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Telomere length as biomarker of nutritional therapy for prevention of type 2 diabetes mellitus development in patients with coronary heart disease: CORDIOPREV randomised controlled trial

Cardiovascular Diabetology volume 23, Article number: 98 (2024) Cite this article

Abstract

Background

Telomere Length (TL), a marker of cellular aging, holds promise as a biomarker to elucidate the molecular mechanism of diabetes. This study aimed to investigate whether shorter telomeres are associated with a higher risk of type 2 diabetes mellitus (T2DM) incidence in patients with coronary heart disease; and to determine whether the most suitable dietary patterns, particularly a Mediterranean diet or a low-fat diet, can mitigate the development of diabetes in these patients after a follow-up period of five years.

Methods

The CORonary Diet Intervention with Olive oil and cardiovascular PREVention study (CORDIOPREV study) was a single-centre, randomised clinical trial done at the Reina Sofia University Hospital in Córdoba, Spain. Patients with established coronary heart disease (aged 20–75 years) were randomly assigned in a 1:1 ratio by the Andalusian School of Public Health to receive two healthy diets. Clinical investigators were masked to treatment assignment; participants were not. Quantitative-PCR was used to assess TL measurements.

Findings

1002 patients (59.5 ± 8.7 years and 82.5% men) were enrolled into Mediterranean diet (n = 502) or a low-fat diet (n = 500) groups. In this analysis, we included all 462 patients who did not have T2DM at baseline. Among them, 107 patients developed T2DM after a median of 60 months. Cox regression analyses showed that patients at risk of short telomeres (TL < percentile 20th) are more likely to experience T2DM than those at no risk of short telomeres (HR 1.65, p-value 0.023). In terms of diet, patients at high risk of short telomeres had a higher risk of T2DM incidence after consuming a low-fat diet compared to patients at no risk of short telomeres (HR 2.43, 95CI% 1.26 to 4.69, p-value 0.008), while no differences were observed in the Mediterranean diet group.

Conclusion

Patients with shorter TL presented a higher risk of developing T2DM. This association could be mitigated with a specific dietary pattern, in our case a Mediterranean diet, to prevent T2DM in patients with coronary heart disease.

Trial Registration

Clinicaltrials.gov number NCT00924937.

Introduction

The growing prevalence of type 2 diabetes mellitus (T2DM) as well as cardiovascular disease (CVD) represents a significant global public health challenge. Notably, coronary heart disease (CHD) is as a major cause of death and disability worldwide [1]. The relationship between T2DM and CHD is well-established, and patients with both diseases may have poorer prognosis, experiencing increased complications and a higher risk of adverse cardiovascular events. The pathophysiological mechanisms underlying T2DM, characterized by insulin resistance and impaired beta-cell function, exert detrimental effects on CHD outcomes, contributing to the progression of atherosclerosis, impaired blood flow regulation and increased inflammatory status [2].

Prevention through lifestyle is the cornerstone of reducing the risk of developing T2DM, especially by increasing physical activity levels and improving diet quality [3]. In this context, determining promising biomarkers to identify individuals at high risk of developing T2DM as well as to assess the efficacy of targeted interventions for prevention is of paramount importance.

Over the last decade, telomere length (TL) has emerged as a potential biomarker to understand the molecular processes that underlie diabetes [4]. Telomeres are repetitive nucleotide sequences (5’ – TTAGGG – 3’) at the end of chromosomes, which provide stability and protection of genetic material. In each cell division, a small telomeric DNA fragment is lost due to the inability of telomerase activity in most cells. In addition, the high guanine content of telomeres makes them susceptible to reactive oxygen species, commonly generating 8-oxoguanine [5]. Consequently, TL naturally reaches a critical size, which can be expedited by a variety of intrinsic and environmental factors through the upregulation of oxidative stress levels [6]. In this sense, TL is often considered a biomarker for cellular aging, and has been associated with increased risk of several diseases, such as CVD [7], obesity [8], diabetes [9,10,11], and cancer [12]. Emerging studies have suggested that cellular aging reflected by TL could be related to the development of T2DM, marked by elevated levels of oxidative stress induced by hyperglycaemia [4]. Despite these findings, the absence of interventional studies assessing how specific dietary approaches could influence the association between TL and the risk of T2DM incidence, especially in the context of secondary cardiovascular prevention, means that this possible association remains unclear.

Based on this, our study aims to assess whether shorter telomeres is associated with a greater risk of T2DM incidence in patients with CHD. Additionally, we aim to determine whether the most suitable dietary patterns, particularly a Mediterranean diet rich in extra virgin olive oil, or a low-fat diet rich in complex carbohydrates, can mitigate the development of diabetes in these patients after a follow-up period of five years.

Materials and methods

Study population

The present study was carried out as part of the CORDIOPREV study, which stands for the CORonary Diet Intervention with Olive oil and cardiovascular PREVention study (Clinicaltrials.gov number NCT00924937). This research was conducted at Reina Sofia University Hospital in Córdoba, Spain. The study design involved a single centre, randomized, single-blind, and controlled dietary intervention. A total of 1002 patients with CHD were included, and detailed information regarding the rationale, study methods, inclusion and exclusion criteria, cardiovascular risk factors, and baseline characteristics of the patients have been published recently [13]. In brief, eligible patients included men and women between the ages of 20 and 75 years, who had established CHD, were free of clinical coronary events in the previous six months, were able to follow a long-term dietary intervention, and had no severe illnesses or an expected life expectancy lower than the length of the study. The upper age limit was set based on the life expectancy at the conception of the trial (2007) and it was in line with the usual practice in contemporary long-term cardiovascular studies.

Informed written consent was obtained from all participants prior to their inclusion in the study. The study protocol received approval from the Human Investigation Review Committee at Reina Sofia University Hospital, following the institutional and Good Clinical Practice guidelines.

The primary objective of the CORDIOPREV study is to evaluate the efficacy of a Mediterranean diet as compared with a low-fat diet to prevent clinical events and mortality in patients with previous CHD through a long-term follow-up study. Here, we report the results of one secondary outcome of the CORDIOPREV study: T2DM incidence. In this work, we included 462 out of 1002 patients who had not been diagnosed with T2DM at the study’s outset. Of these Non-T2DM patients at baseline, 107 patients developed T2DM (Incident-T2DM) according to the American Diabetes Association (ADA) diagnostic criteria [14], after a median follow-up of 60 months. In this study, 19 patients were excluded because we did not have their TL data; thus, the final sample consisted of 338 Non-T2DM and 105 Incident-T2DM (Additional Fig. 1). Every year, T2DM incidence was assessed according to the ADA T2DM criteria: fasting plasma glucose ≥ 126 mg/dL or 2 h plasma glucose in the 75 g oral glucose tolerance test ≥ 200 mg/dL or glycosylated haemoglobin (HbA1c) levels ≥ 6.5%. In the absence of unequivocal hyperglycaemia, diagnosis requires two abnormal test results from the same sample or in two separate test samples [14].

The sample size and the power calculation of this sub-study were calculated based on of the following assumptions: a T2DM incidence rate in the Mediterranean diet group of 10%, and 17% in the low-fat group and a statistical power of 80%, with α of two tails = 0.05. With these assumptions and assuming a 10% of estimated loss, the necessary sample size was established from 163 patients in each of the dietary intervention groups. In the present work, all the subjects who had not been clinically diagnosed with T2DM at baseline were included (n = 462; 216 Low-fat Diet and 246 Mediterranean Diet). Of this group, all 107 subjects who development T2DM were included (42 Low-fat Diet and 65 Mediterranean Diet). The remaining 355 subjects were not diagnosed of T2DM (174 Low-fat Diet and 181 Mediterranean Diet) (Additional Fig. 1).

Randomisation and masking

Randomisation was performed by the Andalusian School of Public Health (1:1 ratio). The dietitians were the only members of the intervention team to know about each participant’s dietary group. Briefly, the randomisation was based on the following variables: sex (male, female), age (< 60 and ≥ 60 years old) and previous myocardial infarction (yes, no). Details about randomisation have been previously reported and summarized [15].

Dietary intervention

Patients were randomized to receive one of two different healthy dietary models: (1) a Mediterranean diet, with a minimum 35% of calories from fat (22% monounsaturated, 6% polyunsaturated and < 10% saturated fatty acids), 15% proteins and a maximum of 50% carbohydrates, and (2) a low-fat diet recommended by the National Cholesterol Education Program, with < 30% of total fat (12–14% monounsaturated, 6–8% polyunsaturated and < 10% saturated fatty acids), 15% proteins and a minimum of 55% carbohydrates. In both diets, the cholesterol content was adjusted to < 300 mg/day. The present study was conducted over a follow-up period of five years. Details about diets have been previously reported and summarized [15].

Patients underwent individual face-to-face interviews with a nutritionist at baseline and annually to complete a 137-item semiquantitative food frequency questionnaire, previously validated in Spain [16]. Each year, the 14-item MEditerranean Diet Adherence Screener [17] was used to measure adherence to the Mediterranean diet and a 9-item dietary screener was used to evaluate adherence to the low-fat diet. In addition, both intervention groups received identical intensive dietary counselling. Nutritionist-conducted personalized one-on-on interviews at baseline and every six months. Furthermore, quarterly educational collectively sessions were held with up 20 participants per session and separate sessions for each group.

Laboratory measurements

After a 12-h overnight fast at the beginning of the study and once a year during the follow-up period, venous blood samples were collected from the participants in EDTA tubes (final concentration of 0.1% EDTA) and plasma was separated from the red cells by centrifugation at 1500 × g for 15 min at 4 °C and immediately frozen at − 80 °C. The biochemical measurements were performed at the Reina Sofia University Hospital by personal who were blinded to the interventions. Lipid variables were assessed with a DDPPII Hitachi modular analyser (Roche, Basel, Switzerland) using specific reagents (Boehringer-Mannheim, Mannheim, Germany). Plasma triglycerides and cholesterol concentrations were assayed by enzymatic procedures. High-density lipoprotein-cholesterol (HDL-c) were measured following precipitation of a plasma aliquot with dextran sulfate-Mg2+. Low-density lipoprotein-cholesterol (LDL-c) concentration was calculated by the Friedewald equation, using the following formula: LDL-c = Total Cholesterol − (HDL-c + Triglycerides/ 5). Glucose measurements were performed by the hexokinase method. High sensitive C-Reactive Protein (hs-CRP) was determined by ELISA techniques (BioCheck, Inc., Foster City, CA, USA).

DNA isolation from blood samples

DNA was isolated from buffy coat fraction through the salting-out method [18], using 10 mL of Montreal-Baltimore buffer (0.32 M sucrose, 0.1 mM Tris-HCl, pH 7.5, 0.025 mM MgCl2, 1% Triton X-100) and mixing and centrifuging to separate the nuclear fraction. The nucleic pellet was homogenized with 3 mL of nuclei lysis buffer (10 mM Tris-HCl, pH 8.2, 2 mM EDTA, 0.4 M NaCl) and 10% SDS and proteinase K. The DNA was precipitated with 6 M NaCl and washed with 100% ethanol. Finally, the genomic DNA was extracted and resuspended in 500 µL of 1× TE buffer. DNA purity and concentration were evaluated by spectrophotometry using NanoDrop ND-2000 (ThermoFisher, Waltham, MA).

Quantitative PCR analysis of TL

TL was determined using the Cawthon method by qPCR [19]. For all samples, we estimated the relative ratio of telomere repeat copy number (T) normalized against a single copy gene, the homo sapiens ribosomal protein L13a gene RPL13a (S). Results for each PCR were relativized to a standard curve, built using a reference DNA sample. The standard curves for telomere and RPL13a gene PCR consisted of eight DNA reference standards (1–25ng). All PCRs were performed with the use of iQ5-BIORAD thermal cycler and SensiFAST SYBR Lo-ROX kit (Bioline). The coefficient of variation (%CV) was 9.32% for the telomere repeat copy number and 6.76% for the single copy gene copy number. The thermal cycler profile for both amplicons began with 95 °C incubation for 3 min to activate the polymerase, followed by 40 cycles of 95 °C for 5 s, 54 °C for 15 s. The reaction mix composition was identical except for the oligonucleotide primers: 20-ng template DNA, 1× SensiFAST SYBR Lo-ROX, 200-nM reverse primer, and 200-nM forward primer. The final volume for each PCR reaction was 20 µL. The primer sequences were (5′→ 3′):

TeloFw, CGGTTTGTTTGGGTTTGGGTTT GGGTTTGGGTTTGGGTT; TeloRw, GGCTTGCCTTACCC TTACCCTTACCCTTACCCTTACCCT; RPL13aFw, CCTGGAGGAGAAGAGGAAAGAGA; RPL13aRw, TTGAGGACCTCTGTGTATTTGTCAA.

DNA extraction and TL measurements were performed at baseline and at the 4-year time point. While assessing TL at additional time points could provide further valuable insights, we did not observe statistically significant changes in TL at 4-year time point within our study. In this work, we evaluate the role of TL at baseline as a marker for identifying individuals at risk of short TL (TL < percentile 20th).

Statistical analyses

The statistical analyses were performed with STATA 14 (STATA Corp., TX, USA). We used the mean and standard error of the mean (mean ± SEM) for continuous variables, and percentages for categorical variables. All p-values were 2-tailed, and a p < 0.05 was considered statistically significant.

The definition of the shortest TL, rather than the average TL, is associated with telomere dysfunction and cellular survival limitation [20, 21]. In this way, patients were classified according to the risk of short TL at baseline, defined as a TL below the 20th percentile and no risk as a TL above the 20th percentile, as it was previously reported [22,23,24].

Student’s unpaired was used for comparison between groups. Categorical variables were compared using Chi-Square tests. We used Fisher’s exact test to evaluate the relationship between participant’s T2DM incidence and risk of short TL. Mosaic plots have been applied to show the relationship between T2DM incidence and the risk of short TL, in which height of bars represents proportions of participants with high or low risk of short telomere, and the width of each bar is proportional to T2DM incidence. Logistic regression model was run to assess the risk of T2DM incidence according to the risk of short telomere. We used the Cox proportional hazards regression to test the potential predictive value of TL and the potential role of TL to select dietary model to decrease the risk of developing diabetes. In addition, we conducted statistical analysis to assess the interaction by diet group and risk of short TL in the Cox regression model. The regression analyses were adjusted by age, gender, body mass index (BMI), waist circumference (WC), HbA1c, HDL-c,triglycerides and family history of both diabetes and early coronary heart disease. As additional analyses, receiver operating characteristic curve (ROC) analysis was run for assessing the potential for TL to classify the population in Incident-T2DM and Non-T2DM patients. We performed two models: the first based on clinical variables (BMI, age, gender, triglycerides and statins use), the second model with added TL.

Results

Baseline characteristics of the participants

Baseline body weight, BMI, WC, HbA1c, fasting glucose, and insulin levels were higher in the Incident-T2DM patients than in Non-T2DM patients (all p < 0.05) (Additional Table 1). Baseline characteristics of the patients classified according to the risk of short telomeres (< 20th percentile) are showed in Table 1. Similar differences were found between Incident-T2DM and Non-T2DM patients with no risk of short telomeres with higher baseline BMI, WC, HbA1, glucose, and insulin levels in Incident-T2DM patients compared to Non-T2DM patients (all p < 0.05). However, in patients at risk of short telomeres, Incident-T2DM patients showed lower HDL-c levels, and higher HbA1 and fasting glucose levels than Non-T2DM patients (all p < 0.05) (Table 1).

Table 1 Baseline characteristics of the participants according to the risk of short telomeres
Full size table

Association between risk of short telomeres and T2DM incidence

We evaluated the association between short telomeres and T2DM incidence (Fig. 1) through the percentage of patients at risk of having short telomeres in a mosaic plot applying the Fisher’s exact test (Fig. 1A), and the logistic association (Fig. 1B). We found a higher percentage of patients at risk of short telomeres in the group of Incident-T2DM patients in comparison with the group of Non-T2DM patients (27% vs. 17%, respectively, p-value 0.038), being the odds ratio 1.86 (95% CI 1.05 to 3.25, p-value 0.036).

Fig. 1
figure 1

Association between risk of short telomeres and T2DM incidence. Participant frequency (A) and Odds Ratio (B) of T2DM incidence according to the risk of short telomeres. Mosaic plots: Height of bars represents proportions of participants at risk or no risk of short telomere, the width of each bar is proportional to T2DM incidence. The analysis were performed applying the Fisher’s exact test (A) and logistic association, Odds ratios and 95% confident intervals of T2DM incidence adjusted by age, gender BMI, WC, HbA1c, triglycerides, HDL-c and family history of both diabetes and early coronary heart disease (B)

Full size image

The risk of T2DM incidence according to telomeres

The risk of T2DM incidence depending on the risk of short telomeres during dietary intervention was estimated using a Kaplan-Meier survival curve (Fig. 2). We observed that patients at risk of short telomeres had a higher incidence of T2DM than those at no risk of short telomeres, with a hazard ratio (HR) of 1.65 (95% CI 1.07 to 2.54, p-value 0.023, Fig. 2A). Significant interaction of diet versus risk of short telomeres was observed (p-value 0.048). Patients at high risk of short telomeres who consumed a low-fat diet had a higher risk of T2DM incidence compared to patients at no risk of short telomeres (HR 2.43, 95CI% 1.26 to 4.69, p-value 0.008) (Fig. 2B), while no differences were observed between patients at risk and those at no risk of short telomeres who consumed a Mediterranean diet (HR 1.23, 95CI% 0.69 to 2.20, p-value 0.478) (Fig. 2C). In addition, we performed a ROC curves analysis to evaluate the potential for TL to classify the patients in Incident-T2DM and Non-T2DM. First, based on the classic predictors of T2DM remission (i.e., BMI, age, gender, triglycerides and statins use), we observed an area under the curve (AUC) of 0.62 (95% CI, 0.56–0.69) (Additional Fig. 2A). To improve this model with our key variable, we carried out the ROC curve analysis added telomere length. Our results showed an AUC of 0.66 (95% CI, 0.60–0.72) (Additional Fig. 2B). The two models were significantly different (p = 0.027) through a DeLong Test.

Fig. 2
figure 2

Risk of T2DM incidence by the risk of short telomeres. In the whole population (A) and in patients who consumed low fat diet (B) or Mediterranean Diet (C) The analysis was performed using a Cox regression curve by risk of short TL and adjusted by age, gender BMI, WC, HbA1c, triglycerides,HDL-c and family history of both diabetes and early coronary heart disease. Red line indicates risk of short telomeres and green line indicates no risk of short telomeres

Full size image

Discussion

Our study showed that CHD patients at risk of short telomeres had a higher risk of T2DM development than those at no risk of short telomeres. Additionally, the risk of T2DM associated with shortened telomeres was mitigated by a Mediterranean diet. Indeed, patients with risk of short telomeres at baseline showed a higher risk of developing T2DM when consuming a low-fat diet compared to patients at no risk of short telomere, while no differences were found in those patients who consumed a Mediterranean diet.

Previous research has extensively explored the link between TL and the risk, onset, and progression of T2DM. Case-control studies have shown that patients with T2DM tend to have shorter TL compared to non-diabetic subjects [25, 26]. In our study, we observed a higher percentage of patients at risk of short telomeres (< 20th percentile) among Incident-T2DM patients compared to Non-T2DM patients, with an 84% higher risk of developing T2DM in those subjects having shortened TL. Similarly, large longitudinal studies have demonstrated that healthy individuals at risk of shorter telomeres have a 30–50% independent and significantly higher risk of developing T2DM [9,10,11]. Taken together with our results, these findings provide support for the notion that telomere shortening may underlie mechanisms of diabetes development. Although the relationship between TL and T2DM incidence in patients with CHD has not been examined thoroughly, Piplani et al. showed the first study with a cross-sectional analysis reporting a relationship between telomere length and T2DM presence in 130 patients diagnosed with ischemic heart [27]. The coexistence of diabetes and CVD leads to a consequent increase in oxidative stress and inflammation levels, which, in turn, lead to higher mortality rates and accelerated telomere shortening [28]. In this sense, our data suggest that a process of early cellular aging, induced by oxidative stress, contributes to increasing cardiovascular complications and mortality by promoting the development of diabetes.

Because patients with CHD and T2DM have a considerably higher risk of developing a new cardiovascular event than those without T2DM [29], research into strategies, such as dietary interventions, for T2DM prevention has become an imminent requirement. Genetic differences between individuals play an important role in determining the efficacy of dietary approaches, leading to the identification of genetic markers in the context of precision nutrition. Thus, our findings propose that epigenetic markers, such as TL, could be a useful biomarker to identify patients at high risk of development common CVD comorbidities and personalize dietary strategies to decrease the risk of T2DM development.

Although several studies have evaluated the impact of lifestyle intervention on telomere shortening in the context of cancer [30], obesity [31] or CVD [23], it is currently unknown whether TL is associated to the response to lifestyle interventions. To our knowledge, this is the first study to demonstrate that the Mediterranean diet may mitigate the effects of having a short TL in CHD patients. We observed that patients at risk of short telomeres at baseline showed a higher risk of developing T2DM when consuming a low-fat diet, in contrast to those adhering to a Mediterranean diet in which no differences were found. Based on the idea that TL could reflect an individual’s cumulative exposure to inflammation and oxidative stress conditions, the Mediterranean diet, known for its rich antioxidant content, could potentially act as a protective factor against telomere shortening [32]. Cánudas et al. presented a recently systematic review and meta-analysis provides the most wide-ranging analysis to date on the positive association between Mediterranean Diet adherence and TL in blood cells. The global effect of the Mediterranean diet on TL suggested that increased adherence to a healthy patter such as Mediterranean diet can serve to counteract multiple age-related diseases by mitigating telomere shortening [33]. In the context of our study, Cano-Ibáñez et al. examined the nutritional disparities between both healthy diets (a Mediterranean and a low-fat diet), which were recommended in CORDIOPREV study. They specifically observed a lower nutritional density of mono and polyunsaturated fatty acids in the low-fat group, attributed to reduced consumption of nuts and olive oil [34]. The consumption of both fatty acids has been associated with TL in several studies, mainly [35], due to their crucial role in protecting against oxidative processes and their influence on lipid mediators that regulate inflammation, which is associated with DNA protection, including telomere integrity.

Additionally, in our study, Non-T2DM patients at risk of short TL exhibited elevated levels of HDL-c compared to Incident-T2DM patients. HDL-c exerts antioxidant and anti-inflammatory effects [36]. Reduced levels of HDL-c observed in patients following a low-fat diet (but not a Mediterranean diet), could potentially lead to greater oxidative damage in G-rich telomere repeat sequences, making these individuals more susceptible to developing T2DM.

Our results support TL being a possible biomarker with the capacity to evaluate how patients with CHD respond to specific dietary treatments in terms of T2DM prevention. Consequently, these findings contribute to reduce the probability of a new cardiovascular event. Nevertheless, our study has limitations. The primary goal of the CORDIOPREV trial was not to prevent T2DM. However, it was a secondary analysis conducted in the subgroup of CHD patients without T2DM at baseline. Therefore, it limits our findings to individuals with this comorbidity.

In conclusion, our study shows that patients with shorter TL have a higher risk of developing T2DM. This association could be mitigated with a specific dietary pattern, in our case a Mediterranean pattern, to prevent the development of T2DM in patients with CHD.

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 light of each work.

Abbreviations

ADA:

American Diabetes Association

BMI:

Body Mass Index

CI:

Confident Intercal

WC:

Waist Circumference

CVD:

Cardiovascular Disease

CORDIOPREV study:

CORonary Diet Intervention with Olive oil and cardiovascular PREVention study

CHD:

Coronary Heart Disease

HbA1c:

Glycosylated Haemoglobin

HR:

Hazard Ratio

hs-CRP:

High sensitive C-Reactive Protein

HDL-c:

High-density lipoprotein-cholesterol

LDL-c:

Low-density lipoprotein-cholesterol

SEM:

Standard Error of the Mean

TL:

Telomere Length

T2DM:

Type 2 Diabetes Mellitus

References

  1. Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global Burden of Cardiovascular diseases and Risk factors, 1990–2019: Update from the GBD 2019 study. J am Coll Cardiol. Elsevier Inc. 2020;76:2982–3021. https://doi.org/10.1016/j.jacc.2020.11.010.

  2. Yuan T, Yang T, Chen H, Fu D, Hu Y, Wang J, et al. New insights into oxidative stress and inflammation during diabetes mellitus-accelerated atherosclerosis. Redox Biol. 2019;20:247–60. https://doi.org/10.1016/j.redox.2018.09.025.

  3. Lindström J, Ilanne-Parikka P, Peltonen M, Aunola S, Eriksson JG, Hemiö K, et al. Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish diabetes Prevention Study. Lancet. 2006;368:1673–9. https://doi.org/10.1016/S0140-6736(06)69701-8.

    Article  PubMed  Google Scholar 

  4. Cheng F, Carroll L, Joglekar MV, Januszewski AS, Wong KK, Hardikar AA, et al. Diabetes, metabolic disease, and telomere length. Lancet Diabetes Endocrinol. 2021;9:117–26. https://doi.org/10.1016/S2213-8587(20)30365-X.

    Article  CAS  PubMed  Google Scholar 

  5. Allsopp RC, Chang E, Kashefi-Aazam M, Rogaev EI, Piatyszek MA, Shay JW, et al. Telomere shortening is associated with cell division in vitro and in vivo. Exp Cell Res. 1995;220:194–200. https://doi.org/10.1006/excr.1995.1306.

    Article  CAS  PubMed  Google Scholar 

  6. Gavia-García G, Rosado-Pérez J, Arista-Ugalde TL, Aguiñiga-Sánchez I, Santiago-Osorio E, Mendoza-Núñez VM. Telomere length and oxidative stress and its relation with metabolic syndrome components in the aging. Biology (Basel). 2021;10:253. https://doi.org/10.3390/biology10040253.

  7. Ojeda-Rodriguez A, Alcala-Diaz JF, Rangel-Zuñiga OA, Arenas-de Larriva AP, Gutierrez-Mariscal FM, Gómez-Luna P et al. Association between telomere length and intima-media thickness of both common carotid arteries in patients with coronary heart disease: from the CORDIOPREV randomized controlled trial. Atherosclerosis. 2023;380:117193. https://doi.org/10.1016/j.atherosclerosis.2023.117193.

  8. Khosravaniardakani S, Bokov DO, Mahmudiono T, Hashemi SS, Nikrad N, Rabieemotmaen S et al. Obesity accelerates leukocyte telomere length shortening in apparently healthy adults: a Meta-analysis. Front Nutr. 2022;9:812846. https://doi.org/10.3389/fnut.2022.812846.

  9. Willeit P, Raschenberger J, Heydon EE, Tsimikas S, Haun M, Mayr A et al. Leucocyte telomere length and risk of type 2 diabetes mellitus: New prospective cohort study and literature-based meta-analysis. PLoS ONE. 2014;9:e112483. https://doi.org/10.1371/journal.pone.0112483.

  10. Zhao J, Zhu Y, Lin J, Matsuguchi T, Blackburn E, Zhang Y, et al. Short leukocyte telomere length predicts risk of diabetes in American indians: the strong heart family study. Diabetes. 2014;63:354–62. https://doi.org/10.2337/db13-0744.

    Article  CAS  PubMed  Google Scholar 

  11. Zhao H, Han L, Chang D, Ye Y, Shen J, Daniel CR, et al. Social-demographics, health behaviors, and telomere length in the Mexican American Mano a Mano Cohort. Oncotarget. 2017;8:96553–67. https://doi.org/10.18632/oncotarget.19903.

    Article  PubMed  Google Scholar 

  12. Blasco MA. Telomeres and human disease: Ageing, cancer and beyond. Nat Rev Genet. 2005;6:611–22. https://doi.org/10.1038/nrg1656.

    Article  CAS  PubMed  Google Scholar 

  13. Delgado-Lista J, Perez-Martinez P, Garcia-Rios A, Alcala-Diaz JF, Perez-Caballero AI, Gomez-Delgado F, et al. CORonary Diet intervention with Olive oil and cardiovascular PREVention study (the CORDIOPREV study): Rationale, methods, and baseline characteristics a clinical trial comparing the efficacy of a Mediterranean diet rich in olive oil versus a low-fat diet on cardiovascular disease in coronary patients. Am Heart J. 2016;177:42–50. https://doi.org/10.1016/j.ahj.2016.04.011.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37:81–90.

    Article  Google Scholar 

  15. Delgado-Lista J, Alcala-Diaz JF, Torres-Peña JD, Quintana-Navarro GM, Fuentes F, Garcia-Rios A, et al. Long-term secondary prevention of cardiovascular disease with a Mediterranean diet and a low-fat diet (CORDIOPREV): a randomised controlled trial. Lancet. 2022;399:1876–85. https://doi.org/10.1016/S0140-6736(22)00122-2.

    Article  CAS  PubMed  Google Scholar 

  16. Fernández-Ballart JD, Piñol JL, Zazpe I, Corella D, Carrasco P, Toledo E, et al. Relative validity of a semi-quantitative food-frequency questionnaire in an elderly Mediterranean population of Spain. Br J Nutr. 2010;103:1808–16. https://doi.org/10.1017/S0007114509993837.

    Article  PubMed  Google Scholar 

  17. Martínez-González MA, Fernández-Jarne E, Serrano-Martínez M, Wright M, Gomez-Gracia E. Development of a short dietary intake questionnaire for the quantitative estimation of adherence to a cardioprotective Mediterranean diet. Eur J Clin Nutr. 2004;58:1550–2. https://doi.org/10.1038/sj.ejcn.1602004.

    Article  PubMed  Google Scholar 

  18. Miller S, Dykes D, Polesky H. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. 1988;16:1215. https://doi.org/10.1093/nar/16.3.1215.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Cawthon RM. Telomere measurement by quantitative PCR. Nucleic Acids Res. 2002;30:e47. https://doi.org/10.1093/nar/30.10.e47.

  20. Hemann MT, Strong MA, Hao LY, Greider CW. The Shortest Telomere, Not Average Telomere Length, Is Critical for Cell Viability and Chromosome Stability. Cell. 2001;107:67–77.

  21. Vera E, Bernardes de Jesus B, Foronda M, Flores JM, Blasco MA. The Rate of Increase of Short Telomeres Predicts Longevity in Mammals. Cell Rep. 2012;2:732–7. https://doi.org/10.1016/j.celrep.2012.08.023.

  22. Alonso-pedrero L, Ojeda-Rodríguez A, Martínez-González MA, Zalba G, Bes-rastrollo M, Marti A. Ultra-processed food consumption and the risk of short telomeres in an elderly population of the SUN Project. Am J Clin Nutr. 2020;111:1259–66. https://doi.org/10.1093/ajcn/nqaa075.

    Article  PubMed  Google Scholar 

  23. García-Calzón S, Martínez-González MA, Razquin C, Arós F, Lapetra J, Martínez JA, et al. Mediterranean diet and telomere length in high cardiovascular risk subjects from the PREDIMED-NAVARRA study. Clin Nutr. 2016;35:1399–405. https://doi.org/10.1016/j.clnu.2016.03.013.

    Article  PubMed  Google Scholar 

  24. Tsoukalas D, Fragkiadaki P, Docea AO, Alegakis AK, Sarandi E, Vakonaki E, et al. Association of nutraceutical supplements with longer telomere length. Int J Mol Med. 2019;44:218–26. https://doi.org/10.3892/ijmm.2019.4191.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Wang J, Dong X, Cao L, Sun Y, Qiu Y, Zhang Y, et al. Association between telomere length and diabetes mellitus: a meta-analysis. J Int Med Res. 2016;44:1156–73. https://doi.org/10.1177/0300060516667132.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Adaikalakoteswari A, Balasubramanyam M, Mohan V. Telomere shortening occurs in Asian Indian type 2 diabetic patients. Diabet Med. 2005;22:1151–6. https://doi.org/10.1111/j.1464-5491.2005.01574.x.

    Article  CAS  PubMed  Google Scholar 

  27. Piplani S, Alemao NN, Prabhu M, Ambar S, Chugh Y, Chugh SK. Correlation of the telomere length with type 2 diabetes mellitus in patients with ischemic heart disease. Indian Heart J. 2018;70:173–6. https://doi.org/10.1016/j.ihj.2018.09.007.

    Article  Google Scholar 

  28. Matheus ASDM, Tannus LRM, Cobas RA, Palma CCS, Negrato CA, Gomes MDB. Impact of diabetes on cardiovascular disease: an update. Int J Hypertens. 2013;2013. https://doi.org/10.1155/2013/653789.

  29. Haffner SM, Lehto S, Rönnemaa T, Pyörälä K, Laakso M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. N Engl J Med. 1998;339:229–34. https://doi.org/10.1056/NEJM199807233390404.

    Article  CAS  PubMed  Google Scholar 

  30. Thomson CA, Crane TE, Miller A, Garcia DO, Basen-Engquist K, Alberts DS. A randomized trial of diet and physical activity in women treated for stage II–IV ovarian cancer: Rationale and design of the Lifestyle intervention for ovarian Cancer enhanced survival (LIVES): an NRG Oncology/Gynecologic Oncology Group (GOG-225) study. Contemp Clin Trials. 2016;49:181–9. https://doi.org/10.1016/j.cct.2016.07.005.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Morell-Azanza L, Ojeda-Rodríguez A, Azcona-SanJulián MC, Zalba G, Marti A. Associations of telomere length with anthropometric and glucose changes after a lifestyle intervention in abdominal obese children. Nutrition, Metabolism and Cardiovascular Diseases. 2019;30:694–700. https://doi.org/10.1016/j.numecd.2019.12.002.

  32. Davinelli S, Trichopoulou A, Corbi G, De Vivo I, Scapagnini G. The potential nutrigeroprotective role of Mediterranean diet and its functional components on telomere length dynamics. Ageing Res Rev. 2019;49:1–10. https://doi.org/10.1016/j.arr.2018.11.001.

  33. Galiè S, Canudas S, Muralidharan J, García-gavilán J, Bulló M, Salas-salvadó J. Impact of Nutrition on Telomere Health: systematic review of Observational Cohort studies and Randomized Clinical trials. Adv Nutr. 2020;11:576–601. https://doi.org/10.1093/advances/nmz107.

    Article  PubMed  Google Scholar 

  34. Cano-Ibáñez N, Quintana-Navarro GM, Alcala-Diaz JF, Rangel-Zuñiga OA, Camargo A, Yubero-Serrano EM, et al. Long-term effect of a dietary intervention with two-healthy dietary approaches on food intake and nutrient density in coronary patients: results from the CORDIOPREV trial. Eur J Nutr. 2022;61:3019–36. https://doi.org/10.1007/s00394-022-02854-7.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Freitas-Simoes T, Ros E, Sala-Vila A. Nutrients, foods, dietary patterns and telomere length: Update of epidemiological studies and randomized trials. Metabolism. 2016;65:406–15. https://doi.org/10.1016/j.metabol.2015.11.004.

  36. Tomás M, Latorre G, Sentí M, Marrugat J. The Antioxidant Function of High Density Lipoproteins: A New Paradigm in Atherosclerosis Rev Esp Cardiol. 2004;57:557–69. https://doi.org/10.1157/13062921.

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Acknowledgements

The authors would like to thank the participants of the trial.

Funding

The CORDIOPREV study is supported by the “Fundación Patrimonio Comunal Olivarero” (Cordioprev-CEAS, 1/2016 to JL-M). The main sponsor was not involved in the design or carrying out the study, and its participation was limited to funding and providing the olive oil used in the study. This project was funded by “Ministerio de Ciencia e Innovación/Agencia Estatal de Investigación (MCIN/AEI/https://doi.org/10.13039/501100011033, Grant AGL2012/39615, AGL2015-67896-P, PI13/00185 and PID2019-104362RB-I00), “Consejería de Transformación Económica, Industria, Conocimiento y Universidades” (Grant PY20/00256) from “Junta de Andalucía” and cofunded by FEDER. Dr. Ana Ojeda-Rodríguez is the recipient of a Sara Borrell grant (CD21/00099) from the “Instituto de Salud Carlos III” (ISCIII). Dr. Elena M. Yubero-Serrano is also the recipient of the Nicolas Monardes Programme from the “Servicio Andaluz de Salud, Junta de Andalucia”, Spain (C1-0005-2019). Dr. Gutiérrez Mariscal is supported by a research contract from the University of Cordoba “Plan Propio de Investigación UCO2017”. The CIBEROBN is an initiative of the ISCIII.

Author information

Author notes

  1. Ana Ojeda-Rodriguez and Oriol Alberto Rangel Zuñiga contributed equally to this work.

  2. Elena M. Yubero-Serrano and Jose Lopez-Miranda contributed equally to this work.

Authors and Affiliations

  1. Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, Cordoba, 14004, Spain

    Ana Ojeda-Rodriguez, Oriol A. Rangel-Zuñiga, Antonio P. Arenas-de Larriva, Francisco M. Gutierrez-Mariscal, Jose D. Torres-Peña, Juan L. Romero-Cabrera, Alicia Podadera-Herreros, Helena García-Fernandez, Esther Porras-Pérez, Pablo Perez-Martinez, Javier Delgado-Lista, Elena M. Yubero-Serrano & Jose Lopez-Miranda

  2. Department of Medical and Surgical Science, University of Cordoba, Cordoba, 14004, Spain

    Ana Ojeda-Rodriguez, Oriol A. Rangel-Zuñiga, Antonio P. Arenas-de Larriva, Francisco M. Gutierrez-Mariscal, Jose D. Torres-Peña, Juan L. Romero-Cabrera, Alicia Podadera-Herreros, Helena García-Fernandez, Esther Porras-Pérez, Pablo Perez-Martinez, Javier Delgado-Lista, Elena M. Yubero-Serrano & Jose Lopez-Miranda

  3. Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Av. Menendez Pidal, s/n, Cordoba, 14004, Spain

    Ana Ojeda-Rodriguez, Oriol A. Rangel-Zuñiga, Antonio P. Arenas-de Larriva, Francisco M. Gutierrez-Mariscal, Jose D. Torres-Peña, Juan L. Romero-Cabrera, Alicia Podadera-Herreros, Helena García-Fernandez, Esther Porras-Pérez, Raul M. Luque, Pablo Perez-Martinez, Javier Delgado-Lista, Elena M. Yubero-Serrano & Jose Lopez-Miranda

  4. CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, 28029, Spain

    Ana Ojeda-Rodriguez, Oriol A. Rangel-Zuñiga, Antonio P. Arenas-de Larriva, Francisco M. Gutierrez-Mariscal, Jose D. Torres-Peña, Juan L. Romero-Cabrera, Alicia Podadera-Herreros, Helena García-Fernandez, Esther Porras-Pérez, Raul M. Luque, Pablo Perez-Martinez, Javier Delgado-Lista, Elena M. Yubero-Serrano & Jose Lopez-Miranda

  5. Department of Cell Biology, Physiology and Immunology, University of Cordoba, Cordoba, 14004, Spain

    Raul M. Luque

  6. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Stefanos N. Kales

  7. Department of Occupational Medicine, Cambridge Health Alliance, Harvard Medical School, Cambridge, MA, USA

    Stefanos N. Kales

Authors
  1. Ana Ojeda-Rodriguez
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Contributions

AO-R and OAR-Z contributed equally to this work. EMY-S and JL-M contributed equally to this work. AO-R, OAR-Z, EMY-S and JL-M wrote the first draft of the manuscript. AO-R, OAR Z, FM-G carried out the analysis. OAR-Z, APA-deL, JDT-P collected the data and performed the classification of participants. OAR-Z, AP-H, HG-F, EP-P performed the experiments. APA-deL, JDT-P and JLR-G performed the medical revisions of participants and clinical databases. AO-R, OAR-Z, FMG-M, RML, SNK, EMY-S and JL-M interpreted the data and contributed to the discussion. FMG-M, AP-H, HG-F, EP-P, RML, SNK, JD-L, PP M, and JL M contributed to the writing of the manuscript and revised it critically for important intellectual content. All authors read and approved the final manuscript. JD-L and JL-M conceptualized the study and designed the research methodology. JD-L and JL M are the guarantors of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Corresponding author

Correspondence to Jose Lopez-Miranda.

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Ethics approval and consent to participate

The study protocol received approval from the Human Investigation Review Committee at Reina Sofia University Hospital, following the institutional and Good Clinical Practice guidelines.

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Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Electronic supplementary material

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Supplementary Material 1: Additional Table 1.

Baseline characteristics of the study population according to the incidence or non-incidence of diabetes

Supplementary Material 2: Additional Figure 1.

Flow Chart of the Study

Supplementary Material 3: Additional Figure 2.

T2DM incidence assessed by ROC curve models based on clinical variables and telomere length

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Ojeda-Rodriguez, A., Rangel-Zuñiga, O.A., Arenas-de Larriva, A.P. et al. Telomere length as biomarker of nutritional therapy for prevention of type 2 diabetes mellitus development in patients with coronary heart disease: CORDIOPREV randomised controlled trial. Cardiovasc Diabetol 23, 98 (2024). https://doi.org/10.1186/s12933-024-02175-5

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Keywords

Cardiovascular Diabetology

ISSN: 1475-2840