Abstract

Identifying risk factors for drug-related side effects represents the foundation of pharmacogenomics. Prediction of risk for antipsychoticinduced weight gain (AIWG) is poor. This common side effect of antipsychotics [1] frequently leads to risk of relapse of psychopathology from dose reduction, drug substitution or noncompliance driven by health and psychological concerns. Yet, the individual variability of AIWG is striking, and family studies have suggested substantial genetic contributions to AIWG risk [2]. Currently, no genetic tests for AIWG are endorsed for clinical application. However, the strength of recent findings linking common variants in energy balance genes with AIWG raise the question – has the pharmacogenomics of AIWG reached clinical significance? Initial studies of the role of monoaminergic candidate gene variants as predictors of AIWG were mixed owing to small samples, population stratification and limited end point data. One exception has been a widely replicated association between a promoter SNP in HTR2C [3]. Nevertheless, variance in AIWG explained by the -759 SNP in HTR2C was small in comparison to AIWG’s estimated heritability, and thusly no consensus supports clinical HTR2C testing despite available commercial tests. AIWG is thought to be multi factorial and polygenic, paralleling obesity per se, and new research has pointed to a broader array of genes and systems hypothesized to underpin AIWG, suggested by the identif ication of over 30 genome-wide significant risk genes for obesity, as well as results from genome-wide pharmacogenomic analyses of the CATIE study of antipsychotic-treated adults with schizophrenia. In the CATIE analyses, weight gain and metabolic effects were significantly associated with

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