Benzi M. Kluger - US grants

7. Project Summary/Abstract: Parkinson's disease (PD) affects 1% of adults over age 65. While traditionally defined by motor symptoms, up to 75% of PD patients will eventually develop dementia making it the leading cause of nursing home placement in this population. Although there is currently no cure for PD, our ability to treat motor symptoms has advanced tremendously since the 1960's based on advances in our understanding of motor symptom neurophysiology. I propose that the treatment and prevention of dementia in PD may also prove possible through advances in our understanding of the neurophysiology of cognitive dysfunction. I will use modern network theory as a theoretical and mathematical framework for this endeavor. My long-term goal is to advance our fundamental understanding of the neurophysiology of cognitive dysfunction in PD to provide empirically testable models, clinically relevant biomarkers, and novel therapeutic targets. The central hypothesis of this proposal is that patterns of cortical functional connectivity critical to normal cognitive function are disrupted by subcortical pathology in PD and that interventions which normalize these patterns will improve cognition. This hypothesis has been formulated on the basis of preliminary data presented in this proposal and other previously published work. The research objectives of this proposal are to further our understanding of how cortical connectivity relates to cognitive dysfunction in PD, develop a novel biomarker for cognitive dysfunction in PD based on cortical physiology and to determine whether modulation of cortical connectivity may result in cognitive improvements in PD. We will accomplish the objectives of this proposal through three Specific Aims: 1) Determine whether graph theory measures of functional cortical activity measured with magnetoencephalography (MEG) are associated with cognitive dysfunction in PD subjects with and without mild cognitive impairment (MCI); 2) Develop a novel state-defining biomarker for cognitive dysfunction in PD based on MEG features through a machine learning approach; and 3) Determine the effects of repetitive transcranial magnetic stimulation (rTMS) on MEG measures of cortical connectivity and cognitive outcomes in PD-MCI patients. The approach is innovative because it represents the first study to apply graph theory measures to understanding the relationship of cortical physiology and cognitive dysfunction in PD; the first study to apply machine learning approaches to cognitive PD biomarker development; and the first clinical trial or mechanistic study of rTMS in PD-MCI. The proposed research is significant because it is expected to advance our understanding of the pathophysiology of cognitive dysfunction in PD and will provide biomarkers and pilot data essential to planning future therapeutic interventions. The training objectives and related research activities of this proposal will provide new skills, manuscripts and pilot data related to advanced MEG analysis, graph theory, biomarker development and rTMS trials necessary to establish my independence in these areas and obtain R01 funding to advance this unique research program.

DESCRIPTION (provided by applicant): Fatigue is associated with increased mortality in older adults and is the leading cause of activity restrictions in this population. Unfortunately, our understanding of the causes of fatigue in older adults is quite limited and we have no proven treatments. While it is known that aging has profound effects on the central nervous system (CNS) and cognitive function there have been no studies to date attempting to understand how CNS and cognitive factors contribute to fatigue complaints and activity restrictions in older adults. This is a striking gap as CNS and cognitive factors may play a central role in many processes suspected to drive fatigue in older adults and would thus be a potent target for therapeutic interventions. Fatigue is a complex construct which includes subjective perceptions (perceived fatigue) and objective changes in performance (fatigability). The research objectives of this proposal are to: 1) Determine the association between an objective measure of cognitive performance fatigability and activity levels in older adults; and 2) Identify potential neuronal mechanisms of this fatigability. The long-term goal is to determine whether interventions directed at cognition and/or CNS targets restore activity levels in older adults afflicted by fatige. The central hypothesis is that cognitive performance fatigability in older adults contributes to activity restrictions and is due to aging related neurocognitive changes. This hypothesis has been formulated on the basis of our preliminary data showing: 1) Significant correlations between cognitive fatigability and both age and fatigue complaints in older adults; and 2) Associations between physiologic markers of cognitive reserve and cognitive fatigability. The rationale for the proposed research is that better objective measures of cognitive and CNS factors are needed to advance our understanding of fatigability in older adults and to identify targets for therapeutic interventions. The hypothesis will be tested through two Specific Aims: 1) Determine the correlation between cognitive performance fatigability and activity levels in older adults; and 2) Determine the relationship between cognitive fatigability and neurophysiological markers of cognitive reserve using electroencephalography (EEG). The approach is innovative because it represents the first study to examine objective cognitive fatigability as a cause of restricted activity in older adults and is the first study to determine whether physiologic measures of cerebral reserve impact cognitive fatigability. The proposed research is significant because it is expected to advance out understanding of the mechanisms of fatigability in older adults and to contribute new tools, mechanistic insights and therapeutic targets essential for advancing this field. The knowledge and techniques developed in this R21 proposal will serve as a foundation for future R01 proposals to investigate the potential for cognitive interventions t improve activity restrictions in older adults and mechanistic studies to better understand the relationship and interaction of potential causes of restricted activity in older adults including cognitive, CNS, muscular, cardiovascular and metabolic factors.

DESCRIPTION (provided by applicant): Parkinson's disease (PD) affects 1% of adults over age 65. While traditionally defined by motor symptoms, up to 75% of PD patients will eventually develop dementia making it the leading cause of nursing home placement in this population. Although there is currently no cure for PD, our ability to treat motor symptoms has advanced tremendously since the 1960's based on advances in our understanding of motor symptom neurophysiology. I propose that the treatment and prevention of dementia in PD may also prove possible through advances in our understanding of the neurophysiology of cognitive dysfunction. I will use modern network theory as a theoretical and mathematical framework for this endeavor. My long-term goal is to advance our fundamental understanding of the neurophysiology of cognitive dysfunction in PD to provide empirically testable models, clinically relevant biomarkers, and novel therapeutic targets. The central hypothesis of this proposal is that patterns of cortical functional connectivity critical to normal cognitive function are disruptd by subcortical pathology in PD and that interventions which normalize these patterns will improve cognition. This hypothesis has been formulated on the basis of preliminary data presented in this proposal and other previously published work. The research objectives of this proposal are to further our understanding of how cortical connectivity relates to cognitive dysfunction in PD, develop a novel biomarker for cognitive dysfunction in PD based on cortical physiology and to determine whether modulation of cortical connectivity may result in cognitive improvements in PD. We will accomplish the objectives of this proposal through three Specific Aims: 1) Determine whether graph theory measures of functional cortical activity measured with magneto encephalography (MEG) are associated with cognitive dysfunction in PD subjects with and without mild cognitive impairment (MCI); 2) Develop a novel state-defining biomarker for cognitive dysfunction in PD based on MEG features through a machine learning approach; and 3) Determine the effects of repetitive trans cranial magnetic stimulation (rTMS) on MEG measures of cortical connectivity and cognitive outcomes in PD-MCI patients. The approach is innovative because it represents the first study to apply graph theory measures to understanding the relationship of cortical physiology and cognitive dysfunction in PD; the first study to apply machine learning approaches to cognitive PD biomarker development; and the first clinical trial or mechanistic study of rTMS in PD-MCI. The proposed research is significant because it is expected to advance our understanding of the pathophysiology of cognitive dysfunction in PD and will provide biomarkers and pilot data essential to planning future therapeutic interventions. The training objectives and related research activities of this proposal will provide new skills, manuscripts and pilot data related to advanced MEG analysis, graph theory, biomarker development and rTMS trials necessary to establish my independence in these areas and obtain R01 funding to advance this unique research program.

? DESCRIPTION (provided by applicant): Parkinson's disease (PD) affects 1% of adults over age 65. While traditionally defined by motor symptoms, up to 75% of PD patients will eventually develop PD-related dementia (PDD) making it the leading cause of nursing home placement in PD. Although there is currently no cure for PD, our ability to treat motor symptoms has advanced tremendously since the 1960's based on advances in our understanding of motor symptom neurophysiology. We propose that the treatment and prevention PDD may also prove possible by advancing our understanding of the neurophysiology underlying cognitive dysfunction. We will use modern network theory as a theoretical and mathematical framework for this endeavor. The long- term goal is to advance our understanding of the neurophysiology underlying cognitive dysfunction in PD to provide empirically testable models, clinically relevant biomarkers, and novel therapeutic targets. The central hypothesis of this proposal is that patterns of functional connectivity critical to normal cognition are disrupted by subcortical pathology in PDD. This hypothesis was formulated on the basis of our own preliminary data and other recent research. We will accomplish the objectives of this proposal through three Specific Aims: 1) Determine whether graph theory measures of network functional connectivity are associated with cognitive phenotypes in PD based on either a) the severity of cognitive dysfunction; or b) specific cognitive domains affected; 2) Develop a novel state-defining biomarker for PDD based on measures of intrinsic network functional activity using a machine learning approach; and 3) Explore the potential role of subcortical sources on cortical network activity and cognition using dynamic causal modeling (DCM). These Aims are achievable within a two-year timeframe as they will involve analyses of a single data set of resting MEG data from 25 control subjects, 25 PDD subjects, 25 PD subjects with normal cognition and 25 PD subjects with mild cognitive impairment. The feasibility of this proposal is aided by leveraging a currently funded NINDS K02 Independent Scientist Award (1 K02 NS080885-01A1). Data and biomarkers generated by this R21 Exploratory/Developmental Research Grant will provide a foundation for future studies to validate state- defining and predictive biomarkers; mechanistic studies on the role of acetylcholine and dopamine in cognition; and therapeutic studies of physiologic or pharmacologic interventions targeting physiological and regional abnormalities. The approach is innovative as the first study to apply graph theory measures to understanding the relationship of cortical physiology and cognitive dysfunction across cognitive domains and severity levels in PD; the first study to apply machine learning approaches to PDD biomarker development; and the first use of DCM to model cortical and subcortical contributions to PDD. The proposed research is significant because it will advance our understanding of the neurophysiology of PD-related cognitive dysfunction and will provide biomarkers, empiric models and therapeutic targets essential to developing more effective interventions.

Project Summary/Abstract: Parkinson's disease (PD) is the second most common neurodegenerative illness affecting approximately 1.5 million Americans and is the 14th leading cause of death in the United States. PD is traditionally described as a movement disorder with characteristic motor symptoms (e.g. tremor). However, more recent research demonstrates the impact of nonmotor symptoms such as pain, depression, and dementia on mortality, quality of life (QOL), nursing home placement and caregiver distress. Regarding models of care for PD, evidence suggests that care including a neurologist results in lower mortality and nursing home placement than care solely from a primary care physician. Unfortunately, there is also significant evidence that many of the needs most important to PD patients and their caregivers (e.g. depression, planning for the future) are poorly addressed under current models of care. Palliative care is an approach to caring for individuals with life-threatening illnesses that focuses on addressing potential causes of suffering including physical and psychiatric symptoms, psychosocial issues and spiritual needs. While developed for cancer patients, palliative care approaches have been successfully applied in other chronic progressive illnesses including heart failure and pulmonary disease. To date there have been minimal attempts to apply these principles to PD although evidence suggests that PD patients' unmet needs under current models of care may be amenable to palliative care. A small but growing cadre of centers offer outpatient palliative care for PD with early evidence of efficacy and a randomized trial of an academic-based outpatient palliative care is underway led by investigators on this proposal. While this work is critical to forwarding this field, further work is needed to provide a model that can be widely disseminated. The current proposal addresses this gap by assessing the effectiveness and feasibility of a novel community-based intervention that empowers community neurology practices to improve care for PD patients and caregivers through palliative care training, coaching and telemedicine resources. We hypothesize that this intervention will improve patient QOL and caregiver burden and will prove feasible and acceptable to community providers. Our Specific Aims are to: 1) Determine the a) effectiveness and b) feasibility of a novel community-based outpatient palliative care intervention for PD.; 2) Describe the effects of a this intervention on patient and caregiver costs and service utilization; and 3) Identify opportunities to optimize community-based palliative care for this population by: a) describing patient and caregiver characteristics associated with intervention benefits; and b) through direct patient, caregiver and provider interviews. Innovations of our approach include a novel model of providing disease-specific community-based palliative care not dependent on limited palliative specialist resources, a stepped-wedge trial design and use of telemedicine resources to provide multidisciplinary care. The research is significant because it will create a foundation for future community-based dissemination studies in PD and the broader field of palliative care.

Project Summary/Abstract: Neurodegenerative illnesses such as Parkinson?s (PD), Lewy Body Dementia (LBD) and Alzheimer?s disease (AD) affect nearly 15% of adults over age 65 and are leading causes of death in the US. While these illnesses are traditionally defined by their neurologic symptoms, more recent research describes the high impact of other medical symptoms on patients and the immense psychosocial consequences of these illnesses on both patients and families. Unfortunately, multiple lines of evidence demonstrate that many of the needs most important to patients and caregivers (e.g. pain management, advance care planning, end-of-life care) are poorly addressed under current care models. Palliative care is an approach to caring for individuals with life-limiting illness that addresses potential causes of suffering including physical symptoms, psychosocial issues and spiritual needs. To date there have been limited attempts to apply these principles to neurodegenerative illnesses despite evidence that patients? and caregivers? unmet needs may be amenable to this approach. Notably, the candidate has played a central role among a growing cadre of academic centers that now offer palliative care services for neurodegenerative illnesses and presents results from a randomized trial of academic-based outpatient palliative care that convincingly demonstrate this approach improves patient and caregiver outcomes over current standards of care. While efficacy trials are critical to forwarding this field, barriers to their dissemination include a limited workforce of palliative care specialists, lack of palliative education amongst neurologists, lack of team-based resources in community settings, and patient mobility/transportation issues. The long-term goal of the candidate is to improve outcomes and raise standards of care for older adults affected by neurodegenerative illnesses through novel, efficient and effective models of delivering palliative care. The Research Aims of this award will be met through: Study 1: Determine the effectiveness and feasibility of individual palliative care training for community neurologists and team-based virtual house calls for PD/LBD patients and caregivers (funded R01); Study 2: Develop a community-based model of palliative care for AD patients and caregivers (funded NIA AD Administrative Supplement; R01 trial to stem from results); Study 3: Determine the effectiveness and feasibility of a novel online community model to support community-based palliative care for PD/LBD (R01 Under Review); and Study 4: Integrate geriatric principles and care into our neuropalliative care model to improve outcomes for patients and caregivers affected by neurodegenerative illness (future P01 grant). As this is an emerging research direction for the candidate, the Career Development Objectives will provide formal training in academic leadership, geriatric palliative care, implementation science, caregiver support, telehealth and healthcare policy. This proposal is significant because it will create a foundation for palliative care dissemination efforts relevant to neurodegenerative illness and the broader field of geriatric palliative care.

Project Summary/Abstract: Parkinson's disease (PD), Lewy Body Dementia (LBD) and related disorders are the second most common neurodegenerative illness affecting over 1.5 million Americans and are the 14th leading cause of death in the United States. Notably, while PD is traditionally described by motor symptoms (e.g. tremor), more recent research demonstrates that nonmotor symptoms such as pain, depression, and dementia are leading causes of mortality, quality of life (QOL), nursing home placement and caregiver distress. Regarding models of care for PD and LBD, evidence suggests that care including a neurologist results in lower mortality and nursing home placement than care solely from a primary care physician. Unfortunately, there is also significant evidence that many of the needs most important to patients and family (e.g. pain, planning for the future) are poorly addressed under current care models. Palliative care is an approach to caring for individuals with serious illness that addresses multiple causes of suffering including medical symptoms, psychosocial issues and spiritual needs. While developed for cancer patients, palliative care approaches have been successfully applied in other chronic progressive illnesses. There is expanding interest in applying these principles to PD and LBD. A small but growing cadre of centers now offer outpatient palliative care for PD and LBD with mounting evidence of efficacy including a randomized trial of academic-based outpatient palliative care led by the PI. While this work is critical to forwarding this field, further work is needed to provide models that can be widely disseminated in the community where the majority of patients receive their care. The current proposal addresses this gap and builds on lessons learned our original R01 grant by assessing the effectiveness and feasibility of a novel community-based intervention that builds online learning communities around palliative care for community neurology practices and augments care for patients and family around social support communities. We hypothesize this intervention will improve patient QOL, caregiver burden and community provider career satisfaction. Our Specific Aims are to: 1) Determine the a) effectiveness and b) feasibility of a novel community- based outpatient palliative care model for PD and LBD; 2) Describe the effects of this model on patient and caregiver costs and healthcare utilization; and 3) Identify opportunities to optimize this model by: a) describing patient and caregiver characteristics associated with intervention benefits; and b) through direct patient, caregiver and provider interviews. Innovations of our approach include the use of online learning communities to implement primary palliative care with neurologists and the use of online networks to provide team-based support and peer connections to patients and families. The research is significant because it tests a potentially more efficient and effective model of providing palliative care to persons affected by PD and LBD, and, in conjunction with other work conducted by our group, will provide data relevant to patients, healthcare providers, policy makers and other stakeholders to guide future dissemination efforts in this field.