Startseite Medizin Serum N-glycans as independent predictors of the incidence of type 2 diabetes: a prospective investigation in the AEGIS cohort
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Serum N-glycans as independent predictors of the incidence of type 2 diabetes: a prospective investigation in the AEGIS cohort

  • Iago Carballo ORCID logo EMAIL logo , Óscar Lado-Baleato ORCID logo , Róisín O’Flaherty ORCID logo , Manuela Alonso-Sampedro ORCID logo , Manuel M. Vicente ORCID logo , Salomé S. Pinho ORCID logo , Radka Saldova ORCID logo , Francisco Gude ORCID logo und Arturo González-Quintela ORCID logo
Veröffentlicht/Copyright: 24. Juni 2025
Clinical Chemistry and Laboratory Medicine (CCLM)
Aus der Zeitschrift Clinical Chemistry and Laboratory Medicine (CCLM) Band 63 Heft 11

Abstract

Objectives

Glycosylation is a tightly controlled co-translational and post-translational enzymatic modification. Total N-glycome profiling in blood serum/plasma provides information on the most common serum/plasma glycosylation. Total plasma N-glycome from various population samples displayed predictive ability for type 2 diabetes incidence in two previous studies; we therefore explored the ability of total serum N-glycome to predict this disease in a general adult population.

Methods

This prospective cohort study included a random sample of 1516 adults from a single Spanish municipality. Participants’ glycemic status (non-diabetes, type 2 diabetes) was evaluated at baseline and at a mean follow-up of 7.4 years. Total serum N-glycome at baseline was also measured. Serum enzymatic N-glycan release was performed on a robotic platform followed by HILIC-UPLC glycan separation. Total serum N-glycans were quantified and employed alone, as well as in combination with classical risk factors, to construct type 2 diabetes prediction models.

Results

Total serum N-glycome peak 37, mainly composed of A3F1G3S3, predisposed participants to type 2 diabetes; however, total serum N-glycome peak 24, mainly composed of A2G2S2, was protective against type 2 diabetes. The interaction between total serum N-glycome peaks 37 and 24 predicted the incidence of type 2 diabetes over time (area under the curve 0.801 [0.750–0.853]). Their predictive power had an independent and additive effect on classical prediction factors.

Conclusions

The interaction between total serum N-glycome peaks 37 and 24 may constitute a promising predictive biomarker for type 2 diabetes improving the classical prediction tools.

Keywords: biomarkers; diabetes; glycosylation; N-glycome; prediabetes; predictive model
Corresponding author: Iago Carballo, MD, PhD, Department of Internal Medicine, University Hospital Complex of Santiago (CHUS), Rúa da Choupana s/n, 15706, Santiago de Compostela, Spain; and Research Methods Group (RESMET), Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain, E-mail:
Iago Carballo and Óscar Lado-Baleato share first authorship.

Funding source: European Regional Development Fund (FEDER)

Funding source: Fundación Alfonso Martín Escudero

Funding source: Instituto de Salud Carlos III

Award Identifier / Grant number: JR21/00007

Award Identifier / Grant number: PI13/2594

Award Identifier / Grant number: PI16/01395

Award Identifier / Grant number: PI16/01404

Award Identifier / Grant number: PT23/00118

Award Identifier / Grant number: RD21/0016/0022

Acknowledgments

The authors would like to thank Carmen Fernández Merino, A Estrada Primary Care Center, A Estrada, Spain, PhD, MD; Luis Meijide Calvo, A Estrada Primary Care Center, A Estrada, Spain, MD; Jesús Rey García, A Estrada Primary Care Center, A Estrada, Spain, MD; Sonia Sánchez Batán, A Estrada Primary Care Center, A Estrada, Spain, MD; Juan Sánchez Castro, A Estrada Primary Care Center, A Estrada, Spain, MD; Vanesa Alende Castro, University Hospital Complex of Santiago (CHUS), Santiago de Compostela, Spain, PhD, MD; and Cristina Macía Rodríguez, University Hospital Complex of Santiago (CHUS), Santiago de Compostela, Spain, PhD, MD; for their contribution to individual recruitment and data collection. The authors would also like to thank Márcia S. Pereira, Institute for Research and Innovation in Health (i3S), University of Porto, Porto, Portugal, PhD, for her contribution in analyzing the data. None of them received financial support for their participation.

  1. Research ethics: The general survey and the specific glycomic studies were approved by the Galician Regional Ethics Committee (codes 2010-315 and 2016-464, respectively) and conformed to the current Helsinki Declaration.

  2. Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.

  3. Author contributions: Iago Carballo: Funding acquisition, Conceptualization, Data curation, Investigation, Methodology, Project administration, Writing – original draft. Óscar Lado-Baleato: Data curation, Investigation, Formal analysis, Methodology, Writing – original draft. Róisín O’Flaherty: Data curation, Investigation, Writing – review & editing. Manuela Alonso-Sampedro: Conceptualization, Data curation, Investigation, Writing – review & editing. Manuel M. Vicente: Formal analysis, Methodology, Writing – review & editing. Salomé S. Pinho: Methodology, Writing – review & editing. Radka Saldova: Investigation, Formal analysis, Writing – review & editing. Francisco Gude: Funding acquisition, Conceptualization, Formal analysis, Methodology, Writing – review & editing. Arturo González-Quintela: Funding acquisition, Conceptualization, Methodology, Supervision, Writing – review & editing. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: Iago Carballo, Óscar Lado-Baleato, Francisco Gude, and Arturo González-Quintela have applied for a patent related to the results described in this work: a method for predicting the risk of type 2 diabetes.

  6. Research funding: This study was supported by grants from the Instituto de Salud Carlos III (ISCIII) (PI16/01404, PI13/2594, PI16/01395, RD21/0016/0022, PT23/00118), the European Regional Development Fund (FEDER), and Fundación Alfonso Martín Escudero. IC was granted a Juan Rodés contract (JR21/00007), funded by Instituto de Salud Carlos III (ISCIII) and co-funded by the European Union. The study funders were not involved in the design of the study; the collection, analysis, and interpretation of data; writing the report; and did not impose any restrictions regarding the publication of the report.

  7. Data availability: The data that support the findings of this study are available on reasonable request from the corresponding author. The data are not publicly available due to Spanish law restrictions.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2025-0045).

Received: 2025-01-14
Accepted: 2025-06-10
Published Online: 2025-06-24
Published in Print: 2025-10-27

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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  6. Mini Review
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https://doi.org/10.1515/cclm-2025-0045
Schlagwörter für diesen Artikel
biomarkers; diabetes; glycosylation; N-glycome; prediabetes; predictive model

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial
  3. Advancing diagnostic stewardship through claims-based utilization analysis: toward a system-wide vision of diagnostic excellence
  4. Review
  5. Biomarkers in body fluids and their detection techniques for human intestinal permeability assessment
  6. Mini Review
  7. Challenges of using natriuretic peptides to screen for the risk of developing heart failure in patients with diabetes: a report from the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Committee on Clinical Applications of Cardiac Bio-Markers (C-CB)
  8. Opinion Papers
  9. Reference intervals in value-based laboratory medicine: a shift from single-point measurements to metabolic variation-based models
  10. Overview of laboratory diagnostics for immediate management of patients presenting to the emergency department with acute bleeding
  11. What Matters Most: an Age-Friendly approach to pathology and laboratory medicine
  12. No fault or negligence after an adverse analytical finding due to a contaminated supplement: mission impossible. Two examples involving trimetazidine
  13. General Clinical Chemistry and Laboratory Medicine
  14. Utilization analysis of laboratory tests using health insurance claims data: advancing nationwide diagnostic stewardship monitoring systems
  15. Evaluating large language models as clinical laboratory test recommenders in primary and emergency care: a crucial step in clinical decision making
  16. A novel corrective model based on red blood cells indices and haemolysis index enables accurate unhaemolysed potassium determination in haemolysed samples – Hemokalc project
  17. Validation of (self-collected) capillary blood using a topper collection system as alternative for venous sampling for 15 common clinical chemistry analytes
  18. Acoustophoresis-based blood sampling and plasma separation for potentially minimizing sampling-related blood loss
  19. Clinical validation of a liquid chromatography single quadrupole mass spectrometry (LC-MS) method using Waters Kairos™ Amino Acid Kit reagents
  20. Robustness of steroidomics-based machine learning for diagnosis of primary aldosteronism: a laboratory medicine perspective
  21. Investigation of the possible cause of over-estimation of human aldosterone in plasma, using a unique, non-synthetic human aldosterone-free matrix
  22. Performance of afternoon (16:00 h) serum cortisol for the diagnosis of Cushing’s syndrome
  23. MAGLUMI® Tacrolimus (CLIA) assay: analytical performances and comparison with LC-MS/MS and ARCHITECT Tacrolimus (CMIA) assay
  24. Assessment of 2023 ACR/EULAR antiphospholipid syndrome classification criteria in a Spanish cohort
  25. Comprehensive evaluation of antiphospholipid antibody testing methodologies in APS diagnosis: performance comparisons across assay systems and clinical subtypes
  26. Candidate Reference Measurement Procedures and Materials
  27. Exploring commutable materials for serum folate measurement: challenges in cross-method harmonization
  28. Reference Values and Biological Variations
  29. Reference ranges for ionized calcium in plasma in Danish children aged 0 days to 3 years using laboratory registry data
  30. A step forward in pediatric hemophagocytic lymphohistiocytosis and autoimmune disease: pediatric reference interval for serum soluble IL-2 receptor and soluble CD163
  31. Cancer Diagnostics
  32. Cellular expression of PD-1, PD-L1 and CTLA-4 in patients with JAK2V617F mutated myeloproliferative disorders
  33. Diabetes
  34. Serum N-glycans as independent predictors of the incidence of type 2 diabetes: a prospective investigation in the AEGIS cohort
  35. Infectious Diseases
  36. An assessment of molecular diagnosis of tuberculosis and multi-drug resistant tuberculosis testing and quality assessment: findings of an international survey
  37. Letters to the Editor
  38. Targeting low-value laboratory care
  39. Is time a significant factor in the release of potassium from lithium heparin plasma and serum?
  40. External quality assessment in resource-constrained laboratories: a survey of practices and perceptions in Nepal
  41. Is successfulness of platelet clump disaggregation by vortexing influenced by platelet measurement methods?
  42. Oligoclonal banding analysis: assessing plasma use and time interval requirements for paired CSF and blood
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