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Prediction of acute myeloid leukaemia risk in healthy individuals

Accepted version
Peer-reviewed

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Type

Article

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Authors

Abelson, Sagi 
Ng, Stanley WK 
Weissbrod, Omer 
Mendelson Cohen, Netta 

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.

Description

Keywords

Adult, Age Factors, Aged, Disease Progression, Electronic Health Records, Female, Genetic Predisposition to Disease, Health, Humans, Leukemia, Myeloid, Acute, Male, Middle Aged, Models, Genetic, Mutagenesis, Mutation, Prevalence, Risk Assessment

Journal Title

Nature

Conference Name

Journal ISSN

0028-0836
1476-4687

Volume Title

559

Publisher

Nature Research
Sponsorship
Medical Research Council (MC_UU_12015/1)
MRC (MC_PC_13048)
Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0512-10135)
Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0617-10149)
Medical Research Council (G0401527)
Medical Research Council (G1000143)
Medical Research Council (MC_PC_12009)
Medical Research Council (MR/N003284/1)
Cancer Research UK (23015)