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Background Abnormalities of cellular signaling are well characterized in neuropsychiatric illnesses, including schizophrenia. Changes in signaling pathways reflect the underlying genetic, environmental, and epigenetic perturbations driving disease phenotypes. A shortcoming of most signaling studies is a focus on one or a few protein kinases at a time, a limitation since protein kinases work in networks with other kinases, phosphatases, and regulatory molecules to effect signaling events. We addressed this challenge by employing a kinome array platform that simultaneously measures protein kinase activity at hundreds of reporter peptide substrates. We then developed a novel bioinformatics pipeline to identify protein kinase nodes, signaling networks, upstream biological pathways, and drug candidates that “reverse” kinomic disease signatures. Methods Postmortem DLPFC brain samples from subjects with schizophrenia (n = 20 per group, 10 males and 10 females per group), were compared to age, PMI and pH matched control subjects (n = 20 per group, 10 males and 10 females per group) using the Pamgene12 serine/threonine kinome array chip. Samples were pooled by diagnosis and gender, and run in triplicate. The R-shiny app KRSA was created to automate assignment of kinases, perform permutation analyses, identify biological pathways, and connect to iLINCs for identification of drugs that reverse kinomic disease signatures. We also performed targeted confirmation studies using specific kinase activity assays, QPCR, and western blot analyses. Results We identified unique and common kinase nodes for each diagnostic group. Several of the nodes (for example AKT) are well characterized in schizophrenia, while others have not previously been identified (such as AMPK). We used AMPK KD cultures and AMPK KO brain tissues to demonstrate the validity if the kinome array for this protein kinase. We used standard kinase activity assays for AMPK and found decreased activity for AMPK (P &amp;lt; 0.05). We also found decreased expression of transcripts for the regulatory subunits of AMPK (P &amp;lt; 0.05). We identified several unique biological pathways, as well as candidate drugs, associated with the disease signature in schizophrenia. Discussion Our results confirm well characterized signaling defects in severe neuropsychiatric illness, and identify novel signaling nodes for further study. Confirmation studies for AMPK kinase show significant changes in expression and activity of this kinase, suggesting perturbation of energy sensing and production pathways in schizophrenia. Bioenergetic pathways may be targeted by myriad mechanisms, and we identified several drug candidates that might help restore this pathway in afflicted persons. Overall our novel workflow and pipeline provides a promising new avenue for understanding the complex signaling perturbations found in brain diseases and may provide new leads for developing treatments for schizophrenia and other cognitive disorders.

schizophrenia bulletin

S183. ABNORMALITIES IN SERINE/THREONINE SIGNALING NETWORKS IN SEVERE NEUROPSYCHIATRIC ILLNESS: DEVELOPMENT OF A PIPELINE TO EXPLORE ABNORMALITIES OF KINASE ACTIVITY AND IDENTIFY NOVEL TREATMENT STRATEGIES FOR SCHIZOPHRENIA