Privacy-preserving multicenter differential protein abundance analysis with FedProt

Burankova Y, Abele M, Bakhtiari M, von Toerne C, Barth TK, Schweizer L, Giesbertz P, Schmidt JR, Kalkhof S, Müller-Deile J, van Veelen PA, Mohammed Y, Hammer E, Arend L, Adamowicz K, Laske T, Hartebrodt A, Frisch T, Meng C, Matschinske J, Späth J, Röttger R, Schwämmle V, Hauck SM, Lichtenthaler SF, Imhof A, Mann M, Ludwig C, Kuster B, Baumbach J, Zolotareva O (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Nature Computational Science Nature Research

DOI: 10.1038/s43588-025-00832-7

Abstract

Quantitative mass spectrometry has revolutionized proteomics by enabling simultaneous quantification of thousands of proteins. Pooling patient-derived data from multiple institutions enhances statistical power but raises serious privacy concerns. Here we introduce FedProt, the first privacy-preserving tool for collaborative differential protein abundance analysis of distributed data, which utilizes federated learning and additive secret sharing. In the absence of a multicenter patient-derived dataset for evaluation, we created two: one at five centers from E. coli experiments and one at three centers from human serum. Evaluations using these datasets confirm that FedProt achieves accuracy equivalent to the DEqMS method applied to pooled data, with completely negligible absolute differences no greater than 4 × 10−12. By contrast, −log10P computed by the most accurate meta-analysis methods diverged from the centralized analysis results by up to 25–26.

Authors with CRIS profile

Janina Müller-Deile Department of Medicine 4 – Nephrology and Hypertension Anne Hartebrodt

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) Universität Hamburg (UHH) DE Germany (DE) Fraunhofer-Institut für Zelltherapie und Immunologie (IZI) DE Germany (DE) Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich DE Germany (DE) Ludwig-Maximilians-Universität (LMU) DE Germany (DE) Max-Planck-Institut für Biochemie / Max Planck Institute of Biochemistry DE Germany (DE) Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) DE Germany (DE) Leiden University Medical Center NL Netherlands (NL) Universitätsmedizin Greifswald / Universitätsklinikum Greifswald DE Germany (DE) University of Southern Denmark / Syddansk Universitet DK Denmark (DK)

How to cite

APA:

Burankova, Y., Abele, M., Bakhtiari, M., von Toerne, C., Barth, T.K., Schweizer, L.,... Zolotareva, O. (2025). Privacy-preserving multicenter differential protein abundance analysis with FedProt. Nature Computational Science. https://doi.org/10.1038/s43588-025-00832-7

MLA:

Burankova, Yuliya, et al. "Privacy-preserving multicenter differential protein abundance analysis with FedProt." Nature Computational Science (2025).

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