Evidence map›Paper›PMID 29867134›Full record

ArticleJournal of human hypertension2018

The association between subclass-specific IgG Fc N-glycosylation profiles and hypertension in the Uygur, Kazak, Kirgiz, and Tajik populations.

J N Liu, M Dolikun, J Štambuk, I Trbojević-Akmačić, J Zhang, H Wang, D Q Zheng, X Y Zhang, H L Peng, Z Y Zhao and 15 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Journal of human hypertension, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Metabolomic heterogeneity of ageing with ethnic diversity: a step closer to healthy ageing.Metabolomics : Official journal of the Metabolomic Society · 2024
    Article
  2. Review
  3. Article
  4. Article
  5. High-Throughput Glycomic Methods.Chemical reviews · 2022
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Glycomics: Immunoglobulin GOmics : a journal of integrative biology · 2020
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
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

25 authors.

J N LiuBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
M DolikunCollege of the Life Sciences and Technology, Xinjiang University, Urumqi, China.
J ŠtambukGenos Glycoscience Research Laboratory, Zagreb, Croatia.
I Trbojević-AkmačićGenos Glycoscience Research Laboratory, Zagreb, Croatia.
J ZhangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
H WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
D Q ZhengBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
X Y ZhangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
H L PengBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
Z Y ZhaoBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
D LiuBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
Y SunBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
Q SunBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
Q H LiBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
J X ZhangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
M SunBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
W J CaoBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
A MomčilovićGenos Glycoscience Research Laboratory, Zagreb, Croatia.
G RazdorovGenos Glycoscience Research Laboratory, Zagreb, Croatia.
L J WuBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
A RussellSchool of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia.
Y X WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China. wangy@ccmu.edu.cn.ORCID 0000-0002-6574-6706
M S SongBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China. songms@ccmu.edu.cn.
G LaucGenos Glycoscience Research Laboratory, Zagreb, Croatia.
W WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.ORCID 0000-0002-1430-1360

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertension results from the interaction of genetic and acquired factors. IgG occurs in the form of different subclasses, of which the effector functions show significant variation. The detailed differences between the glycosylation profiles of the individual IgG subclasses may be lost in a profiling method for total IgG N-glycosylation. In this study, subclass-specific IgG Fc glycosylation profile was investigated in the four northwestern Chinese minority populations, namely, Uygur (UIG), Kazak (KZK), Kirgiz (KGZ), and Tajik (TJK), composed of 274 hypertensive patients and 356 healthy controls. The results showed that ten directly measured IgG N-glycan traits (i.e., IgG1G0F, IgG2G0F, IgG2G1FN, IgG2G1FS, IgG2G2S, IgG4G0F, IgG4G1FS, IgG4G1S, IgG4G2FS, and IgG4G2N) representing galactosylation and sialylation are significantly associated with hypertension, with IgG4 consistently showing weaker associations of its sialylation, across the four ethnic groups. We observed a modest improvement on the AUC of ROC curve when the IgG Fc N-glycan traits are added into the glycan-based model (difference between AUCs, 0.044, 95% CI: 0.016-0.072, P = 0.002). The AUC of the diagnostic model indicated that the subclass-specific IgG Fc N-glycan profiles provide more information reinforcing current models utilizing age, gender, BMI, and ethnicity, and demonstrate the potential of subclass-specific IgG Fc N-glycosylation profiles to serve as a biomarker for hypertension. Further research is however required to determine the additive value of subclass-specific IgG Fc N-glycosylation on top of biomarkers, which are currently used.

Indexed as

AdultAgedAsia, CentralBiomarkersCase-Control StudiesChinaFemaleGlycosylationHumansHypertensionImmunoglobulin GMaleMiddle AgedBiomarkersImmunoglobulin G

Identifiers

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Registered trials

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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.