<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>30(4)</volume><submitter>Canzian F</submitter><pubmed_abstract>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&lt;sup>-15&lt;/sup> 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&lt;sup>-13&lt;/sup> for the highest vs. lowest quintile of the un</pubmed_abstract><journal>European journal of human genetics : EJHG</journal><pagination>474-479</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8991223</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>A polygenic risk score for multiple myeloma risk prediction.</pubmed_title><pmcid>PMC8991223</pmcid><pubmed_authors>Vangsted AJ</pubmed_authors><pubmed_authors>Druzd-Sitek A</pubmed_authors><pubmed_authors>Andersen V</pubmed_authors><pubmed_authors>Watek M</pubmed_authors><pubmed_authors>Lesueur F</pubmed_authors><pubmed_authors>Butrym A</pubmed_authors><pubmed_authors>Petrini M</pubmed_authors><pubmed_authors>Varkonyi J</pubmed_authors><pubmed_authors>Beider K</pubmed_authors><pubmed_authors>Vogel U</pubmed_authors><pubmed_authors>Macauda A</pubmed_authors><pubmed_authors>Andersen NF</pubmed_authors><pubmed_authors>Sainz J</pubmed_authors><pubmed_authors>Dudzinski M</pubmed_authors><pubmed_authors>Marques H</pubmed_authors><pubmed_authors>Kruszewski M</pubmed_authors><pubmed_authors>Rymko M</pubmed_authors><pubmed_authors>Jurczyszyn A</pubmed_authors><pubmed_authors>Kadar K</pubmed_authors><pubmed_authors>Zaucha JM</pubmed_authors><pubmed_authors>Jamroziak K</pubmed_authors><pubmed_authors>Gemignani F</pubmed_authors><pubmed_authors>Dumontet C</pubmed_authors><pubmed_authors>Abildgaard N</pubmed_authors><pubmed_authors>Pelosini M</pubmed_authors><pubmed_authors>Buda G</pubmed_authors><pubmed_authors>Reis RM</pubmed_authors><pubmed_authors>Subocz E</pubmed_authors><pubmed_authors>Orciuolo E</pubmed_authors><pubmed_authors>Razny M</pubmed_authors><pubmed_authors>Piredda C</pubmed_authors><pubmed_authors>Tomczak W</pubmed_authors><pubmed_authors>Mazur G</pubmed_authors><pubmed_authors>Nagler A</pubmed_authors><pubmed_authors>Suska A</pubmed_authors><pubmed_authors>Avet-Loiseau H</pubmed_authors><pubmed_authors>Zawirska D</pubmed_authors><pubmed_authors>Canzian F</pubmed_authors><pubmed_authors>Minvielle S</pubmed_authors><pubmed_authors>Campa D</pubmed_authors></additional><is_claimable>false</is_claimable><name>A polygenic risk score for multiple myeloma risk prediction.</name><description>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&lt;sup>-15&lt;/sup> 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&lt;sup>-13&lt;/sup> for the highest vs. lowest quintile of the un</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Apr</publication><modification>2026-05-30T15:28:12.168Z</modification><creation>2025-04-04T10:02:19.694Z</creation></dates><accession>S-EPMC8991223</accession><cross_references><pubmed>34845334</pubmed><doi>10.1038/s41431-021-00986-8</doi></cross_references></HashMap>