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| Item Type: | Article |
|---|---|
| Title: | Multi-cohort proteogenomic analyses reveal genetic effects across the proteome and diseasome |
| Creators Name: | Koprulu, Mine, Smith-Byrne, Karl, Ferolito, Brian Richard, Macdonald-Dunlop, Erin, Luan, Jian'an, Hedman, Åsa K., Ogamba, Chibuzor Franklin, Kuliesius, Jurgis, Repetto, Linda, Ramisch, Anna, Abbasi, Fahim, Ärnlöv, Johan, Assimes, Themistocles L., Björck, Hanna M., Björkander, Sophia, Böttcher, Morten, Butterworth, Adam Stuart, Chen, Zhengming, Cho, Kelly, Clarke, Robert Joseph, Cox, Simon Riddington, Czene, Kamila, Danesh, John, Dedoussis, George, Elmståhl, Sölve, Eriksson, Niclas, Eriksson, Per, Esko, Tõnu, Ferreiro-Iglesias, Aida, Franks, Paul William, Fu, Jingyuan, Gaziano, J Michael, Ghanbari, Mohsen, Gieger, Christian, Gilly, Arthur, Grallert, Harald, Gunter, Marc James, Gustafsson, Stefan, Göteson, Andreas, Hall, Per Frans Leonard, Hansson, Oskar, Harris, Sarah Elizabeth, Hayward, Caroline, Herder, Christian, Hernandez-Pacheco, Natalia, Hijazi, Ziad, Hillary, Robert F., Hopewell, Jemma Caroline, Hu, Shixian, Hwang, Shih-Jen, Jern, Christina, Johansson, Åsa, Jonsson, Lina, Kalnapenkis, Anette, Kerrison, Nicola Dorothy, Kho, Pik Fang, Klaric, Lucija, Kohleick, Leonhard, Kraft, Julia, Landén, Mikael, Levy, Daniel, Li, Liming, Lind, Lars, Long, Jirong, Mattsson-Carlgren, Niklas, Melén, Erik, Merid, Simon Kebede, Mertins, Philipp, Michaëlsson, Karl, Møller, Peter Loof, Murgia, Federico, Nyegaard, Mette, Park, Young-Chan, Pearson, Ewan, Peters, James, Petrie, John Ross, Png, Grace, Polašek, Ozren, Prins, Bram Peter, Ripke, Stephan, Roden, Michael, Rohde, Palle Duun, Said, Saredo, Shen, Xia, Schwenk, Jochen M., Siegbahn, Agneta, Smith, J. Gustav, Stanne, Tara M, Suhre, Karsten, Sundström, Johan, Thorand, Barbara, Valdes-Marquez, Elsa, Vallerga, Costanza L., van Meurs, Joyce B.J., Viñuela, Ana, Võsa, Urmo, Wallentin, Lars, Walters, Robin G., Wareham, Nicholas John, Weber, Joachim Eduard, Weersma, Rinse Karel, Wilson, James F., Winther, Simon, Yasmeen, Summaira, Zanetti, Daniela, Zeggini, Eleftheria, Zhao, Jing Hua, Zhernakova, Alexandra, Zhernakova, Daria V., Ziehm, Matthias, Kessler, Benedikt Mathias, Pereira, Alexandre C., Mälarstig, Anders, Pietzner, Maik and Langenberg, Claudia |
| Abstract: | Understanding the genetic regulation of circulating protein levels can provide new insights into disease mechanisms. Here, we present the largest proteogenomic study to date (n = 78,664 participants across 38 studies), identifying >24,000 protein quantitative trait loci (QTLs) associated with 1,116 proteins, acting near to (n = 5,040) or distant (n = 19,698) from the cognate gene. Using machine learning-guided effector gene assignment, we provide genetic evidence for pathways, cell types, and tissues that modulate circulating protein levels, highlighting N-linked glycosylation as an important regulatory pathway. We demonstrate that genetic instruments of protein production/function (“cis”) versus modulation (“trans”) reveal distinct phenotypic insights. We identify proteins as candidates for drug targets and engagement (e.g., plasma furin and cardiovascular diseases) by comparing cis-based genetic evidence with protein-disease associations. Systematic triangulation of trans-protein QTLs (pQTLs) with genetic and protein associations across many diseases highlights potential drug repurposing opportunities, e.g., tyrosine kinase 2 (TYK2) inhibitors for rheumatoid arthritis. Our multi-cohort meta-analyses generate proteogenomic insights into disease mechanisms and new treatment opportunities. |
| Source: | Cell |
| ISSN: | 0092-8674 |
| Publisher: | Cell Press |
| Date: | 6 May 2026 |
| Official Publication: | https://doi.org/10.1016/j.cell.2026.03.049 |
| PubMed: | View item in PubMed |
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