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Open Access Methodology article

Genome-wide CNV analysis replicates the association between GSTM1 deletion and bladder cancer: a support for using continuous measurement from SNP-array data

Gaëlle Marenne12, Francisco X Real13, Nathaniel Rothman4, Benjamin Rodríguez-Santiago35, Luis Pérez-Jurado3567, Manolis Kogevinas101189, Montse García-Closas4, Debra T Silverman4, Stephen J Chanock4, Emmanuelle Génin2 and Núria Malats1*

  • * Corresponding author: Núria Malats nmalats@cnio.es

  • † Equal contributors

Author Affiliations

1 Spanish National Cancer Research Center (CNIO), Madrid, E-28029, Spain

2 Inserm UMR-S946, Univ. Paris Diderot, Institut Universitaire d’Hématologie, Paris, F-75010, France

3 Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, E-08003, Spain

4 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20852-4907, USA

5 Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, E-08003, Spain

6 Programa de Medicina Molecular i Genètica, Hospital Universitari Vall d’Hebron, Barcelona, E-08003, Spain

7 Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA

8 Municipal Institute of Medical Research (IMIM-Hospital del Mar), Barcelona, E-08003, Spain

9 Centre for Research in Environmental Epidemiology (CREAL), Barcelona, E-08003, Spain

10 Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Barcelona, E-08003, Spain

11 National School of Public Health, Athens, G-11521, Greece

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BMC Genomics 2012, 13:326  doi:10.1186/1471-2164-13-326

Published: 20 July 2012

Abstract

Background

Structural variations such as copy number variants (CNV) influence the expression of different phenotypic traits. Algorithms to identify CNVs through SNP-array platforms are available. The ability to evaluate well-characterized CNVs such as GSTM1 (1p13.3) deletion provides an important opportunity to assess their performance.

Results

773 cases and 759 controls from the SBC/EPICURO Study were genotyped in the GSTM1 region using TaqMan, Multiplex Ligation-dependent Probe Amplification (MLPA), and Illumina Infinium 1 M SNP-array platforms. CNV callings provided by TaqMan and MLPA were highly concordant and replicated the association between GSTM1 and bladder cancer. This was not the case when CNVs were called using Illumina 1 M data through available algorithms since no deletion was detected across the study samples. In contrast, when the Log R Ratio (LRR) was used as a continuous measure for the 5 probes contained in this locus, we were able to detect their association with bladder cancer using simple regression models or more sophisticated methods such as the ones implemented in the CNVtools package.

Conclusions

This study highlights an important limitation in the CNV calling from SNP-array data in regions of common aberrations and suggests that there may be added advantage for using LRR as a continuous measure in association tests rather than relying on calling algorithms.

Keywords:
Bladder cancer risk; Glutathione S-transferase mu 1 (GSTM1); Copy number variation (CNV); SNP-array