Evidence map›Paper›PMID 27428197›Full record

Observational studyMedicine2016

Profiling IgG N-glycans as potential biomarker of chronological and biological ages: A community-based study in a Han Chinese population.

Xinwei Yu, Youxin Wang, Jasminka Kristic, Jing Dong, Xi Chu, Siqi Ge, Hao Wang, Honghong Fang, Qing Gao, Di Liu and 9 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
6.8field-weighted citation impact, top 3% 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

55 citing papers in PubMed, 1 synthesis or guideline pooled it, 124 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Immunoglobulin G in aging and cancer.Frontiers in immunology · 2026
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Metabolic Markers and Association of Biological Sex in Lupus Nephritis.International journal of molecular sciences · 2023
    Article
  20. 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

19 authors at 4 institutions in 4 countries.

Xinwei YuBeijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia Genos Glycobiology Research Laboratory, Zagreb, Croatia Physical Examination Center, Xuanwu Hospital, Capital Medical University, Beijing, China Centre for Population Health Sciences, Medical School, University of Edinburgh, Edinburgh, UK.
Youxin Wang
Jasminka Kristic
Jing Dong
Xi Chu
Siqi Ge
Hao Wang
Honghong Fang
Qing Gao
Di Liu
Zhongyao Zhao
Hongli Peng
Maja Pucic Bakovic
Lijuan Wu
Manshu Song
Igor Rudan
Harry Campbell
Gordan Lauc
Wei Wang
Capital Medical University · CNGenos (Croatia) · HREdith Cowan University · AUUniversity of Edinburgh · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As an important post-translation modifying process, glycosylation significantly affects the structure and function of immunoglobulin G (IgG) molecules and is essential in many steps of the inflammatory cascade. Studies have demonstrated the potential of using glycosylation features of IgG as a component of predictive biomarkers for chronological age in several European populations, whereas no study has been reported in Chinese. Herein, we report various patterns of changes in IgG glycosylation associated with age by analyzing IgG glycosylation in 701 community-based Han Chinese (244 males, 457 females; 23-68 years old). Eleven IgG glycans, including FA2B, A2G1, FA2[6]G1, FA2[3]G1, FA2[6]BG1, FA2[3]BG1, A2G2, A2BG2, FA2G2, FA2G2S1, and FA2G2S2, change considerably with age and specific combinations of these glycan features can explain 23.3% to 45.4% of the variance in chronological age in this population. This indicates that these combinations of glycan features provide more predictive information than other single markers of biological age such as telomere length. In addition, the clinical traits such as fasting plasma glucose and aspartate aminotransferase associated with biological age are strongly correlated with the combined glycan features. We conclude that IgG glycosylation appears to correlate with both chronological and biological ages, and thus its possible role in the aging process merits further study.

Indexed as

LongevityAdultAgedBiomarkersChinaCross-Sectional StudiesFemaleGlycoproteinsGlycosylationHumansImmunoglobulin GMaleMiddle AgedPolysaccharidesBiomarkersGlycoproteinsglycosylated IgGImmunoglobulin GPolysaccharides

Identifiers

PMID27428197
PMCPMC4956791
OpenAlexW2473360305

What OpenQuestion holds

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LicenceCC BY-NC
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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.