Metabolomics has broad prospects in clinical diagnosis. There are four main applications, application in clinical diagnosis (Biomarker), research and application in etiology and pathological mechanism, clinical diagnosis, etiology and pathological mechanism study, clinical medication guidance and preclinical animal model screening.
Application in Clinical Diagnosis
In general, untargeted metabolomics techniques are firstly used to compare all metabolites in the control and experimental groups and find their differences. Targeted metabolomics techniques are then used to carry out targeted and specific detection and analysis on specific metabolite populations, so as to reveal specific metabolite populations that are associated with diseases. So far, the application and research of metabolomics have achieved rapid development in the diagnosis of genetic metabolic defects, tumors, liver diseases, cardiovascular diseases, mental diseases and other diseases.
Application in Etiology and Pathological Mechanism
As many endogenous small molecule compounds detected by metabolomics are directly involved in various metabolism/circulation in the body, the level of metabolism, to a certain extent, reflects the function and state of the body's biochemical metabolism. Through metabolic network analysis, we can also understand the biochemical metabolic state in the body and communicate the relationship between biochemical metabolism and diseases. It is also helpful to discover new drug targets by exploring and revealing the etiology and pathological mechanism of diseases from related metabolic abnormalities.
Application in Clinical Medication Guidance
Rational use of medicines include many contents, including drug dosage, drug dosage forms, drug toxic and side effects, and complex interactions involved in multi-drug combination, as well as age and condition patients. Medication guidance is of great significance while a huge challenge in clinical treatment. In clinical treatment, the external manifestations caused by changes in the patient's condition and response to drugs are sometimes subtle, and traditional methods often cannot be accurately monitored. Under this circumstance, metabolomics combined with traditional detection methods will provide more precise guidance for treatment. Moreover, these metabolic spectra can provide a basis for evaluation of treatment monitoring, efficacy evaluation, drug toxic and side effects, surgery and prognosis evaluation, and individualized treatment plan customization.
Application in Preclinical Animal Model Screening
As a new approach to understand diseases, metabolomics plays an important role in the discovery and analysis of potential biomarkers and clinical drug screening in a variety of diseases. However, due to the lack of clinical results, in order to obtain better predictive effects, it is urgent to select the best preclinical animal model in the stage of clinical drug target screening. By metabolomics, the most suitable animal models can be screened by characteristic spectra. For example, in the study of dyslipidemia, it was found that the metabolic syndrome of rhesus monkeys is the closest one to humans in 24 animal models using metabolomics.