Author, as appears in the article.: Amigó N; Castelblanco E; Julve J; Martínez-Micaelo N; Alonso N; Hernández M; Ribalta J; Guardiola M; Torán-Monserrat P; Lopez-Lifante V; Herrero-Alonso C; Arteaga I; Ortega E; Franch-Nadal J; Mauricio D
Department: Medicina i Cirurgia
URV's Author/s: Guardiola Guionnet, Montserrat / Ribalta Vives, Josep
Keywords: Type 2 diabetes Time factors Spain Risk factors Risk assessment Reproducibility of results Proton magnetic resonance spectroscopy Prospective studies Prognosis Predictive value of tests Nuclear magnetic resonance spectroscopy Middle aged Male Lipoproteins Humans Heart disease risk factors Glycoproteins Female Diabetes mellitus, type 2 Diabetes mellitus Cardiovascular events Cardiovascular diseases Biomarkers Biomarker Aged
Abstract: Traditional risk factors cannot accurately predict cardiovascular events (CVE) in type 2 diabetes (T2D). The LIPOCAT study aimed to prospectively evaluate the clinical utility of advanced lipoprotein characteristics and glycoproteins to predict future cardiovascular events (CVE) in a large cohort of subjects with type 2 diabetes mellitus (T2D). From four different Spanish prospective cohorts, a total of 933 T2D subjects were selected to form the LIPOCAT study. Advanced 1H-Nuclear Magnetic Resonance (1H-NMR) analysis included lipoprotein (Liposcale®) and glycoprotein (Glycoscale) profiling. Random forest classification models and Area Under the Receiver Operating Characteristics (AUROC) analysis were used to assess the differential contribution of advanced variables in predicting CVE. Validation was performed using an external cohort. Out of 933 T2D subjects, 104 reported a CVE during follow-up. Analysis of Liposcale®/Glycoscale uncovered elevations in the circulating VLDL-cholesterol(C), remnant IDL-triglycerides (TG) and LDL-TG in subjects with CVE, along with glycoproteins (Glyc) A and B. Moreover, the incorporation of advanced Liposcale® variables to a base model constructed with traditional risk factors significantly improved the prediction of CVE, as evidenced by 1.5-fold increase in the C statistic (AUROC), reaching AUROC values of 0.756. In the independent validation cohort, similar improvements in AUROC values were observed by adding the advanced variables to the traditional models. Advanced 1H-NMR analysis revealed previously hidden lipoprotein and glycoprotein characteristics associated with CVE in T2D subjects.
Thematic Areas: Saúde coletiva Medicina ii Medicina i Internal medicine Interdisciplinar Farmacia Endocrinology, diabetes and metabolism Endocrinology & metabolism Educação física Ciências biológicas ii Ciências biológicas i Cardiology and cardiovascular medicine Cardiac & cardiovascular systems Biotecnología
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: montse.guardiola@urv.cat josep.ribalta@urv.cat
Author identifier: 0000-0002-9696-7384 0000-0002-8879-4719
Record's date: 2025-03-22
Paper version: info:eu-repo/semantics/publishedVersion
Paper original source: Cardiovascular Diabetology. 24 (1): 88-
APA: Amigó N; Castelblanco E; Julve J; Martínez-Micaelo N; Alonso N; Hernández M; Ribalta J; Guardiola M; Torán-Monserrat P; Lopez-Lifante V; Herrero-Alons (2025). Advanced serum lipoprotein and glycoprotein profiling for cardiovascular event prediction in type 2 diabetes mellitus: the LIPOCAT study.. Cardiovascular Diabetology, 24(1), 88-. DOI: 10.1186/s12933-025-02636-5
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Entity: Universitat Rovira i Virgili
Journal publication year: 2025
Publication Type: Journal Publications
Repositori URV