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Pharmacogenomics J. 2015 Oct;15(5):414-21. doi: 10.1038/tpj.2015.9. Epub 2015 Mar 10.

Exome sequencing and array-based comparative genomic hybridisation analysis of preferential 6-methylmercaptopurine producers.

Author information

1
Carney Centre for Pharmacogenomics and Department of Pathology, University of Otago Christchurch, Christchurch, New Zealand.
2
Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
3
Department of Clinical Pharmacology, Christchurch Hospital, Canterbury District Health Board, Christchurch, New Zealand.
4
Department of Medicine, University of Otago Christchurch, Christchurch, New Zealand.
5
Molecular Pathology, Canterbury Health Laboratories, Christchurch, New Zealand.
6
School of Biological Sciences, University of Auckland, Auckland, New Zealand.

Abstract

Preferential conversion of azathioprine or 6-mercaptopurine into methylated metabolites is a major cause of thiopurine resistance. To seek potentially Mendelian causes of thiopurine hypermethylation, we recruited 12 individuals who exhibited extreme therapeutic resistance while taking azathioprine or 6-mercaptopurine and performed whole-exome sequencing (WES) and copy-number variant analysis by array-based comparative genomic hybridisation (aCGH). Exome-wide variant filtering highlighted four genes potentially associated with thiopurine metabolism (ENOSF1 and NFS1), transport (SLC17A4) or therapeutic action (RCC2). However, variants of each gene were found only in two or three patients, and it is unclear whether these genes could influence thiopurine hypermethylation. Analysis by aCGH did not identify any unusual or pathogenic copy-number variants. This suggests that if causative mutations for the hypermethylation phenotype exist they may be heterogeneous, occurring in several different genes, or they may lie within regulatory regions not captured by WES. Alternatively, hypermethylation may arise from the involvement of multiple genes with small effects. To test this hypothesis would require recruitment of large patient samples and application of genome-wide association studies.

PMID:
25752523
DOI:
10.1038/tpj.2015.9
[Indexed for MEDLINE]

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