Connectivity analyses of bioenergetic changes in schizophrenia: Identification of novel treatments

Courtney R. Sullivan; Catharine A. Mielnik; Sinead M. O’Donovan; Adam J. Funk; Eduard Bentea; Erica A.K. DePasquale; Zhexing Wen; Vahram Haroutunian; Pavel Katsel; Amy J. Ramsey; Jarek Meller; Robert E. McCullumsmith

Next, we aimed to identify therapeutic compounds with the potential to "reverse" glycolytic deficits as well as the associated changes in the L1000 genes. In order to select a potential drug intervention for preclinical testing, we relied on the 'connectivity' analysis to reveal positively (concordant) and negatively correlated (discordant) chemical (small molecule) and genetic perturbations. We developed a discovery based workflow to generate a list of small molecule perturbagens with L1000 transcript changes in the opposite direction of our knockdown signatures (based on concordance values from iLINCS, i.e. generating an "inverse/discordant signature") ( Figure 1 ). iLINCS provides over 40,000 transcriptomic profiles (signatures) of cell lines following treatment with chemical perturbagens such as FDA approved drugs, chemical probes, and screening library compounds including those with clinical utility and known mechanisms of action (19) . FDA approved drugs generated from this "knockdown signature connectivity" analysis could serve as candidates for therapeutic treatment in a preclinical model of schizophrenia. Peroxisome proliferator-activated receptor (PPAR) agonists had multiple hits in our analysis and similar drugs in this class are currently FDA approved for use in humans (21) .