A polygenic risk score for multiple myeloma risk prediction

被引:0
|
作者
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
机构
[1] German Cancer Research Center (DKFZ),Genomic Epidemiology Group
[2] University of Pisa,Department of Biology
[3] University Hospital of Cracow,Department of Hematology
[4] Aarhus University Hospital,Department of Hematology
[5] Chaim Sheba Medical Center,Hematology Division
[6] Sea Hospital,Department of Hematology
[7] Hypertension and Clinical Oncology,Department of Internal and Occupational Diseases
[8] Medical University Wroclaw,Department of Hematology
[9] Cancer Research Center of Lyon/Hospices Civils de Lyon,Genomic Oncology Area, GENYO. Centre for Genomics and Oncological Research: Pfizer
[10] Hematology Clinic,Hematology department
[11] Holycross Cancer Center,Third Department of Internal Medicine
[12] Institute of Hematology and Transfusion Medicine,Department of Internal and Occupational Diseases
[13] University of Granada/Andalusian Regional Government,Department of Hematology
[14] Virgen de las Nieves University Hospital,Hematology Department
[15] Semmelweis University,Department of Hematology
[16] Medical University Wroclaw,Clinical and Experimental Medicine, Section of Hematology
[17] Odense University Hospital,Department of Haematology
[18] Institut Curie,Department of Hematology
[19] PSL Research University,Life and Health Sciences Research Institute (ICVS), School of Health Sciences/Molecular Oncology Research Center
[20] Mines ParisTech Inserm,Department of Hematology
[21] Teaching Hospital No 1,Institute of Molecular Medicine
[22] Rigshospitalet,Unité de Génomique du Myélome
[23] Copenhagen University,Department of Hematology
[24] University of Pisa,Department of Hematology
[25] Military Institute of Medicine,CRCINA, INSERM, CNRS
[26] Rydygier Specialistic Hospital,undefined
[27] University of Minho,undefined
[28] Jagiellonian University Medical College,undefined
[29] Maria Sklodowska-Curie National Research Institute of Oncology,undefined
[30] National Research Centre for the Working Environment,undefined
[31] University of Southern Denmark,undefined
[32] ICVS/3B’s - PT Government Associate Laboratory,undefined
[33] Molecular Oncology Research Center,undefined
[34] Barretos Cancer Hospital,undefined
[35] Institut Universitaire du Cancer Toulouse – Oncopole,undefined
[36] University Hospital Bydgoszcz,undefined
[37] Medical University of Lublin,undefined
[38] N. Copernicus Town Hospital,undefined
[39] Université d’Angers,undefined
[40] Université de Nantes,undefined
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:474 / 479
页数:5
相关论文
共 50 条
  • [1] A polygenic risk score for multiple myeloma risk prediction
    Canzian, Federico
    Piredda, Chiara
    Macauda, Angelica
    Zawirska, Daria
    Andersen, Niels Frost
    Nagler, Arnon
    Zaucha, Jan Maciej
    Mazur, Grzegorz
    Dumontet, Charles
    Watek, Marzena
    Jamroziak, Krzysztof
    Sainz, Juan
    Varkonyi, Judit
    Butrym, Aleksandra
    Beider, Katia
    Abildgaard, Niels
    Lesueur, Fabienne
    Dudzinski, Marek
    Vangsted, Annette Juul
    Pelosini, Matteo
    Subocz, Edyta
    Petrini, Mario
    Buda, Gabriele
    Razny, Malgorzata
    Gemignani, Federica
    Marques, Herlander
    Orciuolo, Enrico
    Kadar, Katalin
    Jurczyszyn, Artur
    Druzd-Sitek, Agnieszka
    Vogel, Ulla
    Andersen, Vibeke
    Reis, Rui Manuel
    Suska, Anna
    Avet-Loiseau, Herve
    Kruszewski, Marcin
    Tomczak, Waldemar
    Rymko, Marcin
    Minvielle, Stephane
    Campa, Daniele
    [J]. EUROPEAN JOURNAL OF HUMAN GENETICS, 2022, 30 (04) : 474 - 479
  • [2] Association between a Polygenic Risk Score for Multiple Myeloma Risk and Overall Survival
    Clay-Gilmour, Alyssa I.
    Hildebrandt, Michelle
    Asmann, Yan
    Brown, Elizabeth E.
    Hofmann, Jonathan N.
    Spinelli, John
    Giles, Graham
    Bhatti, Parveen
    Cozen, Wendy
    Robinson, Dennis P.
    O'Brien, Daniel R.
    Rajkumar, S. Vincent
    Tian, Shulan
    Berndt, Sonja I.
    Chanock, Stephen J.
    Machiela, Mitchell
    Norman, Aaron D.
    Sinnwell, Jason P.
    Wu, Xifeng
    Waller, Rosalie Griffin
    Milne, Roger L.
    Slager, Susan L.
    Kumar, Shaji K.
    Camp, Nicola J.
    Ziv, Elad
    Vachon, Celine M.
    [J]. BLOOD, 2019, 134
  • [3] Associations between a polygenic risk score and risk of multiple myeloma and its precursor
    Clay-Gilmour, Alyssa I.
    Hildebrandt, Michelle A.
    Camp, Nicola J.
    Ziv, Elad
    Brown, Elizabeth E.
    Hofmann, Jonathan N.
    Spinelli, John J.
    Giles, Graham G.
    Bhatti, Parveen
    Cozen, Wendy
    Wu, Xifeng
    Robinson, Dennis P.
    Norman, Aaron D.
    Sinnwell, Jason P.
    Kumar, Shaji K.
    Rajkumar, S. Vincent
    Slager, Susan L.
    Vachon, Celine M.
    [J]. CANCER RESEARCH, 2019, 79 (13)
  • [4] Integration of risk factor polygenic risk score with disease polygenic risk score for disease prediction
    Jung, Hyein
    Jung, Hae-Un
    Baek, Eun Ju
    Kwon, Shin Young
    Kang, Ji-One
    Lim, Ji Eun
    Oh, Bermseok
    [J]. COMMUNICATIONS BIOLOGY, 2024, 7 (01)
  • [5] Integration of risk factor polygenic risk score with disease polygenic risk score for disease prediction
    Hyein Jung
    Hae-Un Jung
    Eun Ju Baek
    Shin Young Kwon
    Ji-One Kang
    Ji Eun Lim
    Bermseok Oh
    [J]. Communications Biology, 7
  • [6] Does a Multiple Myeloma Polygenic Risk Score Predict Overall Survival of Patients with Myeloma?
    Macauda, Angelica
    Clay-Gilmour, Alyssa
    Hielscher, Thomas
    Hildebrandt, Michelle A. T.
    Kruszewski, Marcin
    Orlowski, Robert Z.
    Kumar, Shaji K.
    Ziv, Elad
    Orciuolo, Enrico
    Brown, Elizabeth E.
    Forsti, Asta
    Waller, Rosalie G.
    Machiela, Mitchell J.
    Chanock, Stephen J.
    Camp, Nicola J.
    Rymko, Marcin
    Rany, Malgorzata
    Cozen, Wendy
    Varkonyi, Judit
    Piredda, Chiara
    Pelosini, Matteo
    Belachew, Alem A.
    Subocz, Edyta
    Hemminki, Kari
    Rybicka-Ramos, Malwina
    Giles, Graham G.
    Milne, Roger L.
    Hofmann, Jonathan N.
    Zaucha, Jan Maciej
    Vangsted, Annette Juul
    Goldschmidt, Hartmut
    Rajkumar, S. Vincent
    Tomczak, Waldemar
    Sainz, Juan
    Butrym, Aleksandra
    Watek, Marzena
    Iskierka-Jazdzewska, Elzbieta
    Buda, Gabriele
    Robinson, Dennis P.
    Jurczyszyn, Artur
    Dudzinski, Marek
    Martinez-Lopez, Joaquin
    Sinnwell, Jason P.
    Slager, Susan L.
    Jamroziak, Krzysztof
    Reis, Rui Manuel Vieira
    Weinhold, Niels
    Bhatti, Parveen
    Carvajal-Carmona, Luis G.
    Zawirska, Daria
    [J]. CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, 2022, 31 (09) : 1863 - 1866
  • [7] Polygenic Risk Score Prediction for Endometriosis
    Kloeve-Mogensen, Kirstine
    Rohde, Palle Duun
    Twisttmann, Simone
    Nygaard, Marianne
    Koldby, Kristina Magaard
    Steffensen, Rudi
    Dahl, Christian Moller
    Rytter, Dorte
    Overgaard, Michael Toft
    Forman, Axel
    Christiansen, Lene
    Nyegaard, Mette
    [J]. FRONTIERS IN REPRODUCTIVE HEALTH, 2021, 3
  • [8] Polygenic Risk Score: An Application to the Prediction of Asthma Risk
    Ricard, Jasmin
    Li, Zhonglin
    Theriault, Sebastien
    Bosse, Yohan
    Eslami, Aida
    [J]. GENETIC EPIDEMIOLOGY, 2021, 45 (07) : 785 - 785
  • [9] A Polygenic Risk Score for Prostate Cancer Risk Prediction
    Schaffer, Kerry R.
    Shi, Mingjian
    Shelley, John P.
    Tosoian, Jeffrey J.
    Kachuri, Linda
    Witte, John S.
    Mosley, Jonathan D.
    [J]. JAMA INTERNAL MEDICINE, 2023, 183 (04) : 386 - 388
  • [10] Evaluation of polygenic risk score for risk prediction of gastric cancer
    Xiao-Yu Wang
    Li-Li Wang
    Lin Xu
    Shu-Zhen Liang
    Meng-Chao Yu
    Qiu-Yue Zhang
    Quan-Jiang Dong
    [J]. World Journal of Gastrointestinal Oncology, 2023, 15 (02) : 276 - 285