Introduction: Despite an impressive amount of metabolomics studies in animal models and humans, most findings have not yet translated into the clinical setting, and the road ahead remains still long. Areas covered: This review provides the most challenging applications of clinical metabolomics testing in human health and disease. Personalized clinical metabolomics testing is incorporated within the test panel to diagnose inborn errors of metabolism, optimize dietary regimens, and discover and develop new drugs. The potential routine utilization of metabolomics in precision medicine has been revised in cancer and nutrition. The association between metabolomics with artificial intelligence and machine learning may open emerging perspectives for more effective utilization and timely introduction of clinical metabolomics testing in the care of patients with acute and chronic diseases. Expert opinion: In conclusion, slotting metabolomics into routine precision medicine implies the direct relationship between metabolomic results and clinical decision-making, similarly to any other clinical test result, as well as it requires the application of clinical laboratory standards, protocols, training, the oversight to a global biochemical profiling technology, and the availability of metabolic profiles from reference populations, defining cutoff values and decision levels.
Slotting metabolomics into routine precision medicine
Mussap M.;Noto A.;Piras C.;Atzori L.;Fanos V.
2021-01-01
Abstract
Introduction: Despite an impressive amount of metabolomics studies in animal models and humans, most findings have not yet translated into the clinical setting, and the road ahead remains still long. Areas covered: This review provides the most challenging applications of clinical metabolomics testing in human health and disease. Personalized clinical metabolomics testing is incorporated within the test panel to diagnose inborn errors of metabolism, optimize dietary regimens, and discover and develop new drugs. The potential routine utilization of metabolomics in precision medicine has been revised in cancer and nutrition. The association between metabolomics with artificial intelligence and machine learning may open emerging perspectives for more effective utilization and timely introduction of clinical metabolomics testing in the care of patients with acute and chronic diseases. Expert opinion: In conclusion, slotting metabolomics into routine precision medicine implies the direct relationship between metabolomic results and clinical decision-making, similarly to any other clinical test result, as well as it requires the application of clinical laboratory standards, protocols, training, the oversight to a global biochemical profiling technology, and the availability of metabolic profiles from reference populations, defining cutoff values and decision levels.File | Dimensione | Formato | |
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