MicroRNAs underlying the antidepressant effect of psilocybin – Establishing an nCounter pipeline for microRNA-quantification in the pig brain

MicroRNAs underlying the antidepressant effect of psilocybin – Establishing an nCounter pipeline for microRNA-quantification in the pig brain | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article MicroRNAs underlying the antidepressant effect of psilocybin – Establishing an nCounter pipeline for microRNA-quantification in the pig brain Erik Kaadt, Rolf Søkilde, Hanne Hansen, Nakul Raval, Lene Lundgaard, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3787179/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Novel treatment strategies are needed to overcome some of the current challenges related to treatment resistance and treatment latency within the psychiatric field. Recently, psilocybin has shown promise as a novel treatment of major depressive disorder. A single dose of psilocybin is associated with lasting changes in personality and mood. In parallel, various studies have indicated that microRNAs (miRNAs) are regulated after antidepressive interventions. Here, pigs were used to study the transcriptional profiles of miRNAs in the prefrontal cortex (PFC) and hippocampus (HIP), 1 day and 1 week after a single dose of psilocybin. A streamlined process was developed to adapt the Nanostring nCounter technology, specifically the Human v3b miRNA Assay panel, for compatibility with pig tissue samples. The mirmachine tool was used to select miRNAs with complete human-pig sequence conservation to make a conservative reannotation of pig microRNAs. Furthermore, different normalization strategies were employed. Utilizing this pipeline, dysregulation of 12 miRNAs in the PFC and 2 miRNAs in the HIP was ∂identified 1 day after psilocybin administration. Seven days after psilocybin administration, only 4 dysregulated miRNAs were observed in the HIP. Among the 18 identified miRNAs, 9 have previously been linked to depression. Notably, miR-212-3p and miR-107 displayed robust acute regulation across all four normalization strategies in the PFC. The two miRNAs are known to exert anti-inflammatory effects, mirroring previously reported effects of psilocybin. These results suggest that psilocybin may exert its acute and sustained molecular effects through the regulation of specific miRNAs in core brain areas of depression. Health sciences/Diseases/Psychiatric disorders/Depression Biological sciences/Neuroscience Figures Figure 1 Figure 2 Introduction The psychedelic drug, psilocybin, has recently gained interest as a promising treatment for depression and anxiety. Psilocybin treatment is particularly exciting due to its remarkable long-lasting antidepressive effects in humans, which can last up to several months following administration of a single dose 1–5 . However, the psychedelic properties remain a key challenge for its therapeutic implementation. The active metabolite of psilocybin, psilocin, is a non-selective compound which display affinity towards both the serotonin 1A receptor (5-HT 1A R), 5-HT 2A R, 5-HT 2B R, and 5-HT 2C R 6–8 , although the psychoactive effects are primarily derived from 5-HT 2A R activation 9 . In rodents, psilocybin-induced 5-HT 2A R activation is commonly observed by the characteristic head-twitch response (HTR) 10 and recently, behavioral changes in terms of headshakes, scratching, and rubbing have been demonstrated in pigs 11 . Remarkably, various 5-HT 2A R agonists, favoring different intracellular signaling cascades, exhibit distinct psychedelic and antidepressive properties 12 , indicating the possible existence of non-psychedelic intracellular mechanisms which retain antidepressive properties 12 . Furthermore, as the duration of psilocybin’s antidepressive effects greatly surpasses the psychedelic experience and the drug half-life 13 , the lasting effects are likely driven by intracellular alterations in gene expression. Previously, gene expression in pig prefrontal cortex (PFC) linked to acute (1 day) and long-lasting (1 week) effects from a single dose of psilocybin has been explored 11 . Surprisingly, only a few acutely regulated genes which reverted to baseline after 1 week were identified. Nonetheless, as the characteristic acute behavior corresponding to 5-HT 2A R-activation was observed in the pigs (headshakes, scratching, and rubbing), it suggests that certain acute alterations must be present in the brain, which might be detectable 1 day and 1 week later. We speculate that non-coding RNAs such as microRNAs (miRNAs) might reflect the underlying mechanisms. Recent evidence has demonstrated that expression of miRNAs is altered in brain and blood from depressed patients compared to healthy subjects and may play a central role in the depression etiology 14–16 . miRNAs are single-stranded regulators of gene expression, which function in a post-transcriptional manner. Once miRNAs are fully matured and loaded into the RNA-induced silencing complex (RISC), from where they exert their silencing function, they are exceptionally stable and can have half-lives of up to several days 17–19 . The greater relative stability is evident in miRNAs originating from the same primary transcripts as messenger RNAs (mRNAs), as the miRNAs accumulate to a much higher level than the co-transcribed mRNA 17–19 . Due to these properties, improved detectability of miRNA-regulation could be expected compared to gene expression studies. Furthermore, endogenous RISC-loaded miRNAs almost exclusively bind with partial complementarity to their corresponding mRNA targets 20, 21 . Employing this binding dynamic, a single miRNA can have hundreds to thousands of mRNA targets and thus have a profound effect across a large number of mRNA targets, but miniscule effect on individual mRNAs. Hence, this cumulative miRNA-induced silencing-effect might not be obvious from gene-expression studies. In the current study, we therefore investigate the PFC and hippocampal (HIP) miRNA-profiles underlying acute (1-day) and long-lasting (7-days) effects produced by a single dose of psilocybin in pigs. For this pupose, we use the relatively unbiased Nanostring nCounter technology with the human v3b chip including 827 miRNAs. A specific chip for pigs is not available, however we expect high sequence homology between humans and pigs 22, 23 . Materials and Methods Animals, treatment, behavior, and sample collection The pigs included in the study and the corresponding experimental procedures regarding drug administration, behavioral scoring, euthanization, brain dissection, and sample storage, have previously been published by Donovan et al. (2020) 11 . In summary, twenty-four adolescent female Danish slaughter pigs (Yorkshire x Duroc x Landrace) weighing 20 kg (approx. 9 weeks old) were included. The animals were housed in individual pens with enriched environment on a 12-h light/dark cycle, free access to water and weight-adjusted food twice daily. All animal experiments conformed to the European Commission's Directive 2010/63/EU and the ARRIVE guidelines. The Danish Council of Animal Ethics had approved all procedures (Journal no. 2016-15-0201-01149). A pilot dose-response study was performed in pigs to determine the relevant dose of psilocybin; a dose of 0.064mg/kg body weight was associated with a robust behavioral response and a brain 5-HT 2A R occupancy of about 65%, as determined by positron emission tomography (PET) 11 . Psilocybin (0.08 mg/kg in 5 ml saline, N = 11 and 0.064mg/kg in 5 ml saline, N = 1) or saline (5 ml, N = 12) was given intravenously through an ear catheter, as described previously 11 . One of the pigs (animal #246, Table S1 ), was used for the occupancy study and was PET scanned the same day. Following the drug administration, behavior was recorded on video and three independent observers blinded to the intervention scored the videos for presence of headshake, scratching, rubbing 11 . Due to the PET scan, behavior from animal #246 was not recorded 11 . Twelve animals (6 psilocybin and 6 saline) were euthanized 1 day after intervention while the remaining twelve pigs were euthanized after 1 week, thus creating four experimental groups each consisting of 6 animals (VEH-1-day, VEH-7-day, PSI-1-day, PSI-7-day). In the subsequent Nanostring studies, animal #246 did not exhibit any outlier characteristics (PSI-7-day). The pigs were euthanized by 15 mL pentobarbital i.v. and the brain including cerebellum and brain stem was swiftly removed, separated into hemispheres, dissected, and snap-frozen with powdered dry-ice. Brain tissue was stored at − 80°C until further use. RNA extraction RNA was extracted from PFC and HIP using the Ambion® PARISTM RNA and protein isolation kit (Ambion, TX, USA). Tissue was weighed and 20x tissue-weight disruption buffer (containing protease and phosphatase inhibitors) was added. The tissue was homogenized using the Precellys Evolution (Bertin Technologies, speed: 6800rpm, cycle: 3x 30 sec, pause: 20 sec) and RNA was extracted as described by Elfving (2022) 24 . RNA concentration and quality Total RNA concentration was measured using the Nanodrop 1000 spectrophotometer (Thermo Fischer Scientific) and the 260/280 and the 260/230 ratios were used as a measure of RNA quality. The miRNA concentration was measured using the Qubit 3.0 fluorometer (Thermo Fisher Scientific) according to the Qubit microRNA Assays Kits protocol ( https://tools.thermofisher.com/content/sfs/manuals/Qubit_microRNA_Assay_UG.pdf ). As the Qubit fluorometer display error messages for miRNA concentrations which surpass the kit-included standard curve, all samples were diluted to 250ng/uL (based on the Nanodrop measurement), prior to Qubit measurements. A sample overview, including the Qubit measurements for the diluted samples are presented in Table S1 . One sample was excluded due to low total RNA concentration (HIP, VEH-1-day, #420, 59.9 ng/µl). The Nanostring Technology The Human v3b miRNA panel (Catalog Number: CSO-MIR3-12 – Nanostring Technologies, USA) detecting 827 endogenous miRNAs was used for the nCounter assays. The panel contains 5 mRNA housekeeping genes (ACTH, B2M, GAPDH, RPL19, RPLP0) and 25 internal reference controls, including six spike-in positive controls. An overview of the nCounter Human v3 miRNA Expression Assay Transcript List is given in Table S2 . Based on prior pilot-studies performed within the department, 3µl sample with a Qubit miRNA concentration of 30 ng/µl was used for the sample preparation (MAN-C0009-08). For the Codeset Hybridization Setup (MAN-C0009-08) we used a slight surplus (5%, total 31.5µl) of the hybridization master mix (21uL), the prepared miRNA sample (5.25uL), and the Capture Probeset (5.25uL) for each reaction to circumvent potential low volumes due to evaporation during the 20 h hybridization at 65°C. Thirty µL of the hybridized samples was loaded into each lane of the Nanostring cartridge and analyzed on the nCounter SPRINT platform (Nanostring Technologies, USA). Data handling and Statistics The raw data in CSV files were imported into nSOLVER 4.0 software (Nanostring Technologies, USA). Systems Quality Control (QC) including imaging QC, binding density QC, and positive control linearity QC was performed on all samples using default settings. A positive Control Limit of Detection (LOD) QC was performed using two standard deviations (SDs) above the mean of the negative controls. No issues were detected during QC. Raw data was then exported to Microsoft Excel (Microsoft Corporation, USA). Raw expression of spike-ins positive controls and housekeeping genes were visualized using GraphPad prism 9. Raw count values were exported from Excel (as .txt file) and global raw expression for each sample was visualized using ggplot in Rstudio (v4.2.2) A background threshold was subsequently set for the raw data in Excel (average of negative controls + 2 SDs) and used as LOD. Initially, a positive control normalization was performed in nSOLVER, using the geometric mean of all positive controls except for the control named F, as per the manufacturer’s recommendation. Since different normalization strategies may influence the results and this was the first time we used the Nanostring technology for miRNA profiling in pig brain tissue, we explored different normalization strategies. Our input RNA amount was aligned according to the miRNA concentrations (Qubit), which favor the nSolver-recommended Top100 normalization and not the housekeeping genes. Normalization for all presented data was therefore performed using the Top100 function in nSolver. However, we also aimed to validate the significantly regulated miRNAs using the chip-included housekeeping genes, the Limma package, and DEseq2. Limma: For the analysis of differentially expressed microRNAs with Limma, an expression level cutoff was applied (> 30 counts in more than 10 samples). The Limma voom normalization was applied on the count matrix with the normalize.method = "scale". We tested for differentially expressed microRNAs with the lmFit, contrast.fit, and eBayes functions before reporting the differentially expressed microRNAs with toptable. DEseq2: The raw miRNA counts were used as input for differential expression analysis via the R Bioconductor package DEseq2 25 . The analysis employed a model design to test for differences between PSI-1-day versus VEH and PSI-7-day versus VEH (design = ~ 0 + group). The PFC and HIP samples were analyzed separately. Ratio data (log2 ratios and p values) between groups (PSI-1-day versus VEH and PSI-7-day versus VEH) for positive control and Top100 normalized data was exported from nSolver to Excel. In Excel, ratio data was filtered for miRNAs above LOD. Then a second filtration was performed using mirmachine to select miRNAs with 100% conservation between pigs and humans. From the supplementary tables of the publication by Umu et al. (2023) 26 , we made a custom script in R to map the nanostring probes to the mirmachine annotated microRNAs. We selected a conservative mapping with full complementarity of the human probe target to pig. The filtered data was visualized in volcano plots using ggplot in Rstudio (v4.2.2). Statistically significantly regulated miRNAs (p < 0.05) were selected for subsequent one-way ANOVA analysis in GraphPad Prism 9. ANOVA analysis: The miRNAs were checked for extreme outliers using the ROUT test (Q = 1%), (no outliers were detected) and for normality using the Shapiro-Wilks test. For normally distributed results, an ordinary one-way ANOVA was used followed by the Tukey’s multiple comparison test. In cases where results did not pass normality, a nonparametric ANOVA test was used (Kruskal-Wallis test followed by Dunn’s multiple comparisons test). Results Nanostring pipeline, data analysis approach, and data quality miRNA expression in the pig brain samples were analyzed using the Human v3b miRNA Assay panel from Nanostring. No specific panels for pigs currently exist, however, we do expect high sequence homology between the species. We used mirmachine to filter the data for miRNAs with 100% sequence conservation between species to account for potential unspecific probe-binding. Using this approach, we detected seventy-nine miRNAs in the PFC and 49 in the HIP above LOD with identical human-pig sequences. The samples were run on four individual chips. PFC samples on chip 1 and 2, Hip samples on chip 3 and 4, respectively. As normalization methods deal with trade-offs between bias that needs correction and bias that may be introduced by the normalization, we initially evaluated variation in the raw data by plotting the spike-in positive controls (Figure S1 A and Figure S2 A), the global expression of all probes in each sample (Figure S1 B and Figure S2 B), and the expression of three of the five chip-included housekeeping genes (B2M. GAPDH, RPL19, ACTB, RPLP0) above LOD (Figure S1 C and Figure S2 C) in the PFC and HIP samples, respectively. We observed low global variation between PFC samples (Figure S1 B). However, two samples (Chip2_4 and Chip2_12) exhibited reduced expression in both the global and spike-in levels (Figure S1 red and orange arrows and dots). Chip2_4 furthermore displayed reduced housekeeping gene levels (Figure S1 C). This is likely a result of reduced loading volume and was corrected by the positive control normalization. We also observed slightly reduced spike-in control counts for another sample (Chip1_12) (Figure S1 yellow arrows and dots), however, this was not translated into housekeeping gene or global expression. Conversely, we observed systematic chip-variation between HIP samples (Figure S2 B) as count-values for all samples on chip4 were significantly higher compared to chip3. This chip variation was also partly observed in the spike-in controls (Figure S2 A) but not adequately represented in the housekeeping genes (Figure S2 C). The top100 normalization would therefore account for the chip variation, while a housekeeping gene normalization likely would not. Nonetheless, the positive control normalization partly corrects this chip variation (Figure S3 ). Overall, this further supports the use of the top100 normalization over housekeeping normalization for our data. Lastly, after nSolver normalization, the evaluation process was iterated according to Bhattacharya et. al (2021) 27 . Two PFC VEH outlier-samples were removed during this iteration, prior to data analysis due to generalized disruptive effects across a very large number of probes (Figure S4 ). Following the outlier exclusion, the two saline groups (VEH-1-day and VEH—7-day) exhibited very similar expression across all probes (Figure S4 A). The two saline groups were therefore pooled (VEH) to increase the power of the downstream analysis. miRNA profiles in prefrontal cortex and hippocampus Psilocybin induces significant miRNA changes 1 day after administration in the prefrontal cortex Twelve miRNAs exhibited significant regulation 1 day after the psilocybin administration in the PFC, 6 were upregulated and 6 were downregulated (Fig. 1 A - PSI-1-day vs. VEH, p values given in Table S3 ) using the Top100 normalization. Using the three other normalization procedures, six overlapping dysregulated miRNAs were identified using the housekeeping gene normalization, five dysregulated miRNAs were identified using Limma, and eight dysregulated miRNAs were identified with DEseq2, respectively (Table 1). Two miRNAs were significantly regulated across all four normalization methods, miR-212-3p was upregulated and miR-107 was downregulated, respectively (Table 1). Comparison of PSI-7-day and VEH resulted in no regulated miRNAs (Fig. 1 A - PSI-7-day vs. VEH). Thus, none of the 12 miRNAs maintained significant regulation after 7 days. We subsequently performed ANOVA analysis on the 12 miRNAs across the 3 groups to explore the overall expression-patterns (Fig. 1 B, p values given in Table S3 ). All miRNAs except miR-128 and miR-98-5p remained significant in the ANOVA analysis (PSI-1-day vs VEH, Table S3 ), although miR-98-5p was significant between PSI-1-day and PSI-7-day (p = 0.0372). A general pattern was observed across the three groups (VEH, PSI-1-day, and PSI-7-day), as miRNAs measured at PSI-7-day exhibited expression levels either equivalent to the VEH group or intermediate between the VEH group and the PSI-1-day group. This pattern was observed for both upregulated and downregulated miRNAs, with the only exception being miR-98-5p (Fig. 1 B). As not all miRNAs had reverted entirely to baseline levels after 7 days (miR-212-3p, miR-145-5p, and miR-423-3p) it could indicate that some miRNAs have more prolonged effects than others. Lastly, we identified five miRNAs which showed significant regulation after 1 day, but were excluded by mirmachine (miR-302d-3p, miR-548ar-5p, miR-3144-3p, miR-4286, miR-4443) (shown in Figure S5 , p values given in Table S3 ). All, except miR-548ar-5p, maintained significance in the ANOVA analysis, although miR-548ar-5p was significant between PSI-1-day and PSI-7-day. All five miRNAs exhibited the same expression pattern as the other miRNAs. Psilocybin induces significant miRNA changes both 1 day and 7 days after administration in the hippocampus In the HIP, miR-92a-3p and miR-485-3p were downregulated 1 day after psilocybin administration, whereas miR-99b-5p, miR-125a-5p, miR-127-3p, and miR-221-3p were downregulated 7 days after psilocybin administration using the Top-100 normalization (Fig. 2 A – PSI-1-day vs VEH & PSI-7-day vs VEH, p values given in Table S3 ). miR-92a-3p and miR-485-3p could be validated using Limma and there was a tendency when using DEseq2 (p = 0.064 and 0.079, respectively (Table 2)). Using Limma, miR-221-3p was significant on PSI-1-day but not on PSI-7-day and miR-127-3p could be validated by housekeeping gene normalization (Table 2). In the subsequent ANOVA test, only miR-221-3p remained significant (Fig. 2 B and Table S3 ), although miR-92a-3p, miR-485-3p, and miR-125a-5p remained nearly significant (Fig. 2 B and Table S3 ). miR-92a-3p, miR-485-3p, and miR-221-3p followed the same general pattern observed in the PFC between VEH, PSI-1-day, and PSI-7-day (Fig. 2 B). Finally, four miRNAs (miR-328-3p, miR-409-3p, miR-598-3p, miR-607) displaying significant regulation 7 days after administration were excluded by mirmachine (PSI-7-day vs VEH, p-values presented in Table S3 ). None of them were significant in the ANOVA test (graphs not shown). Discussion In the current study, we explored the use of the Nanostring nCounter technology and the predefined Human v3b miRNA Assay panel to identify dysregulated miRNAs in the pig brain, in response to a single psychedelic dose of psilocybin. To our knowledge this has not previously been done. We report miRNA-alterations related to acute (PSI-1-day) and prolonged (PSI-7-day) effects of psilocybin in the PFC and HIP of pigs. In total, across the PFC and HIP, we identified 14 and 4 dysregulated miRNAs out of 827 miRNAs in after 1 day and 1 week, respectively. Generally, we observed greater miRNA-response to psilocybin in the PFC than in the HIP. A possible explanation might be the 5-HT 2A R distribution in the brain, as the 5-HT 2A R display high densities in the cerebral cortex whereas the densities in the HIP are very low 28 . The miRNA-regulation observed after 1 day in the PFC generally reverted to baseline levels after one week. On the contrary, we observed the largest regulation in the HIP after 1 week. It can be speculated that this may be caused by psilocybin-induced modifications in the PFC, which stimulate 5-HT 2A R-independent mechanisms in the HIP in a delayed manner. Nine of the 18 miRNAs identified in our study have previously been associated with depression miR-92a-3p, miR-98-5p, miR-99b-3p, miR-107, miR-125a-5p, miR-128-3p, miR-212-3p, miR-221-3p, and miR-485-3p have been identified as dysregulated in brain tissue or blood from rodent models of depression and depressed patients 29, 30 (summarized in Table S4 ). Interestingly, miR-107 and miR-212-3p, which were found differentially regulated in PFC using all 4 normalization methods, were two of the nine miRNAs. miR-212-3p is upregulated 1 day after psilocybin administration in PFC miR-212-3p has previously been linked to treatment of depression. In rats subjected to electroconvulsive stimulation, the animal model equivalent to electroconvulsive therapy, regulation of 6 miRNAs in the HIP has been reported, among them upregulation of miR-212-3p 31 . The 5p transcript (miR-212-5p) has also multiple times in the literature been linked to depression. According to the sequencing density in miRCarta and miRbase, miR-212-3p appear to be the high-abundance/guide strand in humans (Figure S6 ). Therefore, miR-212-5p has not previously been annotated, and thus, not included in the Nanostring v3b panel by the manufacturer. Hence, miR-212-5p could not be quantified in the pigs. In depressed patients, miR-212 has been reported to be elevated in serum after treatment with selective serotonin re-uptake inhibitors (SSRIs) and serotonin and norepinephrine re-uptake inhibitors. It is unclear whether it was the 3p or the 5p strand, that was investigated 32 . To further explore the possible link between depression and miR-212, the antidepressive potential of miR-212 was investigated in a chronic unpredictable mild stress (CUMS) mouse model of depression (Si et al. (2021 33 )). Although not stated explicitly, it was indicated that miR-212-5p was the focus of the study. The CUMS mice exhibited various depressive-like behaviours, determined by body weight, sucrose preference test, forced swimming test, and tail suspension test which all could be ameliorated by either fluoxetine or over-expression of miR-212-5p in the HIP 33 . In addition, it was demonstrated with Targetscan predictions and in luciferase assays, that miR-212-5p targets and downregulates nuclear factor IA (NFIA) and that the antidepressive-like effects mediated by miR-212-5p were abolished when combined with NFIA over-expression 33 . NFIA regulation may thus be a necessary mechanism underlying the antidepressant-like effects of miR-212 - 5p. In the context of bladder cancer, it has been demonstrated with Targetscan predictions and luciferase assays that miR-212-3p also targets NFIA 34 , thus demonstrating that both miR-212-5p and miR-212-3p targets NFIA and may act through similar antidepressive molecular mechanisms. Interestingly, in a study by Si et al. (2021), the depressive-like CUMS mice already exhibited elevated miR-212-5p levels in blood and HIP, but the antidepressant like effects were achieved through further over-expression of miR-212-5p 33 . This indicate that upregulation of miR-212-5p might be a protective compensatory mechanism in CUMS mice, rather than a pathological mechanism that needs to be corrected. In support of this assumption, Si et al. (2021) provided evidence for neuroprotective and anti-inflammatory (reduced Tumor necrosis factor-alpha (TNF-α), Interleukin-1 beta, and Interleukin-6 levels) effects using miR-212-5p mimics in the CUMS mice 33 . Similarly, psilocybin has been reported to acutely decrease TNF-α levels in blood from healthy subjects, as TNF-α was reverted to baseline levels, one week after psilocybin administration 35 . This timeline is comparable to the duration of the miR-212-3p regulation observed in the pigs in our study – upregulated after 1 day, normalized after 7 days. In addition, it has been reported that psilocybin decreased TNF-α levels in human U937 macrophage cells 36 . This could indicate that part of the underlying antidepressive mechanism of psilocybin is to acutely induce neuroprotective and anti-inflammatory effect through expression of miR-212 which acts on NFIA, which in turn regulate TNF-α levels. These results align with prior RNAseq studies performed on the same pigs, which demonstrated that the vast majority of regulated pathways, were immune-related 11 . Lastly, miR-212 has also been observed down-regulated in monocytes from patients with post-partem psychosis (generally thought to belong to the bipolar spectrum) 37 and downregulated in post-mortem tissue from patients with bipolar disorder 38 . miR-107 is downregulated 1 day after psilocybin administration in PFC miR-107 and miR-103-3p are sequence homologs and likely exhibit the same biological functions (Auwera 39 and miRbase.org). Upregulation of miR-107 has been observed in whole blood from manic bipolar patients compared to healthy controls 40 . On the contrary downregulation of both miR-107 and miR-103 has been reported in plasma from psychiatric patients with childhood trauma 39 , which is one of the best predictors of depression later in life 41 . Transforming growth factor beta receptor 3 (TGFBR3) was identified as a target for both miRNAs 39 . In parallel, SNPs which associated with response to antidepressive treatment in a pool of 575 depressed patients were reported 42 . The rs12082710 genotype (SNP within the TGFBR3 gene) achieved the best association and from a total of 14 identified SNPs which associated with antidepressive treatment outcome, 9 were located within TGFBR3 42 . TGFBR3 encode betaglycan, a co-receptor mediating functional antagonism of activin signalling. Hence, it has been demonstrated that injection of Activin A into the mouse HIP provides an antidepressant-like effect 42 . In resemblance with NFIA, Activin has been shown to provide neuroprotective and neuroplastic effects 43 . While the precise nature of the relationship between the pathophysiology of depression and neuroplasticity is complex, it is generally accepted that antidepressants also interfere with neurotrophic factors which modulate neuroprotective and neuroplastic effects 44–48 . It is therefore indicated that miR-107 and its target TGFBR3 might play a key role in depression and antidepressant treatment. However, this might be an oversimplification as our data showed downregulation of miR-107 in the pigs 1 day after psilocybin treatment, which indicate upregulation of TGFBR3, which provide functional antagonism to the antidepressant effects of activin. However, according to Targetscan, miR-107 has 907 conserved target sites across 825 transcripts and might therefore exhibit an array of different functions. In support of this statement, it has been demonstrated that gastrodin ameliorates the neuroinflammatory effects induced by lipopolysaccharide in mice, and that the functional mechanism rely on gastrodin-induced downregulation of miR-107 (overexpression of miR-107 abolish the anti-inflammatory effects of gastrodin) 49 . The observed downregulation of miR-107 in the pigs might thus indicate anti-inflammatory effects in resemblance with the effect of miR-212 overexpression 33 . Overall, it seems that miR-107 upregulation can provide antidepressant effects through reduced TGFBR3-mediated activin antagonism, while miR-107 downregulation can play into the gastrodin pathway causing anti-inflammatory effects. This dualistic effect might explain the diverging observations in psychiatric patients with childhood trauma 39 and bipolar patients 40 . Nonetheless, the observations in patients were based on peripheral blood samples, which might not correlate with regulations in the brain. miR-98-5p and miR-128-3p are downregulated 1 day after psilocybin in PFC It has previously been reported, that among 25 regulated miRNAs, miR-128-3p was upregulated in the amygdala from the learned helplessness rat model of depression 50 . Prediction target analysis revealed genes within the Wnt signalling pathway as miR-128-3p targets, and significantly reduced Wnt signalling genes in the amygdala of the depressive-like rats was observed 50 . In parallel, elevated miR-128-3p levels and decreased Wnt signalling genes (WNT5B, DVL, and LEF1) were also observed in post-mortem amygdala from depressed patients 50 . This is in line with other studies during recent years, as accumulating evidence implicate Wnt signalling in neuropsychiatric disorders, neurogenesis, and in the underlying mechanism of mood-stabilizers 51, 52 . In mice subjected to chronic restraint stress (CRS) reduced levels of Wnt2 and Wnt3 in the ventral HIP have been reported 53 . Furthermore, knockdown of Wnt2 and Wnt3 led to impaired Wnt/β-catenin signalling, neurogenesis deficits, and depression-like behaviours 53 . In contrast, overexpression of Wnt2 or Wnt3 reversed depression-like behaviours in the CRS mice 53 . Lastly, treatment with the selective serotonin re-uptake inhibitors fluoxetine increased Wnt2 and Wnt3 levels in the ventral HIP and Wnt2 or Wnt3 knockdown abolished the effect of fluoxetine 53 . Overall, the results presented here, indicate that when psilocybin is given to pigs Wnt signalling is increased through decreased miR-128-3p levels which in turn might mediate antidepressive effects. In contrast to our results, it has been reported that miR-98-5p is downregulated in the PFC and HIP from mice subjected to chronic social defeat stress and that miR-98-5p overexpression alleviated the depressive-like behaviours 54 . Furthermore, 1 day after ketamine administration, miR-98-5p was elevated and miR-98-5p inhibition blocked the antidepressant effect of ketamine 54 . In our study, miR-98-5p was the only miRNA with the expression levels on day 1 and day 7 being in opposite directions, a significant regulation was observed between PSI-1-day and PSI-7-day (Fig. 1 B). Thus, it can be speculated that there is a time-delayed effect of psilocybin on miR-98-5p, and a greater magnitude of effect might be observed by using stressed/depressive-like pigs. miR-92a-3p and miR-485-3p are downregulated 1 day after psilocybin in HIP Dysregulated miR-92a-3p has previously been linked to depression in clinical studies. It has been reported that miR-92a-3p is downregulated in the dorsolateral PFC from suicide subjects and this was inversely correlated with TNA-α levels, despite not being a direct target of miR-92a-3p 55 . In contrast, subjects with high baseline miR-92a-3p are more likely to develop post-stroke depression 56 . Preclinically, antidepressant effects has been coupled with reduced miR-92a-3p levels in the HIP of CUMS rats and inhibited by AAV-mediated over-expression of miR-92a-3p 57 . In the CUMS rats the depressive-like behaviour was ameliorated, when the rats were exposed to enriched environment (EE). EE reduced neuronal apoptosis and increased Tropomyosin receptor kinase B (TrkB) and Brain-derived neurotrophic factor (BDNF) levels in the rats, this was partially reversed by miR-92a-3p over-expression 57 . Reduction in miR-92a-3p might thus provide a neuroprotective and neurotrophic effect in resemblance with conventional antidepressants. miR-92a-3p was one among only two miRNA that was regulated (down-regulated) in the HIP of the pigs after 1 day, and it remained approximately significantly regulated in the late phase (p = 0.0509, Fig. 2 ). This could indicate that psilocybin induces a neuroprotective and neurotrophic effect through downregulation of miR-92a-3p. To further support this statement, Muñoz-Llanos et. al. reported that miR-92a-3p was elevated in the dorsal HIP of male rats exposed to 14 days of restraint stress. They also reported that miR-485-5p (although not miR-485-3p) was upregulated in the HIP of the restraint stress rats 30 . In silico analysis revealed that miR-92a-3p and miR-485-5p share many biological functions 30 . miR-485-5p was expressed below LOD in the HIP of the pigs and could thus not be reliably detected. Conversely, miR-485-3p has been reported upregulated in peripheral blood mononuclear cells (PBMCs) of depressed patients after 8 weeks of administration of various antidepressants (week 0 versus week 8) 58 . However, regulation in peripheral blood might not reflect changes in the HIP and the use of various antidepressants in the study, might not exert the same regulatory effects as psilocybin. miR-99b-5p, miR-125a-5p, and miR-221-3p are downregulated 7 days after psilocybin in HIP As none of the three miRNAs were regulated after 1 day (Fig. 2 A), this could suggest the presence of distinct antidepressant regulatory mechanisms operating at different time points following psilocybin treatment. Previously, miR-99b-3p (but not the guide strand - miR-99b-5p) has been reported upregulated in post-mortem brains of suicide subjects 59 and plasma miR-99b (strand not specified, but we assume detection of guide – miR-99b-5p) is downregulated after twelve weeks of escitalopram treatment in depressed individuals 60 . Similarly, miR-221-3p is upregulated in serum from depressed subjects 61 and miR-125a-5p has been reported to be upregulated in plasma and cerebrospinal spinal fluid from depressed individuals 62, 63 . Likewise, miR-125a-5p was upregulated in PFC of mice subjected to acute and repeated stress 64 , but downregulated in the HIP of CUMS rats 65 . Thus, the psilocybin-induced downregulation of miR-99b-5p, miR-125a-5p, and miR-221-3p appear to counteract the general upregulations observed in depressed patients and depressive-like animals. Using lentiviral plasmid overexpression of miR-221-3p in HA1800 cells, it has been demonstrated that miR-221-3p target and downregulate interferon regulatory factor 2 (IRF2), a negative regulator of interferon-alpha (IFN-α) 61 . IFN-α is a cytokine closely associated with depression 66 and it is thus suggested that the psilocybin-induced downregulation of miR-221-3p lead to reduced inflammation by downregulating IFN-α through upregulation of IRF2. In conclusion, we have demonstrated that the Nanostring nCounter technology and the predefined Human v3b miRNA Assay panel can be used to explore the miRNA landscape in pig brain tissue. Further, we present evidence that psilocybin may exert its intracellular antidepressant effects through miRNA mechanisms. miR-92a-3p, miR-98-5p, miR-99b-5p, miR-107, miR-125a-5p, miR-128-3p, miR-212-3p, and miR-221-3p have been identified as specific miRNA targets. Previously, these miRNAs have been proven to exhibit antidepressant potential in animal models of depression, however, none of them have been associated with psychedelic effects. The combined effect of these miRNAs might therefore exert the antidepressant potential of psilocybin without aversive psychedelic effects. Further studies are needed to elucidate both the acute and prolonged effect of the psilocybin regulated miRNAs and their downstream targets. Declarations Acknowledgement We acknowledge Tania Aaquist Ammitzbøll for helping with the RNA extractions. The study has been funded by Simon Fougner Hartmanns Fond (BE) and the Novo Nordisk Foundation (grant number NNF20SA0061466) as a part of ODIN toward the project BioPsych (Identification of BIO markers in the human PSYCH iatric brain – focusing on non-coding RNAs and sex differences) (BE). Conflict of interest GMK served as speaker for AbbVie, Angelini, Cybin, H. Lundbeck and Sage Biogen an advisor for Sanos, Onsero, Pangea Botanica, Gilgamesh, AbbVie, PureTechnologies, a research site for Reunion and Delix Therapeutics. Supplementary information is available at MP’s website. References Carhart-Harris RL, Bolstridge M, Day CMJ, Rucker J, Watts R, Erritzoe DE et al. Psilocybin with psychological support for treatment-resistant depression: six-month follow-up. Psychopharmacology (Berl) 2018; 235 (2) : 399-408. 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Antidepressant Pretreatment for the Prevention of Interferon Alfa–Associated Depression: A Systematic Review and Meta-Analysis. Psychosomatics 2014; 55 (3) : 221-234. Tables Table 1 and 2 are available in the Supplementary Files section. Additional Declarations Gitte Mood Knudsen served as speaker for AbbVie, Angelini, Cybin, H. Lundbeck and Sage Biogen an advisor for Sanos, Onsero, Pangea Botanica, Gilgamesh, AbbVie, PureTechnologies, a research site for Reunion and Delix Therapeutics. Supplementary Files FigureS1.jpg Figure S1: A: Count data for positive Human v3b panel spike-in controls (POS_A – POS_F). B: Raw count values for all probes on the Human v3b panel. C: Raw count values for the three housekeeping genes (out of five included on the chip) expressed above LOD. Gray vertical line indicate transition from chip1 to chip2. Red, orange, and yellow arrows/dots indicate observed outliers. FigureS2.jpg Figure S2: A: Count data for positive Human v3b panel spike-in controls (POS_A – POS_F). Colors indicate which chip the samples were included in (Blue: Chip3, Pink: Chip4). B: Raw count values for all probes on the Human v3b panel. C: Raw count values for the three housekeeping genes (out of five included on the chip) expressed above LOD. Gray vertical line indicate transition from chip3 to chip4. FigureS3.jpg Figure S3: Count values for all probes on the Human v3b panel after positive control normalization. FigureS4.jpg Figure S4: A: Brown graphs: Two samples (red dots) consistently present as outliers in the VEH-7-day group across multiple miRNAs. As a result, VEH-7-day become systematically affected. Green graphs: Excluding the two outlier samples result in very uniform expression between the two saline groups (VEH-1-day and VEH-7-day). B: Heatmap analysis across all 827 miRNA reveal that the two outlier samples (the two VEH-7-day samples on the right) exhibit markedly different expression than all other samples across all 827 miRNA-probes. FigureS5.jpg Figure S5: Count values normalized to percent of VEH. *p<0.05 PSI-1-day vs. VEH, # p<0.05 PSI-7-day vs. VEH. N=10, 6, and 6, in the VEH, PSI-1-day, and PSI-7-day group, respectively. FigureS6.jpg Figure S6: Fold and read density from miRCarta of mir-212. TableS1.xlsx Table S1: Initial Nanodrop (ND) concentrations and quality control (QC) ratios are included. In addition, the Qubit concentrations of the diluted samples (diluted to 250ng/uL ND concentration) are presented. TableS2.xlsx Table S2: Table acquired from Nanostring website. *miRNA species identified with an asterisk in the column "Target Note" are targeted by a non-unique probe. All species targeted by the same probe share the same number after the asterisk. TableS3.xlsx Table S3: Bold lines indicate separation between included and mirmachine excluded miRNAs. Black, underlined, pvals indicate the significant ratio presented in the volcano plots (Figure 1 and 2). TableS4.xlsx Table S4: Summary from the Ding et. al. paper and the Muñoz-Llanos et al. paper of the 8 miRNAs (out of 18), which have previously been linked to depression. Table1.xlsx Table 1: The Top100 approach was used to identify dysregulated miRNAs and Limma, Housekeeping, and DEseq2, were used to validate the Top100-identified miRNAs. All Top100 normalized pvals are presented in Table S3. 1Was only sigificant in the ANOVA test between PSI-day and PSI-7day. Table2.xlsx Table 2: The Top100 approach was used to identify regulated miRNAs and Limma, Housekeeping, and DEseq2, were used to validate the Top100-identified miRNAs. All Top100 normalized p values are presented in Table S3. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3787179","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":266349921,"identity":"865e7741-3eb5-4d18-b79e-99d99d7c15b4","order_by":0,"name":"Erik Kaadt","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIie3RMQrCMBSA4RcKdUnt2iLUK0ScHNSrPCk4uztYyFo66y0KgnMlEJceoIKgIjjH3cFYHZzSjg75l4TAR/IIgM32lxEOUOi1cAq4sM9ZmLQi0kXAdgScL6EMEFoQvyc4g3LS757Th8LFCfw1kuPaQMJsxhGqeLCR3jZAdoegQmeUGwgrCS9AOSSX3k7PIgAqdMOLgUw/ZDXNJb3XpN9EGCXvh4mZJm5N2JuYHhboWxiWh3gj50M9i6CD8spHpvH9tHMLlFyOMyGuSj1FFB3i/TE1kDr82VP9uUkTsNlsNltDL+YsUyrorsZaAAAAAElFTkSuQmCC","orcid":"","institution":"Aarhus University","correspondingAuthor":true,"prefix":"","firstName":"Erik","middleName":"","lastName":"Kaadt","suffix":""},{"id":266349922,"identity":"9076e5a1-f05d-49bd-ac80-f631b3564b50","order_by":1,"name":"Rolf Søkilde","email":"","orcid":"","institution":"Aarhus University","correspondingAuthor":false,"prefix":"","firstName":"Rolf","middleName":"","lastName":"Søkilde","suffix":""},{"id":266349923,"identity":"be236778-a1d3-458a-b4cd-713f42eb5891","order_by":2,"name":"Hanne Hansen","email":"","orcid":"https://orcid.org/0000-0001-5564-7627","institution":"Copenhagen University Hospital, Rigshospitalet","correspondingAuthor":false,"prefix":"","firstName":"Hanne","middleName":"","lastName":"Hansen","suffix":""},{"id":266349924,"identity":"50070608-ce4e-4d86-833a-c7b864e6edf5","order_by":3,"name":"Nakul Raval","email":"","orcid":"https://orcid.org/0000-0001-5637-7219","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Nakul","middleName":"","lastName":"Raval","suffix":""},{"id":266349925,"identity":"d77692d2-08d9-42a1-94e2-eb0245ccaa35","order_by":4,"name":"Lene Lundgaard","email":"","orcid":"","institution":"Copenhagen University Hospital, Rigshospitalet","correspondingAuthor":false,"prefix":"","firstName":"Lene","middleName":"","lastName":"Lundgaard","suffix":""},{"id":266349926,"identity":"b074ccb0-6df3-488e-81ce-b1631122663e","order_by":5,"name":"Jesper Just","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jesper","middleName":"","lastName":"Just","suffix":""},{"id":266349927,"identity":"f9e9120b-37f0-45ac-acc4-b32d92149bc3","order_by":6,"name":"Gitte Knudsen","email":"","orcid":"https://orcid.org/0000-0003-1508-6866","institution":"University Hospital Rigshospitalet","correspondingAuthor":false,"prefix":"","firstName":"Gitte","middleName":"","lastName":"Knudsen","suffix":""},{"id":266349928,"identity":"3c3849e7-740c-494a-b764-0757662dbfde","order_by":7,"name":"Betina Elfving","email":"","orcid":"https://orcid.org/0000-0001-6939-5088","institution":"Translational Neuropsychiatry Unit","correspondingAuthor":false,"prefix":"","firstName":"Betina","middleName":"","lastName":"Elfving","suffix":""}],"badges":[],"createdAt":"2023-12-21 13:30:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3787179/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3787179/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49520666,"identity":"50256af5-0bd1-407a-b6ae-a67aa63d9b2a","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1032831,"visible":true,"origin":"","legend":"\u003cp\u003eA: Volcano plot presenting miRNAs regulated 1 day (PSI-1-day vs. VEH) and 1 week (PSI-7-day vs. VEH) after psilocybin administration. Grey lines indicate pval = 0.05. B: Comparison of all three groups (VEH, PSI-1-day, and PSI-7-day) for dysregulated miRNAs. Count values are presented as percent of VEH. 1-way ANOVA *p\u0026lt;0.05, ** p\u0026lt;0.01 PSI-1-day vs. VEH, # p\u0026lt;0.05 PSI-7-day vs. VEH. N=10, 6, and 6, in the VEH, PSI-1-day, and PSI-7-day group, respectively.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/f410638324156c5e826f5816.jpg"},{"id":49520667,"identity":"bcb8f8a4-c9cb-4557-ae58-61bf69054f1f","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":943811,"visible":true,"origin":"","legend":"\u003cp\u003eA: Volcano plot presenting miRNAs regulated 1 day (PSI-1-day vs. VEH) and 1 week (PSI-7-day vs. VEH) after psilocybin administration. Grey lines indicate pval = 0.05. B: Count values, normalized to percent of VEH. 1-way ANOVA \u0026amp;p\u0026lt;0.05 PSI-7-day vs. VEH. Pvals for miR-92a-3p (PSI-1-day vs. VEH), miR-125a-5p (PSI-7-day vs. VEH), and miR-485-3p (PSI-1-day vs. VEH), are noted on graph. N=11, 6, 6, in the VEH, PSI-1-day, and PSI-7-day group, respectively.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/c4f3d06272c96319b3814d45.jpg"},{"id":85878115,"identity":"cd9afe76-c405-4bb7-9b4c-e0b20e3a75c9","added_by":"auto","created_at":"2025-07-02 15:35:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3129592,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/7d4fbda4-39a0-4b64-992b-4e4ee619d61b.pdf"},{"id":49521094,"identity":"0bc5ef97-3f0e-4ffc-a08e-9a72006b96ad","added_by":"auto","created_at":"2024-01-12 09:59:19","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2240157,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S1: A: Count data for positive Human v3b panel spike-in controls (POS_A – POS_F). B: Raw count values for all probes on the Human v3b panel. C: Raw count values for the three housekeeping genes (out of five included on the chip) expressed above LOD. Gray vertical line indicate transition from chip1 to chip2. Red, orange, and yellow arrows/dots indicate observed outliers.\u003c/p\u003e","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/d316c53acee6fea9d2b70b97.jpg"},{"id":49520680,"identity":"380d45e0-93f8-4693-9e7e-4f3fdb375470","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3419312,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S2: A: Count data for positive Human v3b panel spike-in controls (POS_A – POS_F). Colors indicate which chip the samples were included in (Blue: Chip3, Pink: Chip4). B: Raw count values for all probes on the Human v3b panel. C: Raw count values for the three housekeeping genes (out of five included on the chip) expressed above LOD. Gray vertical line indicate transition from chip3 to chip4.\u003c/p\u003e","description":"","filename":"FigureS2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/e98fafebc3cbac93b5aba9e0.jpg"},{"id":49521095,"identity":"7a0f45b9-8d9b-4fde-b162-1428b6530607","added_by":"auto","created_at":"2024-01-12 09:59:19","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1294183,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S3: Count values for all probes on the Human v3b panel after positive control normalization.\u003c/p\u003e","description":"","filename":"FigureS3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/2476485a26926410bbb03076.jpg"},{"id":49520677,"identity":"6f046cda-fdcf-41f9-b036-dd083d7cdc15","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":3883128,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S4: A: Brown graphs: Two samples (red dots) consistently present as outliers in the VEH-7-day group across multiple miRNAs. As a result, VEH-7-day become systematically affected. Green graphs: Excluding the two outlier samples result in very uniform expression between the two saline groups (VEH-1-day and VEH-7-day). B: Heatmap analysis across all 827 miRNA reveal that the two outlier samples (the two VEH-7-day samples on the right) exhibit markedly different expression than all other samples across all 827 miRNA-probes.\u003c/p\u003e","description":"","filename":"FigureS4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/8c1597de27ead163c2ad8d9b.jpg"},{"id":49520674,"identity":"e26b6355-c42e-4338-ad9a-cd92b1fb8854","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1452456,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S5: Count values normalized to percent of VEH. *p\u0026lt;0.05 PSI-1-day vs. VEH, # p\u0026lt;0.05 PSI-7-day vs. VEH. N=10, 6, and 6, in the VEH, PSI-1-day, and PSI-7-day group, respectively.\u003c/p\u003e","description":"","filename":"FigureS5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/43cf8ee9d6bc02cd3894e297.jpg"},{"id":49521098,"identity":"0e3fe1e7-4c7f-4714-8554-117f854bc12c","added_by":"auto","created_at":"2024-01-12 09:59:19","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1094658,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S6: Fold and read density from miRCarta of mir-212.\u003c/p\u003e","description":"","filename":"FigureS6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/e084152c6fcbc8583a9ee518.jpg"},{"id":49520669,"identity":"ffbed6a2-56ba-48c4-97a4-f67e6687f282","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":12695,"visible":true,"origin":"","legend":"\u003cp\u003eTable S1: Initial Nanodrop (ND) concentrations and quality control (QC) ratios are included. In addition, the Qubit concentrations of the diluted samples (diluted to 250ng/uL ND concentration) are presented.\u003c/p\u003e","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/890f704c81a4591ac4c8e946.xlsx"},{"id":49520670,"identity":"0e513544-29a5-415a-b1a6-8d0f6d95c6df","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":86278,"visible":true,"origin":"","legend":"\u003cp\u003eTable S2: Table acquired from Nanostring website. *miRNA species identified with an asterisk in the column \"Target Note\" are targeted by a non-unique probe. All species targeted by the same probe share the same number after the asterisk.\u003c/p\u003e","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/fb28f265f910eeb7f7df8d41.xlsx"},{"id":49520672,"identity":"311bb605-aefe-4a32-9ed2-690c59dfd8f0","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":13160,"visible":true,"origin":"","legend":"\u003cp\u003eTable S3: Bold lines indicate separation between included and mirmachine excluded miRNAs. Black, underlined, pvals indicate the significant ratio presented in the volcano plots (Figure 1 and 2).\u003c/p\u003e","description":"","filename":"TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/b3f32b479a16bf51aa911dde.xlsx"},{"id":49520675,"identity":"d4996dcb-cd03-4403-833b-1ab916ed87a5","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":11549,"visible":true,"origin":"","legend":"\u003cp\u003eTable S4: Summary from the Ding et. al. paper and the Muñoz-Llanos et al. paper of the 8 miRNAs (out of 18), which have previously been linked to depression.\u003c/p\u003e","description":"","filename":"TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/d57f6a92327305591907c510.xlsx"},{"id":49520678,"identity":"1eee1c68-f911-42d0-bac9-42264412293a","added_by":"auto","created_at":"2024-01-12 09:51:19","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":10179,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1: The Top100 approach was used to identify dysregulated miRNAs and Limma, Housekeeping, and DEseq2, were used to validate the Top100-identified miRNAs. All Top100 normalized pvals are presented in Table S3. 1Was only sigificant in the ANOVA test between PSI-day and PSI-7day.\u003c/p\u003e","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/2643d3e5664195699dc97e26.xlsx"},{"id":49521099,"identity":"d671a67d-a4e7-4517-aafc-c3704fc5b6fb","added_by":"auto","created_at":"2024-01-12 09:59:19","extension":"xlsx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":10061,"visible":true,"origin":"","legend":"\u003cp\u003eTable 2: The Top100 approach was used to identify regulated miRNAs and Limma, Housekeeping, and DEseq2, were used to validate the Top100-identified miRNAs. All Top100 normalized p values are presented in Table S3.\u003c/p\u003e","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3787179/v1/a7d9595eb18a2cde58f951e4.xlsx"}],"financialInterests":"\nGitte Mood Knudsen served as speaker for AbbVie, Angelini, Cybin, H. Lundbeck and Sage Biogen\r\nan advisor for Sanos, Onsero, Pangea Botanica, Gilgamesh, AbbVie, PureTechnologies,\r\na research site for Reunion and Delix Therapeutics.","formattedTitle":"MicroRNAs underlying the antidepressant effect of psilocybin – Establishing an nCounter pipeline for microRNA-quantification in the pig brain","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe psychedelic drug, psilocybin, has recently gained interest as a promising treatment for depression and anxiety. Psilocybin treatment is particularly exciting due to its remarkable long-lasting antidepressive effects in humans, which can last up to several months following administration of a single dose\u003csup\u003e1\u0026ndash;5\u003c/sup\u003e. However, the psychedelic properties remain a key challenge for its therapeutic implementation. The active metabolite of psilocybin, psilocin, is a non-selective compound which display affinity towards both the serotonin 1A receptor (5-HT\u003csub\u003e1A\u003c/sub\u003eR), 5-HT\u003csub\u003e2A\u003c/sub\u003eR, 5-HT\u003csub\u003e2B\u003c/sub\u003eR, and 5-HT\u003csub\u003e2C\u003c/sub\u003eR\u003csup\u003e6\u0026ndash;8\u003c/sup\u003e, although the psychoactive effects are primarily derived from 5-HT\u003csub\u003e2A\u003c/sub\u003eR activation\u003csup\u003e9\u003c/sup\u003e. In rodents, psilocybin-induced 5-HT\u003csub\u003e2A\u003c/sub\u003eR activation is commonly observed by the characteristic head-twitch response (HTR)\u003csup\u003e10\u003c/sup\u003e and recently, behavioral changes in terms of headshakes, scratching, and rubbing have been demonstrated in pigs\u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRemarkably, various 5-HT\u003csub\u003e2A\u003c/sub\u003eR agonists, favoring different intracellular signaling cascades, exhibit distinct psychedelic and antidepressive properties\u003csup\u003e12\u003c/sup\u003e, indicating the possible existence of non-psychedelic intracellular mechanisms which retain antidepressive properties\u003csup\u003e12\u003c/sup\u003e. Furthermore, as the duration of psilocybin\u0026rsquo;s antidepressive effects greatly surpasses the psychedelic experience and the drug half-life\u003csup\u003e13\u003c/sup\u003e, the lasting effects are likely driven by intracellular alterations in gene expression. Previously, gene expression in pig prefrontal cortex (PFC) linked to acute (1 day) and long-lasting (1 week) effects from a single dose of psilocybin has been explored\u003csup\u003e11\u003c/sup\u003e. Surprisingly, only a few acutely regulated genes which reverted to baseline after 1 week were identified. Nonetheless, as the characteristic acute behavior corresponding to 5-HT\u003csub\u003e2A\u003c/sub\u003eR-activation was observed in the pigs (headshakes, scratching, and rubbing), it suggests that certain acute alterations must be present in the brain, which might be detectable 1 day and 1 week later. We speculate that non-coding RNAs such as microRNAs (miRNAs) might reflect the underlying mechanisms.\u003c/p\u003e \u003cp\u003eRecent evidence has demonstrated that expression of miRNAs is altered in brain and blood from depressed patients compared to healthy subjects and may play a central role in the depression etiology\u003csup\u003e14\u0026ndash;16\u003c/sup\u003e. miRNAs are single-stranded regulators of gene expression, which function in a post-transcriptional manner. Once miRNAs are fully matured and loaded into the RNA-induced silencing complex (RISC), from where they exert their silencing function, they are exceptionally stable and can have half-lives of up to several days\u003csup\u003e17\u0026ndash;19\u003c/sup\u003e. The greater relative stability is evident in miRNAs originating from the same primary transcripts as messenger RNAs (mRNAs), as the miRNAs accumulate to a much higher level than the co-transcribed mRNA\u003csup\u003e17\u0026ndash;19\u003c/sup\u003e. Due to these properties, improved detectability of miRNA-regulation could be expected compared to gene expression studies. Furthermore, endogenous RISC-loaded miRNAs almost exclusively bind with partial complementarity to their corresponding mRNA targets\u003csup\u003e20, 21\u003c/sup\u003e. Employing this binding dynamic, a single miRNA can have hundreds to thousands of mRNA targets and thus have a profound effect across a large number of mRNA targets, but miniscule effect on individual mRNAs. Hence, this cumulative miRNA-induced silencing-effect might not be obvious from gene-expression studies.\u003c/p\u003e \u003cp\u003eIn the current study, we therefore investigate the PFC and hippocampal (HIP) miRNA-profiles underlying acute (1-day) and long-lasting (7-days) effects produced by a single dose of psilocybin in pigs. For this pupose, we use the relatively unbiased Nanostring nCounter technology with the human v3b chip including 827 miRNAs. A specific chip for pigs is not available, however we expect high sequence homology between humans and pigs\u003csup\u003e22, 23\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals, treatment, behavior, and sample collection\u003c/h2\u003e \u003cp\u003eThe pigs included in the study and the corresponding experimental procedures regarding drug administration, behavioral scoring, euthanization, brain dissection, and sample storage, have previously been published by Donovan et al. (2020)\u003csup\u003e11\u003c/sup\u003e. In summary, twenty-four adolescent female Danish slaughter pigs (Yorkshire x Duroc x Landrace) weighing 20 kg (approx. 9 weeks old) were included. The animals were housed in individual pens with enriched environment on a 12-h light/dark cycle, free access to water and weight-adjusted food twice daily. All animal experiments conformed to the European Commission's Directive 2010/63/EU and the ARRIVE guidelines. The Danish Council of Animal Ethics had approved all procedures (Journal no. 2016-15-0201-01149).\u003c/p\u003e \u003cp\u003eA pilot dose-response study was performed in pigs to determine the relevant dose of psilocybin; a dose of 0.064mg/kg body weight was associated with a robust behavioral response and a brain 5-HT\u003csub\u003e2A\u003c/sub\u003eR occupancy of about 65%, as determined by positron emission tomography (PET)\u003csup\u003e11\u003c/sup\u003e. Psilocybin (0.08 mg/kg in 5 ml saline, N\u0026thinsp;=\u0026thinsp;11 and 0.064mg/kg in 5 ml saline, N\u0026thinsp;=\u0026thinsp;1) or saline (5 ml, N\u0026thinsp;=\u0026thinsp;12) was given intravenously through an ear catheter, as described previously\u003csup\u003e11\u003c/sup\u003e. One of the pigs (animal #246, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), was used for the occupancy study and was PET scanned the same day. Following the drug administration, behavior was recorded on video and three independent observers blinded to the intervention scored the videos for presence of headshake, scratching, rubbing\u003csup\u003e11\u003c/sup\u003e. Due to the PET scan, behavior from animal #246 was not recorded\u003csup\u003e11\u003c/sup\u003e. Twelve animals (6 psilocybin and 6 saline) were euthanized 1 day after intervention while the remaining twelve pigs were euthanized after 1 week, thus creating four experimental groups each consisting of 6 animals (VEH-1-day, VEH-7-day, PSI-1-day, PSI-7-day). In the subsequent Nanostring studies, animal #246 did not exhibit any outlier characteristics (PSI-7-day). The pigs were euthanized by 15 mL pentobarbital i.v. and the brain including cerebellum and brain stem was swiftly removed, separated into hemispheres, dissected, and snap-frozen with powdered dry-ice. Brain tissue was stored at \u0026minus;\u0026thinsp;80\u0026deg;C until further use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction\u003c/h2\u003e \u003cp\u003eRNA was extracted from PFC and HIP using the Ambion\u0026reg; PARISTM RNA and protein isolation kit (Ambion, TX, USA). Tissue was weighed and 20x tissue-weight disruption buffer (containing protease and phosphatase inhibitors) was added. The tissue was homogenized using the Precellys Evolution (Bertin Technologies, speed: 6800rpm, cycle: 3x 30 sec, pause: 20 sec) and RNA was extracted as described by Elfving (2022)\u003csup\u003e24\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eRNA concentration and quality\u003c/h2\u003e \u003cp\u003eTotal RNA concentration was measured using the Nanodrop 1000 spectrophotometer (Thermo Fischer Scientific) and the 260/280 and the 260/230 ratios were used as a measure of RNA quality. The miRNA concentration was measured using the Qubit 3.0 fluorometer (Thermo Fisher Scientific) according to the Qubit microRNA Assays Kits protocol (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tools.thermofisher.com/content/sfs/manuals/Qubit_microRNA_Assay_UG.pdf\u003c/span\u003e\u003cspan address=\"https://tools.thermofisher.com/content/sfs/manuals/Qubit_microRNA_Assay_UG.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). As the Qubit fluorometer display error messages for miRNA concentrations which surpass the kit-included standard curve, all samples were diluted to 250ng/uL (based on the Nanodrop measurement), prior to Qubit measurements. A sample overview, including the Qubit measurements for the diluted samples are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. One sample was excluded due to low total RNA concentration (HIP, VEH-1-day, #420, 59.9 ng/\u0026micro;l).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eThe Nanostring Technology\u003c/h2\u003e \u003cp\u003eThe Human v3b miRNA panel (Catalog Number: CSO-MIR3-12 \u0026ndash; Nanostring Technologies, USA) detecting 827 endogenous miRNAs was used for the nCounter assays. The panel contains 5 mRNA housekeeping genes (ACTH, B2M, GAPDH, RPL19, RPLP0) and 25 internal reference controls, including six spike-in positive controls. An overview of the nCounter Human v3 miRNA Expression Assay Transcript List is given in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eBased on prior pilot-studies performed within the department, 3\u0026micro;l sample with a Qubit miRNA concentration of 30 ng/\u0026micro;l was used for the sample preparation (MAN-C0009-08). For the \u003cem\u003eCodeset Hybridization Setup\u003c/em\u003e (MAN-C0009-08) we used a slight surplus (5%, total 31.5\u0026micro;l) of the hybridization master mix (21uL), the prepared miRNA sample (5.25uL), and the Capture Probeset (5.25uL) for each reaction to circumvent potential low volumes due to evaporation during the 20 h hybridization at 65\u0026deg;C. Thirty \u0026micro;L of the hybridized samples was loaded into each lane of the Nanostring cartridge and analyzed on the nCounter SPRINT platform (Nanostring Technologies, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData handling and Statistics\u003c/h2\u003e \u003cp\u003eThe raw data in CSV files were imported into nSOLVER 4.0 software (Nanostring Technologies, USA). Systems Quality Control (QC) including imaging QC, binding density QC, and positive control linearity QC was performed on all samples using default settings. A positive Control Limit of Detection (LOD) QC was performed using two standard deviations (SDs) above the mean of the negative controls. No issues were detected during QC. Raw data was then exported to Microsoft Excel (Microsoft Corporation, USA). Raw expression of spike-ins positive controls and housekeeping genes were visualized using GraphPad prism 9. Raw count values were exported from Excel (as .txt file) and global raw expression for each sample was visualized using ggplot in Rstudio (v4.2.2)\u003c/p\u003e \u003cp\u003eA background threshold was subsequently set for the raw data in Excel (average of negative controls\u0026thinsp;+\u0026thinsp;2 SDs) and used as LOD. Initially, a positive control normalization was performed in nSOLVER, using the geometric mean of all positive controls except for the control named F, as per the manufacturer\u0026rsquo;s recommendation. Since different normalization strategies may influence the results and this was the first time we used the Nanostring technology for miRNA profiling in pig brain tissue, we explored different normalization strategies. Our input RNA amount was aligned according to the miRNA concentrations (Qubit), which favor the nSolver-recommended Top100 normalization and not the housekeeping genes. Normalization for all presented data was therefore performed using the Top100 function in nSolver. However, we also aimed to validate the significantly regulated miRNAs using the chip-included housekeeping genes, the Limma package, and DEseq2. Limma: For the analysis of differentially expressed microRNAs with Limma, an expression level cutoff was applied (\u0026gt;\u0026thinsp;30 counts in more than 10 samples). The Limma voom normalization was applied on the count matrix with the normalize.method = \"scale\". We tested for differentially expressed microRNAs with the lmFit, contrast.fit, and eBayes functions before reporting the differentially expressed microRNAs with toptable. DEseq2: The raw miRNA counts were used as input for differential expression analysis via the R Bioconductor package DEseq2\u003csup\u003e25\u003c/sup\u003e. The analysis employed a model design to test for differences between PSI-1-day versus VEH and PSI-7-day versus VEH (design\u0026thinsp;=\u0026thinsp;~\u0026thinsp;0\u0026thinsp;+\u0026thinsp;group). The PFC and HIP samples were analyzed separately.\u003c/p\u003e \u003cp\u003eRatio data (log2 ratios and p values) between groups (PSI-1-day versus VEH and PSI-7-day versus VEH) for positive control and Top100 normalized data was exported from nSolver to Excel. In Excel, ratio data was filtered for miRNAs above LOD. Then a second filtration was performed using mirmachine to select miRNAs with 100% conservation between pigs and humans. From the supplementary tables of the publication by Umu et al. (2023)\u003csup\u003e26\u003c/sup\u003e, we made a custom script in R to map the nanostring probes to the mirmachine annotated microRNAs. We selected a conservative mapping with full complementarity of the human probe target to pig. The filtered data was visualized in volcano plots using ggplot in Rstudio (v4.2.2). Statistically significantly regulated miRNAs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were selected for subsequent one-way ANOVA analysis in GraphPad Prism 9. ANOVA analysis: The miRNAs were checked for extreme outliers using the ROUT test (Q\u0026thinsp;=\u0026thinsp;1%), (no outliers were detected) and for normality using the Shapiro-Wilks test. For normally distributed results, an ordinary one-way ANOVA was used followed by the Tukey\u0026rsquo;s multiple comparison test. In cases where results did not pass normality, a nonparametric ANOVA test was used (Kruskal-Wallis test followed by Dunn\u0026rsquo;s multiple comparisons test).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eNanostring pipeline, data analysis approach, and data quality\u003c/h2\u003e \u003cp\u003emiRNA expression in the pig brain samples were analyzed using the Human v3b miRNA Assay panel from Nanostring. No specific panels for pigs currently exist, however, we do expect high sequence homology between the species. We used mirmachine to filter the data for miRNAs with 100% sequence conservation between species to account for potential unspecific probe-binding. Using this approach, we detected seventy-nine miRNAs in the PFC and 49 in the HIP above LOD with identical human-pig sequences. The samples were run on four individual chips. PFC samples on chip 1 and 2, Hip samples on chip 3 and 4, respectively. As normalization methods deal with trade-offs between bias that needs correction and bias that may be introduced by the normalization, we initially evaluated variation in the raw data by plotting the spike-in positive controls (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA and Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA), the global expression of all probes in each sample (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB and Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB), and the expression of three of the five chip-included housekeeping genes (B2M. GAPDH, RPL19, ACTB, RPLP0) above LOD (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC and Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC) in the PFC and HIP samples, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe observed low global variation between PFC samples (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB). However, two samples (Chip2_4 and Chip2_12) exhibited reduced expression in both the global and spike-in levels (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e red and orange arrows and dots). Chip2_4 furthermore displayed reduced housekeeping gene levels (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC). This is likely a result of reduced loading volume and was corrected by the positive control normalization. We also observed slightly reduced spike-in control counts for another sample (Chip1_12) (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e yellow arrows and dots), however, this was not translated into housekeeping gene or global expression.\u003c/p\u003e \u003cp\u003eConversely, we observed systematic chip-variation between HIP samples (Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB) as count-values for all samples on chip4 were significantly higher compared to chip3. This chip variation was also partly observed in the spike-in controls (Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA) but not adequately represented in the housekeeping genes (Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC). The top100 normalization would therefore account for the chip variation, while a housekeeping gene normalization likely would not. Nonetheless, the positive control normalization partly corrects this chip variation (Figure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Overall, this further supports the use of the top100 normalization over housekeeping normalization for our data.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLastly, after nSolver normalization, the evaluation process was iterated according to Bhattacharya et. al (2021)\u003csup\u003e27\u003c/sup\u003e. Two PFC VEH outlier-samples were removed during this iteration, prior to data analysis due to generalized disruptive effects across a very large number of probes (Figure \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). Following the outlier exclusion, the two saline groups (VEH-1-day and VEH\u0026mdash;7-day) exhibited very similar expression across all probes (Figure \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003eA). The two saline groups were therefore pooled (VEH) to increase the power of the downstream analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003emiRNA profiles in prefrontal cortex and hippocampus\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003ePsilocybin induces significant miRNA changes 1 day after administration in the prefrontal cortex\u003c/h2\u003e \u003cp\u003eTwelve miRNAs exhibited significant regulation 1 day after the psilocybin administration in the PFC, 6 were upregulated and 6 were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eA - PSI-1-day vs. VEH, p values given in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e) using the Top100 normalization. Using the three other normalization procedures, six overlapping dysregulated miRNAs were identified using the housekeeping gene normalization, five dysregulated miRNAs were identified using Limma, and eight dysregulated miRNAs were identified with DEseq2, respectively (Table\u0026nbsp;1). Two miRNAs were significantly regulated across all four normalization methods, miR-212-3p was upregulated and miR-107 was downregulated, respectively (Table\u0026nbsp;1). Comparison of PSI-7-day and VEH resulted in no regulated miRNAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eA - PSI-7-day vs. VEH). Thus, none of the 12 miRNAs maintained significant regulation after 7 days.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe subsequently performed ANOVA analysis on the 12 miRNAs across the 3 groups to explore the overall expression-patterns (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, p values given in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). All miRNAs except miR-128 and miR-98-5p remained significant in the ANOVA analysis (PSI-1-day vs VEH, Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e), although miR-98-5p was significant between PSI-1-day and PSI-7-day (p\u0026thinsp;=\u0026thinsp;0.0372).\u003c/p\u003e \u003cp\u003eA general pattern was observed across the three groups (VEH, PSI-1-day, and PSI-7-day), as miRNAs measured at PSI-7-day exhibited expression levels either equivalent to the VEH group or intermediate between the VEH group and the PSI-1-day group. This pattern was observed for both upregulated and downregulated miRNAs, with the only exception being miR-98-5p (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). As not all miRNAs had reverted entirely to baseline levels after 7 days (miR-212-3p, miR-145-5p, and miR-423-3p) it could indicate that some miRNAs have more prolonged effects than others.\u003c/p\u003e \u003cp\u003eLastly, we identified five miRNAs which showed significant regulation after 1 day, but were excluded by mirmachine (miR-302d-3p, miR-548ar-5p, miR-3144-3p, miR-4286, miR-4443) (shown in Figure \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e, p values given in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). All, except miR-548ar-5p, maintained significance in the ANOVA analysis, although miR-548ar-5p was significant between PSI-1-day and PSI-7-day. All five miRNAs exhibited the same expression pattern as the other miRNAs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePsilocybin induces significant miRNA changes both 1 day and 7 days after administration in the hippocampus\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the HIP, miR-92a-3p and miR-485-3p were downregulated 1 day after psilocybin administration, whereas miR-99b-5p, miR-125a-5p, miR-127-3p, and miR-221-3p were downregulated 7 days after psilocybin administration using the Top-100 normalization (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eA \u0026ndash; PSI-1-day vs VEH \u0026amp; PSI-7-day vs VEH, p values given in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). miR-92a-3p and miR-485-3p could be validated using Limma and there was a tendency when using DEseq2 (p\u0026thinsp;=\u0026thinsp;0.064 and 0.079, respectively (Table\u0026nbsp;2)). Using Limma, miR-221-3p was significant on PSI-1-day but not on PSI-7-day and miR-127-3p could be validated by housekeeping gene normalization (Table\u0026nbsp;2). In the subsequent ANOVA test, only miR-221-3p remained significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e), although miR-92a-3p, miR-485-3p, and miR-125a-5p remained nearly significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). miR-92a-3p, miR-485-3p, and miR-221-3p followed the same general pattern observed in the PFC between VEH, PSI-1-day, and PSI-7-day (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFinally, four miRNAs (miR-328-3p, miR-409-3p, miR-598-3p, miR-607) displaying significant regulation 7 days after administration were excluded by mirmachine (PSI-7-day vs VEH, p-values presented in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). None of them were significant in the ANOVA test (graphs not shown).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the current study, we explored the use of the Nanostring nCounter technology and the predefined Human v3b miRNA Assay panel to identify dysregulated miRNAs in the pig brain, in response to a single psychedelic dose of psilocybin. To our knowledge this has not previously been done. We report miRNA-alterations related to acute (PSI-1-day) and prolonged (PSI-7-day) effects of psilocybin in the PFC and HIP of pigs. In total, across the PFC and HIP, we identified 14 and 4 dysregulated miRNAs out of 827 miRNAs in after 1 day and 1 week, respectively.\u003c/p\u003e \u003cp\u003eGenerally, we observed greater miRNA-response to psilocybin in the PFC than in the HIP. A possible explanation might be the 5-HT\u003csub\u003e2A\u003c/sub\u003eR distribution in the brain, as the 5-HT\u003csub\u003e2A\u003c/sub\u003eR display high densities in the cerebral cortex whereas the densities in the HIP are very low\u003csup\u003e\u003cem\u003e28\u003c/em\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe miRNA-regulation observed after 1 day in the PFC generally reverted to baseline levels after one week. On the contrary, we observed the largest regulation in the HIP after 1 week. It can be speculated that this may be caused by psilocybin-induced modifications in the PFC, which stimulate 5-HT\u003csub\u003e2A\u003c/sub\u003eR-independent mechanisms in the HIP in a delayed manner.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eNine of the 18 miRNAs identified in our study have previously been associated with depression\u003c/b\u003e\u003c/h2\u003e \u003cp\u003emiR-92a-3p, miR-98-5p, miR-99b-3p, miR-107, miR-125a-5p, miR-128-3p, miR-212-3p, miR-221-3p, and miR-485-3p have been identified as dysregulated in brain tissue or blood from rodent models of depression and depressed patients\u003csup\u003e29, 30\u003c/sup\u003e (summarized in Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInterestingly, miR-107 and miR-212-3p, which were found differentially regulated in PFC using all 4 normalization methods, were two of the nine miRNAs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003emiR-212-3p is upregulated 1 day after psilocybin administration in PFC\u003c/h2\u003e \u003cp\u003emiR-212-3p has previously been linked to treatment of depression. In rats subjected to electroconvulsive stimulation, the animal model equivalent to electroconvulsive therapy, regulation of 6 miRNAs in the HIP has been reported, among them upregulation of miR-212-3p\u003csup\u003e31\u003c/sup\u003e. The 5p transcript (miR-212-5p) has also multiple times in the literature been linked to depression. According to the sequencing density in miRCarta and miRbase, miR-212-3p appear to be the high-abundance/guide strand in humans (Figure \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003e). Therefore, miR-212-5p has not previously been annotated, and thus, not included in the Nanostring v3b panel by the manufacturer. Hence, miR-212-5p could not be quantified in the pigs. In depressed patients, miR-212 has been reported to be elevated in serum after treatment with selective serotonin re-uptake inhibitors (SSRIs) and serotonin and norepinephrine re-uptake inhibitors. It is unclear whether it was the 3p or the 5p strand, that was investigated\u003csup\u003e32\u003c/sup\u003e. To further explore the possible link between depression and miR-212, the antidepressive potential of miR-212 was investigated in a chronic unpredictable mild stress (CUMS) mouse model of depression (Si et al. (2021\u003csup\u003e33\u003c/sup\u003e)). Although not stated explicitly, it was indicated that miR-212-5p was the focus of the study. The CUMS mice exhibited various depressive-like behaviours, determined by body weight, sucrose preference test, forced swimming test, and tail suspension test which all could be ameliorated by either fluoxetine or over-expression of miR-212-5p in the HIP\u003csup\u003e33\u003c/sup\u003e. In addition, it was demonstrated with Targetscan predictions and in luciferase assays, that miR-212-5p targets and downregulates nuclear factor IA (NFIA) and that the antidepressive-like effects mediated by miR-212-5p were abolished when combined with NFIA over-expression\u003csup\u003e33\u003c/sup\u003e. NFIA regulation may thus be a necessary mechanism underlying the antidepressant-like effects of miR-212\u003cb\u003e-\u003c/b\u003e5p. In the context of bladder cancer, it has been demonstrated with Targetscan predictions and luciferase assays that miR-212-3p also targets NFIA\u003csup\u003e34\u003c/sup\u003e, thus demonstrating that both miR-212-5p and miR-212-3p targets NFIA and may act through similar antidepressive molecular mechanisms. Interestingly, in a study by Si et al. (2021), the depressive-like CUMS mice already exhibited elevated miR-212-5p levels in blood and HIP, but the antidepressant like effects were achieved through further over-expression of miR-212-5p\u003csup\u003e33\u003c/sup\u003e. This indicate that upregulation of miR-212-5p might be a protective compensatory mechanism in CUMS mice, rather than a pathological mechanism that needs to be corrected. In support of this assumption, Si et al. (2021) provided evidence for neuroprotective and anti-inflammatory (reduced Tumor necrosis factor-alpha (TNF-α), Interleukin-1 beta, and Interleukin-6 levels) effects using miR-212-5p mimics in the CUMS mice\u003csup\u003e33\u003c/sup\u003e. Similarly, psilocybin has been reported to acutely decrease TNF-α levels in blood from healthy subjects, as TNF-α was reverted to baseline levels, one week after psilocybin administration\u003csup\u003e35\u003c/sup\u003e. This timeline is comparable to the duration of the miR-212-3p regulation observed in the pigs in our study \u0026ndash; upregulated after 1 day, normalized after 7 days. In addition, it has been reported that psilocybin decreased TNF-α levels in human U937 macrophage cells\u003csup\u003e36\u003c/sup\u003e. This could indicate that part of the underlying antidepressive mechanism of psilocybin is to acutely induce neuroprotective and anti-inflammatory effect through expression of miR-212 which acts on NFIA, which in turn regulate TNF-α levels. These results align with prior RNAseq studies performed on the same pigs, which demonstrated that the vast majority of regulated pathways, were immune-related\u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLastly, miR-212 has also been observed down-regulated in monocytes from patients with post-partem psychosis (generally thought to belong to the bipolar spectrum)\u003csup\u003e37\u003c/sup\u003e and downregulated in post-mortem tissue from patients with bipolar disorder\u003csup\u003e38\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003emiR-107 is downregulated 1 day after psilocybin administration in PFC\u003c/h2\u003e \u003cp\u003emiR-107 and miR-103-3p are sequence homologs and likely exhibit the same biological functions (Auwera\u003csup\u003e39\u003c/sup\u003e and miRbase.org). Upregulation of miR-107 has been observed in whole blood from manic bipolar patients compared to healthy controls\u003csup\u003e40\u003c/sup\u003e. On the contrary downregulation of both miR-107 and miR-103 has been reported in plasma from psychiatric patients with childhood trauma\u003csup\u003e39\u003c/sup\u003e, which is one of the best predictors of depression later in life\u003csup\u003e41\u003c/sup\u003e. \u003cem\u003eTransforming growth factor beta receptor 3\u003c/em\u003e (TGFBR3) was identified as a target for both miRNAs\u003csup\u003e39\u003c/sup\u003e. In parallel, SNPs which associated with response to antidepressive treatment in a pool of 575 depressed patients were reported\u003csup\u003e42\u003c/sup\u003e. The rs12082710 genotype (SNP within the TGFBR3 gene) achieved the best association and from a total of 14 identified SNPs which associated with antidepressive treatment outcome, 9 were located within TGFBR3\u003csup\u003e42\u003c/sup\u003e. TGFBR3 encode betaglycan, a co-receptor mediating functional antagonism of activin signalling. Hence, it has been demonstrated that injection of Activin A into the mouse HIP provides an antidepressant-like effect\u003csup\u003e42\u003c/sup\u003e. In resemblance with NFIA, Activin has been shown to provide neuroprotective and neuroplastic effects\u003csup\u003e43\u003c/sup\u003e. While the precise nature of the relationship between the pathophysiology of depression and neuroplasticity is complex, it is generally accepted that antidepressants also interfere with neurotrophic factors which modulate neuroprotective and neuroplastic effects\u003csup\u003e44\u0026ndash;48\u003c/sup\u003e. It is therefore indicated that miR-107 and its target TGFBR3 might play a key role in depression and antidepressant treatment. However, this might be an oversimplification as our data showed downregulation of miR-107 in the pigs 1 day after psilocybin treatment, which indicate upregulation of TGFBR3, which provide functional antagonism to the antidepressant effects of activin. However, according to Targetscan, miR-107 has 907 conserved target sites across 825 transcripts and might therefore exhibit an array of different functions. In support of this statement, it has been demonstrated that gastrodin ameliorates the neuroinflammatory effects induced by lipopolysaccharide in mice, and that the functional mechanism rely on gastrodin-induced downregulation of miR-107 (overexpression of miR-107 abolish the anti-inflammatory effects of gastrodin)\u003csup\u003e49\u003c/sup\u003e. The observed downregulation of miR-107 in the pigs might thus indicate anti-inflammatory effects in resemblance with the effect of miR-212 overexpression\u003csup\u003e33\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOverall, it seems that miR-107 upregulation can provide antidepressant effects through reduced TGFBR3-mediated activin antagonism, while miR-107 downregulation can play into the gastrodin pathway causing anti-inflammatory effects. This dualistic effect might explain the diverging observations in psychiatric patients with childhood trauma\u003csup\u003e39\u003c/sup\u003e and bipolar patients\u003csup\u003e40\u003c/sup\u003e. Nonetheless, the observations in patients were based on peripheral blood samples, which might not correlate with regulations in the brain.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003emiR-98-5p and miR-128-3p are downregulated 1 day after psilocybin in PFC\u003c/h2\u003e \u003cp\u003eIt has previously been reported, that among 25 regulated miRNAs, miR-128-3p was upregulated in the amygdala from the learned helplessness rat model of depression\u003csup\u003e50\u003c/sup\u003e. Prediction target analysis revealed genes within the Wnt signalling pathway as miR-128-3p targets, and significantly reduced Wnt signalling genes in the amygdala of the depressive-like rats was observed\u003csup\u003e50\u003c/sup\u003e. In parallel, elevated miR-128-3p levels and decreased Wnt signalling genes (WNT5B, DVL, and LEF1) were also observed in post-mortem amygdala from depressed patients\u003csup\u003e50\u003c/sup\u003e. This is in line with other studies during recent years, as accumulating evidence implicate Wnt signalling in neuropsychiatric disorders, neurogenesis, and in the underlying mechanism of mood-stabilizers\u003csup\u003e51, 52\u003c/sup\u003e. In mice subjected to chronic restraint stress (CRS) reduced levels of Wnt2 and Wnt3 in the ventral HIP have been reported\u003csup\u003e53\u003c/sup\u003e. Furthermore, knockdown of Wnt2 and Wnt3 led to impaired Wnt/β-catenin signalling, neurogenesis deficits, and depression-like behaviours\u003csup\u003e53\u003c/sup\u003e. In contrast, overexpression of Wnt2 or Wnt3 reversed depression-like behaviours in the CRS mice\u003csup\u003e53\u003c/sup\u003e. Lastly, treatment with the selective serotonin re-uptake inhibitors fluoxetine increased Wnt2 and Wnt3 levels in the ventral HIP and Wnt2 or Wnt3 knockdown abolished the effect of fluoxetine\u003csup\u003e53\u003c/sup\u003e. Overall, the results presented here, indicate that when psilocybin is given to pigs Wnt signalling is increased through decreased miR-128-3p levels which in turn might mediate antidepressive effects.\u003c/p\u003e \u003cp\u003eIn contrast to our results, it has been reported that miR-98-5p is downregulated in the PFC and HIP from mice subjected to chronic social defeat stress and that miR-98-5p overexpression alleviated the depressive-like behaviours\u003csup\u003e54\u003c/sup\u003e. Furthermore, 1 day after ketamine administration, miR-98-5p was elevated and miR-98-5p inhibition blocked the antidepressant effect of ketamine\u003csup\u003e54\u003c/sup\u003e. In our study, miR-98-5p was the only miRNA with the expression levels on day 1 and day 7 being in opposite directions, a significant regulation was observed between PSI-1-day and PSI-7-day (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Thus, it can be speculated that there is a time-delayed effect of psilocybin on miR-98-5p, and a greater magnitude of effect might be observed by using stressed/depressive-like pigs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003emiR-92a-3p and miR-485-3p are downregulated 1 day after psilocybin in HIP\u003c/h2\u003e \u003cp\u003eDysregulated miR-92a-3p has previously been linked to depression in clinical studies. It has been reported that miR-92a-3p is downregulated in the dorsolateral PFC from suicide subjects and this was inversely correlated with TNA-α levels, despite not being a direct target of miR-92a-3p\u003csup\u003e55\u003c/sup\u003e. In contrast, subjects with high baseline miR-92a-3p are more likely to develop post-stroke depression\u003csup\u003e56\u003c/sup\u003e. Preclinically, antidepressant effects has been coupled with reduced miR-92a-3p levels in the HIP of CUMS rats and inhibited by AAV-mediated over-expression of miR-92a-3p\u003csup\u003e57\u003c/sup\u003e. In the CUMS rats the depressive-like behaviour was ameliorated, when the rats were exposed to enriched environment (EE). EE reduced neuronal apoptosis and increased Tropomyosin receptor kinase B (TrkB) and Brain-derived neurotrophic factor (BDNF) levels in the rats, this was partially reversed by miR-92a-3p over-expression\u003csup\u003e57\u003c/sup\u003e. Reduction in miR-92a-3p might thus provide a neuroprotective and neurotrophic effect in resemblance with conventional antidepressants. miR-92a-3p was one among only two miRNA that was regulated (down-regulated) in the HIP of the pigs after 1 day, and it remained approximately significantly regulated in the late phase (p\u0026thinsp;=\u0026thinsp;0.0509, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This could indicate that psilocybin induces a neuroprotective and neurotrophic effect through downregulation of miR-92a-3p. To further support this statement, Mu\u0026ntilde;oz-Llanos et. al. reported that miR-92a-3p was elevated in the dorsal HIP of male rats exposed to 14 days of restraint stress. They also reported that miR-485-5p (although not miR-485-3p) was upregulated in the HIP of the restraint stress rats\u003csup\u003e30\u003c/sup\u003e. In silico analysis revealed that miR-92a-3p and miR-485-5p share many biological functions\u003csup\u003e30\u003c/sup\u003e. miR-485-5p was expressed below LOD in the HIP of the pigs and could thus not be reliably detected. Conversely, miR-485-3p has been reported upregulated in peripheral blood mononuclear cells (PBMCs) of depressed patients after 8 weeks of administration of various antidepressants (week 0 versus week 8)\u003csup\u003e58\u003c/sup\u003e. However, regulation in peripheral blood might not reflect changes in the HIP and the use of various antidepressants in the study, might not exert the same regulatory effects as psilocybin.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003emiR-99b-5p, miR-125a-5p, and miR-221-3p are downregulated 7 days after psilocybin in HIP\u003c/h2\u003e \u003cp\u003eAs none of the three miRNAs were regulated after 1 day (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), this could suggest the presence of distinct antidepressant regulatory mechanisms operating at different time points following psilocybin treatment.\u003c/p\u003e \u003cp\u003ePreviously, miR-99b-3p (but not the guide strand - miR-99b-5p) has been reported upregulated in post-mortem brains of suicide subjects\u003csup\u003e59\u003c/sup\u003e and plasma miR-99b (strand not specified, but we assume detection of guide \u0026ndash; miR-99b-5p) is downregulated after twelve weeks of escitalopram treatment in depressed individuals\u003csup\u003e60\u003c/sup\u003e. Similarly, miR-221-3p is upregulated in serum from depressed subjects\u003csup\u003e61\u003c/sup\u003e and miR-125a-5p has been reported to be upregulated in plasma and cerebrospinal spinal fluid from depressed individuals\u003csup\u003e62, 63\u003c/sup\u003e. Likewise, miR-125a-5p was upregulated in PFC of mice subjected to acute and repeated stress\u003csup\u003e64\u003c/sup\u003e, but downregulated in the HIP of CUMS rats\u003csup\u003e65\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThus, the psilocybin-induced downregulation of miR-99b-5p, miR-125a-5p, and miR-221-3p appear to counteract the general upregulations observed in depressed patients and depressive-like animals.\u003c/p\u003e \u003cp\u003eUsing lentiviral plasmid overexpression of miR-221-3p in HA1800 cells, it has been demonstrated that miR-221-3p target and downregulate interferon regulatory factor 2 (IRF2), a negative regulator of interferon-alpha (IFN-α)\u003csup\u003e61\u003c/sup\u003e. IFN-α is a cytokine closely associated with depression\u003csup\u003e66\u003c/sup\u003e and it is thus suggested that the psilocybin-induced downregulation of miR-221-3p lead to reduced inflammation by downregulating IFN-α through upregulation of IRF2.\u003c/p\u003e \u003cp\u003eIn conclusion, we have demonstrated that the Nanostring nCounter technology and the predefined Human v3b miRNA Assay panel can be used to explore the miRNA landscape in pig brain tissue. Further, we present evidence that psilocybin may exert its intracellular antidepressant effects through miRNA mechanisms. miR-92a-3p, miR-98-5p, miR-99b-5p, miR-107, miR-125a-5p, miR-128-3p, miR-212-3p, and miR-221-3p have been identified as specific miRNA targets. Previously, these miRNAs have been proven to exhibit antidepressant potential in animal models of depression, however, none of them have been associated with psychedelic effects. The combined effect of these miRNAs might therefore exert the antidepressant potential of psilocybin without aversive psychedelic effects. Further studies are needed to elucidate both the acute and prolonged effect of the psilocybin regulated miRNAs and their downstream targets.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge Tania Aaquist Ammitzb\u0026oslash;ll for helping with the RNA extractions. The study has been funded by Simon Fougner Hartmanns Fond (BE) and the Novo Nordisk Foundation (grant number NNF20SA0061466) as a part of ODIN toward the project BioPsych (Identification of \u003cstrong\u003eBIO\u003c/strong\u003emarkers in the human \u003cstrong\u003ePSYCH\u003c/strong\u003eiatric brain \u0026ndash; focusing on non-coding RNAs and sex differences) (BE). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGMK served as speaker for AbbVie, Angelini, Cybin, H. Lundbeck and Sage Biogen\u003cbr\u003e\u0026nbsp;an advisor for Sanos, Onsero, Pangea Botanica, Gilgamesh, AbbVie, PureTechnologies,\u003cbr\u003e\u0026nbsp;a research site for Reunion and Delix Therapeutics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupplementary information is available at MP\u0026rsquo;s website.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCarhart-Harris RL, Bolstridge M, Day CMJ, Rucker J, Watts R, Erritzoe DE\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Psilocybin with psychological support for treatment-resistant depression: six-month follow-up. \u003cem\u003ePsychopharmacology (Berl)\u003c/em\u003e 2018; \u003cstrong\u003e235\u003c/strong\u003e(2)\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e399-408.\u003c/li\u003e\n \u003cli\u003eCarhart-Harris RL, Bolstridge M, Rucker J, Day CM, Erritzoe D, Kaelen M\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Psilocybin with psychological support for treatment-resistant depression: an open-label feasibility study. \u003cem\u003eLancet Psychiatry\u003c/em\u003e 2016; \u003cstrong\u003e3\u003c/strong\u003e(7)\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e619-627.\u003c/li\u003e\n \u003cli\u003eGriffiths RR, Johnson MW, Carducci MA, Umbricht A, Richards WA, Richards BD\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Psilocybin produces substantial and sustained decreases in depression and anxiety in patients with life-threatening cancer: A randomized double-blind trial. \u003cem\u003eJ Psychopharmacol\u003c/em\u003e 2016; \u003cstrong\u003e30\u003c/strong\u003e(12)\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e1181-1197.\u003c/li\u003e\n \u003cli\u003eGrob CS, Danforth AL, Chopra GS, Hagerty M, McKay CR, Halberstadt AL\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Pilot study of psilocybin treatment for anxiety in patients with advanced-stage cancer. \u003cem\u003eArch Gen Psychiatry\u003c/em\u003e 2011; \u003cstrong\u003e68\u003c/strong\u003e(1)\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e71-78.\u003c/li\u003e\n \u003cli\u003eRoss S, Bossis A, Guss J, Agin-Liebes G, Malone T, Cohen B\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Rapid and sustained symptom reduction following psilocybin treatment for anxiety and depression in patients with life-threatening cancer: a randomized controlled trial. \u003cem\u003eJ Psychopharmacol\u003c/em\u003e 2016; \u003cstrong\u003e30\u003c/strong\u003e(12)\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e1165-1180.\u003c/li\u003e\n \u003cli\u003eRickli A, Moning OD, Hoener MC, Liechti ME. 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Recently, psilocybin has shown promise as a novel treatment of major depressive disorder. A single dose of psilocybin is associated with lasting changes in personality and mood. In parallel, various studies have indicated that microRNAs (miRNAs) are regulated after antidepressive interventions. Here, pigs were used to study the transcriptional profiles of miRNAs in the prefrontal cortex (PFC) and hippocampus (HIP), 1 day and 1 week after a single dose of psilocybin. A streamlined process was developed to adapt the Nanostring nCounter technology, specifically the Human v3b miRNA Assay panel, for compatibility with pig tissue samples. The mirmachine tool was used to select miRNAs with complete human-pig sequence conservation to make a conservative reannotation of pig microRNAs. Furthermore, different normalization strategies were employed. Utilizing this pipeline, dysregulation of 12 miRNAs in the PFC and 2 miRNAs in the HIP was \u0026part;identified 1 day after psilocybin administration. Seven days after psilocybin administration, only 4 dysregulated miRNAs were observed in the HIP. Among the 18 identified miRNAs, 9 have previously been linked to depression. Notably, miR-212-3p and miR-107 displayed robust acute regulation across all four normalization strategies in the PFC. The two miRNAs are known to exert anti-inflammatory effects, mirroring previously reported effects of psilocybin. These results suggest that psilocybin may exert its acute and sustained molecular effects through the regulation of specific miRNAs in core brain areas of depression.\u003c/p\u003e","manuscriptTitle":"MicroRNAs underlying the antidepressant effect of psilocybin – Establishing an nCounter pipeline for microRNA-quantification in the pig brain","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-12 09:51:14","doi":"10.21203/rs.3.rs-3787179/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b4705d3-c415-4941-b7da-f1c52f1b642c","owner":[],"postedDate":"January 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28071130,"name":"Health sciences/Diseases/Psychiatric disorders/Depression"},{"id":28071131,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2025-07-02T15:27:06+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-12 09:51:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3787179","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3787179","identity":"rs-3787179","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}