| Literature DB >> 35565034 |
Marco Colizzi1,2, Riccardo Bortoletto3, Rosalia Costa4, Sagnik Bhattacharyya2, Matteo Balestrieri1.
Abstract
Evidence indicates shared physiopathological mechanisms between autism and psychosis. In this regard, the endocannabinoid system has been suggested to modulate neural circuits during the early stage of neurodevelopment, with implications for both autism and psychosis. Nevertheless, such potential common markers of disease have been investigated in both autism and psychosis spectrum disorders, without considering the conundrum of differentiating the two groups of conditions in terms of diagnosis and treatment. Here, we systematically review all human and animal studies examining the endocannabinoid system and its biobehavioral correlates in the association between autism and psychosis. Studies indicate overlapping biobehavioral aberrancies between autism and schizophrenia, subject to correction by modulation of the endocannabinoid system. In addition, common cannabinoid-based pharmacological strategies have been identified, exerting epigenetic effects across genes controlling neural mechanisms shared between autism and schizophrenia. Interestingly, a developmental and transgenerational trajectory between autism and schizophrenia is supported by evidence that exogenous alteration of the endocannabinoid system promotes progression to inheritable psychosis phenotypes in the context of biobehavioral autism vulnerability. However, evidence for a diametral association between autism and psychosis is scant. Several clinical implications follow from evidence of a developmental continuum between autism and psychosis as a function of the endocannabinoid system dysregulation.Entities:
Keywords: cannabidiol; cannabis; delta-9-tetrahydrocannabinol; mental health; neurodevelopment
Mesh:
Substances:
Year: 2022 PMID: 35565034 PMCID: PMC9105053 DOI: 10.3390/ijerph19095616
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
(a). Summary of animal studies investigating ASD and psychosis as a function of the eCB system. (b). Summary of human studies investigating ASD and psychosis as a function of the eCB system.
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| Study (Country) | Aim of Study | Type of Study | Population | N | Outcome Measure (Test Name or Description) | ASD and Psychosis as a Function of the eCB System: | ASD and Psychosis as a Function of the eCB System: Underlying Model |
| Onaivi et al., (2011) (USA) [ | 1. To assess THC-induced behavioral changes and 2. eCB system-related gene expression in ASD mice | 1. In vivo exposure in animals; | 1. Effects of THC: (a) VHI; (b) THC 1 mg/kg; (c) THC 10 mg/kg; | X | 1. Behavior (MFT, FST); | 1. MFT, spontaneous wheel running: (a) BTBR males > C57 males; (b) BTBR group: THC (10 mg/kg) < VHI, THC (1 mg/kg); (c) VHI groups: BTBR > C57 > S129; (d) THC (10 mg/kg) groups: BTBR < C57, S129; | Diametral |
| Anderson et al., (2015) (USA) [ | To assess β-neurexin KO effect on eCB signaling in mice | 1. Quantitative brain assessment in animals; | cKO mice: 1. Cre; 2. ΔCre. | 1. Number of mice: 3–11 per experimental condition; 2. Number of neurons: 8–55 per experimental condition | 1. Molecular assessment (RNA isolation, qRT-PCR, in vivo infections, Stereotactic injections, Ca++ imaging); | 1. β-neurexin KO is associated with both ASD and SCZ; | Overlapping |
| Doenni et al., (2016) (Canada) [ | 1. To assess adolescent social behavior and 2. eCBs/Aes brain levels following early inflammation in rats | 1. In vivo exposure in animals; | 1. SIT (P40, | 297 | 1. Molecular assessment (ecBs/AEs brain levels); | 1. LPS injection at P14 leads to impaired social behavior at P40; | Overlapping |
| Schrott et al., (2019) (USA) [ | To assess cannabis-induced sperm DNA methylation changes and their intergenerational inheritance in rats | 1. In vivo exposure in animals; | 1. Adults: (a) THC: 7; (b) VHI: 8; | 29 | Molecular assessment (DNA isolation from sperm, RRBS, DNA and RNA isolation from brain tissue, Bisulphite pyrosequencing, qRT-PCR in brain tissue) | 1. DLGAP2 DNA methylation in sperm: THC < VHI; | Developmental trajectory |
| Schrott et al., (2020) (USA) [ | To assess cannabis-induced sperm DNA methylation changes in rats | 1. In vivo exposure in animals; | 1. Oral administration: (a) THC: 9; (b) VHI: 8; | 32 | Molecular assessment (DNA isolation from sperm, RRBS, Bisulphite conversion, Bisulphite pyrosequencing, qRT-PCR) | 1. Lrrtm4 DNA methylation in sperm: THC > VHI; | Developmental trajectory |
| Wanner et al., (2020) (USA) [ | To assess CBD-induced brain DNA methylation changes in mice | 1. In vivo exposure in animals; 2. Quantitative brain assessment in animals; 3. Gene-based study in animals. | 1. CBD; 2. VHI | X | Molecular assessment (DNA isolation, Bisulphite conversion, RRBS, DMLs, and DMRs detection) | 1. CBD administration induces methylation changes in adult mouse hippocampus; | Overlapping |
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| Stringer et al., (2016) (Netherlands) [ | To identify genetic risk variants related to lifetime CU | Gene-based study in humans | International Cannabis Consortium: 13 samples from Europe, USA and Australia | 32 330 | Genetic associations (GWAS) | Association with lifetime cannabis use: 4 genes, 1 intergenic noncoding RNA region: 1. NCAM1: part of the NTAD cluster, involved in neurogenesis and dopaminergic neurotransmission; | Developmental trajectory/Overlapping |
| Aran et al., (2018) (Israel) [ | To assess tolerability and efficacy of CBD-rich cannabis in ASD | In vivo treatment exposure in humans | Severe ASD patients | 60 | Behavior (CaGIC scale, HSQ-ASD, APSI) | 1. Behavior improvement in 61% of patients; | Developmental trajectory/Diametral/Overlapping |
| Guennewig et al., (2018) (Australia) [ | To assess THC-induced gene alteration in hiPSC-derived neurons | 1. In vitro treatment exposure in humans; | 1. Untreated; 2. Acute THC; | X | 1. Molecular assessment (RNA-sequencing, qRT-PCR); 2. Genetic associations (DEGs, enrichment analysis) | 1. Acute THC exposure: 497 altered genes; 2. Chronic THC exposure: 810 altered genes; | Developmental trajectory |
| Legge et al., (2019) (Netherlands) [ | 1. To assess shared genetic liability and 2. identify genetic loci associated with PEs | Gene-based study in humans | UK Biobank individuals: 1. MHQ; 2. nMHQ. | 127,966 | Genetic associations (GWAS, genetic correlation, PRSs, CNV) | 1. PRSs: PEs associated with genetic liability for SCZ, ASD; | Developmental trajectory |
| Schrott et al., (2019) (USA) [ | To assess cannabis-induced sperm DNA methylation changes and their intergenerational inheritance | 1. Gene-based study in humans; | 1. Gene-based tests on sperm: | 55 | Molecular assessment (DNA isolation from sperm, RRBS, DNA, and RNA isolation from conceptal brain and testis tissue, Bisulphite pyrosequencing, qRT-PCR in conceptal brain tissue) | 1. DLGAP2 dysregulation: associated with ASD and SCZ; | Developmental trajectory |
| Schrott et al., (2020) (USA) [ | To assess cannabis-induced sperm DNA methylation changes | 1. Gene-based study in humans; | Gene-based tests on sperm: | 24 | Molecular assessment (DNA isolation from sperm, RRBS, Bisulphite conversion, Bisulphite pyrosequencing, qRT-PCR) | 1. Syt3, Lrrtm4, Nrxn1, Nrxn3, Shank1, Dlg4, Grid1 genes major Biological Process GO terms: social behavior, vocalization behavior, learning; | Developmental trajectory |
| Al-Soleiti et al., (2021) (Netherlands) [ | To assess THC-induced psychotic symptoms in ASD | In vivo exposure in humans | ASD patients | 3 | Clinical assessment | 1. ‘self-prescribed’ medical cannabis (sativa/indica mixtures, 20 % THC, 0 % CBD) to relieve anxiety → hallucinations and paranoid delusions, mood swings → induced BIP I, mixed state, with psychotic symptoms; 2. diagnosis of ARMS at 17 → marijuana consumption to feel calmer (1 g per day) → intense auditory hallucinations, paranoia → diagnosis of SCZ at 19 → medical marijuana card (3–4 g per day, indica strains 10 % THC, occasionally marijuana wax with 90 % THC) → increasing psychotic symptoms. | Developmental trajectory |
| Powell et al., (2021) (USA) [ | To assess iDANs SEGs enrichment for psychiatric diseases | 1. Quantitative brain assessment in humans; | 1. iDANs; 2. iGANs; 3. iGLUTs | X | 1. Molecular assessment (RNA isolation, RT-qPCR, Immunocytochemistry, FANS, nuclear RNA-sequencing on brain samples, whole RNA-sequencing on in vitro samples, MEA, Dopamine ELISA); | 1. SEGs in iDANs are enriched for CUD, ASD and SCZ; | Overlapping |
ASD, Autism Spectrum Disorder; eCB, endocannabinoid; THC, Δ9-tetrahydrocannabinol; VHI, vehicle; mg/kg, milligrams per kilogram; MFT, Motor Function Test; FST, Forced Swim Test; DA, dopamine; 5HT, serotonin; RNA, Ribonucleic Acid; RT-PCR, Reverse transcription polymerase chain reaction; BTBR, BTBR T+tf/J mice; C57, C57BL/6 mice; S129, 129S1/SvImJ mice; vs., versus; NS, not significant; CB2A, CNR2 Gene; NOCHG, no change; cKO, conditional triple KO mice; Cre, infected with lentiviruses to delete β-neurexin; ΔCre, truncate Cre-ricombinase; qRT-PCR, Real-Time Quantitative Reverse Transcription PCR; OFT, Open-Fielt Test; LTP, Long-Term Plasticity; CB1, Cannabinoid receptor type 1; 2-AG, 2-Arachidonoylglycerol; AEs, acylethanolamines; SIT, Social Interaction Test; P40, Postnatal day 40; LPS, lipopolysaccharide; SAL, saline; P14, Postnatal day 14; FAAHi, FAAH inhibitor PF-04457845; FAAH, fatty acid amide hydrolase; P30, Postnatal day 30; AEA, anandamide; BLA, basolateral amygdala; DNA, Deoxyribonucleic Acid; RRBS, reduced representation bisulphite sequencing; DLGAP2, DLG Associated Protein 2; SC, subcutaneous; Lrrtn4, Leucine Rich Repeat Transmembrane Neuronal 4; Shank1, SH3 And Multiple Ankyrin Repeat Domains 1; Syt3, Synaptotagmin 3; Nrxn1, Neurexin 1; Nrxn3, Neurexin 3; Dlg4, Discs Large MAGUK Scaffold Protein 4; Grid1, Glutamate Ionotropic Receptor Delta Type Subunit 1; DMLs, Differentially methylated loci; DMRs, Differentially methylated regions; CBD, cannabidiol; Dlgap4, DLG Associated Protein 4; Cadps2, Calcium Dependent Secretion Activator 2; Arid1b, AT-Rich Interaction Domain 1B; Camk2a, Calcium/Calmodulin Dependent Protein Kinase II Alpha; Lrfn2, Leucine Rich Repeat And Fibronectin Type III Domain Containing 2; Prex1, Phosphatidylinositol-3,4,5-Trisphosphate Dependent Rac Exchange Factor 1; Shank2, SH3 And Multiple Ankyrin Repeat Domains 2; Tsc1, TSC Complex Subunit 1; Wdfy3, WD Repeat And FYVE Domain Containing 3; SCZ, schizophrenia; Nr4a2, Nuclear Receptor Subfamily 4 Group A Member 2; Srgap3, SLIT-ROBO Rho GTPase Activating Protein 3; Magi2, Membrane Associated Guanylate Kinase, WW And PDZ Domain Containing 2; Tcf4, Transcription Factor 4; DO, Disease Ontology; CU, cannabis use; GWAS, Genome-Wide Association Studies; NCAM1, Neural Cell Adhesion Molecule 1; CADM2, Cell Adhesion Molecule 2; SCOC, Short Coiled-Coil Protein; KCNT2, Potassium Sodium-Activated Channel Subfamily T Member 2; CaGIC, Caregiver Global Impression of Change; HSQ-ASD, Home Situation Questionnaire-Modified for ASD; APSI, Autism Parenting Stress Index; hiPSC, Human Induced Pluripotent Stem Cell; DEGs, Differentially Expressed Genes; ID, intellectual disability; PEs, psychotic experiences; MHQ, Mental Health Questionnaire; nMHQ, individuals who provided a negative response to all psychotic experience symptom questions at MHQ; PRSs, Polygenic Risk Scores; CNV, Copy Number Variation; NDDs, Neurodevelopmental Disorders; ANK3, Ankyrin 3; ARMS, At Risk Mental State; iDANs, induced dopaminergic neurons; SEGs, Specifically Expressed Genes; iGANs, induced GABAergic neurons; iGLUTs, induced glutamatergic neurons; FANS, fluorescence-activated nuclei-sorting; MEA, Multielectrode array; ELISA, Enzyme-linked immunosorbent assay; CUD, Cannabis Use Disorder; ↑, increased; >, higher than; <, lower than.
(a). Methodological quality of animal studies investigating ASD and psychosis as a function of the eCB system. (b). Methodological quality of human studies investigating ASD and psychosis as a function of the eCB system.
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| Study | Study Design | Defined Study Population | Age | Gender | Control | eCB System Involvement | ASD Involvement | Psychosis Involvement | Statistical Analyses | Funding or Sponsorship |
| Onaivi et al., (2011) (USA) [ | √ Analytic, observational, interventional | √ BTBR, C57, S129 mice | √ Adult | √ Male and female | √ VHI; C57; S129 | √ 1. THC single administration: (a) 1 mg/kg IP; (b) 10 mg/kg IP; 2. CB2 gene expression | √ Idiopathic animal model | √ Behavioral features | √ Student’s | √ |
| Anderson et al., (2015) (USA) [ | √ Analytic, observational | √ NBF mice | √ 1. mRNA measurements: P30;2. Neuron cultures from newborn NBF: DIV 3–4 to DIV 14–16 | X | √ ΔCre | √ eCBs/AEs signaling | √ Genetically induced animal model | √ Genetically induced animal model | √ Student’s | √ |
| Doenni et al., (2016) (Canada) [ | √ Analytic, observational, interventional | √ Sprague Dawley rats | √ P14 and P40 | √ Male and female | √ SAL | √ 1. Double eCBs/AEs levels assessment (P14, P40); | √ Inflammatory-induced animal model; Behavioral features | √ Inflammatory-induced animal model; Behavioral features | √ F-test; Bonferroni’s post hoc test; Student’s | √ |
| Schrott et al., (2019) (USA) [ | √ Analytic, observational, interventional | √ Sprague Dawley rats | √ 9 weeks | √ Male | √ VHI | √ THC daily administration: 4 mg/kg SC, 28 days | √ Genetic liability | √ Intergenerational genetic liability | √ Student’s | √ |
| Schrott et al., (2020) (USA) [ | √ Analytic, observational, interventional | √ Sprague Dawley rats | √ Young adult | √ Male | √ VHI | √ THC daily administration: (a) 2 mg/kg oral, 12 days; (b) 4 mg/kg SC, 28 days | √ Genetic liability | √ Genetic liability | √ Student’s | √ |
| Wanner et al., (2020) (USA) [ | √ Analytic, observational, interventional | √ C57 mice | √ 14 weeks | √ Male | √ VHI | √ CBD daily administration: 20 mg/kg oral, 14 days | √ Genetic liability | √ Genetic liability | √ chi-square test; Fisher’s exact test; Benjamini-Hochberg adjusted | √ |
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| Stringer et al., (2016) (Netherlands) [ | √ Meta-analysis | √ Lifetime cannabis use | √ 16–87 years (average 34 years) | √ Male and female (30–66%) | √ 4 independent replication samples | √ Cannabis exposure | √ Genetic liability | √ Genetic liability | √ Logistic regression | √ |
| Aran et al., (2018) (Israel) [ | √ Analytic, observational, interventional | √ DSM-5 (77% low cognitive functioning according to ADOS or CARS) | √ 5–17 years [11.8 (± 3.5)] | √ Male (83%) and female | X | √ CBD-rich treatment (CBD:THC = 20:1, sublingual administration), 2–3 times per day, up to 10 mg/kg/die | √ Diagnosed patients | √ Adverse event | √ Mann–Whitney U test; Spearman’s rho correlation; Pearson correlation | X |
| Guennewig et al., (2018) (Australia) [ | √ Analytic, observational, interventional | √ General population: | X | X | √ Untreated; | √ 1. (a) Acute THC-exposure (1 μM for 24 h); (b) Chronic THC-exposure (50 nM; 5 treatments over 7 days); | √ Genetic liability | √ Genetic liability; SCZ-like biological alterations | √ ANOVA; Tukey’s test for | √ |
| Legge et al., (2019) (Netherlands) [ | √ Analytic, observational | √ MHQ | √ 64 (± 7.6) years | √ Male (44%) and female | √ nMHQ | √ Genetic liability | √ Genetic liability | √ 1. Psychotic symptoms; | √ Logistic regression; Bonferroni’s correction | √ |
| Schrott et al., (2019) (USA) [ | √ Analytic, observational | √ General population: | √ 1. 18–40 years; 2. 67–122 gestational days | √ Male and female | √ Gene-based tests on sperm: Non-users | √ Cannabis exposure | √ Genetic liability | √ Genetic liability | √ Student’s | √ |
| Schrott et al., (2020) (USA) [ | √ Analytic, observational | √ General population: screened for 1. past 6-month CU; 2. UDS results; 3. [THCCOOH] in urine | √ 18–40 years | √ Male | √ Non-users | √ Cannabis exposure | √ Genetic liability | √ Genetic liability | √ Student’s | √ |
| Al-Soleiti et al., (2021) (Jordan) [ | √ Case report | √ DSM-5 | √ 1. 20 years old; 2. 23 years old; 3. 23 years old | √ Male | X | √ 1. 2-months daily CBD oil (<0.03 % THC); | √ Diagnosed patients | √ Adverse event | X | X |
| Powell et al., (2021) (USA) [ | √ Analytic, observational | √ General population: | √ Post-mortem samples: adult brains | X | √ hiPSC derived | √ Genetic liability for CUD | √ Genetic liability | √ Genetic liability | √ ANOVA; Tukey’s test for | √ |
eCB, endocannabinoid; ASD, Autism Spectrum Disorder; BTBR, BTBR T+tf/J mice; C57, C57BL/6 mice; S129, 129S1/SvImJ mice; VHI, vehicle; THC, Δ9-tetrahydrocannabinol; mg/kg, milligrams per kilogram; IP, intraperitoneal; ANOVA, analysis of variance; NBF, Neurexin β-floxed; P30, Postnatal day 30; DIV, Days in vitro; ΔCre, truncate Cre-ricombinase; AEs, acylethanolamines; P14, Postnatal day 14; P40, Postnatal day 40; SAL, saline; FAAHi, FAAH inhibitor PF-04457845; BLA, basolateral amygdala; SC, subcutaneous; CBD, cannabidiol; DSM-5, The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; ADOS, Autism Diagnostic Observation Schedule; CARS, Childhood Autism Rating Scale; hiPSC, Human Induced Pluripotent Stem Cell; SCZ, schizophrenia; μM, micromolar; h, hour/hours; nM, nanomolar; MHQ, Mental Health Questionnaire; nMHQ, individuals who provided a negative response to all psychotic experience symptom questions at MHQ; UDS, Urine Drugs Screening; THCCOOH, carboxy-Δ9-tetrahydrocannabinol; iDANs, induced dopaminergic neurons; SEGs, Specifically Expressed Genes; iGANs, induced GABAergic neurons; iGLUTs, induced glutamatergic neurons; CUD, Cannabis Use Disorder; <, lower than.
Figure 1PRISMA flowchart of search strategy for systematic review.