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Proteomics is a valuable tool in exploring mechanisms of disease. We investigated the causal relationship between circulating proteins and MM risk, using two of the largest cohorts with proteomics data to-date. We performed bidirectional two-sample Mendelian randomization (MR; forward MR\u2009=\u2009causal effect estimation of proteins and MM risk; reverse MR\u2009=\u2009causal effect estimation of MM risk and proteins). Summary statistics for plasma proteins were obtained from genome-wide association studies performed using SomaLogic (N\u2009=\u200935,559; deCODE) and Olink (N\u2009=\u200934,557; UK Biobank; UKB) proteomic platforms and for MM risk from a meta-analysis of UKB and FinnGen (case\u2009=\u20091649; control\u2009=\u2009727,247) or FinnGen only (case\u2009=\u20091085; control\u2009=\u2009271,463).\n                    <jats:italic>Cis-<\/jats:italic>\n                    SNPs associated with protein levels were used to instrument circulating proteins. We evaluated proteins for the consistency of directions of effect across MR analyses (with 95% confidence intervals not overlapping the null) and corroborating evidence from genetic colocalization. In the forward MR, 994 (SomaLogic) and 1570 (Olink) proteins were instrumentable. 440 proteins were analysed in both deCODE and UKB; 302 (69%) of these showed consistent directions of effect in the forward MR. Seven proteins had 95% confidence intervals (CIs) that did not overlap the null in both forward MR analyses and did not have evidence for an effect in the reverse direction: higher levels of dermatopontin (DPT), beta-crystallin B1 (CRYBB1), interleukin-18-binding protein (IL18BP) and vascular endothelial growth factor receptor 2 (KDR) and lower levels of odorant-binding protein 2b (OBP2B), glutamate-cysteine ligase regulatory subunit (GCLM) and gamma-crystallin D (CRYGD) were implicated in increasing MM risk. Evidence from genetic colocalization did not meet our threshold for a shared causal signal between any of these proteins and MM risk (h4\u2009&lt;\u20090.8). Our results highlight seven circulating proteins which may be involved in MM risk. Although evidence from genetic colocalization suggests these associations may not be robust to the effects of horizontal pleiotropy, these proteins may be useful markers of MM risk. Future work should explore the utility of these proteins in disease prediction or prevention using proteomic data from patients with MM or precursor conditions.\n                  <\/jats:p>","DOI":"10.1038\/s41598-025-86222-5","type":"journal-article","created":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T05:17:36Z","timestamp":1738214256000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploring the role of circulating proteins in multiple myeloma risk: a Mendelian randomization study"],"prefix":"10.1038","volume":"15","author":[{"given":"Matthew A.","family":"Lee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kate L.","family":"Burley","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emma L.","family":"Hazelwood","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sally","family":"Moore","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah J.","family":"Lewis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucy J.","family":"Goudswaard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,30]]},"reference":[{"key":"86222_CR1","unstructured":"CRUK. 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