Vs. Basile et al., Genetic dissection of atypical antipsychotic-induced weight gain: Novel preliminary data on the pharmacogenetic puzzle, J CLIN PSY, 62, 2001, pp. 45-66
Atypical antipsychotics such as clozapine represent a significant improveme
nt over typical antipsychotics in the treatment of schizophrenia, particula
rly regarding extrapyramidal symptoms. Despite their benefits, use is limit
ed by the occurrence of adverse reactions such as sedation and weight gain.
This article provides a comprehensive review and discussion of obesity-rel
ated pathways and integrates these with the known mechanisms of atypical an
tipsychotic action to identify candidate molecules that may be disrupted du
ring antipsychotic treatment, Novel preliminary data are presented to genet
ically dissect these obesity pathways and elucidate the genetic contributio
n of these candidate molecules to clozapine-induced weight gain. There is c
onsiderable variability among individuals with respect to the ability of cl
ozapine to induce weight gain. Genetic predisposition to clozapine-induced
weight gain has been suggested. Therefore, genetic variation in these candi
date molecules may predict patient susceptibility to clozapine-induced weig
ht gain. This hypothesis was tested for 10 genetic polymorphisms across 9 c
andidate genes, including the serotonin 2C, 2A, and 1A receptor genes (HTR2
C/2A/1A); the histamine H-1 and H-2 receptor genes (H1R/H2R); the cytochrom
e P450 1A2 gene (CYP1A2); the beta (3) and alpha (1a)-adrenergic receptor g
enes (ADRB3/ADRA1A); and tumor necrosis factor-alpha (TNF-alpha). Prospecti
ve weight gain data were obtained for 80 patients with schizophrenia who co
mpleted a structured clozapine trial. Trends were observed for ADRB3, ADRA1
A, TNF-alpha, and HTR2C; however, replication in larger, independent sample
s is required. Although in its infancy, psychiatric pharmacogenetics will i
n the future aid clinical practice in the prediction of response and side e
ffects, such as antipsychotic-induced weight gain, and minimize the current
"trial and error" approach to prescribing.