Zhang Josie Shizhen, Huang Shi, Chen Zigui, Chu Chun-Hung, Takahashi Nobuhiro, Yu Ollie Yiru
Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, PR China.
Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, PR China; Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China.
J Dent. 2024 Feb;141:104801. doi: 10.1016/j.jdent.2023.104801. Epub 2023 Dec 13.
To review the application of omics technologies in the field of cariology research and provide critical insights into the emerging opportunities and challenges.
DATA & SOURCES: 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.
回顾组学技术在龋病学研究领域的应用，并对新出现的机遇和挑战提供重要见解。
截至2022年12月，关于组学技术在龋病学研究中应用的出版物来自在线数据库，包括PubMed、科学网和Scopus。两名独立评审员评估了这些出版物与本综述目标的相关性。
从已识别出版物的初始库中选择采用组学技术研究龋齿的研究。总共纳入了922篇采用一种或多种组学技术的出版物进行全面的文献分析。（元）基因组学（676/922，73%）是纳入研究中应用于龋病学研究的主要组学技术。其他应用的组学技术包括代谢组学（108/922，12%）、蛋白质组学（105/922，11%）和转录组学（76/922，8%）。
本研究确定了多种组学技术在龋病学研究中应用的新趋势。组学技术在制定龋齿检测、分期评估、风险评估、预防和管理策略方面具有巨大潜力。尽管面临众多挑战，但将从个体生物样本中获得的多组学数据与人工智能技术相结合，可能为龋病研究提供进一步探索的潜在途径。
本综述全面概述了组学技术在龋病学研究中的应用，并讨论了使用这些方法检测、评估、预测、预防和治疗龋齿的优势和挑战。它有助于引导研究以更好地理解龋齿，并推动龋病学研究成果的临床转化。
