Schizophrenia (SZ) is a lifelong and devastating psychiatric illness with limited treatment options and no cure. Reduced dendritic spine density of layer 3 pyramidal neurons is among the most consistently reported findings in postmortem studies of SZ and has been reported in multiple brain regions including the primary auditory cortex (Al). This cytoarchitectonic abnormality is believed to underlie several symptom dimensions in SZ, including auditory processing deficits that impair social cognition and auditory hallucinations. Glutamate (Glu) signaling is essential for dendritic spine integrity and multiple lines of evidence implicate synaptic Glu signaling in SZ pathology. Many SZ risk loci code for proteins in the synaptic Glu signaling network and Glu receptor antagonists can induce or exacerbate SZ symptoms in humans and animal models. Thus, current evidence supports a model in which genetic risk factors converge on Glu signaling protein networks leading to the impairments in synaptic structure and activity believed to underlie SZ symptoms. As a first step in testing this model I utilized a targeted-mass spectrometry (MS) approach to quantify over 150 synaptic proteins in Al gray matter homogenates from 23 SZ and matched control subjects. The proteins altered in SZ were enriched for the Gene Ontology term Glutamate Signaling Pathway (p=2.5E-6, q=1.5E-3). Weighted gene co-expression network analysis (WGCNA) revealed a general decrease in the correlated expression of synaptic proteins (p=0.015). Both the dysregulated Glu Signaling Pathway and the de-correlated protein network included the Na+/K+ pump subunit ATP1A3. ATP1A3 mutations contribute to polygenic burden for SZ, and are linked to rapid onset dystonia parkinsonism, a syndrome which presents with cognitive impairments, and in which nearly 20% of patients have comorbid psychosis characterized by auditory hallucinations. Similarly, ATP1A3 +/- mice, in which ATP1A3 expression is decreased by only 15-20%, display cognitive impairments and psychosis like behaviors. My preliminary data further indicates altered expression of Glu signaling proteins in ATP1A3 +/- mouse cortex. Based on these observations I hypothesize that: The Glu signaling protein network is altered in Al deep layer 3 of SZ subjects and that decreased ATP1A3 protein expression contributes to these network alterations and Al deep layer 3 spine loss. I will test this hypothesis using a novel lasr capture microdissection-targeted MS (LCM-tMS) approach to identify Glu protein network alterations linked to spine loss directly in Al deep layer 3 of SZ subjects (Aim 1). Next, I will determine the impact of a 20% decrease in ATP1A3 on Al protein networks and spine density in ATP1A3 +/- mice (Aim 2). Finally, I will utilize quantitative fluorescence microscopy to localize alterations in ATP1A3, as well as selected protein alterations shared by SZ subjects and ATP1A3 +/- mice, to pyramidal or inhibitory cell soma within Al deep layer 3 of SZ subjects (Aim 3). Findings from these studies mapping synaptic Glu protein network impairments in disease will support ongoing drug discovery efforts, especially if homeostatic and/or pathological processes alter the expression of these drug targets in unexpected ways, an assertion strongly supported by my preliminary data. They will also identify novel protein and protein co- expression network alterations for future hypothesis testing (Aims 1 & 2). Localizing ATP1A3 reductions in patients will support the development of cell type specific animal models (Aims 2 & 3). These studies will also support my long term career goal of investigating synaptic pathology in SZ and related neuropsychiatric illnesses in my own NIH funded laboratory at a major medical research institution. They will provide training in three areas essential to achieving this goal: 1. MS based proteomic and systems biology approaches to protein network analysis: MS approaches are rapidly evolving and can now quantify tens-of-thousands of peptides from thousands or proteins in a single experiment. During this award I will receive continued training in these rapidly emerging MS methods and in the statistic, bioinformatic, and systems biology disciplines required for network analysis of complex proteomic data sets. 2. Translational mechanistic studies in genetic mouse models: Descriptive studies in postmortem brain tissue, while essential for identifying molecular alterations in disease, cannot determine the contribution of individual genes/proteins to pathophysiology. In the planned studies I will learn to investigate the effects of a candidate protein on synaptic protein networks and structural pathology, focused on the Na+/K+ pump and the role of ATP1A3. 3. Cortical cell and circuit pathology in SZ: The impact of dysregulated protein expression on cortical function depends on cell and circuit localization. Thus, I require training in laser capture microdissection and quantitative fluorescence microscopy to investigate proteins and protein networks within the context of cortical cells and circuits. To achieve these training aims I have assembled an outstanding mentorship team with primary mentor, Dr. Robert Sweet, a world leader in quantitative fluorescent microscopy and cortical cell and circuit pathology in SZ and Dr. Nathan Yates, an internationally recognized expert in MS based proteomics. The mentorship team has been augmented by the inclusion of consultants with additional expertise in laser capture, statistics, bioinformatics, systems biology, and Na+/K+ pump biology. At the completion of the proposed studies and training I will be an expert in applying cutting-edge proteomic, systems biology, and microscopy approaches to studies of SZ synaptic pathology in human tissue and animal models. Thus, in addition to serving as a compelling protein of interest in SZ, ATP1A3 will serve as a test case for advancing proteins of interest from MS discovery through translational investigations.

Public Health Relevance

Glutamate signaling protein network alterations are believed to underlie dendritic spine loss, contributing to cognitive and psychotic symptoms in schizophrenia; thus, these proteins are currently targets for the development of novel therapeutics. This project will map these glutamate signaling protein network alterations in schizophrenia, supporting the development of these compounds as well as identify novel drug targets. This project will also investigate the contribution of a candidate protein, ATP1A3, to glutamate signaling protein network alterations and spine loss in schizophrenia, validating a potential drug target and establishing a framework for advancing molecules out of proteomic discovery through translational studies.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01MH107756-04
Application #
9482458
Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Chavez, Mark
Project Start
2015-06-16
Project End
2019-05-31
Budget Start
2018-06-01
Budget End
2019-05-31
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Psychiatry
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
MacDonald, Matthew L; Favo, Daley; Garver, Megan et al. (2018) Laser capture microdissection-targeted mass spectrometry: a method for multiplexed protein quantification within individual layers of the cerebral cortex. Neuropsychopharmacology :
Krivinko, Josh M; Erickson, Susan L; Ding, Ying et al. (2018) Synaptic Proteome Compensation and Resilience to Psychosis in Alzheimer's Disease. Am J Psychiatry 175:999-1009
MacDonald, Matthew L; Alhassan, Jamil; Newman, Jason T et al. (2017) Selective Loss of Smaller Spines in Schizophrenia. Am J Psychiatry 174:586-594
Sweet, Robert A; MacDonald, Matthew L; Kirkwood, Caitlin M et al. (2016) Apolipoprotein E*4 (APOE*4) Genotype Is Associated with Altered Levels of Glutamate Signaling Proteins and Synaptic Coexpression Networks in the Prefrontal Cortex in Mild to Moderate Alzheimer Disease. Mol Cell Proteomics 15:2252-62
Wang, Ting; Ren, Zhao; Ding, Ying et al. (2016) FastGGM: An Efficient Algorithm for the Inference of Gaussian Graphical Model in Biological Networks. PLoS Comput Biol 12:e1004755
Kirkwood, Caitlin M; MacDonald, Matthew L; Schempf, Tadhg A et al. (2016) Altered Levels of Visinin-Like Protein 1 Correspond to Regional Neuronal Loss in Alzheimer Disease and Frontotemporal Lobar Degeneration. J Neuropathol Exp Neurol 75:175-82