Mechanistic insights into dietary (poly)phenols and vascular dysfunction-related diseases using multi-omics and integrative approaches: Machine learning as a next challenge in nutrition research
{"title":"Mechanistic insights into dietary (poly)phenols and vascular dysfunction-related diseases using multi-omics and integrative approaches: Machine learning as a next challenge in nutrition research","authors":"Dragan Milenkovic , Tatjana Ruskovska","doi":"10.1016/j.mam.2022.101101","DOIUrl":null,"url":null,"abstract":"<div><p>Dietary (poly)phenols have been extensively studied for their vasculoprotective effects and consequently their role in preventing or delaying onsets of cardiovascular and metabolic diseases. Even though early studies have ascribed the vasculoprotective properties of (poly)phenols primarily on their putative free radical scavenging properties, recent data indicate that in biological systems, (poly)phenols act primarily through genomic and epigenomic mechanisms. The molecular mechanisms underlying their health properties are still not well identified, mainly due to the use of physiologically non-relevant conditions (native molecules or extracts at high concentrations, rather than circulating metabolites), but also due to the use of targeted genomic approaches aiming to evaluate the effect only on few specific genes, thus preventing to decipher detailed molecular mechanisms involved. The use of state-of-the-art untargeted analytical methods represents a significant breakthrough in nutrigenomics, as these methods enable detailed insights into the effects at each specific omics level. Moreover, the implementation of multi-omics approaches allows integration of different levels of regulation of cellular functions, to obtain a comprehensive picture of the molecular mechanisms of action of (poly)phenols. In combination with bioinformatics and the methods of machine learning, multi-omics has potential to make a huge contribution to the nutrition science. The aim of this review is to provide an overview of the use of the omics, multi-omics, and integrative approaches in studying the vasculoprotective properties of dietary (poly)phenols and address the potentials for use of the machine learning in nutrigenomics.</p></div>","PeriodicalId":49798,"journal":{"name":"Molecular Aspects of Medicine","volume":null,"pages":null},"PeriodicalIF":8.7000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Aspects of Medicine","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0098299722000462","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 6
Abstract
Dietary (poly)phenols have been extensively studied for their vasculoprotective effects and consequently their role in preventing or delaying onsets of cardiovascular and metabolic diseases. Even though early studies have ascribed the vasculoprotective properties of (poly)phenols primarily on their putative free radical scavenging properties, recent data indicate that in biological systems, (poly)phenols act primarily through genomic and epigenomic mechanisms. The molecular mechanisms underlying their health properties are still not well identified, mainly due to the use of physiologically non-relevant conditions (native molecules or extracts at high concentrations, rather than circulating metabolites), but also due to the use of targeted genomic approaches aiming to evaluate the effect only on few specific genes, thus preventing to decipher detailed molecular mechanisms involved. The use of state-of-the-art untargeted analytical methods represents a significant breakthrough in nutrigenomics, as these methods enable detailed insights into the effects at each specific omics level. Moreover, the implementation of multi-omics approaches allows integration of different levels of regulation of cellular functions, to obtain a comprehensive picture of the molecular mechanisms of action of (poly)phenols. In combination with bioinformatics and the methods of machine learning, multi-omics has potential to make a huge contribution to the nutrition science. The aim of this review is to provide an overview of the use of the omics, multi-omics, and integrative approaches in studying the vasculoprotective properties of dietary (poly)phenols and address the potentials for use of the machine learning in nutrigenomics.
期刊介绍:
Molecular Aspects of Medicine is a review journal that serves as an official publication of the International Union of Biochemistry and Molecular Biology. It caters to physicians and biomedical scientists and aims to bridge the gap between these two fields. The journal encourages practicing clinical scientists to contribute by providing extended reviews on the molecular aspects of a specific medical field. These articles are written in a way that appeals to both doctors who may struggle with basic science and basic scientists who may have limited awareness of clinical practice issues. The journal covers a wide range of medical topics to showcase the molecular insights gained from basic science and highlight the challenging problems that medicine presents to the scientific community.