Abstract
Metabolic phenotypes represent the overall characterization of an individual's metabolites at a specific point in time. They precisely reflect the complex interactions among genetic background, environmental factors, lifestyle, and gut microbiome, thereby serving as a key molecular link between healthy homeostasis and disease-related metabolic disruption. In recent years, high-throughput metabolomics strategies have enabled the systematic analysis of small molecule metabolites in physiological and pathological processes. These metabolites not only serve as biomarkers for disease diagnosis, prognosis assessment, and treatment response prediction, but also elucidate novel mechanistic pathways in disease progression. The high-coverage, high-sensitivity detection of metabolites afforded by mass spectrometry and NMR-based metabolomics enables advances in precision medicine, facilitating biomarker discovery, pharmacokinetic studies, and the assessment of nutritional interventions. This review uses several common metabolic diseases, such as obesity, diabetes, cardiovascular diseases, and cancer, to explore the key role of metabolic phenotypes in disease risk stratification and precise prediction. Future phenotypic research will shift toward integrating artificial intelligence, big data mining, and multi-omics with the goal of revealing the complete network through which metabolic phenotypes regulate diseases. This research is expected to advance early diagnosis, precise prevention, and targeted treatment, contributing to a medical paradigm shift from disease treatment to health maintenance.