Symptom Dynamics in Psilocybin versus Escitalopram Treatment for Depression: A Dynamic Timewarp Analysis

Abstract

Psilocybin-assisted therapy has shown promising results for the treatment of depression in several studies (see Ko et al., 2023 for a meta-analysis). In these studies, data was typically analyzed using sum scores of individual symptom items, and thresholds were used to indicate depression status. In line with the dominant explanation in the field, this approach assumes that symptoms are equivalent, causally independent, and roughly interchangeable indicators of the underlying disease construct. However, depression is increasingly being conceptualized from a network perspective, where the depression syndrome is hypothesized to stem from mutual causal relations among different symptoms (e.g., Malgaroli et al., 2021). This approach is in line with a complex dynamic systems viewpoint, in which depression can be seen as an attractor that remains stable even if slightly disturbed. Furthermore, increasing evidence points towards the multidimensional character of depression, with a high degree of symptomatic variability between and within patients (Fried & Nesse, 2015). Consequently, there is increasing recognition of the importance of investigating individual symptoms, their dynamic interrelationships, and their development over time. Applying such a dynamic systems viewpoint to psilocybin-assisted therapy could provide us with deeper insights into its effects on specific symptoms, symptom interactions, and symptom course trajectories, both within individual patients (i.e., idiographic approach) and on a group level (i.e., nomothetic approach). This might generate new hypotheses for the therapeutic mechanisms of psilocybin-assisted therapy and is also in line with the aims of the Research Domain Criteria (RDoC) project to deconstruct psychiatric disorders by analyzing the dynamics (e.g., symptom trajectories over time) that lie at their basis (Insel et al., 2010). Increasing our understanding of the therapeutic mechanisms and clinical action from a dynamic systems viewpoint might be especially relevant in the context of psychedelic-assisted therapy, which is increasingly being framed as a potential transdiagnostic treatment for a range of stress-related psychiatric disorders (Kelly et al., 2021). In addition, with the growing evidence for the efficacy of psilocybin-assisted therapy, it is becoming increasingly relevant to understand how therapeutic mechanisms and symptom dynamics compare to other depression treatments, such as escitalopram, one of the most commonly prescribed SSRIs. In the current exploratory study, we aim to compare depression symptom dynamics in patients that received either psilocybin-assisted therapy or escitalopram, by conducting a dynamic time warp (DTW) analysis, a temporal alignment technique which can be applied to assess the progression of symptoms over time (Sakoe & Shiba, 1978; Hebbrecht et al., 2020). Data will be sourced from a double-blind, randomized controlled phase 2 study in patients with moderate-to-severe major depressive disorder (Carhart-Harris et al., 2021). Fifty-nine patients were assigned in a 1:1 ratio to receive two separate doses of 25 mg of psilocybin 3 weeks apart plus 6 weeks of daily placebo (psilocybin group) or two separate doses of 1 mg of psilocybin 3 weeks apart plus 6 weeks of daily oral escitalopram (escitalopram group). Patients in both groups received the same type and hours of psychological support. The 16-item Quick Inventory of Depressive Symptomatology–Self-Report (QIDS-SR-16) was administered 13 times: at baseline, weekly from week 1 to week 6, and monthly during the 6 months of follow-up. A major difference between both types of treatment seems to be the onset of therapeutic effects. While SSRIs typically take multiple weeks of daily administration before showing a significant effect on symptoms of depression, psilocybin-assisted therapy has shown the ability to rapidly reduce depression symptoms after only one administration (e.g., Carhart-Harris et al., 2016; Goodwin et al., 2022). Those symptom reductions seem to be relatively durable over time, for at least multiple weeks to months, although follow-up studies have shown that a significant number of participants might relapse in the months after treatment (Carhart-Harris et al., 2018). However, most analyses have focussed on group-level effects, potentially obscuring the variation in improvement and potential relapse speed among different patients. This phenomenon is tied to the non-ergodic nature of depressive symptoms over time. As a consequence, the temporal order of symptom improvements and potential relapse within individual subjects remains inadequately understood. DTW analysis will allow us to visualize and compare the potential differences in symptom course trajectories between both types of treatment, both regarding initial improvement and potential relapse over time. Additionally, it will allow us to determine whether changes in specific symptoms tend to precede similar changes in other symptoms, which of those symptoms have the greatest out-strength centrality (i.e., symptoms that are the most influential), and how this might differ in both types of treatment. For example, a study applying DTW on data collected during electroconvulsive therapy (ECT) treatment, has shown that somatic symptoms generally improve before mood symptoms (Booij et al., Schuyteneer et al., 2023). In general, such a pattern of symptom improvement is also commonly observed after treatment with SSRIs. An opposite pattern might be expected during a course of psilocybin-assisted therapy, as patients often report improved mood immediately after psilocybin administration (Watts et al., 2017; Carhart-Harris et al., 2016). However, as this will be the first investigation of symptom dynamics during a course of psilocybin-asssisted therapy and much is still unknown regarding symptom course trajectories during psychedelic-assisted therapies, the current study will primarily take an exploratory approach. References: Carhart-Harris, R., et al. (2021). "Trial of Psilocybin versus Escitalopram for Depression." N Engl J Med, 384(15), 1402-1411. Carhart-Harris, R. L., Bolstridge, M., Day, C. M., Rucker, J., Watts, R., Erritzoe, D. E., ... & Nutt, D. J. (2018). Psilocybin with psychological support for treatment-resistant depression: six-month follow-up. Psychopharmacology, 235, 399-408. Carhart-Harris, R. L., Bolstridge, M., Rucker, J., Day, C. M., Erritzoe, D., Kaelen, M., ... & Nutt, D. J. (2016). Psilocybin with psychological support for treatment-resistant depression: an open-label feasibility study. The Lancet Psychiatry, 3(7), 619-627. Fried, E. I. and R. M. Nesse (2015). Depression sum-scores don't add up: why analyzing specific depression symptoms is essential. BMC Med, 13, 72. Hebbrecht, K., et al. (2020). Understanding personalized dynamics to inform precision medicine: a dynamic time warp analysis of 255 depressed inpatients. BMC Med, 18(1), 400. Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., ... & Wang, P. (2010). Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. American Journal of psychiatry, 167(7), 748-751. Kelly, J. R., et al. (2021). Psychedelic Therapy's Transdiagnostic Effects: A Research Domain Criteria (RDoC) Perspective." Front Psychiatry, 12, 800072. Ko, K., et al. (2023). Psychedelic therapy for depressive symptoms: A systematic review and meta-analysis. J Affect Disord, 322, 194-204. Malgaroli, M., et al. (2021). Networks of major depressive disorder: A systematic review. Clin Psychol Rev, 85, 102000. Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE transactions on acoustics, speech, and signal processing, 26(1), 43-49. De Schuyteneer, E., Giltay, E., Vansteelandt, K., Obbels, J., Van den Eynde, L., Verspecht, S., ... & Sienaert, P. (2023). Electroconvulsive therapy improves somatic symptoms before mood in patients with depression: A directed network analysis. Brain Stimulation. Watts, R., Day, C., Krzanowski, J., Nutt, D., & Carhart-Harris, R. (2017). Patients’ accounts of increased “connectedness” and “acceptance” after psilocybin for treatment-resistant depression. Journal of humanistic psychology, 57(5), 520-564.

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