Evidence map›Paper›PMID 40297543›Full record

ArticleJournal of inflammation research2025

Immunoglobulin G N-Glycosylation and Inflammatory Factors: Analysis of Biomarkers for the Diagnosis of Moyamoya Disease.

Xu Zan, Chao Liu, Xinyue Wang, Shuyu Sun, Zhongchen Li, Wenyu Zhang, Tanggui Sun, Jiheng Hao, Liyong Zhang

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Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Xu Zan *School of Clinical Medicine, Shandong Second Medical University, Weifang, People's Republic of China.
Chao Liu *Department of Neurosurgery, Liaocheng People's Hospital, Liaocheng, People's Republic of China.
Xinyue WangSchool of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, People's Republic of China.
Shuyu SunSchool of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, People's Republic of China.
Zhongchen LiDepartment of Neurosurgery, Liaocheng People's Hospital, Liaocheng, People's Republic of China.
Wenyu ZhangSchool of Clinical Medicine, Shandong Second Medical University, Weifang, People's Republic of China.
Tanggui SunDepartment of Neurosurgery, Liaocheng People's Hospital, Liaocheng, People's Republic of China.
Jiheng HaoDepartment of Neurosurgery, Liaocheng People's Hospital, Liaocheng, People's Republic of China.
Liyong ZhangDepartment of Neurosurgery, Liaocheng People's Hospital, Liaocheng, People's Republic of China.ORCID 0000-0001-8244-0082

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: N-glycosylation-modified immunoglobulin G (IgG) is crucial for managing the inflammatory response balance and significantly influences the progression of many inflammatory disorders. IgG N-glycosylation has been demonstrated to correlate with many risk factors for moyamoya disease (MMD), such as hypertension, diabetes, and dyslipidemia. This research aimed to evaluate the diagnostic efficacy of IgG N-glycosylation for MMD. Methods: Ultra-high-performance liquid chromatography (UPLC) was employed to examine the properties of IgG N-glycans in blood samples from 116 patients with MMD and 126 controls, resulting in the quantitative determination of 24 initial glycan peaks (GP). Through the Lasso algorithm and multivariate logistic regression analysis, we constructed a diagnostic model based on initial glycans and related inflammatory factors to distinguish MMD patients from healthy individuals. Results: After adjusting for potential confounding variables, including age, fasting blood glucose (FBG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), neutrophil count (NEUT), and lymphocyte count (LYM), our study demonstrated significant differences in the characteristics of 6 initial glycans and 16 derived glycans between the MMD cohort and the healthy control group. Based on the above findings, we developed an MMD diagnostic model that combines initial glycans with related inflammatory factors. The curve of receiver operating characteristic (ROC) was utilized to evaluate the model's ability to distinguish MMD patients from healthy subjects. The findings indicated a robust area under the curve (AUC) of 0.963 (95% CI: 0.940, 0.987). Conclusion: This study found that the occurrence and progression of MMD may be associated with decreased levels of sialylation, galactosylation, and fucosylation and increased bisecting GlcNAc. This may be involved in the occurrence of MMD by regulating the balance of inflammation. Therefore, the IgG N-glycosylation is expected to become a potential biomarker for the screening of MMD.

Indexed as

biomarkersimmunoglobulin Ginflammationmoyamoya diseaseN-glycans

Identifiers

PMID40297543
PMCPMC12036608

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