Journal article

Multi-SNP pharmacogenomic classifier is superior to single-SNP models for predicting drug outcome in complex diseases

Slavie Petrovski, Cassandra E Szoeke, Leslie J Sheffield, Wendyl D'Souza, Richard M Huggins, Terence J O'Brien

PHARMACOGENETICS AND GENOMICS | LIPPINCOTT WILLIAMS & WILKINS | Published : 2009

Abstract

OBJECTIVES: Most pharmacogenomic studies have attempted to identify single nucleotide polymorphism (SNP) markers that are predictive for treatment outcomes. It is, however, unlikely in complex diseases such as epilepsy, affecting heterogeneous populations, that a single SNP will adequately explain treatment outcomes. This study reports an approach to develop a multi-SNP model to classify treatment outcomes for such a disease and compares this with single-SNP models. METHODS: A prospectively collected dataset of outcomes in 115 patients newly treated for epilepsy, with genotyping for 4041 SNPs in 279 candidate genes, was used for the model development. A cross-validation-based methodology ide..

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Grants

Funding Acknowledgements

The Study was funded In part by a Pfizer Neuroscience Research Grant and the Victor Hurley Grant (chief investigator C.S.) and by the Royal Melbourne Hospital Neuroscience Research Foundation (chief investigator TJ.O.). BloGrid Australia (formerly Bio21: MNMIM) provided server space to house the databases and the implementation of an interface to facilitate data entry