medRxivGenetic & Genomic MedicinePreprint
Multi-ancestry proteome-phenome-wide Mendelian randomization offers a comprehensive protein-disease atlas and potential therapeutic targets
Chen‐Yang SuiD, Adriaan van der GraafiD, Wenmin ZhangiD, Dongkeun JangiD, Susannah Selber‐HnatiwiD, Ta‐Yu YangiD, Guillaume Butler‐LaporteiD, Kevin Y. H. LiangiD, Fumihiko MatsudaiD, Maria C. CostanzoiD, Noël P. BurttiD, Jason A. FlannickiD, Sirui ZhouiD, Vincent MooseriD, Tianyuan LuiD, Satoshi YoshijiiD
Abstract
Circulating proteins influence disease risk and are valuable drug targets. To enhance the discovery of protein-phenotype associations and identify potential therapeutic targets across diverse populations, we conducted proteome-phenome-wide Mendelian randomization in three ancestries, followed by comprehensive sensitivity analyses. We tested the potential causal effects of up to 2,265 unique proteins on a curated list of 355 distinct phenotypes, assessing 726,035 protein-phenotype pairs in European, 33,078 in African, and 115,352 in East Asian ancestries. Notably, 119 proteins were instrumentable only in African ancestry and 17 proteins only in East Asian ancestry due to allele frequency differences that are common in these ancestries but rare in European ancestry. We identified 3,949, 56, and 325 unique protein-phenotype pairs in European, African, and East Asian ancestries, respectively, and assessed their druggability using multiple databases. We highlighted the causal role of IL1RL1 in inflammatory bowel diseases, supported by multiple orthogonal lines of evidence. Taken together, this study underscores the importance of multi-ancestry inclusion and offers a comprehensive atlas of protein-phenotype associations across three ancestries, enhancing our understanding of proteins involved in disease etiology and potential therapeutic targets. Results are available at the Common Metabolic Diseases Knowledge Portal (https://broad.io/protein_mr_atlas).
- organism: human
- assay: proteomics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 17
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