Tackling the translational challenges of multi-omics research in the realm of European personalised medicine: A workshop report

Oldoni, Emanuela; Saunders, Gary; Bietrix, Florence; Bermejo, María Laura García; Niehues, Anna; Hoen, Peter A.C. ‘t; Nordlund, Jessica; Hajdúch, Marián; Scherer, Andreas; Kivinen, Katja; Pitkänen, Esa; Mäkela, Tomi Pekka; Gut, Ivo; Scollen, Serena; Kozera, Łukasz; Esteller, Manel; Shi, Leming; Ussi, Anton; Andreu, Antonio Lorenzo; Gool, Alain J. van

doi:10.3389/fmolb.2022.974799

Cited by 8 publications

(12 citation statements)

References 43 publications

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“…This remains the case when measuring repeated temporal samples: metabolism is a highly dynamic process, with rates of metabolic flux/activity and turnover of proteins often undergoing rapid change in response to physiological perturbation despite minimal changes to overall concentration or abundance, with concentrations and activity not always aligning [ 45 ]. Therefore, traditional measures of the metabolome/proteome inevitably miss important information, key to inferring mechanistic understanding, and which helps to explain the relatively slow translation of OMICs outcomes to clinical implementation [ 46 ]. However, this obstacle can potentially be overcome.…”

Section: Stable Isotope Tracer ‘Omics (“Sitomics”) In Exercise Biomed...mentioning

confidence: 99%

Metabolomic and proteomic applications to exercise biomedicine

Wilkinson,

Crossland,

Atherton

2024

Translational Exercise Biomedicine

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Objectives ‘OMICs encapsulates study of scaled data acquisition, at the levels of DNA, RNA, protein, and metabolite species. The broad objectives of OMICs in biomedical exercise research are multifarious, but commonly relate to biomarker development and understanding features of exercise adaptation in health, ageing and metabolic diseases. Methods This field is one of exponential technical (i.e., depth of feature coverage) and scientific (i.e., in health, metabolic conditions and ageing, multi-OMICs) progress adopting targeted and untargeted approaches. Results Key findings in exercise biomedicine have led to the identification of OMIC features linking to heritability or adaptive responses to exercise e.g., the forging of GWAS/proteome/metabolome links to cardiovascular fitness and metabolic health adaptations. The recent addition of stable isotope tracing to proteomics (‘dynamic proteomics’) and metabolomics (‘fluxomics’) represents the next phase of state-of-the-art in ‘OMICS. Conclusions These methods overcome limitations associated with point-in-time ‘OMICs and can be achieved using substrate-specific tracers or deuterium oxide (D2O), depending on the question; these methods could help identify how individual protein turnover and metabolite flux may explain exercise responses. We contend application of these methods will shed new light in translational exercise biomedicine.

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Section: Stable Isotope Tracer ‘Omics (“Sitomics”) In Exercise Biomed...mentioning

confidence: 99%

Metabolomic and proteomic applications to exercise biomedicine

Wilkinson,

Crossland,

Atherton

2024

Translational Exercise Biomedicine

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“…Furthermore, the main bottleneck of any multi-omics study is the analysis of the obtained data sets. A multi-omics approach requires an integration of multiple data types obtained at various molecular levels from the genome to metabolome, and their relation with the clinical data [ 64 , 83 , 84 ]. The population diversity and the lack of stated regulated procedures and standards for such omics-tests may be another reason for the slow translation of their findings to the medicine.…”

Section: Possible Ways Of a Personalized Metabolomics Implementationmentioning

confidence: 99%

Current State and Future Perspectives on Personalized Metabolomics

et al. 2023

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Metabolomics is one of the most promising ‘omics’ sciences for the implementation in medicine by developing new diagnostic tests and optimizing drug therapy. Since in metabolomics, the end products of the biochemical processes in an organism are studied, which are under the influence of both genetic and environmental factors, the metabolomics analysis can detect any changes associated with both lifestyle and pathological processes. Almost every case-controlled metabolomics study shows a high diagnostic accuracy. Taking into account that metabolomics processes are already described for most nosologies, there are prerequisites that a high-speed and comprehensive metabolite analysis will replace, in near future, the narrow range of chemical analyses used today, by the medical community. However, despite the promising perspectives of personalized metabolomics, there are currently no FDA-approved metabolomics tests. The well-known problem of complexity of personalized metabolomics data analysis and their interpretation for the end-users, in addition to a traditional need for analytical methods to address the quality control, standardization, and data treatment are reported in the review. Possible ways to solve the problems and change the situation with the introduction of metabolomics tests into clinical practice, are also discussed.

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“…[30] Issues such as budgetary constraints and privacy concerns lead to decreased data harmonization across institutions, resulting in lower reliability of results. [30] Data integration is another significant challenge in multiomics analysis. With the diverse signal and noise of different data modalities, increased compute and expert biological interpretation are often needed but often lacking.…”

Section: Introductionmentioning

confidence: 99%

Accelerating precision medicine: a proposed framework for large-scale multiomics data integrity, interoperability, analysis, and collaboration in biomedical discovery

Sriram,

Conard,

Rosenberg

et al. 2024

Preprint

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Objective: To identify and define a process and framework for biomedical discovery research. Our study aim was to characterize the biomedical discovery lifecycle across data modalities and professional stakeholders involved in biomedical research to address the multiomics data challenges of precision medicine. Materials and Methods: We recruited fifteen professionals from various biomedical roles and industries to participate in 60-minute semi-structured interviews, which involved an assessment of common challenges, needs, tasks, and data management methods and a brainstorm exercise to validate each professional's biomedical research process. We applied a qualitative analysis of individual interviews using a constant comparative approach for emerging themes. Results: We found a general process of biomedical discovery across all participants that consisted of four key stages: data plan, data integrity, data analysis, and data-driven discovery. Within each stage of the process, participants highlighted their challenges and needs and emphasized the importance of data integrity and interoperability, particularly during data hand-offs. The process extends across three general levels of data, including non-human, non-clinical human, and clinical human data, to define an overarching framework for biomedical discovery research. Conclusions: The proposed framework provides researchers with an opportunity to align workstreams and converge on a single process to conduct biomedical research across stakeholders and data types. Key opportunities were found that can be explored in the health technology space, including generative artificial intelligence, to help tackle multiomics data challenges to advance precision medicine.

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Tackling the translational challenges of multi-omics research in the realm of European personalised medicine: A workshop report

Cited by 8 publications

References 43 publications

Metabolomic and proteomic applications to exercise biomedicine

Metabolomic and proteomic applications to exercise biomedicine

Current State and Future Perspectives on Personalized Metabolomics

Accelerating precision medicine: a proposed framework for large-scale multiomics data integrity, interoperability, analysis, and collaboration in biomedical discovery

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