Second-generation antipsychotics (SGAs) are increasingly used in the treatment of many psychotic and non-psychotic disorders. Unfortunately, SGAs are often associated with substantial weight gain, with no means to predict which patients are at greatest risk.
To detect alleles of single nucleotide polymorphisms (SNPs) associated with antipsychotic drug-induced weight gain.
Pharmacogenetic association study
Discovery cohort was collected at a U.S. general psychiatric hospital. Three additional cohorts were collected from psychiatric hospitals in the U.S. and Germany, and from a European antipsychotic drug trial.
The discovery cohort was comprised of 139 pediatric patients undergoing first exposure to SGA treatment. An additional three cohorts were comprised of 73, 40 and 92 subjects.
Patients in the discovery cohort were treated with SGAs for twelve weeks. Additional cohorts were treated for six and twelve weeks.
Main outcome measure
We conducted a genome-wide association study (GWAS) assessing weight gain associated with twelve weeks of SGA treatment in patients undergoing first exposure to antipsychotic treatment. We next genotyped three independent cohorts of subjects assessed for antipsychotic drug-induced weight gain.
GWAS yielded twenty SNPs 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 GWAS of obesity in the general population. Effects were recessive, with minor allele homozygotes gaining extreme amounts of weight over the 12-week trial. These results were replicated in three additional cohorts with SNP 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 triglycerides, leptin, insulin, and HOMA-IR in our discovery cohort.
These data implicate the MC4R locus 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.