Identification of ssri response biomarkers for depression by utilizing a pharmacometabolomicsinformed pharmacogenomic approach

Abstract

OBJECTIVES/SPECIFIC AIMS: Major depressive disorder (MDD) is a common psychiatric disease. Selective serotonin reuptake inhibitors (SSRIs) are an important class of drugs used to treat MDD. However, many patients do not respond adequately to SSRI therapy. We applied a pharmacometabolomics-informed pharmacogenomic research strategy to identify citalopram/escitalopram treatment outcome biomarkers. METHODS/ STUDY POPULATION: Metabolomic profiling using a gas chromatography-mass spectrometry platform was performed for plasma samples from 20 escitalopram remitters and 20 nonremitters who were enrolled in a large SSRI pharmacogenomic trial at Mayo. Pharmacometabolomic "signals" were then pursued by performing pharmacogenomic investigation of the possible role of inheritance in variation in response to SSRI treatment of MDD. RESULTS/ANTICIPATED RESULTS: Metabolomic analysis of MDD patients treated with SSRIs showed that baseline plasma glycine level was negatively associated with treatment outcome (p = 0.0054). Genotyping of tag single nucleotide polymorphisms (SNPs) for genes encoding glycine synthesis and degradation enzymes was then performed in 529 DNA samples from the Mayo Clinic SSRI study. The rs10975641 SNP in the glycine dehydrogenase gene was associated with treatment outcome phenotypes in both the initial study and 1245 MDD patients in the STAR*D study that was used for replication (p = 0.02). DISCUSSION/SIGNIFICANCE OF IMPACT: These results highlight both a possible role for glycine in SSRI response and the use of pharmacometabolomics to "inform" pharmacogenomics for the discovery of drug response biomarkers in personalized medicine