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MicroRNAs (miRNAs) regulate the expression of genes associated with the development of diseases, including type 2 diabetes mellitus (T2DM). However, the use of miRNAs to predict T2DM remission has been poorly studied. Therefore, we aimed to investigate whether circulating miRNAs could be used to predict the probability of T2DM remission in patients with coronary heart disease. We included the newly diagnosed T2DM (n = 190) of the 1,002 patients from the CORDIOPREV study. Seventy-three patients reverted from T2DM after 5 years of dietary intervention with a low-fat or Mediterranean diet. Plasma levels of 56 miRNAs were measured by OpenArray. Generalized linear model, receiver operating characteristic (ROC), Cox regression, and pathway analyses were performed. ROC analysis based on clinical variables showed an area under the curve (AUC) of 0.66. After a linear regression analysis, seven miRNAs were identified as the most important variables in the group’s differentiation. The addition of these miRNAs to clinical variables showed an AUC of 0.79. Cox regression analysis using a T2DM remission score including miRNAs showed that high-score patients have a higher probability of T2DM remission (hazard ratio [HR]low versus high, 4.44). Finally, 26 genes involved in 10 pathways were related to the miRNAs. We have identified miRNAs (hsa-let-7b, hsa-miR-101, hsa-miR-130b-3p, hsa-miR-27a, hsa-miR-30a-5p, hsa-miR-375, and hsa-miR-486) that contribute to the prediction of T2DM remission in patients with coronary heart disease., Graphical Abstract, Type 2 diabetes mellitus (T2DM) is one of the most important health problems worldwide, but this disease may revert by the consumption of healthy diets. Our work suggests the use of seven genetic factors (microRNAs) to predict the probability of T2DM remission in patients with coronary heart disease.

Graphical abstract, Highlights • Type 2 diabetes (T2DM) increases the risk of recurrence in myocardial infarction patients. • A gut microbiota profile is associated to the further T2DM development. • Microbiome data improved the prediction of T2DM development when added to clinical parameters. • A risk score including the most predictive genera was associated with the probability of T2DM. • A high risk score was associated with a higher hepatic insulin resistance and β-cell dysfunction., Introduction A distinctive gut microbiome have been linked to type 2 diabetes mellitus (T2DM). Objectives We aimed to evaluate whether gut microbiota composition, in addition to clinical biomarkers, could improve the prediction of new incident cases of diabetes in patients with coronary heart disease. Methods All the patients from the CORDIOPREV (Clinical Trials.gov.Identifier: NCT00924937) study without T2DM at baseline were included (n = 462). Overall, 107 patients developed it after a median of 60 months. The gut microbiota composition was determined by 16S rRNA gene sequencing and predictive models were created using hold-out method. Results A gut microbiota profile associated with T2DM development was determined through a microbiome-based predictive model. The addition of microbiome data to clinical parameters (variables included in FINDRISC risk score and the diabetes risk score of the American Diabetes Association, HDL, triglycerides and HbA1c) improved the prediction increasing the area under the curve from 0.632 to 0.946. Furthermore, a microbiome-based risk score including the ten most discriminant genera, was associated with the probability of develop T2DM. Conclusion These results suggest that a microbiota profile is associated to the T2DM development. An integrate predictive model of microbiome and clinical data that can improve the prediction of T2DM is also proposed, if is validated in independent populations to prevent this disease.

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 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.

Scope The differences between the baseline gut microbiota of patients who developed type 2 diabetes (T2D) consuming a low‐fat (LF) or a Mediterranean (Med) diet are explored and risk scores are developed to predict the individual risk of developing T2D associated with the consumption of LF or Med diet. Methods and Results All the patients from the CORDIOPREV study without T2D at baseline (n = 462) whose fecal sample are available, are included. Gut microbiota is analyzed by 16S sequencing and the risk of T2D after a median follow‐up of 60 months assessed by Cox analysis. Linear discriminant analysis effect size (LEfSe) analysis shows a different baseline gut microbiota in patients who developed T2D consuming LF and Med diets. A higher abundance of Paraprevotella, and lower Gammaproteobacteria and B. uniformis are associated with T2D risk when an LF diet is consumed. In contrast, higher abundances of Saccharibacteria, Betaproteobacteria, and Prevotella are associated with T2D risk when a Med diet is consumed. Conclusion The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of T2D development, which may be used for selecting personalized dietary models to prevent T2D., Agencia de Innovación y Desarrollo de Andalucía. Grant Number: CVI‐7450 Instituto de Salud Carlos III. Grant Numbers: CP14/00114, CPII19/00007, DTS19/00007, FIS PI13/00023, PI16/01777, PI19/00299, PIE 14/00031, PIE14/00005 European Regional Development Fund. Grant Number: na Secretaría de Estado de Investigación, Desarrollo e Innovación. Grant Number: AGL2015‐67896‐P

Summary Background and aim The incidence of type 2 diabetes mellitus (T2DM) has increased worldwide. One of the first actions to reduce the risk of this disease is to implement healthy dietary models; however, no universal dietary strategies have so far been established. In addition, MicroRNAs (miRNAs) are emerging as new biomarkers to predict disease. We aimed to study whether miRNAs could be used to select the nutritional therapy to prevent T2DM development in patients with cardiovascular disease. Methods All patients from the CORDIOPREV study without T2DM at baseline according to the American Diabetes Association (ADA) diagnostic criteria (n = 462) were included in the present study. Of them, after a median dietary intervention period of 60 months with two diets (Low fat or Mediterranean diets), 107 developed T2DM and 355 subjects did not develop the disease. The plasma levels of 24 miRNAs were measured at baseline by qRT-PCR. The risk of T2DM was evaluated by Cox regression analysis based on the plasma levels of the miRNAs at baseline and according to the dietary intervention. Finally, pathways analyses were carried out to identify target genes regulated by the miRNAs studied and cellular processes which could be associated with T2DM development. Results Cox regression analyses showed that patients with low plasma levels of miR-145 at baseline showed a higher risk of developing T2DM after consumption of an LFHCC diet. In addition, patients with low levels of miR-29a, miR-28-3p and miR-126 and high plasma levels of miR-150 at baseline showed a higher risk of developing T2DM after consumption of the Med diet. Finally, pathways analysis showed an interaction of miR-126 and miR-29a in the modulation of FoxO, TNF-α, PI3K-AKT, p53 and mTOR signaling, associated with T2DM development. Conclusion Our results suggest that circulating miRNAs could be used in clinical practice as a new tool for selecting the most suitable diet to prevent type 2 diabetes mellitus development in patients with cardiovascular disease. Clinical trials number NCT00924937.