Schizophrenia is a debilitating psychiatric illness that increases the risk for medical comorbidities, such as metabolic syndrome, diabetes, and cardiovascular disease. Metabolic comorbidities are the leading causes of premature death for veterans with schizophrenia. Although cellular and genetic studies have suggested that metabolic impairments may underlie neural dysfunction, studies in clinical neuroscience are limited. Resting state, functional magnetic resonance imaging (fMRI), is widely used as a clinical research tool and has identified a ?default mode network? that is hypermetabolic in schizophrenia and may underlie psychiatric symptoms. fMRI does not assay neural activity directly, and instead, reflects slow changes in the regional level of blood oxygen commonly interpreted as a surrogate for neural activity. Moreover, these metabolic signals are influenced by systemic physiology, including cardiorespiratory activity under the control of the autonomic nervous system. Metabolic signals from fMRI are typically modeled to reflect neurometabolic coupling, the recruitment of blood and oxygen to support active neural tissue. However, autonomic dysregulation and metabolic dysfunction can impair neurometabolic coupling. In schizophrenia, autonomic signals are dysregulated and are associated with aberrant default mode network activity, but links to neural activity and neurometabolic coupling remain unknown. Electroencephalography (EEG), can measure neural activity directly, but with limited temporal precision. The use of concurrent, simultaneous EEG-fMRI is a promising research tool utilized in animal and human studies to examine neurometabolic coupling. This CDA-1 proposal hypothesizes that neurometabolic coupling is dysregulated in schizophrenia and can be measured using simultaneous EEG-fMRI The experimental context for this CDA-1 is Dr. Judith Ford?s Merit grant, which examines simultaneously acquired EEG-fMRI data of cognitive processing during rumination and mindfulness. This CDA- 1 proposes a path to scientific independence by examining the role of neurometabolic coupling and autonomic activity in aberrant, resting brain activity in schizophrenia. Treatments targeting underlying pathology in schizophrenia are lacking and current pharmacotherapies exacerbate metabolic disease. Measures of neurometabolic coupling may serve as a biomarker to guide novel treatments, leading to new perspectives on the intersection between metabolic disease and mental health. This two-year CDA-1 provides training in the acquisition and analysis of simultaneous EEG-fMRI to examine neurometabolic coupling. In addition, this CDA -1 generates pilot data examining the role of autonomic activity in neurometabolic coupling to support a CDA-2 application. The career and training plan will develop the Principal Investigator?s expertise in multimodal, psychiatric neuroimaging through coursework, methodological workshops, and collaboration with established investigators. This study combines modalities (Autonomic signals, EEG and fMRI) to achieve two specific aims: 1) Examine the neuroanatomy and temporal dynamics of neurometabolic coupling in schizophrenia and, 2) Assess the role of autonomic activity on neurometabolic coupling in SZ, by measuring cardiorespiratory activity concurrently with simultaneous EEG-fMRI.
All aims support the primary goal of mentored training in simultaneous EEG-fMRI to develop scientific independence and expertise in the role of neurometabolism and autonomic activity in schizophrenia. This goal will be accomplished through this proposed CDA-1, the primary findings generated by Aim #1 and the pilot data generated by Aim #2 to support a CDA-2 application.
Metabolic illness is the leading cause of premature death in schizophrenia, a psychiatric illness affecting more than 250,000 veterans. Antipsychotic medications are the mainstay of treatment, ameliorating some psychotic symptoms, but can hasten metabolic syndrome. Metabolic abnormalities may underlie the neural deficits that contribute to psychotic symptoms. Clinical biomarkers of neurometabolism are needed to understand the coupling of metabolism to neural signals and advance novel treatments that may address combined neuropsychiatric and metabolic disease in schizophrenia. This study advances our understanding of neurometabolism in schizophrenia by simultaneously measuring neural activity from electroencephalography (EEG) and metabolic activity from functional magnetic resonance imaging (fMRI) to derive biomarkers of neurometabolic coupling in schizophrenia.
