1. A plasma fatty acid profile associated to type 2 diabetes development: from the CORDIOPREV study.
- Author
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Villasanta-Gonzalez A, Alcala-Diaz JF, Vals-Delgado C, Arenas AP, Cardelo MP, Romero-Cabrera JL, Rodriguez-Cantalejo F, Delgado-Lista J, Malagon MM, Perez-Martinez P, Schulze MB, Camargo A, and Lopez-Miranda J
- Subjects
- Biomarkers, Fatty Acids, Humans, Coronary Disease diagnosis, Coronary Disease epidemiology, Coronary Disease etiology, Diabetes Mellitus, Type 2, Insulin Resistance
- Abstract
Purpose: The prevalence of type 2 diabetes mellitus (T2DM) is increasing worldwide. For this reason, it is essential to identify biomarkers for the early detection of T2DM risk and/or for a better prognosis of T2DM. We aimed to identify a plasma fatty acid (FA) profile associated with T2DM development., Methods: We included 462 coronary heart disease patients from the CORDIOPREV study without T2DM at baseline. Of these, 107 patients developed T2DM according to the American Diabetes Association (ADA) diagnosis criteria after a median follow-up of 60 months. We performed a random classification of patients in a training set, used to build a FA Score, and a Validation set, in which we tested the FA Score., Results: FA selection with the highest prediction power was performed by random survival forest in the Training set, which yielded 4 out of the 24 FA: myristic, petroselinic, α-linolenic and arachidonic acids. We built a FA Score with the selected FA and observed that patients with a higher score presented a greater risk of T2DM development, with an HR of 3.15 (95% CI 2.04-3.37) in the Training set, and an HR of 2.14 (95% CI 1.50-2.84) in the Validation set, per standard deviation (SD) increase. Moreover, patients with a higher FA Score presented lower insulin sensitivity and higher hepatic insulin resistance (p < 0.05)., Conclusion: Our results suggest that a detrimental FA plasma profile precedes the development of T2DM in patients with coronary heart disease, and that this FA profile can, therefore, be used as a predictive biomarker. CLINICAL TRIALS.GOV., Identifier: NCT00924937., (© 2021. The Author(s).)
- Published
- 2022
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