Frontiers in GeneticsGenomicsPeer-reviewed journal article
Genome-wide association analyses identify variants in IRF4 associated with acute myeloid leukemia and myelodysplastic syndrome susceptibility
Junke WangiD, Alyssa Clay‐GilmouriD, Ezgi KaraesmeniD, Abbas Rizvi, Qianqian ZhuiD, Li YaniD, Leah M. Preus, Song LiuiD, Yiwen WangiD, Elizabeth A. GriffithsiD, Daniel O. StramiD, Loreall PooleriD, Xin ShengiD, Christopher A. HaimaniD, David Van Den BergiD, Amy WebbiD, Guy Nathaniel BrockiD, Stephen R. SpellmaniD, Marcelo C. PasquiniiD, Philip L. McCarthyiD, James M. AllaniD, Friedrich StölzeliD, Kenan OneliD, Theresa HahniD, Lara E. Sucheston‐CampbelliD
Abstract
The role of common genetic variation in susceptibility to acute myeloid leukemia (AML), and myelodysplastic syndrome (MDS), a group of rare clonal hematologic disorders characterized by dysplastic hematopoiesis and high mortality, remains unclear. We performed AML and MDS genome-wide association studies (GWAS) in the DISCOVeRY-BMT cohorts (2309 cases and 2814 controls). Association analysis based on subsets (ASSET) was used to conduct a summary statistics SNP-based analysis of MDS and AML subtypes. For each AML and MDS case and control we used PrediXcan to estimate the component of gene expression determined by their genetic profile and correlate this imputed gene expression level with risk of developing disease in a transcriptome-wide association study (TWAS). ASSET identified an increased risk for de novo AML and MDS (OR=1.38, 95% CI, 1.26-1.51, Pmeta=2.8x10-12) in patients carrying the T allele at rs12203592 in Interferon Regulatory Factor 4 (IRF4), a transcription factor which regulates myeloid and lymphoid hematopoietic differentiation. Our TWAS analyses showed increased IRF4 gene expression is associated with increased risk of de novo AML and MDS (OR=3.90, 95% CI, 2.36-6.44, Pmeta =1.0x10-7). The identification of IRF4 by both GWAS and TWAS contributes valuable insight on the role of genetic variation in AML and MDS susceptibility.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 17
- FWCI
- 1.96
- Field percentile
- top 13%
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