29 September 2017
Metabolomics is the study of the products of metabolism (metabolites), which can collectively be referred to as the metabolome. The metabolome is a highly personalised readout of metabolism, reflective of both nature (the proteins encoded and subsequently degraded within an individual) and nurture (nutrients, lifestyle choices, the gut microbiome, and exposures to drugs and environmental toxins).
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These metabolites can typically be detected in bodily fluids and tissue samples. For example, certain metabolic markers detected in the urine may be indicative of kidney disease, and metabolic markers suggestive of cardiovascular disease may be detected in the serum and/or plasma.
The unique aspect of metabolomics among the ‘omic’ technologies (including genomics, epigenomics, transcriptomics and proteomics) is that measuring metabolites provides a retrospective and wide-ranging account of the biological processes that have occurred within an individual, which may be relevant to health and disease states. Ultimately, improved understanding of metabolic pathways in the context of health and disease may offer valuable insights into the mechanisms of diseases and inform the selection and/or generation of targeted pharmacological therapies.
Ultimately, improved understanding of metabolic pathways in the context of health and disease may offer valuable insights into the mechanisms of diseases and inform the selection and/or generation of targeted pharmacological therapies.
How could metabolomics be used in personalised healthcare?
The most commonly used technology in metabolomics is mass spectrometry, which identifies and quantifies molecules within a sample based upon their mass and charge, and is a sensitive and efficient technique capable of measuring thousands of molecules simultaneously in a single sample. Currently, the main use of metabolic profiling using mass spectrometry in the NHS is for the newborn blood spot screening program, which is used to detect rare genetic disorders that interfere with key metabolic pathways.
Although to date very few other metabolites have been established and validated for clinical use, identifying and validating metabolic traits and their disease associations is an active area of research. This raises possibilities for the eventual utilisation of metabolomics in multiple clinical applications, including as biomarkers in screening and monitoring of disease. One such example is the metabolomics-based PolypDx™ urine screening test for pre-cancerous colonic polyps that is commercially available in the United States, although this has not yet been approved by the Food and Drug Administration (FDA) for wider adoption into routine healthcare.
Large-scale genome-wide association studies (GWAS) that seek associations between genetic variations and diseases are beginning to yield interesting and promising associations with metabolic traits in the context of cardiovascular disease, kidney disease, inflammatory bowel disease and cancer, amongst others.
Pharmacometabolomics has been the subject of considerable scientific investigation, and pre-clinical evidence is accumulating that support its predictive value for drug metabolism, efficacy and the risk of adverse events.
Metabolomics may also be beneficial for the development of personalised therapeutic strategies in the future. Progress in so-called ‘pharmacometabolomics’ offers enhanced potential for individualised drug regimens based upon the predicted therapeutic benefit (efficacy) and the risk of adverse effects or toxicity, and could be applied in clinical practice complementarily to pharmacogenomics. Pharmacometabolomics has been the subject of considerable scientific investigation, and pre-clinical evidence is accumulating that support its predictive value for drug metabolism, efficacy and the risk of adverse events.
Whilst metabolomics has exciting potential to provide insight into the pathophysiology of many diseases, there are challenges to address before the clinical applications of metabolomics broaden. These include:
Interpreting mass spectrometry data: In the pre-clinical phase of biomarker discovery, several technical challenges need to be overcome. There can be a high degree of correlation between metabolites in spectral data generated using mass spectrometry, making it difficult to discriminate between metabolites with similar chemical characteristics or significant correlations based on shared metabolic pathways. Biomarker identification in research settings is additionally impeded by differences relating to experimental conditions and naming (nomenclature) of metabolites between research groups. The Metabolomics Society and International Union of Pure and Applied Chemistry (IUPAC) are active proponents of standardisation in methodology and nomenclature in this field.
Identifying biomarkers for clinical use: A major limitation of metabolomics as an emerging healthcare technology is the slow progress in identifying which metabolites may serve as potentially useful biomarkers. This is complicated by the dynamic nature of metabolism, which can be substantially influenced by genetic differences and environmental exposures. Moreover, prior to being incorporated into clinical practice, clinical validation is required to determine whether a given metabolic test is sufficiently sensitive to identify those at risk or affected by a disease and sufficiently specific to a certain disease process.
Establishing standards: Only once biologically significant metabolites have been identified and can be reproducibly quantified can reference ranges be established, which indicate the minimum and maximum values for a given test that would be expected in healthy individuals. It is important that these ranges are sufficiently broad to allow for natural differences between individuals, and that potential sources of variation within an individual, such as the effects of diurnal variation, are also taken into consideration.
Metabolomics has exciting potential to improve our understanding of disease mechanisms and to yield clinically useful biomarkers. In view of the vast numbers of metabolites that can be simultaneously measured in a single biological sample, it is tempting to speculate that metabolomics may form the basis of a broad-spectrum screening tool in the future. However, there is some way to go before whole metabolome analysis is routinely performed in clinical setting.
Going forward, it is essential that technical challenges are overcome, to hasten the identification and clinical validation of biologically important metabolites. Once achieved, since spectroscopy is already an established technique in the public sector, whole metabolome analyses could be integrated into clinical practice with relative ease, and metabolomics may yet prove to be a cost-effective technology that is advantageous to patient care in the future.