Periodic Reporting for period 1 - HUMAN (Harmonising and Unifying Blood Metabolomic Analysis Networks)
Reporting period: 2023-02-01 to 2025-01-31
The main objective of the project is to identify current limitations and discrepancies of metabolomics datasets by studying how variances in metabolomics workflows can change outcomes in terms of metabolite annotation and identification, metabolome coverage, etc. with further aim to propose solutions for cross-cohort data integration and facilitate quality control schemes.
Apart from this, a major scope of the project is to investigate the potentials of Blood Microsampling (BμS) in biomarker discovery and to consolidate, create and implement bioanalytical methods and data analysis methods and tools using BμS in metabolomics studies that can be valuable in health and wellness monitoring.
The specific objectives for the project are summarised in the following:
1) Build a multidisciplinary consortium with the critical mass to address the limitations in human LC-MS-based blood metabolomics, such as result reproducibility and research fragmentation.
2) Perform cross-laboratory comparisons to identify the sources of variability in all steps of metabolomics studies: preanalytical, sample preparation, LC-MS analysis, data quality assessment, normalization, statistical processing, pathway analysis, and biochemical interpretation.
3) Promote the field towards effective integration and co-evaluation of data collected by various labs, improving consistency of findings, data reporting, database implementation, reproducibility, and re-usability of data. Identify bottlenecks in the integration of metabolomics data (pan-cohorts).
4) Investigate the implementation of novel blood microsampling techniques in clinical metabolomics and establish workflows for meaningful blood micro sample analysis in biomarker discovery and health monitoring.
5) Provide proof of concept for the utility of the developed tools by implementing two case studies on human cohorts following exercise and nutritional intervention.
Apart from this, a major scope of the project is to investigate the potentials of Blood Microsampling (BμS) in biomarker discovery and to consolidate, create and implement bioanalytical methods and data analysis methods and tools using BμS in metabolomics studies that can be valuable in health and wellness monitoring.
The specific objectives for the project are summarised in the following:
1) Build a multidisciplinary consortium with the critical mass to address the limitations in human LC-MS-based blood metabolomics, such as result reproducibility and research fragmentation.
2) Perform cross-laboratory comparisons to identify the sources of variability in all steps of metabolomics studies: preanalytical, sample preparation, LC-MS analysis, data quality assessment, normalization, statistical processing, pathway analysis, and biochemical interpretation.
3) Promote the field towards effective integration and co-evaluation of data collected by various labs, improving consistency of findings, data reporting, database implementation, reproducibility, and re-usability of data. Identify bottlenecks in the integration of metabolomics data (pan-cohorts).
4) Investigate the implementation of novel blood microsampling techniques in clinical metabolomics and establish workflows for meaningful blood micro sample analysis in biomarker discovery and health monitoring.
5) Provide proof of concept for the utility of the developed tools by implementing two case studies on human cohorts following exercise and nutritional intervention.
The consortium comprises groups of complementary scientific backgrounds with long expertise in the metabolomics field and the capacity to train and supervise the DCs. The network has organized two interlaboratory ring trials. In the first one, five analytical laboratories have received 1,300 reference standards of metabolites that are currently analyzed by the same chromatographic method and by the established methods of each lab. A thorough investigation of the various sources inducing variation in the obtained data will be performed. The different bioanalytical labs of the network have worked in the analysis of dried-blood specimens and have optimized the preanalytical parameters and the analytical conditions for the untargeted profiling of dried-blood samples based on their instrumentation and complementary methodologies. In parallel, a thorough investigation of the related literature has been performed, and an open access library has been created with this material classified based on their topic in the resources space of the network’s webpage.
Two publications have also been published by the network as a product of this literature survey: 1) Targeted and untargeted metabolomics and lipidomics in dried blood microsampling: Recent applications and perspectives P.Couacault et al (https://doi.org/10.1002/ansa.202400002 ), 2) Volumetric Absorptive Microsampling in the Analysis of Endogenous Metabolites, D. Marques de Sá e Silva et al ( https://doi.org/10.3390/metabo13101038(opens in new window))
Optimisation studies in the untargeted analysis of dried blood samples have been performed under a pilot study involving samples from 10 volunteers with 3 different microsampling devices together with conventional blood samples.
Results have been announced in scientific conferences: in total fourteen presentations at international conferences have been presented.Two original publication has been produced :
1) LC-MS-Based Global Metabolic Profiles of Alternative Blood Specimens Collected by Microsampling, Thaitumu et al, Metabolites 2025, 15, 62 https://doi.org/10.3390/metabo15010062(opens in new window)
2) Highly reliable LC-MS lipidomics database for efficient human plasma profiling based on NIST SRM 1950, Martínez et al, J.of Lipid Res, 2024, 65, 11 https://doi.org/10.1016/j.jlr.2024.100671(opens in new window)
Furthermore, 5 further publications or book chapters are in preparation or already submitted:
The group from the Physical Education and Sport Science AUTh department has designed and got approval for two studies to collect blood samples from healthy volunteers who will be subjected to high-intensity interval exercise and a nutritional intervention. The first study is being performed, 24 volunteers have been recruited, and sample collection is ongoing.
Two publications have also been published by the network as a product of this literature survey: 1) Targeted and untargeted metabolomics and lipidomics in dried blood microsampling: Recent applications and perspectives P.Couacault et al (https://doi.org/10.1002/ansa.202400002 ), 2) Volumetric Absorptive Microsampling in the Analysis of Endogenous Metabolites, D. Marques de Sá e Silva et al ( https://doi.org/10.3390/metabo13101038(opens in new window))
Optimisation studies in the untargeted analysis of dried blood samples have been performed under a pilot study involving samples from 10 volunteers with 3 different microsampling devices together with conventional blood samples.
Results have been announced in scientific conferences: in total fourteen presentations at international conferences have been presented.Two original publication has been produced :
1) LC-MS-Based Global Metabolic Profiles of Alternative Blood Specimens Collected by Microsampling, Thaitumu et al, Metabolites 2025, 15, 62 https://doi.org/10.3390/metabo15010062(opens in new window)
2) Highly reliable LC-MS lipidomics database for efficient human plasma profiling based on NIST SRM 1950, Martínez et al, J.of Lipid Res, 2024, 65, 11 https://doi.org/10.1016/j.jlr.2024.100671(opens in new window)
Furthermore, 5 further publications or book chapters are in preparation or already submitted:
The group from the Physical Education and Sport Science AUTh department has designed and got approval for two studies to collect blood samples from healthy volunteers who will be subjected to high-intensity interval exercise and a nutritional intervention. The first study is being performed, 24 volunteers have been recruited, and sample collection is ongoing.
The project has produced new methods of metabolic profiling analysis of Dried Blood microsamples , by different instrumentation and techniques (metabolomics, lipidomics, HILIC-MS, CE-MS)
In addition new features have been developed for XCMS software for MS metabolomics data, preprocessing and analysis was expanded to improve efficient handling of rich and large-scale data sets. The respective functionality was added to the “Spectra” and “xcms” R packages.
In addition new features have been developed for XCMS software for MS metabolomics data, preprocessing and analysis was expanded to improve efficient handling of rich and large-scale data sets. The respective functionality was added to the “Spectra” and “xcms” R packages.