Context
Second-generation antipsychotics (SGAs) are increasingly used in the treatment of many psychotic and nonpsychotic disorders. Unfortunately, SGAs are often associated with substantial weight gain, with no means to predict which patients are at greatest risk.
Objective
To identify single-nucleotide polymorphisms associated with antipsychotic drug–induced weight gain.
Design
Pharmacogenetic association study.
Setting
The discovery cohort was from a US general psychiatric hospital. Three additional cohorts were from psychiatric hospitals in the United States and Germany and from a European antipsychotic drug trial.
Participants
The discovery cohort consisted of 139 pediatric patients undergoing first exposure to SGAs. The 3 additional cohorts consisted of 73, 40, and 92 subjects.
Intervention
Patients in the discovery cohort were treated with SGAs for 12 weeks. Additional cohorts were treated for 6 and 12 weeks.
Main Outcome Measures
We conducted a genome-wide association study assessing weight gain associated with 12 weeks of SGA treatment in patients undergoing first exposure to antipsychotic drugs. We next genotyped 3 independent cohorts of subjects assessed for antipsychotic drug–induced weight gain.
Results
Our genome-wide association study yielded 20 single-nucleotide polymorphisms at a single locus exceeding a statistical threshold of P < 10−5. This locus, near the melanocortin 4 receptor (MC4R) gene, overlaps a region previously identified by large-scale genome-wide association studies of obesity in the general population. Effects were recessive, with minor allele homozygotes gaining extreme amounts of weight during the 12-week trial. These results were replicated in 3 additional cohorts, with rs489693 demonstrating consistent recessive effects; meta-analysis revealed a genome-wide significant effect (P = 5.59 × 10−12). Moreover, we observed consistent effects on related metabolic indices, including triglyceride, leptin, and insulin levels.
Conclusions
These data implicate MC4R in extreme SGA-induced weight gain and related metabolic disturbances. A priori identification of high-risk subjects could lead to alternative treatment strategies in this population.