Expectancy Effects in Psychedelic Trials.

Clinical trials of psychedelic compounds like psilocybin, lysergic acid diethylamide (LSD), and N,N-dimethyltrptamine (DMT) have forced a reconsideration of how nondrug factors, such as participant expectations, are measured and controlled in mental health research. As doses of these profoundly psychoactive substances increase, so does the difficulty in concealing the treatment condition in the classic double-blind, placebo-controlled trial design. As widespread public enthusiasm for the promise of psychedelic therapy grows, so do questions regarding whether and how much trial results are biased by positive expectancy. First, we review the key concepts related to expectancy and its measurement. Then, we review expectancy effects that have been reported in both micro- and macrodose psychedelic trials from the modern era. Finally, we consider expectancy as a discrete physiological process that can be independent of, or even interact with, the drug effect. Expectancy effects can be harnessed to improve treatment outcomes and can also be actively managed in controlled studies to enhance the rigor and generalizability of future psychedelic trials.

Assessing expectancy and suggestibility in a trial of escitalopram v. psilocybin for depression.

BACKGROUND: To investigate the association between pre-trial expectancy, suggestibility, and response to treatment in a trial of escitalopram and investigational drug, COMP360, psilocybin, in the treatment of major depressive disorder (ClinicalTrials.gov registration: NCT03429075). METHODS: We used data (n = 55) from our recent double-blind, parallel-group, randomized head-to-head comparison trial of escitalopram and investigational drug, COMP360, psilocybin. Mixed linear models were used to investigate the association between pre-treatment efficacy-related expectations, as well as baseline trait suggestibility and absorption, and therapeutic response to both escitalopram and COMP360 psilocybin. RESULTS: Patients had significantly higher expectancy for psilocybin relative to escitalopram; however, expectancy for escitalopram was associated with improved therapeutic outcomes to escitalopram, expectancy for psilocybin was not predictive of response to psilocybin. Separately, we found that pre-treatment trait suggestibility was associated with therapeutic response in the psilocybin arm, but not in the escitalopram arm. CONCLUSIONS: Overall, our results suggest that psychedelic therapy may be less vulnerable to expectancy biases than previously suspected. The relationship between baseline trait suggestibility and response to psilocybin therapy implies that highly suggestible individuals may be primed for response to this treatment.

Claudin expression in pulmonary adenoid cystic carcinoma and mucoepidermoid carcinoma.

Background: Although the expression of tight junction protein claudins (CLDNs) is well known in common histological subtypes of lung cancer, it has not been investigated in rare lung cancers. The aim of our study was to examine the expression of different CLDNs in pulmonary salivary gland tumors. Methods: 35 rare lung cancers including pathologically confirmed 12 adenoid cystic carcinomas (ACCs) and 23 mucoepidermoid carcinomas (MECs) were collected retrospectively. Immunohistochemical (IHC) staining was performed on formalin fixed paraffin embedded (FFPE) tumor tissues, and CLDN1, -2, -3, -4, -5, -7, and -18 protein expressions were analyzed. The levels of immunopositivity were determined with H-score. Certain pathological characteristics of ACC and MEC samples (tumor grade, presence of necrosis, presence of blood vessel infiltration, and degree of lymphoid infiltration) were also analyzed. Results: CLDN overexpression was observed in both tumor types, especially in CLDN2, -7, and -18 IHC. Markedly different patterns of CLDN expression were found for ACC and MEC tumors, especially for CLDN1, -2, -4, and -7, although none of these trends remained significant after correction for multiple testing. Positive correlations between expressions of CLDN2 and -5, CLDN3 and -4, and CLDN5 and -18 were also demonstrated. Tumors of never-smokers presented lower levels of CLDN18 than tumors of current smokers (p-value: 0.003). Conclusion: This is the first study to comprehensively describe the expression of different CLDNs in lung ACC and MEC. Overexpression of certain CLDNs may pave the way for targeted anti-claudin therapy in these rare histological subtypes of lung cancer.

The difference between 'placebo group' and 'placebo control': a case study in psychedelic microdosing.

In medical trials, 'blinding' ensures the equal distribution of expectancy effects between treatment arms in theory; however, blinding often fails in practice. We use computational modelling to show how weak blinding, combined with positive treatment expectancy, can lead to an uneven distribution of expectancy effects. We call this 'activated expectancy bias' (AEB) and show that AEB can inflate estimates of treatment effects and create false positive findings. To counteract AEB, we introduce the Correct Guess Rate Curve (CGRC), a statistical tool that can estimate the outcome of a perfectly blinded trial based on data from an imperfectly blinded trial. To demonstrate the impact of AEB and the utility of the CGRC on empirical data, we re-analyzed the 'self-blinding psychedelic microdose trial' dataset. Results suggest that observed placebo-microdose differences are susceptible to AEB and are at risk of being false positive findings, hence, we argue that microdosing can be understood as active placebo. These results highlight the important difference between 'trials with a placebo-control group', i.e., when a placebo control group is formally present, and 'placebo-controlled trials', where patients are genuinely blind. We also present a new blinding integrity assessment tool that is compatible with CGRC and recommend its adoption.

Self-blinding citizen science to explore psychedelic microdosing.

Microdosing is the practice of regularly using low doses of psychedelic drugs. Anecdotal reports suggest that microdosing enhances well-being and cognition; however, such accounts are potentially biased by the placebo effect. This study used a 'self-blinding' citizen science initiative, where participants were given online instructions on how to incorporate placebo control into their microdosing routine without clinical supervision. The study was completed by 191 participants, making it the largest placebo-controlled trial on psychedelics to-date. All psychological outcomes improved significantly from baseline to after the 4 weeks long dose period for the microdose group; however, the placebo group also improved and no significant between-groups differences were observed. Acute (emotional state, drug intensity, mood, energy, and creativity) and post-acute (anxiety) scales showed small, but significant microdose vs. placebo differences; however, these results can be explained by participants breaking blind. The findings suggest that anecdotal benefits of microdosing can be explained by the placebo effect.

Psychedelic psychotherapy, therapy enhanced with psychedelic drugs such as LSD or psilocybin (the active ingredient of 'magic mushrooms'), has been suggested to improve psychological well-being. For this reason, trials on psychedelic therapy for the treatment of depression, addiction and other conditions are ongoing. Recently, 'microdosing' ­ a way of administering psychedelics that involves taking about 10% of a recreational dose two or three times per week ­ has gained popularity. Unlike taking large doses of psychedelics, microdosing does not induce hallucinations, but anecdotal reports suggest that it yields similar benefits as psychedelic therapy. A key feature of modern medicine are 'placebo control' studies that compare two groups of patients: one that takes a drug and another that takes inactive pills, known as placebos. Crucially, neither group knows whether they are taking drug or placebo. This control ensures that observed effects are due to the drug itself and not to unrelated psychological causes. For example, in trials of mood medicines, participants often expect to feel happier, which in itself improves their mood even when taking a placebo. This is known as the placebo effect. Restrictive drug policies make placebo-controlled studies on psychedelics difficult and expensive, in particular for microdosing, which involves taking psychedelics over a longer time period. To overcome this problem, Szigeti et al. developed a new citizen-science approach, where microdosers implemented their own placebo control based on online instructions. The advantages are the low cost and the ability to recruit participants globally. The experiment was completed by 191 microdosers, making it the largest placebo-controlled study on psychedelics to-date, for a fraction of the cost of an equivalent clinical study. The trial examined whether psychedelic microdosing can improve cognitive function and psychological well-being. The team found that microdosing significantly increased a number of psychological measures, such as well-being and life satisfaction. However, participants taking placebo also improved: there were no significant differences between the two groups. The findings confirmed positive anecdotes about microdosing improving people's moods, but at the same time show that taking empty capsules, knowing they might be microdoses, have the same benefits. This result suggests that the observed benefits are not caused by the microdose, but rather by psychological expectations. The study's innovative 'do-it-yourself' approach to placebo control may serve as a template for future citizen science studies on other popular phenomena where positive expectations and social factors could play a role, such as cannabidiol (CBD) oils, nootropics and nutrition.

Are ecstasy induced serotonergic alterations overestimated for the majority of users?

BACKGROUND: Neuroimaging studies imply that the regular use of ±3,4-methylenedioxymethamphetamine (MDMA), the major constituent of ecstasy pills, alters the brain's serotonergic system in a dose-dependent manner. However, the relevance of these findings remains unclear due to limited knowledge about the ecstasy/MDMA use pattern of real-life users. AIMS: We examined the representativeness of ecstasy users enrolled in neuroimaging studies by comparing their ecstasy use habits with the use patterns of a large, international sample. METHODS: A systematic literature search revealed 10 imaging studies that compare serotonin transporter levels in recreational ecstasy users to matched controls. To characterize the ecstasy use patterns we relied on the Global Drug Survey, the world's largest self-report database on drug use. The basis of the dose comparison were the Usual Amount (pills/session), Use Frequency (sessions/month) and Dose Intensity (pills/year) variables. RESULTS: Both the average Usual Amount (pills/session) and Use Frequency (sessions/month) of neuroimaging study participants corresponded to the top 5-10% of the Global Drug Survey sample and imaging participants, on average, consumed 720% more pills over a year than the Global Drug Survey participants. CONCLUSIONS: Our findings suggest that the serotonin brain imaging literature has focused on unusually heavy ecstasy use and therefore the conclusions from these studies are likely to overestimate the extent of serotonergic alterations experienced by the majority of people who use ecstays.

A blueprint for human whole-cell modeling.

Whole-cell dynamical models of human cells are a central goal of systems biology. Such models could help researchers understand cell biology and help physicians treat disease. Despite significant challenges, we believe that human whole-cell models are rapidly becoming feasible. To develop a plan for achieving human whole-cell models, we analyzed the existing models of individual cellular pathways, surveyed the biomodeling community, and reflected on our experience developing whole-cell models of bacteria. Based on these analyses, we propose a plan for a project, termed the Human Whole-Cell Modeling Project, to achieve human whole-cell models. The foundations of the plan include technology development, standards development, and interdisciplinary collaboration.

Emerging whole-cell modeling principles and methods.

Whole-cell computational models aim to predict cellular phenotypes from genotype by representing the entire genome, the structure and concentration of each molecular species, each molecular interaction, and the extracellular environment. Whole-cell models have great potential to transform bioscience, bioengineering, and medicine. However, numerous challenges remain to achieve whole-cell models. Nevertheless, researchers are beginning to leverage recent progress in measurement technology, bioinformatics, data sharing, rule-based modeling, and multi-algorithmic simulation to build the first whole-cell models. We anticipate that ongoing efforts to develop scalable whole-cell modeling tools will enable dramatically more comprehensive and more accurate models, including models of human cells.

Searching for motifs in the behaviour of larval Drosophila melanogaster and Caenorhabditis elegans reveals continuity between behavioural states.

We present a novel method for the unsupervised discovery of behavioural motifs in larval Drosophila melanogaster and Caenorhabditis elegans. A motif is defined as a particular sequence of postures that recurs frequently. The animal's changing posture is represented by an eigenshape time series, and we look for motifs in this time series. To find motifs, the eigenshape time series is segmented, and the segments clustered using spline regression. Unlike previous approaches, our method can classify sequences of unequal duration as the same motif. The behavioural motifs are used as the basis of a probabilistic behavioural annotator, the eigenshape annotator (ESA). Probabilistic annotation avoids rigid threshold values and allows classification uncertainty to be quantified. We apply eigenshape annotation to both larval Drosophila and C. elegans and produce a good match to hand annotation of behavioural states. However, we find many behavioural events cannot be unambiguously classified. By comparing the results with ESA of an artificial agent's behaviour, we argue that the ambiguity is due to greater continuity between behavioural states than is generally assumed for these organisms.

OpenWorm: an open-science approach to modeling Caenorhabditis elegans.

OpenWorm is an international collaboration with the aim of understanding how the behavior of Caenorhabditis elegans (C. elegans) emerges from its underlying physiological processes. The project has developed a modular simulation engine to create computational models of the worm. The modularity of the engine makes it possible to easily modify the model, incorporate new experimental data and test hypotheses. The modeling framework incorporates both biophysical neuronal simulations and a novel fluid-dynamics-based soft-tissue simulation for physical environment-body interactions. The project's open-science approach is aimed at overcoming the difficulties of integrative modeling within a traditional academic environment. In this article the rationale is presented for creating the OpenWorm collaboration, the tools and resources developed thus far are outlined and the unique challenges associated with the project are discussed.