• Joanne M Droney, Sophy K Gretton, Hiroe Sato, Joy R Ross, Ruth Branford, Kenneth I Welsh, William Cookson, and Julia Riley.
• Imperial College, London, UK. j.droney@nhs.net
• Br J Clin Pharmacol. 2013 May 1;75(5):1340-50.

AimsTo present a statistical model for defining interindividual variation in response to morphine and to use this model in a preliminary hypothesis-generating multivariate genetic association study.MethodsTwo hundred and sixty-four cancer patients taking oral morphine were included in a prospective observational study. Pain and morphine side-effect scores were examined using principal components analysis. The resulting principal components were used in an exploratory genetic association study of single nucleotide polymorphisms across the genes coding for the three opioid receptors, OPRM1, OPRK1 and OPRD1. Associations in multivariate models, including potential clinical confounders, were explored.ResultsTwo principal components corresponding to residual pain and central side-effects were identified. These components accounted for 42 and 18% of the variability in morphine response, respectively, were independent of each other and only mildly correlated. The genetic and clinical factors associated with these components were markedly different. Multivariate regression modelling, including clinical and genetic factors, accounted for only 12% of variability in residual pain on morphine and 3% of variability in central side-effects.ConclusionsAlthough replication is required, this data-driven analysis suggests that pain and central side-effects on morphine may be two separate dimensions of morphine response. Larger study samples are necessary to investigate potential genetic and clinical associations comprehensively.© 2012 The Authors. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society.

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