Ischemic stroke is associated with the pro-inflammatory potential of N-glycosylated immunoglobulin G

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.

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.

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.

Gender and thrombolysis therapy in stroke patients with incidence of dyslipidemia

BACKGROUND

When untreated, dyslipidemia is a higher risk factor for stroke and stroke-related mortality in men than in women. However, when dyslipidemia is treated the risk reduction is the same, but men benefited from mortality reduction more than women. Whether there is a gender difference in exclusion criteria for the use of recombinant tissue plasminogen activator (rtPA) or thrombolysis therapy in an acute ischemic stroke subpopulation with dyslipidemia is yet to be investigated.

METHOD

In a dyslipidemic stroke population obtained from a stroke registry, gender differences in exclusion risk factors were determined using clinical and demographic variables. Univariate analysis compared the recombinant tissue plasminogen activator (rtPA) group and the no rtPA group. Multiple regression analysis was used to determine demographic and clinical factors associated with inclusion and exclusion for rtPA in the total dyslipidemic stroke population and the subsets of the male and female population. The regression model was tested using the Hosmer-Lemeshow test, for the overall correct classification percentage. Significant interactions and multicollinearity between independent variables were examined using variance inflation factors.

RESULTS

A total of 769 patients presented with acute ischemic stroke with incidence dyslipidemia; 325 received rtPA while 444 were excluded from rtPA. Of those excluded from rtPA, 54.30% were female and 45.72% were male. In an adjusted analysis, female patients with increased age (OR = 1.024, 95% CI, 1.001-1.047, P < 0.05), with a history of carotid artery stenosis (OR = 7.063, 95% CI, 1.506-33.134, P < 0.05), and previous stroke (OR = 1.978, 95% CI, 1.136-3.442, P < 0.05) were more likely to be excluded from rtPA. Male patients with atrial fibrillation (OR = 2.053, 95% CI, 1.059-3.978, P = 0.033), carotid artery stenosis (OR = 2.400, 95% CI, 1.062-5.424, P = 0.035), and previous stroke (OR = 1.785, 95% CI, 1.063-2.998, P = 0.028) were more likely to be excluded from rtPA.

CONCLUSION

Although there are some similarities in the clinical risk factors for exclusion in both male and female stroke patients with incidence of dyslipidemia, there are differences as well. Elderly female stroke patients with incidence of dyslipidemia are more likely to be excluded from rtPA, even after adjustment for the effect of confounding variables. Further research should focus on how identified clinical risk factors can be targeted and managed to improve the use of rtPA in elderly female acute ischemic stroke population with incidence of dyslipidemia.

The Association Between Normal BMI With Central Adiposity And Proinflammatory Potential Immunoglobulin G N-Glycosylation

BACKGROUND

The mechanism by which normal body mass index (BMI) with central adiposity (NWCA) increases the risk of the diseases has not been completely elucidated. The inflammatory role of immunoglobulin G (IgG) N-glycosylation in obesity defined by BMI or central adiposity defined by waist-to-hip ratio (WHR) was reported, respectively. We undertook this three-center cross-sectional study to determine the association between the IgG N-glycans and NWCA.

METHODS

The participants were categorized into four different phenotypes: normal BMI with normal WHR (NW), normal BMI with central adiposity (NWCA), obesity with normal WHR (ONCA) and obesity with central adiposity (OCA). The IgG N-glycans were analyzed using ultra-performance liquid chromatography analysis of released glycans, and differences among groups were compared.

RESULTS

In total, 17 out of 24 initial IgG N-glycans were significantly different among the four groups (NW, ONCA, NWCA and OCA) (P<0.05/6*78=0.0001). The changes of IgG glycans in central obesity (12 GPs) were more than those in obesity (3 GPs). In addition, lower galactosylation and bisecting GlcNAc and higher fucosylation were associated with increased risk of NWCA.

CONCLUSION

Central obesity was involved in more changes of IgG N-glycosylation representing stronger inflammation than obesity, which might make a greater contribution to the risk of related disorders. NWCA was associated with an increased pro-inflammatory of IgG N-glycosylation, which was accompanied by the development of central obesity and other related disorders.

IMass Time: The Future, in Future!

Joseph John Thomson discovered and proved the existence of electrons through a series of experiments. His work earned him a Nobel Prize in 1906 and initiated the era of mass spectrometry (MS). In the intervening time, other researchers have also been awarded the Nobel Prize for significant advances in MS technology. The development of soft ionization techniques was central to the application of MS to large biological molecules and led to an unprecedented interest in the study of biomolecules such as proteins (proteomics), metabolites (metabolomics), carbohydrates (glycomics), and lipids (lipidomics), allowing a better understanding of the molecular underpinnings of health and disease. The interest in large molecules drove improvements in MS resolution and now the challenge is in data deconvolution, intelligent exploitation of heterogeneous data, and interpretation, all of which can be ameliorated with a proposed IMass technology. We define IMass as a combination of MS and artificial intelligence, with each performing a specific role. IMass will offer advantages such as improving speed, sensitivity, and analyses of large data that are presently not possible with MS alone. In this study, we present an overview of the MS considering historical perspectives and applications, challenges, as well as insightful highlights of IMass.

CD16a with oligomannose-type N-glycans is the only "low-affinity" Fc γ receptor that binds the IgG crystallizable fragment with high affinity in vitro

Fc γ receptors (FcγRs) bind circulating IgG (IgG1) at the surface of leukocytes. Antibodies clustered at the surface of a targeted particle trigger a protective immune response through activating FcγRs. Three recent reports indicate that the composition of the asparagine-linked carbohydrate chains (N-glycans) of FcγRIIIa/CD16a impacted IgG1-binding affinity. Here we determined how N-glycan composition affected the affinity of the "low-affinity" FcγRs for six homogeneous IgG1 Fc N-glycoforms (G0, G0F, G2, G2F, A2G2, and A2G2F). Surprisingly, CD16a with oligomannose N-glycans bound to IgG1 Fc (A2G2) with a K_D = 1.0 ± 0.1 nm This affinity represents a 51-fold increase over the affinity measured for CD16a with complex-type N-glycans (51 ± 8 nm) and is comparable with the affinity of FcγRI/CD64, the sole "high-affinity" FcγR. CD16a N-glycan composition accounted for increases in binding affinity for the other IgG1 Fc glycoforms tested (10-50-fold). This remarkable sensitivity could only be eliminated by preventing glycosylation at Asn¹⁶² with an Asn-to-Gln mutation; mutations at the four other N-glycosylation sites preserved tighter binding in the Man5 glycoform. None of the other low-affinity FcγRs showed more than a 3.1-fold increase upon modifying the receptor N-glycan composition, including CD16b, which differs from CD16a by only four amino acid residues. This result indicates that CD16a is unique among the low-affinity FcγRs, and modifying only the glycan composition of both the IgG1 Fc ligand and receptor provides a 400-fold range in affinities.

The changes of immunoglobulin G N-glycosylation in blood lipids and dyslipidaemia

BACKGROUND

Alternative N-glycosylation has significant structural and functional consequences on immunoglobulin G (IgG) and can affect immune responses, acting as a switch between pro- and anti-inflammatory IgG functionality. Studies have demonstrated that IgG N-glycosylation is associated with ageing, body mass index, type 2 diabetes and hypertension.

METHODS

Herein, we have demonstrated patterns of IgG glycosylation that are associated with blood lipids in a cross-sectional study including 598 Han Chinese aged 20-68 years. The IgG glycome composition was analysed by ultra-performance liquid chromatography.

RESULTS

Blood lipids were positively correlated with glycan peak GP6, whereas they were negatively correlated with GP18 (P < 0.05/57). The canonical correlation analysis indicated that initial N-glycan structures, including GP4, GP6, GP9-12, GP14, GP17, GP18 and GP23, were significantly correlated with blood lipids, including total cholesterol, total triglycerides (TG) and low-density lipoprotein (r = 0.390, P < 0.001). IgG glycans patterns were able to distinguish patients with dyslipidaemia from the controls, with an area under the curve of 0.692 (95% confidence interval 0.644-0.740).

CONCLUSIONS

Our findings indicated that a possible association between blood lipids and the observed loss of galactose and sialic acid, as well as the addition of bisecting GlcNAcs, which might be related to the chronic inflammation accompanying with the development and procession of dyslipidaemia.