Abstract: Good long-term social outcome of schizophrenia (SZ) subjects is as low as 14%. Because of this, substantial number of SZ subjects suffer from severe and protracted disability. An important contributing factor to poor long-term outcome in schizophrenia is cognitive impairments that are resistant to current treatments. Therefore, it is critical to examine novel mechanisms underlying cognitive impairments to design new treatments. Recent evidence suggests that brain cortical regions and white matter pathways that connect them adapt to pathophysiological processes. Such adaptation can mitigate impairments in selected cognitive domains offering hopes to target selected networks for interventions to improve outcome. Using state-of-art non-invasive neuroimaging techniques, adaptation between the cortical neuropil (synapses, dendrites and its branches, axonal endings and interneurons) and white matter integrity measured using characteristics of water diffusion in white matter fibers can be investigated. The goal of this project is to characterize concurrent changes in cortical neuropil and anisotropy of water diffusion in white matter fiber tracts as a model of neural circuitry adaptability (NCA) and its impact on cognitive performance among SZ subjects compared to healthy control subjects (HC). We will use phosphorus magnetic resonance spectroscopy (31P MRS) at ultra-high magnetic field (7 Tesla) that provides greater sensitivity to investigate neuropil by measuring membrane phospholipid (MPL) metabolites in multiple anatomically well-defined regions across the entire brain. MPLs are critical ingredients of neuronal membranes that naturally form lipid bilayers separating the intra- and extra-cellular environments. During development and disease, imbalance between synthesis and degradation of membranes can be reliably captured. Broadly, higher MPL precursor levels are associated with membrane expansion while higher MPL breakdown products suggest neuropil membrane contraction. Since such dynamic changes are prominently observed in the neuropil, 31P MRS can provide a more specific measure of neuropil than structural imaging measures that includes neuropil as well as interneuronal space, microvasculature and neuronal soma. Neurite Orientation Dispersion and Density Imaging (NODDI) - a state-of-the-art method to measure diffusion of water along white matter tracts and neurite density- will be used to examine integrity of white matter pathways more reliably than the older method of diffusion tensor imaging. Innovative nature of this proposal is highlighted by concurrent changes in MPL metabolites and anisotropy as measures of NCA in relation to cognitive impairments since using single modality imaging cannot measure adaptive changes in multiple tissues. Using our model of NCA by employing multi-modal 31P MRS-NODDI data, we seek to examine association of NCA with cognitive performance across the whole-brain (aim 1). Additionally, factors associated with NCA are unknown. Since SZ is a highly heritable disorder, and inflammation is associated with SZ, we will examine the contribution of selected genetic and peripheral inflammatory markers (Interleukin-6, IL6 and C-reactive protein, CRP) to NCA. Our studies found association of Complement C4A (C4A) gene copy numbers with neuropil changes, and of IL-6 and CRP levels with alterations in neuropil and white matter anisotropy. Based this evidence, our next aim is to determine the association of C4A copy numbers and peripheral immune mediator levels with measures of NCA among SZ and HC (aim 2). Application of integrated state-of-the-art methods to examine a less well understood concept of NCA in SZ makes this proposal highly unique and can have significant impact on novel treatment designs. These efforts may allow us to target adaptable tracts for novel interventions such as customized cognitive enhancement therapies and electrical stimulation strategies using transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) targeted to selected networks.

Public Health Significance Schizophrenia is a chronic and severely debilitating brain disorder with poor outcome. Treatments are symptomatic and the causes are unknown. The associated disability and morbidity adds to major public health burden of severe mental illness. Gaining a greater understanding of the underlying mechanisms associated with cognitive impairments could lead to identification of novel targets for innovative treatments. The proposed effort is driven by intriguing data from diffusion tensor imaging and magnetic resonance spectroscopy. The goal of this proposal to combine these modalities of imaging to understand the neural circuitry resilience – adaptation of neurons to internal and external changes, among SZ that may modulate cognitive impairments that contribute significantly to poor outcome. Currently available treatments minimally affect cognitive impairments. Therefore, the results of this study can potentially help improve long term outcome.