Despite increasing knowledge on the neuroimaging patterns of eating disorder (ED) symptoms in non-clinical populations, studies using whole-brain machine learning to identify connectome-based neuromarkers of ED symptomatology are absent. This study examined the association of connectivity within and between large-scale functional networks with specific symptomatic behaviors and cognitions using connectome-based predictive modeling (CPM).

CPM with ten-fold cross-validation was carried out to probe functional networks that were predictive of ED-associated symptomatology, including body image concerns, binge eating, and compensatory behaviors, within the discovery sample of 660 participants. The predictive ability of the identified networks was validated using an independent sample of 821 participants.

The connectivity predictive of body image concerns was identified within and between networks implicated in cognitive control (frontoparietal and medial frontal), reward sensitivity (subcortical), and visual perception (visual). Crucially, the set of connections in the positive network related to body image concerns identified in one sample was generalized to predict body image concerns in an independent sample, suggesting the replicability of this effect.

These findings point to the feasibility of using the functional connectome to predict ED symptomatology in the general population and provide the first evidence that functional interplay among distributed networks predicts body shape/weight concerns.

The current study tests the relationship between eating disorder (ED) symptoms and trauma exposure. The mechanisms via which trauma is related to ED symptoms have not been sufficiently examined. This study examines the complex role of dissociation and emotional dysregulation in the context of trauma, BMI, ED symptoms and body dissatisfaction (BD).

We hypothesized that dissociation and emotional dysregulation would mediate the relationship between trauma exposure and ED symptoms / BD. We further hypothesized that BMI would play a moderating role in this association.

A community sample of 229 (16.2% male) participants, with a mean age of 29.08±10.68 reported online on traumatic events (Life Events Checklist), dissociation (Dissociative Experiences Scale – II), emotional dysregulation (Difficulties in Emotional Regulation Scale), ED symptoms (Eating Disorders Examination – Questionnaire) and BD (Figure Rating Scale).

Participants reported experiencing a mean of 2.87±2.27 traumatic events, with a relatively high percentage (˜86%) reporting at least one. The most commonly reported traumatic events were transportation accidents and physical assault. Although frequency of traumatic events did not directly predict ED symptoms, BMI, dissociation, emotional dysregulation and BD did. An SEM model showed that traumatic events predicted ED symptoms indirectly through dissociation, emotional dysregulation and BMI. Dissociation and emotional dysregulation predicted ED symptoms directly. BMI also moderated the association between traumatic events and both ED symptoms and BD.

Therapists treating patients with high BMI or obesity should be aware of these relationships and investigate the possibility that trauma and/or PTSD may underlie the presenting disordered eating or eating disorder.

No significant relationships.

In the past decade, network analysis (NA) has been applied to psychopathology to quantify complex symptom relationships. This statistical technique has demonstrated much promise, as it provides researchers the ability to identify relationships across many symptoms in one model and can identify central symptoms that may predict important clinical outcomes. However, network models are highly influenced by node selection, which could limit the generalizability of findings. The current study (N = 6850) tests a comprehensive, cognitive–behavioral model of eating-disorder symptoms using items from two, widely used measures (Eating Disorder Examination Questionnaire and Eating Pathology Symptoms Inventory).

We used NA to identify central symptoms and compared networks across the duration of illness (DOI), as chronicity is one of the only known predictors of poor outcome in eating disorders (EDs).

Our results suggest that eating when not hungry and feeling fat were the most central symptoms across groups. There were no significant differences in network structure across DOI, meaning the connections between symptoms remained relatively consistent. However, differences emerged in central symptoms, such that cognitive symptoms related to overvaluation of weight/shape were central in individuals with shorter DOI, and behavioral central symptoms emerged more in medium and long DOI.

Our results have important implications for the treatment of individuals with enduring EDs, as they may have a different core, maintaining symptoms. Additionally, our findings highlight the importance of using comprehensive, theoretically- or empirically-derived models for NA.