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A polygenic risk score for multiple myeloma risk prediction

Federico Canzian 1, * Chiara Piredda 1, 2 Angelica Macauda 1, 2 Daria Zawirska 3 Niels Frost Andersen 4 Arnon Nagler 5 Jan Maciej Zaucha 6 Grzegorz Mazur 7 Charles Dumontet 8 Marzena Wątek 9 Krzysztof Jamroziak 10 Juan Sainz 11, 12 Judit Varkonyi 13 Aleksandra Butrym 7 Katia Beider 5 Niels Abildgaard 14 Fabienne Lesueur 15 Marek Dudziński 16 Annette Juul Vangsted 17 Matteo Pelosini 2 Edyta Subocz 18 Mario Petrini 2 Gabriele Buda 2 Małgorzata Raźny 19 Federica Gemignani 2 Herlander Marques 20 Enrico Orciuolo 2 Katalin Kadar 13 Artur Jurczyszyn 21 Agnieszka Druzd-Sitek 22 Ulla Vogel 23 Helle Vibeke Andersen 24 Rui Manuel Reis 25, 20, 26 Anna Suska 21 Hervé Avet Loiseau 27 Marcin Kruszewski 28 Waldemar Tomczak 29 Marcin Rymko 30 Stephane Minvielle 31 Daniele Campa 2
* Corresponding author
31 CRCINA-ÉQUIPE 11 - Integrative Oncogenomics of Multiple Myeloma Pathogenesis and Progression
CRCINA - Centre de Recherche en Cancérologie et Immunologie Nantes-Angers
Abstract : There is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genomewide 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.
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https://www.hal.inserm.fr/inserm-03480934
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Submitted on : Wednesday, December 15, 2021 - 8:32:57 AM
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Federico Canzian, Chiara Piredda, Angelica Macauda, Daria Zawirska, Niels Frost Andersen, et al.. A polygenic risk score for multiple myeloma risk prediction. European Journal of Human Genetics, Nature Publishing Group, 2021, Online ahead of print. ⟨10.1038/s41431-021-00986-8⟩. ⟨inserm-03480934⟩

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