Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests

Abstract

Metabolomics refers to the large-scale detection, quantification, and analysis of small molecules (metabolites) in biological media. Although metabolomics, alone or combined with other omics data, has already demonstrated its relevance for patient stratification in the frame of research projects and clinical studies, much remains to be done to move this approach to the clinical practice. This is especially true in the perspective of being applied to personalized/precision medicine, which aims at stratifying patients according to their risk of developing diseases, and tailoring medical treatments of patients according to individual characteristics in order to improve their efficacy and limit their toxicity. In this review article, we discuss the main challenges linked to analytical chemistry that need to be addressed to foster the implementation of metabolomics in the clinics and the use of the data produced by this approach in personalized medicine. First of all, there are already well-known issues related to untargeted metabolomics workflows at the levels of data production (lack of standardization), metabolite identification (small proportion of annotated features and identified metabolites), and data processing (from automatic detection of features to multi-omic data integration) that hamper the inter-operability and reusability of metabolomics data. Furthermore, the outputs of metabolomics workflows are complex molecular signatures of few tens of metabolites, often with small abundance variations, and obtained with expensive laboratory equipment. It is thus necessary to simplify these molecular signatures so that they can be produced and used in the field. This last point, which is still poorly addressed by the metabolomics community, may be crucial in a near future with the increased availability of molecular signatures of medical relevance and the increased societal demand for participatory medicine. Graphical abstract

A photonic crystal fiber–based fluorescence sensor for simultaneous and sensitive detection of lactic acid enantiomers

“…These methods generally require complicated instruments and thus would be difficult to be used in point-of-care testing (POCT), which is of great importance for rapid determination of LA levels in blood with a remote manner. In recent years, biosensors with high sensitivity and good selectivity have developed rapidly and have shown promising applications in various fields of POCT [22][23][24][25][26]. Considering LA analysis, while biosensors using the immobilized enzyme electrochemical approach were reported for detection of l-LA in biological fluids [27][28][29][30][31][32], no such biosensor has been developed for the assay of LA enantiomers.…”

Harnessing Metabolomics to Advance Epilepsy Research

“…As a precision medicine approach, a patient’s metabolome tracked over time could reveal a personalized, predictive biomarker of therapy efficiency. 38 Somewhat related to this application, Olson et al 39 showed that the gut microbiota drove responses to a ketogenic diet and led to changes in the brain metabolome (e.g., glutamate and GABA) in a mouse model of epilepsy. Other studies have used metabolomics to explore the roles of the ketogenic diet 40 and inflammation 41 in the pathogenesis of epilepsy.…”

Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories

“…Mass spectrometry (MS)-based metabolomics have been widely applied to a variety of research fields, targeting microorganisms, plants, animals, and humans, to understand metabolism in the body [1][2][3][4]. Additionally, the relatively large datasets obtained from metabolomics are treated in large-scale studies, such as cohort and epidemiological studies [5][6][7].…”