Document Type

Journal Article

Publication Title

Journal of Diabetes Research

Publisher

Hindawi

School

School of Medical and Health Sciences

RAS ID

31741

Comments

Wu, Z., Li, H., Liu, D., Tao, L., Zhang, J., Liang, B., ... & Wang, W. (2020). IgG glycosylation profile and the glycan score are associated with type 2 diabetes in independent Chinese populations: a case-control study. Journal of Diabetes Research, 2020. https://doi.org/10.1155/2020/5041346

Abstract

Background. The relationship between the IgG glycan panel and type 2 diabetes remains unclear in Chinese population. We aimed to investigate the association of the IgG glycan profile and glycan score with type 2 diabetes. Methods. In the discovery population, 162 individuals diagnosed with type 2 diabetes and 162 matched controls from Beijing health management cohort were included. We analyzed the IgG glycan profile and composed a glycan score for type 2 diabetes. Findings were validated in the replication population from Beijing Xuanwu community cohort (280 cases and 508 controls). Area under curve (AUC) using 10-fold and bootstrap validation, net reclassification index (NRI), and integrated discrimination index (IDI) were calculated for the glycan score. Results. In the discovery population, 5 initial IgG glycans and 7 derived traits were significantly associated with type 2 diabetes after Bonferroni correction and Lasso selection, which were validated in the replication population subsequently. The glycan score composed of these IgG glycans and traits showed a strong association with type 2 diabetes (combined odds ratio (OR): 3.78) and its risk factors. In the replication population, AUC of the model involving clinical traits improved from 0.74 to above 0.90, and the values of NRI and IDI were 0.35 and 0.42, respectively, with the glycan score added. Conclusions. IgG glycosylation profiles were associated with type 2 diabetes and the glycan score may be a novel indicator for diabetes which reflected a proinflammatory status.

DOI

10.1155/2020/5041346

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Research Themes

Health

Priority Areas

Multidisciplinary biological approaches to personalised disease diagnosis, prognosis and management

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