Neural Oscillatory Biomarkers for Genetics and Animal Models of Schizophrenia Project Summary: Neural oscillations are electrical activities of the brain measurable at different frequencies. They can be obtained at many levels, ranging from single cell to local field potentials in animals, to large-scale synchronized activities in human scalp. Patients with schizophrenia exhibit impaired neural oscillatory activities during sensory and cognitive tasks such as sensory gating, working memory, executive functions, and even at rest and during processing of monotonous visual and auditory stimuli. New evidence suggests that there may be common underlying abnormalities in oscillatory activities that are associated with schizophrenia-related cognitive and functional impairments. We have modified and developed experimental paradigms that will elicit oscillatory responses from basic sensory to more complex cognitive performance. We plan to isolate the common oscillatory abnormality in schizophrenia across tasks. In addition, since neural oscillations can be measured in animals and in humans in a similar fashion, it is possible to carry out parallel animal and human research using similar neural oscillatory measures as disease biomarkers. Towards this aim, these electrophysiological paradigms are constructed in a way that they are potentially feasible both in clinical population phenotyping and in small animal implementation, so that neural oscillatory biomarkers validated by this study in schizophrenia patients, and subsequent genetic findings from these neural oscillation phenotypes, can be applied to translational research in animals. Using the Building Translational Research in Integrative Behavioral Science mechanism, we propose to initiate similar paradigms in rodents. The basic neuroscience component of this application is to establish analogous rodent models using experimental paradigm closely matched with that of the human experiments, and then to conduct initial mechanistic studies on the pathophysiological origins of the abnormal neural oscillations found in patients with schizophrenia. This effort should lay the necessary groundwork for interpreting clinical findings and ultimately using neural oscillations as a translational tool in studying the molecular path from genes to pathophysiology and their treatment in schizophrenia. The neurogenesis of neural oscillations is under intense study. However, systematic investigations of their roles as disease phenotypes in schizophrenia populations are needed. The potentially novel biomarkers thus described and validated should significantly shorten the research cycle from biomarker discovery to gene identification and novel drug development in animal models.

Public Health Relevance

Schizophrenia is one of the most severe mental illnesses and causes significant disability in people suffered from it. This study will use brain electrical waves as potential biomarkers for identifying the pathophysiological and molecular causes for schizophrenia and related dysfunctions, which should lead to finding more specific and better treatment.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH085646-04
Application #
8460095
Study Section
Special Emphasis Panel (ZMH1-ERB-X (01))
Program Officer
Meinecke, Douglas L
Project Start
2010-07-01
Project End
2014-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
4
Fiscal Year
2013
Total Cost
$525,716
Indirect Cost
$175,239
Name
University of Maryland Baltimore
Department
Psychiatry
Type
Schools of Medicine
DUNS #
188435911
City
Baltimore
State
MD
Country
United States
Zip Code
21201
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Chiappelli, Joshua; Notarangelo, Francesca M; Pocivavsek, Ana et al. (2018) Influence of plasma cytokines on kynurenine and kynurenic acid in schizophrenia. Neuropsychopharmacology 43:1675-1680
Adhikari, Bhim M; Jahanshad, Neda; Shukla, Dinesh et al. (2018) Comparison of heritability estimates on resting state fMRI connectivity phenotypes using the ENIGMA analysis pipeline. Hum Brain Mapp 39:4893-4902
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Puvvada, Krishna C; Summerfelt, Ann; Du, Xiaoming et al. (2018) Delta Vs Gamma Auditory Steady State Synchrony in Schizophrenia. Schizophr Bull 44:378-387

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