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Shkunnikova S, Mijakovac A, Sironic L, Hanic M, Lauc G, Kavur MM. IgG glycans in health and disease: Prediction, intervention, prognosis, and therapy. Biotechnol Adv 2023; 67:108169. [PMID: 37207876 DOI: 10.1016/j.biotechadv.2023.108169] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/21/2023]
Abstract
Immunoglobulin (IgG) glycosylation is a complex enzymatically controlled process, essential for the structure and function of IgG. IgG glycome is relatively stable in the state of homeostasis, yet its alterations have been associated with aging, pollution and toxic exposure, as well as various diseases, including autoimmune and inflammatory diseases, cardiometabolic diseases, infectious diseases and cancer. IgG is also an effector molecule directly involved in the inflammation processes included in the pathogenesis of many diseases. Numerous recently published studies support the idea that IgG N-glycosylation fine-tunes the immune response and plays a significant role in chronic inflammation. This makes it a promising novel biomarker of biological age, and a prognostic, diagnostic and treatment evaluation tool. Here we provide an overview of the current state of knowledge regarding the IgG glycosylation in health and disease, and its potential applications in pro-active prevention and monitoring of various health interventions.
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Affiliation(s)
- Sofia Shkunnikova
- Genos Glycoscience Research Laboratory, Borongajska cesta 83H, Zagreb, Croatia
| | - Anika Mijakovac
- University of Zagreb, Faculty of Science, Department of Biology, Horvatovac 102a, Zagreb, Croatia
| | - Lucija Sironic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83H, Zagreb, Croatia
| | - Maja Hanic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83H, Zagreb, Croatia
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Borongajska cesta 83H, Zagreb, Croatia; University of Zagreb, Faculty of Pharmacy and Biochemistry, Ulica Ante Kovačića 1, Zagreb, Croatia
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Wang B, Gao L, Zhang J, Meng X, Xu X, Hou H, Xing W, Wang W, Wang Y. Unravelling the genetic causality of immunoglobulin G N-glycans in ischemic stroke. Glycoconj J 2023; 40:413-420. [PMID: 37341803 DOI: 10.1007/s10719-023-10127-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/18/2023] [Accepted: 06/14/2023] [Indexed: 06/22/2023]
Abstract
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.
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Affiliation(s)
- Biyan Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- Department of Health Management, the Second Affiliated Hospital, the Fourth Military Medical University, Xi'an, China
| | - Lei Gao
- Department of Medical Engineering and Medical Supplies Center, PLA General Hospital, Beijing, China
| | - Jie Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Xiaoni Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Xizhu Xu
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Haifeng Hou
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China
- Centre for Precision Medicine, Edith Cowan University, Perth, WA, 6027, Australia
| | - Weijia Xing
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China.
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China.
- Centre for Precision Medicine, Edith Cowan University, Perth, WA, 6027, Australia.
- Centre for Precision Medicine, Edith Cowan University, Perth, 60127, Australia.
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
- Centre for Precision Medicine, Edith Cowan University, Perth, WA, 6027, Australia.
- School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, No.10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, China.
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Wang H, Li Y, Cao W, Zhang J, Cao M, Meng X, Liu D, Wang Y. Leveraging IgG N-glycosylation to infer the causality between T2D and hypertension. Diabetol Metab Syndr 2023; 15:80. [PMID: 37095539 PMCID: PMC10127371 DOI: 10.1186/s13098-023-01053-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 04/07/2023] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Observational studies demonstrated a bidirectional association between type 2 diabetes (T2D) and hypertension, whereas Mendelian randomization (MR) analyses supported the causality from T2D to hypertension but not causal from hypertension to T2D. We previously found that IgG N-glycosylation is associated with both T2D and hypertension, and thus IgG N-glycosylation might link the causality between them. METHODS We carried out a genome-wide association study (GWAS) to identify IgG N-glycosylation-quantitative-trait loci (QTLs) integrating GWAS for T2D and hypertension and then performed bidirectional univariable and multivariable MR analyses to infer the causal association among them. The inverse-variance-weighted (IVW) analysis was performed as the primary analysis, followed by some sensitivity analyses to explore the stability of the results. RESULTS Six putatively causal IgG N-glycans for T2D and four for hypertension were identified in the IVW method. Genetically predicted T2D increased the risk of hypertension (odds ratio [OR] = 1.177, 95% confidence interval (95% CI) = 1.037-1.338, P = 0.012) and vice versa (OR = 1.391, 95% CI = 1.081-1.790, P = 0.010). Multivariable MR showed that T2D remained at risk effect with hypertension ([OR] = 1.229, 95% CI = 1.140-1.325, P = 7.817 × 10-8) after conditioning on T2D-related IgG-glycans. Conversely, hypertension was associated with higher T2D risk (OR = 1.287, 95% CI = 1.107-1.497, P = 0.001) after adjusting for related IgG-glycans. No evidence of horizontal pleiotropy was observed, as MR‒Egger regression provided P values for intercept > 0.05. CONCLUSION Our study validated the mutual causality between T2D and hypertension from the perspective of IgG N-glycosylation, further validating the "common soil" hypothesis underlying the pathogenesis of T2D and hypertension.
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Affiliation(s)
- Haotian Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China
| | - Yuan Li
- Lianyungang Maternal and Child Health Hospital, Lianyungang, 222062, Jiangsu, China
| | - Weijie Cao
- Centre for Precision Medicine, Edith Cowan University, Perth, 60127, Australia
| | - Jie Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China
| | - Mingyang Cao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China
| | - Xiaoni Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China
| | - Di Liu
- Centre for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, University Town, Nanshan District, Shenzhen, 518055, Guangdong, China.
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China.
- Centre for Precision Medicine, Edith Cowan University, Perth, 60127, Australia.
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Adua E. Decoding the mechanism of hypertension through multiomics profiling. J Hum Hypertens 2023; 37:253-264. [PMID: 36329155 PMCID: PMC10063442 DOI: 10.1038/s41371-022-00769-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 08/24/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022]
Abstract
Hypertension, characterised by a constant high blood pressure, is the primary risk factor for multiple cardiovascular events and a major cause of death in adults. Excitingly, innovations in high-throughput technologies have enabled the global exploration of the whole genome (genomics), revealing dysregulated genes that are linked to hypertension. Moreover, post-genomic biomarkers, from the emerging fields of transcriptomics, proteomics, glycomics and lipidomics, have provided new insights into the molecular underpinnings of hypertension. In this paper, we review the pathophysiology of hypertension, and highlight the multi-omics approaches for hypertension prediction and diagnosis.
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Affiliation(s)
- Eric Adua
- School of Clinical Medicine, Medicine & Health, Rural Clinical Campus, University of New South Wales, Wagga Wagga, NSW, Australia.
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
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Krištić J, Lauc G, Pezer M. Immunoglobulin G glycans - Biomarkers and molecular effectors of aging. Clin Chim Acta 2022; 535:30-45. [PMID: 35970404 DOI: 10.1016/j.cca.2022.08.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/04/2022] [Accepted: 08/04/2022] [Indexed: 11/28/2022]
Abstract
Immunoglobulin G (IgG) antibodies are post-translationally modified by the addition of complex carbohydrate molecules - glycans, which have profound effects on the IgG function, most significantly as modulators of its inflammatory capacity. Therefore, it is not surprising that the changes in IgG glycosylation pattern are associated with various physiological states and diseases, including aging and age-related diseases. Importantly, within the inflammaging concept, IgG glycans are considered not only biomarkers but one of the molecular effectors of the aging process. The exact mechanism by which they exert their function, however, remains unknown. In this review, we list and comment on, to our knowledge, all studies that examined changes in IgG glycosylation during aging in humans. We focus on the information obtained from studies on general population, but we also cover the insights obtained from studies of long-lived individuals and people with age-related diseases. We summarize the current knowledge on how levels of different IgG glycans change with age (i.e., the extent and direction of the change with age) and discuss the potential mechanisms and possible functional roles of changes in IgG glycopattern that accompany aging.
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Affiliation(s)
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia; Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Marija Pezer
- Genos Glycoscience Research Laboratory, Zagreb, Croatia.
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Li Y, Shi F, Wang G, Lv J, Zhang H, Jin H, Chen X, Wang M, Li P, Ji L. Expression Profile of Immunoglobulin G Glycosylation in Children With Epilepsy in Han Nationality. Front Mol Neurosci 2022; 15:843897. [PMID: 35845609 PMCID: PMC9283856 DOI: 10.3389/fnmol.2022.843897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 05/30/2022] [Indexed: 12/08/2022] Open
Abstract
Background Epilepsy is a chronic brain disease that recurs during childhood, and more than half of adult epilepsy originates from childhood. Studies suggested that immunoglobulin G (IgG) glycosylation are closely related to neurological diseases. Here we analyzed the characteristics of the immunoglobulin glycosylation profile of children with epilepsy. Methods Patients were recruited in Taian, Shandong Province from December 2019 to March 2020. Serum IgG glycome composition was analyzed by hydrophilic interaction liquid chromatography with ultra-high-performance liquid chromatography approach. Results The proportion of fucosylated glycans in total IgG glycans was 93.72% in the epilepsy patients, which was significantly lower than that in the control group (94.94%). A lower level of total monogalactosylated and digalactosylated glycans were observed in the epilepsy patients group (30.76 and 40.14%) than that in the controls (36.17 and 42.69%). There was no significant difference between the two groups in bisected GlcNAc glycans and sialylated glycans. Conclusion The decrease of core fucosylation and galactosylation may promote the inflammatory reaction of the body and participate in the occurrence of epilepsy in children.
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Affiliation(s)
- Yuejin Li
- Shandong Institute of Parasitic Diseases, Shandong First Medical University & Shandong Academy of Medical Sciences, Jining, China
| | - Fengxue Shi
- School of Clinical, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Guanglei Wang
- Tai’an Maternal and Child Health Hospital, Taian, China
| | - Jian Lv
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Haitao Zhang
- Tai’an Maternal and Child Health Hospital, Taian, China
| | - Hao Jin
- Department of Critical Care Medical Center, Taian City Central Hospital, Taian, China
| | - Xueyu Chen
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Meng Wang
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Peirui Li
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Long Ji
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
- College of Sports Medicine and Rehabilitation, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
- *Correspondence: Long Ji,
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Multi-block data integration analysis for identifying and validating targeted N-glycans as biomarkers for type II diabetes mellitus. Sci Rep 2022; 12:10974. [PMID: 35768493 PMCID: PMC9243128 DOI: 10.1038/s41598-022-15172-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 04/28/2022] [Indexed: 11/08/2022] Open
Abstract
Plasma N-glycan profiles have been shown to be defective in type II diabetes Mellitus (T2DM) and holds a promise to discovering biomarkers. The study comprised 232 T2DM patients and 219 healthy individuals. N-glycans were analysed by high-performance liquid chromatography. The multivariate integrative framework, DIABLO was employed for the statistical analysis. N-glycan groups (GPs 34, 32, 26, 31, 36 and 30) were significantly expressed in T2DM in component 1 and GPs 38 and 20 were related to T2DM in component 2. Four clusters were observed based on the correlation of the expressive signatures of the 39 N-glycans across T2DM and controls. Cluster A, B, C and D had 16, 16, 4 and 3 N-glycans respectively, of which 11, 8, 1 and 1 were found to express differently between controls and T2DM in a univariate analysis \documentclass[12pt]{minimal}
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\begin{document}$$(p < 0.05)$$\end{document}(p<0.05). Multi-block analysis revealed that trigalactosylated (G3), triantennary (TRIA), high branching (HB) and trisialylated (S3) expressed significantly highly in T2DM than healthy controls. A bipartite relevance network revealed that HB, monogalactosylated (G1) and G3 were central in the network and observed more connections, highlighting their importance in discriminating between T2DM and healthy controls. Investigation of these N-glycans can enhance the understanding of T2DM.
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Loaeza-Reyes KJ, Zenteno E, Moreno-Rodríguez A, Torres-Rosas R, Argueta-Figueroa L, Salinas-Marín R, Castillo-Real LM, Pina-Canseco S, Cervera YP. An Overview of Glycosylation and its Impact on Cardiovascular Health and Disease. Front Mol Biosci 2021; 8:751637. [PMID: 34869586 PMCID: PMC8635159 DOI: 10.3389/fmolb.2021.751637] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 10/25/2021] [Indexed: 12/25/2022] Open
Abstract
The cardiovascular system is a complex and well-organized system in which glycosylation plays a vital role. The heart and vascular wall cells are constituted by an array of specific receptors; most of them are N- glycosylated and mucin-type O-glycosylated. There are also intracellular signaling pathways regulated by different post-translational modifications, including O-GlcNAcylation, which promote adequate responses to extracellular stimuli and signaling transduction. Herein, we provide an overview of N-glycosylation and O-glycosylation, including O-GlcNAcylation, and their role at different levels such as reception of signal, signal transduction, and exogenous molecules or agonists, which stimulate the heart and vascular wall cells with effects in different conditions, like the physiological status, ischemia/reperfusion, exercise, or during low-grade inflammation in diabetes and aging. Furthermore, mutations of glycosyltransferases and receptors are associated with development of cardiovascular diseases. The knowledge on glycosylation and its effects could be considered biochemical markers and might be useful as a therapeutic tool to control cardiovascular diseases.
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Affiliation(s)
- Karen Julissa Loaeza-Reyes
- Centro de Estudios en Ciencias de la Salud y la Enfermedad, Facultad de Odontología, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico.,Centro de Investigación Facultad de Medicina-UNAM-UABJO, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico
| | - Edgar Zenteno
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - Rafael Torres-Rosas
- Centro de Estudios en Ciencias de la Salud y la Enfermedad, Facultad de Odontología, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico
| | - Liliana Argueta-Figueroa
- Centro de Estudios en Ciencias de la Salud y la Enfermedad, Facultad de Odontología, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico.,Conacyt - Facultad de Odontología, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico
| | - Roberta Salinas-Marín
- Laboratorio de Glicobiología Humana y Diagnóstico Molecular, Centro de Investigación en Dinámica Celular, Instituto de Investigación en Ciencias Básicas y Aplicadas, Universidad Autónoma del Estado de Morelos, Cuernavaca, Mexico
| | - Lizet Monserrat Castillo-Real
- Centro de Estudios en Ciencias de la Salud y la Enfermedad, Facultad de Odontología, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico
| | - Socorro Pina-Canseco
- Centro de Investigación Facultad de Medicina-UNAM-UABJO, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico
| | - Yobana Pérez Cervera
- Centro de Estudios en Ciencias de la Salud y la Enfermedad, Facultad de Odontología, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico.,Centro de Investigación Facultad de Medicina-UNAM-UABJO, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca, Mexico
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Kifer D, Louca P, Cvetko A, Deriš H, Cindrić A, Grallert H, Peters A, Polašek O, Gornik O, Mangino M, Spector TD, Valdes AM, Padmanabhan S, Gieger C, Lauc G, Menni C. N-glycosylation of immunoglobulin G predicts incident hypertension. J Hypertens 2021; 39:2527-2533. [PMID: 34285147 PMCID: PMC7611954 DOI: 10.1097/hjh.0000000000002963] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
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.
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Affiliation(s)
- Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Panayiotis Louca
- Department of Twin Research, Kings College London, London, England, United Kingdom
| | - Ana Cvetko
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Helena Deriš
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Ana Cindrić
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Annette Peters
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- LMU Munich, IBE-Chair of Epidemiology, 85764 Neuherberg, Germany
| | - Ozren Polašek
- Department of Public Health, University of Split, School of Medicine, Split, Croatia
| | - Olga Gornik
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Massimo Mangino
- Department of Twin Research, Kings College London, London, England, United Kingdom
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London SE1 9RT, UK
| | - Tim D Spector
- Department of Twin Research, Kings College London, London, England, United Kingdom
| | - Ana M Valdes
- Department of Twin Research, Kings College London, London, England, United Kingdom
- Academic Rheumatology Clinical Sciences Building, Nottingham City Hospital, University of Nottingham, United Kingdom
| | | | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Gordan Lauc
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Cristina Menni
- Department of Twin Research, Kings College London, London, England, United Kingdom
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Abstract
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.
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Glycosylation and Cardiovascular Diseases. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1325:307-319. [PMID: 34495542 DOI: 10.1007/978-3-030-70115-4_15] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide, accounting for approximately 18 million deaths in 2017. Coronary artery disease is the predominant cause of death from CVD, followed by stroke. Owing to recent technological advancements, glycans and glycosylation patterns of proteins have been investigated in association with CVD risk factors and clinical events. These studies have found significant associations of glycans as biomarkers of systemic inflammation and major CVD risk factors and events. While more limited, studies have also shown that glycans may be useful for monitoring response to anti-inflammatory therapies and may be responsive to changes in lifestyle, particularly in patients with chronic inflammatory diseases. Glycans capture summative risk information related to inflammatory, immune, and signaling pathways and are promising biomarkers for CVD risk prediction and therapeutic monitoring.
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Wu Z, Pan H, Liu D, Zhou D, Tao L, Zhang J, Wang X, Li X, Wang Y, Wang W, Guo X. Variation of IgG N-linked glycosylation profile in diabetic retinopathy. J Diabetes 2021; 13:672-680. [PMID: 33491329 DOI: 10.1111/1753-0407.13160] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 12/29/2020] [Accepted: 01/20/2021] [Indexed: 12/25/2022] Open
Abstract
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.
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Affiliation(s)
- Zhiyuan Wu
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Department of Public Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
| | - Huiying Pan
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Di Liu
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Di Zhou
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Lixin Tao
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Jie Zhang
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Xiaonan Wang
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Xia Li
- Department of Mathematics and Statistics, La Trobe University, Melbourne, Victoria, Australia
| | - Youxin Wang
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Wei Wang
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Department of Public Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
| | - Xiuhua Guo
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
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13
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Greto VL, Cvetko A, Štambuk T, Dempster NJ, Kifer D, Deriš H, Cindrić A, Vučković F, Falchi M, Gillies RS, Tomlinson JW, Gornik O, Sgromo B, Spector TD, Menni C, Geremia A, Arancibia-Cárcamo CV, Lauc G. Extensive weight loss reduces glycan age by altering IgG N-glycosylation. Int J Obes (Lond) 2021; 45:1521-1531. [PMID: 33941843 PMCID: PMC8236401 DOI: 10.1038/s41366-021-00816-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 02/18/2021] [Accepted: 04/09/2021] [Indexed: 12/30/2022]
Abstract
BACKGROUND Obesity, a major global health problem, is associated with increased cardiometabolic morbidity and mortality. Protein glycosylation is a frequent posttranslational modification, highly responsive to inflammation and ageing. The prospect of biological age reduction, by changing glycosylation patterns through metabolic intervention, opens many possibilities. We have investigated whether weight loss interventions affect inflammation- and ageing-associated IgG glycosylation changes, in a longitudinal cohort of bariatric surgery patients. To support potential findings, BMI-related glycosylation changes were monitored in a longitudinal twins cohort. METHODS IgG N-glycans were chromatographically profiled in 37 obese patients, subjected to low-calorie diet, followed by bariatric surgery, across multiple timepoints. Similarly, plasma-derived IgG N-glycan traits were longitudinally monitored in 1680 participants from the TwinsUK cohort. RESULTS Low-calorie diet induced a marked decrease in the levels of IgG N-glycans with bisecting GlcNAc, whose higher levels are usually associated with ageing and inflammatory conditions. Bariatric surgery resulted in extensive alterations of the IgG N-glycome that accompanied progressive weight loss during 1-year follow-up. We observed a significant increase in digalactosylated and sialylated glycans, and a substantial decrease in agalactosylated and core fucosylated IgG N-glycans (adjusted p value range 7.38 × 10-04-3.94 × 10-02). This IgG N-glycan profile is known to be associated with a younger biological age and reflects an enhanced anti-inflammatory IgG potential. Loss of BMI over a 20 year period in the TwinsUK cohort validated a weight loss-associated agalactosylation decrease (adjusted p value 1.79 × 10-02) and an increase in digalactosylation (adjusted p value 5.85 × 10-06). CONCLUSIONS Altogether, these findings highlight that weight loss substantially affects IgG N-glycosylation, resulting in reduced glycan and biological age.
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Affiliation(s)
- Valentina L Greto
- Translational Gastroenterology Unit and NIHR Oxford Biomedical Research Centre, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Ana Cvetko
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Tamara Štambuk
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Niall J Dempster
- Oxford Centre for Diabetes and NIHR Oxford Biomedical Research Centre, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Helena Deriš
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Ana Cindrić
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | | | - Mario Falchi
- The Department of Twin Research, King's College London, St Thomas' Hospital, London, UK
| | - Richard S Gillies
- Department of Upper GI Surgery, Oxford University Hospitals, Oxford, UK
| | - Jeremy W Tomlinson
- Oxford Centre for Diabetes and NIHR Oxford Biomedical Research Centre, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Olga Gornik
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Bruno Sgromo
- Department of Upper GI Surgery, Oxford University Hospitals, Oxford, UK
| | - Tim D Spector
- The Department of Twin Research, King's College London, St Thomas' Hospital, London, UK
| | - Cristina Menni
- The Department of Twin Research, King's College London, St Thomas' Hospital, London, UK
| | - Alessandra Geremia
- Translational Gastroenterology Unit and NIHR Oxford Biomedical Research Centre, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Carolina V Arancibia-Cárcamo
- Translational Gastroenterology Unit and NIHR Oxford Biomedical Research Centre, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Gordan Lauc
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia.
- Genos Glycoscience Research Laboratory, Zagreb, Croatia.
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14
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Meng X, Song M, Vilaj M, Štambuk J, Dolikun M, Zhang J, Liu D, Wang H, Zhang X, Zhang J, Cao W, Momčilović A, Trbojević-Akmačić I, Li X, Zheng D, Wu L, Guo X, Wang Y, Lauc G, Wang W. Glycosylation of IgG Associates with Hypertension and Type 2 Diabetes Mellitus Comorbidity in the Chinese Muslim Ethnic Minorities and the Han Chinese. J Pers Med 2021; 11:jpm11070614. [PMID: 34209622 PMCID: PMC8307283 DOI: 10.3390/jpm11070614] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/18/2021] [Accepted: 06/21/2021] [Indexed: 01/07/2023] Open
Abstract
Objectives: Hypertension and type 2 diabetes mellitus comorbidity (HDC) is common, which confers a higher risk of cardiovascular disease than the presence of either condition alone. Describing the underlying glycomic changes of immunoglobulin G (IgG) that predispose individuals to HDC may help develop novel protective immune-targeted and anti-inflammatory therapies. Therefore, we investigated glycosylation changes of IgG associated with HDC. Methods: The IgG N-glycan profiles of 883 plasma samples from the three northwestern Chinese Muslim ethnic minorities and the Han Chinese were analyzed by ultra-performance liquid chromatography instrument. Results: We found that 12 and six IgG N-glycan traits showed significant associations with HDC in the Chinese Muslim ethnic minorities and the Han Chinese, respectively, after adjustment for potential confounders and false discovery rate. Adding the IgG N-glycan traits to the baseline models, the area under the receiver operating characteristic curves (AUCs) of the combined models differentiating HDC from hypertension (HTN), type 2 diabetes mellitus (T2DM), and healthy individuals were 0.717, 0.747, and 0.786 in the pooled samples of Chinese Muslim ethnic minorities, and 0.828, 0.689, and 0.901 in the Han Chinese, respectively, showing improved discriminating performance than both the baseline models and the glycan-based models. Conclusion: Altered IgG N-glycan profiles were shown to associate with HDC, suggesting the involvement of inflammatory processes of IgG glycosylation. The alterations of IgG N-glycome, illustrated here for the first time in HDC, demonstrate a biomarker potential, which may shed light on future studies investigating their potential for monitoring or preventing the progression from HTN or T2DM towards HDC.
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Affiliation(s)
- Xiaoni Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Manshu Song
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027, Australia;
- Correspondence:
| | - Marija Vilaj
- Genos Glycoscience Research Laboratory, 10000 Zagreb, Croatia; (M.V.); (J.Š.); (A.M.); (I.T.-A.); (G.L.)
| | - Jerko Štambuk
- Genos Glycoscience Research Laboratory, 10000 Zagreb, Croatia; (M.V.); (J.Š.); (A.M.); (I.T.-A.); (G.L.)
| | - Mamatyusupu Dolikun
- College of the Life Sciences and Technology, Xinjiang University, Urumqi 830046, China;
| | - Jie Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Di Liu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Hao Wang
- Department of Clinical Epidemiology and Evidence-Based Medicine, National Clinical Research Center for Digestive Disease, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China;
| | - Xiaoyu Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Jinxia Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Weijie Cao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Ana Momčilović
- Genos Glycoscience Research Laboratory, 10000 Zagreb, Croatia; (M.V.); (J.Š.); (A.M.); (I.T.-A.); (G.L.)
| | - Irena Trbojević-Akmačić
- Genos Glycoscience Research Laboratory, 10000 Zagreb, Croatia; (M.V.); (J.Š.); (A.M.); (I.T.-A.); (G.L.)
| | - Xingang Li
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027, Australia;
- Centre for Precision Health, Edith Cowan University, Perth, WA 6027, Australia
| | - Deqiang Zheng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Lijuan Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Xiuhua Guo
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027, Australia;
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, 10000 Zagreb, Croatia; (M.V.); (J.Š.); (A.M.); (I.T.-A.); (G.L.)
- Faculty of Pharmacy and Biochemistry, University of Zagreb, 10000 Zagreb, Croatia
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China; (X.M.); (J.Z.); (D.L.); (X.Z.); (J.Z.); (W.C.); (D.Z.); (L.W.); (X.G.); (Y.W.); (W.W.)
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027, Australia;
- Centre for Precision Health, Edith Cowan University, Perth, WA 6027, Australia
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15
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Paton B, Suarez M, Herrero P, Canela N. Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis. Int J Mol Sci 2021; 22:ijms22115788. [PMID: 34071388 PMCID: PMC8198018 DOI: 10.3390/ijms22115788] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/22/2021] [Accepted: 05/25/2021] [Indexed: 12/23/2022] Open
Abstract
Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.
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Affiliation(s)
- Beatrix Paton
- Eurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences, Joint Unit Eurecat-Universitat Rovira i Virgili, Unique Scientific and Technical Infrastructure (ICTS), 43204 Reus, Spain; (B.P.); (N.C.)
| | - Manuel Suarez
- Nutrigenomics Research Group, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43007 Tarragona, Spain
- Correspondence: (M.S.); (P.H.)
| | - Pol Herrero
- Eurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences, Joint Unit Eurecat-Universitat Rovira i Virgili, Unique Scientific and Technical Infrastructure (ICTS), 43204 Reus, Spain; (B.P.); (N.C.)
- Correspondence: (M.S.); (P.H.)
| | - Núria Canela
- Eurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences, Joint Unit Eurecat-Universitat Rovira i Virgili, Unique Scientific and Technical Infrastructure (ICTS), 43204 Reus, Spain; (B.P.); (N.C.)
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16
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Zhang X, Yuan H, Lyu J, Meng X, Tian Q, Li Y, Zhang J, Xu X, Su J, Hou H, Li D, Sun B, Wang W, Wang Y. Association of dementia with immunoglobulin G N-glycans in a Chinese Han Population. NPJ Aging Mech Dis 2021; 7:3. [PMID: 33542243 PMCID: PMC7862610 DOI: 10.1038/s41514-021-00055-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 01/06/2021] [Indexed: 12/24/2022] Open
Abstract
Immunoglobulin G (IgG) functionality can drastically change from anti- to proinflammatory by alterations in the IgG N-glycan patterns. Our previous studies have demonstrated that IgG N-glycans associated with the risk factors of dementia, such as aging, dyslipidemia, type 2 diabetes mellitus, hypertension, and ischemic stroke. Therefore, the aim is to investigate whether the effects of IgG N-glycan profiles on dementia exists in a Chinese Han population. A case–control study, including 81 patients with dementia, 81 age- and gender-matched controls with normal cognitive functioning (NC) and 108 non-matched controls with mild cognitive impairment (MCI) was performed. Plasma IgG N-glycans were separated by ultra-performance liquid chromatography. Fourteen glycan peaks reflecting decreased of sialylation and core fucosylation, and increased bisecting N-acetylglucosamine (GlcNAc) N-glycan structures were of statistically significant differences between dementia and NC groups after controlling for confounders (p < 0.05; q < 0.05). Similarly, the differences for these 14 initial glycans were statistically significant between AD and NC groups after adjusting for the effects of confounders (p < 0.05; q < 0.05). The area under the receiver operating curve (AUC) value of the model consisting of GP8, GP9, and GP14 was determined to distinguish dementia from NC group as 0.876 [95% confidence interval (CI): 0.815–0.923] and distinguish AD from NC group as 0.887 (95% CI: 0.819–0.936). Patients with dementia were of an elevated proinflammatory activity via the significant changes of IgG glycome. Therefore, IgG N-glycans might contribute to be potential novel biomarkers for the neurodegenerative process risk assessment of dementia.
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Affiliation(s)
- Xiaoyu Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.,Department of Anesthesiology, Sanbo Brain Hospital, Capital Medical University, Beijing, 100095, China
| | - Hui Yuan
- Department of Neurology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, 271000, China
| | - Jihui Lyu
- Center for Cognitive Disorders, Beijing Geriatric Hospital, Beijing, 100095, China
| | - Xiaoni Meng
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Qiuyue Tian
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Yuejin Li
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China
| | - Jie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Xizhu Xu
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China
| | - Jing Su
- Department of Geriatrics, Tai'an City Central Hospital, Tai'an, 271000, China
| | - Haifeng Hou
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China
| | - Dong Li
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China
| | - Baoliang Sun
- Key Lab of Cerebral Microcirculation in Universities of Shandong, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China
| | - Wei Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China. .,School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China. .,School of Medical and Health Sciences, Edith Cowan University, Perth, WA, 6027, Australia.
| | - Youxin Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China. .,School of Medical and Health Sciences, Edith Cowan University, Perth, WA, 6027, Australia.
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17
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Abstract
Changes in immunoglobulin G (IgG) glycosylation pattern have been observed in a vast array of auto- and alloimmune, infectious, cardiometabolic, malignant, and other diseases. This chapter contains an updated catalog of over 140 studies within which IgG glycosylation analysis was performed in a disease setting. Since the composition of IgG glycans is known to modulate its effector functions, it is suggested that a changed IgG glycosylation pattern in patients might be involved in disease development and progression, representing a predisposition and/or a functional effector in disease pathology. In contrast to the glycopattern of bulk serum IgG, which likely relates to the systemic inflammatory background, the glycosylation profile of antigen-specific IgG probably plays a direct role in disease pathology in several infectious and allo- and autoimmune antibody-dependent diseases. Depending on the specifics of any given disease, IgG glycosylation read-out might therefore in the future be developed into a useful clinical biomarker or a supplementary to currently used biomarkers.
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Affiliation(s)
- Marija Pezer
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia.
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18
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Wang X, Zhong Z, Balmer L, Wang W. Glycosylation Profiling as a Biomarker of Suboptimal Health Status for Chronic Disease Stratification. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1325:321-339. [PMID: 34495543 DOI: 10.1007/978-3-030-70115-4_16] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
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.
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Affiliation(s)
- Xueqing Wang
- School of Health and Medical Sciences, Edith Cowan University, Perth, Australia
- College of Basic Medical Sciences, Harbin Medical University, Harbin, China
| | - Zhaohua Zhong
- College of Basic Medical Sciences, Harbin Medical University, Harbin, China
| | - Lois Balmer
- School of Health and Medical Sciences, Edith Cowan University, Perth, Australia
| | - Wei Wang
- School of Health and Medical Sciences, Edith Cowan University, Perth, Australia.
- Centre for Precision Health, ECU Strategic Research Centre, Edith Cowan University, Perth, Australia.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China.
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Taian, China.
- First Affiliated Hospital, Shantou University Medical College, Shantou, China.
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19
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Dall'Olio F, Malagolini N. Immunoglobulin G Glycosylation Changes in Aging and Other Inflammatory Conditions. EXPERIENTIA SUPPLEMENTUM (2012) 2021; 112:303-340. [PMID: 34687015 DOI: 10.1007/978-3-030-76912-3_10] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Among the multiple roles played by protein glycosylation, the fine regulation of biological interactions is one of the most important. The asparagine 297 (Asn297) of IgG heavy chains is decorated by a diantennary glycan bearing a number of galactose and sialic acid residues on the branches ranging from 0 to 2. In addition, the structure can present core-linked fucose and/or a bisecting GlcNAc. In many inflammatory and autoimmune conditions, as well as in metabolic, cardiovascular, infectious, and neoplastic diseases, the IgG Asn297-linked glycan becomes less sialylated and less galactosylated, leading to increased expression of glycans terminating with GlcNAc. These conditions alter also the presence of core-fucose and bisecting GlcNAc. Importantly, similar glycomic alterations are observed in aging. The common condition, shared by the above-mentioned pathological conditions and aging, is a low-grade, chronic, asymptomatic inflammatory state which, in the case of aging, is known as inflammaging. Glycomic alterations associated with inflammatory diseases often precede disease onset and follow remission. The aberrantly glycosylated IgG glycans associated with inflammation and aging can sustain inflammation through different mechanisms, fueling a vicious loop. These include complement activation, Fcγ receptor binding, binding to lectin receptors on antigen-presenting cells, and autoantibody reactivity. The complex molecular bases of the glycomic changes associated with inflammation and aging are still poorly understood.
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Affiliation(s)
- Fabio Dall'Olio
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.
| | - Nadia Malagolini
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
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20
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Petrović T, Lauc G, Trbojević-Akmačić I. The Importance of Glycosylation in COVID-19 Infection. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1325:239-264. [PMID: 34495539 DOI: 10.1007/978-3-030-70115-4_12] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently one of the major health problems worldwide. SARS-CoV-2 survival and virulence are shown to be impacted by glycans, covalently attached to proteins in a process of glycosylation, making glycans an area of interest in SARS-CoV-2 biology and COVID-19 infection. The SARS-CoV-2 uses its highly glycosylated spike (S) glycoproteins to bind to the cell surface receptor angiotensin-converting enzyme 2 (ACE2) glycoprotein and facilitate host cell entry. Viral glycosylation has wide-ranging roles in viral pathobiology, including mediating protein folding and stability, immune evasion, host receptor attachment, and cell entry. Modification of SARS-CoV-2 envelope membrane with glycans is important in host immune recognition and interaction between S and ACE2 glycoproteins. On the other hand, immunoglobulin G, a key molecule in immune response, shows a distinct glycosylation profile in COVID-19 infection and with increased disease severity. Hence, further studies on the role of glycosylation in SARS-CoV-2 infectivity and COVID-19 infection are needed for its successful prevention and treatment. This chapter focuses on recent findings on the importance of glycosylation in COVID-19 infection.
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Affiliation(s)
- Tea Petrović
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia.,Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
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21
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Jurić J, Kohrt WM, Kifer D, Gavin KM, Pezer M, Nigrovic PA, Lauc G. Effects of estradiol on biological age measured using the glycan age index. Aging (Albany NY) 2020; 12:19756-19765. [PMID: 33049709 PMCID: PMC7732334 DOI: 10.18632/aging.104060] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Accepted: 08/25/2020] [Indexed: 01/24/2023]
Abstract
Glycan age is a recently developed biomarker based on glycans attached to immunoglobulin G (IgG). In large population cohorts, glycan age associates well with lifestyle and disease-risk biomarkers, while some studies suggested that glycan changes precede development of several age-associated diseases. In this study we evaluated effects of estrogen on the glycan age. Gonadal hormones were suppressed in 36 healthy young women by gonadotropin releasing hormone agonist therapy for 6 months. In 15 of them estradiol was supplemented, while 21 received placebo resulting in very low estrogen levels during intervention. IgG was isolated from plasma samples before intervention, after 6 months of intervention and after subsequent 4-month recovery. Deprivation of gonadal hormones resulted in median increase of glycan age for 9.1 years (IQR 6.8 - 11.5 years, p = 3.73×10-8), which was completely prevented by transdermal estradiol therapy (change in glycan age = -0.23 years, IQR (-2.20 - 2.98). After the recovery period glycan age returned to baseline values in both groups. These results suggest that IgG glycans and consequently also the glycan age are under strong influence of gonadal hormones and that estradiol therapy can prevent the increase of glycan age that occurs in the perimenopausal period.
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Affiliation(s)
- Julija Jurić
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Wendy M. Kohrt
- Division of Geriatric Medicine, School of Medicine,
University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Eastern Colorado VA Geriatric Research, Education and
Clinical Center, Aurora, CO 80045, USA
| | - Domagoj Kifer
- Department of Biochemistry and Molecular Biology, Faculty of
Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Kathleen M Gavin
- Division of Geriatric Medicine, School of Medicine,
University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Eastern Colorado VA Geriatric Research, Education and
Clinical Center, Aurora, CO 80045, USA
| | - Marija Pezer
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Peter A. Nigrovic
- Division of Rheumatology, Inflammation, and Immunity, Brigham
and Women´s Hospital, Boston, MA 02115, USA
- Division of Immunology, Boston Children´s Hospital,
Boston, MA 02115, USA
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- Department of Biochemistry and Molecular Biology, Faculty of
Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
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22
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N-glycans as functional effectors of genetic and epigenetic disease risk. Mol Aspects Med 2020; 79:100891. [PMID: 32861467 DOI: 10.1016/j.mam.2020.100891] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 06/19/2020] [Accepted: 08/03/2020] [Indexed: 12/15/2022]
Abstract
N-glycosylation is a frequent modification of proteins, essential for all domains of life. N-glycan biosynthesis is a dynamic, complex, non-templated process, wherein specific glycoforms are modulated by various microenvironmental cues, cellular signals and local availability of dedicated enzymes and sugar precursors. This intricate regulatory network comprises hundreds of proteins, whose activity is dependent on both sequence of implicated genes and the regulation of their expression. In this regard, variation in N-glycosylation patterns stems from either gene polymorphisms or from stable epigenetic regulation of gene expression in different individuals. Moreover, epigenome alters in response to various environmental factors, representing a direct link between environmental exposure and changes in gene expression, that are subsequently reflected through altered N-glycosylation. N-glycosylation itself has a fundamental role in numerous biological processes, ranging from protein folding, cellular homeostasis, adhesion and immune regulation, to the effector functions in multiple diseases. Moreover, specific modification of the glycan structure can modulate glycoprotein's biological function or direct the faith of the entire cell, as seen on the examples of antibodies and T cells, respectively. Since immunoglobulin G is one of the most profoundly studied glycoproteins in general, the focus of this review will be on its N-glycosylation changes and their functional implications. By deepening the knowledge on the mechanistic roles that certain glycoforms exert in differential pathological processes, valuable insight into molecular perturbations occurring during disease development could be obtained. The prospect of resolving the exact biological pathways involved offers a potential for the development of new therapeutic interventions and molecular tools that would aid in prognosis, early referral and timely treatment of multiple disease conditions.
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23
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Peng J, Vongpatanasin W, Sacharidou A, Kifer D, Yuhanna IS, Banerjee S, Tanigaki K, Polasek O, Chu H, Sundgren NC, Rohatgi A, Chambliss KL, Lauc G, Mineo C, Shaul PW. Supplementation With the Sialic Acid Precursor N-Acetyl-D-Mannosamine Breaks the Link Between Obesity and Hypertension. Circulation 2019; 140:2005-2018. [PMID: 31597453 PMCID: PMC7027951 DOI: 10.1161/circulationaha.119.043490] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
BACKGROUND Obesity-related hypertension is a common disorder, and attempts to combat the underlying obesity are often unsuccessful. We previously revealed that mice globally deficient in the inhibitory immunoglobulin G (IgG) receptor FcγRIIB are protected from obesity-induced hypertension. However, how FcγRIIB participates is unknown. Studies were designed to determine if alterations in IgG contribute to the pathogenesis of obesity-induced hypertension. METHODS Involvement of IgG was studied using IgG μ heavy chain-null mice deficient in mature B cells and by IgG transfer. Participation of FcγRIIB was interrogated in mice with global or endothelial cell-specific deletion of the receptor. Obesity was induced by high-fat diet (HFD), and blood pressure (BP) was measured by radiotelemetry or tail cuff. The relative sialylation of the Fc glycan on mouse IgG, which influences IgG activation of Fc receptors, was evaluated by Sambucus nigra lectin blotting. Effects of IgG on endothelial NO synthase were assessed in human aortic endothelial cells. IgG Fc glycan sialylation was interrogated in 3442 human participants by mass spectrometry, and the relationship between sialylation and BP was evaluated. Effects of normalizing IgG sialylation were determined in HFD-fed mice administered the sialic acid precursor N-acetyl-D-mannosamine (ManNAc). RESULTS Mice deficient in B cells were protected from obesity-induced hypertension. Compared with IgG from control chow-fed mice, IgG from HFD-fed mice was hyposialylated, and it raised BP when transferred to recipients lacking IgG; the hypertensive response was absent if recipients were FcγRIIB-deficient. Neuraminidase-treated IgG lacking the Fc glycan terminal sialic acid also raised BP. In cultured endothelial cells, via FcγRIIB, IgG from HFD-fed mice and neuraminidase-treated IgG inhibited vascular endothelial growth factor activation of endothelial NO synthase by altering endothelial NO synthase phosphorylation. In humans, obesity was associated with lower IgG sialylation, and systolic BP was inversely related to IgG sialylation. Mice deficient in FcγRIIB in endothelium were protected from obesity-induced hypertension. Furthermore, in HFD-fed mice, ManNAc normalized IgG sialylation and prevented obesity-induced hypertension. CONCLUSIONS Hyposialylated IgG and FcγRIIB in endothelium are critically involved in obesity-induced hypertension in mice, and supportive evidence was obtained in humans. Interventions targeting these mechanisms, such as ManNAc supplementation, may provide novel means to break the link between obesity and hypertension.
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Affiliation(s)
- Jun Peng
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Wanpen Vongpatanasin
- Division of Cardiology, Dept. of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Anastasia Sacharidou
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Ivan S. Yuhanna
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Subhashis Banerjee
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Keiji Tanigaki
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Ozren Polasek
- Department of Public Health, University of Split School of Medicine, Split, Croatia
| | - Haiyan Chu
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Nathan C. Sundgren
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Anand Rohatgi
- Division of Cardiology, Dept. of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Ken L. Chambliss
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Gordan Lauc
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Chieko Mineo
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
| | - Philip W. Shaul
- Center for Pulmonary and Vascular Biology, Dept. of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX USA 75390
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24
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Wang H, Li X, Wang X, Liu D, Zhang X, Cao W, Zheng Y, Guo Z, Li D, Xing W, Hou H, Wu L, Song M, Zhong Z, Wang Y, Tan X, Lauc G, Wang W. Next-Generation (Glycomic) Biomarkers for Cardiometabolic Health: A Community-Based Study of Immunoglobulin G N-Glycans in a Chinese Han Population. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2019; 23:649-659. [PMID: 31313980 DOI: 10.1089/omi.2019.0099] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
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.
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Affiliation(s)
- Hao Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Xingang Li
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Xueqing Wang
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Di Liu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Xiaoyu Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Weijie Cao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Yulu Zheng
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Zheng Guo
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Dong Li
- School of Public Health, Shandong First Medical University, Taian, China
| | - Weijia Xing
- School of Public Health, Shandong First Medical University, Taian, China
| | - Haifeng Hou
- School of Public Health, Shandong First Medical University, Taian, China
| | - Lijuan Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Manshu Song
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Zhaohua Zhong
- Department of Microbiology, Harbin Medical University, Harbin, China
- Heilongjiang Key Laboratory of Immunity and Infection, Harbin, China
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Xuerui Tan
- The First Affiliated Hospital of Shantou University Medical College, Shantou University Medical College, Shantou, China
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, BIOCentar, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
- School of Public Health, Shandong First Medical University, Taian, China
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25
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Li X, Wang H, Russell A, Cao W, Wang X, Ge S, Zheng Y, Guo Z, Hou H, Song M, Yu X, Wang Y, Hunter M, Roberts P, Lauc G, Wang W. Type 2 Diabetes Mellitus is Associated with the Immunoglobulin G N-Glycome through Putative Proinflammatory Mechanisms in an Australian Population. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2019; 23:631-639. [PMID: 31526239 DOI: 10.1089/omi.2019.0075] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
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.
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Affiliation(s)
- Xingang Li
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | - Hao Wang
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Alyce Russell
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
- School of Population and Global Health, University of Western Australia, Crawley, Australia
| | - Weijie Cao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Xueqing Wang
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | - Siqi Ge
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yulu Zheng
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | - Zheng Guo
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | - Haifeng Hou
- School of Public Health, Shandong First Medical University (Shandong Academy of Medical Sciences), Taian, China
| | - Manshu Song
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Xinwei Yu
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
- Tiantan Hospital, Capital Medical University, Beijing, China
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Michael Hunter
- School of Population and Global Health, University of Western Australia, Crawley, Australia
- Busselton Health Study Centre, Busselton Population Medical Research Institute, Busselton, Australia
| | - Peter Roberts
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, BIOCentar, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Wei Wang
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
- School of Public Health, Shandong First Medical University (Shandong Academy of Medical Sciences), Taian, China
- The First Affiliated Hospital, Shantou University Medical College, Shantou, China
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26
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Mass spectrometry-based qualitative and quantitative N-glycomics: An update of 2017-2018. Anal Chim Acta 2019; 1091:1-22. [PMID: 31679562 DOI: 10.1016/j.aca.2019.10.007] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Revised: 10/04/2019] [Accepted: 10/05/2019] [Indexed: 12/14/2022]
Abstract
N-glycosylation is one of the most frequently occurring protein post-translational modifications (PTMs) with broad cellular, physiological and pathological relevance. Mass spectrometry-based N-glycomics has become the state-of-the-art instrumental analytical pipeline for sensitive, high-throughput and comprehensive characterization of N-glycans and N-glycomes. Improvement and new development of methods in N-glycan release, enrichment, derivatization, isotopic labeling, separation, ionization, MS, tandem MS and informatics accompany side-by-side wider and deeper application. This review provides a comprehensive update of mass spectrometry-based qualitative and quantitative N-glycomics in the years of 2017-2018.
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27
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Liu J, Dolikun M, Štambuk J, Trbojević-Akmačić I, Zhang J, Zhang J, Wang H, Meng X, Razdorov G, Menon D, Zheng D, Wu L, Wang Y, Song M, Lauc G, Wang W. Glycomics for Type 2 Diabetes Biomarker Discovery: Promise of Immunoglobulin G Subclass-Specific Fragment Crystallizable N-glycosylation in the Uyghur Population. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2019; 23:640-648. [PMID: 31393219 DOI: 10.1089/omi.2019.0052] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
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.
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Affiliation(s)
- Jiaonan Liu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Mamatyusupu Dolikun
- College of the Life Sciences and Technology, Xinjiang University, Urumqi, China
| | - Jerko Štambuk
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | | | - Jie Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Jinxia Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Hao Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Xiaoni Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | | | - Desmond Menon
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Deqiang Zheng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Lijuan Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Manshu Song
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia.,Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
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28
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Gebrehiwot AG, Melka DS, Kassaye YM, Rehan IF, Rangappa S, Hinou H, Kamiyama T, Nishimura SI. Healthy human serum N-glycan profiling reveals the influence of ethnic variation on the identified cancer-relevant glycan biomarkers. PLoS One 2018; 13:e0209515. [PMID: 30592755 PMCID: PMC6310272 DOI: 10.1371/journal.pone.0209515] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 12/06/2018] [Indexed: 12/14/2022] Open
Abstract
Background Most glycomics studies have focused on understanding disease mechanisms and proposing serum markers for various diseases, yet the influence of ethnic variation on the identified glyco-biomarker remains poorly addressed. This study aimed to investigate the inter-ethnic serum N-glycan variation among US origin control, Japanese, Indian, and Ethiopian healthy volunteers. Methods Human serum from 54 healthy subjects of various ethnicity and 11 Japanese hepatocellular carcinoma (HCC) patients were included in the study. We employed a comprehensive glycoblotting-assisted MALDI-TOF/MS-based quantitative analysis of serum N-glycome and fluorescence HPLC-based quantification of sialic acid species. Data representing serum N-glycan or sialic acid levels were compared among the ethnic groups using SPSS software. Results Total of 51 N-glycans released from whole serum glycoproteins could be reproducibly quantified within which 33 glycoforms were detected in all ethnicities. The remaining N-glycans were detected weakly but exclusively either in the Ethiopians (13 glycans) or in all the other ethnic groups (5 glycans). Highest abundance (p < 0.001) of high mannose, core-fucosylated, hyperbranched/hypersialylated N-glycans was demonstrated in Ethiopians. In contrast, only one glycan (m/z 2118) significantly differed among all ethnicities being highest in Indians and lowest in Ethiopians. Glycan abundance trend in Ethiopians was generally close to that of Japanese HCC patients. Glycotyping analysis further revealed ethnic-based disparities mainly in the branched and sialylated structures. Surprisingly, some of the glycoforms greatly elevated in the Ethiopian subjects have been identified as serum biomarkers of various cancers. Sialic acid level was significantly increased primarily in Ethiopians, compared to the other ethnicities. Conclusion The study revealed ethnic-specific differences in healthy human serum N-glycome with highest abundance of most glycoforms in the Ethiopian ethnicity. The results strongly emphasized the need to consider ethnicity matching for accurate glyco-biomarker identification. Further large-scale study employing various ethnic compositions is needed to verify the current result.
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Affiliation(s)
- Abrha G Gebrehiwot
- Division of Drug Discovery Research, Faculty of Advanced Life Science and Graduate School of Life Science, Hokkaido University, Kita-ku, Sapporo, Japan
| | - Daniel Seifu Melka
- Department of Biochemistry, School of Medicine, Addis Ababa University, Addis Ababa, Ethiopia
| | - Yimenashu Mamo Kassaye
- Department of Biochemistry, School of Medicine, Addis Ababa University, Addis Ababa, Ethiopia
| | - Ibrahim F Rehan
- Division of Drug Discovery Research, Faculty of Advanced Life Science and Graduate School of Life Science, Hokkaido University, Kita-ku, Sapporo, Japan.,Department of Animal Behaviour and Husbandry, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt
| | - Shobith Rangappa
- Division of Drug Discovery Research, Faculty of Advanced Life Science and Graduate School of Life Science, Hokkaido University, Kita-ku, Sapporo, Japan
| | - Hiroshi Hinou
- Division of Drug Discovery Research, Faculty of Advanced Life Science and Graduate School of Life Science, Hokkaido University, Kita-ku, Sapporo, Japan
| | - Toshiya Kamiyama
- Department of Gastroenterological Surgery I, Graduate School of Medicine, Hokkaido University, N15, W7, Kita-ku, Sapporo, Japan
| | - Shin-Ichiro Nishimura
- Division of Drug Discovery Research, Faculty of Advanced Life Science and Graduate School of Life Science, Hokkaido University, Kita-ku, Sapporo, Japan
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29
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Gudelj I, Lauc G, Pezer M. Immunoglobulin G glycosylation in aging and diseases. Cell Immunol 2018; 333:65-79. [DOI: 10.1016/j.cellimm.2018.07.009] [Citation(s) in RCA: 206] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 07/19/2018] [Accepted: 07/19/2018] [Indexed: 01/01/2023]
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30
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Liu D, Chu X, Wang H, Dong J, Ge SQ, Zhao ZY, Peng HL, Sun M, Wu LJ, Song MS, Guo XH, Meng Q, Wang YX, Lauc G, Wang W. The changes of immunoglobulin G N-glycosylation in blood lipids and dyslipidaemia. J Transl Med 2018; 16:235. [PMID: 30157878 PMCID: PMC6114873 DOI: 10.1186/s12967-018-1616-2] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Accepted: 08/23/2018] [Indexed: 11/19/2022] Open
Abstract
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.
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Affiliation(s)
- Di Liu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Xi Chu
- Center for Physical Examination, Xuanwu Hospital, Capital Medical University, Beijing, 100050 China
| | - Hao Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
- School of Medical Sciences, Edith Cowan University, Perth, WA 6027 Australia
| | - Jing Dong
- Center for Physical Examination, Xuanwu Hospital, Capital Medical University, Beijing, 100050 China
| | - Si-Qi Ge
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
- School of Medical Sciences, Edith Cowan University, Perth, WA 6027 Australia
| | - Zhong-Yao Zhao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Hong-Li Peng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Ming Sun
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Li-Juan Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Man-Shu Song
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Xiu-Hua Guo
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Qun Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - You-Xin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
- School of Medical Sciences, Edith Cowan University, Perth, WA 6027 Australia
| | - Gordan Lauc
- Genos Glycobiology Research Laboratory, 10000 Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, 10000 Zagreb, Croatia
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
- School of Medical Sciences, Edith Cowan University, Perth, WA 6027 Australia
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31
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Liu JN, Dolikun M, Štambuk J, Trbojević-Akmačić I, Zhang J, Wang H, Zheng DQ, Zhang XY, Peng HL, Zhao ZY, Liu D, Sun Y, Sun Q, Li QH, Zhang JX, Sun M, Cao WJ, Momčilović A, Razdorov G, Wu LJ, Russell A, Wang YX, Song MS, Lauc G, Wang W. The association between subclass-specific IgG Fc N-glycosylation profiles and hypertension in the Uygur, Kazak, Kirgiz, and Tajik populations. J Hum Hypertens 2018; 32:555-563. [PMID: 29867134 DOI: 10.1038/s41371-018-0071-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Revised: 03/15/2018] [Accepted: 04/06/2018] [Indexed: 01/01/2023]
Abstract
Hypertension results from the interaction of genetic and acquired factors. IgG occurs in the form of different subclasses, of which the effector functions show significant variation. The detailed differences between the glycosylation profiles of the individual IgG subclasses may be lost in a profiling method for total IgG N-glycosylation. In this study, subclass-specific IgG Fc glycosylation profile was investigated in the four northwestern Chinese minority populations, namely, Uygur (UIG), Kazak (KZK), Kirgiz (KGZ), and Tajik (TJK), composed of 274 hypertensive patients and 356 healthy controls. The results showed that ten directly measured IgG N-glycan traits (i.e., IgG1G0F, IgG2G0F, IgG2G1FN, IgG2G1FS, IgG2G2S, IgG4G0F, IgG4G1FS, IgG4G1S, IgG4G2FS, and IgG4G2N) representing galactosylation and sialylation are significantly associated with hypertension, with IgG4 consistently showing weaker associations of its sialylation, across the four ethnic groups. We observed a modest improvement on the AUC of ROC curve when the IgG Fc N-glycan traits are added into the glycan-based model (difference between AUCs, 0.044, 95% CI: 0.016-0.072, P = 0.002). The AUC of the diagnostic model indicated that the subclass-specific IgG Fc N-glycan profiles provide more information reinforcing current models utilizing age, gender, BMI, and ethnicity, and demonstrate the potential of subclass-specific IgG Fc N-glycosylation profiles to serve as a biomarker for hypertension. Further research is however required to determine the additive value of subclass-specific IgG Fc N-glycosylation on top of biomarkers, which are currently used.
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Affiliation(s)
- J N Liu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - M Dolikun
- College of the Life Sciences and Technology, Xinjiang University, Urumqi, China
| | - J Štambuk
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | | | - J Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - H Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - D Q Zheng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - X Y Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - H L Peng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Z Y Zhao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - D Liu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Y Sun
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Q Sun
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Q H Li
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - J X Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - M Sun
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - W J Cao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - A Momčilović
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - G Razdorov
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - L J Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - A Russell
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
| | - Y X Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
| | - M S Song
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China. .,School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia.
| | - G Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia.,Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - W Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
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32
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Affiliation(s)
- Donna K. Arnett
- From the College of Public Health, University of Kentucky, Lexington
| | - Steven A. Claas
- From the College of Public Health, University of Kentucky, Lexington
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33
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Protein N-Glycosylation in Cardiovascular Diseases and Related Risk Factors. CURRENT CARDIOVASCULAR RISK REPORTS 2018. [DOI: 10.1007/s12170-018-0579-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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