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Positron Emission Tomography in the Neuroimaging of Autism Spectrum Disorder

Written By

Zhiqiang Tan, Weijian Ye, Hao Xu and Lu Wang

Submitted: 04 July 2022 Reviewed: 28 July 2022 Published: 30 August 2022

DOI: 10.5772/intechopen.106825

Autism Spectrum Disorders IntechOpen
Autism Spectrum Disorders Recent Advances and New Perspectives Edited by Marco Carotenuto

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Autism Spectrum Disorders - Recent Advances and New Perspectives

Edited by Marco Carotenuto

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Abstract

Autism spectrum disorder (ASD) is a pervasive developmental disease characterized by persistent impairment, repetitive and stereotypical behaviors in social interaction, as well as restricted interests and activities. The etiology of ASD is not clear yet, which results in difficulties in clinical diagnosis and treatment, and also brings heavy burden to patients and society. Positron emission tomography (PET) is a frequently used molecular imaging technology in quantitative, dynamic and in vivo research for therapeutic efficacy evaluation, pathophysiological mechanism investigation, thereby promoting development of ASD therapeutic drugs. More and more imaging studies have been reported on ASD recently, and the physiological changes featured by PET have been disclosed. This chapter reviews the specific radioligands for PET imaging of critical biomarkers involved in ASD. Herein, we discuss cerebral blood perfusion, cerebral glucose metabolism, and neurotransmitter system (transporters, precursors and receptors), as well as some other novel targets, including arginine vasopressin receptor targets and neuroinflammation related targets. The status of application and future prospect of the PET technology in research of ASD were discussed. This chapter provides a detailed and comprehensive literature review on ASD PET probe development, thereby can help readers intuitively and conveniently understand the status quo of research on ASD PET, and develop new research directions in this field.

Keywords

  • autism spectrum disorder
  • ASD
  • neuroimaging
  • positron emission tomography
  • PET
  • radioligands

1. Introduction

Autism spectrum disorder (ASD) is a pervasive developmental disorder characterized by persistently impaired interpersonal communication and social interactions, significantly limited activities and interests, as well as repetitive, stereotyped and limited behaviors. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) published in 2013 revolutionized the ASD diagnostic criteria [1], and identified four previously defined pervasive developmental disorders that are now referred to as ASD: pervasive developmental disorder not otherwise specified (PDD-NOS), autistic disorder, childhood disintegrative syndrome (also known as Heller Syndrome), and asperger syndrome (AS). The diagnostic criteria were reduced to two items: social dysfunction, and stereotypical and repetitive behavior. The previous diagnostic criteria including and non-verbal and verbal communication disorders are ascribed to social disorders. These changes have impacted the diagnosis and therapy of a variety of pervasive developmental disorder subtypes, and influenced the comparability and consistency of imaging studies. Each document cited will be marked with “ASD/AS/AutismPDD” according to diagnostic criteria to avoid unnecessary confusion.

The understanding of etiology of idiopathic ASD is still not sufficient, and the current evidence indicates that ASD might be driven by affected synaptic function, cortical networks as well as brain maturations induced by environmental and genetic factor interactions. Obstetric complications and early childhood environmental influences may play critical roles in ASD development [2, 3]. Moreover, children who experience obstetric complications are also more likely to exhibit genetic causation of the disease [4]. The latest large gene study has identified 102 risk genes associated with ASD in human [5]. Most risk genes are closely correlated with neurodevelopment and neurophysiology and are expressed in early stage of brain development, especially in inhibitory and excitatory neurons, consistent with ASD-associated excitation/inhibition imbalances.

Currently, ASD diagnosis is mainly based on clinical evaluation and medical history of patients as well as medical history of patients’ families. Autism Diagnostic Interview Revised (ADI-R), a structured interview for patients’ family members [6], and the Autism Diagnostic Observation Schedule (ADOS), a play-based interview for children and their families or high-functioning children, adolescents, or adults [7] are two collection tools for medical history data, which are considered gold standard for clinical ASD diagnosis. ASD patients’ clinical evaluation mainly includes neurological and physical examinations [8], as well as neuroimaging. Though no specific biomarkers can be used for ASD diagnose thus far, neuroimaging techniques have exhibited potentials for explaining signs and symptoms in ASD [9], and have been applied in elucidation of pathophysiologic mechanisms underlying ASD-related abnormalities in neurotransmitter system, blood perfusion, and brain glucose metabolism in the past decades. Therefore, neuroimaging techniques will act as important tools in ASD diagnosis, therapeutics and efficacy evaluation.

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2. Positron emission tomography

Positron emission tomography (PET) detects processes associated with the metabolism and distribution of positron emitting radionuclide-labeled probes in vivo. The commonly used radionuclides include 11C (T1/2 ~ 20.4 min), 18F (T1/2 ~ 109.8 min), 13N (T1/2 ~ 10.0 min) and 15O (T1/2 ~ 2.0 min). It should be noted that radionuclides with short half-lives, such as 11C (T1/2 ~ 20.4 min) and 15O (T1/2 ~ 2.0 min), can only be used with onsite cyclotrons at tertiary medical centers. With the probe distribution in the body, nuclear decay occurs, emitting positrons, which collide with electrons surrounding to generate two gamma photons (511 keV each) in a 180° reverse manner. The gamma photon signals detected are then processed by computer software to generate three-dimensional images [10]. Compared to magnetic resonance imaging (MRI) and single photon emission computed tomography (SPECT), PET has significant advantages in spatial resolution, sensitivity, and time efficiency, and therefore is much more advantageous quantification of substantial parameters including protein synthesis rate, enzyme activity and receptor density, glucose metabolic rate, and gene expression.

Based on radioactive probe, PET imaging technology has dramatic advantages in detection a variety of receptors, transporters, metabolites, enzymes, as well as drugs. With microdose, PET tracers can be applied in preclinical and early clinical studies to investigate in vivo drug physiological performance, pharmacodynamics and pharmacokinetics, target occupancy, providing critical information for clinical trials [11]. PET probe can be used for both clinical diagnose and evaluation. More than 1000 PET probes have been developed and applied in numerous fields including labeling of metabolic analogs or substrates including fatty acids, amino acids, and glucose, the [12], labeling specific proteins, such as transporters or receptors [13, 14], as well as labeling in signal transduction, immunological features, hypoxia, angiogenesis, apoptosis and genes [15, 16]. PET probes as effective neuroimaging tools have high binding specificity and affinity, good brain penetration ability, and a good distribution volume and metabolic stability. Table 1 lists the main ASD research targets and the corresponding PET probes.

TargetPET probeChemical formulaClinical application
Glucose[18F]FDGC6H1118FO5Y
CBF[15O]H2OH215OY
[15O]CO2CO15OY
[11C]butanolC211CH8OY
5-HT
precursor		[11C]AMTC1111CH14N2O2Y
5-HTT[11C](+)McN5652C1811CH21NSY
[11C]DASBC1511CH17N3SY
[11C]MADAMC1511CH20N2SY
[18F]FMeNER-d2C18H18D218FNO3Y
[11C]ADAMC1411CH17IN2SN
[11C]DAPAC1411CH17BrN2SN
[11C]AFMC1511CH19FN2SN
5-HT2AR[18F]setoperoneC21H2418FN3O2SY
[11C]MDL100907C22H1818FNO3Y
[18F]altanserinC22H2218FN3O2SN
5-HT1AR[18F]MPPFC25H2718FN4O2Y
[18F]F13714C21H25ClF18FN4ON
OXT
OXTR		[11C]PF-3274167C1811CH19ClFN5O3N
[11C]EMPAC2211CH26N4O4SN
DA
precursor		[18F]FDOPAC9H1018FNO4Y
DAT[11C]WIN35,428C1511CH20FNO2Y
[11C]methylphenidate
[11C]cocaine		C14H19NO2
C17H21NO4		N
N
[18F]FE-PE2IC20H2518FINO2N
D2R[11C]NMSC2311CH28FN3O2Y
[11C]racloprideC1411CH20Cl2N2O3Y
D2R, D3R[18F]fallyprideC20H2918FN2O3N
[11C]-(+)-PHNOC1411CH21NO2N
D1R[11C]NNC112C1811CH18ClNO2N
[11C]SCH23390C1611CH18ClNOY
GABA
GABABR		[18F]1bC16H16Cl18FN2O3N
GABAAR[18F]FMZC15H1418FN3O3Y
[11C]Ro15–4513C1411CH14N6O3Y
AChE
receptor		[18F]FAC9H1118FN2ON
precursor[11C]MP4AC711CH15NO2Y
Leucine[11C]leucineC511CH13NO2Y
Glutamate
mGLuR5[18F]FPEBC14H718FN2Y
[11C]ABP-688C1411CH16N2ON
mGLuR1[11C]ITMMC1811CH18N5O2SN
mGLuR7[11C]MMPIPC1811CH15N3O3N
TSPO[11C]PK11195C2011CH21ClN2OY
[11C]DPA713C2011CH28N4O2N
[18F]FEPPAC22H2118FN2O3N
[11C]PBR28C2011CH20N2O3Y
[11C]ER176C1911CH20ClN3ON
[18F]GE180C20H2718FN2O2N
[18F]FEPPAC22H2118FN2O3N
P2X7R[11C]A-740003C2511CH30N6O3N
[11C]JNJ-717C1811CH17Cl2N5O2N
[18F]JNJ64413739C18H14F318FN6ON
[11C]SMW139C1811CH21ClF3NO2N
MAO-B[11C]SL25.1188C1511CH17F3N2O5N
COX-1[11C]PS13C1711CH16F3N3O3N
COX-2[11C]MC1C1611CH17N3O3S2N
CSF1R[11C]CPPCC2111CH27N5O2N
AVP
V1aR		[18F]SRX246
[11C]SRX246
[11C](1S,5R)-1
[11C]PF-184563		C42H4818FN5O5
C4211CH51N5O5
C2511CH30N2O2
C2011CH23ClN6		N
N
N
N

Table 1.

Summary of ASD research targets and their corresponding PET probes.

Abbreviations: Application, Whether applied in ASD research; CBF, Cerebral Blood Flow; 5-HT, 5-Hydroxytryptamine/Serotonin, 5-HT; 5-HTT, 5-Hydroxytryptamine Transporter/Serotonin Transporter; 5-HT2AR, Serotonin 2A Receptor; 5-HT1AR, Serotonin 1A Receptor; OXT, Oxytocin; OXTR, Oxytocin Receptor; DA, Dopamine; DAT, Dopamine Transporter; D1R, Dopamine D1 Receptor; D2R, Dopamine D2 Receptor; D3R, Dopamine D3 Receptor; GABA, γ-Aminobutyric Acid; GABAAR, γ-Aminobutyric Acid Type A Receptor; GABABR, γ-Aminobutyric Acid Type B Receptor; AChE, Acetylcholinesterase; mGLuR1, metabotropic Glutamate Receptor 1; mGLuR5, metabotropic Glutamate Receptor 5; mGLuR7, metabotropic Glutamate Receptor 7; TSPO, 18 kDa Translocator Protein; P2X7R, Purinergic P2X7 Receptor; MAO-B, monoamine oxidase B; COX-1, Cyclooxygenase 1; COX-2, Cyclooxygenase 2; CSF1R, Colony Stimulating Factor 1 Receptor; AVP, Arginine Vasopressin; V1Ar, Vasopressin 1a Receptor; Y, Yes; N, No.

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3. PET molecular imaging in ASD

The development of PET has provided noninvasive and dynamic technical support for the study of ASD in vivo [17]. Though the pathology and etiology of ASD remain unclear, during the past decades, PET has been widely applied in many fields of ASD research, and substantial valuable information and evidence has been obtained [18, 19, 20, 21, 22, 23, 24, 25, 26].

The neuroimaging studies on ASD have been reviewed in several articles with different focuses [25, 26, 27, 28]. Some focused on the state of ASD imaging research [26, 27]. Others focused on the application of specific neuroimaging techniques [28]. With the development of ASD PET probes, the newly research results need to be updated. In this review, we discuss neurotransmitter system (receptors, precursors, and transporters), cerebral blood perfusion, cerebral glucose metabolism, as well as some new research targets including arginine vasopressin receptor targets and neuroinflammation related targets. The current application and future prospect of PET technology in ASD research were discussed through summarizing both clear ASD pathophysiological mechanism and unclear research conclusions. This review provides a detailed comprehensive literature review on ASD PET probe development, thereby can help readers intuitively and conveniently understand the status quo of research on ASD PET more, and develop new research directions in this field.

3.1 Cerebral glucose metabolism

Glucose is the main energy source of brain cells, therefore, glucose metabolism can reflect brain function changes. [18F]fluorodeoxyglucose ([18F]FDG) is glucose analog, and can be taken up by brain cells, however, [18F]FDG cannot be used in glycolysis due to the absence of oxygen at site 2, therefore, [18F]FDG can be used to reflect glucose uptake and distribution in brain cells [29]. [18F]FDG is therefore very valuable in ASD PET research due to its excellent imaging characteristics, including a long half-life, short scanning time, mature preparation process, and relatively simple scanning process [25].

Brain glucose metabolism has been most frequently studied in ASD PET. Most studies have focused on changes in brain glucose metabolism in ASD patients. However, no consistent conclusion has been drawn FDG metabolism changes in ASD patients. As early as 1985, Rumsey et al., performed a brain [18F]FDG PET study and found that the cerebral glucose metabolism in ASD patients was more diffuse compared with that in controls [30]. However, most of the following [18F]FDG PET studies found a reduced brain glucose metabolism in ASD patients than controls except for specific brain regions [31, 32, 33, 34, 35, 36, 37, 38]. Chugani et al. observed reduced glucose metabolism in cerebellum, frontal cortex, anterior cingulate gyrus, right temporal cortex, and bilateral medial temporal regions in four autistic children with wine spotting [39]. The glucose metabolism asymmetry in frontal temporal lobe was different from the symptom in typical autism children. More studies showed that ASD patients exhibited either increased or decreased glucose metabolism in different regions of brain [40, 41, 42, 43, 44, 45]. In addition, earlier studies also reported no significant difference in cerebral glucose metabolism between the autism and control subjects [46, 47, 48]. No consensus has been drawn on glucose metabolism change in different specific brain regions in ASD patients, however, some common findings included decreased glucose metabolism in temporal lobe as well as abnormal glucose metabolism in the highly connected areas including the adjacent limbic cortex, parietal lobe, and frontal lobe, which is consistent with the anatomical connectivity between the associative and supratemporal cortexes [49, 50, 51] and is supported by findings on the brain functional network for glucose metabolism [52, 53, 54].

[18F] FDG PET is applied in both study of glucose metabolism changes in specific brain regions of ASD patients and ASD treatment evaluation via neuroimaging. An [18F]FDG PET study performed on fluoxetine treated ASD patients found that the glucose metabolic rate in the right frontal lobe, especially in the orbitofrontal cortex and anterior cingulate gyrus, was remarkably increased after treatment. Moreover, they found the patients with higher glucose metabolic rates in the anterior cingulate and medial frontal lobe before treatment exhibited a more significant response to fluoxetine, indicating that response to fluoxetine is closely correlated with baseline cingulate metabolism [55]. However, the cerebral glucose metabolism in ASD patients after treatment does not consistently exhibit an increasing glucose metabolism. Another [18F]FDG PET study conducted on a 14 years old ASD patient showed that after two years of treatment with nucleus accumbens (NAc) deep brain stimulation (DBS), the patient’s clinical symptoms were significantly improved with brain [18F]FDG PET results showing that the glucose metabolism in the occipital, frontal, and prefrontal cortexes was dramatically reduced after treatment [56]. Another [18F]FDG PET study was conducted on a 6 years old ASD patient to assess the efficacy of ketogenic diet (KD) treatment, a commonly used therapy for refractory epilepsy. Glucose metabolism bilateral local reduction was observed in the cerebellum, proximal meso-temporal lobe, and basal ganglia region in patient, and after a 12-month KD treatment, glucose metabolism was markedly decreased throughout the entire cerebral cortex [57], with the main brain cell energy changing from glucose to ketone bodies as the underlying mechanism [58, 59]. The findings taken together suggest that ASD therapy can alter the cerebral glucose metabolism state and improve patients’ clinical symptoms. The [18F]FDG PET application in glucose metabolism assessment can help screen subjects for further efficient clinical therapy, as well as evaluate treatment efficacy. It is worth noting that the effects of ASD therapeutic drugs targeting dopamine, 5-hydroxytryptamine, gamma-aminobutyric acid, as well as other neurotransmitter systems on brain glucose metabolism need further study.

3.2 Cerebral blood flow

The [15O]CO2 steady-state inhalation technique has been widely used in the early stages of PET imaging to study cerebral perfusion, but its reliability is insufficient. Imaging with probes that have a small relative molecular weight and are uncharged and fat-soluble (mainly [15O]H2O) are now more preferable. These probes can go through the blood–brain barrier, so the probe amount in brain cells is positively related to regional cerebral blood flow (rCBF), which is directly correlated with local brain function. Therefore, cerebral perfusion imaging can reflect the local brain function to a certain extent. To calculate rCBF, the dynamic intracranial distribution of probe in human body is recorded, and blood samples are collected continuously to assess the input function of carotid artery. With image processing, the radiation concentration-time curves are obtained for calculation of the rCBF values for different brain regions [60].

In early experiments, cerebral perfusion imaging was performed on 6 ASD patients and 8 normal controls after nasal inhalation of [15O]CO2 and no difference in rCBF was found [47]. These negative results may be due to the influence of [15O]CO2 absorption on cerebral perfusion imaging quality or limitations of early low-resolution PET cameras. High-resolution PET combined with statistical parameter mapping was able to find some local abnormalities that the low-resolution PET failed to detect [61]. In subsequent experiments, [15O]H2O was administrated to ASD patients via intravenous injection for cerebral perfusion imaging. The cerebral perfusion imaging was performed with patients carrying out various tasks or social functions such as listening, speaking, thinking, emotional processing, etc., and based on the voxel statistical parameters, the image data analysis was performed to compare perfusion in distinct brain regions between ASD patients and controls [62, 63, 64]. The different activation regions for different tasks shown by cerebral perfusion imaging were correlated with behavioral function control areas in brain. Due to the influence of factors, such as IQ and age on ASD patients’ ability to perform tasks, the results from different studies were not comparable. However, continuous studies revealed general rules for rCBF and brain function changes in ASD patients. When [15O]H2O PET was used to study the differences in rCBF in four ASD patients and five controls during a verbal task [63], it was found that the left frontal region 46 and right dentate nucleus were activated more during motor speech function while less during hearing, speech, and expressive language in ASD patients compared with controls. During speech expression, the thalamus exhibited similar intergroup differences with those in region 46. In 1999, [15O]H2O PET was used to explore differences in rCBF between five highly functioning adult ASD patients and five typical developing controls during a verbal task [65]. The results showed that the patients’ hearing was closely related to left hemisphere dominance reversal, and cerebellar and bilateral superior temporal gyrus rCBF decreased in ASD patients, indicative of reduced involvement of cerebellar in language expression and non-verbal auditory perception. These results are consistent with a previous report that dentate-thalamo-cortical pathway was affected by dys-serotonin synthesis in ASD boy patients, indicating the dentate-thalamo-cortical pathway atypical functional specialization, in line with brain regional-specific biochemical disorder in autism development [66]. Three studies using [15O]H2O to explore changes of rCBF in ASD patients during a language task observed decreased rCBF in the left temporal lobe area of patients’ brain and the resulted abnormal function of the temporal lobe, consistent with the glucose metabolism pattern changes in brains of ASD patients [61, 67, 68].

For task-state cerebral perfusion imaging, functional magnetic resonance such as arterial spin labeling (ASL) sequence has unique advantages [69]. Comparative studies or joint imaging with PET and fMRI will have a wider application in the future.

3.3 5-hydroxytryptamine system

5-hydroxytryptamine (5-HT)/serotonin, is a well-known inhibitory neurotransmitter, which regulates synaptogenesis and neuronal migration in brain development [70]. The abnormalities of the 5-HT system in autism were first reported in 1961 [71]. In a whole blood test study, 5-HT was found to be significantly increased in 23 children with autism and severe mental disability, and slightly increased in 7 children without autism but had severe mental disability. In contrast, normal level of 5-HT was tested in 12 children with mild mental retardation and four non-autistic and non-mentally handicapped children. Enhanced 5-HT levels in whole blood in ASD patients was further confirmed in follow-up studies; moreover, enhanced whole blood 5-HT levels were also detected in their immediate family members [21]. In addition, 5-HT antagonists can lead to improvement in ASD symptoms [72, 73, 74]. 5-HT has been most frequently tested in ASD studies, due to the close relationship between the 5-HT system and ASD. Based on the current ASD-related 5-HT PET imaging studies, the 5-HT system abnormalities in ASD patients mainly include decreased 5-HT transporters in brain, abnormal functions of brain 5-HT receptors, increased whole blood 5-HT levels, and disorder of 5-HT synthesis in brain.

3.3.1 5-HT precursor

Tryptophan hydroxylase is a precursor of 5-HT and α-methyl-L-tryptophan can specifically bind to tryptophan hydroxylase. Therefore, radio-labeled [11C]AMT has been widely used as a specific probe to measure 5-HT synthesis [75, 76]. Unilateral changes in 5-HT synthesis in the dentate-thalamo-cortical pathway in ASD patients were analyzed with [11C]AMT PET [66]. In all the 7 boys with autism tested but not in a girl with autism, 5-HT synthesis asymmetry was observed in cerebellar dentate nucleus, frontal cortex, and thalamus. Decreased 5-HT synthesis was observed in thalamus and left frontal cortex in 5 boys, while in thalamus and right frontal cortex in the other two boys. While increased 5-HT synthesis was detected in the contralateral dentate nucleus of all the 7 boys. Chugani et al. used [11C]AMT PET to test 5-HT synthesis in 30 children with autism, 8 non-autistic siblings of the patients, and 16 non-autistic children with epilepsy [77]. They found in a non-autistic child before 5 years old, 5-HT synthesis was more than twice that of an adult and then dropped to adult levels after 5 years. However, during the childhood of ASD patients, the whole-brain 5-HT synthesis reduced, but between 2 and 15 years old, it gradually increased, and reached a level 1.5 times that of the normal adult level with no gender difference. Age-dependent differences were observed in 5-HT synthesis between the epileptic and autism groups, as well as between the autism and sibling groups. Chandana et al. used [11C]AMT PET to study the relationship between language and handedness functions and serotonin synthesis local and global abnormalities in children with autism [78]. Abnormal 5-HT synthesis in multiple cortex including non-lateralization, left and right cortex was observed by analysis in 117 children with autism. A more severe language impairment was observed in ASD children with reduced AMT binding in the left cortex, while a higher autism prevalence was found in ambidextrous and left-handed ASD children with reduced AMT binding in the right cortex. The local or global serotonin system abnormal asymmetrical development may both cause faulty neural circuitry.

3.3.2 5-HT transporter

5-hydroxytryptamine transporter (5-HTT), also named serotonin transporter (SERT) can transfer 5-HT to 5-hydroxytryptamergic neurons. Dysregulation of 5-HTT and 5-HT system happens simultaneously in ASD patients, but the association between 5-HTT and ASD remains unclear. The current PET probes for 5-HTT study include [11C]DASB, [11C](+)McN5652, [11C]MADAM, and [18F]Fmener-D2.

[11C](+)McN5652 is the first probe used for 5-HTT imaging [79]. Nakamura et al. used [11C](+)McN5652 PET in study of 5-HTT in ASD patients, and found that the whole brain 5-HTT level in ASD patients was lower than controls [80]. [11C]DASB is more widely used probe than [11C](+)McN5652 due to its high reliability and repeatability resulted from its reversible high-affinity binding with 5-HTT [81]. However, different studies on 5-HTT in ASD patients using [11C]DASB reported different results. Girgis et al. did not find significant difference in 5-HTT between ASD and control groups [82]. Andersson et al., found significantly lower levels of 5-HTT in brain stem, gray matter, as well as nine gray matter subregions in ASD patients compared with controls [83], consistent with previous report that in ASD patients, 5-HTT level is decreased [84]. The different conclusions from different studies might be due to the heterogeneous study subjects, or different imaging for different ASD subtypes. The development of new probes for 5-HTT study (such as [11C]AFM, [11C]ADAM, and [11C]DAPA) will promote elucidation of the association between 5-HTT and ASD, and significantly improve our understanding of the ASD pathophysiological mechanisms [85, 86].

3.3.3 5-HT receptor

Totally 14 subtypes of 5-HT receptor (5-HTR) have been found until now. 5-HT can stimulate different subtypes of 5-HTR, thereby exerting different physiological effects. The relationship between 5-HTR content changes and ASD remains unclear. Among 5-HTR subtypes, only 5-HT1AR and 5-HT2AR have been used in studies of ASD PET. [18F]F13714 and [18F]MPPF are 5-HT1AR targeting probes, and [18F]Altanserin, [11C]MDL100907, and [18F]Setoperone are 5-HT2AR targeting probes.

[18F]Setoperone has a high specificity for 5-HT2AR [87]. Beversdorf et al., used [18F]Setoperone PET and found much less [18F]Setoperone binding in the thalamus of ASD patients compared with control group, however, no significant difference was observed in other regions [88]. Goldberg et al. used [18F]Setoperone PET and found a significant lower cortical 5-HT2AR binding potential (BPND) and also a lower cortical 5-HT2AR density in the parents of the ASD children when compared with the control group. A negative correlation was also observed between the platelet 5-HT levels and the cortical 5-HT2AR BPND in the parents of the ASD children [89]. These results were consistent with reduced 5-HT2AR expression and function observed in ASD patients, and also further elucidated the pathophysiological mechanism of elevated 5-HT level in ASD patients’ peripheral blood. Another study using probe [11C]MDL100907 observed no significant difference in regional [11C]MDL100907 BPND between adult patients with AS and controls [82].

A PET study using [18F]MPPF, a 5-HT1AR-specific probe was carried out on adult ASD patients and controls to study the correlations between gray matter volume (GMV), social personality, and 5-HT1AR binding potential [90], and found a regional negative relationship between 5-HT1AR BPND and GMV, while 5-HT1AR density was similar between ASD patients and controls. However, the correlations observed in control group between GMV, 5-HT1AR, and social personality scores in the striatum were not observed in the ASD group, suggesting in the striatum of ASD patients, there is a 5-HT system disturbance correlated with the changes of 5-HT1AR density.

With the development of probe, PET probes targeting other 5-HTR subtypes will be widely applied in ASD research, which can significantly improve elucidation of the ASD pathogenesis [25].

3.4 Oxytocin

Oxytocin (OXT) is a neuropeptide that plays an important role in the regulation of social behavior in mammals by interacting with oxytocin receptor (OTR). Previous studies have found abnormal OXT levels in patients with autism [91]. Numerous studies have demonstrated significantly improved social behavior in ASD patients resulted from intranasal OXT treatment. Guastella et al. reported a significantly improved ASD patient performance in an eye-mind task after administration of OXT via intranasal inhalation [92]. FMRI studies showed that after OXT treatment, several brain regions exhibited enhanced responses to stimuli in ASD patients [93, 94].

Unfortunately, PET probes targeting OTR satisfactorily have yet to be successfully developed. The probes [11C]EMPA [95] and [11C]PF-3274167 [96] have not been widely applied because their physical and chemical properties are not unsatisfactory. 5-HT and OXT are integrated both in structure and function, mediating emotion-based behavior. The amygdala is the key area for 5-HT regulation by OXT. OXT can inhibit the activity of amygdala and reduce anxiety; in contrast, dysregulation of 5-HT and high activity of amygdala are correlated with enhanced anxiety. Substantial studies have been performed to investigate 5-HT system changes after treatment with OXT and further explore the functions and related mechanisms of OXT in ASD. Using [18F]MPPF PET, Mottolese et al. detected changes of 5-HT1AR in the brain after OXT treatment, and found that OXT enhanced [18F]MPPF BPND in the dorsal raphe nucleus (the core region for 5-HT synthesis), orbitofrontal cortex, insula, and amygdala/hippocampus complex [97]. Using [18F]MPPF PET, Lefevre et al. did not find significant difference in the 5-HT1AR distribution and content between ASD patients and controls [98]. However, they found OXT dramatically enhanced [18F]MPPF BPND in some regions of brain in control group, but not in ASD group. Using [11C]DASB PET, Hirosawa et al. observed significantly increased [11C]DASB BPND in the left inferior and left middle frontal gyrus in ASD patients after treatment with OXT. However, no close relationship was found between [11C]DASB BPND and symptom changes in clinic [99]. Taken together, these studies revealed the inhibitory effect of OXT on 5-HT signaling, and the relationship between serotonergic system changes and prosociality after treatment with OXT. The relationship between OXT and ASD needs further studies.

3.5 Dopamine system

Dopamine (DA) is a neurotransmitter of catecholamine, and it is involved in various central nervous system functions, including social motivation and social reward. A correlation between DA transporter and receptor-associated gene mutations and ASD clinical symptoms has been reported by numerous studies [100, 101, 102]. Some DA system-targeting psychotherapeutic medicines have exhibited good efficacy in improving ASD clinical symptoms, suggesting the critical roles of DA system in mediating behaviors of ASD patients. Many PET studies have been conducted on DA system, however, no consensus has been drawn on changes of DA transporters, receptors and precursor in the brains of ASD patients.

3.5.1 DA precursor

Dopa, the precursor of DA, can be absorbed, metabolized, and stored by dopaminergic endings, and [18F]FDOPA imaging can be used to analyze DA synthesis in brain. Using [18F]FDOPA PET, Ernst et al. analyzed the brain DA synthesis difference between 14 ASD children and controls [103], and they found a 39% reduction in DA ratio in anterior medial prefrontal cortex/occipital cortex of ASD children compared with controls. Another study found increased [18F]FDOPA inflow value (Ki) in the striatum and frontal cortex of ASD patients compared with control group [104]. However, other similar studies did not detect significant difference in dopamine production by striatum between ASD patients and controls [105, 106]. The inconsistent results of these studies might be due to the heterogeneity of the study subjects.

3.5.2 DA transporter

A study using [11C]McN-5652 to detect 5-HTT and using [11C]WIN-35,428 to measure DAT observed a remarkably higher DAT binding in the orbital prefrontal cortex of ASD patients when compared with controls. Moreover, in the orbitofrontal cortex of ASD patients, the DAT binding was inversely correlated with 5-HTT binding [80].

3.5.3 DA receptor

Fernell et al. conducted a PET study using [11C]NMS on ASD children treated with R-BH4 (a tyrosine hydroxylase cofactor in the serotonin and catecholamine biosynthesis pathways), and found a 10% reduction of dopamine receptor 2 (D2R) from pre-treatment abnormally high levels to after treatment normal levels in the caudate and putamen of ASD children compared with controls with improvement in ASD symptoms [107]. Fujino et al. used [11C]SCH23390 PET to explore the differences in dopamine receptor 1 (D1R) between ASD patients and controls, and they found the D1R binding in the anterior cingulate cortex, striatum, and temporal cortex was positively correlated with emotional perception scores, while negatively correlated with ASD detail attention scores [108]. However, no significant differences were observed in the anterior cingulate cortex, striatum, and temporal cortex. Another study using [11C]raclopride PET found decreased D2R/D3R binding in left caudate nucleus and bilateral putamen in ASD group compared with the control group [109].

3.6 Amino acid neurotransmitters

Protein synthesis is critical and necessary for a series of processes in the brain, including long-term memory, synaptic plasticity, and experience-dependent development. Atypical synapse protein synthesis is very important in ASD due to the close correlation between ASD and single-gene mutations, such as in neuroprotein 1, shank 3, and glial 3/4 [110]. The basic protein components are amino acids, therefore, quantitative analysis of amino acids and their receptors can help reveal abnormal protein synthesis in ASD.

3.6.1 Gamma-aminobutyric acid

Gamma-aminobutyric acid (GABA) is a key inhibitory neurotransmitter, which plays a crucial role in regulation of development and synaptic pruning. GABA dysfunction can induce imbalance in excitation/inhibition of the nervous system, which is closely correlated with ASD [111]. Previous human genetics studies found numerous mutations in the GABAA receptor gene as well as genes related to GABA synthesis in ASD patients [112, 113]. Autoradiography studies revealed reduced GABAA in the hippocampus and anterior cingulate cortex of ASD patients [114, 115]. Studies on rodent ASD models of found a prolonged neuronal excitation caused by early GABA inhibition, which may be an underlying ASD induction mechanism [116]. A substantial evidence indicates that GABA changes might relate to ASD, however, current PET studies on GABA are very few.

PET has been widely used to explore the roles of GABA in ASD pathogenesis. A study performed by Mendez et al. using [11C]RO15–4513 PET found markedly decreased GABAA α5 subtype levels in the bilateral amygdala and NAc in the brains of ASD patients compared with controls [117]. These results provide support for further study of GABA system abnormalities in ASD patients. However, another study using [18F]FMZ or [11C]RO15–4513 did not find differences in either GABAA receptors or GABAA α5 subtype in any region of the brain between ASD and control groups [118]. Fung et al. measured GABA concentrations using 1H-MRS and total GABAA receptor densities using [18F]FMZ PET. [18F]FMZ PET showed no significant difference in GABAA receptor density in the left dorsolateral prefrontal cortex (DLPFC) and bilateral thalamus between the ASD and control groups However, 1H-MRS detection revealed a significantly higher GABA/Water ratio in the left DLPFC of ASD patients compared to the control group [119].

3.6.2 Glutamate

Due to the imbalance in brain excitation/inhibition in ASD patients, glutamate is also a focus of ASD neuroimaging research [120]. A series of glutamate receptor specific probes including [11C]ITMM, [11C]MMPIP, and [18F]FPEB have been reported, which can specifically bind to metabolic glutamate receptor 1 (mGluR1), metabolic glutamate receptor 7 (mGluR7), and metabolic glutamate receptor 5 (mGluR5), respectively [121, 122, 123, 124]. However, only [18F]FPEB has been widely applied in clinical ASD PET research.

The correlation between glutamate system imbalance and ASD has been demonstrated by animal model studies using [18F]FPEB PET. of a Shank3 complete knockout mouse model (Shank3B−/−) showed that of A significantly increased mGluR5 BPND was observed in the thalamus, striatum, amygdala, and hippocampus in Shank3B−/− mice compared with normal mice as shown in [18F]FPEB PET imaging [125]. Using [18F]FPEB PET, Fatemi et al. found a remarkably higher [18F]FPEB BPND in the cerebellum and posterior central gyri of ASD patients [126]. A negative relationship between [18F]FPEB BPND and age was observed in the cerebellum, but not in the posterior central gyrus. A positive relationship was observed between precuneus [18F]FPEB BPND and sleepiness scale score on the Abnormal Behavior Checklist (ABC), while a negative relationship was observed between cerebellar [18F]FPEB BPND and ABC hyperactivity subscale, ABC inappropriate speech subscale, and ABC total score. These results showed altered mGluR5 binding in key regions of ASD patient brains, indicative of abnormal glutamate signaling in these areas, which might influence ASD symptoms. Brašićet al., used [18F]FPEB PET to study the mGluR5 distribution in brain of patients with fragile X syndrome (FXS), TD and idiopathic autism spectrum disorder (IASD) [127], and they observed a significantly increased mGluR5 expression in the cortical regions of IASD patients when compared with TD patients, while they observed a significantly decreased mGluR5 expression in all regions of FXS patients when compared with TD patients.

Currently, some mGluR7 and mGluR1 probes are also under investigation. Future imaging studies will elucidate more pathophysiological mechanisms of glutamate in ASD.

3.6.3 Leucine

Leucine impacts neuron protein synthesis and plays a critical role in dendritic spines regulation, therefore functions in neuropsychiatric diseases [128]. Shandal et al. investigated the leucine involvement in protein synthesis using [11C]Leucine PET [129], and found increased protein synthesis in the temporal lobe language region of stunted children with PDD. Consistently, previous studies showed abnormal protein synthesis in the language region and abnormalities in the temporal lobe region of children with PDD and developmental delay. However, another study reported no significant differences in cerebral protein synthesis between patients with Fragile X syndrome and controls using [11C] Leucine PET for measurement [130]. In contrast, another study using robust radiolabeled assay found decreased protein synthesis in peripheral blood mononuclear cells (PMCS) and platelets of patients with Fragile X syndrome when compared with controls [131]. Taken together, these studies suggest that more research is needed to demonstrate the correlation between leucine abnormality and ASD.

3.6.4 Acetylcholine

A series of studies showed that inhibition of acetylcholinesterase (AChE) attenuated inattention, aggression, and overall ASD symptoms in both ASD patients and ASD animal models [132, 133, 134], indicative of the critical roles of the cholinergic system in ASD etiology. However, only one PET study was reported. A lack of cholinergic innervation was observed in the fusiform gyri of ASD patients when using the acetylcholine analog [11C]MP4A to detect the activity of acetylcholinesterase [135]. Additional targeted PET studies in the future will help clarify the role of cholinergic dysfunction in the pathogenesis of ASD.

3.7 Neuroinflammation

Immune-mediated mechanisms are considered to be among the pathophysiological factors leading to ASD [136]. Inflammation including microglial activation and related changes of microglial pathology has been found in central nervous system of ASD patients, and many psychotropic agents have exhibited direct effect on microglia [137]. However, the correlation between microglia and ASD remains unclear.

Microglia play critical roles in development of immunity and central nervous system. The translocator protein (TSPO) is an important neuroinflammation imaging biomarker, which is overexpressed in activated microglia. A series of TSPO probes have been developed including [11C]PK11195, the first generation, [18F]FEPPA, [11C]PBR28 and [11C]DPA713, the second generation and [11C]ER176 and [18F]GE180, the third generation [138, 139]. Suzuki et al. investigated microglia activation differences between ASD patients and controls using [11C]PK11195 [140], and they found increased [11C]PK11195 binding in prefrontal cortex, fusiform gyrus, midbrain, cerebellum and cingulate cortex in ASD patients compared with controls. Another study using [11C]PBR28 reported a lower regional TSPO expression in bilateral precuneus/posterior cingulate gyrus, bilateral temporal gyrus, bilateral insular cortex, superior limbic gyrus, and angular gyrus of brain in ASD patients than in controls [141]. These two studies reported inconsistent results, possibly due to the heterogeneity of ASD patients or the influence of TSPO gene polymorphism. The applications of more TSPO probes have been reported [142, 143, 144, 145]. Future imaging studies will help us understand the relationship between neuroinflammation and ASD.

A series of novel neuroinflammation targets and corresponding probes have been developed including cyclooxygenase (COX)-1 and its specific probe [11C]PS13, monoamine oxidase B (MAO-B) and its specific probe [11C]SL25.1188, colony-stimulating factor 1 receptor (CSF1R) and its specific probe [11C]CPPC, and purinergic P2X7 receptor (P2X7R) and its specific probes [11C]JNJ-54173717 (JNJ-717), [18F]JNJ-64413739, and [11C]SMW139, as well as cyclooxygenase (COX)-2 and its specific probe [11C]MC1. These probes have been successfully applied in neuroimaging to explore the potential functions of these targets in neuroinflammation, as well as the potential relationships with ASD [24].

3.8 Arginine vasopressin

Arginine vasopressin (AVP) plays a series of physiological roles in mammals including increasing blood pressure, regulating social behavior, releasing adrenal corticosteroid, as well as antidiuretic activity [146, 147]. Since early animal studies have found that AVP plays critical roles in regulating biosocial behaviors, including parentage, mating, aggression and sociability, an increasing number of studies have focused on the correlation between AVP and ASD [148, 149, 150]. Regarding the differences in AVP contents between ASD patients and controls, although no consistent conclusion has been drawn, AVP related signaling pathways have been demonstrated to be promising and studies on them could help ASD diagnosis and treatment [151, 152, 153, 154]. V1a receptor antagonists have been shown to be able to regulate AVP functions, thereby improving the ASD symptoms. A novel V1a receptor antagonist of Balovaptan can improve the Vineland-II Adaptive Behavior Scale (including social interaction, daily living skills, and secondary endpoints of communication) in ASD adults [155], but not in ASD children and adolescents [156]. The V1a receptor has become a new focus of ASD research, and a series of V1a receptor probes including [11C]SRX246, [18F]SRX246 [157], [11C](1S,5R)-1 [158], and [11C]PF-184563 [159] have been developed recently. These PET probes have exhibited their values in in autoradiography and animal studies, however, they have not been applied in human studies yet. The development of PET probes that can be widely used inhuman ASD studies will help elucidate the relationship between AVP and ASD.

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4. Conclusion

ASD is a disease induced by both environmental and heredity factors, and its major cause and induction process still remain unclear. Early and clear diagnosis of ASD is conducive to improving ASD symptoms in patients, thereby affecting treatment efficacy. PET can be applied to quantitatively and dynamically evaluate cerebral glucose metabolism, task and resting states, neurotransmitter system biomarkers, and cerebral blood flow perfusion, explore ASD pathophysiology, and promote ASD therapeutic drug development, as well as in ASD diagnosis and treatment. The identification of ASD biomarkers and PET probes is critical in ASD diagnosis, and drug development and evaluation. Numerous ASD associated biomarkers have been identified in cerebral blood perfusion, glucose metabolism, neuroinflammation, and neurotransmitter systems. However, due to the differences in ASD subtypes, experimental design (e.g., imaging conditions, anesthesia/sleep/awake, and/or task-state/resting-state), and subjects (e.g., gender, IQ and age), contradictory conclusions may be drawn from different studies [160]. There a limitation in the current ASD studies. The PET imaging studies showed that there might be differences in the pathophysiological mechanisms for different ASD subtypes and therefore different results may be observed and different conclusions may be drawn for different ASD subtypes. Therefore, more attention should be paid on this in future ASD PET studies to explore the possible differences in the pathophysiological mechanisms of different ASD subtypes, and selection of experimental subjects and design of experiments should be determined and performed based on these differences to provide more valuable references for clinical diagnosis and treatment of ASD [161].

In this chapter, several ASD related targets, including cerebral blood perfusion, cerebral glucose metabolism, neuroinflammation, arginine vasopressin receptor, neurotransmitter system, as well as the corresponding probes and their applications in ASD imaging studies and the experimental results are summarized. PET studies using different probes can obtain similar results, while PET studies using the same probe can also produce different results due to the heterogeneity of ASD patients and the influence of TSPO gene polymorphism [162]. Therefore, although identify new biomarkers and develop novel PET probes are very helpful for ASD study, evaluation the application value of each probe in the existing system is difficult. Therefore, it is crucial to seek and investigate the associations between a probe, a biomarker, and a specific ASD subtype at molecular level [163], which is the most valuable exploration direction in future ASD studies.

PET molecular imaging is very helpful for ASD diagnosis and treatment, however, there are still some limitations and difficulties in execution. First, patients are required to lie on a machine for PET/MR and PET/CT scanning, and protection from radiation is required during the imaging process, so high coordination of patients is very important. Second, ASD patients often have a large age span and significant differences in IQ , so professional technicians need to train some patients to make them get familiar with drug injection, task process or even anesthesia operation and adapt to scanning environment. Therefore, the joint efforts of patients, doctors, technicians, nurses, researchers, as well as other specialists in neuropsychiatry, rehabilitation, and nuclear medicine to promote continuous advancements in ASD research, diagnosis and treatment.

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Acknowledgments

We would like to thank the support of K.C. Wong Education Foundation (China). This work was financially supported by the National Natural Science Foundation of China (No. 82071974 and No. 82102107), and the Science and Technology Program of Guangzhou, China (202206010106).

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Conflicts of interest

The authors declare no conflicts of interest.

References

  1. 1. Association AP. Diagnostic and Statistical Manual of Mental Disorders (DSM-5). 5th ed. Arlington, VA: Author; 2013
  2. 2. Brasic JR, Holland JA. Reliable classification of case-control studies of autistic disorder and obstetric complications. Journal of Developmental and Physical Disabilities. 2006;18(4):355-381
  3. 3. Brasic JR, Holland JA. A qualitative and quantitative review of obstetric complications and autistic disorder. Journal of Developmental and Physical Disabilities. 2007;19(4):337-364
  4. 4. Katsanis N. The continuum of causality in human genetic disorders. Genome Biology. 2016;17(1):233
  5. 5. Satterstrom FK, Kosmicki JA, Wang J, Breen MS, De Rubeis S, An JY, et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell. 2020;180(3):568-84.e23
  6. 6. Le Couteur A, Lord C, Rutter M. The Autism Diagnostic Interview-Revised (ADI-R). Los Angeles, CA: Western Psychological Services; 2003
  7. 7. Lord C, Rutter M, DiLavore PC, Risi S, Gotham K, Bishop S. Autism Diagnostic Observation Schedule: ADOS-2. Los Angeles, CA: Western Psychological Services; 2012
  8. 8. Brasić JR, Barnett JY, Kowalik S, Tsaltas MO, Ahmad R. Neurobehavioral assessment of children and adolescents attending a developmental disabilities clinic. Psychological Reports. 2004;95(3 Pt 2):1079-1086
  9. 9. Walton E, Turner JA, Ehrlich S. Neuroimaging as a potential biomarker to optimize psychiatric research and treatment. International Review of Psychiatry. 2013;25(5):619-631
  10. 10. Volkow ND, Mullani NA, Bendriem B. Positron emission tomography instrumentation: An overview. American Journal of Physiologic Imaging. 1988;3(3):142-153
  11. 11. McCluskey SP, Plisson C, Rabiner EA, Howes O. Advances in CNS PET: The state-of-the-art for new imaging targets for pathophysiology and drug development. European Journal of Nuclear Medicine and Molecular Imaging. 2020;47(2):451-489
  12. 12. Shiue CY, Welch MJ. Update on PET radiopharmaceuticals: Life beyond fluorodeoxyglucose. Radiologic Clinics of North America. 2004;42(6):1033-1053 viii
  13. 13. Smith GS, Koppel J, Goldberg S. Applications of neuroreceptor imaging to psychiatry research. Psychopharmacology Bulletin. 2003;37(4):26-65
  14. 14. Gjedde A, Wong DF, Rosa-Neto P, Cumming P. Mapping neuroreceptors at work: On the definition and interpretation of binding potentials after 20 years of progress. International Review of Neurobiology. 2005;63:1-20
  15. 15. MacLaren DC, Toyokuni T, Cherry SR, Barrio JR, Phelps ME, Herschman HR, et al. PET imaging of transgene expression. Biological Psychiatry. 2000;48(5):337-348
  16. 16. Jain M, Batra SK. Genetically engineered antibody fragments and PET imaging: A new era of radioimmunodiagnosis. Journal of Nuclear Medicine. 2003;44(12):1970-1972
  17. 17. Syed AB, Brasic JR. Nuclear neurotransmitter molecular imaging of autism spectrum disorder. AIMS Molecular Science. 2019;6(4):87-106
  18. 18. Schifter T, Hoffman JM, Hatten HP Jr, Hanson MW, Coleman RE, DeLong GR. Neuroimaging in infantile autism. Journal of Child Neurology. 1994;9(2):155-161
  19. 19. Rumsey JM, Ernst M. Functional neuroimaging of autistic disorders. Mental Retardation and Developmental Disabilities Research Reviews. 2000;6(3):171-179
  20. 20. Chugani DC. Neuroimaging and neurochemistry of autism. Pediatric clinics of North America. 2012;59(1):63-73 x
  21. 21. Hwang BJ, Mohamed MA, Brašić JR. Molecular imaging of autism spectrum disorder. International Review of Psychiatry. 2017;29(6):530-554
  22. 22. Wolff JJ, Jacob S, Elison JT. The journey to autism: Insights from neuroimaging studies of infants and toddlers. Development and Psychopathology. 2018;30(2):479-495
  23. 23. Girault JB, Piven J. The neurodevelopment of autism from infancy through toddlerhood. Neuroimaging Clinics of North America. 2020;30(1):97-114
  24. 24. Meyer JH, Cervenka S, Kim MJ, Kreisl WC, Henter ID, Innis RB. Neuroinflammation in psychiatric disorders: PET imaging and promising new targets. The Lancet Psychiatry. 2020;7(12):1064-1074
  25. 25. Zürcher NR, Bhanot A, McDougle CJ, Hooker JM. A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neuroscience and Biobehavioral Reviews. 2015;52:56-73
  26. 26. Kowalewska B, Drozdz W, Kowalewski L. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in autism research: Literature review. Irish Journal of Psychological Medicine. Sep 2022;39(3):272-286
  27. 27. McPartland JC, Lerner MD, Bhat A, Clarkson T, Jack A, Koohsari S, et al. Looking Back at the next 40 years of ASD neuroscience research. Journal of Autism and Developmental Disorders. 2021;51(12):4333-4353
  28. 28. Li X, Zhang K, He X, Zhou J, Jin C, Shen L, et al. Structural, functional, and molecular imaging of autism Spectrum disorder. Neuroscience Bulletin. 2021;37(7):1051-1071
  29. 29. Fowler JS, Ido T. Initial and subsequent approach for the synthesis of 18FDG. Seminars in Nuclear Medicine. 2002;32(1):6-12
  30. 30. Rumsey JM, Duara R, Grady C, Rapoport JL, Margolin RA, Rapoport SI, et al. Brain metabolism in autism. Resting cerebral glucose utilization rates as measured with positron emission tomography. Archives of General Psychiatry. 1985;42(5):448-455
  31. 31. Buchsbaum MS, Siegel BV Jr, Wu JC, Hazlett E, Sicotte N, Haier R, et al. Brief report: Attention performance in autism and regional brain metabolic rate assessed by positron emission tomography. Journal of Autism and Developmental Disorders. 1992;22(1):115-125
  32. 32. Chugani HT, Da Silva E, Chugani DC. Infantile spasms: III. Prognostic implications of bitemporal hypometabolism on positron emission tomography. Annals of Neurology. 1996;39(5):643-649
  33. 33. Haznedar MM, Buchsbaum MS, Metzger M, Solimando A, Spiegel-Cohen J, Hollander E. Anterior cingulate gyrus volume and glucose metabolism in autistic disorder. The American Journal of Psychiatry. 1997;154(8):1047-1050
  34. 34. Haznedar MM, Buchsbaum MS, Wei TC, Hof PR, Cartwright C, Bienstock CA, et al. Limbic circuitry in patients with autism spectrum disorders studied with positron emission tomography and magnetic resonance imaging. The American Journal of Psychiatry. 2000;157(12):1994-2001
  35. 35. Haznedar MM, Buchsbaum MS, Hazlett EA, LiCalzi EM, Cartwright C, Hollander E. Volumetric analysis and three-dimensional glucose metabolic mapping of the striatum and thalamus in patients with autism spectrum disorders. The American Journal of Psychiatry. 2006;163(7):1252-1263
  36. 36. Deriaz N, Willi JP, Orihuela-Flores M, Galli Carminati G, Ratib O. Treatment with levetiracetam in a patient with pervasive developmental disorders, severe intellectual disability, self-injurious behavior, and seizures: A case report. Neurocase. 2012;18(5):386-391
  37. 37. Dilber C, Calışkan M, Sönmezoğlu K, Nişli S, Mukaddes NM, Tatlı B, et al. Positron emission tomography findings in children with infantile spasms and autism. Journal of Clinical Neuroscience. 2013;20(3):373-376
  38. 38. Manglunia AS, Puranik AD. FDG PET/CT findings in a clinically diagnosed case of childhood autism. Indian Journal of Nuclear Medicine: IJNM. 2016;31(2):138-140
  39. 39. Chugani HT, Juhász C, Behen ME, Ondersma R, Muzik O. Autism with facial port-wine stain: A new syndrome? Pediatric Neurology. 2007;37(3):192-199
  40. 40. Siegel BV Jr, Asarnow R, Tanguay P, Call JD, Abel L, Ho A, et al. Regional cerebral glucose metabolism and attention in adults with a history of childhood autism. The Journal of Neuropsychiatry and Clinical Neurosciences. 1992;4(4):406-414
  41. 41. Asano E, Chugani DC, Muzik O, Behen M, Janisse J, Rothermel R, et al. Autism in tuberous sclerosis complex is related to both cortical and subcortical dysfunction. Neurology. 2001;57(7):1269-1277
  42. 42. Hazlett EA, Buchsbaum MS, Hsieh P, Haznedar MM, Platholi J, LiCalzi EM, et al. Regional glucose metabolism within cortical Brodmann areas in healthy individuals and autistic patients. Neuropsychobiology. 2004;49(3):115-125
  43. 43. Anil Kumar BN, Malhotra S, Bhattacharya A, Grover S, Batra YK. Regional cerebral glucose metabolism and its Association with phenotype and cognitive functioning in patients with autism. Indian Journal of Psychological Medicine. 2017;39(3):262-270
  44. 44. Mitelman SA, Bralet MC, Mehmet Haznedar M, Hollander E, Shihabuddin L, Hazlett EA, et al. Positron emission tomography assessment of cerebral glucose metabolic rates in autism spectrum disorder and schizophrenia. Brain Imaging and Behavior. 2018;12(2):532-546
  45. 45. Kadwa RA, Sahu JK, Singhi P, Malhi P, Mittal BR. Prevalence and characteristics of sensory processing abnormalities and its correlation with FDG-PET findings in children with autism. Indian Journal of Pediatrics. 2019;86(11):1036-1042
  46. 46. De Volder A, Bol A, Michel C, Congneau M, Goffinet AM. Brain glucose metabolism in children with the autistic syndrome: Positron tomography analysis. Brain & Development. 1987;9(6):581-587
  47. 47. Herold S, Frackowiak RS, Le Couteur A, Rutter M, Howlin P. Cerebral blood flow and metabolism of oxygen and glucose in young autistic adults. Psychological Medicine. 1988;18(4):823-831
  48. 48. Heh CW, Smith R, Wu J, Hazlett E, Russell A, Asarnow R, et al. Positron emission tomography of the cerebellum in autism. The American Journal of Psychiatry. 1989;146(2):242-245
  49. 49. Seltzer B, Pandya DN. Afferent cortical connections and architectonics of the superior temporal sulcus and surrounding cortex in the rhesus monkey. Brain Research. 1978;149(1):1-24
  50. 50. Pandya DN, Yeterian EHJCC. Architecture and connections of cortical association areas. In: Peters A, Jones EG, editors. Association and Auditory Cortices. Cerebral Cortex. Vol. 4. Boston, MA: Springer; 1985
  51. 51. Sitoh YY, Tien RD. The limbic system. An overview of the anatomy and its development. Neuroimaging Clinics of North America. 1997;7(1):1-10
  52. 52. Lee H, Chung MK, Kang H, Kim BN, Lee DS. Computing the shape of brain networks using graph filtration and Gromov-Hausdorff metric. Medical Image Computing and Computer-Assisted Intervention: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Berlin, Heidelberg, 2011;14(Pt 2):302-309.
  53. 53. Lee H, Lee DS, Kang H, Kim BN, Chung MK. Sparse brain network recovery under compressed sensing. IEEE Transactions on Medical Imaging. 2011;30(5):1154-1165
  54. 54. Lee H, Kang H, Chung MK, Kim BN, Lee DS. Persistent brain network homology from the perspective of dendrogram. IEEE Transactions on Medical Imaging. 2012;31(12):2267-2277
  55. 55. Buchsbaum MS, Hollander E, Haznedar MM, Tang C, Spiegel-Cohen J, Wei TC, et al. Effect of fluoxetine on regional cerebral metabolism in autistic spectrum disorders: A pilot study. The International Journal of Neuropsychopharmacology. 2001;4(2):119-125
  56. 56. Park HR, Kim IH, Kang H, Lee DS, Kim BN, Kim DG, et al. Nucleus accumbens deep brain stimulation for a patient with self-injurious behavior and autism spectrum disorder: Functional and structural changes of the brain: Report of a case and review of literature. Acta Neurochirurgica. 2017;159(1):137-143
  57. 57. Żarnowska I, Chrapko B, Gwizda G, Nocuń A, Mitosek-Szewczyk K, Gasior M. Therapeutic use of carbohydrate-restricted diets in an autistic child; a case report of clinical and 18FDG PET findings. Metabolic Brain Disease. 2018;33(4):1187-1192
  58. 58. Frye RE, Rossignol DA. Treatments for biomedical abnormalities associated with autism spectrum disorder. Frontiers in Pediatrics. 2014;2:66
  59. 59. Courchesne-Loyer A, Croteau E, Castellano CA, St-Pierre V, Hennebelle M, Cunnane SC. Inverse relationship between brain glucose and ketone metabolism in adults during short-term moderate dietary ketosis: A dual tracer quantitative positron emission tomography study. Journal of Cerebral Blood Flow and Metabolism. 2017;37(7):2485-2493
  60. 60. Joseph-Mathurin N, Su Y, Blazey TM, Jasielec M, Vlassenko A, Friedrichsen K, et al. Utility of perfusion PET measures to assess neuronal injury in Alzheimer's disease. Alzheimer's & Dementia. 2018;10:669-677
  61. 61. Boddaert N, Chabane N, Barthélemy C, Bourgeois M, Poline JB, Brunelle F, et al. Bitemporal lobe dysfonction in infantile autism: Positron emission tomography study. Journal de Radiologie. 2002;83(12 Pt 1):1829-1833
  62. 62. Happé F, Ehlers S, Fletcher P, Frith U, Johansson M, Gillberg C, et al. 'Theory of mind' in the brain. Evidence from a PET scan study of Asperger syndrome. Neuroreport. 1996;8(1):197-201
  63. 63. Müller RA, Chugani DC, Behen ME, Rothermel RD, Muzik O, Chakraborty PK, et al. Impairment of dentato-thalamo-cortical pathway in autistic men: Language activation data from positron emission tomography. Neuroscience Letters. 1998;245(1):1-4
  64. 64. Hall GB, Szechtman H, Nahmias C. Enhanced salience and emotion recognition in autism: A PET study. The American Journal of Psychiatry. 2003;160(8):1439-1441
  65. 65. Müller RA, Behen ME, Rothermel RD, Chugani DC, Muzik O, Mangner TJ, et al. Brain mapping of language and auditory perception in high-functioning autistic adults: A PET study. Journal of Autism and Developmental Disorders. 1999;29(1):19-31
  66. 66. Chugani DC, Muzik O, Rothermel R, Behen M, Chakraborty P, Mangner T, et al. Altered serotonin synthesis in the dentatothalamocortical pathway in autistic boys. Annals of Neurology. 1997;42(4):666-669
  67. 67. Boddaert N, Belin P, Chabane N, Poline JB, Barthélémy C, Mouren-Simeoni MC, et al. Perception of complex sounds: Abnormal pattern of cortical activation in autism. The American Journal of Psychiatry. 2003;160(11):2057-2060
  68. 68. Boddaert N, Chabane N, Belin P, Bourgeois M, Royer V, Barthelemy C, et al. Perception of complex sounds in autism: Abnormal auditory cortical processing in children. The American Journal of Psychiatry. 2004;161(11):2117-2120
  69. 69. Saitovitch A, Rechtman E, Lemaitre H, Tacchella J-M, Vinçon-Leite A, Douard E, et al. Superior temporal sulcus hypoperfusion in children with autism spectrum disorder: An arterial spin-labeling magnetic resonance study. BioRxiv. 2019:771584
  70. 70. Yang CJ, Tan HP, Du YJ. The developmental disruptions of serotonin signaling may involved in autism during early brain development. Neuroscience. 2014;267:1-10
  71. 71. Schain RJ, Freedman DX. Studies on 5-hydroxyindole metabolism in autistic and other mentally retarded children. The Journal of Pediatrics. 1961;58:315-320
  72. 72. McDougle CJ, Naylor ST, Cohen DJ, Volkmar FR, Heninger GR, Price LH. A double-blind, placebo-controlled study of fluvoxamine in adults with autistic disorder. Archives of General Psychiatry. 1996;53(11):1001-1008
  73. 73. Croen LA, Grether JK, Yoshida CK, Odouli R, Hendrick V. Antidepressant use during pregnancy and childhood autism spectrum disorders. Archives of General Psychiatry. 2011;68(11):1104-1112
  74. 74. Hollander E, Soorya L, Chaplin W, Anagnostou E, Taylor BP, Ferretti CJ, et al. A double-blind placebo-controlled trial of fluoxetine for repetitive behaviors and global severity in adult autism spectrum disorders. The American Journal of Psychiatry. 2012;169(3):292-299
  75. 75. Chakraborty PK, Mangner TJ, Chugani DC, Muzik O, Chugani HT. A high-yield and simplified procedure for the synthesis of alpha-[11C]methyl-L-tryptophan. Nuclear Medicine and Biology. 1996;23(8):1005-1008
  76. 76. Chugani DC, Muzik O. Alpha[C-11]methyl-L-tryptophan PET maps brain serotonin synthesis and kynurenine pathway metabolism. Journal of Cerebral Blood Flow and Metabolism. 2000;20(1):2-9
  77. 77. Chugani DC, Muzik O, Behen M, Rothermel R, Janisse JJ, Lee J, et al. Developmental changes in brain serotonin synthesis capacity in autistic and nonautistic children. Annals of Neurology. 1999;45(3):287-295
  78. 78. Chandana SR, Behen ME, Juhász C, Muzik O, Rothermel RD, Mangner TJ, et al. Significance of abnormalities in developmental trajectory and asymmetry of cortical serotonin synthesis in autism. International Journal of Developmental Neuroscience. 2005;23(2-3):171-182
  79. 79. Suehiro M, Scheffel U, Ravert HT, Dannals RF, Wagner HN Jr. [11C](+)McN5652 as a radiotracer for imaging serotonin uptake sites with PET. Life Sciences. 1993;53(11):883-892
  80. 80. Nakamura K, Sekine Y, Ouchi Y, Tsujii M, Yoshikawa E, Futatsubashi M, et al. Brain serotonin and dopamine transporter bindings in adults with high-functioning autism. Archives of General Psychiatry. 2010;67(1):59-68
  81. 81. Wilson AA, Ginovart N, Hussey D, Meyer J, Houle S. In vitro and in vivo characterisation of [11C]-DASB: A probe for in vivo measurements of the serotonin transporter by positron emission tomography. Nuclear Medicine and Biology. 2002;29(5):509-515
  82. 82. Girgis RR, Slifstein M, Xu X, Frankle WG, Anagnostou E, Wasserman S, et al. The 5-HT(2A) receptor and serotonin transporter in Asperger's disorder: A PET study with [11C]MDL 100907 and [11C]DASB. Psychiatry Research. 2011;194(3):230-234
  83. 83. Andersson M, Tangen Ä, Farde L, Bölte S, Halldin C, Borg J, et al. Serotonin transporter availability in adults with autism-a positron emission tomography study. Molecular Psychiatry. May 2021;26(5):1647-1658
  84. 84. Lundberg J, Halldin C, Farde L. Measurement of serotonin transporter binding with PET and [11C]MADAM: A test-retest reproducibility study. Synapse. 2006;60(3):256-263
  85. 85. Huang Y, Bae S-A, Zhu Z, Guo N, Hwang D-R, Laruelle M. Fluorinated analogues of ADAM as new PET radioligands for the serotonin transporter: Synthesis and pharmacological evaluation. Journal of Labelled Compounds and Radiopharmaceuticals. 2001;44(S1):S18-S20
  86. 86. Huang Y, Hwang DR, Narendran R, Sudo Y, Chatterjee R, Bae SA, et al. Comparative evaluation in nonhuman primates of five PET radiotracers for imaging the serotonin transporters: [11C]McN 5652, [11C]ADAM, [11C]DASB, [11C]DAPA, and [11C]AFM. Journal of Cerebral Blood Flow and Metabolism. 2002;22(11):1377-1398
  87. 87. Blin J, Sette G, Fiorelli M, Bletry O, Elghozi JL, Crouzel C, et al. A method for the in vivo investigation of the serotonergic 5-HT2 receptors in the human cerebral cortex using positron emission tomography and 18F-labeled setoperone. Journal of Neurochemistry. 1990;54(5):1744-1754
  88. 88. Beversdorf DQ , Nordgren RE, Bonab AA, Fischman AJ, Weise SB, Dougherty DD, et al. 5-HT2 receptor distribution shown by [18F] setoperone PET in high-functioning autistic adults. The Journal of Neuropsychiatry and Clinical Neurosciences. 2012;24(2):191-197
  89. 89. Goldberg J, Anderson GM, Zwaigenbaum L, Hall GB, Nahmias C, Thompson A, et al. Cortical serotonin type-2 receptor density in parents of children with autism spectrum disorders. Journal of Autism and Developmental Disorders. 2009;39(1):97-104
  90. 90. Lefevre A, Richard N, Mottolese R, Leboyer M, Sirigu A. An Association between serotonin 1A receptor, Gray matter volume, and sociability in healthy subjects and in autism Spectrum disorder. Autism Research. 2020;13(11):1843-1855
  91. 91. Modahl C, Green L, Fein D, Morris M, Waterhouse L, Feinstein C, et al. Plasma oxytocin levels in autistic children. Biological Psychiatry. 1998;43(4):270-277
  92. 92. Guastella AJ, Einfeld SL, Gray KM, Rinehart NJ, Tonge BJ, Lambert TJ, et al. Intranasal oxytocin improves emotion recognition for youth with autism spectrum disorders. Biological Psychiatry. 2010;67(7):692-694
  93. 93. Domes G, Heinrichs M, Kumbier E, Grossmann A, Hauenstein K, Herpertz SC. Effects of intranasal oxytocin on the neural basis of face processing in autism spectrum disorder. Biological Psychiatry. 2013;74(3):164-171
  94. 94. Gordon I, Vander Wyk BC, Bennett RH, Cordeaux C, Lucas MV, Eilbott JA, et al. Oxytocin enhances brain function in children with autism. Proceedings of the National Academy of Sciences of the United States of America. 2013;110(52):20953-20958
  95. 95. Wang C, Moseley CK, Carlin SM, Wilson CM, Neelamegam R, Hooker JM. Radiosynthesis and evaluation of [11C]EMPA as a potential PET tracer for orexin 2 receptors. Bioorganic & Medicinal Chemistry Letters. 2013;23(11):3389-3392
  96. 96. Vidal B, Karpenko IA, Liger F, Fieux S, Bouillot C, Billard T, et al. [(11)C]PF-3274167 as a PET radiotracer of oxytocin receptors: Radiosynthesis and evaluation in rat brain. Nuclear Medicine and Biology. 2017;55:1-6
  97. 97. Mottolese R, Redouté J, Costes N, Le Bars D, Sirigu A. Switching brain serotonin with oxytocin. Proceedings of the National Academy of Sciences of the United States of America. 2014;111(23):8637-8642
  98. 98. Lefevre A, Mottolese R, Redouté J, Costes N, Le Bars D, Geoffray MM, et al. Oxytocin fails to recruit serotonergic neurotransmission in the autistic brain. Cerebral Cortex. 2018;28(12):4169-4178
  99. 99. Hirosawa T, Kikuchi M, Ouchi Y, Takahashi T, Yoshimura Y, Kosaka H, et al. A pilot study of serotonergic modulation after long-term administration of oxytocin in autism spectrum disorder. Autism Research. 2017;10(5):821-828
  100. 100. Gadow KD, Roohi J, DeVincent CJ, Hatchwell E. Association of ADHD, tics, and anxiety with dopamine transporter (DAT1) genotype in autism spectrum disorder. Journal of Child Psychology and Psychiatry, and Allied Disciplines. 2008;49(12):1331-1338
  101. 101. Staal WG, de Krom M, de Jonge MV. Brief report: The dopamine-3-receptor gene (DRD3) is associated with specific repetitive behavior in autism spectrum disorder (ASD). Journal of Autism and Developmental Disorders. 2012;42(5):885-888
  102. 102. Hamilton PJ, Campbell NG, Sharma S, Erreger K, Herborg Hansen F, Saunders C, et al. De novo mutation in the dopamine transporter gene associates dopamine dysfunction with autism spectrum disorder. Molecular Psychiatry. 2013;18(12):1315-1323
  103. 103. Ernst M, Zametkin AJ, Matochik JA, Pascualvaca D, Cohen RM. Low medial prefrontal dopaminergic activity in autistic children. Lancet. 1997;350(9078):638
  104. 104. Nieminen-von Wendt TS, Metsähonkala L, Kulomäki TA, Aalto S, Autti TH, Vanhala R, et al. Increased presynaptic dopamine function in Asperger syndrome. Neuroreport. 2004;15(5):757-760
  105. 105. Schalbroeck R, de Geus-Oei LF, Selten JP, Yaqub M, Schrantee A, van Amelsvoort T, et al. Cerebral [(18)F]-FDOPA uptake in autism Spectrum disorder and its Association with autistic traits. Diagnostics. 2021;11(12):2404
  106. 106. Schalbroeck R, van Velden FHP, de Geus-Oei LF, Yaqub M, van Amelsvoort T, Booij J, et al. Striatal dopamine synthesis capacity in autism spectrum disorder and its relation with social defeat: An [(18)F]-FDOPA PET/CT study. Translational Psychiatry. 2021;11(1):47
  107. 107. Fernell E, Watanabe Y, Adolfsson I, Tani Y, Bergström M, Hartvig P, et al. Possible effects of tetrahydrobiopterin treatment in six children with autism--clinical and positron emission tomography data: A pilot study. Developmental Medicine and Child Neurology. 1997;39(5):313-318
  108. 108. Fujino J, Tei S, Takahata K, Matsuoka K, Tagai K, Sano Y, et al. Binding of dopamine D1 receptor and noradrenaline transporter in individuals with autism Spectrum disorder: A PET study. Cerebral Cortex. 2020;30(12):6458-6468
  109. 109. Zürcher NR, Walsh EC, Phillips RD, Cernasov PM, Tseng CJ, Dharanikota A, et al. A simultaneous [(11)C]raclopride positron emission tomography and functional magnetic resonance imaging investigation of striatal dopamine binding in autism. Translational Psychiatry. 2021;11(1):33
  110. 110. Kelleher RJ 3rd, Bear MF. The autistic neuron: Troubled translation? Cell. 2008;135(3):401-406
  111. 111. Pizzarelli R, Cherubini E. Alterations of GABAergic signaling in autism spectrum disorders. Neural Plasticity. 2011;2011:297153
  112. 112. Cook EH Jr, Courchesne RY, Cox NJ, Lord C, Gonen D, Guter SJ, et al. Linkage-disequilibrium mapping of autistic disorder, with 15q11-13 markers. American Journal of Human Genetics. 1998;62(5):1077-1083
  113. 113. Coghlan S, Horder J, Inkster B, Mendez MA, Murphy DG, Nutt DJ. GABA system dysfunction in autism and related disorders: From synapse to symptoms. Neuroscience and Biobehavioral Reviews. 2012;36(9):2044-2055
  114. 114. Blatt GJ, Fitzgerald CM, Guptill JT, Booker AB, Kemper TL, Bauman ML. Density and distribution of hippocampal neurotransmitter receptors in autism: An autoradiographic study. Journal of Autism and Developmental Disorders. 2001;31(6):537-543
  115. 115. Oblak A, Gibbs TT, Blatt GJ. Decreased GABAA receptors and benzodiazepine binding sites in the anterior cingulate cortex in autism. Autism Research. 2009;2(4):205-219
  116. 116. Tyzio R, Nardou R, Ferrari DC, Tsintsadze T, Shahrokhi A, Eftekhari S, et al. Oxytocin-mediated GABA inhibition during delivery attenuates autism pathogenesis in rodent offspring. Science. 2014;343(6171):675-679
  117. 117. Mendez MA, Horder J, Myers J, Coghlan S, Stokes P, Erritzoe D, et al. The brain GABA-benzodiazepine receptor alpha-5 subtype in autism spectrum disorder: A pilot [(11)C]Ro15-4513 positron emission tomography study. Neuropharmacology. 2013;68:195-201
  118. 118. Horder J, Andersson M, Mendez MA, Singh N, Tangen Ä, Lundberg J, et al. GABA(a) receptor availability is not altered in adults with autism spectrum disorder or in mouse models. Science Translational Medicine. 2018;10(461):eaam8434
  119. 119. Fung LK, Flores RE, Gu M, Sun KL, James D, Schuck RK, et al. Thalamic and prefrontal GABA concentrations but not GABA(a) receptor densities are altered in high-functioning adults with autism spectrum disorder. Molecular Psychiatry. 2020;26(5):1634-1646
  120. 120. Rubenstein JL, Merzenich MM. Model of autism: Increased ratio of excitation/inhibition in key neural systems. Genes, Brain, and Behavior. 2003;2(5):255-267
  121. 121. Barret O, Tamagnan G, Batis J, Jennings D, Zubal G, Russel D, et al. Quantitation of glutamate mGluR5 receptor with 18F-FPEB PET in humans. NeuroImage. 2010;52:215
  122. 122. Sullivan JM, Lim K, Labaree D, Lin SF, McCarthy TJ, Seibyl JP, et al. Kinetic analysis of the metabotropic glutamate subtype 5 tracer [(18)F]FPEB in bolus and bolus-plus-constant-infusion studies in humans. Journal of Cerebral Blood Flow and Metabolism. 2013;33(4):532-541
  123. 123. Wong DF, Waterhouse R, Kuwabara H, Kim J, Brašić JR, Chamroonrat W, et al. 18F-FPEB, a PET radiopharmaceutical for quantifying metabotropic glutamate 5 receptors: A first-in-human study of radiochemical safety, biokinetics, and radiation dosimetry. Journal of Nuclear Medicine. 2013;54(3):388-396
  124. 124. Toyohara J, Sakata M, Oda K, Ishii K, Ito K, Hiura M, et al. Initial human PET studies of metabotropic glutamate receptor type 1 ligand 11C-ITMM. Journal of Nuclear Medicine. 2013;54(8):1302-1307
  125. 125. Cai G, Wang M, Wang S, Liu Y, Zhao Y, Zhu Y, et al. Brain mGluR5 in Shank3B(−/−) mice studied with in vivo [(18)F]FPEB PET imaging and ex vivoimmunoblotting. Frontiers in Psychiatry. 2019;10:38
  126. 126. Fatemi SH, Wong DF, Brašić JR, Kuwabara H, Mathur A, Folsom TD, et al. Metabotropic glutamate receptor 5 tracer [(18)F]-FPEB displays increased binding potential in postcentral gyrus and cerebellum of male individuals with autism: A pilot PET study. Cerebellum & Ataxias. 2018;5:3
  127. 127. Brašić JR, Nandi A, Russell DS, Jennings D, Barret O, Martin SD, et al. Cerebral expression of metabotropic glutamate receptor subtype 5 in idiopathic autism Spectrum disorder and fragile X syndrome: A pilot study. International Journal of Molecular Sciences. 2021;22(6):2863
  128. 128. Shih YT, Hsueh YP. The involvement of endoplasmic reticulum formation and protein synthesis efficiency in VCP- and ATL1-related neurological disorders. Journal of Biomedical Science. 2018;25(1):2
  129. 129. Shandal V, Sundaram SK, Chugani DC, Kumar A, Behen ME, Chugani HT. Abnormal brain protein synthesis in language areas of children with pervasive developmental disorder: A L-[1-11C]-leucine PET study. Journal of Child Neurology. 2011;26(11):1347-1354
  130. 130. Schmidt KC, Loutaev I, Quezado Z, Sheeler C, Smith CB. Regional rates of brain protein synthesis are unaltered in dexmedetomidine sedated young men with fragile X syndrome: A L-[1-(11)C]leucine PET study. Neurobiology of Disease. 2020;143:104978
  131. 131. Dionne O, Lortie A, Gagnon F, Corbin F. Rates of protein synthesis are reduced in peripheral blood mononuclear cells (PBMCs) from fragile X individuals. PLoS One. 2021;16(5):e0251367
  132. 132. Hardan AY, Handen BL. A retrospective open trial of adjunctive donepezil in children and adolescents with autistic disorder. Journal of Child and Adolescent Psychopharmacology. 2002;12(3):237-241
  133. 133. Nicolson R, Craven-Thuss B, Smith J. A prospective, open-label trial of galantamine in autistic disorder. Journal of Child and Adolescent Psychopharmacology. 2006;16(5):621-629
  134. 134. Karvat G, Kimchi T. Acetylcholine elevation relieves cognitive rigidity and social deficiency in a mouse model of autism. Neuropsychopharmacology. 2014;39(4):831-840
  135. 135. Suzuki K, Sugihara G, Ouchi Y, Nakamura K, Tsujii M, Futatsubashi M, et al. Reduced acetylcholinesterase activity in the fusiform gyrus in adults with autism spectrum disorders. Archives of General Psychiatry. 2011;68(3):306-313
  136. 136. Stigler KA, Sweeten TL, Posey DJ, McDougle CJ. Autism and immune factors: A comprehensive review. Research in Autism Spectrum Disorder. 2009;3(4):840-860
  137. 137. Kato TA, Yamauchi Y, Horikawa H, Monji A, Mizoguchi Y, Seki Y, et al. Neurotransmitters, psychotropic drugs and microglia: Clinical implications for psychiatry. Current Medicinal Chemistry. 2013;20(3):331-344
  138. 138. Best L, Ghadery C, Pavese N, Tai YF, Strafella AP. New and old TSPO PET Radioligands for imaging brain microglial activation in neurodegenerative disease. Current Neurology and Neuroscience Reports. 2019;19(5):24
  139. 139. Werry EL, Bright FM, Piguet O, Ittner LM, Halliday GM, Hodges JR, et al. Recent developments in TSPO PET imaging as a biomarker of Neuroinflammation in neurodegenerative disorders. International Journal of Molecular Sciences. 2019;20(13):3161
  140. 140. Suzuki K, Sugihara G, Ouchi Y, Nakamura K, Futatsubashi M, Takebayashi K, et al. Microglial activation in young adults with autism spectrum disorder. JAMA Psychiatry. 2013;70(1):49-58
  141. 141. Zürcher NR, Loggia ML, Mullett JE, Tseng C, Bhanot A, Richey L, et al. [(11)C]PBR28 MR-PET imaging reveals lower regional brain expression of translocator protein (TSPO) in young adult males with autism spectrum disorder. Molecular Psychiatry. 2020;26(5):1659-1669
  142. 142. Owen DR, Howell OW, Tang SP, Wells LA, Bennacef I, Bergstrom M, et al. Two binding sites for [3H]PBR28 in human brain: Implications for TSPO PET imaging of neuroinflammation. Journal of Cerebral Blood Flow and Metabolism. 2010;30(9):1608-1618
  143. 143. Fujita M, Kobayashi M, Ikawa M, Gunn RN, Rabiner EA, Owen DR, et al. Comparison of four (11)C-labeled PET ligands to quantify translocator protein 18 kDa (TSPO) in human brain: (R)-PK11195, PBR28, DPA-713, and ER176-based on recent publications that measured specific-to-non-displaceable ratios. EJNMMI Research. 2017;7(1):84
  144. 144. Hafizi S, Tseng HH, Rao N, Selvanathan T, Kenk M, Bazinet RP, et al. Imaging microglial activation in untreated first-episode psychosis: A PET study with [(18)F]FEPPA. The American Journal of Psychiatry. 2017;174(2):118-124
  145. 145. Kobayashi M, Jiang T, Telu S, Zoghbi SS, Gunn RN, Rabiner EA, et al. (11)C-DPA-713 has much greater specific binding to translocator protein 18 kDa (TSPO) in human brain than (11)C-(R)-PK11195. Journal of Cerebral Blood Flow and Metabolism. 2018;38(3):393-403
  146. 146. Koob GF, Bloom FE. Behavioral effects of neuropeptides: Endorphins and vasopressin. Annual Review of Physiology. 1982;44:571-582
  147. 147. Jard S. Vasopressin receptors. A historical survey. Advances in Experimental Medicine and Biology. 1998;449:1-13
  148. 148. Goodson JL, Thompson RR. Nonapeptide mechanisms of social cognition, behavior and species-specific social systems. Current Opinion in Neurobiology. 2010;20(6):784-794
  149. 149. Kelly AM, Goodson JL. Hypothalamic oxytocin and vasopressin neurons exert sex-specific effects on pair bonding, gregariousness, and aggression in finches. Proceedings of the National Academy of Sciences of the United States of America. 2014;111(16):6069-6074
  150. 150. Caldwell HK. Oxytocin and vasopressin: Powerful regulators of social behavior. The Neuroscientist. 2017;23(5):517-528
  151. 151. Miller M, Bales KL, Taylor SL, Yoon J, Hostetler CM, Carter CS, et al. Oxytocin and vasopressin in children and adolescents with autism spectrum disorders: Sex differences and associations with symptoms. Autism Research. 2013;6(2):91-102
  152. 152. Shou XJ, Xu XJ, Zeng XZ, Liu Y, Yuan HS, Xing Y, et al. A volumetric and functional connectivity MRI study of brain arginine-vasopressin pathways in autistic children. Neuroscience Bulletin. 2017;33(2):130-142
  153. 153. Parker KJ, Garner JP, Oztan O, Tarara ER, Li J, Sclafani V, et al. Arginine vasopressin in cerebrospinal fluid is a marker of sociality in nonhuman primates. Science Translational Medicine. 2018;10(439):eaam9100
  154. 154. Wilczyński KM, Zasada I, Siwiec A, Janas-Kozik M. Differences in oxytocin and vasopressin levels in individuals suffering from the autism spectrum disorders vs general population - a systematic review. Neuropsychiatric Disease and Treatment. 2019;15:2613-2620
  155. 155. Bolognani F, Rubido MV, Squassante L, Wandel C, Derks M, Murtagh L, et al. A phase 2 clinical trial of a vasopressin V1a receptor antagonist shows improved adaptive behaviors in men with autism spectrum disorder. Science Translational Medicine. 2019;11(491):eaat7838
  156. 156. Schnider P, Bissantz C, Bruns A, Dolente C, Goetschi E, Jakob-Roetne R, et al. Discovery of Balovaptan, a vasopressin 1a receptor antagonist for the treatment of autism Spectrum disorder. Journal of Medicinal Chemistry. 2020;63(4):1511-1525
  157. 157. Fabio K, Guillon C, Lacey CJ, Lu SF, Heindel ND, Ferris CF, et al. Synthesis and evaluation of potent and selective human V1a receptor antagonists as potential ligands for PET or SPECT imaging. Bioorganic & Medicinal Chemistry. 2012;20(3):1337-1345
  158. 158. Naik R, Valentine H, Hall A, Mathews WB, Harris JC, Carter CS, et al. Development of a radio ligand for imaging V1a vasopressin receptors with PET. European Journal of Medicinal Chemistry. 2017;139:644-656
  159. 159. Haider A, Xiao Z, Xia X, Chen J, Van RS, Kuang S, et al. Development of a triazolobenzodiazepine-based PET probe for subtype-selective vasopressin 1A receptor imaging. Pharmacological Research. 2021;173:105886
  160. 160. Lombardo MV, Lai MC, Baron-Cohen S. Big data approaches to decomposing heterogeneity across the autism spectrum. Molecular Psychiatry. 2019;24(10):1435-1450
  161. 161. Hong SJ, Vogelstein JT, Gozzi A, Bernhardt BC, Yeo BTT, Milham MP, et al. Toward neurosubtypes in autism. Biological Psychiatry. 2020;88(1):111-128
  162. 162. Owen DR, Yeo AJ, Gunn RN, Song K, Wadsworth G, Lewis A, et al. An 18-kDa translocator protein (TSPO) polymorphism explains differences in binding affinity of the PET radioligand PBR28. Journal of Cerebral Blood Flow and Metabolism. 2012;32(1):1-5
  163. 163. McPartland JC, Bernier RA, Jeste SS, Dawson G, Nelson CA, Chawarska K, et al. The autism biomarkers consortium for clinical trials (ABC-CT): Scientific context, study design, and Progress toward biomarker qualification. Frontiers in Integrative Neuroscience. 2020;14:16

Written By

Zhiqiang Tan, Weijian Ye, Hao Xu and Lu Wang

Submitted: 04 July 2022 Reviewed: 28 July 2022 Published: 30 August 2022

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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