Evidence map›Paper›PMID 30157878›Full record

Observational studyJournal of translational medicine2018

The changes of immunoglobulin G N-glycosylation in blood lipids and dyslipidaemia.

Di Liu, Xi Chu, Hao Wang, Jing Dong, Si-Qi Ge, Zhong-Yao Zhao, Hong-Li Peng, Ming Sun, Li-Juan Wu, Man-Shu Song and 5 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Journal of translational medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
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

49 citing papers in PubMed, 88 citations in OpenAlex.

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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

15 authors at 3 institutions in 3 countries.

Di LiuBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Xi ChuCenter for Physical Examination, Xuanwu Hospital, Capital Medical University, Beijing, 100050, China.
Hao WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Jing DongCenter for Physical Examination, Xuanwu Hospital, Capital Medical University, Beijing, 100050, China.
Si-Qi GeBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Zhong-Yao ZhaoBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Hong-Li PengBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Ming SunBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Li-Juan WuBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Man-Shu SongBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Xiu-Hua GuoBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Qun MengBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
You-Xin WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China. wangy@ccmu.edu.cn.ORCID 0000-0002-6574-6706
Gordan LaucGenos Glycobiology Research Laboratory, 10000, Zagreb, Croatia.
Wei WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069, China.
Capital Medical University · CNEdith Cowan University · AUUniversity of Zagreb · HR

Funding

Australian-China Collaborative Grant NH&MRC-APP1112767Australian-China Collaborative Grant NSFC 81561128020National Natural Science Foundation of China 81370083National Natural Science Foundation of China 81530087National Natural Science Foundation of China 81673247National Natural Science Foundation of China 81773527
6 · The paper itself

Abstract

backgroundAlternative 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.

methodsHerein, 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.

resultsBlood 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).

conclusionsOur 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.

Indexed as

GlycosylationAdultAgedAnthropometryBody Mass IndexChinaChromatography, High Pressure LiquidCross-Sectional StudiesDyslipidemiasFemaleHumansImmunoglobulin GLipidsMaleMiddle AgedOdds RatioImmunoglobulin GLipidsPolysaccharidesBlood lipidsDyslipidaemiaImmunoglobulin GN-Glycosylation

Identifiers

PMID30157878
PMCPMC6114873
OpenAlexW2889507865

What OpenQuestion holds

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LicenceCC BY
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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.