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Published on: February 4, 2014
Outcome definitions and clinical predictors influence pharmacogenetic associations between HTR3A gene polymorphisms
A P Rajkumar1, B Poonkuzhali, A Kuruvilla
1Department of Psychiatry, Christian Medical College, Vellore 632002, India.
Rationale:
Pharmacogenetics of schizophrenia has not yet delivered anticipated clinical dividends. Clinical heterogeneity of schizophrenia contributes to the poor replication of the findings of pharmacogenetic association studies. Functionally important HTR3A gene single-nucleotide polymorphisms (SNPs) were reported to be associated with response to clozapine.
Objective:
The aim of this study was to investigate how the association between HTR3A gene SNP and response to clozapine is influenced by various clinical predictors and by differing outcome definitions in patients with treatment-resistant schizophrenia (TRS).
Methods:
We recruited 101 consecutive patients with TRS, on stable doses of clozapine, and evaluated their HTR3A gene SNP (rs1062613 and rs2276302), psychopathology, and serum clozapine levels. We assessed their socio-demographic and clinical profiles, premorbid adjustment, traumatic events, cognition, and disability using standard assessment schedules. We evaluated their response to clozapine, by employing six differing outcome definitions. We employed appropriate multivariate statistics to calculate allelic and genotypic association, accounting for the effects of various clinical variables.
Results:
T allele of rs1062613 and G allele of rs2276302 were significantly associated with good clinical response to clozapine (p = 0.02). However, varying outcome definitions make these associations inconsistent. rs1062613 and rs2276302 could explain only 13.8 % variability in the responses to clozapine, while combined clinical predictors and HTR3A pharmacogenetic association model could explain 38 % variability.
Conclusions:
We demonstrated that the results of pharmacogenetic studies in schizophrenia depend heavily on their outcome definitions and that combined clinical and pharmacogenetic models have better predictive values. Future pharmacogenetic studies should employ multiple outcome definitions and should evaluate associated clinical variables.
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