Evidence map›Paper›PMID 42059453›Full record

ArticlemAbs2026

Population-level analysis of glycoprotein glycoforms.

Alejandro Gomez Toledo, James T Sorrentino, Sanne Schoffelen, Bjørn Voldborg, Erika Velasquez, Aaron M Scott, Göran Larson, Nathan E Lewis, Johan Malmström

Abstract read
In one paragraph

Article in mAbs, 2026. 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

9 authors.

Alejandro Gomez ToledoDivision of Infection Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden.
James T SorrentinoBioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, USA.
Sanne SchoffelenDepartment of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark.
Bjørn VoldborgDepartment of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark.ORCID 0000-0002-7005-1642
Erika VelasquezIPSC Laboratory for CNS Disease Modelling, Department of Experimental Medical Science, BMC D10, Lund University, Lund, Sweden.
Aaron M ScottDivision of Infection Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden.
Göran LarsonDepartment of Laboratory Medicine, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden.
Nathan E LewisDepartments of Pediatrics and Bioengineering, University of California, San Diego, La Jolla, CA, USA.
Johan MalmströmDivision of Infection Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden.

Funding

Unraveling the mammalian secretory pathway through systems biology and algorithm developmentR35GM119850 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LEWIS, NATHAN ENOCH · 2016 to 2025
$4.3M
ALF agreement ALFGBG_1006161NIGMS NIH HHS R35 GM119850Novo Nordisk Foundation NNF10CC1016517Novo Nordisk Foundation NNF20SA0066621Swedish Research Council 2018-05795Swedish Research Council 2019-01646Wallenberg academy fellow KAW 2017.0271Wallenberg foundation WAF 2017.0271
6 · The paper itself

Abstract

The structure and function of many proteins are regulated post-translationally through glycan attachment. These glycans, assembled via competing enzymatic reactions, generate diverse glycoform populations - variants sharing a protein backbone but differing in glycan structures. While current analyses often focus on individual glycoforms, we demonstrate that population-level glycoform analysis - integrating spectral, biosynthetic, and physicochemical relationships - reveals new insights into glycoprotein regulation. Applied to immunoglobulin subclasses and antithrombin III (AT3), this approach provides comprehensive coverage of glycoform repertoires from human and murine plasma and biopharmaceuticals. It also enables sensitive quantification of glycosylation changes arising from in vitro manipulations or in vivo infections. Finally, we introduce a statistical framework adapted from ecological biodiversity studies, revealing that both IgG and AT3 exhibit skewed glycoform distributions shaped by biosynthetic constraints and degradation. Our findings demonstrate the added value of population-level glycoform analysis in understanding protein function and regulation through glycosylation.

Indexed as

GlycoproteinsPolysaccharidesStreptococcal InfectionsAnimalsAntithrombin IIICHO CellsCricetulusDisease Models, AnimalFemaleGlycosylationHumansImmunoglobulin GMass SpectrometryMetabolomicsMiceMice, Inbred C57BLAntithrombin IIIGlycoproteinsImmunoglobulin GPolysaccharidesGlycan heterogeneityglycoproteomicsglycosylationimmunoglobulin

Identifiers

PMID42059453
PMCPMC13134397

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.