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A human pan-disease blood atlas of the circulating proteome

Science, 2025

Álvez M., Bergström S., Kenrick J., Johansson E., Åberg M., Akyildiz M., Altay O., Sköld H., Antonopoulos K., Apostolakis E., Balcioglu Y., Bergström A., Bergström G., Björkander S., Brage S., Brodin P., Butler L., Cajander S., Danielsson H., Dayangac M., Dinler-Doganay G., Doğanay L., Enblad G., Enblad M., Fagerberg L., Falck-Jones S., Färnert A., Forsberg M., Gonzalez L., Gummesson A., Gunnarsson K., Gunnarsson I., Gyllensten U., Hesselager G., Hober A., Höglund M., Holmqvist M., Horuluoglu B., Hultgren R., Iglesias M., Janols H., Johansson F., Johnsson A., Klareskog L., Kotol D., Kull I., Kvarnström M., Lautenbach M., Liljedahl U., Lindman H., Lindskog C., Lipcsey M., Lundberg I., Mardinoglu A., Melén E., Meng L., Merritt A., Mulder J., Nguyen M., Nordlund J., Norrby-Teglund A., Notarnicola A., Nowak P., Odeberg J., Oksvold P., Olsson T., Padyukov L., Pauksens K., Piehl F., Pin E., Pontén F., Rameika N., Reepalu A., Roy J., Schwenk J., Sen M., Siika A., Simonson O., Sivertsson ?., Sjöblom T., Sjöstedt E., Skoglund L., Smed-Sörensen A., Sondén K., Sönnerborg A., Stålberg K., Strålin K., Sundén-Cullberg J., Sundling C., Sutantiwanichkul T., Svedman F., Svensson M., Svenungsson E., Lakshmikanth T., Tran-Minh K., Türkez H., Unge C., Venge P., Wahren-Herlenius M., Woessmann J., Yang H., Yeşilkaya U., Yuan M., Zeybel M., Zhang C., Zhong W., Zwahlen M., von Feilitzen K., Nilsson P., Edfors F., Uhlén M.

Disease areaApplication areaSample typeProducts
Wider Proteomics Studies
Pathophysiology
Patient Stratification
Plasma
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Abstract

The human blood proteome provides a holistic readout of health states through the assessment of thousands of circulating proteins. Here, we present a pan-disease resource to enable the study of diverse disease phenotypes within a harmonized proteomics dataset. By profiling protein concentrations across 59 diseases and healthy cohorts, we identified proteins associated with age, sex, and BMI, as well as disease-specific signatures. This study highlights shared and distinct protein patterns across conditions, demonstrating the power of a unified proteomics approach to uncover biological insights. The dataset, covering 8,262 individuals and up to 5,416 proteins, serves as an online resource for exploring disease-specific protein profiles and advancing precision medicine research.

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