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Cited by 401Glycosylation and Glycoproteins ResearchAdvanced Glycation End Products researchMonoclonal and Polyclonal Antibodies Research

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Glycans Are a Novel Biomarker of Chronological and Biological Ages

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Krištić, Jasminka, Vučković, Frano, Menni, Cristina, Klarić, Lucija, Keser, Toma, Beceheli, Ivona, Pučić-Baković, Maja, Novokmet, Mislav, Mangino, Massimo, Thaqi, Kujtim, Rudan, Pavao, Novokmet, Natalija, Šarac, Jelena, Missoni, Saša, Kolčić, Ivana, Polašek, Ozren, Rudan, Igor, Campbell, Harry, Hayward, Caroline, Aulchenko, Yurii, Valdes, Ana, Wilson, James F., Gornik, Olga, Primorac, Dragan, Zoldoš, Vlatka, Spector, Tim, Lauc, Gordan·2014·The Journals of Gerontology: Series A
DOI 10.1093/gerona/glt190PMC PMC4049143
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Abstract

Fine structural details of glycans attached to the conserved N-glycosylation site significantly not only affect function of individual immunoglobulin G (IgG) molecules but also mediate inflammation at the systemic level. By analyzing IgG glycosylation in 5,117 individuals from four European populations, we have revealed very complex patterns of changes in IgG glycosylation with age. Several IgG glycans (including FA2B, FA2G2, and FA2BG2) changed considerably with age and the combination of these three glycans can explain up to 58% of variance in chronological age, significantly more than other markers of biological age like telomere lengths. The remaining variance in these glycans strongly correlated with physiological parameters associated with biological age. Thus, IgG glycosylation appears to be closely linked with both chronological and biological ages. Considering the important role of IgG glycans in inflammation, and because the observed changes with age promote inflammation, changes in IgG glycosylation also seem to represent a factor contributing to aging. SIGNIFICANCE STATEMENT: Glycosylation is the key posttranslational mechanism that regulates function of immunoglobulins, with multiple systemic repercussions to the immune system. Our study of IgG glycosylation in 5,117 individuals from four European populations has revealed very extensive and complex changes in IgG glycosylation with age. The combined index composed of only three glycans explained up to 58% of variance in age, considerably more than other biomarkers of age like telomere lengths. The remaining variance in these glycans strongly correlated with physiological parameters associated with biological age; thus, IgG glycosylation appears to be closely linked with both chronological and biological ages. The ability to measure human biological aging using molecular profiling has practical applications for diverse fields such as disease prevention and treatment, or forensics.

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Crossref · 10.1093/gerona/glt190

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Figures

Figure 1. UPLC analysis of immunoglobulin G (IgG) glycosylation. Each IgG contains one conserved N-glycosylation site on Asn197 of its heavy chain. Different glycans can be attached to this site and the process seems to be highly regulated. UPLC analysis can reveal composition of the glycome attached to a population of IgG molecules by separating total IgG N-glycome into 24 chromatographic glycan peaks (GP1–GP24), mostly corresponding to individual glycan structures.
Figure 1. UPLC analysis of immunoglobulin G (IgG) glycosylation. Each IgG contains one conserved N-glycosylation site on Asn197 of its heavy chain. Different glycans can be attached to this site and the process seems to be highly regulated. UPLC analysis can reveal composition of the glycome attached to a population of IgG molecules by separating total IgG N-glycome into 24 chromatographic glycan peaks (GP1–GP24), mostly corresponding to individual glycan structures.CC BY-NC · PubMed Central
Figure 2. Relationship between age and selected glycan structures. Plots indicate associations between the individual contributions of four selected glycan structures to the total immunoglobulin G glycome and chronological age in four different human populations. Blue and red curves are fitted local regression models describing gender-specific relationship between age and glycan structure. The shaded region is a pointwise 95% confidence interval on the fitted values (there is 95% confidence that the true regression curve lies within the shaded region).
Figure 2. Relationship between age and selected glycan structures. Plots indicate associations between the individual contributions of four selected glycan structures to the total immunoglobulin G glycome and chronological age in four different human populations. Blue and red curves are fitted local regression models describing gender-specific relationship between age and glycan structure. The shaded region is a pointwise 95% confidence interval on the fitted values (there is 95% confidence that the true regression curve lies within the shaded region).CC BY-NC · PubMed Central
Figure 3. Individual changes in immunoglobulin G (IgG) glycans with age. Two time points of relative levels of glycans (percentages of individual glycan structures within the total IgG glycome), which associated strongly with age within an individual, are presented on the background showing levels of the same glycans for different individuals from the same population.
Figure 3. Individual changes in immunoglobulin G (IgG) glycans with age. Two time points of relative levels of glycans (percentages of individual glycan structures within the total IgG glycome), which associated strongly with age within an individual, are presented on the background showing levels of the same glycans for different individuals from the same population.CC BY-NC · PubMed Central
Figure 4. Prediction of chronological age from measured immunoglobulin G glycans. Using the simplified GlycanAge model, predicted age was calculated for 2,035 individuals from the Orkney cohort and plotted against real chronological age of the same individual (A). The prediction of age was further improved by inclusion of forced expiratory volume and systolic blood pressure (B).
Figure 4. Prediction of chronological age from measured immunoglobulin G glycans. Using the simplified GlycanAge model, predicted age was calculated for 2,035 individuals from the Orkney cohort and plotted against real chronological age of the same individual (A). The prediction of age was further improved by inclusion of forced expiratory volume and systolic blood pressure (B).CC BY-NC · PubMed Central

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Research works printed but not linked: 1

  1. Lauc, 2013, Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers, PLoS Genet, 9, 10.1371/journal.pgen.1003225 · DOI

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Metadata

Authors
Krištić, J., Vučković, F., Menni, C., Klarić, L., Keser, T., Beceheli, I., Pučić-Baković, M., Novokmet, M., Mangino, M., Thaqi, K., Rudan, P., Novokmet, N., Šarac, J., Missoni, S., Kolčić, I., Polašek, O., Rudan, I., Campbell, H., Hayward, C., Aulchenko, Y., Valdes, A., Wilson, J. F., Gornik, O., Primorac, D., Zoldoš, V., Spector, T., & Lauc, G.
Affiliations
  • King's College London (GB)
  • University of Zagreb (HR)
  • Institute for Anthropological Research (HR)
  • University of Split (HR)
  • University of Edinburgh (GB)
  • Institute of Genetics and Cancer (GB)
  • Institute of Cytology and Genetics (RU)
  • University of Osijek (HR)
Corresponding author
  • Krištić, Jasminka
  • Vučković, Frano
ORCID
Venue
The Journals of Gerontology: Series A
Publisher
Oxford University Press (OUP)
Published
2013-12-10
Volume
69
Issue
7
Pages
779-789
ISSN
  • 1079-5006 (ISSN-L)
  • 1758-535X
DOI
10.1093/gerona/glt190
PMC
PMC4049143
OpenAlex
W2136722035
Cited by
400
References
52
Citations by year
2026: 33 · 2025: 41 · 2024: 50 · 2023: 41 · 2022: 40 · 2021: 37 · 2020: 44 · 2019: 25 · 2018: 28 · 2017: 18 · 2016: 25 · 2015: 13 · 2014: 2 · 2013: 1
FWCI
6.12
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • The Journals of Gerontology Series A (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Research Portal (King's College London) (publishedVersion, other-oa)
  • Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by-nc)
Funders
  • Wellcome Trust
  • National Institute for Health and Care Research
  • European Commission (305479)
  • Russian Foundation for Basic Research
  • National Institutes of Health
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Glycosylation and Glycoproteins Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Advanced Glycation End Products research
  • Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
Keywords
IgG glycosylation, glycans, biological age, chronological age, aging biomarkers, N-glycosylation, telomere length, inflammation, post-translational modification, IgG
MeSH terms
Adolescent, Adult, Aged, Aged, 80 and over, Aging, Female, Glycosylation, United Kingdom, Humans, Immunoglobulin G, Longevity, Male, Middle Aged, Models, Biological, Polysaccharides, Protein Processing, Post-Translational, Scotland, Cohort Studies, Biomarkers, Croatia, Inflammation Mediators, Young Adult

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