NCT00088699 In the first years of this project, candidate gene studies implicated a few genes in treatment outcome and other genes in adverse effects. We also participated in a meta-analysis of three genome-wide association studies of antidepressant outcome. Despite greater power of this combined sample to uncover association with common genetic markers, no genome-wide significant associations were found. We concluded that no common alleles of large effect on antidepressant outcome exist in these samples. In recent years, we have been using high-throughput sequencing methods to test for rarer genetic variants that may exert larger effects, at least in patients whose depression is resistant to usual treatments. Treatment resistant depression (TRD) is a serious illness that can ruin lives and careers. Sequencing of the coding regions of the genome (exome) was completed on over 250 patients with TRD or with depression that responded to typical treatments. Some exome sequencing was carried out at the NIH Intramural Sequencing Center with funds provided by the NIH Clinical Center Genomics Opportunity (CCGO) program, which also provided exome sequence from about 200 non-psychiatric patients for comparison. To increase power, we also obtained exome sequence data from nearly 2,000 psychiatrically healthy controls available through dbGAP. Five different genes each carried exome-wide significant excess burdens of uncommon genetic variants in people with TRD. Analysis of 41 pre-selected gene sets suggested an excess of uncommon, functional variants among genes involved in lithium response. Among the genes identified in previous TRD studies, one, ZDHHC3, was also significant in this sample after multiple test correction. This gene regulates synaptic clustering of GABA and glutamate receptors involved in signaling between neurons. These results implicate uncommon, functional alleles in TRD and suggest promising novel targets for future research. In collaboration with Carlos Zarate and colleagues, and with the help of the NHLBI Stem Cell Core, we have also undertaken a series of studies aimed at characterizing the impact of antidepressant medication on gene expression and cellular morphology in human neurons derived from induced pluripotent stem cells. Early results from experiments with a metabolite of the novel antidepressant, ketamine, suggested that the drug changes expression of a large number of genes involved in regulation of cellular growth and development. Over the past year, we have used the same strategy to evaluate psilocin, the active metabolite of psilocybin, which has garnered recent attention as a potential rapid-acting therapy for TRD. Studies in mice have shown that a single dose of psilocin can increase dendritic spines and promote synapse formation, but this has so far not been demonstrated in human neurons due to the limitations of accessing the human brain. hiPSC-derived neurons present a unique opportunity to bridge this gap. In this study, we used confocal imaging of hiPSC-derived cortical neurons and multiple electrode array (MEA) assays to explore the impact of psilocin on neuronal morphology and electrophysiology. Seven paired cultures of hiPSC-derived, cortical neurons were treated for 1 week with either psilocin or vehicle. Psilocin significantly increased neurite number and also appeared to increase the average length of neurites, neurite path length, and neurite branch points. On the MEA, psilocyn significantly increased firing rate, mean spikes per burst, and other measures of neuronal network activity. These effects peaked 24 h after treatment and persisted for up to 2 days. These findings suggest that psilocin promotes both structural and functional changes in hiPSC-derived cortical neurons, leading to sustained increases in network activity. These in vitro effects may contribute to the putative antidepressant effects of psilocybin. We plan to carry out similar assays using other novel antidepressants in order to test the hypothesis that some novel antidepressants act through common, or overlapping, downstream mechanisms or signaling pathways. If this project is successful, identification of genes and biological pathways involved in response to antidepressant treatment could provide important clues about how to develop more effective antidepressant therapies in the future.