The Autism–Psychosis Continuum Conundrum: Exploring the Role of the Endocannabinoid System
Abstract
:1. Introduction
Objectives
2. Experimental Procedures
2.1. Inclusion and Exclusion Criteria
2.2. Search Strategy and Data Extraction
2.3. Risk of Bias
3. Results
3.1. Study Selection
3.2. Evidence for a Diametral Relationship between Autism and Psychosis-Related Phenotypes as a Function of the eCB System Modulation
3.3. Evidence for an Overlapping Relationship between Autism and Psychosis-Related Phenotypes as a Function of the eCB System Modulation
3.4. Evidence for a Developmental Trajectory between Autism and Psychosis-Related Phenotypes as a Function of the eCB System Modulation
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, (DSM-5), 5th ed.; American Psychiatric Association: Washington, DC, USA, 2013. [Google Scholar]
- Mercier, C. Sanity and Insanity; Walter Scott Publishing, Co.: Newcastle-on-Tyne, UK,, 1890. [Google Scholar]
- Ornitz, E.M. Disorders of perception common to early infantile autism and schizophrenia. Compr Psychiatry 1969, 10, 259–274. [Google Scholar] [CrossRef]
- Bleuler, E. Dementia Praecox oder Grupper der Schizophrenien; Deuticke: Leipzig, Germany, 1911. [Google Scholar]
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, (DSM-III), 3rd ed.; American Psychiatric Association: Washington, DC, USA, 1980. [Google Scholar]
- King, B.H.; Lord, C. Is schizophrenia on the autism spectrum? Brain Res. 2011, 1380, 34–41. [Google Scholar] [CrossRef] [PubMed]
- de Lacy, N.; King, B.H. Revisiting the relationship between autism and schizophrenia: Toward an integrated neurobiology. Annu. Rev. Clin. Psychol. 2013, 9, 555–587. [Google Scholar] [CrossRef]
- Morris-Rosendahl, D.; Crocq, M. Neurodevelopmental disorders-the history and future of a diagnostic concept. Dialogues in Clin. Neurosci. 2020, 22, 65–72. [Google Scholar] [CrossRef] [PubMed]
- Colizzi, M.; Lasalvia, A.; Ruggeri, M. Prevention and early intervention in youth mental health: Is it time for a multidisciplinary and trans-diagnostic model for care? Int. J. Ment. Health Syst. 2020, 14, 23. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Owen, M.J.; O’Donovan, M.C. Schizophrenia and the neurodevelopmental continuum:evidence from genomics. World Psychiatry 2017, 16, 227–235. [Google Scholar] [CrossRef] [Green Version]
- Pontillo, M.; Averna, R.; Tata, M.C.; Chieppa, F.; Pucciarini, M.L.; Vicari, S. Neurodevelopmental Trajectories and Clinical Profiles in a Sample of Children and Adolescents With Early- and Very-Early-Onset Schizophrenia. Front. Psychiatry 2021, 12, 662093. [Google Scholar] [CrossRef]
- Bhati, M.T. Defining psychosis: The evolution of DSM-5 schizophrenia spectrum disorders. Curr. Psychiatry Rep. 2013, 15, 409. [Google Scholar] [CrossRef]
- Kenny, E.M.; Cormican, P.; Furlong, S.; Heron, E.; Kenny, G.; Fahey, C.; Kelleher, E.; Ennis, S.; Tropea, D.; Anney, R.; et al. Excess of rare novel loss-of-function variants in synaptic genes in schizophrenia and autism spectrum disorders. Mol. Psychiatry 2014, 19, 872–879. [Google Scholar] [CrossRef] [Green Version]
- De Rubeis, S.; He, X.; Goldberg, A.P.; Poultney, C.S.; Samocha, K.; Cicek, A.E.; Kou, Y.; Liu, L.; Fromer, M.; Walker, S.; et al. Synaptic, transcriptional and chromatin genes disrupted in autism. Nature 2014, 515, 209–215. [Google Scholar] [CrossRef]
- Fromer, M.; Pocklington, A.J.; Kavanagh, D.H.; Williams, H.J.; Dwyer, S.; Gormley, P.; Georgieva, L.; Rees, E.; Palta, P.; Ruderfer, D.M.; et al. De novo mutations in schizophrenia implicate synaptic networks. Nature 2014, 506, 179–184. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Basavarajappa, B.S.; Nixon, R.A.; Arancio, O. Endocannabinoid system: Emerging role from neurodevelopment to neurodegeneration. Mini Rev. Med. Chem. 2009, 9, 448–462. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kendall, D.A.; Yudowski, G.A. Cannabinoid Receptors in the Central Nervous System: Their Signaling and Roles in Disease. Front. Cell. Neurosci. 2016, 10, 294. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lu, H.C.; Mackie, K. An Introduction to the Endogenous Cannabinoid System. Biol. Psychiatry 2016, 79, 516–525. [Google Scholar] [CrossRef] [Green Version]
- Díaz-Alonso, J.; Guzmán, M.; Galve-Roperh, I. Endocannabinoids via CB1 receptors act as neurogenic niche cues during cortical development. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2012, 367, 3229–3241. [Google Scholar] [CrossRef] [Green Version]
- Galve-Roperh, I.; Palazuelos, J.; Aguado, T.; Guzmán, M. The endocannabinoid system and the regulation of neural development: Potential implications in psychiatric disorders. Eur. Arch. Psychiatry Clin. Neurosci. 2009, 259, 371–382. [Google Scholar] [CrossRef]
- Sun, X.; Dey, S.K. Aspects of endocannabinoid signaling in periimplantation biology. Mol. Cell. Endocrinol. 2008, 286, S3–S11. [Google Scholar] [CrossRef] [Green Version]
- Younts, T.J.; Castillo, P.E. Endogenous cannabinoid signaling at inhibitory interneurons. Curr. Opin. Neurobiol. 2014, 26, 42–50. [Google Scholar] [CrossRef] [Green Version]
- Zhou, Y.; Falenta, K.; Lalli, G. Endocannabinoid signalling in neuronal migration. Int. J. Biochem. Cell. Biol. 2014, 47, 104–108. [Google Scholar] [CrossRef]
- Song, C.G.; Kang, X.; Yang, F.; Du, W.Q.; Zhang, J.J.; Liu, L.; Kang, J.J.; Jia, N.; Yue, H.; Fan, L.Y.; et al. Endocannabinoid system in the neurodevelopment of GABAergic interneurons: Implications for neurological and psychiatric disorders. Rev. Neurosci. 2021, 32, 803–831. [Google Scholar] [CrossRef]
- Onaivi, E.S.; Benno, R.; Halpern, T.; Mehanovic, M.; Schanz, N.; Sanders, C.; Yan, X.; Ishiguro, H.; Liu, Q.R.; Berzal, A.L.; et al. Consequences of cannabinoid and monoaminergic system disruption in a mouse model of autism spectrum disorders. Curr. Neuropharmacol. 2011, 9, 209–214. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Anderson, G.R.; Aoto, J.; Tabuchi, K.; Földy, C.; Covy, J.; Yee, A.X.; Wu, D.; Lee, S.J.; Chen, L.; Malenka, R.C.; et al. β-Neurexins Control Neural Circuits by Regulating Synaptic Endocannabinoid Signaling. Cell 2015, 162, 593–606. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Doenni, V.M.; Gray, J.M.; Song, C.M.; Patel, S.; Hill, M.N.; Pittman, Q.J. Deficient adolescent social behavior following early-life inflammation is ameliorated by augmentation of anandamide signaling. Brain Behav. Immun. 2016, 58, 237–247. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Schrott, R.; Acharya, K.; Itchon-Ramos, N.; Hawkey, A.B.; Pippen, E.; Mitchell, J.T.; Kollins, S.H.; Levin, E.D.; Murphy, S.K. Cannabis use is associated with potentially heritable widespread changes in autism candidate gene. Epigenetics 2020, 15, 161–173. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Schrott, R.; Rajavel, M.; Acharya, K.; Huang, Z.; Acharya, C.; Hawkey, A.; Pippen, E.; Lyerly, H.K.; Levin, E.D.; Murphy, S.K. Sperm DNA methylation altered by THC and nicotine: Vulnerability of neurodevelopmental genes with bivalent chromatin. Sci. Rep. 2020, 10, 16022. [Google Scholar] [CrossRef]
- Wanner, N.M.; Colwell, M.; Drown, C.; Faulk, C. Subacute cannabidiol alters genome-wide DNA methylation in adult mouse hippocampus. Environ. Mol. Mutagen. 2020, 61, 890–900. [Google Scholar] [CrossRef]
- Stringer, S.; Minică, C.C.; Verweij, K.J.; Mbarek, H.; Bernard, M.; Derringer, J.; van Eijk, K.R.; Isen, J.D.; Loukola, A.; Maciejewski, D.F.; et al. Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32 330 subjects from the International Cannabis Consortium. Transl. Psychiatry 2016, 6, e769. [Google Scholar] [CrossRef]
- Aran, A.; Cassuto, H.; Lubotzky, A.; Wattad, N.; Hazan, E. Brief Report: Cannabidiol-Rich Cannabis in Children with Autism Spectrum Disorder and Severe Behavioral Problems—A Retrospective Feasibility Study. J. Autism Dev. Disord. 2019, 49, 1284–1288. [Google Scholar] [CrossRef]
- Guennewig, B.; Bitar, M.; Obiorah, I.; Hanks, J.; O’Brien, E.A.; Kaczorowski, D.C.; Hurd, Y.L.; Roussos, P.; Brennand, K.J.; Barry, G. THC exposure of human iPSC neurons impacts genes associated with neuropsychiatric disorders. Transl. Psychiatry 2018, 8, 89. [Google Scholar] [CrossRef]
- Legge, S.E.; Jones, H.J.; Kendall, K.M.; Pardiñas, A.F.; Menzies, G.; Bracher-Smith, M.; Escott-Price, V.; Rees, E.; Davis, K.A.S.; Hotopf, M.; et al. Association of Genetic Liability to Psychotic Experiences With Neuropsychotic Disorders and Traits. JAMA Psychiatry 2019, 76, 1256–1265. [Google Scholar] [CrossRef] [Green Version]
- Al-Soleiti, M.; Balaj, K.; Thom, R.P.; McDougle, C.J.; Keary, C.J. Brief Report: Suspected Cannabis-Induced Mania and Psychosis in Young Adult Males with Autism Spectrum Disorder. J. Autism Dev. Disord. 2021. [Google Scholar] [CrossRef] [PubMed]
- Powell, S.K.; O’Shea, C.; Townsley, K.; Prytkova, I.; Dobrindt, K.; Elahi, R.; Iskhakova, M.; Lambert, T.; Valada, A.; Liao, W.; et al. Induction of dopaminergic neurons for neuronal subtype-specific modeling of psychiatric disease risk. Mol. Psychiatry 2021. [Google Scholar] [CrossRef] [PubMed]
- Chakrabarti, B.; Persico, A.; Battista, N.; Maccarrone, M. Endocannabinoid Signaling in Autism. Neurotherapeutics 2015, 12, 837–847. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Minichino, A.; Senior, M.; Brondino, N.; Zhang, S.H.; Godwlewska, B.R.; Burnet, P.W.J.; Cipriani, A.; Lennox, B.R. Measuring Disturbance of the Endocannabinoid System in Psychosis: A Systematic Review and Meta-analysis. JAMA Psychiatry 2019, 76, 914–923. [Google Scholar] [CrossRef] [PubMed]
- Aran, A.; Harel, M.; Cassuto, H.; Polyansky, L.; Schnapp, A.; Wattad, N.; Shmueli, D.; Golan, D.; Castellanos, F.X. Cannabinoid treatment for autism: A proof-of-concept randomized trial. Mol. Autism 2021, 12, 6. [Google Scholar] [CrossRef] [PubMed]
- Pretzsch, C.M.; Voinescu, B.; Mendez, M.A.; Wichers, R.; Ajram, L.; Ivin, G.; Heasman, M.; Williams, S.; Murphy, D.G.; Daly, E.; et al. The effect of cannabidiol (CBD) on low-frequency activity and functional connectivity in the brain of adults with and without autism spectrum disorder (ASD). J. Psychopharmacol 2019, 33, 1141–1148. [Google Scholar] [CrossRef]
- Appiah-Kusi, E.; Mondelli, V.; McGuire, P.; Bhattacharyya, S. Effects of cannabidiol treatment on cortisol response to social stress in subjects at high risk of developing psychosis. Psychoneuroendocrinology 2016, 71, 23–24. [Google Scholar] [CrossRef]
- O’Neill, A.; Wilson, R.; Blest-Hopley, G.; Annibale, L.; Colizzi, M.; Brammer, M.; Giampietro, V.; Bhattacharyya, S. Normalization of mediotemporal and prefrontal activity, and mediotemporal-striatal connectivity, may underlie antipsychotic effects of cannabidiol in psychosis. Psychol. Med. 2020, 51, 596–606. [Google Scholar] [CrossRef]
- Larson, F.V.; Wagner, A.P.; Jones, P.B.; Tantam, D.; Lai, M.C.; Baron-Cohen, S.; Holland, A.J. Psychosis in autism: Comparison of the features of both conditions in a dually affected cohort. Br. J. Psychiatry 2017, 210, 269–275. [Google Scholar] [CrossRef]
- Colizzi, M.; Iyegbe, C.; Powell, J.; Ursini, G.; Porcelli, A.; Bonvino, A.; Taurisano, P.; Romano, R.; Masellis, R.; Blasi, G.; et al. Interaction Between Functional Genetic Variation of DRD2 and Cannabis Use on Risk of Psychosis. Schizophr. Bull. 2015, 41, 1171–1182. [Google Scholar] [CrossRef] [Green Version]
- Colizzi, M.; Burnett, N.; Costa, R.; De Agostini, M.; Griffin, J.; Bhattacharyya, S. Longitudinal assessment of the effect of cannabis use on hospital readmission rates in early psychosis: A 6-year follow-up in an inpatient cohort. Psychiatry Res. 2018, 268, 381–387. [Google Scholar] [CrossRef] [Green Version]
- D’Souza, D.C.; Cortes-Briones, J.A.; Ranganathan, M.; Thurnauer, H.; Creatura, G.; Surti, T.; Planeta, B.; Neumeister, A.; Pittman, B.; Normandin, M.; et al. Rapid Changes in CB1 Receptor Availability in Cannabis Dependent Males after Abstinence from Cannabis. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 2016, 1, 60–67. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Colizzi, M.; McGuire, P.; Giampietro, V.; Williams, S.; Brammer, M.; Bhattacharyya, S. Modulation of acute effects of delta-9-tetrahydrocannabinol on psychotomimetic effects, cognition and brain function by previous cannabis exposure. Eur. Neuropsychopharmacol. 2018, 28, 850–862. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Colizzi, M.; McGuire, P.; Giampietro, V.; Williams, S.; Brammer, M.; Bhattacharyya, S. Previous cannabis exposure modulates the acute effects of delta-9-tetrahydrocannabinol on attentional salience and fear processing. Exp. Clin. Psychopharmacol. 2018, 26, 582–598. [Google Scholar] [CrossRef] [PubMed]
- Colizzi, M.; Weltens, N.; Lythgoe, D.J.; Williams, S.C.; Van Oudenhove, L.; Bhattacharyya, S. Differential sensitivity to the acute psychotomimetic effects of delta-9-tetrahydrocannabinol associated with its differential acute effects on glial function and cortisol. Psychol. Med. 2020. [Google Scholar] [CrossRef] [PubMed]
- Colizzi, M.; Weltens, N.; McGuire, P.; Lythgoe, D.; Williams, S.; Van Oudenhove, L.; Bhattacharyya, S. Delta-9-tetrahydrocannabinol increases striatal glutamate levels in healthy individuals: Implications for psychosis. Mol. Psychiatry 2019. [Google Scholar] [CrossRef] [PubMed]
- Howes, O.D.; Kapur, S. The dopamine hypothesis of schizophrenia: Version III—The final common pathway. Schizophr. Bull. 2009, 35, 549–562. [Google Scholar] [CrossRef] [Green Version]
- Viñals, X.; Moreno, E.; Lanfumey, L.; Cordomí, A.; Pastor, A.; de La Torre, R.; Gasperini, P.; Navarro, G.; Howell, L.A.; Pardo, L.; et al. Cognitive Impairment Induced by Delta9-tetrahydrocannabinol Occurs through Heteromers between Cannabinoid CB1 and Serotonin 5-HT2A Receptors. PLoS Biol. 2015, 13, e1002194. [Google Scholar] [CrossRef] [Green Version]
- Coleman, M. Serotonin and central nervous system syndromes of childhood: A review. J. Autism Child. Schizophr. 1973, 3, 27–35. [Google Scholar] [CrossRef]
- Sasson, N.J.; Pinkham, A.E.; Ziermans, T.B. Editorial: Neurobiology and Cognition Across the Autism-Psychosis Spectrum. Front. Psychiatry 2021, 12, 654246. [Google Scholar] [CrossRef]
- Grace, A.A.; Moore, H.; O’Donnell, P. The modulation of corticoaccumbens transmission by limbic afferents and dopamine: A model for the pathophysiology of schizophrenia. Adv. Pharmacol. 1998, 42, 721–724. [Google Scholar] [CrossRef] [PubMed]
- Thapar, A.; Riglin, L. The importance of a developmental perspective in Psychiatry: What do recent genetic-epidemiological findings show? Mol. Psychiatry 2020, 25, 1631–1639. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- St Pourcain, B.; Eaves, L.J.; Ring, S.M.; Fisher, S.E.; Medland, S.; Evans, D.M.; Davey Smith, G. Developmental Changes Within the Genetic Architecture of Social Communication Behavior: A Multivariate Study of Genetic Variance in Unrelated Individuals. Biol. Psychiatry 2018, 83, 598–606. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- St Pourcain, B.; Robinson, E.B.; Anttila, V.; Sullivan, B.B.; Maller, J.; Golding, J.; Skuse, D.; Ring, S.; Evans, D.M.; Zammit, S.; et al. ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties. Mol. Psychiatry 2018, 23, 263–270. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Blest-Hopley, G.; Colizzi, M.; Prata, D.; Giampietro, V.; Brammer, M.; McGuire, P.; Bhattacharyya, S. Epigenetic Mediation of AKT1 rs1130233’s Effect on Delta-9-Tetrahydrocannabinol-Induced Medial Temporal Function during Fear Processing. Brain Sci. 2021, 11, 1240. [Google Scholar] [CrossRef]
- Crespi, B.; Badcock, C. Psychosis and autism as diametrical disorders of the social brain. Behav Brain Sci 2008, 31, 241–261. [Google Scholar] [CrossRef]
- Colizzi, M.; Ruggeri, M.; Bhattacharyya, S. Unraveling the Intoxicating and Therapeutic Effects of Cannabis Ingredients on Psychosis and Cognition. Front. Psychol. 2020, 11, 833. [Google Scholar] [CrossRef]
- Colizzi, M.; Weltens, N.; McGuire, P.; Van Oudenhove, L.; Bhattacharyya, S. Descriptive Psychopathology of the Acute Effects of Intravenous Delta-9-Tetrahydrocannabinol Administration in Humans. Brain Sci. 2019, 9, 93. [Google Scholar] [CrossRef] [Green Version]
- Ishiguro, H.; Horiuchi, Y.; Ishikawa, M.; Koga, M.; Imai, K.; Suzuki, Y.; Morikawa, M.; Inada, T.; Watanabe, Y.; Takahashi, M.; et al. Brain cannabinoid CB2 receptor in schizophrenia. Biol. Psychiatry 2010, 67, 974–982. [Google Scholar] [CrossRef]
- Du, Y.; Fu, Z.; Xing, Y.; Lin, D.; Pearlson, G.; Kochunov, P.; Hong, L.E.; Qi, S.; Salman, M.; Abrol, A.; et al. Evidence of shared and distinct functional and structural brain signatures in schizophrenia and autism spectrum disorder. Commun. Biol. 2021, 4, 1073. [Google Scholar] [CrossRef]
- Kern, J.K.; Geier, D.A.; King, P.G.; Sykes, L.K.; Mehta, J.A.; Geier, M.R. Shared Brain Connectivity Issues, Symptoms, and Comorbidities in Autism Spectrum Disorder, Attention Deficit/Hyperactivity Disorder, and Tourette Syndrome. Brain Connect. 2015, 5, 321–335. [Google Scholar] [CrossRef] [PubMed]
- Owen, M.J.; O’Donovan, M.C.; Thapar, A.; Craddock, N. Neurodevelopmental hypothesis of schizophrenia. Br. J. Psychiatry 2011, 198, 173–175. [Google Scholar] [CrossRef] [PubMed]
- Riglin, L.; Collishaw, S.; Richards, A.; Thapar, A.K.; Maughan, B.; O’Donovan, M.C.; Thapar, A. Schizophrenia risk alleles and neurodevelopmental outcomes in childhood: A population-based cohort study. Lancet Psychiatry 2017, 4, 57–62. [Google Scholar] [CrossRef] [Green Version]
- Rutter, M.; Kim-Cohen, J.; Maughan, B. Continuities and discontinuities in psychopathology between childhood and adult life. J. Child. Psychol. Psychiatry 2006, 47, 276–295. [Google Scholar] [CrossRef]
- Niarchou, M.; Zammit, S.; van Goozen, S.H.; Thapar, A.; Tierling, H.M.; Owen, M.J.; van den Bree, M.B. Psychopathology and cognition in children with 22q11.2 deletion syndrome. Br. J. Psychiatry 2014, 204, 46–54. [Google Scholar] [CrossRef] [Green Version]
- Bal, V.H.; Kim, S.H.; Fok, M.; Lord, C. Autism spectrum disorder symptoms from ages 2 to 19 years: Implications for diagnosing adolescents and young adults. Autism Res 2019, 12, 89–99. [Google Scholar] [CrossRef] [Green Version]
- Orinstein, A.; Tyson, K.E.; Suh, J.; Troyb, E.; Helt, M.; Rosenthal, M.; Barton, M.L.; Eigsti, I.M.; Kelley, E.; Naigles, L.; et al. Psychiatric Symptoms in Youth with a History of Autism and Optimal Outcome. J Autism Dev Disord 2015, 45, 3703–3714. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kessler, R.C.; McLaughlin, K.A.; Green, J.G.; Gruber, M.J.; Sampson, N.A.; Zaslavsky, A.M.; Aguilar-Gaxiola, S.; Alhamzawi, A.O.; Alonso, J.; Angermeyer, M.; et al. Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. Br. J. Psychiatry 2010, 197, 378–385. [Google Scholar] [CrossRef] [Green Version]
- McGorry, P.D.; Mei, C. Ultra-high-risk paradigm: Lessons learnt and new directions. Evid. Based Ment. Health 2018, 21, 131–133. [Google Scholar] [CrossRef]
- McGorry, P.D.; Mei, C. Early intervention in youth mental health: Progress and future directions. Evid. Based Ment. Health 2018, 21, 182–184. [Google Scholar] [CrossRef]
- Allen, D.; Gillen, E.; Rixson, L. The Effectiveness of Integrated Care Pathways for Adults and Children in Health Care Settings: A Systematic Review. JBI Libr. Syst. Rev. 2009, 7, 80–129. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fox, S.E.; Levitt, P.; Nelson, C.A. How the timing and quality of early experiences influence the development of brain architecture. Child Dev. 2010, 81, 28–40. [Google Scholar] [CrossRef] [PubMed]
- Hall, W.; Degenhardt, L. What are the policy implications of the evidence on cannabis and psychosis? Can. J. Psychiatry 2006, 51, 566–574. [Google Scholar] [CrossRef] [PubMed] [Green Version]
(a) | |||||||
---|---|---|---|---|---|---|---|
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: Summary of Evidence | ASD and Psychosis as a Function of the eCB System: Underlying Model |
Onaivi et al., (2011) (USA) [25] | 1. To assess THC-induced behavioral changes and 2. eCB system-related gene expression in ASD mice | 1. In vivo exposure in animals; 2. Quantitative tissue assessment in animals. | 1. Effects of THC: (a) VHI; (b) THC 1 mg/kg; (c) THC 10 mg/kg; 2. CB2 gene expression: non-injected mice. | X | 1. Behavior (MFT, FST); 2. Molecular assessment (Neurochemical Analysis of DA, 5HT, and their metabolites, RNA isolation, RT-PCR) | 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; 2. FST: (a) basal immobility time: BTBR < C57, S129; (b) basal immobility counts: BTBR > C57, S129; (c) BTBR group immobility time: VHI vs. THC (1, 10 mg/kg), NS; THC (1 mg/kg) vs. THC (10 mg/kg), NS; (f) BTBR group immobility count: VHI vs. THC (1, 10 mg/kg), NS; THC (1 mg/kg) vs. THC (10 mg/kg), NS; (g) THC (1, 10 mg/kg) did not modify the immobility time and counts of BTBR vs. C57 and S129; 3. CB2A gene expression in BTBR mice: cerebellum ↑; fontal cortex, striatum, NOCHG. | Diametral |
Anderson et al., (2015) (USA) [26] | To assess β-neurexin KO effect on eCB signaling in mice | 1. Quantitative brain assessment in animals; 2. In vitro measurement 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); 2. Behavior (OFT, Fear Conditioning); 3. Electrophysiology | 1. β-neurexin KO is associated with both ASD and SCZ; 2. β-neurexin KO leads to endocannabinoid-mediated inhibition of synaptic transmission and blocks LTP; 3. β-neurexins KO in CA1-region neurons impairs contextual fear memory; 4. LTP is restored by CB1 inhibition or 2-AG synthesis inhibition. | Overlapping |
Doenni et al., (2016) (Canada) [27] | 1. To assess adolescent social behavior and 2. eCBs/Aes brain levels following early inflammation in rats | 1. In vivo exposure in animals; 2. Quantitative brain assessment in animals. | 1. SIT (P40, n = 48): (a) LPS; (b) SAL; 2. OFT (P40, n = 32): (a) LPS; (b) SAL; 3. CB1 receptor binding (P40, n = 20): (a) LPS; (b) SAL; 4. eCB extraction and analysis: (a) P14, n = 39; (b) P40, n = 34; (c) €, n = 4; (d) VHI, n = 8; (e) FAAHi, n = 8; 5. FAAH activity assay (P40, n = 17): (a) LPS; (b) SAL; 6. Oral FAAHi administration (P14, n = 32): (a) LPS; (b) SAL; 7. BLA FAAHi injection (P30, n = 55): (a) LPS; (b) SAL. | 297 | 1. Molecular assessment (ecBs/AEs brain levels); 2. Behavior (SIT, OFT) | 1. LPS injection at P14 leads to impaired social behavior at P40; 2. AEA levels: (a) P14: LPS < SAL; (b) P40: LPS > SAL; 3. 2-AG levels (P14, P40): LPS vs. SAL, NS; 4. CB1 binding site density (P40): LPS < SAL; 5. FAAH activity (P40): LPS > SAL; 6. Oral FAAHi administration ↑ AEA and restores social behavior; 7. BLA FAAHi injection restores social behavior in female. | Overlapping |
Schrott et al., (2019) (USA) [28] | To assess cannabis-induced sperm DNA methylation changes and their intergenerational inheritance in rats | 1. In vivo exposure in animals; 2. Quantitative tissue assessment in animals. | 1. Adults: (a) THC: 7; (b) VHI: 8; 2. Offspring: (a) THC: 6; (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; 2. Offspring nucleus accumbens: CpG site 2 hypomethylated as in the sperm of THC exposed adults. | Developmental trajectory |
Schrott et al., (2020) (USA) [29] | To assess cannabis-induced sperm DNA methylation changes in rats | 1. In vivo exposure in animals; 2. Quantitative tissue assessment in animals. | 1. Oral administration: (a) THC: 9; (b) VHI: 8; 2. SC injection: (a) THC: 8; (b) VHI: 7. | 32 | Molecular assessment (DNA isolation from sperm, RRBS, Bisulphite conversion, Bisulphite pyrosequencing, qRT-PCR) | 1. Lrrtm4 DNA methylation in sperm: THC > VHI; 2. Shank1, Syt3, Nrxn1, Nrxn3, Dlg4, Grid1 DNA methylation in sperm: THC < VHI. | Developmental trajectory |
Wanner et al., (2020) (USA) [30] | 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; 2. ASD [Dlgap4 (3), Shank3 (3), Cadps2 (2), Arid1b (1), Camk2a (1), Lrfn2 (1), Prex1 (1), Shank2 (1), Tsc1 (1), Wdfy3 (1)] and SCZ [Nr4a2 (3), Shank3 (3), Srgap3 (2), Magi2 (1), Tcf4 (1)] are among the top 10 DO terms organized by DMLs and average DMLs/gene. | Overlapping |
(b) | |||||||
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: Summary of Evidence | ASD and Psychosis as a Function of the eCB System: Underlying Model |
Stringer et al., (2016) (Netherlands) [31] | 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; 2. CADM2: part of the SynCAM family, associated with ASD; 3. SCOC: regulation of gene expression through regulation of transcription factor binding; 4. KCNT2: potassium voltage-gated channel. | Developmental trajectory/Overlapping |
Aran et al., (2018) (Israel) [32] | 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; 2. In 29 insufficient responders, lower CBD:THC ratios (up to 6:1) led to a behavior improvement; 3. Higher CBD:THC ratio (up to 20:1) was well tolerated; 4. Lower CBD:THC ratio led to a serious psychotic episode requiring treatment with an antipsychotic. | Developmental trajectory/Diametral/Overlapping |
Guennewig et al., (2018) (Australia) [33] | To assess THC-induced gene alteration in hiPSC-derived neurons | 1. In vitro treatment exposure in humans; 2. Gene-based study in humans. | 1. Untreated; 2. Acute THC; 3. Chronic 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; 3. High overlap: subsets of genes involved in glutamate receptor pathway and mitochondrial function; 4. THC-altered transcripts: 80 genes linked to ASD, fewer genes linked to SCZ; 5. Overlap between THC and SCZ: WNT and mitochondrial signaling pathways. | Developmental trajectory |
Legge et al., (2019) (Netherlands) [34] | 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; 2. CNV: burden of SCZ- and NDDs-related CNV in individuals reporting PEs; 3. GWAS of any PEs: ANK3 intronic variant (rs10994278); 4. GWAS of distressing PEs: CNR2 (encoding for CB2) intronic variant (rs75459873), not associated with CU. | Developmental trajectory |
Schrott et al., (2019) (USA) [28] | To assess cannabis-induced sperm DNA methylation changes and their intergenerational inheritance | 1. Gene-based study in humans; 2. Quantitative tissue assessment in humans. | 1. Gene-based tests on sperm: (a) Users: 12; (b) Non-users: 12; 2. Brain tissue assessment: 28; 3. Testis tissue assessment: 3. | 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; 2. DLGAP2 DNA methylation in sperm: Cannabis-users < Non Cannabis-users; 3. Inverse relationship between DLGAP2 DNA methylation in brain and mRNA expression (female > male). | Developmental trajectory |
Schrott et al., (2020) (USA) [29] | To assess cannabis-induced sperm DNA methylation changes | 1. Gene-based study in humans; 2. Quantitative tissue assessment in humans. | Gene-based tests on sperm: 1. Users: 12; 2. Non-users: 12 | 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; 2. Bivalent chromatin marks: THC alters genes connected to ASD, which also present with future risk of disruption. | Developmental trajectory |
Al-Soleiti et al., (2021) (Netherlands) [35] | 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) [36] | To assess iDANs SEGs enrichment for psychiatric diseases | 1. Quantitative brain assessment in humans; 2. In vitro measurement in humans; 3. Gene-based study 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); 2. Electrophysiology. | 1. SEGs in iDANs are enriched for CUD, ASD and SCZ; 2. CUD and SCZ risk loci are enriched for unique subsets of SEGs in iDANs, iGANs, and iGLUTs; 3. ASD risk loci are only enriched in iDAN SEGs. | Overlapping |
(a) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
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) [25] | √ 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 t-test; ANOVA; Tukey’s test | √ |
Anderson et al., (2015) (USA) [26] | √ 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 t-test | √ |
Doenni et al., (2016) (Canada) [27] | √ Analytic, observational, interventional | √ Sprague Dawley rats | √ P14 and P40 | √ Male and female | √ SAL | √ 1. Double eCBs/AEs levels assessment (P14, P40); 2. FAAHi single administration (oral, BLA injection) | √ Inflammatory-induced animal model; Behavioral features | √ Inflammatory-induced animal model; Behavioral features | √ F-test; Bonferroni’s post hoc test; Student’s t-test; ANOVA | √ |
Schrott et al., (2019) (USA) [28] | √ 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 t-test; Bonferroni’s post hoc test; Pearson correlation | √ |
Schrott et al., (2020) (USA) [29] | √ 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 t-test; Bonferroni’s post hoc test; Pearson correlation; Fisher’s exact test | √ |
Wanner et al., (2020) (USA) [30] | √ 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 p-values | √ |
(b) | ||||||||||
Study | Study Design | Defined Study Population | Age | Gender | Control | eCB System Involvement | ASD Involvement | Psychosis Involvement | Statistical Analyses | Funding or Sponsorship |
Stringer et al., (2016) (Netherlands) [31] | √ 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) [32] | √ 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) [33] | √ Analytic, observational, interventional | √ General population: hiPSC-derived neurons | X | X | √ Untreated; SCZ hiPSC- derived neurons | √ 1. (a) Acute THC-exposure (1 μM for 24 h); (b) Chronic THC-exposure (50 nM; 5 treatments over 7 days); 2. Genetic liability | √ Genetic liability | √ Genetic liability; SCZ-like biological alterations | √ ANOVA; Tukey’s test for multiple comparisons | √ |
Legge et al., (2019) (Netherlands) [34] | √ Analytic, observational | √ MHQ | √ 64 (± 7.6) years | √ Male (44%) and female | √ nMHQ | √ Genetic liability | √ Genetic liability | √ 1. Psychotic symptoms; 2. Genetic liability | √ Logistic regression; Bonferroni’s correction | √ |
Schrott et al., (2019) (USA) [28] | √ Analytic, observational | √ General population: 1. Screened for (a) past 6-month CU; (b) UDS results; (c) [THCCOOH] in urine;2. Conceptal tissues from elective pregnancy termination | √ 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 t-test; Bonferroni’s post hoc test; Pearson correlation | √ |
Schrott et al., (2020) (USA) [29] | √ 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 t-test; Bonferroni’s post hoc test; Pearson correlation; Fisher’s exact test | √ |
Al-Soleiti et al., (2021) (Jordan) [35] | √ 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); 2. Self-prescribed sativa/indica mixtures (20 % THC); 3. Marijuana consumption (until 90% THC) | √ Diagnosed patients | √ Adverse event | X | X |
Powell et al., (2021) (USA) [36] | √ Analytic, observational | √ General population: 1. hiPSC derived iDANs; 2. Post-mortem samples | √ Post-mortem samples: adult brains | X | √ hiPSC derived 1. iGANs; 2. iGLUTs | √ Genetic liability for CUD | √ Genetic liability | √ Genetic liability | √ ANOVA; Tukey’s test for multiple comparisons; Bonferroni’s post hoc test | √ |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Colizzi, M.; Bortoletto, R.; Costa, R.; Bhattacharyya, S.; Balestrieri, M. The Autism–Psychosis Continuum Conundrum: Exploring the Role of the Endocannabinoid System. Int. J. Environ. Res. Public Health 2022, 19, 5616. https://doi.org/10.3390/ijerph19095616
Colizzi M, Bortoletto R, Costa R, Bhattacharyya S, Balestrieri M. The Autism–Psychosis Continuum Conundrum: Exploring the Role of the Endocannabinoid System. International Journal of Environmental Research and Public Health. 2022; 19(9):5616. https://doi.org/10.3390/ijerph19095616
Chicago/Turabian StyleColizzi, Marco, Riccardo Bortoletto, Rosalia Costa, Sagnik Bhattacharyya, and Matteo Balestrieri. 2022. "The Autism–Psychosis Continuum Conundrum: Exploring the Role of the Endocannabinoid System" International Journal of Environmental Research and Public Health 19, no. 9: 5616. https://doi.org/10.3390/ijerph19095616
APA StyleColizzi, M., Bortoletto, R., Costa, R., Bhattacharyya, S., & Balestrieri, M. (2022). The Autism–Psychosis Continuum Conundrum: Exploring the Role of the Endocannabinoid System. International Journal of Environmental Research and Public Health, 19(9), 5616. https://doi.org/10.3390/ijerph19095616