Dataset Information

Epigenetic Biomarkers in Cardiovascular Diseases.

ABSTRACT: Cardiovascular diseases are the number one cause of death worldwide and greatly impact quality of life and medical costs. Enormous effort has been made in research to obtain new tools for efficient and quick diagnosis and predicting the prognosis of these diseases. Discoveries of epigenetic mechanisms have related several pathologies, including cardiovascular diseases, to epigenetic dysregulation. This has implications on disease progression and is the basis for new preventive strategies. Advances in methodology and big data analysis have identified novel mechanisms and targets involved in numerous diseases, allowing more individualized epigenetic maps for personalized diagnosis and treatment. This paves the way for what is called pharmacoepigenetics, which predicts the drug response and develops a tailored therapy based on differences in the epigenetic basis of each patient. Similarly, epigenetic biomarkers have emerged as a promising instrument for the consistent diagnosis and prognosis of cardiovascular diseases. Their good accessibility and feasible methods of detection make them suitable for use in clinical practice. However, multicenter studies with a large sample population are required to determine with certainty which epigenetic biomarkers are reliable for clinical routine. Therefore, this review focuses on current discoveries regarding epigenetic biomarkers and its controversy aiming to improve the diagnosis, prognosis, and therapy in cardiovascular patients.

SUBMITTER: Soler-Botija C

PROVIDER: S-EPMC6795132 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Epigenetic Biomarkers in Cardiovascular Diseases.

Soler-Botija Carolina C Gálvez-Montón Carolina C Bayés-Genís Antoni A

Frontiers in genetics 20191009

Cardiovascular diseases are the number one cause of death worldwide and greatly impact quality of life and medical costs. Enormous effort has been made in research to obtain new tools for efficient and quick diagnosis and predicting the prognosis of these diseases. Discoveries of epigenetic mechanisms have related several pathologies, including cardiovascular diseases, to epigenetic dysregulation. This has implications on disease progression and is the basis for new preventive strategies. Advanc ...[more]

PMID: 31649728

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Project description:BackgroundA growing number of cohort studies revealed an inverse association between cheese intake and cardiovascular diseases, yet the causal relationship is unclear.ObjectiveTo assess the causal relationship between cheese intake, and cardiovascular diseases and cardiovascular biomarkers.MethodsA two-sample Mendelian randomization (MR) analysis based on publicly available genome-wide association studies was employed to infer the causal relationship. The effect estimates were calculated using the random-effects inverse-variance-weighted method.ResultsCheese intake per standard deviation increase causally reduced the risks of type 2 diabetes (odds ratio (OR) = 0.46; 95% confidence interval (CI), 0.34-0.63; p = 1.02 × 10-6), heart failure (OR = 0.62; 95% CI, 0.49-0.79; p = 0.0001), coronary heart disease (OR = 0.65; 95% CI, 0.53-0.79; p = 2.01 × 10-5), hypertension (OR = 0.67; 95% CI, 0.53-0.84; p = 0.001), and ischemic stroke (OR = 0.76; 95% CI, 0.63-0.91; p = 0.003). Suggestive evidence of an inverse association between cheese intake and peripheral artery disease was also observed. No associations were observed for atrial fibrillation, cardiac death, pulmonary embolism, or transient ischemic attack. The better prognosis associated with cheese intake may be explained by lower body mass index (BMI; effect estimate = -0.58; 95% CI, from -0.88 to -0.27; p = 0.0002), waist circumference (effect estimate = -0.49; 95% CI, from -0.76 to -0.23; p = 0.0003), triglycerides (effect estimate = -0.33; 95% CI, from -0.50 to -0.17; p = 4.91 × 10-5), and fasting glucose (effect estimate = -0.20; 95% CI, from -0.33 to -0.07; p = 0.0003). There was suggestive evidence of a positive association between cheese intake and high-density lipoprotein. No influences were observed for blood pressure or inflammation biomarkers.ConclusionsThis two-sample MR analysis found causally inverse associations between cheese intake and type 2 diabetes, heart failure, coronary heart disease, hypertension, and ischemic stroke.

Project description:Cardiovascular diseases (CVDs) are widely recognized as the leading cause of mortality worldwide. Despite the advances in clinical management over the past decades, the underlying pathological mechanisms remain largely unknown. Exosomes have drawn the attention of researchers for their relevance in intercellular communication under both physiological and pathological conditions. These vesicles are suggested as complementary prospective biomarkers of CVDs; however, the role of exosomes in CVDs is still not fully elucidated. Here, we performed a literature search on exosomal biogenesis, characteristics, and functions, as well as the different available exosomal isolation techniques. Moreover, aiming to give new insights into the interaction between exosomes and CVDs, network analysis on the role of exosome-derived mediators in coronary artery disease (CAD) and heart failure (HF) was also performed to incorporate the different sources of information. The upregulated exosomal miRNAs miR-133a, miR-208a, miR-1, miR-499-5p, and miR-30a were described for the early diagnosis of acute myocardial infarction, while the exosome-derived miR-192, miR-194, miR-146a, and miR-92b-5p were considered as potential biomarkers for HF development. In CAD patients, upregulated exosomal proteins, including fibrinogen beta/gamma chain, inter-alpha-trypsin inhibitor heavy chain, and alpha-1 antichymotrypsin, were assessed as putative protein biomarkers. From downregulated proteins in CAD patients, albumin, clusterin, and vitamin D-binding protein were considered relevant to assess prognosis. The Vesiclepedia database included miR-133a of exosomal origin upregulated in patients with CAD and the exosomal miR-192, miR-194, and miR-146a upregulated in patients with HF. Additionally, Vesiclepedia included 5 upregulated and 13 downregulated exosomal proteins in patients in CAD. The non-included miRNAs and proteins have not yet been identified in exosomes and can be proposed for further research. This report highlights the need for further studies focusing on the identification and validation of miRNAs and proteins of exosomal origin as biomarkers of CAD and HF, which will enable, using exosomal biomarkers, the guiding of diagnosis/prognosis in CVDs.

Dataset Information

Epigenetic Biomarkers in Cardiovascular Diseases.

Publications

Epigenetic Biomarkers in Cardiovascular Diseases.

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