Evidence map›Paper›PMID 41373650›Full record

ArticleInternational journal of molecular sciences2025

Quantitative Modeling of IgG N-Glycosylation Profiles from Population Data.

Elena Kutumova, Nikita Mandrik, Ruslan Sharipov, Maja Pučić-Baković, Borna Rapčan, Yurii Aulchenko, Gordan Lauc, Fedor Kolpakov

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Elena KutumovaDepartment of Computational Biology, Sirius University of Science and Technology, 354340 Sirius, Russia.ORCID 0000-0001-7746-5760
Nikita MandrikBiosoft.Ru, Ltd., 630058 Novosibirsk, Russia.
Ruslan SharipovLaboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, 630090 Novosibirsk, Russia.ORCID 0000-0003-2182-5493
Maja Pučić-BakovićGenos Glycoscience Research Laboratory, 10000 Zagreb, Croatia.ORCID 0000-0003-0866-623X
Borna RapčanGenos Glycoscience Research Laboratory, 10000 Zagreb, Croatia.ORCID 0009-0000-7265-5581
Yurii AulchenkoLaboratory of Theoretical and Applied Functional Genomics, Novosibirsk State University, 630090 Novosibirsk, Russia.
Gordan LaucGenos Glycoscience Research Laboratory, 10000 Zagreb, Croatia.ORCID 0000-0003-1840-9560
Fedor KolpakovDepartment of Computational Biology, Sirius University of Science and Technology, 354340 Sirius, Russia.

Funding

Russian Science Foundation 24-14-20031
6 · The paper itself

Abstract

Glycosylation of immunoglobulin G (IgG) is a critical regulator of its functional properties. We present an original mathematical model, calibrated and validated using quantitative IgG N-glycosylation data from two independent cohorts, 915 individuals from Korčula Island and 890 individuals from Vis Island, Croatia, reported in prior studies. The datasets comprise relative glycan levels measured by ultrahigh-performance liquid chromatography (UHPLC), represented by 22 chromatographic peaks per individual. By fitting the model to these data, we estimated the total concentrations of seven key enzymes involved in glycan biosynthesis across four Golgi compartments. The model revealed an age-related decline in β-N-acetylglucosaminylglycopeptide β-1,4-galactosyltransferase (GalT) concentrations in both populations, emphasizing its essential role in driving age-dependent changes in IgG glycan profiles and underscoring its potential as a biomarker of aging.

Indexed as

Immunoglobulin GAdultAgedAged, 80 and overAgingCroatiaFemaleGlycoproteinsGlycosylationHumansMaleMiddle AgedModels, TheoreticalPolysaccharidesGlycoproteinsglycosylated IgGImmunoglobulin GPolysaccharidesBioUMLGolgi apparatusimmunoglobulin GN-glycosylationrule-based modeling

Identifiers

PMID41373650
PMCPMC12692266

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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.