ABSTRACT BACKGROUND Type 2 diabetes mellitus (T2DM) is currently a major global public health problem. Although disease remission is possible, few biomarkers have been identified which can

help us select the diet that best promotes remission. Our aim was to study the potential of miRNAs as a tool to apply the Mediterranean diet or the low-fat diet in order to achieve T2DM

remission in patients with coronary heart disease. METHODS From the CORDIOPREV study (_n_ = 1002), a prospective, randomized, single-blind, controlled dietary intervention trial, all

patients newly diagnosed with T2DM (_n_ = 190) at baseline were included in the present study. Of these, after adhering to a low fat or Mediterranean diet for 60 months, 73 patients showed

diet. In addition, patients with high levels of _miR-141-5p, miR-182_, and _miR-192_ at baseline showed a high probability of T2DM remission after following the Mediterranean diet. Scores

built using miRNAs and clinical variables showed that high levels of a low-fat diet score and a high Mediterranean diet score were associated with a high probability of T2DM remission.

CONCLUSION MiRNAs could be used as a tool for selecting the most efficient nutritional therapy (mediterranean or low-fat diet) to achieve T2DM remission in patients with coronary heart

disease. SIMILAR CONTENT BEING VIEWED BY OTHERS CIRCULATING MICRORNAS 34A, 122, AND 192 ARE LINKED TO OBESITY-ASSOCIATED INFLAMMATION AND METABOLIC DISEASE IN PEDIATRIC PATIENTS Article Open

access 13 May 2021 EFFECTS OF LUSEOGLIFLOZIN AND VOGLIBOSE ON HIGH-RISK LIPID PROFILES AND INFLAMMATORY MARKERS IN DIABETES PATIENTS WITH HEART FAILURE Article Open access 14 September 2022

LONG-TERM EFFICACY AND SAFETY OF EARLY ALOGLIPTIN INITIATION IN SUBJECTS WITH TYPE 2 DIABETES: AN EXTENSION OF THE SPEAD-A STUDY Article Open access 05 September 2023 INTRODUCTION Type 2

diabetes mellitus (T2DM) is currently one of the major problems for health services worldwide [1]. More than 48 million individuals in the European Union were estimated to have T2DM in 2019,

which represents 9.9% of the population. In addition, diabetes was the direct cause of 1.5 million deaths, and 48% of all deaths due to diabetes occurred before the age of 70 years [2].

Moreover, T2DM is also directly related to the increasing incidence of obesity, considered now as a pandemic [3]. Patients with T2DM undergo deterioration in their quality of life,

increasing the probability of death from cardiovascular disease, compared to healthy subjects [4]. In fact, subjects with a cardiovascular event and T2DM have a higher probability of a new

event than subjects without T2DM [5]. Although the disease involves several metabolic alterations, including dysregulation of glucose homeostasis and lipid metabolism, remission of the

disease is possible. Remission of T2DM is defined as reaching glucose levels below the range that is characteristic of diabetic patients, according to the ADA criteria, for 2 consecutive

years: glycosylated hemoglobin < 6.5%, fasting plasma glucose <126 mg/dL and 2 h plasma glucose after an oral glucose tolerance (OGTT) test <200 mg/dL, and the absence of drug

therapy or surgery [6]. However, the greatest likelihood of success in diabetes remission is due to bariatric surgery [7], and to a lesser extent to physical activity [8] or to diets

involving caloric restriction [9, 10]. In this context, adherence to heart-healthy diets has become a key non-invasive tool to achieve disease remission. However, given the genetic

differences between individuals, there is no universal dietary model applicable to the general population that facilitates T2DM remission. For this reason, genetic or epigenetic markers are

needed to help us choose the dietary model that most favors the remission of the disease. MicroRNAs (miRNAs) are short RNA sequences of 19–22 nucleotides that participate in the regulation

of gene expression, and they are, therefore, directly involved in the development and progression of different diseases [11]. In fact, previous studies by this research group have

demonstrated the potential of miRNAs to predict the development of T2DM [12] and even to select between two healthy diets, a low-fat diet and a Mediterranean model (Med diet), to benefit

patients with coronary heart disease (CHD) and help them remain free of T2DM [13]. In our previous study, we included all the non-T2DM at baseline of the CORDIPOREV study with the aim of

identifying a miRNA profile associated with T2DM according to the diet, in order to select the more suitable diet for preventing T2DM development. In contrast, we now hypothesize that a

miRNAs plasma profile may be associated to T2DM remission in a CORDIOPREV subset of patients with T2DM at baseline of the CORDIPOREV study. Based on these previous observations, our aim was

to study the potential of baseline miRNAs plasma levels as a tool to administer the Mediterranean diet or the low-fat diet to achieve T2DM remission after 5 years of follow-up in

newly-diagnosed T2DM patients with coronary heart disease, who were diagnosed with T2DM when recruited to the CORDIOPREV study. MATERIALS AND METHODS STUDY SUBJECTS This work was conducted

within the framework of the CORDIOPREV study. The rationale, methods, and baseline characteristics have been reported by Delgado-Lista et al. [14, 15] and provided in Clinicaltrials.gov

(NTC00924937). The CORDIOPREV study is an ongoing prospective, randomized, single-blind, controlled dietary intervention trial in 1002 patients with coronary heart disease, at high

cardiovascular risk. The inclusion/exclusion criteria have been described in detail elsewhere [15]. Briefly, the inclusion criteria were: patients with acute coronary syndrome (unstable

angina, acute myocardial infarction) and high-risk chronic CHD according to the following criteria: (A) acute myocardial infarction; (B) unstable angina; and (C) chronic high-risk ischemic

heart disease. The exclusion criteria were: (a) patients <20 years of age or >75 years old, or with a life expectancy <5 years; (b) severe heart failure, NYHA functional class III

or IV, with the exception of self-limited episodes of acute heart failure at the time of the acute ischemic event; (c) severe left ventricular systolic dysfunction (with ejection fraction

≤35%); (d) patients with restricted capacity to follow the protocol: those unable to follow the prescribed diet for whatever reason, due to personal or family circumstances; (e) risk factors

which are severe or difficult to control (such as hypertension and diabetes, where there is organ involvement that limits their survival, chronic renal failure and disabling clinical

manifestations of cerebral atherosclerosis); (f) chronic diseases unrelated to coronary risk; and (g) participants in other studies. The subjects were randomized into two different dietary

models (Mediterranean and low-fat diets) during a median follow-up of 7 years. Written consent was obtained from all the subjects before recruitment and the study protocol and all amendments

were approved by the Ethics Committee of Hospital Reina Sofia, following the Helsinki Declaration and good clinical practices. The present study (CORDIOPREV-DIRECT) included all the newly

diagnosed T2DM patients who had not been receiving glucose-lowering treatment at the beginning of the study (190 out of 1002 patients). Of these, 7 patients were excluded due to their

inability to perform the diagnostic test used in this work. T2DM remission was evaluated in the remaining 183 patients during the 5-year follow-up period. Moreover, 3 participants died

during the follow-up period without achieving diabetes remission. The 183 newly diagnosed T2DM patients were classified as Responders, patients who reverted from T2DM during a median of 60

months of the dietary intervention without the use of diabetes medication (_n_ = 73); or Non-Responders, who did not achieve diabetes remission at the end of the follow-up period (_n_ = 

110). T2DM remission was defined as glycosylated hemoglobin <6.5%, fasting plasma glucose <126 mg/dL and 2 h plasma glucose after an oral glucose tolerance (OGTT) test <200 mg/dL,

for at least 2 consecutive years, and without the use of diabetes medication to lower blood glucose levels [16]. DIET, DIETARY ASSESSMENT, AND FOLLOW-UP VISITS The enrolled patients were

randomized in two different dietary patterns with well-known metabolic health effects: a Med diet rich in fat from olive oil, with 35% of the calories from fat (22% monounsaturated, 6%

polyunsaturated, <10% saturated), and a maximum of 50% carbohydrates and 15% protein; and the low-fat, high-complex carbohydrate diet (LFHCC) recommended by the National Cholesterol

Education Program and the American Heart Association, comprising <30% total fat (<10% saturated fat, 12–14% MUFA fat, and 6–8% PUFA fat), 15% protein, and a minimum of 55%

carbohydrates. The follow-up visits and dietary adherence in the CORDIOPREV study have been reported previously by Quintana-Navarro et al. [17]. During the study, dieticians administered

personalized individual face-to-face interviews at inclusion and every 6 months (Food Frequency Questionnaire (FFQ), Mediterranean Diet Adherence Screener (MEDAS) [18] to assess Med diet

adherence, or used a 9-item dietary screener for the low-fat diet to assess low-fat diet adherence [19], among other variables). Additionally, 2-h group sessions were held every 3–4 months

to reinforce the dietary recommendations and to deliver the resource materials. Finally, a bimonthly telephone follow-up was conducted in order to monitor compliance with the assigned diet,

negotiate nutrition goals, and reinforce the dietary recommendations. Full study diets, dietary assessments, and follow-up visits have been reported previously [15]. BIOCHEMICAL MEASUREMENTS

OF METABOLIC PARAMETERS Venous blood from the participants was collected in tubes containing Ethylenediaminetetraacetic acid (EDTA) as an anticoagulant after a 12-h overnight fast. Lipid

variables (HDL-c, LDL-c, and triglycerides), glucose homeostasis variables (glucose, insulin, and glycosylated hemoglobin (HbA1c)), and inflammatory variables (hs-CRP) were determined, as

previously reported [12]. ORAL GLUCOSE TOLERANCE TEST The oral glucose tolerance test (OGTT) has been reported previously [12, 20]. In summary, patients underwent a standard Matsuda test at

baseline and year-to-year during the follow-up period. After an overnight fast, blood was sampled from a vein before the oral glucose intake (0 min) and again after a 75 g flavored glucose

load (75 g dextrose monohydrate in 250 mL water, NUTER. TEC GLUCOSA 50). Blood samples were taken at 30, 60, 90, and 120 min to determine glucose and insulin concentrations [21]. ISOLATION

OF CIRCULATING MIRNAS FROM PLASMA SAMPLES Venous blood from the 183 newly-diagnosed T2DM patients who had not been receiving glucose-lowering treatment at the beginning of the study was

collected at baseline (day 0 before dietary intervention) in tubes containing EDTA, and centrifuged at 2000×_g_ for 10 min to separate the plasma from the blood cells. RNA isolation was

carried out from plasma samples, as previously described by Jimenez-Lucena et al. [12]. CDNA SYNTHESIS AND CIRCULATING MIRNAS LEVELS USING REAL-TIME PCR The cDNA synthesis was carried out

using the TaqMan MicroRNA Reverse Transcription Kit (Life Technologies—Thermofisher Scientific, Carlsbad, CA, USA), following the manufacturer’s instructions, as previously described in our

group by Jimenez-Lucena et al. [12]. The circulating miRNAs study was carried out on 56 miRNAs, of which our group had previously studied 28 in a population of non-diabetic patients [12,

22]. The remaining 28 miRNAs were selected based on a bibliographic search according to their association with insulin sensitivity, insulin secretion, inflammation, and the growth and

proliferation of beta-cells (Supplementary Table 1). We measured the levels of miRNAs at the baseline of the CORDIOPREV study using the OpenArray® platform (Life Technologies—Thermofisher

Scientific, Carlsbad, CA, USA), following the manufacturer’s instructions. The relative expression data were analyzed using OpenArray® Real-Time qPCR Analysis Software (Life

Technologies—Thermofisher Scientific, Carlsbad, CA, USA) and the normalization method has been described previously [16]. STATISTICS The differences between Responders and Non-Responders in

the study population baseline characteristics were assessed using One-way ANOVA analysis. To analyze the interaction between diet and groups, an analysis of the baseline characteristics of

the participants was carried out using a univariate general linear model. In addition, the 183 patients included in our study were classified according to the tertiles (T1 = low levels, T2 =

 intermediate levels and T3 = high levels) of circulating levels of 45 miRNAs and then COX regression analyses were performed for each miRNA separately for each diet, where T1 was considered

as the reference. We also assessed the hazard ratio (HR) between T3 and T1, with 95% CI. To evaluate the differences in circulating levels of miRNAs between Responders and Non-Responders

according to the diet consumed by the patients, a One-Way ANOVA analysis was performed separately by diet. _p_ Values < 0.05 were considered statistically significant. These analyses were

performed using SPSS software (now PASW Statistic for Windows, version 21) (IBM, Chicago, IL, USA). In addition, clinical variables (BMI, Age, HDL-c, triglycerides) and miRNA data were

transformed (centering and scaling) using the preProcess function from the _caret_ package through the free statistical software “R” version 3.6.1. This function uses two methods for the

normalization and transformation of the variables included in the models. Thus, the method = "center" subtracts the mean of each variable from each absolute value of the variable,

while the method = "scale" divides each value of the variable by its standard deviation. Next, ROC curve analyses were carried out in two steps, first through the glm (General

lineal model) function, which is used to fit generalized linear models and gives a symbolic description of the linear predictor and a description of the error distribution [23]. Next, we

performed the ROC curve using the pROC library. pROC is a tool for visualizing, smoothing, and comparing ROC curves. The AUC can be compared with a statistical test based on U statistics or

bootstrap analysis. After the analysis, we evaluated the AUC, sensitivity, specificity, accuracy and threshold values for each model built. The most significant variables were identified by

Pr(>|_z_|) values < 0.05, registered in the summary of each glm analysis. T2DM SCORES BASED ON MIRNAS ADDED TO CLINICAL VARIABLES In the present study, based on miRNAs and clinical

variables, T2DM remission scores were calculated with the aim of selecting a dietary model (Med or low-fat diets) that promotes disease remission. To this end, we calculated the score in

three steps. First, we performed a glm analysis using the R software, including four miRNAs and six clinical variables, and we assessed the _z_ value of each variable in the summary analysis

separately for both the Med and low-fat diets (Supplementary Tables 2 and 3). Next, we multiplied the _z_ value of each variable by the absolute values of the variables in all the patients

included in the study. Third, the miRNAs and clinical variables were added together to obtain a single score per subject. To evaluate the probability of T2DM remission based on scores, the

183 patients included in our study were classified according to the tertiles of the T2DM remission score for both the Med and low-fat diets (T1, low score; T2, intermediate score; T3, high

score). Using the SPSS software (now PASW Statistic for Windows, version 21) (IBM, Chicago, IL, USA), we performed a Cox regression analysis for each diet assessing the hazard ratio (HR),

with T1 as the reference. OPTIMAL CUT-OFF POINTS FOR T2DM REMISSION SCORE BY DIET To identify the cut-off points that allow us to select a dietary model that promotes remission using the

scores, a ROC analysis was initially carried out. Next, we obtained the coordinates of the curve for each score (T2DM remission score for the low-fat diet and T2DM remission score for the

Mediterranean diet). After that, the Youden index was calculated according to the equation (sensitivity + specificity) − 1 [24]. The Youden index was then plotted against the score values

for both the Med and low-fat diets. We identified the maximum value of the Youden index with its respective score value, which was considered as the cut-off point. RESULTS BASELINE

CHARACTERISTICS OF PATIENTS ACCORDING TO THE DIET The baseline characteristics of the study population have been previously published [16, 25]. In summary, patients who did not achieve

diabetes remission at the end of the follow-up period (Non-Responders) showed higher weight, BMI, waist circumference, HbA1c, fasting glucose, insulin and HOMA-IR than patients who reverted

from T2DM during a median of 60 months of dietary intervention (Responders) (Supplementary Table 4). According to diet, we observed significant differences between the two diets in relation

to systolic blood pressure (_p_ diet vs group = 0.007). No significant differences were observed in the diet _vs_ group interaction in the other baseline characteristics (Table 1). COX

REGRESSION ANALYSIS Of the 56 miRNAs selected for the study, 9 did not amplify in at least 80% of the samples and 2 (_hsa-miR-143_ and _hsa-miR-144_) were used for data normalization, as

previously described by our group [12, 22]. In order to test the potential relationship between miRNA levels and T2DM remission associated with the consumption of a specific diet, we

performed a Cox regression analysis for each miRNA of the remaining 45 included in the panel. We found that low baseline plasma levels of _miR-let7b-3p_ were associated with a higher

probability of T2DM remission when the low-fat diet was consumed, but no association between _miR-let7b-3p_ plasma levels and T2DM remission was found when patients consumed the Med diet. In

addition, high baseline plasma levels of _miR-141-5p_, _miR-182_, and _miR-192_ were linked to a higher probability of T2DM remission when the Med diet was consumed, while no association

was observed when patients consumed the low-fat diet (Fig. 1) (Supplementary Table 5). RECEIVER OPERATING CHARACTERISTIC CURVE ANALYSIS To evaluate the potential of miRNAs plasma levels as a

tool to select the most suitable dietary pattern for inducing T2DM remission, ROC curve analyses were performed separately by diet. A model was built including patients who followed a

low-fat diet with the clinical parameters (age, gender, HDL-c, triglycerides, BMI and intensity of statins treatment), showing an AUC = 0.695 (95% CI = 0.592–0.798) (Fig. 2A), which

increased to AUC = 0.767 (95% CI = 0.673-0.861) by adding the plasma levels of _miR-let7b-3p_ (Fig. 2B) (Supplementary Table 6). In addition, a model built with the clinical parameters

including patients who followed the Med diet showed an AUC = 0.750 (95% CI = 0.641–0.859) (Fig. 2C), which increased to an AUC = 0.803 (95% CI = 0.707–0.899) by adding the miRNAs

_miR-141-5p_, _miR-182_, _miR-192_ to the clinical parameters (Fig. 2D) (Supplementary Table 6). T2DM REMISSION SCORES A score built with the clinical parameters (age, gender, BMI, HDL-c,

triglycerides, intensity of statin treatment) and _miR-let7b-3p_ was associated with T2DM remission after the consumption of the low-fat diet. Thus, patients who consumed the low-fat diet

were categorized by tertiles of the T2DM remission score and a COX regression analysis was performed using tertile 1 (T1) as the reference. We observed that patients with high scores showed

a higher probability of T2DM remission when consuming the low-fat diet (HR low vs high = 3.90 (95% CI: 1.562–9.725)) (Fig. 3A). In contrast, no statistically significant associations were

observed when this score was applied to patients who consumed the Med diet (Supplementary Fig. 1). Furthermore, a score including the clinical parameters and _miR-141-5p_, _miR-182_ and

_miR-192_ was associated by COX regression analysis to T2DM remission in the patients who consumed the Med diet. We observed that patients with high scores showed a higher probability of

T2DM remission when consuming the Med diet (HR low vs high: 11.84 (95% CI: 2.728–51.392)) (Fig. 3B). In contrast, no statistically significant associations were observed when this score was

applied to patients who consumed the low-fat diet (Supplementary Fig. 1). OPTIMAL CUT-OFF POINTS FOR T2DM REMISSION SCORES To identify the cut-off points for T2DM remission scores, we first

calculated the Youden index for the ROC curves obtained with both the Med and low-fat scores. We then plotted the values of each score against the values of the Youden index, selecting the

highest value of the index with the corresponding score value. Thus, the optimal cut-off point for the T2DM remission score was 4.22 for the low-fat diet, and −5.04 for the Med diet (Fig.

4). DISCUSSION Our study suggests the potential of circulating levels of specific miRNAs for selecting a specific dietary pattern to achieve type 2 diabetes mellitus (T2DM) remission in

patients with coronary heart disease. In the study, we showed that a low baseline plasma level of _miR-let7b-3p_ was associated with T2DM remission when a low-fat diet was consumed.

Conversely, high baseline plasma levels of _miR-141-5p_, _miR-182_, and _miR-192_ were associated with T2DM remission when consuming the Med diet. The increasing incidence of obesity has led

to an increase in the incidence of metabolic diseases such as T2DM, making it one of the leading causes of death in the world [26]. Moreover, subjects with a cardiovascular event and T2DM

have a higher probability of a new event than those subjects without T2DM [5]. For this reason, efforts have been focused on achieving T2DM disease remission, which is defined as achieving

normal glucose levels without pharmacological treatment [6]. However, to date, this goal has been achieved mainly with invasive methods such as bariatric surgery [27], physical activity [8],

or dietary interventions focused on caloric restriction [9, 10]. In line with this, diabetes remission can also be achieved by the consumption of healthy dietary models such as the

Mediterranean diet or the low-fat diet [28, 29]. However, given the genetic and epigenetic differences of the population, these dietary models should not be generalized to the whole

population and it is important to identify markers to select the dietary model which the patient will benefit most from in order to achieve T2DM remission [30, 31]. Currently, miRNAs are

recognized as important regulators of gene expression and central players in the control of several biological and pathological processes associated with diseases such as T2DM [32].

Additionally, previous studies have demonstrated the association between the dietary components, such as polyphenols, micronutrients, macronutrients, phytochemicals and the expression of

miRNAs [33]. Other studies have demonstrated differences in miRNA levels at different timepoints after bariatric surgery. Indeed, a meta-analysis identified previous studies in humans with

post-surgery times ranging from 3 to 24 months, in which deregulation of miRNA diversity was demonstrated [34], suggesting a dynamic change between diabetes remission and miRNA plasma

levels. In our study, we explored the capacity of miRNAs to predict diabetes remission according to the diet consumed by analyzing baseline plasma levels. We found that ROC curve analyses

showed an AUC = 0.767 when _miR-let7b-3p_ are added to the clinical parameters for the low-fat diet, whereas an AUC = 0.803 was observed after the addition of _miR-141-5p_, _miR-182_,

_miR-192_ to the clinical parameters for the Med diet. Previous studies have demonstrated the differential expression of _miR-let7b-5p_ among healthy people, subjects with T2DM, and T2DM and

diabetic retinopathy [35]. It has also been demonstrated in animal models that _miR-let-7b-5p_ not only upregulated the mt-Cytb gene in mitochondria, but also downregulated insulin receptor

substrate 1 in cytosol in db/db mice [36]. However, few studies have addressed the mechanistic role of _miR-let7b-3p_ in the development or remission of T2DM. In relation to _miR-141-5p_, a

previous study showed that elevated levels of this miRNA were associated with increased beta-cell apoptosis [37]. In turn, previous studies in animal models showed that _miR-182_

participates in glucose homeostasis by regulating the _FOXO1_ and _PDK4_ genes, decreasing blood glucose levels [38]. Finally, _miR-192_ has been reported as being upregulated in diabetic

patients and patients with diabetic nephropathy [39]. However, the overall information about gene expression and/or modulation by diet of these miRNAs is scarce, and even more so in the

context of T2DM. In addition, future studies are needed to investigate the interaction of dietary components and gene expression, which may determine the effect of a specific diet on T2DM

remission, or on global health. Furthermore, several scores have been developed to predict T2DM development, including the PREDIMED-Clinical score (in patients with high cardiovascular

disease) [40], the discrimination of Finnish Diabetes Risk Score (FINDRISC) [41], and the German Diabetes Risk Score (GDRS) [42], in addition to the DiaREM score for T2DM remission [43].

However, such scores do not evaluate remission or help to select the most suitable diet to prevent diabetes development. A previous study performed by our group demonstrated that miRNAs

could be used to select the most suitable dietary pattern to prevent T2DM development [13]. This previous study focused exclusively on the non-T2DM patients at the beginning of the

CORDIOPREV study, of whom some developed T2DM during the follow-up period. In other words, we studied T2DM incidence, but we did not build an epigenetic score based on miRNAs and clinical

variables as we have done in the current work for T2DM remission. Along these lines, in another study, we demonstrated the use of a clinical-epigenetic score to predict disease remission

[16]. In the current work, we have demonstrated that miRNA plasma levels could be used to predict the most suitable diet to induce T2DM remission by building specific clinical-epigenetic

scores for the low-fat and a Med diet. Our study proposes, for the first time, the use of diet-specific clinic-epigenetic scores (Low-Fat score and Med score) to select the dietary pattern

that patients with CHD and T2DM should follow to achieve T2DM remission more efficiently. Nevertheless, our study has some limitations; firstly, we conducted a targeted study on 28 miRNAs

with previously published knowledge, which means that other miRNAs that might be of interest but are not published were not included. Secondly, our study was conducted in patients with

cardiovascular disease, which limits the extrapolation of the results to a healthy population. In conclusion, our results indicate that miRNAs could be applied as a clinical tool to select

the most efficient nutritional therapy (Mediterranean or low-fat diet) to achieve T2DM remission in patients with coronary heart disease. DATA AVAILABILITY Collaborations with the CORDIOPREV

Study are open to Biomedical Institutions, always after an accepted proposal for a scientific work. Depending on the nature of the collaboration, electronic data, hard copy data, or

biological samples should be provided. All collaborations will be made after a collaboration agreement. Terms of the collaboration agreement will be specific for each collaboration, and the

extent of the shared documentation (i.e., deidentified participant data, data dictionary, biological samples, hard copy, or other specified data sets) will be also specifically set on the

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procedures in Hispanic and non-Hispanic white patients. Obes Surg. 2018;28:61–8. Article  CAS  PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS We would like to express our

gratitude to all the subjects who participated in the study, and the Córdoba branch of the Biobank of the Sistema Sanitario Público de Andalucía (Andalusia, Spain) for providing the human

biological samples. We would also like to thank the EASP (Escuela Andaluza de Salud Publica), Granada, Spain, which performed the randomization process for this study. The CORDIOPREV study

is supported by the Fundación Patrimonio Comunal Olivarero, Junta de Andalucía (Consejería de Salud, Consejería de Agricultura y Pesca, Consejería de Innovación, Ciencia y Empresa),

Diputaciones de Jaén y Córdoba, Centro de Excelencia en Investigación sobre Aceite de Oliva y Salud and Ministerio de Medio Ambiente, Medio Rural y Marino, Gobierno de España; Ministerio de

Economía y Competitividad (AGL2012/39615, PIE14/00005, and PIE 14/00031 to JL-M; AGL2015-67896-P to JL-M and AC); Consejería de Innovación, Ciencia y Empresa, Proyectos de Investigación de

Excelencia, Junta de Andalucía (CVI-7450 to JL-M); and by the Fondo Europeo de Desarrollo Regional (FEDER), JPI HDHL-NutriCog (PCIN-2016-084 to JL-M). The CIBEROBN is an initiative of the

Instituto de Salud Carlos III, Madrid, Spain. Oriol Alberto Rangel Zúñiga and Antonio Camargo are supported by an ISCIII research contract (Programa Miguel-Servet CP19/00142 and CP14/00114,

respectively, funded by Instituto de Salud Carlos III, and co-funded by the Fondo Social Europeo “_El FSE invierte en tu futuro_”). JMO is supported by the US Department of Agriculture,

under agreement No. 8050-51000-098-00D. Thanks also go to Jose Andres Morales Martinez and Rosario Carreras for providing technical assistance. AUTHOR INFORMATION Author notes * These

authors contributed equally: Juan Francisco Alcala-Diaz, Antonio Camargo. * These authors jointly supervised this work: Oriol Alberto Rangel-Zuñiga, Jose Lopez-Miranda. AUTHORS AND

AFFILIATIONS * Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004, Córdoba, Spain Juan Francisco Alcala-Diaz, Antonio Camargo, Cristina

Vals-Delgado, Ana Leon-Acuña, Helena Garcia-Fernandez, Antonio P. Arenas-de Larriva, Magdalena Perez-Cardelo, Marina Mora-Ortiz, Pablo Perez-Martinez, Javier Delgado-Lista, Oriol Alberto

Rangel-Zuñiga & Jose Lopez-Miranda * Department of Medical and Surgical Sciences, University of Córdoba, 14004, Córdoba, Spain Juan Francisco Alcala-Diaz, Antonio Camargo, Cristina

Vals-Delgado, Ana Leon-Acuña, Helena Garcia-Fernandez, Antonio P. Arenas-de Larriva, Magdalena Perez-Cardelo, Marina Mora-Ortiz, Pablo Perez-Martinez, Javier Delgado-Lista, Oriol Alberto

Rangel-Zuñiga & Jose Lopez-Miranda * Maimónides Biomedical Research Institute of Córdoba (IMIBIC), Córdoba, Spain Juan Francisco Alcala-Diaz, Antonio Camargo, Cristina Vals-Delgado, Ana

Leon-Acuña, Helena Garcia-Fernandez, Antonio P. Arenas-de Larriva, Magdalena Perez-Cardelo, Marina Mora-Ortiz, Pablo Perez-Martinez, Javier Delgado-Lista, Maria Del Mar Malagon, Oriol

Alberto Rangel-Zuñiga & Jose Lopez-Miranda * CIBER Fisiopatologia de la Obesidad y la Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain Juan Francisco

Alcala-Diaz, Antonio Camargo, Cristina Vals-Delgado, Ana Leon-Acuña, Antonio P. Arenas-de Larriva, Pablo Perez-Martinez, Javier Delgado-Lista, Maria Del Mar Malagon, Jose M. Ordovas, Oriol

Alberto Rangel-Zuñiga & Jose Lopez-Miranda * Department of Cell Biology, Physiology and Immunology, University of Córdoba, 14004, Córdoba, Spain Maria Del Mar Malagon * Nutrition and

Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, 0211, USA Jose M. Ordovas * Centro Nacional de

Investigaciones Cardiovasculares, 28029, Madrid, Spain Jose M. Ordovas * IMDEA Food Institute, CEI UAM + CSIC, 28049, Madrid, Spain Jose M. Ordovas Authors * Juan Francisco Alcala-Diaz View

author publications You can also search for this author inPubMed Google Scholar * Antonio Camargo View author publications You can also search for this author inPubMed Google Scholar *

Cristina Vals-Delgado View author publications You can also search for this author inPubMed Google Scholar * Ana Leon-Acuña View author publications You can also search for this author

inPubMed Google Scholar * Helena Garcia-Fernandez View author publications You can also search for this author inPubMed Google Scholar * Antonio P. Arenas-de Larriva View author publications

You can also search for this author inPubMed Google Scholar * Magdalena Perez-Cardelo View author publications You can also search for this author inPubMed Google Scholar * Marina

Mora-Ortiz View author publications You can also search for this author inPubMed Google Scholar * Pablo Perez-Martinez View author publications You can also search for this author inPubMed 

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CONTRIBUTIONS Conception and design of the experiments: JFA-D, AC, CV-D, OAR-Z, and JL-M; recruitment and nutritional control of the volunteers: JFA-D, AL-A, APA-L, PP-M, JD-L, and JL-M;

experiments and data collection: JFA-D, AC, CV-D, HG-F and OAR-Z; data analysis and interpretation: AC, CV-D, MP-C, MM-O, OAR-Z, and JL-M; writing the paper: AC, OAR-Z and JL-M; study

conception and design: PP-M, JD-L and JL-M; critical revision of the paper for important intellectual content: MDM, JMO and JL-M; integrity of the data and the accuracy of the data analysis:

JFA-D, AC, PP-M, JD-L, OAR-Z and JL-M. All the authors were involved in writing the paper and gave their final approval to the submitted and published versions. CORRESPONDING AUTHOR

Correspondence to Jose Lopez-Miranda. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains

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licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Alcala-Diaz, J.F., Camargo, A., Vals-Delgado, C. _et al._

MiRNAs as biomarkers of nutritional therapy to achieve T2DM remission in patients with coronary heart disease: from the CORDIOPREV study. _Nutr. Diabetes_ 15, 7 (2025).

https://doi.org/10.1038/s41387-025-00362-1 Download citation * Received: 28 August 2023 * Revised: 22 January 2025 * Accepted: 31 January 2025 * Published: 22 February 2025 * DOI:

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