2026-04-05T12:43:46Zhttps://recercat.cat/oai/request

oai:recercat.cat:10459.1/4687992025-10-20T18:34:04Zcom_2072_3622col_2072_479130

Lipidomic analysis reveals metabolism alteration associated with subclinical carotid atherosclerosis in type 2 diabetes Barranco-Altirriba, Maria Rossell, Joana Alonso, Núria Weber, Ralf J.M. Ortega, Emilio Lloyd, Gavin R. Hernández García, Marta Yanes, Oscar Capellades, Jordi Winder, Catherine Junza, Alexandra Falguera, Mireia Franch-Nadal, Josep Dunn, Warwick B. Perera-Lluna, Alexandre Castelblanco Echavarría, Esmeralda Mauricio Puente, Dídac Lipidomic profile Smoking habit Subclinical carotid atherosclerosis Type 1 diabetes Type 2 diabetes Background. Disruption of lipid metabolism contributes to increased cardiovascular risk in diabetes. Methods. We evaluated the associations between serum lipidomic profile and subclinical carotid atherosclerosis (SCA) in type 1 (T1D) and type 2 (T2D) diabetes, and in subjects without diabetes (controls) in a cross-sectional study. All subjects underwent a lipidomic analysis using ultra-high performance liquid chromatography–electrospray ionization tandem mass spectrometry, carotid ultrasound (mode B) to assess SCA, and clinical assessment. Multiple linear regression models were used to assess the association between features and the presence and burden of SCA in subjects with T1D, T2D, and controls separately. Additionally, multiple linear regression models with interaction terms were employed to determine features significantly associated with SCA within risk groups, including smoking habit, hypertension, dyslipidaemia, antiplatelet use and sex. Depending on the population under study, different confounding factors were considered and adjusted for, including sample origin, sex, age, hypertension, dyslipidaemia, body mass index, waist circumference, glycated haemoglobin, glucose levels, smoking habit, diabetes duration, antiplatelet use, and alanine aminotransferase levels. Results. A total of 513 subjects (151 T1D, 155 T2D, and 207 non-diabetic control) were included, in whom the percentage with SCA was 48.3%, 49.7%, and 46.9%, respectively. A total of 27 unique lipid species were associated with SCA in subjects with T2D, in former/current smokers with T2D, and in individuals with T2D without dyslipidaemia. Phosphatidylcholines and diacylglycerols were the main SCA-associated lipidic classes. Ten different species of phosphatidylcholines were up-regulated, while 4 phosphatidylcholines containing polyunsaturated fatty acids were down-regulated. One diacylglycerol was down-regulated, while the other 3 were positively associated with SCA in individuals with T2D without dyslipidaemia. We discovered several features significantly associated with SCA in individuals with T1D, but only one sterol could be partially annotated. Conclusions. We revealed a significant disruption of lipid metabolism associated with SCA in subjects with T2D, and a larger SCA-associated disruption in former/current smokers with T2D and individuals with T2D who do not undergo lipid-lowering treatment. This work was funded by Spanish Ministry of Health, Instituto de Salud Carlos III (Madrid, Spain) grants PI15/0625 (to DM and EC), PI17/01362 (to NA), PI18/0328 (to DM), FEDER “Una manera de hacer Europa”, and by Fundació La Marató de TV3 2016 (303/C/2016) (201602.30.31) (to NA). This work was supported by the Grant PID2021-122952OB-I00 funded by AEI h t t p s : / / d o i . o r g / 1 0 . 1 3 0 3 9 / 5 0 1 1 0 0 0 1 1 0 3 3 and by ERDF A way of making Europe (to AP). This research was supported by Biomedical Research Networking Center in Diabetes and Associated Metabolic Disorders (CIBERDEM–CB15/00071) (to DM) and Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), initiatives of Instituto de Investigación Carlos III (ISCIII); ISCIII (grant AC22/00035) (to AP); and the CERCA Programme / Generalitat de Catalunya. B2SLab is certified as 2021 SGR 01052. Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau is accredited by the Generalitat de Catalunya as Centre de Recerca de Catalunya (CERCA). 2025-10-20T18:34:03Z 2025-10-20T18:34:03Z 2025 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/10459.1/468799 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-122952OB-I00/ES/METODOS Y APLICACIONES DE APRENDIZAJE PROFUNDO Y SUPERFICIAL DE FENOTIPOS PARA ANALISIS Y PREDICCION DE DATOS BIOMEDICOS Reproducció del document publicat a: https://doi.org/10.1186/s12933-025-02701-z Cardiovascular Diabetology, 2025, vol. 24, núm. 1, 152 cc-by (c)The Authors, 2025 Attribution 4.0 International info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ BioMed Central