Evidence of Altered Monoamine Oxidase B, an Astroglia Marker, in Early Psychosis with Cannabis Use

doi:10.21203/rs.3.rs-4058038/v1

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Evidence of Altered Monoamine Oxidase B, an Astroglia Marker, in Early Psychosis with Cannabis Use

https://doi.org/10.21203/rs.3.rs-4058038/v1

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published 07 Nov, 2024

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A novel radiotracer, [¹¹C]SL25.1188 targets monoamine oxidase-B (MAO-B) enzyme, which metabolizes monoamines (including dopamine) primarily found in astrocytes. Altered astrocyte function in schizophrenia is supported by convergent evidence from post-mortem, genetic, transcriptomic, peripheral and preclinical findings. However, this has never been tested in living brains of early psychosis. Thirty-eight participants including antipsychotic-free/minimally exposed patients with first-episode psychosis (FEP), clinical high-risk (CHR) individuals and healthy volunteers (HVs) underwent a 90-minute positron emission tomography (PET) scan with [¹¹C]SL25.1188, to measure MAO-B V_T, an index of MAO-B concentration. Participants were excluded if tested positive on urine drug screen (except for cannabis). This study of 14 FEP (mean[SD] age, 25.7[5.7] years; 6 F), 7 CHR (mean[SD] age, 20.9[3.7] years; 4 F) and 17 HV (mean[SD] age, 31.2[13.9] years; 9 F) demonstrated significant group differences in regional MAO-B V_T (F_(2,37.46) = 4.56, p = 0.02, Cohen’s f = 0.49), controlling for tobacco (F _(1,37.46) = 5.50 p = 0.02) and cannabis use (F_(1,37.46) = 5.05, p = 0.03) with significant reductions in CHR compared to HV (Cohen’s d = 0.99). We report a significant cannabis effect on MAO-B V_T (F_(1,39.47) = 12.45, p = 0.001, Cohen’s f = 0.56), with a significant group-by-cannabis interaction (F_(2,37.35) = 3.81, p = 0.03, Cohen’s f = 0.45), indicating lower MAO-B V_T in cannabis-using patients. Decreased MAO-B V_T levels was more robust in striatal than cortical regions, in both clinical groups (F_(12,46.07) = 2.00, p = 0.046, Cohen’s f = 0.72) and in cannabis users (F_(6,46.07) = 6.01, p < 0.001, Cohen’s f = 0.89). Reduced MAO-B concentration supports astrocyte dysfunction in cannabis-using CHR and FEP patients. Reduced MAO-B is consistent with replicated striatal dopamine elevation in psychosis, as well as astrocyte dysfunction in schizophrenia.

Health sciences/Biomarkers/Diagnostic markers

Biological sciences/Neuroscience

Schizophrenia is a neurodevelopmental disorder characterized by neuronal and glial cell changes. Among the latter, astrocytes play critical roles, such as providing energy and metabolic support to neurons (1) and regulation of synaptic formation, maintenance, and myelination (2). In addition, astrocytes regulate homeostasis of neurotransmitters such as glutamate by facilitating glutamate biosynthesis, reuptake, and N-methyl-D-aspartate receptor (NMDAR) activation with the co-agonist D-serine (3). Astrocytes also modulate dopamine levels through the expression of vesicular monoamine transporter 2 (VMAT2) and monoamine oxidase-B (MAO-B) enzyme (4). Furthermore, astrocytes provide neuroprotection against oxidative stress and excitotoxicity from various brain insults (5). Astrocytic alterations have been implicated in schizophrenia pathophysiology, with convergent evidence from post-mortem, genetic, transcriptomic and preclinical findings (6, 7). However, whether astrocytic function is altered in the living brain of psychosis patients remains to be determined.

MAO-B is a high-density protein confined to the outer mitochondrial membrane mostly within astrocytes, as well as in serotonergic neurons and dopaminergic cells in the substantia nigra (8, 9). MAO-B is responsible for the catabolism of dopamine, and other amines in humans (for example, benzylamine (10, 11)), perhaps explaining the well replicated increased striatal dopamine synthesis and release repeatedly observed in schizophrenia (12, 13), and the putative prodromal phase before psychosis onset (Clinical High-Risk, CHR (14–16)). MAO-B is also involved in the aberrant hydrogen peroxide production in reactive astrocytes (17). Further, MAO-B overexpression in reactive astrocytes (18) and its significant correlation with astrocyte proteins such as glial fibrillary acidic protein (GFAP), and significant increase in MAO-B levels in autopsied striatum of patients with multiple system atrophy, a disease characterized by marked increase in astrogliosis positions MAO-B as an in vivo reactive astroglia marker (19).

Early post-mortem evidence in schizophrenia reported varying MAO-B activity in several brain regions. Some showed elevated (20), reduced (21) or unaltered MAO-B activity (22–24). Further, homeostatic astrocyte proteins such as glutamine synthetase, GFAP, and S100β demonstrated differing findings in post-mortem samples with either increased (25, 26) or decreased (27–29) astrocyte density, number, morphology, and function. Moreover, reduced platelet MAO-B activity has been reported in the peripheral tissues of individuals with schizophrenia, although its relation to central MAO-B is debated (see review (30)). Nevertheless, tobacco smoking among patients in these prior investigations was a major confounder, due to both MAO-B binding (31) and astrocyte inhibitory chemicals present in cigarette smoke (32). To date, the status of MAO-B in living brains of patients with psychosis is unknown.

Positron Emission Tomography (PET) allows in-vivo quantification of MAO-B. A third-generation novel radiotracer, [¹¹C]SL25.1188 (33, 34) reliably quantifies MAO-B with the validated outcome measure, total distribution volume (V_T), an index of MAO-B concentration (35). [¹¹C]SL25.1188 has improved PET tracer kinetic characteristics (36) including excellent reversibility, brain uptake, selectivity and reproducibility (35) over previous analogues (see (30)). Moreover, the PET outcome measure MAO-B V_T correlated significantly with post-mortem MAO-B protein concentration (r² > 0.9) (19). In brain tissue, changes in MAO-B density are proportional to changes in its activity (11, 18).

Given the well known dopamine and glutamate hypotheses in schizophrenia (37, 38) and the replicated microglial density reductions (Translocator Protein 18 kDa, TSPO) (39), our primary hypothesis was that regional MAO-B V_T is reduced in first-episode psychosis (FEP) patients and CHR individuals compared to healthy volunteers (HV). Furthermore, given the pre-clinical evidence of reduced GFAP expression and astrocytic alterations (32, 40) and decreased in-vitro MAO-B expression (41, 42) in response to cannabis or delta-9-tetrahydrocannabinol (THC) exposure, we expected lower MAO-B V_T with cannabis use. We also predicted that the group and cannabis effect on MAO-B V_T will differ between regions, given the varying MAO-B density across brain regions (35) and region-specific striatal alterations in psychosis (43). Exploratorily, we investigated if duration of illness or untreated psychosis, clinical symptoms and cognitive measures were associated with MAO-B V_T levels. Additionally, we conducted a sub-analysis on the most recent single nucleus RNA sequencing (snRNA-seq) data including only controls from dorsolateral prefrontal cortex (DLPFC) (healthy controls (HC) (44), anterior cingulate cortex (ACC) (neurotypical subjects) (Dehestani M., unpublished data, 2023) and striatum (Wild type (WT) control mice) (45) to assess the brain cell-type expression of MAO-B as a reliable reactive astroglial marker.

Participants

Of the forty-three subjects in the study, 4 patient participants withdrew prior to the PET scan (early discharge) and 1 FEP was not included in the final analysis (Supplementary Fig. 1) as the data exhibited marked deviation in quality control (QC) for reliable estimation of MAO-B V_T values (Supplementary Method 1). Thus, a total of 38 participants including 14 FEP (5 antipsychotic-naïve), 7 CHR (6 antipsychotic-naïve) and 17 healthy volunteers were included in this study. The healthy volunteer sample for current study were shared from a collaborator’s PET study that met the inclusion/exclusion criteria of the current study (46). Healthy volunteers were scanned contemporaneously with the clinical cohort between February 2017 to November 2019 in a tertiary care psychiatric hospital, Ontario, Canada. Our HV sample is consistent with the published HV data using [¹¹C]SL25.1188 (46–48) (Supplementary Table 1). In our sample, all subjects screened negative for drugs of abuse, except for 2 HV, 2 CHR and 1 FEP who had a positive urine drug screen for only cannabis. Of the 5 participants who tested positive for cannabis, only the three in clinical cohorts met criteria for Cannabis use disorder (CUD) assessed as per Diagnostic and Statistical Manual (DSM-5) using Structural Clinical Interview for DSM-5 disorder (SCID-V) (49). In addition, 3 FEP and 1 CHR were tobacco smokers. Eleven of 21 participants of the clinical cohort were antipsychotic-free at the time of scanning, 9 FEP and 1 CHR were on antipsychotic medication and of these 7 were on subtherapeutic dose (< 200 mg/day of chlorpromazine equivalent).

This study was performed under a repository protocol that allowed analysis of previously acquired data, approved by the Centre for Addiction and Mental Health Research Ethics Board (REB) and now approved under Clinical and Translational Sciences (CaTS) BioBank by REB of the Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal – Mental Health and Neuroscience subcommittee. Participants included in this study were recruited in Toronto from February 2017 to November 2019 (Ontario, Canada). Written informed consent was obtained from all participants at the beginning of screening after a full explanation of anticipated study procedures.

To be eligible, FEP patients had to have a recent (within 5 years) diagnosis of a psychotic disorder (including schizophrenia, schizophreniform disorder, schizoaffective disorder, delusional disorder, brief psychotic episode, or psychosis not otherwise specified (NOS)) according to the DSM-5 using SCID-V (49). Individuals in the CHR group were included if they met diagnostic criteria for prodromal risk syndrome as assessed using the Criteria of Prodromal Syndromes (50). Healthy volunteers were included if they did not have any past or present neurological or psychiatric illnesses including any substance use disorders (SUD) (except cannabis and nicotine) assessed as per DSM-5 using SCID-IV (51). HVs from collaborator’s study (46) met our inclusion/exclusion criteria which included no history of psychoactive medication use, no concomitant or past severe medical conditions, no first-degree family members with psychotic-related disorders, and a clean urine drug screen at screening and on scan day (except for cannabis). All participants were excluded if they were pregnant or breastfeeding, had metal implants that precluded a MRI scan, or exceeded the radiation exposure limit (20 mSv in a 12-month period and/or 8 PET scans lifetime). Additionally, competency to fully comprehend the purpose of the study to make rational decision whether to participate (as determined by the MacCAT) was evaluated in all patient participants. Positive and negative syndrome scale (PANSS) was used to assess severity of symptoms in the FEP group (52). In the CHR group, we assessed clinical status and severity of prodromal symptoms using the Structured Interview for Psychosis-Risk Syndromes (SIPS) and the Scale of Psychosis-Risk Symptoms (SOPS) (50). In the clinical cohorts (FEP and CHR), symptom severity and other behavioural measures were assessed with the Global Assessment of Functioning scale (GAF), Beck-anxiety inventory (BAI) (anxiety scale), Snaith-Hamilton Pleasure Scale (SHAPS) (pleasure scale), Apathy Evaluation Scale (apathy scale) and Hamilton Depression Rating Scale (HAM-D) (depression scale) and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) (53) (cognitive performance). Assessments are referenced in the supplementary information that accompanies the online edition of this article (Supplementary Method 2).

PET and MRI image acquisition and analysis

PET and MRI data acquisition have been described in detail elsewhere (35) and are summarized below. All subjects underwent a 90-min [¹¹C]SL25.1188 PET scan which was performed using a high-resolution research tomograph (HRRT) neuro-PET camera system (Siemens Molecular Imaging, Knoxville, TN, USA). Following transmission scan, 370 MBq of [¹¹C]SL25.1188 was administered as a 1-minute bolus with an electronic pump injection (Harvard Apparatus, Holliston, MA, USA) into the antecubital vein. Emission data was acquired for 90 minutes and images were reconstructed into a series of 28-time frames. The first frame was of variable length depending on the time between the start of acquisition and the arrival of [¹¹C]SL2511.88 in the tomograph field of view (FOV). The subsequent frames were defined as 5×30 sec, 1×45 sec, 2×60 sec, 1×90 sec, 1×120 sec, 1×210 sec, and 16×300 sec after the activity appears in the FOV.

MRI Scanning was completed on a Discovery MR750 3.0 Tesla General Electric (GE) research-dedicated scanner. A proton density (PD)-weighted brain MRI scan (fast spin echo imaging, echo time/repetition time/echo train length = Min-Full/6s/8, receiver BW ± 15.63 kHz, FOV = 22 cm, 256 × 256 sampling matrix, slice thickness = 2 mm and a parallel imaging acceleration factor of 2) was acquired per subject and used for the anatomical delineation of regions of interest (ROIs) and quantification of PET images.

An in-house automated brain parcellation program (ROMI) (54) was used to delineate the ROIs on each subject’s MRI. Each subject’s MRI was co-registered to their summed [¹¹C]SL25.1188 PET images with a rigid body transformation using normalized mutual information algorithm (54). The individual refined ROI template was transformed to the PET image space to allow the time-activity curve (TAC) generation from each ROI.

Blood data acquisition and kinetic analysis and calculation of total distribution volume ( V _T )

Arterial blood sampling was collected continuously using an automatic blood sampling system (ABSS, Model #PBS-101 from Veenstra Instruments, Joure, Netherlands) for the first 22 minutes after injection of [¹¹C]SL25.1188 starting at a rate of 350 ml/hour and then slowed to 150ml/hour after 7.25 minutes. In addition, 5 to 10 ml manual samples were drawn at -5, 3.5, 7, 12, 15, 20, 30, 45, 60, and 80 minutes to complement the ABSS data by measuring radioactivity concentration in blood using the γ-counter 2480 Wizard^2TM (PerkinElmer, MA, USA) and determining the relative proportion of radiolabelled metabolites in plasma. The input function for kinetic analysis, delay and dispersion corrected were created as previously described (35).

Logan graphical analysis with arterial input function was applied to 90 minutes of scan data to estimate the outcome measure, V_T for each selected ROI (35, 55).

Post-mortem MAO-B expression pattern in different brain cell types using single cell type transcriptomic analysis

snRNA-seq provides cell type specific transcriptomic data relevant to specific targets in post-mortem samples. In the DLPFC dataset (44), a total of 34 healthy controls (16 M (mean [SD] age, 47.89 [4.45] years); 18 F (mean [SD] age, 38.38 [4.58] years) were included and the ACC dataset involved 2 neurotypical males (age range, 65–80 years old). The striatal dataset (45) featured 4 WT male control mice (14–15-month-old) with their single-nuclei profiled to assess MAO-B expression in brain cell types (Supplementary Method 3). Dot plots were created using Seurat's Dot Plot function with default parameters, incorporating MAO-B as the inputted feature (56). The fraction of cells in a cell group for example, astrocyte cluster expressing MAO-B indicated as the percentage of MAO-B-expressing cells and the average expression i.e., the quantity-level of MAO-B (MAO-B mRNA copies) in each cell are expressed.

Statistical analyses

To test our primary hypothesis of study group differences in regional MAO-B V_T levels, we used linear mixed model with study group (HV, CHR, and FEP) and cannabis use as fixed factors; ROI as a repeated within-subject fixed factor with a diagonal covariance structure (allowed for different residual variances at different ROIs); participants as random effects, and regional MAO-B V_T as the dependent variable. Tobacco use was controlled in all the analyses (31). The a-priori ROIs included in the model were functional divisions of the striatum namely, associative striatum (AST), limbic striatum (LST), and sensorimotor striatum (SMST) and cortical regions including DLPFC, medial prefrontal cortex (mPFC), ACC and hippocampus (HIP). Brain regions were selected based on their relevance for MAO-B brain distribution (35) and hyperdopaminergic signaling observed in the striatal regions in schizophrenia (12, 43) and CHR (14, 15). Analyses including confounding variables (age, sex, and antipsychotic dose) as covariates are presented by adding them as fixed factors and regional MAO-B V_T as the dependent variable in separated models after reporting primary results excluding these variables. Standardized effect sizes (Cohen’s f: small = 0.10, medium = 0.25 and large = 0.4) were calculated using F-statistics. Additionally, we tested the groups pairwise and reported their effect sizes (Cohen’s d: small = 0.20, medium = 0.5, and large = 0.8). All statistical analyses were implemented using SPSS 29.0 (SPSS 29.0; IBM Corp., NY). For the primary hypotheses, a Bonferroni-corrected threshold of 2-sided p < 0.05 was required, while all remaining analyses (post-hoc p-values) were not adjusted for multiple testing.

We tested cannabis use, group-by-cannabis use; group-by-ROI; and cannabis use-by-ROI in a secondary linear mixed model and reported using estimated effects and 95% confidence intervals (CI). Exploratory analyses of the association between regional MAO-B V_T and other clinical variables, such as duration of illness and untreated psychosis in the FEP group, were also investigated applying mixed effect models. Correlations of MAO-B V_T in each brain region with symptomatology (PANSS/SIPS), cognitive measures (RBANS), and other clinical or behavioural measures (GAF/BAI/SHAPS/AES/HAM-D) were explored in clinical groups using univariate analysis (sub-analysis in non-cannabis using CHR) and Pearson partial correlations while controlling for tobacco and group effect (Supplementary Result; Supplementary Tables 2–5).

Demographic and clinical characteristics of participants

Demographic and clinical characteristics of groups are presented in Table 1. Only three out of nine FEP participants on antipsychotic medication were taking therapeutic doses: lurasidone 80 mg, paliperidone 9 mg and olanzapine 15 mg, while the remaining were on subtherapeutic doses. Other demographic variables and PET radiotracer injection parameters did not significantly differ between the patient and healthy groups (all p > 0.05). The CHR group had (non-significant) higher average injected mass, primarily due to one CHR subject who was injected 13.12 µg. We noted this subject had the highest MAO-B V_T (across ROIs) in the CHR group, thus making an eventual mass effect unlikely.

Table 1

Demographic and Clinical Measures of the Participants
Variable				HV (n = 17)	CHR (n = 7)	FEP (n = 14)	Test statistic	P value
Age (years)		Mean		31.24	20.86	25.71	2.83¹	0.07
Age (years)		SD		13.99	3.67	5.68	2.83¹	0.07
Male, n				8	3	8	0.38²	0.54
Female, n				9	4	6	0.38²	0.54
BMI (Kg/m²)		Mean		23.41	22.32	24.78	1.21¹	0.31
BMI (Kg/m²)		SD		2.87	4.54	3.89	1.21¹	0.31
Current substance use	Non-tobacco smokers, n			17	6	11	0.15²	0.69
	Tobacco smokers⁴, n			0	1	3	0.15²	0.69
	Non-cannabis users, n			15	5	13	1.92²	0.21
	Cannabis users⁵, n			2	2	1	1.92²	0.21
Antipsychotic use		AP-free, n		N/A	6	5	4.68²	0.03
Antipsychotic use		AP-current, n		N/A	1	9	4.68²	0.03
PET Parameters	Amount injected (mCi)		Mean	10.09	9.75	9.75	1.26¹	0.29
	Amount injected (mCi)		SD	0.71	0.52	0.65	1.26¹	0.29
	Specific activity (mCi/µmol)		Mean	1804.99	1849.93	1983.41	0.15¹	0.86
	Specific activity (mCi/µmol)		SD	815.25	1170.70	902.34	0.15¹	0.86
	Mass injected (µg)		Mean	2.65	4.03	2.26	1.58¹	0.22
	Mass injected (µg)		SD	1.36	4.48	1.17	1.58¹	0.22
GAF Score		Mean		NA	53.57	52.86	-0.49³	0.62
GAF Score		SD		NA	5.47	7.42	-0.49³	0.62
Total PANSS Score		Mean		N/A	N/A	52.14 ± 15.58	N/A	N/A
Total PANSS Score		SD		N/A	N/A	52.14 ± 15.58	N/A	N/A
Total RBANS Score		Mean		NA	95.14	81.50	-1.48³	0.16
Total RBANS Score		SD		NA	17.85	16.74	-1.48³	0.16
SOPS Total Symptom Severity Score		Mean		N/A	28.43	N/A	N/A	N/A
SOPS Total Symptom Severity Score		SD		N/A	16.06	N/A	N/A	N/A
Abbreviations: BMI – Body Mass Index; AP – Antipsychotic; N/A – Not applicable; NA – Not Available; GAF - Global Assessment of Functioning; PANSS - Positive and Negative Syndrome Scale; RBANS - Repeatable Battery for the Assessment of Neuropsychological Status; SOPS - Scale of Prodromal Syndromes Statistical analysis was performed using - ¹ANOVA F-test ²χ² test ³Independent samples T-test ⁴Of the 4 tobacco smokers (1 CHR, 3 FEP), only 1 FEP uses both tobacco and cannabis. ⁵Cannabis use (route of administration and pattern of use): HV, n = 2 [Joint (0.25g occasionally); Edibles (1–2 times/month)]; CHR, n = 2 [Joint (3-4g every 2 days); Joint (1g/day)]; FEP, n = 1 [Joint (1g/day)]

MAO-B V_T is significantly different between study groups

We found a significant effect of the study group (F_{(2, 37.46)} = 4.56, p = 0.02, Cohen’s f = 0.49), ROI: (F_{(6, 50.41)} = 264.62, p < 0.001) on MAO-B V_T (Fig. 1A and B), controlling for tobacco (F _(1,37.46) = 5.50 p = 0.02) and cannabis use (F _(1,37.46) = 5.05 p = 0.03) with significant reductions in CHR individuals relative to healthy volunteers (p = 0.01, Cohen’s d = 0.99). Post-hoc pairwise comparisons revealed non-significant differences between HV and FEP (p = 0.97, Cohen’s d = 0.33). The main outcome retained a large effect size (Cohen’s f = 0.45) with a trend for significance (group effect: F_{(1, 20.69)} = 4.12, p = 0.055), with no effect of antipsychotic dose on MAO-B V_T (F_(1,20.69) = 0.12, p = 0.73).

The main study group effect remained unaltered after controlling for other covariates such as age (F_(1,37,45) = 0.36, p = 0.56; group effect: F_{(2, 37.45)} = 3.53, p = 0.04), and sex (F_(1,37.46) = 0.23, p = 0.64; group effect: F_(2,37.46) = 4.39, p = 0.02).

Exploratorily, lower MAO-B V_T levels correlated with greater symptom severity (AST: SOPS total (r= -0.97, p = 0.03), SOPS negative (r = -0.98, p = 0.02); SMST: SOPS negative (r = -0.96, p = 0.04); Hippocampus: SOPS negative (r = -0.96, p = 0.04)) in non-cannabis using CHR, not surviving Bonferroni corrections for multiple testing.

Significant effect of cannabis use on MAO-B V_T and more pronounced effects in striatal regions

We report a significant effect of cannabis use on MAO-B V_T (cannabis: F_{(1, 39.47)} = 12.45, p = 0.001, Cohen’s f = 0.56; group effect: F_{(2, 38.47)} = 11.29, p < 0.001), with lower MAO-B V_T in cannabis users relative to non-users. We found a significant group-by-cannabis interaction (F_{(2, 37.35)} = 3.81, p = 0.03, Cohen’s f = 0.45, group effect: F_{(2, 38.47)} = 11.29, p < 0.001) (Fig. 2A), indicating larger cannabis effects in CHR and FEP clinical groups compared to the HV group.

Further, we report a significant group-by-ROI interaction (F_{(12, 46.07)} = 2.00, p = 0.046, Cohen’s f = 0.72; group: F_{(2, 38.47)} = 11.29, p < 0.001), showing that the group differences were more pronounced in striatal regions (SMST, AST and LST) as compared to cortical regions in the clinical groups (Fig. 2B, Table 2). We also found a significant cannabis-by-ROI interaction (F_{(6, 46.07)} = 6.01, p < 0.001, Cohen’s f = 0.89; group effect: F_{(2, 38.47)} = 11.29, p < 0.001), reflecting relatively larger cannabis effects in the striatal ROIs versus cortical ROIs (Supplementary Fig. 2).

Table 2

Post-hoc regional MAO-B V_T differences between groups
ROI	Study group	Mean	Standard error	P value¹			Effect size²
ROI	Study group	Mean	Standard error	HV vs. CHR	HV vs. FEP	FEP vs. CHR	HV vs. CHR	HV vs. FEP	FEP vs. CHR
DLPFC	HV	23.51	1.82	0.02	0.49	0.08	0.77	0.22	0.56
	CHR	18.32	2.00
	FEP	22.27	1.67
mPFC	HV	27.43	1.82	0.005	0.25	0.06	0.93	0.37	0.61
	CHR	21.02	2.00
	FEP	23.35	1.67
ACC	HV	29.35	1.84	0.003	0.31	0.04	0.91	0.31	0.64
	CHR	22.56	2.05
	FEP	27.47	1.70
HIP	HV	27.23	1.85	0.03	0.60	0.10	0.64	0.16	0.50
	CHR	22.35	2.07
	FEP	26.27	1.71
AST	HV	42.12	1.96	< 0.001	0.22	0.007	0.96	0.30	0.69
	CHR	32.22	2.30
	FEP	39.55	1.85
LST	HV	52.26	2.19	< 0.001	0.08	0.005	1.04	0.41	0.68
	CHR	38.49	2.75
	FEP	47.81	2.14
SMST	HV	35.93	1.98	0.002	0.29	0.03	0.78	0.26	0.55
	CHR	27.57	2.35
	FEP	33.66	1.88
¹p < 0.05 ²Standardized effect sizes (Cohen’s d: small = 0.20, medium = 0.5 and large = 0.8) calculated using t-statistics are presented. Linear mixed model analysis evaluated group interaction with region using regional MAO-B V_T as the dependent variable, group as the predictor variable and group-by-ROI as fixed factor, controlling for tobacco and cannabis use. Model estimated means and post-hoc p values (unadjusted for multiple comparisons) are presented, together with their effect sizes.

Single cell transcriptomic analysis show astrocytes are the main glial cells expressing MAO-B

The DLPFC data analysis revealed that MAO-B is expressed primarily in excitatory neurons (ExN) (approximately 28%), followed by astrocytes (around 13%), with astrocytes being the main glial cells expressing MAO-B. In the ACC, approximately 44% of nuclei in the excitatory neurons’ cluster expressed MAO-B, while around 58% of nuclei within the astrocyte cluster expressed MAO-B. Importantly, in the striatum, around 72% of nuclei in the astrocyte cluster expressed MAO-B. Essentially, although the main cell type that express MAO-B are excitatory neurons (for example in DLPFC), the average expression of MAO-B i.e., the quantity of MAO-B mRNA copies in each cell is notably elevated in the astrocyte clusters compared to other brain cell type clusters across all the three regional snRNA-seq datasets (Supplementary Fig. 3A-C).

To our knowledge, this is the first PET study to investigate brain MAO-B in psychosis patients and its putative prodrome. We demonstrated that CHR and FEP clinical groups, who were cannabis users, had lower MAO-B V_T compared to non-users with more robust effect in the striatal regions. Notably, these findings persist with a large effect size while controlling for antipsychotic use, sex or other possible confounders.

Our finding of reduced MAO-B V_T in early psychosis with significant reductions in prodromal stages is in line with previous post-mortem evidence (21) demonstrating low MAO-B activity in schizophrenia patients (post-mortem studies specific to at-risk state, are not available). Reduced MAO-B concentration could explain the diminished capacity to terminate dopaminergic synaptic signaling, resulting in increased dopaminergic tone, particularly in striatal regions. In this context, pharmacological interventions that restore MAO-B activity or increase MAO-B concentration could potentially normalize striatal dopaminergic transmission in patients. Speculatively, the CHR and cannabis-using groups could be considered as potential targets for such clinical trials. The more pronounced effect in CHR may reflect the increasingly altered dopamine/glutamate function in these patients (versus FEP patients, some of whom were on low-dose antipsychotics), or it could be attributed to an amplified influence of cannabis use within the CHR group. Longitudinal studies should investigate this question, particularly given the known heterogeneity in CHR and high prevalence of cannabis use in youth.

Decreased MAO-B is also consistent with the glutamate dysfunction previously reported in schizophrenia (38), considering the fundamental involvement of astrocytes in glutamatergic processes, including biosynthesis, reuptake, and release (3). For instance, altered astrocyte expression of excitatory amino acid transporter 1 (EAAT1) and EAAT2 may lead to impaired glutamate clearance from synapses, resulting in prolonged glutamate signaling (3). Furthermore, diminished astrocyte function could relate to an impaired regulation of D-serine and glycine levels, both of which endogenous co-agonists for glutamatergic NMDARs (3), showing reduced serum and cerebrospinal fluid (CSF) D-serine levels (57, 58). Thus, astrocyte dysfunction, here as indexed by lower MAO-B, is consistent with both dopaminergic and glutamatergic transmission abnormalities previously reported in psychosis.

While in a small sample, we report lower MAO-B V_T in cannabis using patients. The lower MAO-B concentration in cannabis users is consistent with the low GFAP expression secondary to chronic cannabis exposure in hippocampal rat brains (40). A recent in vitro study demonstrated decreased MAO-B gene expression after acute low-dose cannabis exposure (41), consistent with a prior study that revealed an inhibitory effect of delta-9-tetrahydrocannabinol (THC) on MAO-B, albeit at high concentrations (42). Interestingly, previous investigations showed smaller stress-induced striatal dopamine release in CHR with cannabis use compared to non-users (14), resembling findings in schizophrenia with substance dependence including cannabis use (59). Despite this blunting of dopamine release in patients (CHR and schizophrenia) who were cannabis users, there was evidence of transient positive symptom increase (59). This could be partially attributed to low MAO-B concentration, resulting in increased synaptic dopamine levels by reducing its turnover in cannabis using patients.

Our findings reveal more significant group effects in the striatal compared to cortical regions. These observations could be due to the regional heterogeneity of MAO-B expression which was highest in the caudate (associative striatum), thalamic, and putamen regions followed by the cortical and hippocampal regions, and relatively lower levels in the cerebellar cortex and white matter tissue (8, 11, 35). Reduced MAO-B concentration in the striatum in the clinical cohorts may also explain the increased region-specific striatal dopamine signaling repeatedly observed in schizophrenia (12, 43) and CHR (14, 15). We also demonstrated larger cannabis effects on MAO-B V_T in the striatal regions, a key area involved in substance use disorders, compared to cortical regions. Finally, because MAO-B is critically involved in the aberrant production of hydrogen peroxide in reactive astrocytes (17), our findings align with emerging evidence of altered brain bioenergetics and cellular oxidative status in CHR (60, 61), FEP (62), and in cannabis use (63).

Some limitations of this study should be considered when interpreting the results. First, as is standard with PET imaging studies, the measure of MAO-B V_T reflects binding of the radiotracer to MAO-B plus non-specific binding. However, our latest estimate of the non-specific binding (V_ND) of 6.6 mL/cm³ suggests that between 70% (cerebellar cortex) and 89% (caudate) of V_T corresponds to specific binding supporting the use of V_T as the best outcome measure to quantify [¹¹C]SL25.1188 in the human brain (35). Second, the specific binding compartment of the MAO-B V_T reflects both density and affinity of the radiotracer to MAO-B, although empirically MAO-B V_T quantitated with [¹¹C]SL25.1188 PET is highly correlated with MAO-B density in human brain (35). Third, the patient group reflects the heterogeneity of clinical presentation, including co-morbid Axis 1 disorders (depression, n = 4; 1 FEP, 3 CHR; and anxiety n = 7; 4 FEP, 3 CHR). However, main results retained a trend for significance when controlling for co-morbid major depressive disorder (MDD) (F_(1,37.45) = 0.10, p = 0.76; group effect: F_(2,37.45) = 3.11, p = 0.056) and anxiety disorder (F_(1,37.44) = 1.47, p = 0.23; group effect: F_(2,37.44) = 3.00, p = 0.06). Furthermore, while our findings (low MAO-B) specifically pertain to cannabis/tobacco using patients with psychotic disorders, which represent the reality of our patients; here, excluding tobacco and cannabis use revealed no significant group effect (F_{(2, 29.77)} = 1.17, p = 0.32). However, group effect size (Cohen’s f) remained at 0.28 (medium effect) highlighting the potential importance of MAO-B in non cannabis using psychosis patients. Similarly, pairwise comparisons between HV vs. CHR also remained (Cohen’s d, 0.56). Furthermore, analysis of the data excluding one CHR with very low MAO-B V_T in the a-priori ROIs, still retained medium-to-large effect size (Cohen’s f, 0.39). While inclusion of these heterogenous clinical participants is a strength of our study, future studies will need to investigate whether our results apply to samples with no co-morbid illness and/or substance use (cannabis or tobacco). Fourth, while small sample size is a potential limitation in molecular imaging studies, here we report large effect sizes, highlighting the importance of MAO-B in cannabis/tobacco using patients with psychotic disorders and its putative prodrome. Thus, our findings represent an important contribution to our understanding of molecular changes in an heterogenous group of patients with psychosis and may not be specific for CHR or FEP. Future studies will investigate MAO-B in CUD. Finally, [¹¹C]SL25.1188 V_T reflects MAO-B availability on astrocytes as well as in other cellular types including serotonergic neurons (8, 9), and as such the PET signal is not specific to astrocytes. Definitive assessment of astrocyte status in brain requires brain neuropathological assessment. To address this concern, we conducted a post-mortem sub-analysis on snRNA sequencing data including only controls from the DLPFC (healthy controls (HC), n = 34) (44), ACC (neurotypical subjects, n = 2) (Dehestani M., unpublished data, 2023) and striatum (Wild type (WT) control mice, n = 4) (45) revealing that the average MAO-B concentration is higher in astrocyte clusters relative to other brain cell type clusters. This is consistent with previous evidence of correlation between GFAP and MAO-B in reactive astrocytes (19). Thus, while MAO-B is also expressed in other cell types, notably in excitatory neurons in post-mortem tissue of controls (human/mice), our findings can also be interpreted as reduced MAO-B labelled astrocytes in cannabis/tobacco using CHR and PET patients, especially in striatal regions. Our results are consistent with recent post-mortem and pluripotent stem cell findings highlighting the critical role of astrocyte-neuron interactions in schizophrenia (64) (Ling E., unpublished data, 2024).

MAO-B V_T is lower in cannabis/tobacco using CHR and FEP patients, with more pronounced differences in striatal regions. Reduced MAO-B is consistent with the replicated striatal region-specific dopamine elevation as well as the altered glutamate and mitochondrial dysfunction previously reported in psychosis. This study presents a potential therapeutic target for early psychosis treatment via MAO-B activity restoration, particularly in cannabis using CHR and FEP patients. MAO-B targeted intervention is consistent with emerging precision psychiatry, which is critical given recent data demonstrating that cannabis use increases risk for relapse in schizophrenia patients and precede symptomatic and social functioning worsening one year later (65).

Data Availability: Anonymized individual participant data and analyses codewill be made available in Supplementary Appendix at the time of publication.

Acknowledgements: This work was partially funded by Canadian Institutes of Health Research (CIHR) Grant (APP461645) and was done as part of the research undertaken thanks, in part, to funding from the Canada First Research Excellence Fund, awarded to the Healthy Brains for Healthy Lives initiative at McGill University to Dr. Mizrahi.

The authors thank the staff of the FYPP clinic (Dr. Michael Kiang) for aiding in participant recruitment in Toronto and the PET Research Imaging Centre for the acquisition of data. We would also like to thank the participants and their families for their cooperation.

Conflict of Interest: NL is an employee at the Vertex Pharmaceuticals and the authors collectively declare that they have no financial relationships with commercial interests that could have appeared to influence the work reported in this paper. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Author Contributions: Dr. Mizrahi and Ms. Nisha Aji had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Mizrahi. Acquisition, analysis, or interpretation of data: Lalang, Nisha Aji, Ramos-Jiménez, Rusjan, Mizrahi, Rahimian. Drafting of the manuscript: Nisha Aji, Mizrahi, Rahimian, Rusjan. Critical revision of the manuscript for important intellectual content: Nisha Aji, Mizrahi, Rusjan, Meyer, Boileau, Rahimian, Mechawar, Turecki, Chartrand. Statistical analysis: Nisha Aji, Mizrahi, Ramos-Jiménez. Obtained funding: Mizrahi. Administrative, technical, or material support: Rusjan, Chartrand. Supervision: Mizrahi, Rusjan.

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Evidence of Altered Monoamine Oxidase B, an Astroglia Marker, in Early Psychosis with Cannabis Use

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PET and MRI image acquisition and analysis

Post-mortem MAO-B expression pattern in different brain cell types using single cell type transcriptomic analysis

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Results

Demographic and clinical characteristics of participants

Single cell transcriptomic analysis show astrocytes are the main glial cells expressing MAO-B

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