Brain connectome modularity in weight-restored anorexia nervosa and body dysmorphic disorder

Cytoarchitectonically Defined Volumes of Early Extrastriate Visual Cortex in Unmedicated Adults With Body Dysmorphic Disorder

BACKGROUND

Individuals with body dysmorphic disorder (BDD) misperceive that they have prominent defects in their appearance, resulting in preoccupations, time-consuming rituals, and distress. Previous neuroimaging studies have found abnormal activation patterns in the extrastriate visual cortex, which may underlie experiences of distorted perception of appearance. Correspondingly, we investigated gray matter volumes in individuals with BDD in the early extrastriate visual cortex using cytoarchitectonically defined maps that were previously derived from postmortem brains.

METHODS

We analyzed T1-weighted magnetic resonance imaging data from 133 unmedicated male and female participants (BDD: n = 65; healthy control subjects: n = 68). We used cytoarchitectonically defined probability maps for the early extrastriate cortex, consisting of areas corresponding to V2, V3d, V3v/VP, V3a, and V4v. Gray matter volumes were compared between groups, supplemented by testing associations with clinical symptoms.

RESULTS

The BDD group exhibited significantly larger gray matter volumes in the left and right early extrastriate cortex. Region-specific follow-up analyses revealed multiple subregions showing larger volumes in BDD, significant in the left V4v. There were no significant associations after corrections for multiple comparisons between gray matter volumes in early extrastriate cortex and BDD symptoms, comorbid symptoms, or duration of illness.

CONCLUSIONS

Greater volumes of the early extrastriate visual cortex were evident in those with BDD, which aligns with outcomes of prior studies revealing BDD-specific functional abnormalities in these regions. Enlarged volumes of the extrastriate cortex in BDD might manifest during neurodevelopment, which could predispose individuals to aberrant visual perception and contribute to the core phenotype of distortion of perception for appearance.

Neural representations of anxiety in adolescents with anorexia nervosa: a multivariate approach

Anorexia nervosa (AN) is characterized by low body weight, fear of gaining weight, and distorted body image. Anxiety may play a role in the formation and course of the illness, especially related to situations involving food, eating, weight, and body image. To understand distributed patterns and consistency of neural responses related to anxiety, we enrolled 25 female adolescents with AN and 22 non-clinical female adolescents with mild anxiety who underwent two fMRI sessions in which they saw personalized anxiety-provoking word stimuli and neutral words. Consistency in brain response patterns across trials was determined using a multivariate representational similarity analysis (RSA) approach within anxiety circuits and in a whole-brain voxel-wise searchlight analysis. In the AN group there was higher representational similarity for anxiety-provoking compared with neutral stimuli predominantly in prefrontal regions including the frontal pole, medial prefrontal cortex, dorsolateral prefrontal cortex, and medial orbitofrontal cortex, although no significant group differences. Severity of anxiety correlated with consistency of brain responses within anxiety circuits and in cortical and subcortical regions including the frontal pole, middle frontal gyrus, orbitofrontal cortex, thalamus, lateral occipital cortex, middle temporal gyrus, and cerebellum. Higher consistency of activation in those with more severe anxiety symptoms suggests the possibility of a greater degree of conditioned brain responses evoked by personally-relevant emotional stimuli. Anxiety elicited by disorder-related stimuli may activate stereotyped, previously-learned neural responses within- and outside of classical anxiety circuits. Results have implications for understanding consistent and automatic responding to environmental stimuli that may play a role in maintenance of AN.

Large-Scale Exploration of Whole-Brain Structural Connectivity in Anorexia Nervosa: Alterations in the Connectivity of Frontal and Subcortical Networks

BACKGROUND

Anorexia nervosa (AN) is characterized by disturbances in cognition and behavior surrounding eating and weight. The severity of AN combined with the absence of localized brain abnormalities suggests distributed, systemic underpinnings that may be identified using diffusion-weighted magnetic resonance imaging and tractography to reconstruct white matter pathways.

METHODS

Diffusion-weighted magnetic resonance imaging data acquired from female patients with AN (n= 147) and female healthy control (HC) participants (n = 119), ages 12 to 40 years, were combined across 5 studies. Probabilistic tractography was completed, and full-cortex connectomes describing streamline counts between 84 brain regions were generated and harmonized. Graph theory methods were used to describe alterations in network organization in AN. The network-based statistic tested between-group differences in brain subnetwork connectivity. The metrics strength and efficiency indexed the connectivity of brain regions (network nodes) and were compared between groups using multiple linear regression.

RESULTS

Individuals with AN, relative to HC peers, had reduced connectivity in a network comprising subcortical regions and greater connectivity between frontal cortical regions (p < .05, familywise error corrected). Node-based analyses indicated reduced connectivity of the left hippocampus in patients relative to HC peers (p < .05, permutation corrected). Severity of illness, assessed by body mass index, was associated with subcortical connectivity (p < .05, uncorrected).

CONCLUSIONS

Analyses identified reduced structural connectivity of subcortical networks and regions, and stronger cortical network connectivity, among individuals with AN relative to HC peers. These findings are consistent with alterations in feeding, emotion, and executive control circuits in AN, and may direct hypothesis-driven research into mechanisms of persistent restrictive eating behavior.

Attachment Trauma Is Associated with White Matter Fiber Microstructural Alterations in Adolescents with Anorexia Nervosa before and after Exposure to Psychotherapeutic and Nutritional Treatment

In the present study, we explore the role of attachment for microstructural white matter (WM) changes in adolescents with anorexia nervosa (AN) before and after exposure to short-term and nutritional treatment. The case sample consisted of 22 female adolescent inpatients with AN (mean age: 15.2 ± 1.2 years) and the control sample were 18 gender-matched healthy adolescents (mean age: 16.8 ± 0.9 years). We performed a 3T MRI in the patient group during the acute state of AN and after weight restoration (duration: 2.6 ± 1 months) and compared the data to a healthy control group. To classify attachment patterns, we used the Adult Attachment Projective Picture System. In the patient sample, over 50% were classified with an attachment trauma/unresolved attachment status. Prior to treatment exposure, fractional anisotropy (FA) reductions and concordant mean diffusivity (MD) increases were evident in the fornix, the corpus callosum and WM regions of the thalamus, which normalized in the corpus callosum and the fornix post-therapy in the total patient sample (p < 0.002). In the acute state, patients with an attachment trauma demonstrated significant FA decreases compared to healthy controls, but no MD increases, in the corpus callosum and cingulum bilaterally, which remained decreased after therapy. Attachment patterns seem to be associated with region-specific changes of WM alterations in AN.

Complex functional brain network properties in anorexia nervosa

BACKGROUND

Anorexia nervosa (AN) is a disorder characterized by an incapacitating fear of weight gain and by a disturbance in the way the body is experienced, facets that motivate dangerous weight loss behaviors. Multimodal neuroimaging studies highlight atypical neural activity in brain networks involved in interoceptive awareness and reward processing.

METHODS

The current study used resting-state neuroimaging to model the architecture of large-scale functional brain networks and characterize network properties of individual brain regions to clinical measures. Resting-state neuroimaging was conducted in 62 adolescents, 22 (21 female) with a history of AN and 40 (39 female) healthy controls (HCs). Sensorimotor and basal ganglia regions, as part of a 165-region whole-brain network, were investigated. Subject-specific functional brain networks were computed to index centrality. A contrast analysis within the general linear model covarying for age was performed. Correlations between network properties and behavioral measures were conducted (significance q < .05).

RESULTS

Compared to HCs, AN had lower connectivity from sensorimotor regions, and greater connectivity from the left caudate nucleus to the right postcentral gyrus. AN demonstrated lower sensorimotor centrality, but higher basal ganglia centrality. Sensorimotor connectivity dyads and centrality exhibited negative correlations with body dissatisfaction and drive for thinness, two essential features of AN.

CONCLUSIONS

These findings suggest that AN is associated with greater communication from the basal ganglia, and lower information propagation in sensorimotor cortices. This is consistent with the clinical presentation of AN, where individuals exhibit patterns of rigid habitual behavior that is not responsive to bodily needs, and seem "disconnected" from their bodies.

Brain networks in eating disorders: a systematic review of graph theory studies

PURPOSE

Recent evidence from neuroimaging research has shown that eating disorders (EDs) are characterized by alterations in interconnected neural systems, whose characteristics can be usefully described by connectomics tools. The present paper aimed to review the neuroimaging literature in EDs employing connectomic tools, and, specifically, graph theory analysis.

METHODS

A systematic review of the literature was conducted to identify studies employing graph theory analysis on patients with eating disorders published before the 22nd of June 2020.

RESULTS

Twelve studies were included in the systematic review. Ten of them address anorexia nervosa (AN) (AN = 199; acute AN = 85, weight recovered AN with acute diagnosis = 24; fully recovered AN = 90). The remaining two articles address patients with bulimia nervosa (BN) (BN = 48). Global and regional unbalance in segregation and integration properties were described in both disorders.

DISCUSSION

The literature concerning the use of connectomics tools in EDs evidenced the presence of alterations in the topological characteristics of brain networks at a global and at a regional level. Changes in local characteristics involve areas that have been demonstrated to be crucial in the neurobiology and pathophysiology of EDs. Regional imbalances in network properties seem to reflect on global patterns.

LEVEL OF EVIDENCE

Level I, systematic review.

Structural neuroimaging of somatoform disorders: A systematic review

Although there has been an increment in neuroimaging research in somatoform disorders (SD), to date little is known about the neural correlates of these diseases. Therefore, in this systematic, review we aimed at summarizing the existing evidence of structural brain alterations in SD as per DSM-IV and DSM-5 criteria. Three electronic databases (Scopus, PubMed and Web of Science) were searched. Only case-control studies using structural neuroimaging were included. Forty-five out of 369 articles fulfilled inclusion criteria and were reviewed. Compared to controls, subjects with SD showed morphological alterations encompassing motor, limbic and somatosensory circuits. Although far from being conclusive, the results suggested that SD are characterized by selective alterations of large-scale brain networks implicated in cognitive control, emotion regulation and processing, stress and somatic-visceral perception. This review highlights the need for further multimodal neuroimaging studies with longitudinal designs, in larger and better-characterized samples, to elucidate the temporal and causal relationship between neuroanatomical changes and SD, which is paramount for informing tailored treatments.

What is the relationship between body mass index and eating disorder symptomatology in professional female fashion models?

Low body mass index (BMI<18/18.5) is utilized as a mandated cutoff for professional fashion model employment, based on assumptions that low BMI indicates eating disorder pathology. No previous studies have examined the association between experimenter-measured BMI and eating disorder symptomatology in professional fashion models. We measured BMI and Eating Disorder Examination Questionnaire (EDE-Q) responses in United Kingdom (UK) professional fashion models, and nonmodels. Characteristics were compared using robust standardized mean difference (rSMD) obtained via probability of superiority. Associations between BMI and eating disorder symptomatology were examined using robust regression, controlling for age. Models exhibited lower BMI but higher fat-percentage and muscle mass. On the EDE-Q, models had higher Restraint, Global, Eating, and Weight Concerns, and similar Shape Concern scores compared to nonmodels. BMI was positively associated with eating disorder symptoms in both groups, and all but one of the eight models with clinically significant EDE-Q level had ≥18.5 measured BMI. Lower BMI was not indicative of worse eating disorder symptomatology in models or nonmodels. Thus, using a low BMI cutoff (<18.5) may not be an appropriate single index of health for detecting elevated eating disorder symptoms in models. Different policies to protect models' health should be considered.

Altered global brain network topology as a trait marker in patients with anorexia nervosa

BACKGROUND

Resting state functional magnetic resonance imaging studies have identified functional connectivity patterns associated with acute undernutrition in anorexia nervosa (AN), but few have investigated recovered patients. Thus, a trait connectivity profile characteristic of the disorder remains elusive. Using state-of-the-art graph-theoretic methods in acute AN, the authors previously found abnormal global brain network architecture, possibly driven by local network alterations. To disentangle trait from starvation effects, the present study examines network organization in recovered patients.

METHODS

Graph-theoretic metrics were used to assess resting-state network properties in a large sample of female patients recovered from AN (recAN, n = 55) compared with pairwise age-matched healthy controls (HC, n = 55).

RESULTS

Indicative of an altered global network structure, recAN showed increased assortativity and reduced global clustering as well as small-worldness compared with HC, while no group differences at an intermediate or local network level were evident. However, using support-vector classifier on local metrics, recAN and HC could be separated with an accuracy of 70.4%.

CONCLUSIONS

This pattern of results suggests that long-term recovered patients have an aberrant global brain network configuration, similar to acutely underweight patients. While the finding of increased assortativity may represent a trait marker of AN, the remaining findings could be seen as a scar following prolonged undernutrition.

Anorexia nervosa and diffusion weighted imaging: An open methodological question raised by a systematic review and a fractional anisotropy anatomical likelihood estimation meta-analysis

BACKGROUND

Anorexia nervosa (AN) is characterized by white matter abnormalities in neuroimaging studies. Fractional anisotropy (FA) is a diffusion tensor imaging (DTI) index that is considered an instrument for the evaluation of white matter alterations. However, the literature has recently pointed out the role of the partial volume effect (PVE) as a confounding factor for the identification of juxtaposed tissues. Our goal was to review the DTI literature in AN and evaluate possible confounding factors linked to the reported results.

METHOD

A systematic review of the literature was conducted to identify Diffusion Tensor Imaging studies of individuals with AN and, subsequently, an anatomical likelihood estimation (ALE) meta-analysis was performed on studies published before March 18, 2019.

RESULTS

Twenty-four studies (AN = 517, controls = 542) were included in the qualitative systematic review of the literature. Ten published studies underwent the ALE-analysis (AN = 210, controls = 229), plus data from an unpublished cohort (AN = 38, controls = 38). Two clusters of decreased FA were identified, namely in the left corona radiata, and in the left thalamus. Only one article took the PVE correction analysis into account.

CONCLUSIONS

The alterations identified must be considered within the limits of a possible methodological bias regarding PVE and free water and re-analysis of the data may be recommended. The preliminary data showed that the alteration of white matter pathways between the limbic structures and brain cortex may be linked to the processing of somatosensory information that could play a key role in the psychopathology of the disorder.

White Matter Abnormalities in the Corpus Callosum in Acute and Recovered Anorexia Nervosa Patients-A Diffusion Tensor Imaging Study

Objective: Severe malnutrition in patients with anorexia nervosa (AN) as well as possible trait-related aberrations lead to pronounced structural brain changes whose reversibility after recovery is currently unclear. Previous diffusion tensor imaging (DTI) studies investigating white matter (WM) microstructure alterations in AN are inconsistent. Methods: In this so far largest DTI study in adults, we investigated 33 AN patients, 20 recovered (REC), and 33 healthy women. DTI data were processed using the "DTI and Fiber tools," and the Computational Anatomy Toolbox. WM integrity, both in terms of fractional anisotropy (FA) and mean diffusivity (MD), was assessed. Results: We found a significant FA decrease in the corpus callosum (body) and an MD decrease in the posterior thalamic radiation in the AN group. The REC group displayed FA decrease in the corpus callosum in comparison to HC, whereas there were no MD differences between the REC and HC groups. Conclusion: Despite prolonged restoration of weight in the REC group, no significant regeneration of WM integrity in terms of FA could be observed. Transient changes in MD likely represent a reversible consequence of the acute state of starvation or result from dehydration. Reduction of FA either may be due to WM damage resulting from malnutrition or may be considered a pre-morbid marker.

Dynamic changes in white matter microstructure in anorexia nervosa: findings from a longitudinal study

BACKGROUND

Gray matter (GM) 'pseudoatrophy' is well-documented in patients with anorexia nervosa (AN), but changes in white matter (WM) are less well understood. Here we investigated the dynamics of microstructural WM brain changes in AN patients during short-term weight restoration in a combined longitudinal and cross-sectional study design.

METHODS

Diffusion-weighted images were acquired in young AN patients before (acAN-Tp1, n = 56) and after (acAN-Tp2, n = 44) short-term weight restoration as well as in age-matched healthy controls (HC, n = 60). Images were processed using Tract-Based-Spatial-Statistics to compare fractional anisotropy (FA) across groups and timepoints.

RESULTS

In the cross-sectional comparison, FA was significantly reduced in the callosal body in acAN-Tp1 compared with HC, while no differences were found between acAN-Tp2 and HC. In the longitudinal arm, FA increased with weight gain in acAN-Tp2 relative to acAN-Tp1 in large parts of the callosal body and the fornix, while it decreased in the right corticospinal tract.

CONCLUSIONS

Our findings reveal that dynamic, bidirectional changes in WM microstructure in young underweight patients with AN can be reversed with brief weight restoration therapy. These results parallel those previously observed in GM and suggest that alterations in WM in non-chronic AN are also state-dependent and rapidly reversible with successful intervention.

Differentiating weight-restored anorexia nervosa and body dysmorphic disorder using neuroimaging and psychometric markers

Anorexia nervosa (AN) and body dysmorphic disorder (BDD) are potentially life-threatening conditions whose partially overlapping phenomenology—distorted perception of appearance, obsessions/compulsions, and limited insight—can make diagnostic distinction difficult in some cases. Accurate diagnosis is crucial, as the effective treatments for AN and BDD differ. To improve diagnostic accuracy and clarify the contributions of each of the multiple underlying factors, we developed a two-stage machine learning model that uses multimodal, neurobiology-based, and symptom-based quantitative data as features: task-based functional magnetic resonance imaging data using body visual stimuli, graph theory metrics of white matter connectivity from diffusor tensor imaging, and anxiety, depression, and insight psychometric scores. In a sample of unmedicated adults with BDD (n = 29), unmedicated adults with weight-restored AN (n = 24), and healthy controls (n = 31), the resulting model labeled individuals with an accuracy of 76%, significantly better than the chance accuracy of 35% (p^<10‑4). In the multivariate model, reduced white matter global efficiency and better insight were associated more with AN than with BDD. These results improve our understanding of the relative contributions of the neurobiological characteristics and symptoms of these disorders. Moreover, this approach has the potential to aid clinicians in diagnosis, thereby leading to more tailored therapy.

Resting state functional connectivity of networks associated with reward and habit in anorexia nervosa

Neurobiological disturbances associated with reward and/or habit learning are theorized to maintain symptoms of anorexia nervosa (AN). Although research has investigated responses in brain regions associated with reward and habit to disorder-specific cues (e.g., food) and presumed rewards (e.g., money), little is known about the functional organization of the circuits underlying these constructs independent of stimulus. This study aimed to provide initial data on the synchrony of networks associated with reward and habit in AN by comparing resting-state functional connectivity (RSFC) patterns between AN and healthy control (HC) participants in these circuits and delineating how these patterns relate to symptoms. Using theoretically selected seeds in the nucleus accumbens (NAcc), ventral caudate, and dorsal caudate, reflecting a continuum from reward- to habit- oriented regions, RSFC patterns were compared between AN restricting subtype (n = 19) and HC (n = 19) participants (cluster threshold: p < .01). Exploratory correlations between RSFC z-scores and Eating Disorder Examination (EDE) scores, BMI, and illness duration were conducted. The AN group demonstrated lower RSFC between the NAcc and superior frontal gyrus, between the ventral caudate and frontal and posterior regions, and between the dorsal caudate and frontal, temporal, and posterior regions. In the AN group, lower NAcc- superior frontal gyrus RSFC correlated with greater EDE Global scores (r = -.58, CI: -.83, -.13). These resting-state synchrony disruptions of the ventral and dorsal frontostriatal circuits, considered in context of the broader literature, support the utility of further investigating possible reward and habit disturbances supporting symptoms in AN.

Structural Neuroimaging of Anorexia Nervosa: Future Directions in the Quest for Mechanisms Underlying Dynamic Alterations

Anorexia nervosa (AN) is a serious eating disorder characterized by self-starvation and extreme weight loss. Pseudoatrophic brain changes are often readily visible in individual brain scans, and AN may be a valuable model disorder to study structural neuroplasticity. Structural magnetic resonance imaging studies have found reduced gray matter volume and cortical thinning in acutely underweight patients to normalize following successful treatment. However, some well-controlled studies have found regionally greater gray matter and persistence of structural alterations following long-term recovery. Findings from diffusion tensor imaging studies of white matter integrity and connectivity are also inconsistent. Furthermore, despite the severity of AN, the number of existing structural neuroimaging studies is still relatively low, and our knowledge of the underlying cellular and molecular mechanisms for macrostructural brain changes is rudimentary. We critically review the current state of structural neuroimaging in AN and discuss the potential neurobiological basis of structural brain alterations in the disorder, highlighting impediments to progress, recent developments, and promising future directions. In particular, we argue for the utility of more standardized data collection, adopting a connectomics approach to understanding brain network architecture, employing advanced magnetic resonance imaging methods that quantify biomarkers of brain tissue microstructure, integrating data from multiple imaging modalities, strategic longitudinal observation during weight restoration, and large-scale data pooling. Our overarching objective is to motivate carefully controlled research of brain structure in eating disorders, which will ultimately help predict therapeutic response and improve treatment.

The significance of negative correlations in brain connectivity

Understanding the modularity of functional magnetic resonance imaging (fMRI)-derived brain networks or "connectomes" can inform the study of brain function organization. However, fMRI connectomes additionally involve negative edges, which may not be optimally accounted for by existing approaches to modularity that variably threshold, binarize, or arbitrarily weight these connections. Consequently, many existing Q maximization-based modularity algorithms yield variable modular structures. Here, we present an alternative complementary approach that exploits how frequent the blood-oxygen-level-dependent (BOLD) signal correlation between two nodes is negative. We validated this novel probability-based modularity approach on two independent publicly-available resting-state connectome data sets (the Human Connectome Project [HCP] and the 1,000 functional connectomes) and demonstrated that negative correlations alone are sufficient in understanding resting-state modularity. In fact, this approach (a) permits a dual formulation, leading to equivalent solutions regardless of whether one considers positive or negative edges; (b) is theoretically linked to the Ising model defined on the connectome, thus yielding modularity result that maximizes data likelihood. Additionally, we were able to detect novel and consistent sex differences in modularity in both data sets. As data sets like HCP become widely available for analysis by the neuroscience community at large, alternative and perhaps more advantageous computational tools to understand the neurobiological information of negative edges in fMRI connectomes are increasingly important.