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mock grant proposal of “how psilocybin can treat depression”
Specific Aims
Psilocybin is a naturally occurring psychedelic compound found in mushrooms (Madsen
et al., 2019). It has been studied for use in treating depression, with some reports showing that it
can reduce symptoms of major depressive disorder (MDD) (Goodwin et al., 2022). One of the
ways psilocybin works is by binding to serotonin receptors and increasing serotonin levels,
which helps regulate mood and behavior (Goodwin et al., 2022). However, its mechanism of
action is more complex and not fully understood (Goodwin et al., 2022). Although psilocybin
may be effective in treating depression, several questions surround its safety and optimal dosage
(Goodwin et al., 2022). Evidence suggests that at certain doses, the drug can have adverse effects
such as nausea, dizziness, anxiety, and paranoia (Goodwin et al., 2022). This experiment aims to
determine if using psilocybin to treat depression is safe and effective at various doses by testing
the following hypotheses:
H1: A single dose of psilocybin will reduce symptoms of MDD significantly more than a dose of
a placebo
H2: Higher doses of psilocybin will lead to a more pronounced reduction in MDD symptoms
H3: Higher doses of psilocybin will lead to more adverse events.
The specific aims of this experiment are as follows:
1) To determine how different dosages affect symptom reduction over time
2) To identify any potential adverse side effects associated with each dosage level
3) To monitor participants’ response over time after treatment with psilocybin
Studies have suggested that psilocybin can be effective for treatment-resistant depression
(Goodwin et al., 2022). However, the dosage levels used for such cases are usually high and have
a greater risk of adverse effects (Goodwin et al., 2022). This experiment can help determine the
optimal trade-off, particularly for treatment-resistant depression. The project’s overall impact will
be to expand treatment options for patients suffering from depression while ensuring safety.
Significance
According to the National Institute of Mental Health [NIMH] (2022), up to 21 million
U.S. adults experienced at least one episode of major depression in 2020. Further, 14.8 million
had a severe impairment caused by depression in the past year (NIMH, 2022). Notably, only
66% of this population received treatment in the past year (NIMH, 2022). The treatment statistics
are even lower for adolescents at 41.6% (NIMH, 2022). Evidently, there is a need for effective
and accessible treatment for the rising levels of depression. Pharmacological interventions,
which are often necessary for severe depression, have mixed outcomes and guidelines (Gabriel et
al., 2020). Some studies suggest that psilocybin may offer additional benefits from contemporary
antidepressants because of its complex mechanism of action, among other factors (Carhart-Harris
et al., 2021). Therefore, more rigorous studies can help provide new options for treatment,
especially for individuals resistant to the commonly used antidepressants.
Goodwin et al. (2022) compared different doses of psilocybin for treatment-resistant
depressive episodes. They found that higher doses than commonly advocated, such as 25 mg,
had a significant efficacy for treatment-resistant depression (Goodwin et al., 2022). Further,
compared to common antidepressants, only a single dose was required. However, the higher
doses were related to more adverse events, especially physical ones such as dizziness, headaches,
and nausea (Goodwin et al., 2022). There were no differences between adverse psychological
effects such as suicide ideation or self-injury between the lower and higher dosage groups
(Goodwin et al., 2022). Carhart-Haris et al. (2021) also conducted an experiment that compared
the efficacy of psilocybin and escitalopram, a common antidepressant. The study found no
significant difference in the anti-depressive effects of the two substances, but secondary effects
favored psilocybin (Cahart-Harris et al., 2021). However, the results were not corrected for
multiple comparisons, and more rigorous tests are required to confirm additional benefits
(Cahart-Harris et al., 2021).
The results of this study will expand knowledge on the efficacy of psilocybin at different
dosage levels. This knowledge can allow more comparison with established antidepressants and
create use scenarios such as treatment-resistant depression episodes. This study’s specific aims,
such as identifying efficacy of different dosages, side effects at each level, and monitoring
participants, will take at least 6 weeks and can extend up to 12 weeks.
Approach
Overview: The experimental design will have three groups of 30 participants for a total of 90
participants. The participants will be recruited from outpatient clinics or online based on their
diagnosis of major depressive disorder (MDD. The inclusion criteria for this study will require
that participants meet all DSM-5 criteria for MDD and have not been treated with
antidepressants within the past month. Excluding patients who have taken antidepressants
recently will help avoid drug interactions and confounding results from past medication. This
assertion is because even short-term use of antidepressants can have long-lasting effects (Lee et
al., 2019). The exclusion criteria will also include any history of substance abuse or mental
health disorders other than MDD, such as schizophrenia or bipolar disorder. This choice is
because there is an increased risk of adverse events for people with these conditions (Gard et al.,
2021). The first group of participants will receive a low dose of psilocybin (5 mg), the second
group a medium dose (10 mg), and the third group a high dose (25 mg).
Before beginning treatment, the study will assess the baseline symptoms of depression
for each participant using the Hamilton Depression Rating Scale (HDRS). This scale measures
severity by asking questions about physical and psychological symptoms associated with
depression (Ma et al., 201). In addition, patients’ anxiety levels will also be measured using the
State-Trait Anxiety Inventory (STAI). This inventory assesses general trait anxiety and current
state anxiety (APA, 2011). Multiple tests have shown that STAI has a high internal consistency
and validity (APA, 2011). The participants’ medical histories and demographic data will also be
collected at baseline to identify potential confounding factors that may influence outcomes. Once
baseline information is collected from all participants, they will be assigned to the three
treatment groups using a random number generator
Each treatment session will last approximately 4 hours and will be monitored by trained
personnel who can provide support if needed. The participants must stay within clinical premises
for 6 hours after each session to ensure their safety and monitor their response during the peak
hours of the drug’s effect. Afterward, they will be discharged home with instructions on how to
monitor themselves over the next 24 hours until the drug clears from their system. To evaluate
the effectiveness of different dosages over time, HDRS and STAI tests will be done one-day
post-treatment and 6 weeks later at the follow-up visit. The participants will also be required to
report any adverse effects they experience daily through email. Regular visits will also be
scheduled at the participant’s convenience to measure and intervene in case of any adverse
effects between the follow up-periods.
Aim 1: To determine how different dosages affect symptom reduction over time.
Design: HDRS scores will be collected via a questionnaire administered to participants at each
assessment period. Participants’ medical histories and demographic data will also be collected
before beginning treatment to identify potential confounding factors that may influence
outcomes. Afterward, the experiment will use repeated measures ANOVA to compare the
differences in Hamilton Depression Rating Scale (HDRS) scores at baseline, 1-day posttreatment, and 6 weeks later (Lee, 2015). The results will be interpreted based on the difference
between group means. The results of the ANOVA analyses will reveal whether there is a
significant difference in symptom reduction over time between the three groups receiving
different dosages of psilocybin. If there is a significant difference, we can then look further into
which dosage was most effective in reducing symptoms of depression over time by looking at
pairwise comparisons between the groups.
Potential Challenges: Some participants may drop out before the conclusion of the study. In
cases where most of the participants that drop out are from one group, there is a risk of biased
results. To address this issue, we can conduct an intent-to-treat analysis by imputing missing
values with multiple imputation techniques or last observation carried forward methods
depending on the nature and pattern of missing values across all three assessments (McCoy,
2017).
Expected Results: We expect that higher doses of psilocybin will lead to greater symptom
reduction compared with lower doses over time as measured by HDRS scores.
Alternatives: If our results deviate from expectations, we can explore alternative approaches
such as examining longitudinal trajectories through growth curve modeling or quantifying
changes in symptoms over time through effect sizes instead of focusing solely on group means at
each assessment period (Herle et al., 2020).
Aim 2: To identify any potential adverse side effects associated with each dosage level.
Design: Adverse side effects experienced by participants after taking psilocybin treatments will
be monitored during visits scheduled before study completion. Notably, in between visits,
patients will be encouraged to report any adverse effects via email. Additional data will be
collected using self-reports during clinical visits scheduled for follow-up purposes, along with
physical examination by trained physicians who have experience working with psilocybin drug
users. The analysis will use chi-square tests for categorical variables such as the presence or
absence of symptoms such as nausea, vomiting, dizziness, or changes in visual and auditory
perception, among others (Hazra & Gogtay, 2016). Logistic regression models will also be
employed based on prior knowledge obtained from medical literature related to psilocybin use
and its effects (Schober & Vetter, 2021). The Chi-Square tests will help determine the
association between various adverse events reported by patients and their corresponding dose,
while Logistic Regression Modeling will help understand the role of covariates such as age,
gender, and comorbidities while assessing risk.
Potential Challenges: Since the chi-square test works only when expected cell counts are
greater than 5, additional simulation techniques might be needed when expected cell counts fall
below 5 (Hazra & Gogtay, 2015). Additionally, logistic regression requires a large sample size,
especially when running regressions involving multiple covariates (Schober & Vetter, 2021).
Therefore, there might be a need to use a larger sample or simulations.
Expected Results: We expect that higher doses would increase the risk and incidences of
adverse events in the participants, particularly physical ones as indicated by Goodwin et al.
(2020).
Alternatives: If our results deviate from expectations, we will use mediation models to
understand the influence of other variables such as age and gender on the study results.
Aim 3: To monitor participants’ response over time after treatment with psilocybin.
Design: The experiment will use a longitudinal study design to monitor participants’ responses
over time after treatment with psilocybin. The data collected at baseline and follow-up visits will
include HDRS scores and STAI scores, as well as any adverse effects reported by participants.
Descriptive statistics such as means, medians, and standard deviations will be used to analyze the
data. The differences in the mean HDRS score between baseline and follow-up visits in each
group will be compared using an independent samples t-test or one-way ANOVA (Mishra et al.,
2019). The same methods can be used to compare the STAI tests. The adverse effects reported
by participants will be examined using descriptive statistics such as frequency tables. Results
from the analysis of HDRS and STAI scores will indicate whether psilocybin was effective in
reducing symptoms of MDD for each dose level over time. The frequency tables of adverse
events reported by participants can provide insight into the safety profile of different doses of
psilocybin when treating depression over time.
Potential Challenges: Some participants may not complete all study visits due to a lack of
motivation or other factors, leading to incomplete data collection or biased results. The study will
include counseling sessions and offer incentives to motivate patients to complete the experiment.
Expected Results: We expect that higher doses of psilocybin will lead to greater reductions in
MDD symptoms than lower doses with an increased risk of adverse effects at higher doses
(Goodwin et al., 2020). We also anticipate that there would be fewer adverse events associated
with lower doses than with higher ones (Goodwin et al., 2020).
Alternatives: If results deviate from expectations, alternative approaches can include increasing
the sample size or altering the inclusion criteria to exclude participants who have taken
antidepressants three months before the experiment. Additionally, other psychological scales
besides HDRS and STAI could also be used during follow-up visits to provide further insight
into the effectiveness of psilocybin.
