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Quantification of lipoproteins by proton nuclear magnetic resonance spectroscopy ( 1 H-NMRS) improves the prediction of cardiac autonomic dysfunction in patients with type 1 diabetes.

Authors :
Nattero-Chávez L
Insenser M
Amigó N
Samino S
Martínez-Micaelo N
Dorado Avendaño B
Quintero Tobar A
Escobar-Morreale HF
Luque-Ramírez M
Source :
Journal of endocrinological investigation [J Endocrinol Invest] 2024 Aug; Vol. 47 (8), pp. 2075-2085. Date of Electronic Publication: 2024 Jan 06.
Publication Year :
2024

Abstract

Aims: To assess if advanced characterization of serum glycoprotein and lipoprotein profile, measured by proton nuclear magnetic resonance spectroscopy ( <superscript>1</superscript> H-NMRS) improves a predictive clinical model of cardioautonomic neuropathy (CAN) in subjects with type 1 diabetes (T1D).<br />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 <superscript>1</superscript> H-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 (AUC <subscript>ROC</subscript> ).<br />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 (R <superscript>2</superscript>  = 0.078; P = 0.003) retained intermediate-density lipoprotein-triglycerides (IDL-TG) [β:0.082 (95%CI: 0.005; 0.160); P = 0.039], high-density lipoprotein-triglycerides (HDL-TGL)/HDL-Cholesterol [β:3.633 (95%CI: 0.873; 6.394); P = 0.010], and large-HDL particle number [β: 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 A <subscript>1c</subscript> enhanced its diagnostic performance, improving AUC <subscript>ROC</subscript> from 0.546 (95%CI: 0.404; 0.688) to 0.728 (95%CI: 0.616; 0.840).<br />Conclusions: When added to clinical variables, <superscript>1</superscript> H-NMRS-lipoprotein particle profiles may be helpful to identify those patients with T1D at risk of CAN.<br /> (© 2024. The Author(s), under exclusive licence to Italian Society of Endocrinology (SIE).)

Details

Language :
English
ISSN :
1720-8386
Volume :
47
Issue :
8
Database :
MEDLINE
Journal :
Journal of endocrinological investigation
Publication Type :
Academic Journal
Accession number :
38182920
Full Text :
https://doi.org/10.1007/s40618-023-02289-9