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Quantification of lipoproteins by proton nuclear magnetic resonance spectroscopy (1H-NMRS) improves the prediction of cardiac autonomic dysfunction in patients with type 1 diabetes.
Nattero-Chávez, L; Insenser, M; Amigó, N; Samino, S; Martínez-Micaelo, N; Dorado Avendaño, B; Quintero Tobar, A; Escobar-Morreale, H F; Luque-Ramírez, M.
Affiliation
  • Nattero-Chávez L; Department of Endocrinology and Nutrition, Hospital Universitario Ramón y Cajal, Madrid, Spain. marialia.nattero@salud.madrid.org.
  • Insenser M; Diabetes, Obesity and Human Reproduction Research Group, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) and Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain. marialia.nattero@salud.madrid.org.
  • Amigó N; Diabetes, Obesity and Human Reproduction Research Group, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) and Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain. mariarosa.insenser@salud.madrid.org.
  • Samino S; Biosfer Teslab, CIBERDEM, Madrid, Spain.
  • Martínez-Micaelo N; Department of Basic Medical Sciences, Universitat Rovira i Virgili (URV), Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
  • Dorado Avendaño B; Biosfer Teslab, CIBERDEM, Madrid, Spain.
  • Quintero Tobar A; Biosfer Teslab, CIBERDEM, Madrid, Spain.
  • Escobar-Morreale HF; Department of Endocrinology and Nutrition, Hospital Universitario Ramón y Cajal, Madrid, Spain.
  • Luque-Ramírez M; Diabetes, Obesity and Human Reproduction Research Group, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) and Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain.
J Endocrinol Invest ; 2024 Jan 06.
Article in En | MEDLINE | ID: mdl-38182920
ABSTRACT

AIMS:

To assess if advanced characterization of serum glycoprotein and lipoprotein profile, measured by proton nuclear magnetic resonance spectroscopy (1H-NMRS) improves a predictive clinical model of cardioautonomic neuropathy (CAN) in subjects with type 1 diabetes (T1D).

METHODS:

Cross-sectional study (ClinicalTrials.gov Identifier NCT04950634). CAN was diagnosed using Ewing's score. Advanced characterization of macromolecular complexes including glycoprotein and lipoprotein profiles in serum samples were measured by 1H-NMRS. We addressed the relationships between these biomarkers and CAN using correlation and regression analyses. Diagnostic performance was assessed by analyzing their areas under the receiver operating characteristic curves (AUCROC).

RESULTS:

Three hundred and twenty-three patients were included (46% female, mean age and duration of diabetes of 41 ± 13 years and 19 ± 11 years, respectively). The overall prevalence of CAN was 28% [95% confidence interval (95%CI) 23; 33]. Glycoproteins such as N-acetylglucosamine/galactosamine and sialic acid showed strong correlations with inflammatory markers such as high-sensitive C-reactive protein, fibrinogen, IL-10, IL-6, and TNF-α. On the contrary, we did not find any association between the former and CAN. A stepwise binary logistic regression model (R2 = 0.078; P = 0.003) retained intermediate-density lipoprotein-triglycerides (IDL-TG) [ß0.082 (95%CI 0.005; 0.160); P = 0.039], high-density lipoprotein-triglycerides (HDL-TGL)/HDL-Cholesterol [ß3.633 (95%CI 0.873; 6.394); P = 0.010], and large-HDL particle number [ß 3.710 (95%CI 0.677; 6.744); P = 0.001] as statistically significant determinants of CAN. Adding these lipoprotein particles to a clinical prediction model of CAN that included age, duration of diabetes, and A1c enhanced its diagnostic performance, improving AUCROC from 0.546 (95%CI 0.404; 0.688) to 0.728 (95%CI 0.616; 0.840).

CONCLUSIONS:

When added to clinical variables, 1H-NMRS-lipoprotein particle profiles may be helpful to identify those patients with T1D at risk of CAN.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: J Endocrinol Invest Year: 2024 Document type: Article Affiliation country: España

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: J Endocrinol Invest Year: 2024 Document type: Article Affiliation country: España