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

Carballo Fernández, Iago; Lado Baleato, Oscar; O'Flaherty, Róisín; Alonso Sampedro, Manuela; Vicente, Manuel M; Pinho, Salomé S; Saldova, Radka; Gude Sampedro, Francisco; González Quintela, Arturo
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URI: http://hdl.handle.net/20.500.11940/22001
PMID: 41025837
DOI: 10.1515/cclm-2025-0045
ESSN: 1437-4331
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Clin Chem Lab Med . 2025 Jun 24;63(11):2330-2340. (3.077Mb)
Material suplementario. Figura 1 (10.24Kb)
Material suplementario. Figura 2 (261.7Kb)
Material suplementario. Tabla 1 (311.1Kb)
Data de publicación
2025
Título da revista
Clinical chemistry and laboratory medicine
Tipo de contido
Artigo
DeCS
incidencia | adulto | estudios de cohortes | insulina | polisacáridos | factores de riesgo | diabetes mellitus | estudios prospectivos
MeSH
Prospective Studies | Diabetes Mellitus | Adult | Risk Factors | Insulin | Cohort Studies | Population | Polysaccharides | Incidence
Resumo
[EN] 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. 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. 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. 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.

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