Metabonomics and it’s Potential Application in Clinic Diagnosis and Therapy

Abstract

Metabolomics is a new-generation omics technology emerging after genomics, transcriptomics, and proteomics, It focuses on all small-molecule metabolites with molecular weights below 1 kDa within biological systems, providing a direct reflection of the terminal phenotypic changes in the physiological and pathological states of organisms. With the continuous iteration of detection platforms such as mass spectrometry and nuclear magnetic resonance, both untargeted and targeted metabolomics have been widely used to screen disease-specific metabolic biomarkers and construct non-invasive, and precise disease diagnostic models. This article summarized the main technical platforms and data analysis workflows of metabolomics, consolidated diagnostic applications of metabolomics in the fields including malignant tumors, metabolic diseases, neurological disorders, and autoimmune diseases, while discussing current bottlenecks in sample standardization, biomarker validation, and metabolic-disease causal analysis. Additionally, the article also explored the development prospects of artificial intelligence combined with spatial metabolomics in clinical precision diagnostics, it provides a reference for the translation of metabolomics from basic research to clinical diagnosis.