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Challenges in Metabolomics-Based Tests, Biomarkers Revealed by Metabolomic Analysis, and the Promise of the Application of Metabolomics in Precision Medicine.

Alessandro Di MinnoMonica GelzoMarianna CaterinoMichele CostanzoMargherita RuoppoloGiuseppe Castaldo
Published in: International journal of molecular sciences (2022)
Metabolomics helps identify metabolites to characterize/refine perturbations of biological pathways in living organisms. Pre-analytical, analytical, and post-analytical limitations that have hampered a wide implementation of metabolomics have been addressed. Several potential biomarkers originating from current targeted metabolomics-based approaches have been discovered. Precision medicine argues for algorithms to classify individuals based on susceptibility to disease, and/or by response to specific treatments. It also argues for a prevention-based health system. Because of its ability to explore gene-environment interactions, metabolomics is expected to be critical to personalize diagnosis and treatment. Stringent guidelines have been applied from the very beginning to design studies to acquire the information currently employed in precision medicine and precision prevention approaches. Large, prospective, expensive and time-consuming studies are now mandatory to validate old, and discover new, metabolomics-based biomarkers with high chances of translation into precision medicine. Metabolites from studies on saliva, sweat, breath, semen, feces, amniotic, cerebrospinal, and broncho-alveolar fluid are predicted to be needed to refine information from plasma and serum metabolome. In addition, a multi-omics data analysis system is predicted to be needed for omics -based precision medicine approaches. Omics -based approaches for the progress of precision medicine and prevention are expected to raise ethical issues.
Keyphrases
  • mass spectrometry
  • liquid chromatography
  • data analysis
  • primary care
  • healthcare
  • deep learning
  • genome wide
  • big data
  • bone marrow
  • cancer therapy
  • transcription factor
  • artificial intelligence