Multivariate patterns linking brain microstructure to behavior in adolescent eating disorders
Poster No:
466
Submission Type:
Abstract Submission
Authors:
Carolina Makowski1, Golia Shafiei2, Megan Martinho1, Donald Hagler Jr1, Diliana Pecheva3, Anders Dale1, Christine Fennema-Notestine1, Amanda Bischoff-Grethe1, Christina Wierenga1
Institutions:
1University of California San Diego, San Diego, CA, 2University of Pennsylvania, Philadelphia, PA, 3University of California, San Diego, San Diego, CA
First Author:
Co-Author(s):
Introduction:
Eating disorders (EDs) are multifaceted psychiatric disorders characterized by dysregulated eating patterns and body image distortion, and often, are followed by a chronic, costly, and disabling illness course1,2. Uncovering brain-based biomarkers of EDs with neuroimaging is an important pursuit to improve treatment and prognosis for patients, but has been hampered by case-control study designs and inclusion of a limited set of regions of interest and/or symptoms3-5. There is a need for neuroimaging-related research in EDs to incorporate a wider array of behaviors, traits, and cognitive profiles to more accurately parse symptom heterogeneity and severity. The current study harnesses multivariate methods to map microstructural and morphometric patterns across the entire brain to multiple domains of behavior and symptomatology in adolescent patients with EDs.
Methods:
The current study included 91 adolescent female patients with an ED and 48 healthy controls (mean age = 16.1 years, range = 13.1-18.2). Diffusion-weighted images were acquired on a 3.0T GE MR750 scanner and were modeled with restriction spectrum imaging6, a higher-order diffusion model that allows for better resolution of crossing fibers and tissue microstructure beyond white matter. Specifically, we investigated models of restricted normalized directional (RND), or anisotropic, diffusion, describing directed diffusion of water molecules within intracellular spaces confined by cell membranes. We included 37 behavioral measures encompassing cognition, emotion regulation, temperament, interoception and ED symptoms. Partial least squares analysis7,8 was applied to map behavioral measures to restricted diffusion in white matter tracts and subcortical structures across 65 regions of interest. Finally, we tested the clinical utility of these derived scores, and investigated whether individual-level scores mapped onto clinically-derived diagnostic subtypes (e.g., binge-purge vs restrictive subtypes of EDs) or could be predictive of future clinical symptoms in a subset of 72 patients with one-year follow-up data.
Results:
The first significant latent variable (LV-1) explained 46.9% of the covariance between microstructure and behavior (Figure 1). LV-1 retained a significant brain-behavior correlation in held-out data (permuted p=0.04), where lower scores on abstract reasoning, effortful control, and interoceptive awareness and higher emotional dysregulation and novelty seeking, were linked to increased restricted diffusion across white matter tracts, particularly those joining frontal, limbic, and thalamic regions. Individually-derived brain and behavior scores for LV-1 were higher in patients with binge-purge symptoms, compared to those with only restrictive eating symptoms (brain: t(89)=-3.66, p=4.26e-4; behavior: t(89)=-2.32, p=0.022), but did not predict ED symptom severity one year later ( r=0.10, p=0.41).
Conclusions:
Altogether, our findings uncovered a neuroimaging-informed behavioral pattern which parallels that of an 'undercontrolled' or dysregulated personality profile that has been described previously in temperament-based clustering of ED patients9,10. Our results emphasize the value of applying multivariate methods to more accurately and reproducibly model the array of brain-behavior relationships inherent to the heterogeneous clinical presentation of eating disorders. These behavioral and brain-based patterns may also be important in differentiating between clinical subgroups of patients and in future prediction-based frameworks of clinical outcomes in eating disorders.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Lifespan Development:
Early life, Adolescence, Aging
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Multivariate Approaches 2
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
Cognition
Eating Disorders
Multivariate
Psychiatric Disorders
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Restriction spectrum imaging
1|2Indicates the priority used for review
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4. Noble, S. (2024). The tip of the iceberg: a call to embrace anti-localizationism in human neuroscience research. Imaging Neuroscience. 2:1-10.
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8. McIntosh, A. R. (2013). Multivariate statistical analyses for neuroimaging data. Annual Review of Psychology, 64(1), 499–525.
9. Isaksson, M. (2021). Overcontrolled, undercontrolled, and resilient personality styles among patients with eating disorders. Journal of Eating Disorders, 9(1), 47.
10. Turner, B. J. (2014). Personality profiles in Eating Disorders: further evidence of the clinical utility of examining subtypes based on temperament. Psychiatry Research, 219(1), 157–165.