Literature DB >> 24159609

Genome-wide genotype-based risk model for survival in acute myeloid leukaemia patients with normal karyotype.

Hangseok Choi, Chulwon Jung, Sang Kyun Sohn, Seonwoo Kim, Hyeoung-Joon Kim, Yeo-Kyeoung Kim, TaeHyung Kim, Zhaolei Zhang, Eun-Soon Shin, Jong-Eun Lee, Joon Ho Moon, Sung Hyun Kim, Kyoung Ha Kim, Yeung-Chul Mun, Hawk Kim, Jinny Park, Jhingook Kim, Dennis Kim.   

Abstract

Single nucleotide polymorphisms (SNP) are inter-individual genetic variations that could explain inter-individual differences of response/survival to chemotherapy. The present study was performed to build up a risk model for survival in 247 patients with acute myeloid leukaemia (AML) with normal karyotype (AML-NK). Genome-wide Affymetrix SNP array 6.0 was used for genotyping in discovery set (n = 118). After identifying significant SNPs for overall survival (OS) in single SNP analysis, a risk model was constructed. Out of 632 957 autosomal SNPs analysed, finally four SNPs (rs2826063, rs12791420, rs11623492 and rs2575369) were introduced into the risk model. The model could stratify the patients according to their OS in discovery set (P = 1·053656 × 10−4). Replication was performed using Sequenom platform for genotyping in the validation cohort (n = 129). The model incorporated with clinical and four SNP risk score was successfully replicated in a validation set (P = 5·38206 × 10−3). The integration of four SNPs and clinical factors into the risk model showed higher area under the curve (AUC) reults than in the model incorporating only clinical or only four SNPs, suggesting improved prognostic stratification power by combination of four SNPs and clinical factors. In conclusion, a genome-wide SNP-based risk model in 247 patients with AML-NK can identify a group of high risk patients with poor survival.

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Year:  2013        PMID: 24159609     DOI: 10.1111/bjh.12492

Source DB:  PubMed          Journal:  Br J Haematol        ISSN: 0007-1048            Impact factor:   6.998


  2 in total

1.  Prediction of a time-to-event trait using genome wide SNP data.

Authors:  Jinseog Kim; Insuk Sohn; Dae-Soon Son; Dong Hwan Kim; Taejin Ahn; Sin-Ho Jung
Journal:  BMC Bioinformatics       Date:  2013-02-19       Impact factor: 3.169

2.  The AutGO Initiative: A Conceptual Framework for Developing Genetics-Outcomes Research Hypotheses.

Authors:  Zohreh Talebizadeh; Ayten Shah
Journal:  Autism Res       Date:  2020-07-03       Impact factor: 5.216

  2 in total

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