Literature DB >> 31511194

A Unified Conceptual Framework for Metabolic Phenotyping in Diagnosis and Prognosis.

Jeremy R Everett1, Elaine Holmes2, Kirill A Veselkov2, John C Lindon2, Jeremy K Nicholson3.   

Abstract

Understanding metabotype (multicomponent metabolic characteristics) variation can help to generate new diagnostic and prognostic biomarkers, as well as models, with potential to impact on patient management. We present a suite of conceptual approaches for the generation, analysis, and understanding of metabotypes from body fluids and tissues. We describe and exemplify four fundamental approaches to the generation and utilization of metabotype data via multiparametric measurement of (i) metabolite levels, (ii) metabolic trajectories, (iii) metabolic entropies, and (iv) metabolic networks and correlations in space and time. This conceptual framework can underpin metabotyping in the scenario of personalized medicine, with the aim of improving clinical outcomes for patients, but the framework will have value and utility in areas of metabolic profiling well beyond this exemplar.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  metabolic entropy; metabolomics; personalized medicine; pharmacometabonomics; precision medicine; systems medicine

Mesh:

Substances:

Year:  2019        PMID: 31511194     DOI: 10.1016/j.tips.2019.08.004

Source DB:  PubMed          Journal:  Trends Pharmacol Sci        ISSN: 0165-6147            Impact factor:   14.819


  8 in total

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5.  Metabolic Signatures of Gestational Weight Gain and Postpartum Weight Loss in a Lifestyle Intervention Study of Overweight and Obese Women.

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7.  Metabonomics study of the effects of single copy mutant KRAS in the presence or absence of WT allele using human HCT116 isogenic cell lines.

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Review 8.  Merging the exposome into an integrated framework for "omics" sciences.

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  8 in total

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