Progression to AML is predictable and distinct from age related clonal hematopoiesis

To examine the occurrence of somatic mutations prior to the development of acute myeloid leukemia, we undertook deep ECS (estimated limit of detection 1 mutation in 2500 cells) of 261 AML associated genes in 96 pre-AML cases and 420 age and gender-matched healthy controls of an average of 3853 unique DNA molecules covering each of the 1.19M bases spanning the target gene panel. The findings suggest that the development of clonal hematopoiesis and accumulation of somatic mutations is distinct and accelerated in pre-AML cases compared to healthy individuals

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 3 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001003583	516 DNA samples were collected from individuals upon enrollment into the European Prospective Investigation into Cancer and Nutrition study between 1993 and 1998 across 17 different centers. 126bp pair-end reads sequencing data from the Illumina platform were converted to fastq format, the 2bp molecular barcode information at each read of the pair was trimmed and was written in the reads name. The Thymine nucleotide required for ligation was removed from the sequences. Burroughs-Wheeler Aligner (BWA-mem) was used for alignment of the processed fastq files to the reference hg19 genome, following indel-re-alignment using GATK. An in-house algorithm was written to collapse read families that share the same molecular barcode sequence		516

Publications	Citations
Prediction of acute myeloid leukaemia risk in healthy individuals. Abelson S, Collord G, Ng SWK, Weissbrod O, Mendelson Cohen N, Niemeyer E, Barda N, Zuzarte PC, Heisler L, Sundaravadanam Y, Luben R, Hayat S, Wang TT, Zhao Z, Cirlan I, Pugh TJ, Soave D, Ng K, Latimer C, Hardy C, Raine K, Jones D, Hoult D, Britten A, McPherson JD, Johansson M, Mbabaali F, Eagles J, Miller JK, Pasternack D, Timms L, Krzyzanowski P, Awadalla P, Costa R, Segal E, Bratman SV, Beer P, Behjati S, Martincorena I, Wang JCY, Bowles KM, Quirós JR, Karakatsani A, La Vecchia C, Trichopoulou A, Salamanca-Fernández E, Huerta JM, Barricarte A, Travis RC, Tumino R, Masala G, Boeing H, Panico S, Kaaks R, Krämer A, Sieri S, Riboli E, Vineis P, Foll M, McKay J, Polidoro S, Sala N, Khaw KT, Vermeulen R, Campbell PJ, Papaemmanuil E, Minden MD, Tanay A, Balicer RD, Wareham NJ, Gerstung M, Dick JE, Brennan P, Vassiliou GS, Shlush LI. Nature 559: 2018 400-404	393
Integration of intra-sample contextual error modeling for improved detection of somatic mutations from deep sequencing. Abelson S, Zeng AGX, Nofech-Mozes I, Wang TT, Ng SWK, Minden MD, Pugh TJ, Awadalla P, Shlush LI, Murphy T, Chan SM, Dick JE, Bratman SV. Sci Adv 6: 2020 eabe3722	6
Interacting evolutionary pressures drive mutation dynamics and health outcomes in aging blood. Skead K, Ang Houle A, Abelson S, Agbessi M, Bruat V, Lin B, Soave D, Shlush L, Wright S, Dick J, Morris Q, Awadalla P. Nat Commun 12: 2021 4921	11