A polygenic risk score for multiple myeloma risk prediction

Federico Canzian; Chiara Piredda; Angelica Macauda; Daria Zawirska; Niels Frost Andersen; Arnon Nagler; Jan Maciej Zaucha; Grzegorz Mazur; Charles Dumontet; Marzena Wątek; Krzysztof Jamroziak; Juan Sainz; Judit Várkonyi; Aleksandra Butrym; Katia Beider; Niels Abildgaard; Fabienne Lesueur; Marek Dudziński; Annette Juul Vangsted; Matteo Pelosini; Edyta Subocz; Mario Petrini; Gabriele Buda; Małgorzata Raźny; Federica Gemignani; Herlander Marques; Enrico Orciuolo; Katalin Kadar; Artur Jurczyszyn; Agnieszka Druzd-Sitek; Ulla Vogel; Vibeke Andersen; Rui Manuel Reis; Anna Suska; Hervé Avet-Loiseau; Marcin Kruszewski; Waldemar Tomczak; Marcin Rymko; Stephane Minvielle; Daniele Campa

doi:10.1038/s41431-021-00986-8

A polygenic risk score for multiple myeloma risk prediction

Federico Canzian, Chiara Piredda, Angelica Macauda, Daria Zawirska, Niels Frost Andersen, Arnon Nagler, Jan Maciej Zaucha, Grzegorz Mazur, Charles Dumontet, Marzena Wątek, Krzysztof Jamroziak, Juan Sainz, Judit Várkonyi, Aleksandra Butrym, Katia Beider, Niels Abildgaard, Fabienne Lesueur, Marek Dudziński, Annette Juul Vangsted, Matteo PelosiniEdyta Subocz, Mario Petrini, Gabriele Buda, Małgorzata Raźny, Federica Gemignani, Herlander Marques, Enrico Orciuolo, Katalin Kadar, Artur Jurczyszyn, Agnieszka Druzd-Sitek, Ulla Vogel, Vibeke Andersen, Rui Manuel Reis, Anna Suska, Hervé Avet-Loiseau, Marcin Kruszewski, Waldemar Tomczak, Marcin Rymko, Stephane Minvielle, Daniele Campa

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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 × 10-15 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.

Originalsprog	Engelsk
Tidsskrift	European journal of human genetics : EJHG
Vol/bind	30
Udgave nummer	4
Sider (fra-til)	474-479
Antal sider	6
ISSN	1018-4813
DOI	https://doi.org/10.1038/s41431-021-00986-8
Status	Udgivet - apr. 2022

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Canzian, F., Piredda, C., Macauda, A., Zawirska, D., Andersen, N. F., Nagler, A., Zaucha, J. M., Mazur, G., Dumontet, C., Wątek, M., Jamroziak, K., Sainz, J., Várkonyi, J., Butrym, A., Beider, K., Abildgaard, N., Lesueur, F., Dudziński, M., Vangsted, A. J., ... Campa, D. (2022). A polygenic risk score for multiple myeloma risk prediction. European journal of human genetics : EJHG, 30(4), 474-479. https://doi.org/10.1038/s41431-021-00986-8

Canzian, F, Piredda, C, Macauda, A, Zawirska, D, Andersen, NF, Nagler, A, Zaucha, JM, Mazur, G, Dumontet, C, Wątek, M, Jamroziak, K, Sainz, J, Várkonyi, J, Butrym, A, Beider, K, Abildgaard, N, Lesueur, F, Dudziński, M, Vangsted, AJ, Pelosini, M, Subocz, E, Petrini, M, Buda, G, Raźny, M, Gemignani, F, Marques, H, Orciuolo, E, Kadar, K, Jurczyszyn, A, Druzd-Sitek, A, Vogel, U, Andersen, V, Reis, RM, Suska, A, Avet-Loiseau, H, Kruszewski, M, Tomczak, W, Rymko, M, Minvielle, S & Campa, D 2022, 'A polygenic risk score for multiple myeloma risk prediction', European journal of human genetics : EJHG, bind 30, nr. 4, s. 474-479. https://doi.org/10.1038/s41431-021-00986-8

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title = "A polygenic risk score for multiple myeloma risk prediction",

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 × 10-15 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.",

author = "Federico Canzian and Chiara Piredda and Angelica Macauda and Daria Zawirska and Andersen, {Niels Frost} and Arnon Nagler and Zaucha, {Jan Maciej} and Grzegorz Mazur and Charles Dumontet and Marzena W{\c a}tek and Krzysztof Jamroziak and Juan Sainz and Judit V{\'a}rkonyi and Aleksandra Butrym and Katia Beider and Niels Abildgaard and Fabienne Lesueur and Marek Dudzi{\'n}ski and Vangsted, {Annette Juul} and Matteo Pelosini and Edyta Subocz and Mario Petrini and Gabriele Buda and Ma{\l}gorzata Ra{\'z}ny and Federica Gemignani and Herlander Marques and Enrico Orciuolo and Katalin Kadar and Artur Jurczyszyn and Agnieszka Druzd-Sitek and Ulla Vogel and Vibeke Andersen and Reis, {Rui Manuel} and Anna Suska and Herv{\'e} Avet-Loiseau and Marcin Kruszewski and Waldemar Tomczak and Marcin Rymko and Stephane Minvielle and Daniele Campa",

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T1 - A polygenic risk score for multiple myeloma risk prediction

AU - Canzian, Federico

AU - Piredda, Chiara

AU - Macauda, Angelica

AU - Zawirska, Daria

AU - Andersen, Niels Frost

AU - Nagler, Arnon

AU - Zaucha, Jan Maciej

AU - Mazur, Grzegorz

AU - Dumontet, Charles

AU - Wątek, Marzena

AU - Jamroziak, Krzysztof

AU - Sainz, Juan

AU - Várkonyi, Judit

AU - Butrym, Aleksandra

AU - Beider, Katia

AU - Abildgaard, Niels

AU - Lesueur, Fabienne

AU - Dudziński, Marek

AU - Vangsted, Annette Juul

AU - Pelosini, Matteo

AU - Subocz, Edyta

AU - Petrini, Mario

AU - Buda, Gabriele

AU - Raźny, Małgorzata

AU - Gemignani, Federica

AU - Marques, Herlander

AU - Orciuolo, Enrico

AU - Kadar, Katalin

AU - Jurczyszyn, Artur

AU - Druzd-Sitek, Agnieszka

AU - Vogel, Ulla

AU - Andersen, Vibeke

AU - Reis, Rui Manuel

AU - Suska, Anna

AU - Avet-Loiseau, Hervé

AU - Kruszewski, Marcin

AU - Tomczak, Waldemar

AU - Rymko, Marcin

AU - Minvielle, Stephane

AU - Campa, Daniele

PY - 2022/4

Y1 - 2022/4

N2 - 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.

AB - 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.

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U2 - 10.1038/s41431-021-00986-8

DO - 10.1038/s41431-021-00986-8

M3 - Journal article

C2 - 34845334

SN - 1018-4813

VL - 30

SP - 474

EP - 479

JO - European journal of human genetics : EJHG

JF - European journal of human genetics : EJHG

IS - 4

ER -

A polygenic risk score for multiple myeloma risk prediction

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