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Multiparameter prediction of myeloid neoplasia risk.

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Gu, Muxin 
Kovilakam, Sruthi Cheloor 
Dunn, William G 
Marando, Ludovica 


The myeloid neoplasms encompass acute myeloid leukemia, myelodysplastic syndromes and myeloproliferative neoplasms. Most cases arise from the shared ancestor of clonal hematopoiesis (CH). Here we analyze data from 454,340 UK Biobank participants, of whom 1,808 developed a myeloid neoplasm 0-15 years after recruitment. We describe the differences in CH mutational landscapes and hematology/biochemistry test parameters among individuals that later develop myeloid neoplasms (pre-MN) versus controls, finding that disease-specific changes are detectable years before diagnosis. By analyzing differences between 'pre-MN' and controls, we develop and validate Cox regression models quantifying the risk of progression to each myeloid neoplasm subtype. We construct 'MN-predict', a web application that generates time-dependent predictions with the input of basic blood tests and genetic data. Our study demonstrates that many individuals that develop myeloid neoplasms can be identified years in advance and provides a framework for disease-specific prognostication that will be of substantial use to researchers and physicians.


Acknowledgements: This work was funded by an Early Detection Project Grant from Cancer Research UK (EDDCPJT\100010) and a joint grant from the Leukemia and Lymphoma Society (RTF6006-19), and the Rising Tide Foundation for Clinical Cancer Research (CCR-18-500) awarded to G.S.V. The Cambridge Stem Cell Institute is supported by the Wellcome Trust (203151/Z/16/Z, 203151/A/16/Z) and the UKRI Medical Research Council (MC_PC_17230). W.G.D is funded by a Clinical Research Fellowship from the Cancer Research UK Cambridge Centre (CTRQQR-2021\100012). S.P.K. is supported by a UK Research and Innovation (UKRI) Future Leaders Fellowship (MR/T043202/1). P.M.Q. is funded by the Miguel Servet Program (CP20/00130). A.S. is funded by Cancer Research UK (grant 29685) and Blood Cancer UK (grant 503). G.S.V. is supported by a Cancer Research UK Senior Cancer Fellowship (C22324/A23015) and work in his laboratory is also funded by the European Research Council, Kay Kendall Leukemia Fund, Blood Cancer UK and the Wellcome Trust. This research was conducted using the UK Biobank resource under approved application 56844. We thank the participants and investigators involved in the UK Biobank resource and in the other genome-wide association studies cited in this work who collectively made this research possible.


Cambridge Stem Cell Institute

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Nat Genet

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Springer Science and Business Media LLC
Wellcome Trust (203151/Z/16/Z)
Wellcome Trust (203151/A/16/Z)
Cancer Research UK (23015)
Leukemia & Lymphoma Society (RTF6006-19)
Medical Research Council (MC_PC_17230)