María Bueno Álvez, Sofia Bergström, Josefin Kenrick, Emil Johansson, Mikael Åberg, Murat Akyıldız, Özlem Altay, Hilda Sköld, Κωνσταντίνος Αντωνόπουλος, Emmanouil Apostolakis, Yasin Hasan Balcıoğlu, Anna Bergström, Göran Bergström, Sophia Björkander, Suzanne Egyhazi Brage, Petter Brodin, Lynn M. Butler, Sara Cajander, Hanna Danielsson, Murat Dayangaç, Gizem Dinler Doğanay, Levent Doğanay, Gunilla Enblad, Malin Enblad, Linn Fagerberg, Sara Falck‐Jones, Anna Färnert, Mattias Forsberg, Laura González‐Aguilera, Anders Gummesson, Karin Gunnarsson, Iva Gunnarsson, Ulf Gyllensten, Göran Hesselager, Andreas Hober, Martin Höglund, Marie Holmqvist, Begum Horuluoglu, Rebecka Hultgren, María Jesús Iglesias, Helena Janols, Fredric Johansson, Anette Johnsson, Lars Klareskog, David Kotol, Inger Kull, Marika Kvarnström, Maximilian Julius Lautenbach, Ulrika Liljedahl, Henrik Lindman, Cecilia Lindskog, Miklós Lipcsey, Ingrid E. Lundberg, Adil Mardinoğlu, Erik Melén, Lingqi Meng, Anne‐Sophie Merritt, Jan Mulder, M. Nguyen, Jessica Nordlund, Anna Norrby‐Teglund, Antonella Notarnicola, Piotr Nowak, Jacob Odeberg, Per Oksvold, Tomas Olsson, Leonid Padyukov, Karlis Pauksens, Fredrik Piehl, Elisa Pin, Fredrik Pontén, Natallia Rameika, Anton Reepalu, Joy Roy, Jochen M. Schwenk, Meltem Sen, Antti Siika, Oscar E. Simonson, Åsa Sivertsson, Tobias Sjöblom, Evelina Sjöstedt, Lovisa Skoglund, Anna Smed‐Sörensen, Klara Sondén, Anders Sönnerborg, Karin Stålberg, Kristoffer Strålin, Jonas Sundén‐Cullberg, Christopher Sundling, Thanadol Sutantiwanichkul, Fernanda Costa Svedman, Mattias Svensson, Elisabet Svenungsson, Tadepally Lakshmikanth, Khue Hua Tran-Minh, Hasan Türkez, Christian Unge, Per Venge, Marie Wahren‐Herlenius, Jakob Woessmann
The human blood proteome provides a holistic readout of health states through the assessment of thousands of circulating proteins. In this study, 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 body mass index, 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 8262 individuals and up to 5416 proteins, serves as an online resource for exploring disease-specific protein profiles and advancing precision medicine research.