ABSTRACT Salivary metabolomics is increasingly recognized as a powerful, noninvasive approach for studying human health and disease. Unlike blood or urine, saliva is easily accessible, minimally invasive, and suitable for repeated sampling. Advances in nuclear magnetic resonance, mass spectrometry, capillary electrophoresis, and bioinformatics have improved the sensitivity and reproducibility of salivary metabolite profiling, enabling its use across diverse systemic diseases such as cancer, cardiovascular disorders, diabetes, viral infections, autoimmune diseases, and neurodegenerative conditions. Despite this progress, clinical translation is limited by variability in sampling, lack of standardized protocols, and insufficient large‐scale validation. This review synthesizes recent developments in human salivary metabolomics, emphasizing disease‐specific biomarkers and key applications in systemic disease diagnosis and monitoring. We also examine methodological and biological factors that influence data reliability, including collection methods, storage conditions, circadian rhythms, age, and host–microbiome interactions. Furthermore, integration of multiomics strategies, machine learning, and clinical registry data is discussed as a means to enhance biomarker discovery and translational potential. By addressing these challenges, salivary metabolomics can evolve into a reliable platform for noninvasive diagnosis, longitudinal disease monitoring, and personalized medicine, providing a valuable complement to blood‐based diagnostics in precision healthcare.
Zhao et al. (Sun,) studied this question.