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Ahadi, S.* ; Babacic, H.* ; Cantrell, L.S.* ; Hornburg, D.* ; Muller-Reif, J.B.* ; Dagley, L.F.* ; Guerrera, I.C.* ; Albrecht, V.* ; Edfors, F.* ; Yu, X.* ; Sun, Z.* ; Moritz, R.L.* ; Schmidt, F.* ; Hauck, S.M. ; Deutsch, E.W.* ; Omenn, G.S.* ; Schwenk, J.M.* ; Geyer, P.E.*

Unlockingthe circulating proteome: Toward clinical translation.

J. Proteome Res. 25, 4367-4379 (2026)
DOI
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Blood-based proteomics; Clinical proteomics; Biomarkers; Machine learning; Population-scaleproteomics; Multiomics integration; Early diseasedetection; Therapeutic monitoring; Patient stratification; Causal inference; Dna; Biology
ISSN (print) / ISBN 1535-3893
e-ISSN 1535-3907
Zeitschrift Journal of Proteome Research
Quellenangaben Band: 25, Heft: 9, Seiten: 4367-4379 Artikelnummer: , Supplement: ,
Verlag American Chemical Society (ACS)
Verlagsort 1155 16th St, Nw, Washington, Dc 20036 Usa
Begutachtungsstatus Peer reviewed
Institut(e) Core Facility Metabolomics and Proteomics (CF-MPC)