Cheri A. Levinson - US grants

Project Summary/ Abstract Social anxiety disorder (SAD) and eating disorders (EDs) are common and debilitating disorders that are highly comorbid[7-14]. Conceptualizations of comorbidity suggest that there may be underlying genetic and environmental vulnerabilities that create risk for multiple disorders[1-4]. Research on the shared vulnerabilities of SAD and EDs suggest that fear of negative evaluation may be a common underlying risk factor[29-31]. However, relatively little is known about the development of fear of negative evaluation into SAD and EDs and the underlying genetic vulnerabilities common to both disorders. Thus, the aims of this proposal are to examine the shared environmental and genetic vulnerabilities of these disorders and to develop a new model in which fear of negative evaluation and fear of negative evaluation of one[unreadable]s appearance, or social appearance anxiety, contribute to both SAD and EDs. The current project proposes three studies to address these aims. In Study 1 we will test for shared genetic risk between SAD and EDs using an archival data set of twin pairs. In Study 2 the contribution of fear of negative evaluation and social appearance anxiety on social anxiety and disordered eating will be tested longitudinally over six months using measures of social anxiety and disordered eating with strong psychometric properties. In Study 3 fear of negative evaluation and social appearance anxiety will be experimentally primed using a modified speech task. Eating behaviors, state social anxiety, and galvanic skin response will be measured as dependent outcomes. This experiment will test whether an environmental trigger of fear of negative evaluation and social appearance anxiety cause eating and social anxiety outcomes. The integration of these studies will provide the skills for future research that tests a model of vulnerability spanning from genes to self-report of traits and behavior. Results from these studies and from future potential research may lead to the creation of treatments that address genetic and environmental vulnerabilities of both SAD and EDs in the same treatment protocol.

PROJECT SUMMARY/ABSTRACT Eating disorders (EDs) are severe mental illnesses with the highest mortality rate of any psychiatric disorder. The most widely used empirically supported treatment for EDs (cognitive behavior therapy) is only efficacious for ~50% of individuals. This low response rate is due to the fact that EDs are heterogeneous conditions with diverse symptom trajectories that are not adequately addressed in current ?one-size-fits-all? psychotherapies. Until we can identify what maintains or exacerbates individual symptoms, clinicians will continue to have difficulty accurately predicting prognosis and will have no empirical guidance to develop targeted treatment plans to promote recovery. Our scientific premise, developed from our past work, is that the application of network theory will enable the identification of cognitive-behavioral symptom networks that maintain and ?trigger? EDs both between and within individuals. Our study goals are to (1) identify individual ED ?trigger? symptoms (cognitions, behaviors, affect, and physiology) and (2) correlate trigger symptoms with real-time physiological data to create an algorithm predicting onset of ED behaviors. These goals will ultimately identify symptoms that prevent full remission and lead to relapse. We will use a multiple units of analysis approach combined with novel, cutting-edge advances in network science. We will collect intensive real- time data on cognitions, behavior, affect, and physiology using mobile and sensor-technology from 120 individuals with a diagnosis of anorexia nervosa (AN), atypical AN, and bulimia nervosa across 30 days. At 1-month and 6-month follow ups we will assess ED outcomes (e.g., remission status, ED behaviors) to test if ?trigger? symptoms predict ED outcomes. Network science and state-of-the-art machine learning techniques will allow us, for the first time, to discover whether certain trigger symptoms predict worse outcomes. Specific aims are to (1) develop personalized networks to identify which cognitive, behavioral, affective, and physiological symptoms maintain EDs and predict ED outcomes and (2) utilize sensor data to identify physiological patterns both within and across people that correlate with core maintaining symptoms and that predict ED behaviors. The proposed research uses highly innovative methods, combining intensive longitudinal data collection methods, all remote procedures, novel advances in network science and sensor-technology, and state-of-the-art machine learning techniques to answer previously unresolvable questions pinpointing which personalized symptoms trigger EDs. The proposed research has clinical impact. If we identify patterns that contribute to symptom network variation within individuals, these data will provide a model of personalized medicine for the entire field of psychiatry, as well as providing novel intervention targets to prevent and treat EDs.

PROJECT SUMMARY/ABSTRACT Eating disorders (EDs) are chronic and disabling; most individuals never achieve full remission, even after intensive treatment, and 50% of those who access intensive treatment will relapse within 6-months of discharge. These high relapse rates occur often and contribute to the poor outcomes seen in EDs. Importantly, existing treatments to not differ from control treatments in the ability to alter cognitive ED pathology, which is the primary remaining symptomatology at discharge from intensive care. ED relapse-prevention treatments are urgently needed that can disrupt the persistent cycle of admission and discharge from intensive treatment and that are explicitly targeted at core cognitive-affective pathology. Our scientific premise, developed from our past work, is that the application of an online exposure protocol will engage fear extinction - improving outcomes, enhancing full recovery, and decreasing the likelihood of relapse. Our study goals are to (1) develop and test the acceptability, feasibility, and preliminary efficacy of a randomization of an online exposure relapse-prevention protocol that can be delivered post- acute treatment versus a writing control treatment and (2) to test if this treatment targets fear extinction, which is a core aspect of ED cognitive-affective pathology. These goals will ultimately lead to a highly deployable and accessible online treatment targeted at core ED mechanisms. The proposed research uses highly innovative methods; we will use an all remote technology- based approach, combining an online treatment with mobile technology that assesses the target of fear extinction. The combination of an online treatment with mobile assessment allows, for the first time, the creation of an engaged and targeted treatment, which can rapidly be disseminated during a critical period of care. Specific aims are to (1) collect preliminary data on the feasibility and acceptability of the randomization of two treatment conditions after discharge from intensive ED treatment: a relapse-prevention online exposure protocol (n=65; ROEP) and a control treatment writing condition (n=65) (2) To test for differences between ROEP and control treatment for the prevention of relapse and preliminary change on clinical ED outcomes (3) To examine if ROEP targets fear extinction and if fear extinction is associated with relapse and ED outcomes, and (3b) To test if baseline differences in fear conditioning relate to change in ED outcomes across treatment. The proposed research has clinical impact. Ultimately, this proposal will lead directly to the creation and dissemination of a highly user-friendly, easily accessible and deployable intervention that can prevent relapse in the EDs, which will decrease mortality, morbidity, and the high costs associated with chronic treatment.

PROJECT SUMMARY/ABSTRACT Eating disorders (EDs) are severe mental illnesses with the highest mortality rate of any psychiatric disorder, in part due to the high rates of suicide found within the EDs. Despite the documented relations between suicidal ideation (i.e., thinking about, planning, or considering suicide)7 and behaviors (i.e., potentially injurious behavior with an intent to die)7 and EDs, there has been little research examining how suicidality relates to ED symptoms. Further, there have been no examinations, to date, of how SIB impact the process of ED remission. New statistical approaches that incorporate state-based measurement of momentary symptoms are necessary in understanding the dynamic relations between suicidality and ED symptoms across time. Further, we need a way to develop personalized models of such dynamic relations to capture the individual differences and high levels of heterogeneity found across the EDs. The specific aims are of the proposed project are: (1) examine whether suicidality moderate networks of ED symptoms (i.e., the way in which ED symptoms interrelate), (2) use personalized networks to examine how central symptoms vary at the individual level for ED participants high in suicidality, and (3) determine whether central symptoms of those with elevated eating disorders and suicidality are predictive of ED outcomes and remission. This project will be an important initial step towards better understanding the relations between eating disorders, suicidality, and outcomes in eating disorders. Importantly, the career development and mentorship plan outlined in this diversity supplement application will promote Ms. Hunt's success as a minority researcher and contribute to the initiative of building a scientific workforce.