Katherine L. Narr - US grants

[unreadable] DESCRIPTION (provided by applicant): This career development plan will support the candidate's goals of mastering new imaging methodologies to investigate multiple aspects of a specific brain system in schizophrenia. This systems approach will allow a deeper understanding of the mechanisms associated with declarative memory (DM) impairments that are mediated by the medial temporal lobe (MTL) memory system (hippocampus, parahippocampal region and cerebral cortex). Guidance from accomplished investigators, state-of-the-art imaging facilities, and didactic training provide the infrastructure needed to achieve these goals. The rich institutional environment at UCLA further supports the candidate's long-term plan to develop a productive and independent program of research using imaging methods to better understand the pathophysiological underpinnings of brain disturbances in neuropsychiatric disorders. DM impairments and hippocampal volume reductions are shown particularly vulnerable to disease processes in schizophrenia and to indicate a genetic predisposition towards the illness. However, it is uncertain whether abnormalities of declarative memory (DM) reflect disturbances in regional brain activity and/or in functional connectivity and whether such impairments relate to structural abnormalities within this neural network. To address these questions, the candidate will combine structural, functional and diffusion tensor imaging to map structural and functional abnormalities of the MTL memory system in schizophrenia patients, first-degree relatives of patients and healthy comparison subjects recruited through a larger NIMH study, "Transmission of Vulnerability Factors for Schizophrenia." The research plan includes advanced structural image analysis techniques and functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) strategies that will be employed to dissociate the structural and functional correlates of MTL disturbances including declarative memory deficits in schizophrenia and to establish the presence of genetic liability effects. [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Major Depressive Disorder (MDD) disrupts the lives of millions of people each year and presents a substantial societal and economic burden. Despite prior research, the mechanisms underlying treatment response and relapse in MDD remain unclear. Several treatments for MDD are available, but establishing the best form of treatment can be a protracted trial and error process where some patients remain unresponsive. Advances in imaging technologies and in computational image analysis techniques continue to provide new and unique opportunities for elucidating the neurobiological bases of MDD and the neural processes associated with treatment success. To accelerate knowledge in this area, we propose to apply a leading-edge multimodal imaging approach to identify biomarkers indexing complementary aspects of treatment-induced brain plasticity focusing on fronto-limbic and striatal circuitry. Magnetic resonance imaging (MRI) will include structural, functional, diffusion and perfusion imaging and MR proton magnetic resonance spectroscopy (1HMRS), which jointly reflect brain chemistry, morphology, tissue architecture, resting state activity and blood flow, which is coupled to metabolism. Longitudinal and cross-sectional analyses will identify baseline factors and treatment-related changes in imaging biomarkers predictive of treatment outcome that may translate into the clinical setting to guide more effective treatment strategies. Electroconvulsive therapy (ECT), used to treat refractory depression, is an established and highly effective procedure eliciting a rapid response in eligible individuals. Since response occurs over a relatively short time period compared to psycho- or pharmacotherapy, ECT will be used as the treatment model to establish neurobiological correlates of therapeutic response. Patients with MDD will be followed prospectively to characterize the trajectories of ECT-related biological responses, which are expected to overlap those of other forms of treatment. Imaging will be performed at 4 time points: prior to the 1st ECT treatment, after the 2nd ECT session, 1 week after completion of the ECT index series and at 6- months post treatment when relapse will be determined. Clinical assessments will be made at two additional interval time points. Demographically similar control subjects will be imaged twice to allow estimation of the variance associated with serial assessments and to determine normalization of biomarkers in association with treatment success in MDD. The potential impact of the proposed research to science and health is large. New scientific leads may inform novel treatment approaches, identify individuals at risk for developing depression, elucidate disease-related genetic or endophenotypic factors, identify subpopulations of MDD patients who are more likely to benefit from a particular treatment, and may predictively identify patients at high risk for relapse thereby allowing for the use of alternate or more aggressive individualized treatment strategies. Multimodal longitudinal imaging in the context of the rapid clinical response to ECT is an innovative approach ideally suited for charting the trajectory of mental illness to determine where, when and how to intervene.

DESCRIPTION (provided by applicant): Major depressive disorder (MDD) is a serious and recurrent illness and a leading cause of disability. Though treatments are available, these often take weeks to months to exert their effect, and some people only respond partially or do not respond at all. To guide more effective, faster acting and personalized treatment strategies in the clinical setting, there is thus an important need to identify biological markers predictive of rapid therapeutic response. To advance discovery in this area, this K24 proposal includes mentorship, career development and research aims that build onto the goals of our NIH-funded R01 (MH092301), which is focused on using advanced neuroimaging methods to detect different aspects of treatment-related brain plasticity in MDD. Electroconvulsive therapy (ECT), which is currently the most effective acute treatment for severe MDD and which involves direct action on the central nervous system, is used as the R01 treatment modality. Since a combination of biological markers may better characterize the mechanisms and predictors of treatment response, as a recent adjunct to our R01, we are also examining peripheral lymphocyte gene expression to more comprehensively address the biological bases of rapid therapeutic response to ECT. Producing a clinical response within hours, the NMDA receptor antagonist, ketamine, has recently emerged as a novel pharmacologic agent for depression treatment with a response rate comparable only to ECT. To obtain a greater understanding of the biological processes underlying fast-acting therapies and to confirm basic science findings implicating glutamatergic pathways, the candidate's K24 Research Plan is to identify imaging and gene expression markers of therapeutic response to ketamine treatment. To target overlapping rapid response mechanisms, by leveraging data from our R01 project, candidate markers of response to ketamine and ECT will be compared. Novel imaging methods applied in a subsample of ketamine patients will provide further opportunity to explore treatment-related neuroplasticity localized to dorsal and/or ventral fronto-limbic networks. To allow the candidate to better design and lead clinical studies incorporating interdisciplinary approaches to investigate and compare mechanisms of rapid antidepressant action, the candidate's Career Development Plan is to develop knowledge and/or new skills in the field of genomics and in the pharmacological basis of antidepressant treatments for MDD as well as also hone existing skills in neuroimaging. In line with the candidate's area of expertise in imaging and clinical neuroscience, the Mentoring Plan will provide theoretical and hands-on training to mentees in clinical imaging applications directed towards the longitudinal investigation of treatment mechanisms in MDD and potentially in other psychiatric conditions, and the skills to successfully incorporate imaging methods into patient-oriented research (POR) programs that will lead to future independent funding. The candidate's research and career development aims, which are both complementary and unique to our funded R01, will provide a rich basis for training while furthering POR in a critical area.

? DESCRIPTION (provided by applicant): Depression affects a large portion of the world's population. Though treatable, two thirds of patients will not respond sufficiently to two or more standard pharmacotherapies and will be defined as treatment resistant (TRD). Quality of life for these individuals is extremely low and unremitting symptoms lead to loss of productivity, impaired social relationships, high health care costs, and in some cases, loss of life by suicide. Though several different brain networks are implicated, despite much research, the mechanisms causal to depression and its successful treatment remain unclear. The overarching goal of the current proposal is to leverage optimized non-invasive MRI technologies and normative data available through the NIMH/NIA-funded Human Connectome Project (HCP, U54 MH091657) to 1) identify connectome-specific correlates and predictors of successful treatment outcome to 3 therapeutic interventions, each with a rapid onset of action and to 2) characterize alterations in neural connectivity associated with individual clinical, behavioral and physiologica differences across TRD. Following harmonization of HCP MRI protocols, structural, functional and diffusion MRI data and behavioral testing batteries modeled from the HCP Lifespan protocol with added clinical assessments will be collected. Arterial spin labeling (ASL) perfusion MRI, measuring cerebral blood flow, and peripheral blood measures of gene function will supplement these protocols. Our first aim is longitudinal and will determine whether changes in brain network connectivity relate to and predict response to fast-acting perturbations known to elicit robust antidepressant effects. These perturbations include electroconvulsive therapy (ECT), serial ketamine infusion and total sleep deprivation (TSD). Since TRD includes different categorical diagnoses such as unipolar and bipolar depression and other comorbidities, our second specific aim is cross-sectional and will determine if heterogeneity in behavioral and symptom profiles, clinical histories and sex and age contribute to variations in the patterns of altered structural and functional connectivity in TRD. Subjects will include 200 patients clinicall eligible to receive ECT (n=60), serial ketamine (n=60) or TSD (n=80) and 140 controls, combining control data collected locally (n=40) with control data from the HCP resource (n=100). Each patient will receive MRI, behavioral/cognitive testing and a blood draw before and after completing one of the interventions. Behavioral constructs and sub-constructs of interest will include cognitive control, negativity bias and rumination and reward hypersensitivity, widely implicated in depression, functions that are governed by prefrontal and anterior cingulate cortex (cognitive control, mood regulation) and amygdala, hippocampus, ventral striatum/pallidum (emotion and reward) regions and circuitry. Data will be released to the scientific community through the Connectome Coordination Facility. The infrastructure of the HCP provides an unprecedented opportunity for to discover the mechanisms of disease and treatment response, which could lead to more effective treatment strategies based on individual connectivity profiles.

PROJECT SUMMARY DESCRIPTION: Dementia, especially Alzheimer's dementia (AD), is a growing public health problem with a prevalence of 5M in the US alone (33M worldwide). Despite a decrease in incidence rates, with the aging of the population, the prevalence of dementia is expected to increase to 16M in the US (115M worldwide) with associated costs rising to $1T. Delaying long-term care by 1 month for older Americans would save $60B annually in direct care cost. Efforts to prevent or delay dementia have been largely unsuccessful. However, major depressive disorder in late life (?late-life depression?, LLD) has been identified as one of six treatable risk factors for dementia, especially AD and vascular dementia. The depression-dementia relationship may be magnified in elders who do not respond to antidepressant treatment and experience persistent symptoms. Thus, resolving whether those with treatment-resistant late-life depression (TRLLD) are at higher risk of cognitive decline and progression to dementia compared to those with treatment-responsive LLD is critically important. Leveraging a Patient-Centered Outcomes Research Institute (PCORI)-funded treatment study of N=1500 people with LLD, across 5 sites, we propose to comprehensively delineate neurocognitive and neuroimaging biomarkers associated with progression to dementia in people with persistent LLD (i.e., TRLLD) compared to those whose LLD remits with treatment. We anticipate enrolling 750 elders with LLD and characterizing their symptomatic trajectory over 24 months. We will assess each participant at three time points with neurocognitive and advanced neuroimaging. We hypothesize that changes in executive functions and the executive control network, as well as changes in episodic memory and the default mode/cortico-limbic network, will be greater in those with TRLLD than in those who respond to treatment and stay well. We also hypothesize that changes over two years in executive function and episodic memory will be specifically associated with changes in executive- control and cortico-limbic circuitry, respectively. Based on our recent findings that inflammatory and related molecular markers can differentiate those with neurocognitive impairment and LLD from those with LLD alone, we will build a predictive multivariate model combining baseline neurocognitive, neuroimaging, and plasma protein data to determine who is at greatest risk for cognitive decline and dementia. Finally, we will also explore whether latent class trajectories of depressive symptoms can go beyond the dichotomy of remission/non-remission to identify subsets of elders with LLD at highest risk of cognitive decline, neural circuit change, and progression to dementia. This work will set the stage for neural circuit- targeted preventive care to delay dementia in subsets of older patients with LLD. If successful, our work can accelerate therapeutic efforts and innovation targeting the depression- dementia pathway and reduce suffering for large numbers of elders and their families.

PROJECT SUMMARY First-line pharmacotherapies for major depressive disorder (MDD) are only moderately successful. With anodal stimulation of the left dorsolateral prefrontal cortex (DLPFC), transcranial direct current stimulation (tDCS), a low-intensity neuromodulation technique of minimal risk, may elicit antidepressant effects and improve cognitive control in individuals with MDD. Prior evidence suggests that prefrontal-limbic circuits, including the DLPFC and dorsomedial anterior cingulate cortex (dACC), are involved in the regulation of mood and emotion. Their modulation by tDCS may thus contribute to antidepressant effects. However, the extent to which these regions are engaged by tDCS and how their recruitment contributes to clinical response is unknown. Response to tDCS also remains mixed at the individual level where the size, location and intensity of stimulation might account for varied therapeutic effects. Recently, high definition (HD) tDCS has been developed that allows for more focal neural stimulation. During the R61 phase of this Exploratory Clinical Trial we aim to apply and compare HD-tDCS, conventional tDCS (C-tDCS) and sham tDCS in patients with moderate to severe MDD (N=60, n=20 in each group) to test for differences in the engagement of mood regulating DLPFC and dACC regions between conditions using a randomized, double blind design. We will use MRI-guided stereotaxy to optimize and standardize DLPFC electrode placement and novel MRI techniques with concurrent tDCS to test the regional distribution of tDCS current at different stimulation intensities. We will use 3D GRASE pseudo- continuous arterial spin labeling (pCASL) MRI, compared before and after subjects complete 12 daily 30 minute sessions of 2 mA stimulation, to test for tDCS-related changes in regional cerebral blood flow (rCBF) in prefrontal circuitry. Significant tDCS induced magnetic field changes in DLPFC and significant changes in rCBF between baseline and the end of the tDCS trial in the DLPFC and dACC for either of the active tDCS conditions compared to sham will constitute the go-no-go criterion for proceeding to the R33 Phase. Using the active tDCS modality showing greater target engagement and neurophysiological effects without peripheral side effects, the R33 Phase will randomize patients with moderate to severe MDD (N=100, n=50 in each group) to active or sham left anodal DLPFC tDCS. Patients will again complete MRI scans including tDCS- current mapping and pCASL as well as two functional imaging tasks probing cognitive control and emotion negativity bias, recruiting prefrontal-limbic circuitry, before and after completing a 12-day trial of 30-minute tDCS sessions. Demonstration that target engagement with active tDCS varies in association with improved mood (primary outcome), cognitive function and changes in task-related brain activation (secondary outcomes) will constitute the criterion for continued R01 investigation. Results of this trial are expected to lead to an optimized MRI guided tDCS treatment of MDD and deepen understanding of the physiological mechanisms of tDCS therapy.

Quantum sciences and technologies have progressed remarkably in recent years. This progress includes, for example, new quantum processors with unique computational capabilities, secure channels over metropolitan distances, and unprecedented resolution in fields and force sensing. Continued progress requires the training of a new generation of scientists and engineers to develop these technologies. This National Science Foundation Research Traineeship (NRT) award to the University of California Los Angeles will accelerate these computation, communication, and sensing milestones and their interdisciplinary interfaces by training doctoral students in this nascent field of quantum science and technologies. The program will train 134 doctoral students, including 67 funded trainees, bridging relevant concepts from engineering, physics, materials, chemistry, and mathematics. The traineeship has a particularly strong emphasis on increasing the representation of women and minority students in quantum sciences and technologies through broad yet specific outreach recruitment, mentoring, and retention programs.

The Accelerating Interdisciplinary Frontiers in Quantum Sciences and Technologies (AIF-Q) program consists of four thrusts. These include: (1) atomic qubits and novel chemistry; (2) materials and algorithms towards new forms of computation; (3) optical qubits for quantum simulations; and (4) trapped ions for many-body physics. Spanning these interdisciplinary layers, the traineeship ties together core pillars of heterogeneous materials, microwave spectroscopy, and quantum algorithms. Central to the thrusts and core pillars is interdisciplinary graduate education and research training, guided by the faculty and industry-national laboratory interactions. The integrated training program consists of interdisciplinary three-faculty advising and mentoring through laboratory rotations, new course offerings in interdisciplinary quantum sciences and technologies, distinguished external advisory and internal steering councils, and formative-summative assessments. The program team will pursue seed and joint interactions together with industry and national laboratory partners. A long-term institutional commitment will be embodied in the proposed formation of a University of California Inter-Departmental Degree Program in Quantum Sciences and Technologies.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, potentially transformative, and scalable models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.