Prediction of acute myeloid leukaemia risk in healthy individuals.

Abstract

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without a detectable prodrome and 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 pre-leukaemic haematopoietic stem and progenitor cells (HSPC) 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. To distinguish individuals at high risk of developing AML from those with benign ARCH, we undertook deep sequencing of genes recurrently mutated in AML in the peripheral blood cells of 95 individuals sampled 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 with more mutations per sample, higher variant allele frequencies (VAF) reflective of greater clonal expansion, and enrichment for 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-AMLs and 262 controls. Since 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 a proof-of-concept that it is possible to discriminate ARCH from pre-AML many years prior to malignant transformation. This could in the future enable earlier detection, monitoring and potentially inform intervention.