Can neuroimaging measures differentiate the disease course of anorexia nervosa? A systematic review

Exploring the neurobiological correlates of psilocybin-assisted psychotherapy in eating disorders: a review of potential methodologies and implications for the psychedelic study design

Eating disorders (EDs) are a group of debilitating mental illnesses characterized by maladaptive eating behaviors and severe cognitive-emotional dysfunction, directly affecting 1-3% of the population. Standard treatments are not effective in approximately one third of ED cases, representing the need for scientific advancement. There is emerging evidence for the safety and efficacy of psilocybin-assisted psychotherapy (PAP) to improve treatment outcomes in individuals with EDs. However, the limited knowledge of the neurobiological mechanisms underlying the therapeutic effects of PAP restricts the ability to confirm its clinical utility. This narrative review presents an overview of methodologies used to elucidate the pathophysiological mechanisms of EDs or the effects of psilocybin that could be employed to probe the neurobiological correlates of PAP in EDs, including magnetic resonance imaging and molecular neuroimaging techniques, electrophysiological approaches, and neuroplasticity markers. Finally, the implications of these methodologies are described in relation to the unique features of the psychedelic study design, challenges, limitations, and future directions to advance the field. This paper represents a valuable resource for scientists during study conceptualization and design phases and stimulates advancement in the identification of effective therapeutic interventions for EDs.

Predicting long-term outcome in anorexia nervosa: a machine learning analysis of brain structure at different stages of weight recovery

BACKGROUND

Anorexia nervosa (AN) is characterized by sizable, widespread gray matter (GM) reductions in the acutely underweight state. However, evidence for persistent alterations after weight-restoration has been surprisingly scarce despite high relapse rates, frequent transitions to other psychiatric disorders, and generally unfavorable outcome. While most studies investigated brain regions separately (univariate analysis), psychiatric disorders can be conceptualized as brain network disorders characterized by multivariate alterations with only subtle local effects. We tested for persistent multivariate structural brain alterations in weight-restored individuals with a history of AN, investigated their putative biological substrate and relation with 1-year treatment outcome.

METHODS

We trained machine learning models on regional GM measures to classify healthy controls (HC) (N = 289) from individuals at three stages of AN: underweight patients starting intensive treatment (N = 165, used as baseline), patients after partial weight-restoration (N = 115), and former patients after stable and full weight-restoration (N = 89). Alterations after weight-restoration were related to treatment outcome and characterized both anatomically and functionally.

RESULTS

Patients could be classified from HC when underweight (ROC-AUC = 0.90) but also after partial weight-restoration (ROC-AUC = 0.64). Alterations after partial weight-restoration were more pronounced in patients with worse outcome and were not detected in long-term weight-recovered individuals, i.e. those with favorable outcome. These alterations were more pronounced in regions with greater functional connectivity, not merely explained by body mass index, and even increases in cortical thickness were observed (insula, lateral orbitofrontal, temporal pole).

CONCLUSIONS

Analyzing persistent multivariate brain structural alterations after weight-restoration might help to develop personalized interventions after discharge from inpatient treatment.