Immunoglobulin G N-glycans Research Articles

Predicting Biochemical and Physiological Parameters: Deep Learning from IgG Glycome Composition.

In immunoglobulin G (IgG), N-glycosylation plays a pivotal role in structure and function. It is often altered in different diseases, suggesting that it could be a promising health biomarker. Studies indicate that IgG glycosylation not only associates with various diseases but also has predictive capabilities. Additionally, changes in IgG glycosylation correlate with physiological and biochemical traits known to reflect overall health state. This study aimed to investigate the power of IgG glycans to predict physiological and biochemical parameters. We developed two models using IgG N-glycan data as an input: a regression model using elastic net and a machine learning model using deep learning. Data were obtained from the Korčula and Vis cohorts. The Korčula cohort data were used to train both models, while the Vis cohort was used exclusively for validation. Our results demonstrated that IgG glycome composition effectively predicts several biochemical and physiological parameters, especially those related to lipid and glucose metabolism and cardiovascular events. Both models performed similarly on the Korčula cohort; however, the deep learning model showed a higher potential for generalization when validated on the Vis cohort. This study reinforces the idea that IgG glycosylation reflects individuals' health state and brings us one step closer to implementing glycan-based diagnostics in personalized medicine. Additionally, it shows that the predictive power of IgG glycans can be used for imputing missing covariate data in deep learning frameworks.

Potentially causal association between immunoglobulin G N-glycans and cardiometabolic diseases: Bidirectional two-sample Mendelian randomization study

BackgroundObservational studies support that altered immunoglobulin G (IgG) N-glycosylation and inflammatory factors are associated with cardiometabolic diseases (CMDs); nevertheless, the causality between them remains unclear. MethodsTwo-sample Mendelian randomization (MR) analyses were conducted to systematically investigate the bidirectional causality between IgG N-glycans and nine CMDs in both East Asians and Europeans. ResultsIn the forward MR analysis, the univariable MR analysis presented suggestive causality of 14 and eight genetically instrumented IgG N-glycans with CMDs in East Asians and Europeans, respectively; the multivariable MR analysis showed that ten and 11 pairs of glycan-CMD associations were identified in East Asian and European populations, respectively. In the reverse MR analysis, based on East Asians and Europeans, the univariable MR analysis presented suggestive causality of seven and 12 genetically instrumented CMDs with IgG N-glycans, respectively; the multivariable MR analysis presented that six and five CMD-glycan causality were found in East Asian and Europeans, respectively. ConclusionsThe comprehensive MR analyses provide suggestive evidence of bidirectional causality between IgG N-glycans and CMDs. This work helps to understand the molecular mechanism of the occurrence/progression of CMDs, optimize existing and develop new strategies to prevent CMDs, and contribute to the early identification of high-risk groups of CMDs.

Glycan clock of ageing-analytical precision and time-dependent inter- and i-individual variability.

Ageing is a complex biological process with variations among individuals, leading to the development of ageing clocks to estimate biological age. Glycans, particularly in immunoglobulin G (IgG), have emerged as potential biomarkers of ageing, with changes in glycosylation patterns correlating with chronological age.For precision analysis, three different plasma pools were analysed over 26days in tetraplicates, 312 samples in total. In short-term variability analysis, two cohorts were analysed: AstraZeneca MFO cohort of 26 healthy individuals (median age 20) and a cohort of 70 premenopausal Chinese women (median age 22.5) cohort monitored over 3months. Long-term variability analysis involved two adult men aged 47 and 57, monitored for 5 and 10years, respectively. Samples were collected every 3months and 3weeks, respectively. IgG N-glycan analysis followed a standardized approach by isolating IgG, its subsequent denaturation and deglycosylation followed by glycan cleanup and labelling. Capillary gel electrophoresis with laser-induced fluorescence (CGE-LIF) and ultra-performance liquid chromatography analyses were employed for glycan profiling. Statistical analysis involved normalization, batch correction, and linear mixed models to assess time effects on derived glycan traits.The intermediate precision results consistently exhibited very low coefficient of variation values across all three test samples. This consistent pattern underscores the high level of precision inherent in the CGE method for analysing the glycan clock of ageing. The AstraZeneca MFO cohort did not show any statistically significant trends, whereas the menstrual cycle cohort exhibited statistically significant trends in digalactosylated (G2), agalactosylated (G0) and fucosylation (F). These trends were attributed to the effects of the menstrual cycle. Long-term stability analysis identified enduring age-related trends in both subjects, showing a positive time effect in G0 and bisected N-acetylglucosamine, as well as a negative time effect in G2 and sialylation, aligning with earlier findings. Time effects measured for monogalactosylation, and F remained substantially lower than ones observed for other traits.The study found that IgG N-glycome analysis using CGE-LIF exhibited remarkably high intermediate precision. Moreover, the study highlights the short- and long-term stability of IgG glycome composition, coupled with a notable capacity to adapt and respond to physiological changes and environmental influences such as hormonal changes, disease, and interventions. The discoveries from this study propel personalized medicine forward by deepening our understanding of how IgG glycome relates to age-related health concerns. This study underscores the reliability of glycans as a biomarker for tracking age-related changes and individual health paths.

Bidirectional Two-Sample Mendelian Randomization Study of Immunoglobulin G N-Glycosylation and Senescence-Associated Secretory Phenotype.

Observational studies revealed changes in Immunoglobulin G (IgG) N-glycosylation during the aging process. However, it lacks causal insights and remains unclear in which direction causal relationships exist. The two-sample bidirectional Mendelian randomization (MR) design was adopted to explore causal associations between IgG N-glycans and the senescence-associated secretory phenotype (SASP). Inverse variance weighted (IVW) and Wald ratio methods were used as the main analyses, supplemented by sensitivity analyses. Forward MR analyses revealed causal associations between the glycan peak (GP) and SASP, including GP6 (odds ratio [OR] = 0.428, 95% confidence interval [CI] = 0.189-0.969) and GP17 (OR = 0.709, 95%CI = 0.504-0.995) with growth/differentiation factor 15 (GDF15), GP19 with an advanced glycosylation end-product-specific receptor (RAGE) (OR = 2.142, 95% CI = 1.384-3.316), and GP15 with matrix metalloproteinase 2 (MMP2) (OR = 1.136, 95% CI =1.008-1.282). The reverse MR indicated that genetic liability to RAGE was associated with increased levels of GP17 (OR = 1.125, 95% CI = 1.003-1.261) and GP24 (OR = 1.222, 95% CI = 1.046-1.428), while pulmonary and activation-regulated chemokines (PARC) exhibited causal associations with GP10 (OR = 1.269, 95% CI = 1.048-1.537) and GP15 (OR = 1.297, 95% CI = 1.072-1.570). The findings provided suggested evidence on the bidirectional causality between IgG N-glycans and SASP, which might reveal potential regulatory mechanisms.

An integrated method for IgG N-glycans enrichment and analysis: Understanding the role of IgG glycosylation in diabetic foot ulcer

Diabetic foot ulcer (DFU) is the most common and serious complication of diabetes, and its incidence, disability, and mortality rates are increasing worldwide. The pathogenesis of DFU is associated with dysregulated inflammation mediated by abnormal immunoglobulin G (IgG) glycosylation. In this study, we developed a comprehensive method for IgG N-linked glycosylation in the serum of DFU patients. Through analysis, we identified 31 IgG1 glycans, 32 IgG2 glycans, and 30 IgG4 glycans in the DFU serum. Furthermore, 13 IgG1 glycans, 12 IgG2 glycans, and 5 IgG4 glycans in the DFU groups were found to be significantly different from those of the control groups (p < 0.05). Of these, compared with the control group, one glycan was unique to DFU patients, and seven glycans were not detected in the DFU group. In terms of glycan characteristics, we observed a substantial decrease in galactosylation, sialylation and bisecting GlcNAcylation, and a significant increase in agalactosylation. Abnormal IgG N-glycosylation modifications were significantly associated with the chronic inflammation that is characteristic of DFU. Further, this is the first comprehensive analysis of subclass-specific IgG N-glycosylation in DFU patients, which not only fills the gap of DFU in terms of the pathological mechanisms related to IgG glycosylation but also may provide valuable clues for the immunotherapeutic pathway of DFU.

Association between immunoglobulin G N-glycosylation and lupus nephritis in female patients with systemic lupus erythematosus: a case-control study.

Lupus nephritis (LN) is a crucial complication of systemic lupus erythematosus (SLE) and has important clinical implications in guiding treatment. N-glycosylation of immunoglobulin G (IgG) plays a key role in the development of SLE by affecting the balance of anti-inflammatory and proinflammatory responses. This study aimed to evaluate the performance of IgG N-glycosylation for diagnosing LN in a sample of female SLE patients. This case-control study recruited 188 women with SLE, including 94 patients with LN and 94 age-matched patients without LN. The profiles of plasma IgG N-glycans were detected by hydrophilic interaction chromatography with ultra-performance liquid chromatography (HILIC-UPLC). A multivariate logistic regression model was used to explore the associations between IgG N-glycans and LN. A diagnostic model was developed using the significant glycans as well as demographic factors. The performance of IgG N-glycans in the diagnosis of LN was evaluated by receiver operating characteristic (ROC) curve analysis, and the area under the curve (AUC) and its 95% confidence interval (CI) were calculated. There were significant differences in 9 initial glycans (GP2, GP4, GP6, GP8, GP10, GP14, GP16, GP18 and GP23) between women with SLE with and without LN (P < 0.05). The levels of sialylated, galactosylated and fucosylated glycans were significantly lower in the LN patients than in the control group, while bisected N-acetylglucosamine (GlcNAc) glycans were increased in LN patients (P < 0.05). GP8, GP10, GP18, and anemia were included in our diagnostic model, which performed well in differentiating female SLE patients with LN from those without LN (AUC = 0.792, 95% CI: 0.727 to 0.858). Our findings indicate that decreased sialylation, galactosylation, and core fucosylation and increased bisecting GlcNAc might play a role in the development of LN by upregulating the proinflammatory response of IgG. IgG N-glycans can serve as potential biomarkers to differentiate individuals with LN among SLE patients.

Divergent Enzymatic Assembly of a Comprehensive 64-Membered IgG N-Glycan Library for Functional Glycomics.

N-Glycosylation, a main post-translational modification of Immunoglobulin G (IgG), plays a significant role in modulating the immune functions of IgG. However, the precise function elucidation of IgG N-glycosylation remains impeded due to the obstacles in obtaining comprehensive and well-defined N-glycans. Here, an easy-to-implement divergent approach is described to synthesize a 64-membered IgG N-glycan library covering all possible biantennary and bisected N-glycans by reprogramming biosynthetic assembly lines based on the inherent branch selectivity and substrate specificity of enzymes. The unique binding specificities of 64 N-glycans with different proteins are deciphered by glycan microarray technology. This unprecedented collection of synthetic IgG N-glycans can serve as standards for N-glycan structure identification in complex biological samples and the microarray data enrich N-glycan glycomics to facilitate biomedical applications.

The impact of immunoglobulin G N-glycosylation level on COVID-19 outcome: evidence from a Mendelian randomization study.

The coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID-19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial. We conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran's Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results. We found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92-0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy. Our study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels.

IgG glycomic profiling identifies potential biomarkers for diagnosis of echinococcosis

Echinococcosis caused by larval stage of the genus Echinococcus, is a serious and potentially fatal parasitic zoonosis distributed globally. The two types of the disease in human are cystic echinococcosis (CE) and alveolar echinococcosis (AE). As the biological and encysting characteristics of the parasite, early diagnosis remains to address. In the present study, we demonstrate the value of Immunoglobulin G (IgG) glycome as a potential diagnostic biomarker for echinococcosis. Serum IgG glycome profiles were analyzed by ultra-performance liquid chromatography in a cohort comprised of 127 echinococcosis patients, of them 98 were diagnosed as CE and 29 as AE. IgG N-glycome analysis in pretreatment serum of echinococcosis patients presents 25 glycans and 64 derived traits. Compared with IgG glycans of healthy control group, neutral glycans, fucosylation and agalactosylated N-glycans increased while sialylation and galactosylation decreased in echinococcosis patients. Combined with a machine-learning-based approach, we built three biomarker combinations to distinguish CE, AE and healthy controls. Meanwhile, galactosylation, sialylation and A2BG2S1 in IgG glycan profiles were evidently associated with different types of CE (from CE1 to CE5). Our findings suggest that the alterations in IgG N-glycome may be of value in CE and AE diagnosis and follow-up CE disease progress. The role of IgG N-glycans as diagnostic biomarker remains to be verified in future study.

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

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. 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. 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. 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.

Anti-TNF Biologicals Enhance the Anti-Inflammatory Properties of IgG N-Glycome in Crohn's Disease.

Crohn's disease (CD) is a chronic inflammation of the digestive tract that significantly impairs patients' quality of life and well-being. Anti-TNF biologicals revolutionised the treatment of CD, yet many patients do not adequately respond to such therapy. Previous studies have demonstrated a pro-inflammatory pattern in the composition of CD patients' immunoglobulin G (IgG) N-glycome compared to healthy individuals. Here, we utilised the high-throughput UHPLC method for N-glycan analysis to explore the longitudinal effect of the anti-TNF drugs infliximab and adalimumab on N-glycome composition of total serum IgG in 198 patients, as well as the predictive potential of IgG N-glycans at baseline to detect primary non-responders to anti-TNF therapy in 1315 patients. We discovered a significant decrease in IgG agalactosylation and an increase in monogalactosylation, digalactosylation and sialylation during the 14 weeks of anti-TNF treatment, regardless of therapy response, all of which suggested a diminished inflammatory environment in CD patients treated with anti-TNF therapy. Furthermore, we observed that IgG N-glycome might contain certain information regarding the anti-TNF therapy outcome before initiating the treatment. However, it is impossible to predict future primary non-responders to anti-TNF therapy based solely on IgG N-glycome composition at baseline.

A Nested Case-Control Study to Explore the Association between Immunoglobulin G N-glycans and Ischemic Stroke

ObjectiveThis study prospectively investigates the association between immunoglobulin G (IgG) N-glycan traits and ischemic stroke (IS) risk. MethodsA nested case-control study was conducted in the China suboptimal health cohort study, which recruited 4,313 individuals in 2013–2014. Cases were identified as patients diagnosed with IS, and controls were 1:1 matched by age and sex with cases. IgG N-glycans in baseline plasma samples were analyzed. ResultsA total of 99 IS cases and 99 controls were included, and 24 directly measured glycan peaks (GPs) were separated from IgG N-glycans. In directly measured GPs, GP4, GP9, GP21, GP22, GP23, and GP24 were associated with the risk of IS in men after adjusting for age, waist and hip circumference, obesity, diabetes, hypertension, and dyslipidemia. Derived glycan traits representing decreased galactosylation and sialylation were associated with IS in men (FBG2S2/(FBG2 + FBG2S1 + FBG2S2): odds ratio (OR) = 0.92, 95% confidence interval (CI): 0.87–0.97; G1n: OR = 0.74, 95% CI: 0.63–0.87; G0n: OR = 1.12, 95% CI: 1.03–1.22). However, these associations were not found among women. ConclusionThis study validated that altered IgG N-glycan traits were associated with incident IS in men, suggesting that sex discrepancies might exist in these associations.

Mechanism of glycoform specificity and in vivo protection by an anti-afucosylated IgG nanobody

Immunoglobulin G (IgG) antibodies contain a complex N-glycan embedded in the hydrophobic pocket between its heavy chain protomers. This glycan contributes to the structural organization of the Fc domain and determines its specificity for Fcγ receptors, thereby dictating distinct cellular responses. The variable construction of this glycan structure leads to highly-related, but non-equivalent glycoproteins known as glycoforms. We previously reported synthetic nanobodies that distinguish IgG glycoforms. Here, we present the structure of one such nanobody, X0, in complex with the Fc fragment of afucosylated IgG1. Upon binding, the elongated CDR3 loop of X0 undergoes a conformational shift to access the buried N-glycan and acts as a ‘glycan sensor’, forming hydrogen bonds with the afucosylated IgG N-glycan that would otherwise be sterically hindered by the presence of a core fucose residue. Based on this structure, we designed X0 fusion constructs that disrupt pathogenic afucosylated IgG1-FcγRIIIa interactions and rescue mice in a model of dengue virus infection.

Physical Exercise Induces Significant Changes in Immunoglobulin G N-Glycan Composition in a Previously Inactive, Overweight Population.

Regular exercise improves health, modulating the immune system and impacting inflammatory status. Immunoglobulin G (IgG) N-glycosylation reflects changes in inflammatory status; thus, we investigated the impact of regular exercise on overall inflammatory status by monitoring IgG N-glycosylation in a previously inactive, middle-aged, overweight and obese population (50.30 ± 9.23 years, BMI 30.57 ± 4.81). Study participants (N = 397) underwent one of three different exercise programs lasting three months with blood samples collected at baseline and at the end of intervention. After chromatographically profiling IgG N-glycans, linear mixed models with age and sex adjustment were used to investigate exercise effects on IgG glycosylation. Exercise intervention induced significant changes in IgG N-glycome composition. We observed an increase in agalactosylated, monogalctosylated, asialylated and core-fucosylated N-glycans (padj = 1.00 × 10-4, 2.41 × 10-25, 1.51 × 10-21 and 3.38 × 10-30, respectively) and a decrease in digalactosylated, mono- and di-sialylated N-glycans (padj = 4.93 × 10-12, 7.61 × 10-9 and 1.09 × 10-28, respectively). We also observed a significant increase in GP9 (glycan structure FA2[3]G1, β = 0.126, padj = 2.05 × 10-16), previously reported to have a protective cardiovascular role in women, highlighting the importance of regular exercise for cardiovascular health. Other alterations in IgG N-glycosylation reflect an increased pro-inflammatory IgG potential, expected in a previously inactive and overweight population, where metabolic remodeling is in the early stages due to exercise introduction.

Associations between plasma protein, IgG and IgA N-glycosylation and metabolic health markers in pregnancy and gestational diabetes.

Monitoring human circulating N-glycome could provide valuable insight into an individual's metabolic status. Therefore, we examined if aberrant carbohydrate metabolism in gestational diabetes mellitus (GDM) associates with alterations in plasma protein, immunoglobulin G (IgG) and immunoglobulin A (IgA) N-glycosylation. Plasma protein, IgG and IgA N-glycans were enzymatically released, purified and chromatographically profiled in 48 pregnant women with normal glucose tolerance and 41 pregnant women with GDM, all sampled at 24-28 weeks of gestation. Linear mixed models adjusting for age and multiple testing (FDR<0.05) were used to investigate the associations between glycosylation features, metabolic markers and GDM status. Fasting insulin exhibited significant associations to numerous glycan traits, including plasma protein galactosylation, sialylation, branching, core fucosylation and bisection, to IgG core fucosylated, bisected (FA2B) and afucosylated disialylated (A2G2S2) glycan and to IgA trisialylated triantennary (A3G3S3) glycan (padj range: 4.37x10-05-4.94x10-02). Insulin resistance markers HOMA2-IR and HOMA2-%B were mostly associated to the same glycan structures as fasting insulin. Both markers showed positive association with high-branched plasma glycans (padj = 1.12x10-02 and 2.03x10-03) and negative association with low-branched plasma glycans (padj = 1.21x10-02 and 2.05x10-03). Additionally, HOMA2-%B index was significantly correlated with glycosylation features describing IgG sialylation. Multiple plasma protein IgG and IgA glycans showed significant associations with total cholesterol and triglyceride levels. None of the tested glycan traits showed a significant difference between GDM and normoglycemic pregnancies. Markers of glucose homeostasis and lipid metabolism in pregnancy show extensive associations to various N-glycosylation features. However, plasma protein, IgG and IgA N-glycans were not able to differentiate pregnant women with and without GDM, possibly due to numerous physiological changes accompanying pregnancy, which confound the impact of GDM on protein glycosylation.

Storage stability and HILIC-UHPLC-FLR analysis of immunoglobulin G N-glycome from saliva.

Immunoglobulin G (IgG) is the most abundant antibody in the blood and plays a critical role in host immune defense against infectious agents. Glycosylation is known to modulate the effector functions of IgG and is involved in disease development and progression. It is no surprise that the N-glycome of IgG from plasma has already been proposed as a biomarker for various physiological and pathological conditions. However, because saliva is easy to collect, it could be useful for exploring the functional role of salivary IgG N-glycosylation and its potential as a diagnostic biomarker. Therefore, in this study, we described a method for N-glycome analysis of IgG from saliva samples. Salivary IgG N-glycans were analyzed by ultra-high-performance liquid chromatography based onhydrophilic interactions with fluorescence detection (HILIC-UHPLC-FLR). In addition, we compared IgG N-glycan profiles from saliva with those from plasma, assessed the stability of salivary IgG N-glycan profiles under different storage conditions, and evaluated the effects of using a saliva preservation medium. This study provides an ultrasensitive UHPLC method for the analysis of total IgG N-glycosylation from saliva, gives insight into storage stability of salivary IgG, and highlights its (dis)advantages for further biomarker-related research.

Abstract 40: Score Based on Immunoglobulin G N-glycans for Cardiovascular Risk Prediction: Secondary Analysis of Two Randomized Trials of Primary and Secondary Prevention

Introduction: Immunoglobulin G (IgG) are post-translationally modified proteins with the addition of complex carbohydrate molecules (glycans). These glycans can modulate IgG inflammatory capacity and determine the transition from healthy to diseased tissue. Hypothesis: A glycan score based on certain IgG glycosylation patterns is associated with CVD risk and can improve model prediction. Methods: IgG glycosylation profiles were measured on baseline plasma samples from nested CVD case-control participants from 2 studies: JUPITER (NCT00239681; Npairs=162; discovery) and the TNT (NCT00327691; Npairs=367, validation). Lasso regression was used to select IgG glycan peaks (GPs). The linear combination of selected IgG-GPs that significantly associated with CVD in a mutually adjusted conditional regression comprised the glycan score (IgG GS ). CVD prediction using IgG GS was investigated controlling for clinical risk factors. Using a parametric approach, we calculated the area under the curve (AUC) with and without IgG GS . Results: From 24 IgG-GPs, Lasso selected 4 IgG-GPs that were also associated with incident CVD (P&lt;.05) in a mutually adjusted conditional logistic regression. These 4 IgG-GPs (9, 12, 19, 20) composed the IgG glycan score (IgG GS ; Fig1A), which was significantly associated with incident CVD in JUPITER after adjusting for clinical risk factors (model 2 hazard ratio [HR]: 2.1, 95% CI 1.55 - 2.84), with significant validation in TNT (HR = 1.2, 95% CI 1.03 - 1.4; Fig. 1B). The AUC was higher for the model with IgG GS (0.74, 95%CI = 0.69 - 0.81) than without (0.69, 95%CI = 0.67 - 0.71) in JUPITER; replicating in TNT: 0.72 [0.71 - 0.83] vs 0.64, [0.62 - 0.65]. The P-value for the likelihood ratio test comparing models with and without IgG GS was 5.9x10 -8 in JUPITER and .02 in TNT. Conclusions: An IgG glycan score with 4 IgG N-glycans was positively associated with incident CVD in the JUPITER primary prevention population, which replicated in TNT, a secondary prevention cohort, and improved model prediction performance.

IgG N-Glycosylation Is Altered in Coronary Artery Disease.

Coronary artery disease (CAD) is the most common cardiovascular disease (CVD), and previous studies have shown a significant association between N-glycosylation, a highly regulated posttranslational modification, and the development of atherosclerotic plaques. Our aim was to determine whether the N-glycome of immunoglobulin G (IgG) is associated with CAD, as N-glycans are known to alter the effector functions of IgG, which may enhance the inflammatory response in CAD. Therefore, in this study, we isolated IgG from subjects with coronary atherosclerosis (CAD+) and from subjects with clean coronaries (CAD-). The purified IgGs were denatured and enzymatically deglycosylated, and the released and fluorescently labelled N-glycans were analysed by ultra-high performance liquid chromatography based on hydrophilic interactions with fluorescence detection (HILIC-UHPLC-FLR). Sex-stratified analysis of 316 CAD- and 156 CAD+ cases revealed differences in IgG N-glycome composition. The most notable differences were observed in women, where the presence of sialylated N-glycan structures was negatively associated with CAD. The obtained chromatograms provide insight into the IgG N-glycome composition in CAD as well as the biomarker potential of IgG N-glycans in CAD.

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

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

IgG Glycosylation Profiling of Peripheral Artery Diseases with Lectin Microarray.

Background: Inflammation plays a key role in the progression of atherosclerotic plaque for peripheral artery disease (PAD). Immunoglobulin G (IgG) glycosylation could modulate immunological effector functions and has been explored as biomarkers for various diseases. Methods: Lectin microarray was applied to analyze the expression profile of serum IgG glycosylation in patients with lower-extremity peripheral artery disease (LEPAD), carotid artery stenosis (CAS), abdominal aortic aneurysm (AAA), and healthy controls. Lectin blot was performed to validate the differences. Results: SNA (Sambucus nigra agglutinin) binding (preferred sialic acid) was significantly higher in the LEPAD (3.21 ± 2.06) and AAA (3.34 ± 2.42) groups compared to the CAS (2.47 ± 1.45) group. Significantly higher binding levels of ConA (Concanavalin A) (preferred mannose) and PSA (Pisum sativum agglutinin) (preferred fucose) were also observed in LEPAD compared to CAS patients. Among LEPAD patients, a significant lower binding level of Black bean crude (preferred GalNAc) was present for dyslipidemia patients. A higher binding level of MNA-M (Morniga M agglutinin) (preferred Mannose) and Jacalin-AIA (Artocarpus integrifolia agglutinin) (preferred Galβ3GalNAc) was observed for Fontaine severe patients. Higher binding levels of PHA-E (Phaseolus vulgaris Erythroagglutinin) and PHA-L (Phaseolus vulgaris Leucoagglutinin) (preferred Galβ4GlcNAc) were observed for diabetic patients, and higher binding of ASA (Allium sativum agglutinin) (preferred Mannose) was present in patients with hypertension. The level of high-sensitivity C-reactive protein (hsCRP) was positively associated with LTL (Lotus tetragonolobus lectin) (r = 0.44), PSA (r = 0.44), LCA (Lens Culinaris agglutinin) (r = 0.39), SNA (r = 0.57), and CSA (Cytisus sscoparius agglutinin) (r = 0.56). For CAS, symptomatic patients had lower binding levels of AAL (Aleuria aurantia lectin) (preferred fucose) and IAA (Iberis amara agglutinin) (preferred GalNAc). Blood total cholesterol level was positively associated with SNA-I (r = 0.36) and SBA (Soybean agglutinin) (r = r = 0.35). Creatinine levels were positively associated with lectins including, but not limited to, MNA-M (r = 0.42), CSA (r = 0.45), GHA (Glechoma hederacea agglutinin) (r = 0.42), and MNA-G (Morniga G agglutinin) (r = 0.45). Conclusion: LEPAD patients had increased IgG binding levels of SNA and ConA compared to CAS, which could provide potential diagnostic value. Fontaine severity was associated with Mannose-rich IgG N-glycan, while diabetic LEPAD correlated with bisecting GlcNAc. The levels of hsCRP and creatinine were positively associated with IgG fucosylation and galactosylation. Changes in IgG glycosylation may play important roles in PAD pathogenesis and progression.