Therapeutic targets for inflammatory bowel disease: proteome-wide Mendelian randomization and colocalization analyses

Identifying new drug targets for inflammatory bowel disease (IBD) is urgently needed. The proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) and colocalization analyses to identify possible targets for IBD. Summary-level data of 4907 circulating protein levels were extracted from a large-scale protein quantitative trait loci study including 35,559 individuals. Genetic associations with IBD and its subtypes were obtained from the Inflammatory Bowel Disease Genetics Consortium (25,024 cases and 34,915 controls), the FinnGen study (7206 cases and 253,199 controls), and the UK Biobank study (7045 cases and 449,282 controls). MR analysis was conducted to estimate the associations between protein and IBD risk. The colocalization analysis was used to examine whether the identified proteins and IBD shared casual variants. Genetically predicted levels of 3, and 5 circulating proteins were associated with IBD and ulcerative colitis (UC), respectively. With high supporting evidence of colocalization, genetically predicted MST1 (macrophage stimulating 1) and HGFAC (hepatocyte growth factor activator) levels were inversely associated with IBD risks. The associations of STAT3 (signal transducer and activator of transcription 3), MST1, CXCL5 (C-X-C motif chemokine ligand 5), and ITPKA (inositol-trisphosphate 3-kinase A) with the risk of UC were supported by colocalization analysis. The proteome-wide MR investigation identified many proteins associated with the risk of IBD. MST1, HGFAC, STAT3, ITPKA, and CXCL5 deserve further investigation as potential therapeutic targets for IBD. SCL is supported by research grants from the Swedish Research Council for Health, Working Life and Welfare (Forte; grant no. 2018-00123) and the Swedish Research Council (Vetenskapsrådet; grant no. 2019-00977). XYW is supported by research grants from the National Natural Science Foundation of China (81970494) and Key Project of Research and Development Plan of Hunan Province (2019SK2041). XL is supported by research grants from the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001).