Multi-omics approaches for in-depth understanding of therapeutic mechanism for Traditional Chinese Medicine

Abstract

Traditional Chinese Medicine (TCM) is extensively utilized in clinical practice due to its therapeutic and preventative treatments for various diseases. With the development of high-throughput sequencing and systems biology, TCM research was transformed from traditional experiment-based approaches to a combination of experiment-based and omics-based approaches. Numerous academics have explored the therapeutic mechanism of TCM formula by omics approaches, shifting TCM research from the “one-target, one-drug” to “multi-targets, multi-components” paradigm, which has greatly boosted the digitalization and internationalization of TCM. In this review, we concentrated on multi-omics approaches in principles and applications to gain a better understanding of TCM formulas against various diseases from several aspects. We first summarized frequently used TCM quality assessment methods, and suggested that incorporating both chemical and biological ingredients analytical methods could lead to a more comprehensive assessment of TCM. Secondly, we emphasized the significance of multi-omics approaches in deciphering the therapeutic mechanism of TCM formulas. Thirdly, we focused on TCM network analysis, which plays a vital role in TCM-diseases interaction, and serves for new drug discovery. Finally, as an essential source for storing multi-omics data, we evaluated and compared several TCM databases in terms of completeness and reliability. In summary, multi-omics approaches have infiltrated many aspects of TCM research. With the accumulation of omics data and data-mining resources, deeper understandings of the therapeutic mechanism of TCM have been acquired or will be gained in the future.