Leanne Williams - US grants

DESCRIPTION (provided by applicant): The immediate goal of this project is to use functional imaging to define dimensional constructs for reactivity and regulation of potential threat, within the Negative Valence system of the Research Domain Criteria (RDoC). By using these constructs we ground the understanding of anxiety in neural mechanisms, rather than using pre-set diagnostic boundaries, which have inherent assumptions about the structure of anxiety symptoms. In our community, the experience of anxiety is prevalent, and costs $47 billion per year in care and lost time. A wide range of anxiety disorders share common symptoms of anxious arousal, and show hyper- reactivity of the amygdala in functional imaging studies, which we call excessive Threat reactivity. Some of these disorders also involve a more generalized loss of adaption accompanied by more cognitive experiences of anxiety, such as apprehensive expectations. They show hypo-activation of the ventral-rostral anterior cingulate, which we call poor Threat regulation. Given the commonalities in anxiety phenomena and imaging findings, our goal is to determine whether imaging-defined dimensions of Threat reactivity and regulation provide a primary organizing principle for distinguishing specific features of anxiety and mood symptoms, the behaviors they generate, and their impact on the real world capacity to function socially and at work. To do this we will recruit all people who come through a large community psychology clinic which attends to a broad spectrum of anxiety and mood-related symptoms. These participants will be unmedicated and studied using a coordinated battery of functional imaging, behavioral, self-report and genetic probes, with well established paradigms for threat reactivity and regulation. The immediate aim is to determine if imaging-defined dimensions of amygdala threat reactivity and anterior cingulate threat regulation relate to severity of anxiety symptoms, specifically anxious arousal and apprehensive expectations. A second aim is to determine how these dimensions also relate in a cohesive way to behavioral performance in emotional and cognitive domains since, for instance, disruptions to threat processing can temporarily impair cognitive control. The third aim of the study is to assess how the imaging-defined dimensions affect real world functions related to burden of illness, specifically social functioning, quality of life and work productivity. This will create a personalized medicine approach for the treatment of anxiety disorders that will lead to specific treatments most likely t result in remission of symptoms. Outcomes will result in conceptually valid constructs for understanding what neural mechanisms generate specific experiences of anxiety.

? DESCRIPTION (provided by applicant): Background: Obesity affects 36% of US women and men and increases lifetime risk for diabetes and cardiovascular disease. Similarly, depression affects 20% of US women and 13% of men and is the leading cause of disability worldwide. Further, the 2 disorders have a bidirectional positive relationship. Proven behavioral interventions to treat obesity and depression exist; however, the underlying biological mechanisms remain unknown. This lack of understanding significantly hampers efforts to optimize the effectiveness of behavioral interventions and limits their dissemination and implementation into widespread practice to curtail the adverse consequences of obesity and depression and promote population health. Rapid advances in human neuroscience and behavioral science and integration of the two could provide unique opportunity to fill this gap. Objective: Leveraging a recently funded 2-year randomized controlled trial (RAINBOW target n=404; PI Dr. Jun Ma) of a first-ever integrated treatment for comorbid obesity and depression in primary care that uniquely combines 2 nationally recognized behavioral interventions, we propose a 2-phased project to identify, validate and refine a set of assays to measure self-regulation targets; and to engage these targets to optimize behavioral treatment of obesity and depression. Specific Aims: In the UH2 phase, we will (1) Conduct secondary data analysis and hold workshops and a symposium to finalize selection of self-regulation targets and assays for testing; (2) Leverage the RAINBOW intervention to engage identified targets; and (3) Verify target engagement across multiple domains (neural, physiological, behavioral, psychological), settings (laboratory, virtual, and naturalistic), and time points (0, 4 weeks, 6, 12 and 24 months) Transitional milestones are to (1) Establish assay(s) that reliably and accurately measure the identified targets; (2) Demonstrate malleability of the self-regulation target(s) in response to th RAINBOW integrated treatment; and (3) Identify self-regulation profile(s) that predict treatment response in health behaviors (medical regimen adherence, physical activity, diet) and outcomes (weight, depression). In the UH3 phase, we will conduct a pilot randomized controlled trial in which an additional 100 obese and depressed adults will be randomized to intervention or wait-list control and assessed at baseline, 4 weeks and 6 months. Intervention subjects will receive the first 4 weeks of the RAINBOW intervention, followed by target-guided tailoring of the intervention components in order to optimize target engagement and enhance behavioral change based on their individual self-regulation profile during the first 4 weeks. We will use the insights from intervention subjects to then further refine the tailoring strategies for the waitlis subjects. Implications: This research will provide a toolkit of well-validated assays of self-regulation targets important for health behavior change, as well as target- guided personalization of intervention strategies, in the treatment of comorbid obesity and depression. Impact: Given the widespread relevance of these disorders and the targeted health behaviors, this research will be a prototype for treating multiple chronic conditions with profound potential impacts on population health.

PROJECT SUMMARY/ABSTRACT Our objective is to use HCP protocols to acquire and make public a large dataset of imaging, behavioral, and symptom data from patients with disordered emotional states. We will also develop and make public new methods for examining how connectome disorganization gives rise to these disordered states at the level of the individual patient. Psychopathology arising from enhanced negative emotion or from the loss of positive emotional experience affects over 400 million people globally. Such states of disordered emotion cut across multiple diagnostic categories and are compounded by accompanying disruptions in cognitive function. Not surprisingly, therefore, these forms of psychopathology are a leading cause of disability. To address these issues our investigative strategy is informed by the Research Domain Criteria (RDoC) initiative spearheaded by NIMH. We focus on three RDoC domains and constructs: 1) acute threat within the Negative Valence System (NVS) domain, a construct relevant to automatic reactions to fear and physical symptoms of anxiety; 2) reward valuation and responsiveness within the Positive Valence System (PVS) domain, a construct involving incentive salience, hedonic responses and symptoms of anhedonia; and 3) working memory within the Cognitive System (CS) domain, a construct that implicates top-down regulation of cognitive rumination and worry. Our approach is grounded in strict adherence to HPC protocols and a strong commitment to data sharing. We unite complementary expertise, including (1) state-of-the-art MRI technology and data management systems; (2) a field-leading Center for Reproducible Neuroscience; (3) a track record in leading large-scale neuroradiology consortia; (4) leaders in RDoC-informed approaches to large-scale imaging in depression and anxiety; and (5) pioneering statistical approaches for high-dimensional data. Our aims are to (1) use the HCP protocols to acquire multi-modal data for 300 people aged 22-25 years of age who are experiencing varying degrees of acute threat, loss of reward valuation/responsiveness, and difficulties in working memory, (2) elucidate the nature of the relations among connectomes, symptoms, and behavior based on networks related to the RDoC constructs of interest, and (3) to develop data-driven, machine-learning methods to discover how connectomes for these constructs combine together to form naturally organized clusters of people. Our data will advance a neurobiological model that maps network dysfunctions to specific behaviors and symptoms. This model will provide a foundation for ultimately guiding more classifications and treatment choices according to types of neural dysfunction rather than relying on diagnostic categories that are agnostic to neurobiology.

SUMMARY MDMA (?ecstasy?) and ketamine are drugs of abuse that have steadily gained in popularity. Compared to more traditional stimulants or narcotics, however, less is known about their mode of action, their subjective effects, and how these effects promote continued use. Our objective is to develop a theoretically-informed characterization of the effects of MDMA, methamphetamine and ketamine on the neurobehavior of specific circuits for processing risk and reward, the connectivity of these circuits, and how these circuits and their connectivity predict acute drug experience and drug use outcomes. We will first pursue optogenetic techniques for neural control to map the effects of MDMA, methamphetamine and ketamine on neurobehavior related to risk and reward in rodents. Second, we will use neuroimaging to map both the acute and cumulative influence of these drugs on neurobehavioral targets in humans, focusing on risk and reward circuits and accompanying behaviors. We will also assess the extent to which these influences of drug exposure on neurobehavioral targets predict future use patterns over a follow up period of 6 months. Third, we will extend our approach to characterizing the acute and cumulative effects of MDMA, methamphetamine and ketamine on whole brain connectivity and associated behaviors such as degree of control. Under this third objective we will assess the prediction of future use patterns over the same follow up period. The results will advance our scientific understanding about why people are motivated to use these drugs, and provide a foundation for future investigations of tailored intervention strategies.

! PROJECT SUMMARY/ABSTRACT Despite the wide scale adoption of repetitive transcranial magnetic stimulation (rTMS, hereafter simply TMS), we still lack mechanistically-driven biomarkers designed to identify who is most likely to respond, and why. rTMS is indicated for pharmacoresistant depression. It is imperative that we find more precise solutions for these patients given that pharmacoresistant depression can be life threatening: suicide attempts are twice the rate of non-resistant depression. Our objective is to use a prospective design to evaluate cognitive control network connectivity as a predictive biomarker of the clinical effect of repetitive transcranial magnetic stimulation, and as a response biomarker of change with TMS. We have a novel opportunity to address this objective through a systematic evaluation of brain network biomarkers in 100 patients taking part in a Veterans Administration multi- site clinical TMS program. By utilizing the umbrella Clinical rTMS Program, we can standardize delivered parameters to ensure uniformity. Our primary biomarker is functional connectivity of the cognitive control network of the human brain that is central to the regulation of thought and emotion. We will also assess corresponding behavioral performance. Clinical outcomes are symptom severity, suicidality, and quality of life. Biomarkers will be assessed at baseline, after 5 sessions of rTMS (?low dose?) to explore mechanisms of early response, and upon completion of treatment after 30 sessions (?higher dose?). To power the study for an anticipated conservative effect size of at least .25, we will recruit 100 patients participating in the VA Clinical TMS Program. Using standardized stimulation parameters and harmonized neuroimaging procedures, our aims are to 1) probe the putative mechanistic effect of rTMS on promoting cognitive control and to assess whether connectivity of the cognitive control network changes in a dose-dependent manner, 2) to assess whether extent of change in cognitive control network connectivity predicts corresponding change in behavioral performance and, 3) to identify if baseline functional connectivity and behavior, along with early change in connectivity and behavior, predict subsequent outcomes in symptom severity, suicidal ideation, and quality of life. Innovations of our design include 1) adequate power to interrogate imaging markers, 2) standardization to minimize variability, 3) implementation of a longitudinal design to quantify rTMS-related changes in imaging markers, 4) integration of task-evoked and resting state imaging markers and, and 5) establishing the foundations for expanding lessons learned to additional diagnoses and parameters. !