UK Consortium for MetAbolic Phenotyping (MAP UK)
Lead Research Organisation:
Imperial College London
Department Name: Surgery and Cancer
Abstract
Metabolic phenotyping is the study of human health by observation of the chemical composition of biofluids (e.g. urine and blood) and tissues. Advanced technologies are used to measure the amounts of thousands of metabolites in human samples in an unbiased "untargeted" manner, generating individual profiles (or chemical "fingerprints") that represent the individual's metabolic phenotype. A phenotype is the product of a person's genes and the influence of numerous environmental factors including diet, lifestyle, occupation, stress, exercise, and exposures (e.g. to medications, toxins, pollutants, etc). A phenotype can be understood and measured by direct measurement of a person's metabolites, either in circulation (e.g. in blood), localised to a tissue (e.g. a muscle biopsy), or as the end products of metabolism (e.g. urine). Metabolic phenotyping is key as an emerging technology used to increase our understanding of human health and disease, with applications in the prediction of disease predisposition, onset, and potential for recovery, as well as the power to guide personalised therapies and clinical interventions where needed (a field called "stratified medicine").
To be used to its full potential, metabolic phenotyping requires collaboration among many specialist areas of science. Clinicians, epidemiologists, and other scientists who wish to use phenotyping tools to investigate specific scientific questions (related to health in individuals, populations, or the underlying chemical mechanisms of diseases) must work together with technologists and analytical chemists who understand biofluid handling and measurement, data scientists (e.g. bioinformaticians) who can make sense of large amounts of complex data, and biochemists who can interpret that data. With many different ways to raise hypotheses, design studies, measure biofluids, and analyse data, metabolic phenotyping is a field of specialists who use specialist tools to answer specific questions. While it is not practical for one person to master all of these disciplines, an appreciation for the whole process is vital to ensure efficient use of powerful technologies and precious human samples, and communication among specialists is vital to achieving positive and impactful research outcomes.
With this in mind, we aim to advance metabolic phenotyping for the benefit of UK scientists by driving cooperation, collaborative development, and education within the framework of a partnership among leading UK research institutions. We will organise and share specialist methods for metabolic measurement and data analysis among expert technologists, analytical chemists, and data scientists, as well as improve the visibility and availability of these tools to the UK research community. We will start our programme by listening to the UK research community, identifying their phenotyping needs and matching them to potential technological/methodological solutions held within our partnership. We will ensure the availability of these solutions by cross-site training, developing a strong network of research capability and capacity within the UK. Where gaps in our collective abilities exist, analytical and informatics development programmes will work to address those specific needs as well as maximise the obtainable value from phenotyping data. We will test and demonstrate our collective abilities by turning this newly organised resource toward the study of example applications, and we will conclude our programme by presenting our work and harmonised platform for phenotyping back to the UK research community. We will augment this cycle with external training of all user groups to raise awareness for the strengths, limitations, specific considerations and diversity of phenotyping approaches, enabling more efficient, more impactful, and higher quality human health and disease research throughout the UK.
To be used to its full potential, metabolic phenotyping requires collaboration among many specialist areas of science. Clinicians, epidemiologists, and other scientists who wish to use phenotyping tools to investigate specific scientific questions (related to health in individuals, populations, or the underlying chemical mechanisms of diseases) must work together with technologists and analytical chemists who understand biofluid handling and measurement, data scientists (e.g. bioinformaticians) who can make sense of large amounts of complex data, and biochemists who can interpret that data. With many different ways to raise hypotheses, design studies, measure biofluids, and analyse data, metabolic phenotyping is a field of specialists who use specialist tools to answer specific questions. While it is not practical for one person to master all of these disciplines, an appreciation for the whole process is vital to ensure efficient use of powerful technologies and precious human samples, and communication among specialists is vital to achieving positive and impactful research outcomes.
With this in mind, we aim to advance metabolic phenotyping for the benefit of UK scientists by driving cooperation, collaborative development, and education within the framework of a partnership among leading UK research institutions. We will organise and share specialist methods for metabolic measurement and data analysis among expert technologists, analytical chemists, and data scientists, as well as improve the visibility and availability of these tools to the UK research community. We will start our programme by listening to the UK research community, identifying their phenotyping needs and matching them to potential technological/methodological solutions held within our partnership. We will ensure the availability of these solutions by cross-site training, developing a strong network of research capability and capacity within the UK. Where gaps in our collective abilities exist, analytical and informatics development programmes will work to address those specific needs as well as maximise the obtainable value from phenotyping data. We will test and demonstrate our collective abilities by turning this newly organised resource toward the study of example applications, and we will conclude our programme by presenting our work and harmonised platform for phenotyping back to the UK research community. We will augment this cycle with external training of all user groups to raise awareness for the strengths, limitations, specific considerations and diversity of phenotyping approaches, enabling more efficient, more impactful, and higher quality human health and disease research throughout the UK.
Technical Summary
The overarching goal of the partnership will be to develop, optimise, transfer, harmonise and validate efficient, high-quality research and training methods, specifically tailored to the growing need of high quality biomedical studies that require metabolic phenotyping. We propose to: i) conduct a comprehensive review of current capabilities and the requirements of the epidemiology community in relation to assays, computational workflows in collaboration with the epidemiology community in the UK and globally; ii) conduct a comprehensive assessment of compatibility and complementarity of analytical methods (including untargeted profiling and targeted quantitative methods), workflows and data processing pipelines and establish best practice; iii) develop untargeted method characterisation databases and novel targeted quantitative methods and protocols to meet gaps in molecular coverage of key disease-related pathways; iv) create a system for protocol and information exchange; v) develop a framework for Method harmonization, and coordination of results and databases; vi) validate the NMR-MS integrated analysis pipeline for comprehensive coverage of the metabolome in clinically-relevant cohorts; vii) improve capacity building and application of metabolic phenotyping in epidemiology through training, education and outreach. We envision this will create a core UK capability for delivering high quality metabolic phenotyping data to academics, clinicians and industry to serve the emerging priority area of population phenotyping. Ultimately this UK partnership will provide the network, tools and expertise to improve understanding of lifetime disease risks, provide a framework for making collective decisions for future disease and healthcare roadmaps and inform future global public health policies.
Planned Impact
The formation of an unprecedented network within the UK focused on small molecule phenotyping will benefit the UK immediately by creating an organised and governed structure for communication among and between leaders in this field and the broader UK research community. This partnership will provide a structure for receiving input on deeds and desires to support UK research, addressing those needs with dedicated development and training, and relaying new advances back to the UK research community, bringing the project full circle for maximum impact. Increased capability and capacity (including analytical methods and data analysis) will benefit phenotyping cohorts (including UK Biobank, ALSPAC and Born in Bradford) and delivery of new insights into disease and disease risk. Delivery of accelerated high-quality training programmes focused on instilling practical and theoretical competence in the metabolic phenotyping community will quickly increase the pool of analytical expertise in the UK and ensure the UK's place at the forefront of this field, and ensure further awareness of metabolic phenotyping in the clinical sector (NHS).
The UK technology industry will benefit in the medium term, including numerous phenotyping instrument manufacturers (see letters of support), with the UK academic partners working closely with industrial collaborators to optimize work flows and targeted assays, ultimately resulting in increased analytical efficiency and potentially commercialisable assays, methods and databases.
Longer term the development of a database of the complete phenotypic results for large cohort studies, along with relevant other-omics and metadata, housed in the EBI database will create a valuable resource for the UK research community. Combined data from multiple centres will facilitate replication and validation of candidate biomarkers for numerous diseases and will allow rapid identification of centre/population specific effects thereby improving the efficiency of the biomarker discovery pipeline. For rare diseases (where Birmingham hosts the centre for Rare Diseases), the increased power afforded by shared technologies and databases will, for the first time, allow collection of metabolic data across disparate centres and hence the interrogation of disease mechanisms - vital for comparing across rare diseases where a number of related genes may be involved and hence requiring further stratification of a patient group (e.g. lysosomal storage disorders). The open access policy adopted will provide opportunities for external validation of models and datasets improving the quality of data analysis. Knowledge of biomarkers of increased risk within the UK population will also enhance the potential for national screening, where this is applicable, to provide assistance to potentially high risk sectors of the population, particularly in the fields of cancer, cardiovascular disease and mental health where there is increased demand for nationwide screening programmes. In addition it will offer ways to influence government policy by highlighting significant areas of environmental or societal changes which could benefit the health of the nation. Money spent on these more preventative forms of disease management could have significant impact upon healthcare spending. Biomarkers may offer opportunities to develop new therapeutic agents in addition to the creation of the technologies to implement assessment for these markers. Pharma companies may utilise this knowledge to change the biological pathways in which they focus research, resulting in the potential for a more effective drug discovery pipeline. This would be significant for the UK economy given the central importance of both the pharmaceutical industry (e.g. GlaxoSmithKline, AstraZeneca) and biotechnology (e.g. Medimmune, Selcia, Astex) to the UK economy.
The UK technology industry will benefit in the medium term, including numerous phenotyping instrument manufacturers (see letters of support), with the UK academic partners working closely with industrial collaborators to optimize work flows and targeted assays, ultimately resulting in increased analytical efficiency and potentially commercialisable assays, methods and databases.
Longer term the development of a database of the complete phenotypic results for large cohort studies, along with relevant other-omics and metadata, housed in the EBI database will create a valuable resource for the UK research community. Combined data from multiple centres will facilitate replication and validation of candidate biomarkers for numerous diseases and will allow rapid identification of centre/population specific effects thereby improving the efficiency of the biomarker discovery pipeline. For rare diseases (where Birmingham hosts the centre for Rare Diseases), the increased power afforded by shared technologies and databases will, for the first time, allow collection of metabolic data across disparate centres and hence the interrogation of disease mechanisms - vital for comparing across rare diseases where a number of related genes may be involved and hence requiring further stratification of a patient group (e.g. lysosomal storage disorders). The open access policy adopted will provide opportunities for external validation of models and datasets improving the quality of data analysis. Knowledge of biomarkers of increased risk within the UK population will also enhance the potential for national screening, where this is applicable, to provide assistance to potentially high risk sectors of the population, particularly in the fields of cancer, cardiovascular disease and mental health where there is increased demand for nationwide screening programmes. In addition it will offer ways to influence government policy by highlighting significant areas of environmental or societal changes which could benefit the health of the nation. Money spent on these more preventative forms of disease management could have significant impact upon healthcare spending. Biomarkers may offer opportunities to develop new therapeutic agents in addition to the creation of the technologies to implement assessment for these markers. Pharma companies may utilise this knowledge to change the biological pathways in which they focus research, resulting in the potential for a more effective drug discovery pipeline. This would be significant for the UK economy given the central importance of both the pharmaceutical industry (e.g. GlaxoSmithKline, AstraZeneca) and biotechnology (e.g. Medimmune, Selcia, Astex) to the UK economy.
Organisations
Publications
Israr MZ
(2021)
Association of gut-related metabolites with outcome in acute heart failure.
in American heart journal
Theodoridis G
(2023)
Ensuring Fact-Based Metabolite Identification in Liquid Chromatography-Mass Spectrometry-Based Metabolomics
in Analytical Chemistry
Broeckling C
(2023)
Current Practices in LC-MS Untargeted Metabolomics: A Scoping Review on the Use of Pooled Quality Control Samples
in Analytical Chemistry
Correia GDS
(2022)
1H NMR Signals from Urine Excreted Protein Are a Source of Bias in Probabilistic Quotient Normalization.
in Analytical chemistry
Takis PG
(2021)
A Computationally Lightweight Algorithm for Deriving Reliable Metabolite Panel Measurements from 1D 1H NMR.
in Analytical chemistry
Albreht A
(2022)
Structure Elucidation and Mitigation of Endogenous Interferences in LC-MS-Based Metabolic Profiling of Urine.
in Analytical chemistry
Sands CJ
(2021)
Representing the Metabolome with High Fidelity: Range and Response as Quality Control Factors in LC-MS-Based Global Profiling.
in Analytical chemistry
Viant M
(2024)
Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice
in Archives of Toxicology
Takis P
(2022)
NMRpQuant : an automated software for large scale urinary total protein quantification by one-dimensional 1H NMR profiles
in Bioinformatics
Wolfer AM
(2021)
peakPantheR, an R package for large-scale targeted extraction and integration of annotated metabolic features in LC-MS profiling datasets.
in Bioinformatics (Oxford, England)
Inglese P
(2022)
Mass recalibration for desorption electrospray ionization mass spectrometry imaging using endogenous reference ions.
in BMC bioinformatics
Lima C
(2022)
Simultaneous Raman and infrared spectroscopy: a novel combination for studying bacterial infections at the single cell level.
in Chemical science
Augustin A
(2023)
Faecal metabolite deficit, gut inflammation and diet in Parkinson's disease: Integrative analysis indicates inflammatory response syndrome.
in Clinical and translational medicine
Goodacre R
(2019)
The blind men and the elephant: challenges in the analysis of complex natural mixtures.
in Faraday discussions
Vilca-Melendez S
(2021)
1H Nuclear Magnetic Resonance: A Future Approach to the Metabolic Profiling of Psychedelics in Human Biofluids?
in Frontiers in psychiatry
Takis P
(2023)
Mapping of 1 H NMR chemical shifts relationship with chemical similarities for the acceleration of metabolic profiling: Application on blood products
in Magnetic Resonance in Chemistry
Roberts I
(2023)
Quantitative LC-MS study of compounds found predictive of COVID-19 severity and outcome.
in Metabolomics : Official journal of the Metabolomic Society
Winder CL
(2022)
Providing metabolomics education and training: pedagogy and considerations.
in Metabolomics : Official journal of the Metabolomic Society
Finch JP
(2022)
Spectral binning as an approach to post-acquisition processing of high resolution FIE-MS metabolome fingerprinting data.
in Metabolomics : Official journal of the Metabolomic Society
De Jonge NF
(2023)
MS2Query: reliable and scalable MS2 mass spectra-based analogue search.
in Nature communications
Garcia-Perez I
(2020)
RETRACTED ARTICLE: Dietary metabotype modelling predicts individual responses to dietary interventions.
in Nature food
Blaise BJ
(2021)
Statistical analysis in metabolic phenotyping.
in Nature protocols
Yurekten O
(2023)
MetaboLights: open data repository for metabolomics
in Nucleic Acids Research
Dehghan A
(2022)
Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer's disease.
in Proceedings of the National Academy of Sciences of the United States of America
Description | Online discussion session on molecular phenomics at the Patient Experience Research Centre (PERC) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | An online discussion was hosted on Tuesday 14th September 2021 (5pm to 6.30pm) via Zoom Pro and was attended by 29 members of the public from a wide range of backgrounds The aim of this particular online session was to: -Introduce the Imperial Biomedical Research Centre and the Molecular Phenomics Theme (5 mins) -Provide an overview of molecular phenomics (15 mins) -Provide real life examples of how molecular phenomics can improve clinical care, population health and personalised medicine (10 mins) -Give attendees an opportunity to ask questions (15 mins) -Facilitate small group discussions |
Year(s) Of Engagement Activity | 2021 |
URL | https://spiral.imperial.ac.uk/bitstream/10044/1/94138/7/Public%20Involvement%20Insight%20Report%20-M... |