%0 Journal Article
%A Canzian, Federico
%A Piredda, Chiara
%A Macauda, Angelica
%A Zawirska, Daria
%A Andersen, Niels Frost
%A Nagler, Arnon
%A Zaucha, Jan Maciej
%A Mazur, Grzegorz
%A Dumontet, Charles
%A Watek, Marzena
%A Jamroziak, Krzysztof
%A Sainz, Juan
%A Varkonyi, Judit
%A Butrym, Aleksandra
%A Beider, Katia
%A Abildgaard, Niels
%A Lesueur, Fabienne
%A Dudzinski, Marek
%A Vangsted, Annette Juul
%A Pelosini, Matteo
%A Subocz, Edyta
%A Petrini, Mario
%A Buda, Gabriele
%A Razny, Malgorzata
%A Gemignani, Federica
%A Marques, Herlander
%A Orciuolo, Enrico
%A Kadar, Katalin
%A Jurczyszyn, Artur
%A Druzd-Sitek, Agnieszka
%A Vogel, Ulla
%A Andersen, Vibeke
%A Reis, Rui Manuel
%A Suska, Anna
%A Avet-Loiseau, Herve
%A Kruszewski, Marcin
%A Tomczak, Waldemar
%A Rymko, Marcin
%A Minvielle, Stephane
%A Campa, Daniele
%T A polygenic risk score for multiple myeloma risk prediction
%D 2021
%@ 1018-4813
%U https://hdl.handle.net/10668/26366
%X 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 x 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 x 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.
%K Monoclonal gammopathy
%K Stratification
%K Polymorphisms
%K Epidemiology
%~