Prediction of acute myeloid leukaemia risk in healthy individuals

Sagi Abelson, Grace Collord, Stanley W. K. Ng, Omer Weissbrod, Netta Mendelson Cohen, Elisabeth Niemeyer, Noam Barda, Philip C. Zuzarte, Lawrence Heisler, Yogi Sundaravadanam, Robert Luben, Shabina Hayat, Ting Ting Wang, Zhen Zhao, Iulia Cirlan, Trevor J. Pugh, David Soave, Karen Ng, Calli Latimer, Claire Hardy, Keiran Raine, David Jones, Diana Hoult, Abigail Britten, John D. McPherson, Mattias Johansson, Faridah Mbabaali, Jenna Eagles, Jessica K. Miller, Danielle Pasternack, Lee Timms, Paul Krzyzanowski, Philip Awadalla, Rui Costa, Eran Segal, Scott V. Bratman, Philip Beer, Sam Behjati, Inigo Martincorena, Jean C. Y. Wang, Kristian M. Bowles, J. Ramón Quirós, Anna Karakatsani, Carlo Vecchia, Antonia Trichopoulou, Elena Salamanca-Fernández, José M. Huerta, Aurelio Barricarte, Ruth C. Travis, Rosario Tumino, Giovanna Masala, Heiner Boeing, Salvatore Panico, Rudolf Kaaks, Alwin Krämer, Sabina Sieri, Elio Riboli, Paolo Vineis, Matthieu Foll, James McKay, Silvia Polidoro, Núria Sala, Kay-Tee Khaw, Roel Vermeulen, Peter J. Campbell, Elli Papaemmanuil, Mark D. Minden, Amos Tanay, Ran D. Balicer, Nicholas J. Wareham, Moritz Gerstung (), John E. Dick (), Paul Brennan (), George S. Vassiliou () and Liran I. Shlush ()
Additional contact information
Sagi Abelson: Princess Margaret Cancer Centre, University Health Network (UHN)
Grace Collord: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Stanley W. K. Ng: Institute of Biomaterials and Biomedical Engineering, University of Toronto
Omer Weissbrod: Weizmann Institute of Science
Netta Mendelson Cohen: Weizmann Institute of Science
Elisabeth Niemeyer: Weizmann Institute of Science
Noam Barda: Clalit Research Institute
Philip C. Zuzarte: Ontario Institute for Cancer Research
Lawrence Heisler: Ontario Institute for Cancer Research
Yogi Sundaravadanam: Ontario Institute for Cancer Research
Robert Luben: University of Cambridge School of Clinical Medicine
Shabina Hayat: University of Cambridge School of Clinical Medicine
Ting Ting Wang: Princess Margaret Cancer Centre, University Health Network (UHN)
Zhen Zhao: Princess Margaret Cancer Centre, University Health Network (UHN)
Iulia Cirlan: Princess Margaret Cancer Centre, University Health Network (UHN)
Trevor J. Pugh: Princess Margaret Cancer Centre, University Health Network (UHN)
David Soave: Ontario Institute for Cancer Research
Karen Ng: Ontario Institute for Cancer Research
Calli Latimer: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Claire Hardy: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Keiran Raine: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
David Jones: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Diana Hoult: MRC Epidemiology Unit, University of Cambridge
Abigail Britten: MRC Epidemiology Unit, University of Cambridge
John D. McPherson: Ontario Institute for Cancer Research
Mattias Johansson: International Agency for Research on Cancer, World Health Organization
Faridah Mbabaali: Ontario Institute for Cancer Research
Jenna Eagles: Ontario Institute for Cancer Research
Jessica K. Miller: Ontario Institute for Cancer Research
Danielle Pasternack: Ontario Institute for Cancer Research
Lee Timms: Ontario Institute for Cancer Research
Paul Krzyzanowski: Ontario Institute for Cancer Research
Philip Awadalla: Ontario Institute for Cancer Research
Rui Costa: European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Wellcome Genome Campus
Eran Segal: Weizmann Institute of Science
Scott V. Bratman: Princess Margaret Cancer Centre, University Health Network (UHN)
Philip Beer: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Sam Behjati: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Inigo Martincorena: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Jean C. Y. Wang: Princess Margaret Cancer Centre, University Health Network (UHN)
Kristian M. Bowles: The University of East Anglia
J. Ramón Quirós: Public Health Directorate
Anna Karakatsani: Hellenic Health Foundation
Carlo Vecchia: Hellenic Health Foundation
Antonia Trichopoulou: Hellenic Health Foundation
Elena Salamanca-Fernández: Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada/Universidad de Granada
José M. Huerta: CIBER Epidemiology and Public Health CIBERESP
Aurelio Barricarte: CIBER Epidemiology and Public Health CIBERESP
Ruth C. Travis: Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford
Rosario Tumino: Cancer Registry and Histopathology Department, Civic-M. P. Arezzo Hospital, Azienda Sanitaria Provinciale
Giovanna Masala: Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute – ISPO
Heiner Boeing: German Institute of Human Nutrition (DIfE)
Salvatore Panico: Dipartimento Di Medicina Clinica E Chirurgia, Federico II University
Rudolf Kaaks: German Cancer Research Center (DKFZ)
Alwin Krämer: Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center (DKFZ) and Department of Internal Medicine V, University of Heidelberg
Sabina Sieri: Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori
Elio Riboli: School of Public Health, Imperial College London
Paolo Vineis: School of Public Health, Imperial College London
Matthieu Foll: International Agency for Research on Cancer, World Health Organization
James McKay: International Agency for Research on Cancer, World Health Organization
Silvia Polidoro: Italian Institute for Genomic Medicine
Núria Sala: Unit of Nutrition and Cancer, Cancer Epidemiology Research Program and Translational Research Laboratory, Catalan Institute of Oncology, ICO-IDIBELL
Kay-Tee Khaw: University of Cambridge
Roel Vermeulen: Division of Environmental Epidemiology and Veterinary Public Health, Institute for Risk Assessment Sciences, Utrecht University
Peter J. Campbell: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Elli Papaemmanuil: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Mark D. Minden: Princess Margaret Cancer Centre, University Health Network (UHN)
Amos Tanay: Weizmann Institute of Science
Ran D. Balicer: Clalit Research Institute
Nicholas J. Wareham: MRC Epidemiology Unit, University of Cambridge
Moritz Gerstung: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
John E. Dick: Princess Margaret Cancer Centre, University Health Network (UHN)
Paul Brennan: International Agency for Research on Cancer, World Health Organization
George S. Vassiliou: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Liran I. Shlush: Princess Margaret Cancer Centre, University Health Network (UHN)

Nature, 2018, vol. 559, issue 7714, 400-404

Abstract: Abstract The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure1. The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion2,3. However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)4–8. Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention.

Date: 2018
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DOI: 10.1038/s41586-018-0317-6

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