Abstracts 1249 >400 downregulated. Functional annotation indicated over-representation of pathways related to nervous system development and neuronal function for the upregulated genes, and cellular responses to cytokines or organic substances for downregulated genes. We selected the top 23 DEG based on significance, fold- change and biological relevance, and used the nCounter Analysis System (NanoString) platform to validate these in an independent series of cell culture experiments. Clear validation was observed for ADAM23, LSP1, MAOB, MMP13, PAK3, SERPINB2, SNAP91, WNT6, and ZCCHC12. We also found that lithium at 1mM and 2mM co-regulated LSP1. The mood stabilizer lamotrogine did not appear to have signifi- cant regulatory effects on any of these genes. Using the NanoString platform, we also explored the ef- fects of the VPA analogue valpromide, and HDAC inhibitors (HDACi) including trichostatin A and CI994, on the selected genes. Expression of eight of the selected genes was mod- ified by exposure of RN46A to HDACi: ZCCHC12 was upreg- ulated by VPA and CI994 but downregulated by trichostatin A; SHANK3 was upregulated by CI994 but downregulated by TSA; CDKN1C, MAOB, NGFR and WNT6 were upregulated by CI994 only, and MMP13 and VGF were upregulated by TSA only. Discussion: We observed extensive gene expression changes in this serotonergic cell line when exposed to VPA for 72 hours, and many of these genes are involved in neuronal function or nervous system development. For the selected subgroup of genes, we observed complex regulatory effects of different HDACi or the non-HDACi VPA analogue valpro- mide, suggesting that VPA can exert its regulatory effects via both HDACi-dependent and independent properties. Understanding the broader gene regulatory effects of VPA in this serotonergic cell model should provide insights into how this widely used drug works, whether other HDACi com- pounds may have similar gene regulatory effects, and per- haps highlight molecular processes that may underlie regu- lation of mood. Disclosure: Nothing to disclose. doi: 10.1016/j.euroneuro.2018.08.331 SA110 PHARMACOGENETIC DECISION SUPPORT TOOLS AND SYMPTOM REMISSION: A META-ANALYSIS OF PROSPEC- TIVE RANDOMIZED CONTROLLED TRIALS IN MAJOR DEPRESSIVE DISORDER Chad Bousman 1 , Katarina Arandjelovic 2 , Serafino Mancuso 3 , Harris Eyre 3 , Dunlop Boadie 4 1 University of Calgary 2 Deakin University 3 University of Melbourne 4 Emory University Background: The clinical utility of pharmacogenetic deci- sion support tools remains uncertain and has been the topic of much debate. To assist antidepressant prescribers in their evaluation of these decision support tools, we conducted a systematic review and meta-analysis of randomized con- trolled trials (RCTs) that examined the effect of these tools on remission rates in major depressive disorder. Methods: Medline, Embase, Google Scholar, Pubmed and the Cochrane Database of Systematic Reviews were searched. Studies were selected, and quality assessed by two independent reviewers using the Cochrane Collabora- tion Criteria. Random-effects meta-analyses were used to calculate pooled relative risk (RR) of remission across the eligible RCTs. Results: Five prospective RCTs with a total of 1737 eli- gible subjects were identified and assessed. Although no- table risks of bias and a high degree of between study het- erogeneity (I-squared = 71%) were present in all five stud- ies, random-effects meta-analysis of the five RCTs revealed that individuals receiving pharmacogenetic-guided therapy (n = 887) were 1.71 (95% CI = 1.17 – 2.48, p = 0.005) times more likely to achieve symptom remission relative to indi- viduals who received treatment as usual (n = 850). Discussion: The current evidence suggests these phar- macogenetic decision support tools might improve treat- ment outcomes, particularly symptom remission among those with prior treatment failure/intolerance. However, industry-independent replication studies are required. Disclosure: Nothing to disclose. doi: 10.1016/j.euroneuro.2018.08.332 SA111 UNDERSTANDING EPIGENETICS OF SCHIZOPHRENIA USING GENETIC AND PHARMACOEPIGENOMIC AP- PROACHES Moinak Banerjee 1 , Swathy Babu 1 , Saradalekshmi KR 1 , Indu Nair 2 , Chandrashekaran Nair 3 1 Rajiv Gandhi Centre for Biotechnology 2 Mental Health Center, Thiruvananthapuram 3 Nair’s Hospital, Ernakulam Background: Schizophrenia is known to be influenced by both gene and environment. Based on this hypothesis the genetics and epigenetics have been extensively investi- gated. DNA methylation is one of the most common signa- tures of the environmental impact on the host epigenome. Several reports suggest differences in the pattern of DNA methylation both at global and gene specific level in Schizophrenia. However, many of these observations could not be replicated unanimously. In the present study we present the influence on epigenetics in the background of its genetic and antipsychotic medications. Methods: We first investigated the genetics of methylation by evaluating the genetic variation in DNMTs, folate cycle, methionine cycle and transulfuration cycle. The observa- tions from these will indicate how genetic variations can influence the methylome. Subsequently we investigated how antipsychotics can influence the host methylome. For this we first tried in an in-vitro cell culture system, and then followed it up in a clinical setting. For in-vitro we selected a human liver and a neuronal cell line. Cell lines