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Predicting the outcome of psilocybin treatment for depression from baseline fMRI functional connectivity.

Debora Copa, David Erritzøe, Bruna Giribaldi, David Nutt, Robin Carhart-Harris, Enzo Tagliazucchi

J Affect Disord February 27, 2024 DOI: 10.1016/j.jad.2024.02.089 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Observational cohort Peer reviewed
Sample size 38
Population Patients with treatment-resistant depression or moderate-to-severe major depression
Intervention Psilocybin
Dose 25 mg
Duration 24-week follow-up
Topics Psychedelic-assisted therapy Depression Psilocybin
Keywords Psilocybin therapy Psilocybin treatment Psychedelics for depression Brain imaging FMRI Neuroimaging Brain scans Functional connectivity Neural signatures Brain activity Personalized medicine Precision medicine Tailored therapy Predictive biomarkers Individualized treatment Depression treatment Mental health treatment Antidepressant therapy
Citations 31
Key findings Baseline resting-state functional connectivity of visual, default mode, executive, and salience networks predicted symptom improvement up to 24 weeks after psilocybin treatment, with accuracy around 0.9.

Abstract

BackgroundPsilocybin is a serotonergic psychedelic drug under assessment as a potential therapy for treatment-resistant and major depression. Heterogeneous treatment responses raise interest in predicting the outcome from baseline data.MethodsA machine learning pipeline was implemented to investigate baseline resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI) as a predictor of symptom severity in psilocybin monotherapy for treatment-resistant depression (16 patients administered two 5 mg capsules followed by 25 mg, separated by one week). Generalizability was tested in a sample of 22 patients who participated in a psilocybin vs. escitalopram trial for moderate-to-severe major depression (two separate doses of 25 mg of psilocybin 3 weeks apart plus 6 weeks of daily placebo vs. two separate doses of 1 mg of psilocybin 3 weeks apart plus 6 weeks of daily oral escitalopram). The analysis was repeated using both samples combined.ResultsFunctional connectivity of visual, default mode and executive networks predicted early symptom improvement, while the salience network predicted responders up to 24 weeks after treatment (accuracy≈0.9). Generalization performance was borderline significant. Consistent results were obtained from the combined sample analysis. Fronto-occipital and fronto-temporal coupling predicted early and late symptom reduction, respectively.LimitationsThe number of participants and differences between the two datasets limit the generalizability of the findings, while the lack of a placebo arm limits their specificity.ConclusionsBaseline neurophysiological measurements can predict the outcome of psilocybin treatment for depression. Future research based on larger datasets should strive to assess the generalizability of these predictions.

Comparable studies

Other observational and cohort studies on psilocybin and psychedelic-assisted therapy, most cited first.

Study Year Design Participants
Acute subjective effects in LSD- and MDMA-assisted psychotherapy Patients with psychiatric disorders (posttraumatic stress disorder and major... 2020 Observational study n = 18
Natural speech algorithm applied to baseline interview data can predict which patients will respond to psilocybin for treatment-resistant depression. 17 patients with treatment-resistant depression and 18 untreated age-matched healthy... 2018 Observational cohort with machine learning classification n = 35
The Promise of Therapeutic Psilocybin: An Evaluation of the 134 Clinical Trials, 54 Potential Indications, and 0 Marketing Approvals on ClinicalTrials.gov. Psilocybin clinical trials listed on ClinicalTrials.gov 2024 Observational study n = 134
Naturalistic psychedelic therapy: The role of relaxation and subjective drug effects in antidepressant response 28 PAT patients and 28 healthy volunteers 2024 Observational cohort with comparison group n = 56
Body mass index (BMI) does not predict responses to psilocybin 2022 Observational cohort

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