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Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients

Hyperglycaemia can strongly alter the epigenetic signatures in many types of human vascular cells providing persistent perturbations of protein–protein interactions both in micro- and macro-domains. The establishment of these epigenetic changes may precede cardiovascular (CV) complications and help...

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Autores principales: Napoli, Claudio, Benincasa, Giuditta, Schiano, Concetta, Salvatore, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363021/
https://www.ncbi.nlm.nih.gov/pubmed/31665258
http://dx.doi.org/10.1093/ehjcvp/pvz062
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author Napoli, Claudio
Benincasa, Giuditta
Schiano, Concetta
Salvatore, Marco
author_facet Napoli, Claudio
Benincasa, Giuditta
Schiano, Concetta
Salvatore, Marco
author_sort Napoli, Claudio
collection PubMed
description Hyperglycaemia can strongly alter the epigenetic signatures in many types of human vascular cells providing persistent perturbations of protein–protein interactions both in micro- and macro-domains. The establishment of these epigenetic changes may precede cardiovascular (CV) complications and help us to predict vascular lesions in diabetic patients. Importantly, these epigenetic marks may be transmitted across several generations (transgenerational effect) and increase the individual risk of disease. Aberrant DNA methylation and imbalance of histone modifications, mainly acetylation and methylation of H3, represent key determinants of vascular lesions and, thus, putative useful biomarkers for prevention and diagnosis of CV risk in diabetics. Moreover, a differential expression of some micro-RNAs (miRNAs), mainly miR-126, may be a useful prognostic biomarker for atherosclerosis development in asymptomatic subjects. Recently, also environmental-induced chemical perturbations in mRNA (epitranscriptome), mainly the N(6)-methyladenosine, have been associated with obesity and diabetes. Importantly, reversal of epigenetic changes by modulation of lifestyle and use of metformin, statins, fenofibrate, and apabetalone may offer useful therapeutic options to prevent or delay CV events in diabetics increasing the opportunity for personalized therapy. Network medicine is a promising molecular-bioinformatic approach to identify the signalling pathways underlying the pathogenesis of CV lesions in diabetic patients. Moreover, machine learning tools combined with tomography are advancing the individualized assessment of CV risk in these patients. We remark the need for combining epigenetics and advanced bioinformatic platforms to improve the prediction of vascular lesions in diabetics increasing the opportunity for CV precision medicine.
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spelling pubmed-73630212020-07-20 Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients Napoli, Claudio Benincasa, Giuditta Schiano, Concetta Salvatore, Marco Eur Heart J Cardiovasc Pharmacother Current Opinion Hyperglycaemia can strongly alter the epigenetic signatures in many types of human vascular cells providing persistent perturbations of protein–protein interactions both in micro- and macro-domains. The establishment of these epigenetic changes may precede cardiovascular (CV) complications and help us to predict vascular lesions in diabetic patients. Importantly, these epigenetic marks may be transmitted across several generations (transgenerational effect) and increase the individual risk of disease. Aberrant DNA methylation and imbalance of histone modifications, mainly acetylation and methylation of H3, represent key determinants of vascular lesions and, thus, putative useful biomarkers for prevention and diagnosis of CV risk in diabetics. Moreover, a differential expression of some micro-RNAs (miRNAs), mainly miR-126, may be a useful prognostic biomarker for atherosclerosis development in asymptomatic subjects. Recently, also environmental-induced chemical perturbations in mRNA (epitranscriptome), mainly the N(6)-methyladenosine, have been associated with obesity and diabetes. Importantly, reversal of epigenetic changes by modulation of lifestyle and use of metformin, statins, fenofibrate, and apabetalone may offer useful therapeutic options to prevent or delay CV events in diabetics increasing the opportunity for personalized therapy. Network medicine is a promising molecular-bioinformatic approach to identify the signalling pathways underlying the pathogenesis of CV lesions in diabetic patients. Moreover, machine learning tools combined with tomography are advancing the individualized assessment of CV risk in these patients. We remark the need for combining epigenetics and advanced bioinformatic platforms to improve the prediction of vascular lesions in diabetics increasing the opportunity for CV precision medicine. Oxford University Press 2020-07 2019-10-26 /pmc/articles/PMC7363021/ /pubmed/31665258 http://dx.doi.org/10.1093/ehjcvp/pvz062 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the European Society of Cardiology http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Current Opinion
Napoli, Claudio
Benincasa, Giuditta
Schiano, Concetta
Salvatore, Marco
Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients
title Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients
title_full Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients
title_fullStr Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients
title_full_unstemmed Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients
title_short Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients
title_sort differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients
topic Current Opinion
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363021/
https://www.ncbi.nlm.nih.gov/pubmed/31665258
http://dx.doi.org/10.1093/ehjcvp/pvz062
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