Neural predictors of outcome during relapse prevention treatment for anorexia nervosa

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Anorexia nervosa (AN) is a devastating psychiatric illness with significant morbidity and mortality rates, and relapse rates ranging from 40-80% after acute treatment. Extreme restriction of food intake is the central behavioral disturbance in illness, and confers significantly greater risk for relapse. Illness follows a heterogeneous course and clinical predictors of response to treatment are largely unknown. Maladaptive behavior in AN has behavioral and neural features suggesting habitual control. Yet, brain-based factors that relate to long-term outcomes and treatment response have not been studied. In other areas of psychiatry, both neural predictors of persistent illness and neural predictors of treatment response have been identified through patterns of neural activity and neural connectivity. By studying neural predictors of outcome in AN, this study addresses a critical gap in knowledge about the treatment of AN. This developmental study will leverage an existing clinical trial providing relapse prevention treatment for AN for individuals with AN who normalized weight as inpatients in our treatment program. The intervention, Relapse Prevention and Changing Habits (REACH+), targets habitual control of maladaptive behavior, especially restriction of food intake. REACH+ compares different versions of cognitive and behavioral psychotherapeutic interventions in a randomized design. The proposed R21 will acquire fMRI data from patients hospitalized for AN who have achieved full weight restoration, prior to starting REACH+ treatment. To identify neural predictors of outcome, we will acquire fMRI activity during a task with established utility in capturing the maladaptive restriction that predicts relapse in AN (Food Choice Task) as well as functional connectivity at rest. We will test whether these neural markers predict weight slope after hospital discharge, an established marker of longer-term outcome, to test for biomarkers of relapse. In addition, we will acquire fMRI activity during a cognitive control task with established utility in predicting response to cognitive behavior therapy (in non-AN populations). We will explore whether individual differences in cognitive control-related activity, as well as other patterns of resting state connectivity, moderate response to variations in behavioral and cognitive interventions included in REACH+. By evaluating how neural activity predicts outcome, this work is responsive to the NIMH call for the development of clinically relevant biomarkers of recovery and relapse in AN. This study will establish new avenues for research in personalized medicine in AN.