cannabis sativa, provided that omics technologies can be utilized to build a robust scientific evidence base on their clinical safety and efficacy. Precision herbal medicine buttressed by omics systems science would also help identify new molecular targets for drug discovery against COVID-19.

Glycomics: Immunoglobulin G N-Glycosylation Associated with Mammary Gland Hyperplasia in Women

Mammary gland hyperplasia (MGH) is very common, especially among young and middle-aged women. New diagnostics and biomarkers for MGH are needed for rational clinical management and precision medicine. We report, in this study, new findings using a glycomics approach, with a focus on immunoglobulin G (IgG) N-glycosylation. A cross-sectional study was conducted in a community-based population sample in Beijing, China. A total of 387 participants 40-65 years of age were enrolled in this study, including 194 women with MGH (cases) and 193 women who had no MGH (controls). IgG N-glycans were characterized in the serum by ultra-performance liquid chromatography. The levels of the glycan peaks (GPs) GP2, GP5, GP6, and GP7 were lower in the MGH group compared with the control group, whereas GP14 was significantly higher in the MGH group (p < 0.05). A predictive model using GP5, GP21, and age was established and a receiver operating characteristic curve analysis was performed. The sensitivity and specificity of the model for MGH was 61.3% and 63.2%, respectively, likely owing to receptor mechanisms and/or inflammation regulation. To the best of our knowledge, this is the first study reporting on an association between IgG N-glycosylation and MGH. We suggest person-to-person variations in IgG N-glycans and their combination with multiomics biomarker strategies offer a promising avenue to identify novel diagnostics and individuals at increased risk of MGH.

Digging Deeper into Precision/Personalized Medicine: Cracking the Sugar Code, the Third Alphabet of Life, and Sociomateriality of the Cell

Precision/personalized medicine is a hot topic in health care. Often presented with the motto "the right drug, for the right patient, at the right dose, and the right time," precision medicine is a theory for rational therapeutics as well as practice to individualize health interventions (e.g., drugs, food, vaccines, medical devices, and exercise programs) using biomarkers. Yet, an alien visitor to planet Earth reading the contemporary textbooks on diagnostics might think precision medicine requires only two biomolecules omnipresent in the literature: nucleic acids (e.g., DNA) and proteins, known as the first and second alphabet of biology, respectively. However, the precision/personalized medicine community has tended to underappreciate the third alphabet of life, the "sugar code" (i.e., the information stored in glycans, glycoproteins, and glycolipids). This article brings together experts in precision/personalized medicine science, pharmacoglycomics, emerging technology governance, cultural studies, contemporary art, and responsible innovation to critically comment on the sociomateriality of the three alphabets of life together. First, the current transformation of targeted therapies with personalized glycomedicine and glycan biomarkers is examined. Next, we discuss the reasons as to why unraveling of the sugar code might have lagged behind the DNA and protein codes. While social scientists have historically noted the importance of constructivism (e.g., how people interpret technology and build their values, hopes, and expectations into emerging technologies), life scientists relied on the material properties of technologies in explaining why some innovations emerge rapidly and are more popular than others. The concept of sociomateriality integrates these two explanations by highlighting the inherent entanglement of the social and the material contributions to knowledge and what is presented to us as reality from everyday laboratory life. Hence, we present a hypothesis based on a sociomaterial conceptual lens: because materiality and synthesis of glycans are not directly driven by a template, and thus more complex and open ended than sequencing of a finite length genome, social construction of expectations from unraveling of the sugar code versus the DNA code might have evolved differently, as being future-uncertain versus future-proof, respectively, thus potentially explaining the "sugar lag" in precision/personalized medicine diagnostics over the past decades. We conclude by introducing systems scientists, physicians, and biotechnology industry to the concept, practice, and value of responsible innovation, while glycomedicine and other emerging biomarker technologies (e.g., metagenomics and pharmacomicrobiomics) transition to applications in health care, ecology, pharmaceutical/diagnostic industries, agriculture, food, and bioengineering, among others.

IgG Glycosylation Profile and the Glycan Score Are Associated with Type 2 Diabetes in Independent Chinese Populations: A Case-Control Study

BACKGROUND

The relationship between the IgG glycan panel and type 2 diabetes remains unclear in Chinese population. We aimed to investigate the association of the IgG glycan profile and glycan score with type 2 diabetes.

METHODS

In the discovery population, 162 individuals diagnosed with type 2 diabetes and 162 matched controls from Beijing health management cohort were included. We analyzed the IgG glycan profile and composed a glycan score for type 2 diabetes. Findings were validated in the replication population from Beijing Xuanwu community cohort (280 cases and 508 controls). Area under curve (AUC) using 10-fold and bootstrap validation, net reclassification index (NRI), and integrated discrimination index (IDI) were calculated for the glycan score.

RESULTS

In the discovery population, 5 initial IgG glycans and 7 derived traits were significantly associated with type 2 diabetes after Bonferroni correction and Lasso selection, which were validated in the replication population subsequently. The glycan score composed of these IgG glycans and traits showed a strong association with type 2 diabetes (combined odds ratio (OR): 3.78) and its risk factors. In the replication population, AUC of the model involving clinical traits improved from 0.74 to above 0.90, and the values of NRI and IDI were 0.35 and 0.42, respectively, with the glycan score added.

CONCLUSIONS

IgG glycosylation profiles were associated with type 2 diabetes and the glycan score may be a novel indicator for diabetes which reflected a proinflammatory status.