Unlockingthe Circulating Proteome: Toward ClinicalTranslation

Abstract Blood-based proteomics is approaching a translational inflection point. Driven by advances in measurement technologies, rapid expansion of analytical capabilities, and growing adoption across research and medical communities, there is increasing demand for clinically actionable biomarkers. As the field transitions away from purely large-scale discovery-oriented studies toward more informed, targeted, application-driven analyses, the generation of proteomic data is no longer the bottleneck. Instead, the central challenge is to translate these measurements into robust, reproducible, and clinically meaningful insights. In this Review, we assess recent technological and methodological developments, evaluate persistent preanalytical and interpretative limitations, and outline the key steps required for clinical translation. We focus on three deeply interconnected dimensions: the capabilities and constraints of current measurement platforms, the role of computational and machine learning approaches in extracting biological and clinical signals, and the emergence of large-scale population studies that create new opportunities for validation and generalization. Finally, we discuss a forward-looking vision in which proteomics plays a central role in dynamic, multilayered omics frameworks, where integration with genomics, temporal profiling, and imaging can deepen our understanding of health, disease, and therapeutic response.

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Publication Details

Journal
Journal of Proteome Research
Published
2026-08-17
DOI
https://doi.org/10.1021/acs.jproteome.6c00277
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Unlockingthe Circulating Proteome: Toward ClinicalTranslation

Haris Babačić, Gilbert S. Omenn, Laura F. Dagley, Daniel Hornburg et al.
Journal of Proteome Research
Advanced Proteomics Techniques and Applications
article

Unlockingthe Circulating Proteome: Toward ClinicalTranslation

Haris Babačić, Gilbert S. Omenn, Laura F. Dagley, Daniel Hornburg, Stefanie M. Hauck, Sara Ahadi, Jochen M. Schwenk, Robert L. Moritz, Xiaobo Yu, Lee S. Cantrell, Albrecht, Zhi Sun, Ida Chiara Guerrera, Johannes B. Müller-Reif, Philipp E. Geyer, Frank Schmidt, Eric W. Deutsch, Fredrik Edfors
article en

Abstract

Abstract Blood-based proteomics is approaching a translational inflection point. Driven by advances in measurement technologies, rapid expansion of analytical capabilities, and growing adoption across research and medical communities, there is increasing demand for clinically actionable biomarkers. As the field transitions away from purely large-scale discovery-oriented studies toward more informed, targeted, application-driven analyses, the generation of proteomic data is no longer the bottleneck. Instead, the central challenge is to translate these measurements into robust, reproducible, and clinically meaningful insights. In this Review, we assess recent technological and methodological developments, evaluate persistent preanalytical and interpretative limitations, and outline the key steps required for clinical translation. We focus on three deeply interconnected dimensions: the capabilities and constraints of current measurement platforms, the role of computational and machine learning approaches in extracting biological and clinical signals, and the emergence of large-scale population studies that create new opportunities for validation and generalization. Finally, we discuss a forward-looking vision in which proteomics plays a central role in dynamic, multilayered omics frameworks, where integration with genomics, temporal profiling, and imaging can deepen our understanding of health, disease, and therapeutic response.

Journal of Proteome Research
Centre National de la Recherche Scientifique (FR), Karolinska University Hospital (SE), Inserm (FR), The University of Melbourne (AU), Walter and Eliza Hall Institute of Medical Research (AU), Cornell University (US), University of Michigan (US), Center for Environmental Health (US), Karolinska Institutet (SE), Institute for Systems Biology (US), InfoConsult (Germany) (DE), Manning Applied Technology (United States) (US), InSysBio (Russia) (RU), Galorath (United States) (US), Max Planck Institute of Psychiatry (DE), Beijing Proteome Research Center (CN), KTH Royal Institute of Technology (SE)
Knut och Alice Wallenbergs Stiftelse, Max-Planck-Gesellschaft, National Key Research and Development Program of China
Openalex Percentile: Top 19%
Advanced Proteomics Techniques and Applications
DOISourceOpenAlex
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