Literature DB >> 31313980

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

Hao Wang1,2, Xingang Li2, Xueqing Wang2, Di Liu1, Xiaoyu Zhang1, Weijie Cao1, Yulu Zheng2, Zheng Guo2, Dong Li3, Weijia Xing3, Haifeng Hou3, Lijuan Wu1, Manshu Song1,2, Zhaohua Zhong4,5, Youxin Wang1, Xuerui Tan6, Gordan Lauc7,8, Wei Wang1,2,3.   

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.

Entities:  

Keywords:  Chinese Han population; N-glycans; biomarkers; cardiometabolic disease; glycomics; public health

Mesh:

Substances:

Year:  2019        PMID: 31313980     DOI: 10.1089/omi.2019.0099

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  4 in total

1.  The history of IgG glycosylation and where we are now.

Authors:  Brian A Cobb
Journal:  Glycobiology       Date:  2020-03-20       Impact factor: 4.313

2.  Glycomic biomarkers are instrumental for suboptimal health status management in the context of predictive, preventive, and personalized medicine.

Authors:  Xiaoni Meng; Biyan Wang; Xizhu Xu; Manshu Song; Haifeng Hou; Wei Wang; Youxin Wang
Journal:  EPMA J       Date:  2022-04-11       Impact factor: 8.836

3.  Expression Profile of Immunoglobulin G Glycosylation in Children With Epilepsy in Han Nationality.

Authors:  Yuejin Li; Fengxue Shi; Guanglei Wang; Jian Lv; Haitao Zhang; Hao Jin; Xueyu Chen; Meng Wang; Peirui Li; Long Ji
Journal:  Front Mol Neurosci       Date:  2022-07-01       Impact factor: 6.261

4.  Effects of estradiol on biological age measured using the glycan age index.

Authors:  Julija Jurić; Wendy M Kohrt; Domagoj Kifer; Kathleen M Gavin; Marija Pezer; Peter A Nigrovic; Gordan Lauc
Journal:  Aging (Albany NY)       Date:  2020-10-13       Impact factor: 5.955

  4 in total

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