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.
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Key Points
In the last few years, several studies have shown that plasma lipid species are a determinant factor for T2DM development, suggesting that changes in this profile may trigger the development of this disease. Moreover, the specific fatty acids (FA) composition in plasma phospholipids has also been shown to be useful for assessing T2DM risk. Here, several works have studied the association between FA and the probability of diabetes development. However, most of these studies analyzed individual FA or FA groups, such as saturated FA or polyunsaturated omega 3 or 6 rather than analyzing the full FA profile.
Based on this previous evidence, it was hypothesized that a specific plasma FA profile rather individual fatty acids may precede T2DM development in coronary heart patients, and, therefore, could be used as a biomarker to assess T2DM risk. The aim here was to evaluate the plasma FA profile as an associated biomarker for T2DM development in the non-T2DM coronary heart disease patients from the CORDIOPREV study.
This study identified a fatty acids (FA) profile in patients with CHD to assess the T2DM development risk by Random Survival Forest, a decision tree for prediction which sorted the different fatty acids by their importance according to the time of the T2DM development, and reduced the number of variables to 4 fatty acids from a total of 24 FA identified in plasma. Further testing in a Validation set of patients yielded reproducible results. Moreover, patients with a deleterious FA profile (higher FA Score values) have lower insulin sensitivity as determined by ISI index, and higher hepatic insulin resistance, as determined by the HIRI index. The relationship between plasma ALA levels and T2DM is supported by both animal and in vitro studies, which have demonstrated the capacity of ALA to regulate glucose homeostasis by affecting insulin sensitivity in different ways, such as potential functions in gene regulation, or fat metabolism. In this study, plasma ALA accurately assessed the T2DM risk and was also associated with insulin action. In fact, patients with higher levels of ALA showed better insulin sensitivity, with a lower insulin resistance and lower hepatic insulin resistance.
In addition to the ALA, an even-chain saturated FA, myristic acid (MA), an n6 PUFA, arachidonic acid (AA), and petroselinic acid (PA) were jointly selected by random survival forest in the model with the lowest error prediction to assess T2DM development. The results suggest that an altered fatty acid profile precedes T2DM development and may be used as a predictive biomarker for the detection of patients at risk of T2DM development. In addition, our results also support the association between plasma lipid quantity and quality and insulin sensitivity, based on the relationship between a defined fatty acid profile, combined as a FA Score, and individual FA plasma levels with insulin sensitivity assessing indexes. Further studies are needed to assess the effectiveness of nutritional intervention in changing the FA profile and, therefore, preventing the development of type 2 diabetes mellitus.