There is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53–4.69, p = 3.55 × 10−15 for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34–4.33, p = 1.62 × 10−13 for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.
Background:Genome-wide association studies (GWAS) of multiple myeloma (MM) in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g. colorectum and melanoma), risk loci have also been associated with patient survival. Methods:We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with MM overall survival (OS) in multiple populations of EA (IMMEnSE consortium, InterLymph consortium, CoMMpass and the German GWAS) for a total of 3748 MM cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. Results:SNP associations were meta-analyzed. From the meta-analysis, two MM risk SNPs were associated with OS (p<0.05), specifically POT1-AS1-rs2170352 (HR=1.37, 95% C.I.=1.09-1.73, p=0.007) and TNFRSF13B-rs4273077 (HR=1.19, 95% C.I.=1.01-1.41, p=0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. Conclusions:Overall, our results did not support an association between the majority of MM risk SNPs and OS. Impact:This is the first study to investigate the association between MM PRS and OS in MM.
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