M80 - METABOLIC ABNORMALITIES RELATED TO TREATMENT WITH SELECTIVE SEROTONIN REUPTAKE INHIBITORS IN PATIENTS WITH SCHIZOPHRENIA OR BIPOLAR DISORDER: A GENOME WIDE ASSOCIATION STUDY

Abstract

Background Patients’ tolerability and experienced efficacy of psychopharmacological drugs such as Selective Serotonin Reuptake Inhibitors (SSRIs) are influenced by both environmental and genetic factors. SSRIs are sometimes used as add-on therapy in schizophrenia and bipolar disorder. Association between use of SSRIs and metabolic abnormalities has been shown, but little is known about the genetic associations in this context. Our aim is to study genetic variations associated with individual differences in SSRI-induced metabolic side effects. Methods We conducted a genome-wide association study to identify genetic variants affecting susceptibility to SSRI-induced metabolic abnormalities by using data from the Norwegian Thematically Organized Psychosis study. Patients (n=1120) suffering from schizophrenia (n=719) or bipolar disorder (n=401) were included. SSRI exposure was expressed in dosages or serum concentrations of SSRIs (n=237). Metabolic outcome variables were: Levels of total cholesterol, low and high density lipoprotein (LDL and HDL) cholesterol, triglycerides, glucose and Body Mass Index (BMI). Single nucleotide polymorphisms (SNP) and use of SSRIs were tested for associations to outcome variables. To account for the effect of age, gender and co-medication with olanzapine, quetiapine or clozapine, these were included as covariates in the analysis. Results In preliminary analysis, we identified 31 regions associated with SSRI-induced metabolic abnormalities in outcome variables total cholesterol level, HDL- and LDL cholesterol levels and triglycerides (significance threshold: P Discussion The present findings indicate that SSRI-induced metabolic abnormalities are potentially affected by common genetic variation. Several markers were associated with triglyceride levels, with strongest signal seen for marker rs13428203, and for several markers in PRRC2A gene, previously associated with age-at-onset of insulin-dependent diabetes mellitus, as well as a possible involvement in the inflammatory process of pancreatic beta-cell destruction during development of insulin-dependent diabetes mellitus. Further, markers in APOE were associated with both total cholesterol-and LDL cholesterol levels. In addition, several variants in ACSL4 were associated with HDL cholesterol. Our findings warrant further investigation to elucidate the mechanisms involved, which may ultimately guide to the discovery of novel drug targets and predictive markers.