Abstract
Background
Multiple myeloma (MM) is an incurable blood cancer with unclear aetiology. Proteomics, the high-throughput measurement of circulating proteins, 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.
Methods
We performed bidirectional two-sample Mendelian randomization (MR; forward MR = causal effect estimation of proteins and MM risk; reverse MR = causal effect estimation of MM risk and proteins). Summary statistics for plasma proteins were obtained from genome-wide association studies performed using SomaLogic (N = 35,559; deCODE) and Olink (N = 34,557; UK Biobank; UKB) proteomic platforms and for MM risk from a meta-analysis of UKB and FinnGen (case = 1,649; control = 727,247) or FinnGen only (case = 1,085; control = 271,463). Cis-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.
Results
In the forward MR, 994 (SomaLogic) and 1,570 (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. MR evidence was strongest for the effect of dermatopontin on MM risk (deCODE) OR: 1.49 per SD higher protein levels, 95% CI 1.06–2.09; (UKB) OR: 1.47; 95% CI 1.14–1.90). Evidence from genetic colocalization did not meet our threshold for a shared causal signal between this protein and MM risk (h4 < 0.8).
Conclusions
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 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.