Association of tardive dyskinesia with variation in CYP2D6: Is there a role for active metabolites?. (July 2014)

• Record Type: Journal Article
• Authors: Koola, Maju M; Tsapakis, Evangelia M; Wright, Padraig; Smith, Shubulade; Kerwin (RIP), Robert W; Nugent, Katie L; Aitchison, Katherine J
• Is Part Of: Journal of psychopharmacology. Volume 28:Number 7(2014:Jul.)
• Page Start: 665
• Page End: 670
• Publication Date: 2014-07
• Subjects: Cytochrome P450 -- genotype -- antipsychotic -- tardive dyskinesia -- Parkinsonism; Psychopharmacology -- Periodicals; 615.78
• DOI: 10.1177/0269881114523861
• Languages: English
• ISSNs: 0269-8811

Abstract

Background: The aim of this study was to examine whether there was an association between tardive dyskinesia (TD) and number of functional CYP2D6 genes. Methods: A Caucasian sample of 70 patients was recruited in 1996–1997 from South London and Maudsley National Health Service (NHS) Foundation Trust, UK. Subjects had a DSM-IIIR diagnosis of schizophrenia and were treated with typical antipsychotics at doses equivalent to at least 100 mg chlorpromazine daily for at least 12 months prior to assessment. All patients were genotyped for CYP2D6 alleles *3–5, *41, and for amplifications of the gene. Results: There were 13 patients with TD. The mean (standard deviation (SD)) years of duration of antipsychotic treatment in TD-positive was 15.8 (7.9) vs TD-negative 11.1 (7.4) ( p =0.04). Increased odds of experiencing TD were associated with increased ability to metabolize CYP2D6, as measured by genotypic category (odds ratio (OR)=4.2), increasing duration in treatment (OR=1.0), and having drug-induced Parkinsonism (OR=9.7). Discussion: We found a significant association between CYP2D6 genotypic category and TD with the direction of effect being an increase in the number of functional CYP2D6 genes being associated with an increased risk of TD. This is the first study to examine the association between TD and CYP2D6 in Caucasians with this number of genotypic categories. In the future, metabolomics may be utilized in the discovery of biomarkers and novel drug targets.