Autism spectrum disorder (ASD) is a complex behavioral condition with onset during early childhood and a lifelong course in the vast majority of cases. To date, no behavioral, genetic, brain imaging, or electrophysiological test can specifically validate a clinical diagnosis of ASD. However, these medical procedures are often implemented in order to screen for syndromic forms of the disorder (i.e., autism comorbid with known medical conditions). In the last 25 years a good deal of information has been accumulated on the main components of the “endocannabinoid (eCB) system”, a rather complex ensemble of lipid signals (“endocannabinoids”), their target receptors, purported transporters, and metabolic enzymes. It has been clearly documented that eCB signaling plays a key role in many human health and disease conditions of the central nervous system, thus opening the avenue to the therapeutic exploitation of eCB-oriented drugs for the treatment of psychiatric, neurodegenerative, and neuroinflammatory disorders. Here we present a modern view of the eCB system, and alterations of its main components in human patients and animal models relevant to ASD. This review will thus provide a critical perspective necessary to explore the potential exploitation of distinct elements of eCB system as targets of innovative therapeutics against ASD.
Key WordsAutism spectrum disorder endocannabinoid system fragile X syndrome metabolic regulation reward system
The Endocannabinoid System
Much like AEA, the biological activity of 2-AG is controlled through cellular mechanisms that include: 1) synthesis through rapid hydrolysis of inositol phospholipids by a specific phospholipase C to generate diacylglycerol that is then converted into 2-AG by a sn-1-specific diacylglycerol lipase (DAGL) ; and 2) degradation to AA and glycerol by a monoacylglycerol lipase (MAGL) , as schematically represented in Fig. 1. AEA and 2-AG can be also oxidized by cyclooxygenase-2, different lipoxygenase isozymes, as well as by cytochrome P450, to generate, respectively, prostaglandin–ethanolamides  and prostaglandin-glyceryl esters , hydroxy-anandamides and hydroxyleicosatetraenoyl-glycerols , and epoxy-eicosatrienoyl-glycerols .
An open question concerning eCB metabolism remains the transport of these compounds across the plasma membrane [19, 20]. As yet, the most accepted mechanisms are: 1) passive diffusion, which can be favored by the formation of AEA–cholesterol complexes, possibly in preferred microdomains called “lipid rafts” [21, 22]; 2) facilitated transport through a purported eCB membrane transporter ; and 3) endocytosis assisted by caveolins (reviewed in ). Once taken up, intracellular AEA reaches distinct sites, where distinct metabolic and signaling pathways take place. Heat shock protein 70, and albumin and fatty acid binding proteins 5 and 7 have been shown to act as eCB intracellular transporters, able to ferry AEA (and likely also 2-AG) within the cytoplasm to the nucleus and other destinations, including storage compartments like adiposomes [5, 25].
eCBs act principally through type-1 and type-2 (CB1 and CB2) cannabinoid receptors. Interestingly, CB1 but not CB2 resides within lipid rafts, and their interaction with these specialized microdomains influences signal transduction thereof . Additionally, eCBs are also able to interact with non-CB1/non-CB2 targets, such as 1) the transient receptor potential vanilloid type 1 channel, which is activated by both AEA and 2-AG [27, 28]; 2) peroxisome proliferator-activated receptor-α and peroxisome proliferator-activated receptor-γ ; and 3) the orphan G protein-coupled receptor GPR55 [30, 31]. By interacting with these receptors, eCBs trigger a multiplicity of signaling pathways that are involved in both physiological and pathological conditions . On a final note, the existence of compounds structurally related to eCBs, and collectively known as “eCB-like” substances, should be recalled because of their “entourage effect”. These compounds potentiate eCB activity at their receptors by increasing binding affinity or by inhibiting eCB hydrolysis [33, 34, 35]. A schematic representation of eCBs, their molecular targets, biosynthetic and hydrolizing enzymes, and extra- and intracellular transporters, is depicted in Fig. 1.
Autism Spectrum Disorder: Clinical Traits, Neuropsychological Deficits, and Neuroanatomical Underpinnings
Autism spectrum disorder (ASD) is a complex behavioral condition with onset during early childhood and a lifelong course in the vast majority of cases. It is characterized by deficits in communication and social interaction, as well as by stereotypic behaviors, restricted patterns of interest, and abnormal sensory issues . The diagnosis is based on clinical observation, substantiated by standardized testing of the patient with the Autism Diagnostic Observation Schedule-Generic , later revised into the Autism Diagnostic Observation Schedule-2 , and/or by parental interview with the Autism Diagnostic Interview-Revised . To date, no behavioral, genetic, brain imaging, or electrophysiological test can specifically validate a clinical diagnosis of ASD, although these medical procedures are regularly implemented in order to screen for syndromic forms of the disorder (i.e., autism due to known medical conditions). Two essential features distinguish ASD from most other behavioral disorders: 1) an impressive clinical and pathogenetic heterogeneity, which has led to the designaton, by the term “autisms”, of a set of neurodevelopmental disorders with early onset in life, sharing autism as a common feature, but produced through distinct processes ; 2) the distribution of autistic features as a dimensional continuum in the general population, which fully justifies referring to the “autism spectrum” rather than to a categorical distinction between “affected” and “unaffected” [41, 42]. As many as 1 in 68 (1.6 %) 8-year-old children receive an ASD diagnosis , with a male:female ratio of 4:1. Siblings of children already diagnosed with ASD have a significantly higher incidence of the same disorder, reported at 18.7 % in a prospective follow-up study , and ranging from 15 % to 25 % depending on sex and clinical severity. The prospective follow-up of these siblings later diagnosed with ASD has led to the observation that some behavioral abnormalities can appear very early on (e.g.,, sensory issues [e.g., extreme responses to certain sounds/textures, fascination with lights/spinning objects] are already present at 7 months of age), others emerge at 12–14 months (e.g., disengagement of visual attention), while the bulk of more typical autistic abnormalities has an onset between 14 and 24 months [45, 46, 47, 48]. Frequently, comorbid conditions include intellectual disability (65 %), seizures (30 %), and different forms of sleep problems [49, 50, 51]; less recognized, but equally impairing, are frequent psychiatric comorbidities, that include anxiety disorders, obsessive–compulsive disorders, and depression . Altered neurodevelopment during early pregnancy represents the neuropathological cause of ASD [53, 54]. Postmortem studies have unveiled neuroanatomical and cytoarchitectonic abnormalities in the cerebellum, inferior olivary complex, deep cerebellar nuclei, hippocampus, amygdala, entorhinal cortex, fusiform gyrus, and anterior and posterior cingulate cortex, with thinner cortical minicolumns, excessive growth of the frontal lobes, and excessive dendritic spine density . These abnormalities are suggestive of derangements occurring during the first/second trimester of pregnancy, namely reduced programmed cell death and/or increased cell proliferation, altered cell migration, abnormal cell differentiation with reduced neuronal body size, abnormal neurite sprouting, and pruning that result in atypical cell–cell wiring. In addition, neurodevelopmental mechanisms extending into late prenatal/postnatal life include reduced synapse formation and delayed myelination [40, 56, 57]. The latter result in abnormal neuronal wiring, which was previously believed to be characterized by long-range hypoconnectivity and local hyperconnectivity , but more recently has been shown to be a highly individualized mix of hyper- and hypoconnectivity specific to each single patient with ASD . These abnormalities have been associated with deficits in multiple behavioral tasks that relate to social behavior, such as empathy, theory of mind, joint attention, and face and emotion processing. Many of these observed behavioral features suggest a deficit in the social reward processing system in ASD, as we discuss in the following section. The neurocognitive phenotype in ASD stems from a complex and highly heterogeneous array of genetic and environmental causes, with patients ranging from “purely genetic” cases due to known ASD-causing chromosomal aberrations or mutations to “purely environmental” cases due to rare prenatal exposure to specific viral agents, drugs, and toxins [60, 61, 62]. In between these extremes, ASD for most cases fully qualifies for the definition of a “complex” disorder, whereby a host of rare and common genetic variants, often but not necessarily in conjunction with epigenetic factors , yield the neurodevelopmental abnormalities summarized above, resulting in autistic behaviors. Finally, neuroinflammation is also a frequent finding in postmortem brains of autistic individuals [64, 65]. It may represent a nonspecific consequence of insufficient neurite pruning and abnormal wiring of neural networks, resulting in elevated oxidative stress (possibly a common feature shared by several neurodevelopmental disorders) , but it could also stem from a broader immune dysfunction which, together with gastrointestinal disturbances and recurrent infections, collectively qualifies ASD as a systemic disorder [67, 68, 69, 70, 71].
Autism and Reward System
Both of these possible accounts of the social motivation hypothesis are faced with a key question. Do people with ASD find social stimuli rewarding or do they have a domain-general dysfunction of the reward system? To test these possibilities, a number of studies have compared processing of social and nonsocial reward stimuli in people with and without ASD. An early study using a continuous performance task found no behavioral evidence for group differences in trials with monetary rewards versus nonrewards . Similarly, comparable behavioral performance in a reward-processing task using a variant of the go–no-go task was found in children and adults with and without ASD [79, 80]. In contrast, using a similar task, DeMurie et al.  demonstrated that children with ASD were slower in responding to social rewards than monetary rewards, but this was not specific to ASD. Overall, the behavioral evidence summarized above appears equivocal about any circumscribed deficit in social reward processing in ASD. Yet, a main group effect in the majority of these studies points toward a domain-general deficit in the reward system. In contrast to the behavioral studies using button-press responses, eyegaze tracking, electroencephalography, and functional magnetic resonance imaging studies suggest clear differences in processing of social rewards in ASD compared with typically developed controls . Eyegaze tracking studies typically involve measuring gaze fixation patterns in response to social and nonsocial stimuli. Children and adults with ASD are found to look less at social stimuli than at nonsocial stimuli [83, 84, 85]. Gaze fixation patterns have often been used as proxy metrics related to reward processing , thus supporting the hypothesis of atypical processing of social rewards in ASD. Using electroencephalography in children with ASD, a recent study reported lower magnitude of a component related to reward anticipation (stimulus preceding negativity) in response to social versus nonsocial stimuli . Similarly, functional magnetic resonance imaging studies revealed lower activity in the ventral striatum in response to social stimuli (neutral faces) in individuals with ASD . The latter finding is consistent with the observation that a reduced ventral striatal response to happy faces was associated with lower self-reported empathy in individuals with and without ASD .
In sum, there is substantial evidence across different techniques to suggest atypical reward processing in ASD. Irrespective of their domain specificity, such functional differences in the reward circuit in ASD have important consequences for the processing of social stimuli. Atypical response to social rewards from an early age can result in deficits in learning about the social world, which, in turn, can lead to social behavioral impairments in adulthood.
Alterations of the eCB System in Autism
The complexities that make autism hard to understand, from the diagnostic criteria and clinical heterogeneity to the genetic/environmental causes that provoke communication and behavioral problems to the innovative therapies to be applied in order to give patients the best quality of life, encourage scientists to look at predictive biomarkers and/or therapeutic targets for the pharmacological management of this disorder [90, 91]. It is now clear that eCB system is altered in several neurodegenerative diseases and, very interestingly, that distinct elements of the eCB system in peripheral blood mirror these perturbations, providing novel and noninvasive diagnostic tools for several neuroinflammatory diseases [92, 93]. In addition, the eCB system controls emotional responses , behavioral reactivity to context , and social interaction . Thus, it can be hypothesized that alterations in this endogenous circuitry may contribute to the autistic phenotype. In this and the following sections, we critically discuss the evidence for this proposition from animal and human studies. Recent investigations have addressed the involvement of eCBs in autism, where, unfortunately, the role of these bioactive lipids remains poorly understood. Indeed, autism is uniquely human and there are only a few validated animal models (e.g., fmr1 knockout mice, BTBR mice, and valproic acid-treated rats), that display autistic-like features. Fragile X syndrome (FXS) is an inherited disorder caused by mutations in FMR1, which is translated into the fragile X mental retardation 1 protein, which, in turn, plays a role in the development of synapses [97, 98]. Expansion mutations of FMR1 produce autistic features in approximately 40 % of patients with FXS, and thus FXS provides a valuable model for identifying novel biomarkers/targets for autism and for dissecting the underlying neurochemical pathways . In the first study addressing eCB system in FXS, it has been reported that the ablation fmr1 gene causes a dysfunctional 2-AG metabolism, with increasing DAGL and MAGL activities in the striatum of fmr1–/– mutants, but unaltered striatal 2-AG levels . According to a more recent study , stimulation of 2-AG signaling could be a useful treatment for mitigating FXS symptoms because it is able to normalize synaptic activity through type I metabotropic glutamate activation; additionally, genetic or pharmacological attenuation of CB1-dependent signal transduction and blockade of the mammalian target of rapamycin pathway might provide alternative strategies to treat autistic patients .
Molecular markers of the endocannabinod (eCB) system in autism and related phenotypes in humans
Molecular markers of the eCB system in autism-related animal models
↑DAGL and MAGL activity
Rat valproic acid
= AEA, OEA, PEA and 2-AG levels
= AEA, OEA, PEA and 2-AG levels
↓PPAR-α and ↓GPR55 mRNA
↑AEA, ↑OEA, ↑PEA content*
↓PPAR-γ and ↓GPR55 mRNA
BTBR T + tF/J mouse
↑CB2A isoform mRNA
Additionally, it is worth noting that plasma levels of polyunsaturated fatty acids (which are components of eCBs) are lower in patients with autism, and that 2 derivatives of docosahexaenoic acid and eicosapentaenoic acid (also components of eCBs) are able to activate both CB1 and CB2 receptors . These data further suggest that a dysregulation of eCB signaling might be driven by diet, resulting in an imbalance of pro- and anti-inflammatory metabolites, and thus favoring the development of autism .
Suggested Roles of the eCB System in Autism
The first clue comes from a human neuroimaging study that measured striatal response to social rewards (happy faces vs neutral faces). This investigation found that common single nucleotide polymorphisms in CNR1 are associated with activity in the ventral striatal cluster in response to happy (but not to disgusted) faces , and later on it was replicated in an independent cohort . In view of the central role of the ventral striatum in reward processing, it is reasonable to infer that variation in CNR1 was linked to differences in sensitivity to social rewards such as happy faces. Another study in an independent sample used eyegaze tracking to show that the same CNR1 polymorphisms were associated with greater gaze duration to happy faces, but again not to disgust faces . A parallel population genetic study found a nominal association of the same CNR1 genetic variations with trait empathy . Individuals with ASD score low in trait empathy, and, consistent with this, a gene expression study in postmortem brains of individuals with autism had earlier reported a reduced expression of CB1 [120, 121]. In sum, multiple indirect lines of evidence suggest a role for CNR1 genetic variations in underlying social reward responsivity, a putative endophenotype for autism. These findings in human patients parallel observations in animal models that show a strong role for the eCB system in social play behavior, which is a proxy measure for social reward responsivity [122, 123].
A second clue for the role of eCB system in autism comes from observations in early neural development . Autism is neurodevelopmental in nature, and atypical development of neural connectivity has been suggested to underlie its key phenotypic features . A set of genes involved in neurodevelopmental processes that mediate the formation, stabilization, and pruning of synapses has been consistently associated with autism-related phenotypes in animal models [126, 127, 128]. Neuroligins (NLGN) represent a significant part of this set, and indeed several genes of NLGN family have been associated with autism . In a mouse model, an autism-associated mutation in NLGN3 was found to be associated with deficits in social behavior and disrupted tonic eCB signaling [130, 131]. Evidence from this study and several others (reviewed in ) provides a potential causal bridge between atypical neural development and potential dysfunction of the eCB system in autism.
A third clue comes from the role of the eCB system in influencing circadian rhythm in animal models [132, 133, 134]. Autism has been associated with atypical sleep patterns and circadian rhythms . Polymorphisms in ASMT (involved in melatonin synthesis), paralleled by reduced levels of circulating melatonin, have been reported in autism . Interestingly, the eCB system also plays a role in regulating circadian rhythms , thus making it a putative target to examine using animal models of autism-related phenotypes.
The fourth clue comes from comorbidities commonly observed in autism. First of these is anxiety, which is highly comorbid with autism (42–56 %). The eCB system, and cannabidiol in particular, is known to mediate anxiety and related phenotypes [137, 138]. Anecdotal reports of cannabis use in autism suggest a reduction in anxiety-related symptoms. A potential role for the eCB system in ASD can thus also be mediated through its influence on the anxiety-related component of the disease. The second commonly occuring comorbidity in autism relevant to the current review is epilepsy (up to 30 %). The eCB system is studied intensively as targets for potential antiepileptic drugs . It is therefore possible that a potential future drug acting on the eCB system is better able to ameliorate epilepsy-related comorbidities in ASD.
Accumulated evidence suggests that the eCB system constitutes a relatively less investigated piece of a puzzle that brings together 4 phenotypic features known to be atypical in autism: 1) social reward responsivity; 2) neural development; 3) circadian rhythm; and 4) anxiety-related symptoms. Therefore, the potential therapeutic exploitation of distinct elements of this system (e.g., receptor targets, biosynthetic and hydrolytic enzymes, and transmembrane/intracellular transporters) seems immense. As supported by the evidence presented in the previous sections in humans and animal models, any potential therapeutic approach is unlikely to involve a simple choice between activation versus inhibition of the eCB system to target specific features related to autism. Any such approach will need to be precisely tuned to the developmental timeline and to the specific pathogenetic underpinnings of autism in the single patient. Our understanding of eCB signaling in autism is still in its infancy compared with other disorders of the central nervous system or of peripheral tissues, where eCB-based therapies have already reached preclinical and clinical phases . However, research in this field is rapidly evolving, and novel drugs able to hit specifically a distinct element of the eCB system are developed at a surprising speed . Among them, those that target metabolic enzymes of eCBs, and, at the same time, key enzymes of oxidative pathways like cyclooxygenases seem to hold promise as next-generation therapeutics against human disorders with an inflammatory component , and therefore they will possibly result in also being beneficial for ASD. A second medium-term target could focus on the antiepileptic drugs that are being developed, focusing on the eCB system. These drugs could potentially ameliorate the epilepsy-related symptoms that commonly co-occur with ASD. On a final note, it seems of major interest that preliminary data, showing consistency between changes in distinct eCB system elements (i.e., CB2) in animal models of ASD and in peripherabl blood mononuclear cells from young patients with ASD [106, 107], support a role for these elements in the (early) diagnosis of the disease. Future work should test expression profiles for key players of the eCB system in prospective samples to test the potential of these as diagnostic biomarkers. In this context, it should be recalled that easily accessible biomarkers of neurological disorders are highly searched for, and some of them have been already identified to hold promise in human neurodegenerative/neuroinflammatory diseases .
This investigation was partly supported by Ministero dell’Istruzione, dell’Università e della Ricerca (PRIN 2010-2011 grant) to MM. BC was supported by Medical Research Council UK (grant: G1100359/1).
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- 11.Tsuboi K, Sun YX, Okamoto Y, Araki N, Tonai T, Ueda N. Molecular characterization of N-acylethanolamine-hydrolyzing acid amidase, a novel member of the choloylglycine hydrolase family with structural and functional similarity to acid ceramidase. J Biol Chem 2005;280:11082-11092.PubMedCrossRefGoogle Scholar
- 34.Costa B, Comelli F, Bettoni I, Colleoni M, Giagnoni G. The endogenous fatty acid amide, palmitoylethanolamide, has anti-allodynic and anti-hyperalgesic effects in a murine model of neuropathic pain: involvement of CB(1), TRPV1 and PPARgamma receptors and neurotrophic factors. Pain 2008;139:541-550.PubMedCrossRefGoogle Scholar
- 36.American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. American Psychiatric Association, Arlington, VA, 2013.Google Scholar
- 37.Lord C, Rutter M, DiLavore PC, Risi S. ADOS, Autism Diagnostic Observation Schedule. Western Psychological Services, Los Angeles, CA, 2002.Google Scholar
- 39.Rutter M, Le Couter A, Lord C. ADI-R, Autism Diagnostic Interview-Revised. Western Psychological Services, Los Angeles, CA, 2003.Google Scholar
- 40.Persico AM. Autisms. In: Neural circuit development and function in the healthy and diseased brain: comprehensive developmental neuroscience, vol. 3 (Rakic P. and Rubenstein J, eds). Elsevier, New York, 2013, pp. 651-694.Google Scholar
- 43.Developmental Disabilities Monitoring Network Surveillance Year 2010 Principal Investigators; Centers for Disease Control and Prevention (CDC). Prevalence of autism spectrum disorder among children aged 8 years – autism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveill Summ 2014;63:1-21.Google Scholar
- 103.Schultz ST. Can autism be triggered by acetaminophen activation of the endocannabinoid system? Acta Neurobiol Exp (Wars) 2010;70:227-231.Google Scholar
- 105.Liu QR, Pan CH, Hishimoto A, et al. Species differences in cannabinoid receptor 2 (CNR2 gene): identification of novel human and rodent CB2 isoforms, differential tissue expression and regulation by cannabinoid receptor ligands. Genes Brain Behav 2009;8:519-530.PubMedCentralPubMedCrossRefGoogle Scholar
- 111.Chiurchiù V, Battistini L, Maccarrone M. Endocannabinoid signaling in innate and adaptive immunity. Immunol 2015;144:352-364.Google Scholar