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A polygenic risk score for multiple myeloma risk prediction.

Frederico CanzianChiara PireddaAngelica MacaudaDaria ZawirskaNiels Frost AndersenArnon NaglerJan Maciej ZauchaGrzegorz MazurCharles DumontetMarzena WątekKrzysztof JamroziakJuan SainzJudit VárkonyiAleksandra ButrymKatia BeiderNiels AbildgaardFabienne LesueurMarek DudzińskiAnnette Juul VangstedMatteo PelosiniEdyta SuboczMario PetriniGabriele BudaMałgorzata RaźnyFederica GemignaniHerlander MarquesEnrico OrciuoloKatalin KadarArtur JurczyszynAgnieszka Druzd-SitekUlla Birgitte VogelVibeke AndersenRui Manuel ReisAnna SuskaHervé Avet-LoiseauMarcin KruszewskiWaldemar TomczakMarcin RymkoStephane MinvielleDaniele Campa
Published in: European journal of human genetics : EJHG (2021)
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.
Keyphrases
  • multiple myeloma
  • genome wide association
  • genome wide
  • copy number
  • magnetic resonance
  • contrast enhanced
  • gene expression
  • network analysis
  • genome wide association study