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A polygenic risk score for multiple myeloma risk prediction
dc.contributor.author | Canzian, Federico | |
dc.contributor.author | Sáinz Pérez, Juan | |
dc.date.accessioned | 2021-12-16T12:02:55Z | |
dc.date.available | 2021-12-16T12:02:55Z | |
dc.date.issued | 2021-11-30 | |
dc.identifier.citation | Canzian, F... [et al.]. A polygenic risk score for multiple myeloma risk prediction. Eur J Hum Genet (2021). [https://doi.org/10.1038/s41431-021-00986-8] | es_ES |
dc.identifier.uri | http://hdl.handle.net/10481/72091 | |
dc.description | This work was partially supported by intramural funds of the University of Pisa, DKFZ, and University Hospital of Southern Jutland, Denmark, and by a grant of the French National Cancer Institute (INCA). The authors wish to thank Dr. Dominic Edelmann (Division of Biostatistics, DKFZ) for helpful advice about data analysis. | es_ES |
dc.description.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 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. | es_ES |
dc.description.sponsorship | University of Pisa, DKFZ | es_ES |
dc.description.sponsorship | University Hospital of Southern Jutland, Denmark | es_ES |
dc.description.sponsorship | Institut National du Cancer (INCA) France | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Nature | es_ES |
dc.rights | Atribución 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.title | A polygenic risk score for multiple myeloma risk prediction | es_ES |
dc.type | journal article | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.1038/s41431-021-00986-8 | |
dc.type.hasVersion | VoR | es_ES |