Evidence map›Paper›PMID 29699572›Full record

ArticleJournal of neuroinflammation2018

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

Di Liu, Zhongyao Zhao, Anxin Wang, Siqi Ge, Hao Wang, Xiaoyu Zhang, Qi Sun, Weijie Cao, Ming Sun, Lijuan Wu and 4 more

Open access · goldAbstract read
In one paragraph

Article in Journal of neuroinflammation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 82 citations in OpenAlex.

  1. Pooled it
  2. Immunoglobulin G in aging and cancer.Frontiers in immunology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 2 institutions in 2 countries.

Di LiuBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Zhongyao ZhaoBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Anxin WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Siqi GeBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Hao WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Xiaoyu ZhangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Qi SunBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Weijie CaoBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Ming SunBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Lijuan WuBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Manshu SongBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Yong ZhouBeijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China.
Wei WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China.
Youxin WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Beijing, 100069, China. wangy@ccmu.edu.cn.ORCID http://orcid.org/0000-0002-6574-6706
Capital Medical University · CNEdith Cowan University · AU

Funding

Joint Project of the Australian National Health & Medical Research Council (NHMRC) and the NSFC NHMRC APP1112767, NSFC 81561128020National Natural Science Foundation of China 81370083National Natural Science Foundation of China 81673247
6 · The paper itself

Abstract

backgroundGlycosylation significantly affects protein structure and function and thus participates in multiple physiologic and pathologic processes. Studies demonstrated that immunoglobulin G (IgG) N-glycosylation associates with the risk factors of ischemic stroke (IS), such as aging, obesity, dyslipidemia, type 2 diabetes, and hypertension.

methodsThe study aimed to investigate the association between IgG N-glycosylation and IS in a Chinese population. IgG glycome composition in patients with IS (n = 78) and cerebral arterial stenosis (CAS) (n = 75) and controls (n = 77) were analyzed by ultra-performance liquid chromatography.

resultsEleven initial glycans and 10 derived glycans in IgG glycome representing galactosylation, sialylation, and bisecting GlcNAc significantly differed between IS patients and CAS and healthy controls after controlling for gender, age, obesity, diabetes, hypertension, and dyslipidemia. Logistic regression models incorporating IgG glycan traits were able to distinguish IS from CAS (area under receiver-operator characteristic curves (AUC), 0.802; 95% confidence interval (CI), 0.732-0.872) and controls (AUC, 0.740; 95% CI, 0.661-0.819). The canonical correlation analysis indicated that initial N-glycan structures are significantly correlated with inflammation markers (r = 0.566, p < 0.001).

conclusionOur findings indicated that loss of galactose and sialic acid, as well as addition of bisecting GlcNAc, might involve in pro- or anti-inflammatory IgG functionality and further contribute to the pathogenesis of IS. IgG glycan profiles may be developed as clinical useful biomarkers for chronic disease in the future.

Indexed as

AdultBrain IschemiaChromatography, LiquidCorrelation of DataC-Reactive ProteinFemaleGlycoproteinsGlycosylationHumansImmunoglobulin GMaleMatrix Metalloproteinase 9Middle AgedPolysaccharidesRetrospective StudiesROC CurveC-Reactive ProteinGlycoproteinsglycosylated IgGImmunoglobulin GMatrix Metalloproteinase 9MMP9 protein, humanPolysaccharidesTumor Necrosis Factor-alphaCerebral arterial stenosisImmunoglobulin GInflammation markersIschemic strokeN-glycans

Identifiers

PMID29699572
PMCPMC5921323
OpenAlexW2807457024

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.