Multi-cohort proteogenomic analyses reveal genetic effects across the proteome and diseasome.
Koprulu M., Smith-Byrne K., Ferolito BR., Macdonald-Dunlop E., Luan J., Hedman ÅK., Ogamba CF., Kuliesius J., Repetto L., Ramisch A., Abbasi F., Ärnlöv J., Assimes TL., BeLOVE Study Group ., Björck HM., Björkander S., Böttcher M., Butterworth AS., Chen Z., Cho K., Clarke RJ., Cox SR., Czene K., Danesh J., Dedoussis G., Elmståhl S., Eriksson N., Eriksson P., Esko T., Estonian Biobank Research Team ., Ferreiro-Iglesias A., Franks PW., Fu J., Gaziano JM., Ghanbari M., Gieger C., Gilly A., Grallert H., Gunter MJ., Gustafsson S., Göteson A., Hall PFL., Hansson O., Harris SE., Hayward C., Herder C., Hernandez-Pacheco N., Hijazi Z., Hillary RF., Hopewell JC., Hu S., Hwang S-J., Jern C., Johansson Å., Jonsson L., Kalnapenkis A., Kerrison ND., Kho PF., Klaric L., Kohleick L., Kraft J., Landén M., Levy D., Li L., Lind L., Long J., Mattsson-Carlgren N., Melén E., Merid SK., Mertins P., Michaëlsson K., Møller PL., Murgia F., Nyegaard M., Park Y-C., Pearson E., Peters J., Petrie JR., Png G., Polašek O., Prins BP., Ripke S., Roden M., Rohde PD., Said S., SCALLOP Consortium ., Shen X., Schwenk JM., Siegbahn A., Smith JG., Stanne TM., Suhre K., Sundström J., Thorand B., Valdes-Marquez E., Vallerga CL., van Meurs JBJ., Viñuela A., Võsa U., Wallentin L., Walters RG., Wareham NJ., Weber JE., Weersma RK., Wilson JF., Winther S., Yasmeen S., Zanetti D., Zeggini E., Zhao JH., Zhernakova A., Zhernakova DV., Ziehm M., Kessler BM., Pereira AC., Mälarstig A., Pietzner M., Langenberg C.
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.