RT Journal Article
T1 Prediction of acute myeloid leukaemia risk in healthy individuals.
A1 Abelson, Sagi
A1 Collord, Grace
A1 Ng, Stanley W K
A1 Weissbrod, Omer
A1 Mendelson Cohen, Netta
A1 Niemeyer, Elisabeth
A1 Barda, Noam
A1 Zuzarte, Philip C
A1 Heisler, Lawrence
A1 Sundaravadanam, Yogi
A1 Luben, Robert
A1 Hayat, Shabina
A1 Wang, Ting Ting
A1 Zhao, Zhen
A1 Cirlan, Iulia
A1 Pugh, Trevor J
A1 Soave, David
A1 Ng, Karen
A1 Latimer, Calli
A1 Hardy, Claire
A1 Raine, Keiran
A1 Jones, David
A1 Hoult, Diana
A1 Britten, Abigail
A1 McPherson, John D
A1 Johansson, Mattias
A1 Mbabaali, Faridah
A1 Eagles, Jenna
A1 Miller, Jessica K
A1 Pasternack, Danielle
A1 Timms, Lee
A1 Krzyzanowski, Paul
A1 Awadalla, Philip
A1 Costa, Rui
A1 Segal, Eran
A1 Bratman, Scott V
A1 Beer, Philip
A1 Behjati, Sam
A1 Martincorena, Inigo
A1 Wang, Jean C Y
A1 Bowles, Kristian M
A1 Quirós, J Ramón
A1 Karakatsani, Anna
A1 La Vecchia, Carlo
A1 Trichopoulou, Antonia
A1 Salamanca-Fernández, Elena
A1 Huerta, José M
A1 Barricarte, Aurelio
A1 Travis, Ruth C
A1 Tumino, Rosario
A1 Masala, Giovanna
A1 Boeing, Heiner
A1 Panico, Salvatore
A1 Kaaks, Rudolf
A1 Krämer, Alwin
A1 Sieri, Sabina
A1 Riboli, Elio
A1 Vineis, Paolo
A1 Foll, Matthieu
A1 McKay, James
A1 Polidoro, Silvia
A1 Sala, Núria
A1 Khaw, Kay-Tee
A1 Vermeulen, Roel
A1 Campbell, Peter J
A1 Papaemmanuil, Elli
A1 Minden, Mark D
A1 Tanay, Amos
A1 Balicer, Ran D
A1 Wareham, Nicholas J
A1 Gerstung, Moritz
A1 Dick, John E
A1 Brennan, Paul
A1 Vassiliou, George S
A1 Shlush, Liran I
AB 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.
YR 2018
FD 2018-07-09
LK http://hdl.handle.net/10668/12699
UL http://hdl.handle.net/10668/12699
LA en
DS RISalud
RD Apr 28, 2025