Cross-diagnostic Prediction of Dimensional Psychiatric Phenotypes in Anorexia Nervosa and Body Dysmorphic Disorder Using Multimodal Neuroimaging and Psychometric Data

  • Jamie D. FeusnerEmail author
  • Wesley T. Kerr
  • Teena D. Moody
  • Aifeng F. Zhang
  • Mark S. Cohen
  • Alex D. Leow
  • Michael A. Strober
  • Don A. Vaughn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11044)


Anorexia nervosa (AN) and body dysmorphic disorder (BDD) share several phenomenological features including distorted perception of appearance, obsessions/compulsions, and limited insight. They also show partially overlapping patterns of brain activation, white matter connectivity, and electrophysiological responses. These markers have also shown associations with symptom severity within each disorder. We aimed to determine: (a) if, cross-diagnostically, neural activity and connectivity predict dimensional clinical phenotypes, and (b) the relative contribution of multimodal markers to these predictions beyond demographics and psychometrics, in a multivariate context. We used functional magnetic resonance imaging (fMRI) data from a visual task, graph theory metrics of white matter connectivity from diffusor tensor imaging, anxiety and depression psychometric scores, and demographics to predict dimensional phenotypes of insight and obsession/compulsions across a sample of unmedicated adults with BDD (n = 29) and weight-restored AN (n = 24). The multivariate model that included fMRI and white matter connectivity data performed significantly better in predicting both insight and obsessions/compulsions than a model only including demographics and psychometrics. These results demonstrate the utility of neurobiologically-based markers to predict important clinical phenotypes. The findings also contribute to understanding potential cross-diagnostic substrates for these phenotypes in these related but nosologically discrete disorders.


fMRI DTI Insight Obsessions Compulsions Multivariate 


Funding and Disclosure

This work was supported by NIMH grants (R01MH093535 and R01MH105662) to JDF, a Postdoctoral Fellowship to DAV from the UCLA Collaboratory directed by Matteo Pellegrini. The authors declare no conflict of interest in this publication.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Jamie D. Feusner
    • 1
    • 2
    Email author
  • Wesley T. Kerr
    • 1
    • 2
    • 3
  • Teena D. Moody
    • 1
    • 2
  • Aifeng F. Zhang
    • 4
  • Mark S. Cohen
    • 1
    • 2
  • Alex D. Leow
    • 4
    • 5
  • Michael A. Strober
    • 1
    • 2
  • Don A. Vaughn
    • 1
    • 6
  1. 1.Semel Institute for Neuroscience and Human BehaviorUniversity of CaliforniaLos AngelesUSA
  2. 2.David Geffen School of MedicineUniversity of CaliforniaLos AngelesUSA
  3. 3.Department of Internal MedicineEisenhower HealthRancho MirageUSA
  4. 4.Department of PsychiatryUniversity of IllinoisChicagoUSA
  5. 5.Department of BioengineeringUniversity of IllinoisChicagoUSA
  6. 6.Department of PsychologySanta Clara UniversitySanta ClaraUSA

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