Publications on the application of omics technologies in cariology research up to December 2022 were sourced from online databases, including PubMed, Web of Science and Scopus. Two independent reviewers assessed the relevance of the publications to the objective of this review.
Studies that employed omics technologies to investigate dental caries were selected from the initial pool of identified publications. A total of 922 publications with one or more omics technologies adopted were included for comprehensive bibliographic analysis. (Meta)genomics (676/922, 73 %) is the predominant omics technology applied for cariology research in the included studies. Other applied omics technologies are metabolomics (108/922, 12 %), proteomics (105/922, 11 %), and transcriptomics (76/922, 8 %).
This study identified an emerging trend in the application of multiple omics technologies in cariology research. Omics technologies possess significant potential in developing strategies for the detection, staging evaluation, risk assessment, prevention, and management of dental caries. Despite the numerous challenges that lie ahead, the integration of multi-omics data obtained from individual biological samples, in conjunction with artificial intelligence technology, may offer potential avenues for further exploration in caries research.
This review presented a comprehensive overview of the application of omics technologies in cariology research and discussed the advantages and challenges of using these methods to detect, assess, predict, prevent, and treat dental caries. It contributes to steering research for improved understanding of dental caries and advancing clinical translation of cariology research outcomes.
方法:截至2022年12月,有关组学技术在Cariology研究中的应用的出版物均来自在线数据库,包括PubMed,WebofScience和Scopus两名独立审稿人评估了出版物与本审查目标的相关性。
方法:采用组学技术调查龋齿的研究是从最初的已确定出版物中选择的。共有922种出版物采用了一种或多种组学技术,用于综合书目分析。(meta)基因组学(676/922,73%)是纳入研究中用于生态学研究的主要组学技术。其他应用的组学技术是代谢组学(108/922,12%),蛋白质组学(105/922,11%),和转录组学(76/922,8%)。
结论:这项研究确定了在人类学研究中应用多种组学技术的新兴趋势。组学技术在开发检测策略方面具有巨大潜力,分期评估,风险评估,预防,和龋齿的管理。尽管前面有许多挑战,整合从单个生物样本中获得的多组数据,结合人工智能技术,可能为龋齿研究提供进一步探索的潜在途径。
结论:这篇综述全面概述了组学技术在理学研究中的应用,并讨论了使用这些方法检测的优势和挑战,评估,预测,防止,治疗龋齿。它有助于指导研究,以提高对龋齿的理解并促进Cariology研究成果的临床翻译。