Ramírez Vélez, Robinson

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Ramírez Vélez

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Robinson

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Ciencias de la Salud

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  • PublicationOpen Access
    Comparative lipidomic profiling in adolescents with obesity and adolescents with type 1 diabetes
    (Elsevier, 2025-01-18) García Hermoso, Antonio; Huerta Uribe, Nidia; Izquierdo Redín, Mikel; González-Ruíz, Katherine; Correa Bautista, Jorge Enrique; Ramírez Vélez, Robinson; Ciencias de la Salud; Osasun Zientziak
    Objective: Both adolescents with obesity and those with type 1 diabetes (T1D) exhibit alterations in lipid profiles, but direct comparisons are limited. Comparing lipidomic profiles between obese individuals and those with T1D is crucial for identifying specific metabolic markers, informing tailored interventions, and advancing precision medicine strategies for these distinct populations. The aim of the study was to compare lipidomic profiles between adolescents with obesity and those with T1D, and to analyze associations between metabolites and clinical parameters. Methods: We included 156 adolescents aged 11–18 years (59.6% girls) from the HEPAFIT (n=114, obesity) and Diactive-1 Cohort (n=42, T1D) studies. Clinical measures included anthropometrics, body composition, lipids, liver enzymes, glucose, and HbA1c. Lipidomic analysis of 277 serum/ plasma metabolites used UHPLC-MS. Results: Distinct lipid profiles were seen, with higher diglycerides, triglycerides, and certain phosphatidylinositols in the obesity group, while phosphatidylcholines, phosphatidylethanolamines, cholesterol esters, sphingomyelins, and ceramides were elevated in T1D. Triglycerides acyl chain lengths and saturation levels also varied. Multivariate analysis identified seven metabolites –PC(O-18:1/18:1), PC(O-18:1/22:4), PE(O-16:0/18:1), PE(18:2e/22:6), PC(40:1), PC(O22:1/20:4), and PE(P-18:0/18:1)– significantly associated with clinical parameters. Conclusions: Distinct lipid profiles were observed among adolescents with obesity and T1D in the study, emphasizing the importance of understanding specific metabolite associations with clinical parameters for more precise health management.