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Article

Reduced Expression of Cerebral Metabotropic Glutamate Receptor Subtype 5 in Men with Fragile X Syndrome

1
Section of High Resolution Brain Positron Emission Tomography Imaging, Division of Nuclear Medicine and Molecular Imaging, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
2
Clinical Research, Institute for Neurodegenerative Disorders, New Haven, CT 06510, USA
3
Research Clinic, Invicro LLC, New Haven, CT 06510, USA
4
Denali Therapeutics, Inc., South San Francisco, CA 94080, USA
5
Department of Psychiatry and Behavioral Sciences-Child Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
6
Department of Behavioral Psychology, Kennedy Krieger Institute, Baltimore, MD 21205, USA
7
Department of Psychiatry and Behavioral Sciences-General Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
8
Department of Neuroscience, Zanvyl Krieger School of Arts and Sciences, The Johns Hopkins University, Baltimore, MD 21218, USA
9
Departments of Pediatrics, Neurological Sciences, and Biochemistry, Rush University Medical Center, Chicago, IL 60612, USA
10
Precision Radio-Theranostics Translational Laboratories, Mallinckrodt Institute of Radiology, School of Medicine, Washington University, Saint Louis, MO 63110, USA
11
Departments of Psychiatry and Neurogenetics, Kennedy Krieger Institute, Baltimore, MD 21205, USA
*
Authors to whom correspondence should be addressed.
Brain Sci. 2020, 10(12), 899; https://doi.org/10.3390/brainsci10120899
Received: 30 August 2020 / Revised: 7 November 2020 / Accepted: 14 November 2020 / Published: 24 November 2020
(This article belongs to the Section Developmental Neuroscience)

Abstract

Glutamatergic receptor expression is mostly unknown in adults with fragile X syndrome (FXS). Favorable behavioral effects of negative allosteric modulators (NAMs) of the metabotropic glutamate receptor subtype 5 (mGluR5) in fmr1 knockout (KO) mouse models have not been confirmed in humans with FXS. Measurement of cerebral mGluR5 expression in humans with FXS exposed to NAMs might help in that effort. We used positron emission tomography (PET) to measure the mGluR5 density as a proxy of mGluR5 expression in cortical and subcortical brain regions to confirm target engagement of NAMs for mGluR5s. The density and the distribution of mGluR5 were measured in two independent samples of men with FXS (N = 9) and typical development (TD) (N = 8). We showed the feasibility of this complex study including MRI and PET, meaning that this challenging protocol can be accomplished in men with FXS with an adequate preparation. Analysis of variance of estimated mGluR5 expression showed that mGluR5 expression was significantly reduced in cortical and subcortical regions of men with FXS in contrast to age-matched men with TD.
Keywords: binding potential; caudate nucleus; FMR1 gene; Fragile X Mental Retardation Protein (FMRP); genetic mutation; magnetic resonance imaging (MRI); mosaicism; neuropsychological testing; positron emission tomography (PET); 3-[18F]fluoro-5-(2-pyridinylethynyl)benzonitrile ([18F]FPEB) binding potential; caudate nucleus; FMR1 gene; Fragile X Mental Retardation Protein (FMRP); genetic mutation; magnetic resonance imaging (MRI); mosaicism; neuropsychological testing; positron emission tomography (PET); 3-[18F]fluoro-5-(2-pyridinylethynyl)benzonitrile ([18F]FPEB)

1. Introduction

1.1. Background

Fragile X syndrome (FXS) is caused by expansion full mutation (≥200 CGGs) of the fragile X mental retardation 1 (FMR1) gene leading to epigenetic silencing of the gene, resulting in reduction of its product: fragile X mental retardation protein (FMRP) [1]. FXS is the leading single-gene cause of inherited intellectual disability (ID) and autism spectrum disorder (ASD) [2,3]. Indeed, studies of humans with FXS have consistently demonstrated a wide range of global neurobehavioral impairments [4,5,6,7,8,9]. This is not surprising, as FMRP controls translation around 4% of mRNA in human brains. To illustrate, FMRP binds brain mRNAs, inhibits synthesis of a myriad of proteins [10], and increases the dosages of FMRP target proteins (over 600 to date) of relevance to ASD [11]. The FMRP expression in the brain is the ultimate factor determining the severity of the neurobehavioral phenotype [12]. The absence of adequate FMRP results in overactive glutamatergic signaling of group 1 metabotropic (mGluR1 and mGluR5) pathways, and consequently overactive downstream signaling cascades, such as the mammalian target of rapamycin (mTOR) and mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK). The overactive downstream signaling leads to excessive protein synthesis in an fmr1 knockout (KO) mouse model [13]. Namely, abnormal mGluR5-modulated long-term depression (LTD) in the hippocampus in the fmr1 KO model led to “the mGluR5 theory” of neuronal dysfunction in FXS [14]. Indeed, the abnormal signaling in the absence of FMRP is associated with aberrant synaptic plasticity and immature dendritic spine morphology. The abnormal excitation–inhibition that leads to an excessive de novo protein synthesis also occurs in humans with FXS [15,16,17,18]. Targeted treatment studies using mGluR5 negative allosteric modulators (NAMs) then unfolded in both the fmr1 KO mouse model and in humans with FXS [3,12]. Yet, mGluR5 expression in animal studies and in autopsy studies of humans with FXS produced inconsistent results. Moreover, mGluR5 expression in vivo has not been measured in humans with FXS.
Although a necropsy study pooling human brains with FXS and premutation of the FMR1 gene (PM, 55–200 CGGs) showed increased mGluR5s and marginal protein overexpression [19], these studies do not exist in the living human brain. Since the limited necropsy findings may represent the changes in agonal and post-mortem periods, in vivo measurement of the expression of mGluR5s is needed, which may bring an initial insight into failed clinical trials that used investigational agents acting on mGluR5 in humans FXS. Novel, specific mGluR5 ligands that allow quantitative measurement of the density and distribution of mGluR5s in the brain, such as 3-[18F]fluoro-5-(2-pyridinylethynyl)benzonitrile ([18F]FPEB), require studies of feasibility.
Indeed, quantification of mGluR5 expression in the living human brain of men with FXS is needed to help understand results of past mGluR5 trials in humans with FXS, and to help provide information for successful clinical trial designs. For example, an alteration of expression of mGluR5s, such as internalization of membrane mGluR5s, may be one possible explanation for the negligible therapeutic effect of NAMs in “failed” clinical trials of humans with FXS [20]. Since proteins and receptors occupy different locations on the membranes, the living brain may show protein overexpression and reduction of receptors due to receptor internalization or other alterations. Thus, the use of [18F]FPEB may serve as an effective tool to confirm target engagement of NAMs for mGluR5s.

1.2. Measurement of mGluR5s in the Living Human Brain

While several techniques exist to estimate the concentration of glutamate in the living brain, including magnetic resonance imaging (MRI) and brain biopsy, positron emission tomography (PET) uniquely provides the optimal means to measure mGluR5s. For these reasons, radiotracers that bind to mGluR5 in the living brain and can be visualized with PET are promising tools to quantify the density and the distribution of mGluR5s in humans with FXS.

[18F]FPEB

3-[18F]fluoro-5-(2-pyridinylethynyl)benzonitrile ([18F]FPEB), a novel, specific mGluR5 ligand to quantitatively measure the density and distribution of mGluR5s in the brain regions of humans with FXS through PET [21,22,23,24,25,26,27,28,29,30] (Figure 1), constitutes an effective tool to confirm target engagement of mGluR5s of relevance to clinical trials of NAMs for individuals with FXS [31].
Specifically, [18F]FPEB [22,34,35,36,37] has been shown to demonstrate high uptake and specific binding during the test–retest paradigm for mGluR5 in the anterior cingulate gyrus, putamen, caudate nucleus, and frontal, parietal, and temporal cortices [28,29]. [18F]FPEB has demonstrated deficits in the striatal and neocortical mGluR5s in people with mild Huntington’s disease [34,35] and increments in the mGluR5s in people with mild Parkinson’s disease [36,37,38] and men with ASD [25].
We sought to quantify the density and distribution of mGluR5 expression in FXS [39,40,41,42,43,44,45,46,47,48,49,50,51] by means of PET.

2. Materials and Methods

2.1. Participants

2.1.1. Recruiting Sites

The study is approved by Johns Hopkins Medicine Institutional Review Board IRB 169 249. The protocols for the study of humans with FXS were approved by the Institutional Review Boards of the Institute for Neurodegenerative Disorders (IND) in New Haven, Connecticut [52] and Johns Hopkins University (JHU) in Baltimore, Maryland [53,54]. Since exposure to radioactivity in PET constitutes greater than minimal risk, this pilot study was restricted to adults. Written informed consent was obtained from each participant at both locations.

2.1.2. Inclusion Criteria

Inclusion criteria for all subjects were age 18–60 years and a diagnosis of FXS based on FMR1 DNA gene testing by PCR/Southern Blot, supplemented by clinical neurobehavioral profiling [52].

2.1.3. Exclusion Criteria

Exclusion criteria were clinically significant abnormal laboratory values and/or clinically significant unstable serious medical, neurological, or psychiatric illnesses [52].

2.1.4. Institute for Neurodegenerative Disorders (IND)

Participants with FXS had completed genetic and other evaluations before traveling to the IND with a caregiver. One day after arrival to the IND, they underwent a screening assessment to confirm the inclusion and exclusion criteria, neuropsychological evaluation, mock scanner training, and PET scans. Participants with TD were recruited from community residents.
Seven men with FXS (mean age 25 ± 5, range 23–34 years) recruited from Rush University Medical Center, Chicago, Illinois, and three age-matched men with typical development (TD) (mean aged 32 ± 4, range 27–39 years) participated in the protocol. Clinical and demographic data [55] confirmed that all participants met the criteria to receive the adult dose of 185 megabecquerels (MBqs) (5 millicuries (mCis)) of [18F]FPEB.

2.1.5. Johns Hopkins University (JHU)

Four men with FXS (mean age 28 ± 9, range 19–41 years) were recruited from the Kennedy Krieger Institute, Baltimore, Maryland, and Rush University Medical Center, including referrals from the Fragile X Online Registry With Accessible Research Database (FORWARD) of the National Fragile X Foundation (NFXF) funded by the Centers for Disease Control and Prevention (CDC), Atlanta, Georgia. The results of two of the four men with FXS (mean age 25.5 ± 2.1, range 24–27) who completed PET scans were reported in this article. Findings were compared and contrasted with five age-matched historical control men with TD who had already completed similar protocols (mean age 29.6 ± 6.02, range 24–39 years) [25,30]. Clinical and demographic data confirmed that all participants met the criteria to receive the adult dose of 185 MBqs (5 mCis) of [18F]FPEB [55].

2.2. Assessments

2.2.1. Institute for Neurodegenerative Disorders (IND)

Assessments of participants with FXS (600 to 1600 CGGs) included mean FMRP of 0.047 ± 0.04 ng/microgram total protein (reference mean FMRP of 0.87 for healthy normal controls with TD), reading level under first grade level, and scores for the Dementia Screening Questionnaire for Individuals with Intellectual Disabilities (DSQIID) [56] ranging from 0 to 2 [55].

2.2.2. Johns Hopkins University (JHU)

Assessments of participants with FXS (>200 CGGs) included mean FMRP of 0.00025, mean abbreviated IQ [57,58] of 48.5 ± 2.12 [55], and mean Adaptive Behavior Composite Standard Score [59] of 71.5 ± 26.16 [55].

2.3. Procedures

2.3.1. Magnetic Resonance Imaging (MRI)

IND

In order to minimize anxiety and claustrophobia, participants with FXS at the IND did not undergo MRI. Participants with TD underwent MRI to compare and contrast with other cohorts (N = 3) [52,55].

JHU

Participants with FXS and TD at JHU underwent MRI (Table 1) to rule out intracranial pathology and to co-register with PET [55].

2.3.2. Positron Emission Tomography (PET)

IND

With the head stabilized by a gauze strip taped across the forehead and a rounded head holder, each participant received an intravenous bolus injection of 185 MBqs (5 mCis) of [18F]FPEB [30] at 1 PM, followed by scans on an ECAT EXACT HR+ PET attaining an axial resolution of approaching y = 4–5 mm [61], with consecutive 6 × 300 s frames performed for 90 to 120 min after the injection time.
Statistical parametric mapping (SPM) [33] was applied to PET frames to obtain regional time (radioactivity) curves (TACs). The ratio of uptake in the volumes of interest (VOIs) to the uptake in the whole cerebellum, a reference region with minimal [18F]FPEB uptake [28,29], was calculated.

JHU

MRI was performed an hour before PET. Each participant with FXS underwent training using a mock scanner [62,63,64]. Each participant had a custom fitted face mask made by nuclear medical technologists to hold the head in the same position throughout the scan [65,66]. After receiving intravenous bolus injections of 185 MBq (5 mCis) of [18F]FPEB (30), participants underwent PET scans on a high resolution research tomograph (HRRT), attaining an axial resolution approaching 2.3 to 2.5 mm [67,68] at 1 PM for 90 min.
VOIs were obtained automatically of cortical regions with Freesurfer 6.0 [69,70] and of subcortical regions with the subcortical segmentation tools of the software library of the Oxford Centre for fMRI of the Brain [71,72,73]. VOIs were transferred from MRI to PET space according to MRI-to-PET co-registration parameters obtained with the co-registration module [74,75] of statistical parametric mapping (SPM) [33] and applied to PET frames to obtain regional TACs. With the cerebellar white matter as the reference VOI [28,29], regional BPNDs [32] were obtained by reference tissue graphical analysis (RTGA) [76,77].

2.3.3. Comparisons and Contrasts of Cohorts from the IND and JHU

In order to directly compare and contrast data from both cohorts including nine men with FXS (mean age 27.21 ± 4.17, range 22.3–33.6) and eight historical control age-matched men with TD who had already completed similar protocols (mean age 30.63 ± 5.58, range 24–39 years) [25,30,52,55], we approximated the data with several estimates by means of multiple assumptions: (1) consistency over time of both standard uptake volume ratios (SUVRs) and distribution volume ratios (DVRs), since JHU PET scans spanned 0 to 90 min after radiotracer injections, while IND PET scans spanned 90–120 min; (2) approximately equivalent anatomical brain regions, as MRI-based segmentation was utilized for VOI analysis at JHU, but an atlas-based approach was applied to the IND data; and (3) approximately equivalent analyses, although the resolution of the scans from the IND was approximately twice the resolution of scans from JHU. Using the measurements of SUVR from the IND dataset, we derived estimates of binding potentials as DVR-1 [78], which were pooled with the comparable BPND estimates from the JHU data.

3. Results

3.1. mGluR5s in Humans with FXS

3.1.1. IND

The density of mGluR5s was comparable in the men with FXS and the men with TD (Figure 2) [55].

3.1.2. JHU

Participant JHUFXS1 withdrew before scans due to a family emergency.
Participant JHUFXS2 completed both MRI and PET scans in one day without mock scanner training.
Due to scheduling problems, MRI and PET scans were conducted on Participant JHUFXS3 on separate days a week apart without mock scanner training. Despite the administration of 2.0 mg of lorazepam before each scan, he could not complete either scan due to anxiety and agitation.
Participant JHUFXS4 had already completed MRI scans of 30 and 60 min on separate days at another institution. For this prior investigation, a psychologist met with him online regularly for weeks before the scans to practice holding still despite the noise. He had never had a PET scan. His mother began practicing relaxation and holding still while listening to MRI sounds for weeks before the session at JHU. His mother and an investigator accompanied him into the MRI chamber throughout the MRI scan. His mother sat at the operator’s booth throughout the PET scan to praise him for holding still during the PET scan.
The non-displaceable binding potentials (BPNDs) [32] of [18F]FPEB by reference tissue graphical analysis (RTGA) [76,77] in each VOI of two men with FXS were below the BPNDs of five age-matched men with TD [25,30,55] (Figure 3). mGluR5 expression was lower in the men with FXS than the men with TD (Figure 3).

3.1.3. IND and JHU

Combined (IND and JHU) estimates of mGluR5 were significantly reduced in all eight volumes of interest (anterior cingulate, caudate, occipital, parietal, posterior cingulate, putamen, temporal, and thalamus) in the men with FXS (N = 9) in contrast to the age-matched men with TD (Figure 4, Table 2). Although the axial resolution of the IND scans was approximately twice that of the JHU scans, the combined results are striking.
Furthermore, a two-way analysis of variance on an initial pooled dataset showed that both independent variables of institution (IND and JHU, df = 1, F = 34.3, p < 0.0001) as well as diagnosis (FXS and TD, df = 1, F = 38.7, p < 0.0001) had non-random effects on regional estimates of BP [80] (Table 2).

4. Discussion

We showed the feasibility and safety of administering MRI and PET in two independent pilot samples of men with FXS. We applied PET to quantitatively measure the density of mGluR5s in cortical and subcortical brain regions of these men with FXS following exposure to [18F]FPEB), which is a first study to our knowledge. We found that mGluR5 density was significantly reduced in the cingulate, cortex, striatum, and thalamus in men with FXS in contrast to age-matched men with TD. The tracer is a novel, specific mGluR5 ligand to measure the density and distribution of mGluR5s in the brains of humans, which constitutes an effective tool to confirm target engagement of NAMs for mGluR5s. The feasibility of this complex protocol requires a multidisciplinary effort that includes mock scanner training and practice sessions taught with behavioral psychology.

4.1. mGluR5s in Humans with FXS

4.1.1. Feasibility of a Complex Protocol of MRI and PET Scans in Participants with FXS

Adults

A primary goal of this study was to determine the feasibility and safety of a complex protocol that included MRI and PET scans on men with FXS. We showed that this challenging protocol can be accomplished with mock scanner training and practice sessions taught with behavioral psychology [62,63,64] and trained parents. Additionally, an investigator and a parent routinely accompanied participants into the MRI chamber to assist with the process during the entire MRI series. Since state-of-the-art PET scanners provide three-dimensional image reconstruction, face masks may no longer be required to stabilize heads. Scans may be accomplished with gauze for optimal comfort.
We recommend several modifications to facilitate the completion of the MRI and PET scans on individuals with FXS. Mock scanner training beginning online for weeks before the actual scans provides the means to train participants and parents to relax quietly without moving while loud noises like a jackhammer are played [62,63,64]. Behavioral psychologists can meet with participants and parents repeatedly online to utilize training sessions for holding still while MRI soundtracks are played through recordings. The sessions can begin with short practices of 15 s. Gradually, the duration of the session can be increased to 30 or 60 min to train participants to calmly endure the challenges of the noise and stillness. Additionally, behavioral psychologists can provide the example of providing positive feedback to the participants. In other words, praising the participant for holding still during the practice session is a valuable positive reinforcement for desired behavior. On the other hand, criticizing the participant for moving may increase anxiety and lead to agitation and uncooperative behavior. Therefore, parents can be taught to reward the desired behavior.
Another approach to facilitate successful completion of scans includes the shortening of the duration of PET scans and the use of gauze instead of a rigid face mask. Additionally, performing PET and MRI scans on two separate days allows participants to recover from the stress of one scan before undergoing the next. The use of PET/MRI machines would simplify the protocol to accomplish both PET and MRI in a single session [81].

Adolescents and Children

Since PET involves greater than minimal risk due to radiation exposure, the safety and efficacy must be shown in adults before exposing vulnerable populations. For this reason, the current protocol was administered only to adults with FXS. After safety and efficacy are established in adults, then the procedure will be sequentially administered to adolescents, followed by children. The procedure may be modified for children to reduce the duration of scans. The procedure of the IND to conduct a 30 min scan 90 to 120 min after radiotracer injection with gauze to stabilize the head will shorten the stress of remaining on the scanner table. Another modification will be the utilization of PET/MRI scanners to conduct both PET and MRI scans in a single session instead of separate sessions for PET and MRI scans [81]. Mock scanner training by experienced behavioral psychologists [62,63,64] will be crucial to prepare children and adolescents for scans. Additionally, the participation of parents for each step is key to the accomplishment of this challenging protocol.

4.2. mGluR5 Measurement in Men with FXS

Another goal of this investigation was to find out if the study protocol can quantify mGluR5 expression in the brains of adult males with FXS. The data from our study show that the PET ligand binds mGluR5s in the brains of men with FXS, and that the expression of these receptors is decreased. This finding could be mediated by excessive upstream signaling resulting in reduced expression of mGluR5s. Internalization of the mGluR5s [20,82] throughout the brain induced by the radiotracer, the scanner, or other aspects of the environment of PET scans may explain the reductions in mGluR5s in our participants with FXS.
A preliminary attempt to perform an analysis on a combined dataset of both FXS/TD data from the IND and JHU showed that the source of the data was a non-random factor that influenced the outcome variable. We shall strive to reduce this possible confounding influence to improve the effect size in future analyses. As a future direction, we are developing other means of analyzing larger datasets from multiple institutions in a comparable manner so that the data can be pooled after removing the confounding factors of methodological differences.

4.3. Avoiding Effects of Diurnal Variations of mGluR5s

We administered PET scans to participants with FXS at the same time of day (1 PM) to minimize effects of diurnal variations of mGluR5s. Participants with TD received radiotracer injections 32 ± 120 min (range −135 to +163) from 1 PM [55], resulting in a confounding influence of diurnal variation. Large alterations in radiotracer uptake on the same individuals during the same day suggest that there may be considerable diurnal variation in mGluR5s, with increased uptake later in the day [21,83,84,85]. Participants with FXS may experience greater anxiety with scans than participants with TD. Anxiety may increase cortisol values and result in diurnal variations. Thus, we assume that our participants with FXS likely exhibited the maximal radiotracer uptake at the time of their scans. Measurement of cortisol levels and administration of PET scans at the same time of day to all participants minimizes the effects diurnal variations of mGluR5s.

4.4. Limitations and Future Studies

There is a need for comprehensive protocols uniformly administered to all cohorts. The use of different protocols for PET at the collaborating institutions [52,86] confounds comparisons and contrasts of the results. Future investigations at multiple centers will benefit from the use of identical protocols and analyses for PET and MRI conducted contemporaneously. Analysis of results by a single center will facilitate the uniformity of the findings. Despite different protocols, the uniformity of the finding of reduced mGluR5 expression in multiple brain regions independent of protocol strengthens this study’s key finding.
Administration of the full neuropsychological battery to contemporaneous cohorts at all participating centers will provide the foundation to apply statistical analyses. Normalization of cognitive test scores for participants with FXS will remove a “floor effect” [58]. Future studies will benefit from examining participants with FXS exhibiting a spectrum of ID and ASD and comparison groups without FXS with levels of ID matched to the participants with FXS.
The current pilot study is limited by the incomplete FMR1 gene and epigenetic (methylation) parameter identification, and incomplete size mosaicism and quantification of FMRP. Future studies will be enhanced by including these measures and whole exome sequencing (WES) [87] on all participants to test the hypothesis that the parameters are correlated [12].
Since increased protein synthesis has been demonstrated in fibroblasts of individuals with FXS and fmr1 KO mice [88], measurement of protein synthesis, particularly in the mTOR and ERK signaling cascades, would be a valuable parameter to correlate with mGluR5 density and distribution in future investigations of FXS in humans. However, the absence of increased protein synthesis in young men with FXS sedated with dexmedetomidine for PET with L[1-11C]leucine suggests that humans with FXS may not demonstrate the increased protein synthesis seen in animal models [89].

Multimodal Imaging

Multimodal imaging can enhance future investigations by linking PET, electroencephalography [90], event-related brain potential (ERP) [91], resting state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI), and movement measurement [92], along with quantitative measurements of FMRP and fmr1 [3]. Newly developed PET/MRI scanners [81] may produce visualization of the density and distribution of mGluR5s that is superior to images obtained from HRRT co-registered with MRI. PET/MRI units are appealing for future investigations because a single session would be required. PET/MRI provides both functional (PET) and structural (MRI) findings in one encounter. Thus, PET/MRI instrumentation and many other multimodal techniques may be utilized when available for subsequent investigations.

5. Conclusions

We showed the feasibility and safety of applying PET as a tool to quantify mGluR5 receptor expression in the brains of humans with FXS.
We showed that the proposed protocol of MR and PET scans in one day is feasible in individuals with FXS who have received mock scanner training by an experienced behavioral psychology team.
Most importantly, we found for the first time that quantified mGluR5 expression using [18F]FPEB is reduced in the living human brain of men with FXS in contrast to healthy normal age- and sex-matched controls with TD.
Larger studies with additional molecular biomarkers [93] are needed to expand on the feasibility finding of this protocol to evaluate the receptor expression of mGluR5s using [18F]FPEB as a helpful tool for the design of clinical trials of glutamatergic agents in FXS.

Author Contributions

Conceptualization, J.R.B., D.S.R., K.S., E.M.B.-K., D.F.W. and D.B.B.; data curation, J.R.B., A.N., D.S.R., D.J., O.B., A.M., S.D.M., Z.B., P.V., E.M.B.-K., D.F.W. and D.B.B.; formal analysis, J.R.B., A.N., O.B., K.S., Z.B., E.M.B.-K., D.F.W. and D.B.B.; funding acquisition, J.R.B., D.S.R., E.M.B.-K., D.F.W. and D.B.B.; investigation, J.R.B., A.N., D.S.R., D.J., K.S., T.S., S.D.M., Z.B., P.V., J.P.S., E.M.B.-K., D.F.W. and D.B.B.; methodology, J.R.B., A.N., D.S.R., D.J., O.B., A.M., K.S., T.S., S.D.M., Z.B., P.V., J.P.S., E.M.B.-K., D.F.W. and D.B.B.; project administration, J.R.B., A.N., D.S.R., D.J., A.M., P.V., J.P.S., E.M.B.-K., D.F.W. and D.B.B.; resources, J.R.B., A.N., D.S.R., O.B., A.M., T.S., P.V., J.P.S., E.M.B.-K., D.F.W. and D.B.B.; software, A.N., O.B. and S.D.M.; supervision, J.R.B., D.S.R., A.M., K.S., T.S., J.P.S., E.M.B.-K., D.F.W. and D.B.B.; validation, J.R.B., A.N., D.S.R., D.J., O.B., A.M., K.S., T.S., S.D.M., Z.B., P.V., J.P.S., E.M.B.-K., D.F.W. and D.B.B.; visualization, J.R.B., A.N., D.S.R., D.J., O.B., S.D.M., J.P.S., E.M.B.-K., D.F.W. and D.B.B.; writing—original draft preparation, J.R.B., A.N., S.D.M., E.M.B.-K., D.F.W. and D.B.B., writing—review and editing, J.R.B., A.N., D.S.R., S.D.M., E.M.B.-K. and D.B.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was made possible by a Radiology BRidge/Development Funding Initiative to STimulate and Advance Research (RAD BriteStar Bridge) Award from the Johns Hopkins University School of Medicine, Baltimore, Maryland to JRB with the assistance of DFW; the Intellectual & Developmental Disabilities Research Center (U54 HD079123), Kennedy Krieger Institute, and Johns Hopkins Medical Institutions, Baltimore, Maryland, to JRB; and the Johns Hopkins Institute for Clinical and Translational Research (ICTR), Johns Hopkins University School of Medicine, Baltimore, Maryland, to JRB, which is funded in part by Grant Number UL1 TR003098 from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the Johns Hopkins ICTR, NCATS, or NIH.

Acknowledgments

The authors thank the patients and families for their participation and dedication to these studies; they are the inspiration for our efforts at improving treatments. The authors thank the FORWARD Database and Registry of the National Fragile X Foundation (NFXF) funded by the Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, for referral of participants. The authors thank the teams of the Institute of Neurodegenerative Disorders, the Positron Emission Tomography (PET) Radiotracer Service Center, and the Research Magnetic Resonance Imaging (MRI) Service Center of the Johns Hopkins University School of Medicine for conducting the scans. The authors thank Hiroto Kuwabara for PET analysis. The authors acknowledge Rohan Panaparambil and Mathew Shneyderman for their guidance to revise the paper. The authors thank Brian Hwang for contributing to the graphical abstract. Earlier versions of this article were presented at the 2020 Annual Meeting, Society of Nuclear Medicine and Molecular Imaging, 11–14 July 2020 [86], and the World Molecular Imaging Congress 2020.

Conflicts of Interest

The authors declare no financial conflicts of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of the data, in the writing of the manuscript, or in the decision to publish the results.

Abbreviations

[18F]FPEB3-[18F]fluoro-5-(2- pyridinylethynyl)benzonitrile
ASDAutism spectrum disorder
BPNDNon-displaceable binding potential
CDCCenters for Disease Control and Prevention
DTIDiffusion tensor imaging
ERKExtracellular signal-regulated kinase
ERPEvent-related brain potential
FORWARDFragile X Online Registry With Accessible Research Database of the National Fragile X Foundation (NFXF)
FMR1Fragile X mental retardation 1
FMRPFragile X Mental Retardation Protein
FXSFragile X syndrome
IDIntellectual disability
LTDLong-term depression
MAPKMitogen-activated protein kinase
MBqMegabecquerel
mCiMillicurie
mGluR5Metabotropic glutamate receptor subtype 5
MRIMagnetic resonance imaging
mTORMammalian target of rapamycin (mTOR)
NAMNegative allosteric modulator
NFXFNational Fragile X Foundation
PETPositron emission tomography
PET/MRIPositron emission tomography/magnetic resonance imaging
rs-FMRIResting-state functional magnetic resonance imaging
RTGAReference tissue graphical analysis
SPMStatistical parametric mapping
TACsTime activity curves
TDTypical development
VOIsVolumes of interest
(period)Missing data

References

  1. Bardoni, B.; Schenck, A.; Mandel, J.-L. The Fragile X Mental Retardation Protein. Brain Res. Bull. 2001, 56, 375–382. [Google Scholar] [CrossRef]
  2. Brasic, J.R.; Farhadi, F.; Elshourbagy, T. Autism Spectrum Disorder. Medscape Drugs & Diseases. Updated 18 March 2020. Available online: http://emedicine.medscape.com/article/912781-overview (accessed on 21 November 2020).
  3. Budimirovic, D.B.; Berry-Kravis, E.; Erickson, C.A.; Hall, S.S.; Hessl, D.; Reiss, A.L.; King, M.K.; Abbeduto, L.; Kaufmann, W.E. Updated report on tools to measure outcomes of clinical trials in fragile X syndrome. J. Neurodev. Disord. 2017, 9, 14. [Google Scholar] [CrossRef] [PubMed]
  4. Budimirovic, D.B.; Kaufmann, W.E. What can we learn about autism from studying fragile X syndrome? Dev. Neurosci. 2011, 33, 379–394. [Google Scholar] [CrossRef] [PubMed]
  5. Budimirovic, D.B.; Subramanian, M. Neurobiology of autism and intellectual disability: Fragile X syndrome. In Neurobiology of Disease, 2nd ed.; Johnston, M.V., Ed.; Oxford University Press: New York, NY, USA, 2016; pp. 375–384. [Google Scholar]
  6. Hagerman, R.J.; Des-Portes, V.; Gasparini, F.; Jacquemont, S.; Gomez-Mantilla, B. Translating molecular advances in fragile X syndrome into therapy: A review. J. Clin. Psychiatry 2014, 75, e294–e307. [Google Scholar] [CrossRef] [PubMed]
  7. Hagerman, R.J.; Berry-Kravis, E.; Kaufmann, W.E.; Ono, M.Y.; Tartaglia, N.; Lachiewicz, A.; Kronk, R.; Delahunty, C.; Hessl, D.; Visootsak, J.; et al. Advances in the treatment of fragile X syndrome. Pediatrics 2009, 123, 378–390. [Google Scholar] [CrossRef] [PubMed]
  8. Kaufmann, W.E.; Capone, G.; Clarke, M.; Budimirovic, D.B. Autism in genetic intellectual disability: Insights into idiopathic autism. In Autism: Current Theories and Evidence; Zimmerman, A.W., Ed.; The Humana Press Inc.: Totowa, NJ, USA, 2008; pp. 81–108. [Google Scholar]
  9. Pretto, D.I.; Kumar, M.; Cao, Z.; Cunningham, C.L.; Durbin-Johnson, B.; Qi, L.; Berman, R.; Noctor, S.C.; Hagerman, R.J.; Pessah, I.N.; et al. Reduced excitatory amino acid transporter 1 and metabotropic glutamate receptor 5 expression in the cerebellum of fragile X mental retardation gene 1 premutation carriers with fragile X-associated tremor/ataxia syndrome. Neurobiol. Aging 2014, 35, 1189–1197. [Google Scholar] [CrossRef]
  10. Ascano, M., Jr.; Mukherjee, N.; Bandaru, P.; Miller, J.B.; Nusbaum, J.D.; Corcoran, D.L.; Langlois, C.; Munschauer, M.; Dewell, S.; Hafner, M.; et al. FMRP targets distinct mRNA sequence elements to regulate protein expression. Nature 2012, 492, 382–386. [Google Scholar] [CrossRef]
  11. Darnell, J.C.; Van Driesche, S.J.; Zhang, C.; Hung, K.Y.S.; Mele, A.; Fraser, C.E.; Stone, E.F.; Chen, C.; Fak, J.J.; Chi, S.W.; et al. FMRP stalls ribosomal translocation on mRNAs linked to synaptic function and autism. Cell 2011, 146, 247–261. [Google Scholar] [CrossRef]
  12. Budimirovic, D.B.; Schlageter, A.; Filopovic-Sadic, S.; Protic, D.D.; Bram, E.; Mahone, E.M.; Nicholson, K.; Culp, K.; Javanmardi, K.; Kemppainnen, J.; et al. A genotype-phenotype study of high-resolution FMR1 nucleic acid and protein analyses in fragile X patients with neurobehavioral assessments. Brain Sci. 2020, 10, 694. [Google Scholar] [CrossRef]
  13. Bagni, C.; Zukin, R.S. A synaptic perspective of fragile X syndrome and autism spectrum disorders. Neuron 2019, 101, 1070–1088. [Google Scholar] [CrossRef]
  14. Bear, M.F.; Huber, K.M.; Warren, S.T. The mGluR theory of fragile X mental retardation. Trends Neurosci. 2004, 27, 370–377. [Google Scholar] [CrossRef] [PubMed]
  15. D’Antoni, S.; Spatuzza, M.; Bonaccorso, C.M.; Musumeci, S.A.; Ciranna, L.; Nicoletti, F.; Huber, K.M.; Catania, M.V. Dysregulation of group-1 metabotropic glutamate (mGlu) receptor mediated signalling in disorders associated with intellectual disability and autism. Neurosci. Biobehav. Rev. 2014, 46 (Pt 2), 228–241. [Google Scholar] [CrossRef]
  16. Hajós, M. Portraying inhibition of metabotropic glutamate receptor 5 in fragile X mice. Biol. Psychiatry 2014, 75, 177–178. [Google Scholar] [CrossRef] [PubMed]
  17. Hinton, V.J.; Brown, W.T.; Wisniewski, K.; Rudelli, R.D. Analysis of neocortex in three males with the fragile X syndrome. Am. J. Med. Genet. 1991, 41, 289–294. [Google Scholar] [CrossRef] [PubMed]
  18. Kaufmann, W.E.; Moser, H.W. Dendritic anomalies in disorders associated with mental retardation. Cereb. Cortex 2000, 10, 981–991. [Google Scholar] [CrossRef] [PubMed]
  19. Lohith, T.G.; Osterweil, E.K.; Fujita, M.; Jenko, K.J.; Bear, M.F.; Innis, R.B. Is metabotropic glutamate receptor 5 upregulated in prefrontal cortex in fragile X syndrome? Mol. Autism 2013, 4, 15. [Google Scholar] [CrossRef]
  20. Jong, Y.-J.I.; Harmon, S.K.; O’Malley, K.L. Location and cell-type-specific bias of metabotropic glutamate receptor, mGlu5, negative allosteric modulators. ACS Chem. Neurosci. 2019, 10, 4558–4570. [Google Scholar] [CrossRef]
  21. DeLorenzo, C.; Gallezot, J.-D.; Gardus, J.; Yang, J.; Planeta, B.; Nabulsi, N.; Ogden, R.T.; Labaree, D.C.; Huang, Y.H.; Mann, J.J.; et al. In vivo variation in same-day estimates of metabotropic glutamate receptor subtype 5 binding using [11C]ABP688 and [18F]FPEB. J. Cereb. Blood Flow Metab. 2017, 37, 2716–2727. [Google Scholar] [CrossRef]
  22. Ansari, M.S.; Jones, C.K.; Felts, A.S.; Lindsley, C.W.; Alagille, D.; Tamagnan, G.D.; Kessler, R.M.; Baldwin, R.M. One pot synthesis of [18F]FPEB in a semi-automated module. J. Labelled Comp. Radiopharm. 2009, 52 (Suppl. 1), 318. [Google Scholar]
  23. Barret, O.; Tamagnan, G.; Batis, J.; Jennings, D.; Zubal, G.; Russel, D.; Marek, K.; Seibyl, J. Quantitation of glutamate mGluR5 receptor with 18F-FPEB PET in humans. Neuroimage 2010, 52 (Suppl. 1), S202. [Google Scholar] [CrossRef]
  24. Brasic, J.R.; Syed, A.B.; Farhadi, F.; Wong, D.F. PET Scanning in Autism Spectrum Disorder. Medscape Drugs & Diseases. Updated 16 April 2020. Available online: http://emedicine.medscape.com/article/1155568-overview (accessed on 21 November 2020).
  25. Fatemi, S.H.; Wong, D.F.; Brašić, J.R.; Kuwabara, H.; Mathur, A.; Folsom, T.D.; Jacob, S.; Realmuto, G.M.; Pardo, J.V.; Lee, S. Metabotropic glutamate receptor 5 tracer [18F]-FPEB displays increased binding potential in postcentral gyrus and cerebellum of male individuals with autism: A pilot PET study. Cerebellum Ataxias 2018, 5, 3. [Google Scholar] [CrossRef]
  26. Leurquin-Sterk, G.; Postnov, A.; Celen, S.; de Laat, B.; Bormans, G.; Van Laere, K.J. Kinetic modeling and longterm test-retest of 18F-FPEB mGluR5 PET in healthy volunteers. J. Nucl. Med. 2015, 56 (Suppl. 3), 49. [Google Scholar]
  27. Leurquin-Sterk, G.; Postnov, A.; de Laat, B.; Casteels, C.; Celen, S.; Crunelle, C.L.; Bormans, G.; Koole, M.; Van Laere, K. Kinetic modeling and long-term test-retest reproducibililty of the mGluR5 PET tracer 18F-FPEB in human brain. Synapse 2016, 70, 153–162. [Google Scholar] [CrossRef] [PubMed]
  28. Sullivan, J.M.; Lim, K.; Labaree, D.; Lin, S.-F.; McCarthy, T.J.; Seibyl, J.P.; Tamagnan, G.; Huang, Y.; Carson, R.E.; Ding, Y.-S.; et al. Kinetic analysis of the metabotropic glutamate subtype 5 tracer [18F]FPEB in bolus and bolus plus-constant-infusion studies in humans. J. Cereb. Blood Flow Metab. 2013, 33, 532–541. [Google Scholar] [CrossRef] [PubMed]
  29. Sullivan, J.; Planeta-Wilson, B.; Lim, K.; Lin, S.F.; Najafzadeh, S.; McCarthy, T.; Ding, Y.S.; Carson, R.E.; Morris, E.D.; Williams, W.A. Test-retest evaluation of [F-18] FPEB, a PET tracer for the mGluR5 receptors in humans. J. Cereb. Blood Flow Metab. 2012, 32 (Suppl. 1), S122–S123. [Google Scholar]
  30. Wong, D.F.; Waterhouse, R.; Kuwabara, H.; Kim, J.; Brašić, J.R.; Chamroonrat, W.; Stabins, M.; Holt, D.P.; Dannals, R.F.; Hamill, T.G.; 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. J. Nucl. Med. 2013, 54, 388–396. [Google Scholar] [CrossRef]
  31. Brašić, J.R.; Mathur, A.K.; Budimirovic, D.B. The urgent need for molecular imaging to confirm target engagement for clinical trials of fragile X syndrome and other subtypes of autism spectrum disorder. Arch. Neurosci. 2019, 6, e91831. [Google Scholar] [CrossRef]
  32. Innis, R.B.; Cunninghamm, V.J.; Delforge, J.; Fujita, M.; Gjedde, A.; Gunn, R.N.; Holden, J.; Houle, S.; Huang, S.C.; Ichise, M.; et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J. Cereb. Blood Flow Metab. 2007, 27, 1533–1539. [Google Scholar] [CrossRef]
  33. The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK. Statistical Parametric Mapping (SPM). 2020. Available online: http://www.fil.ion.ucl.ac.uk/spm/ (accessed on 21 November 2020).
  34. Russell, D.; Jennings, D.; Tamagnan, G.; Seibyl, J.; Koren, A.; Zubal, G.; Marek, K. Evaluation of novel radiotracers targeting non-dopaminergic striatal biomarkers in HD: 18F-FPEB and PET imaging for metabotropic glutamate receptor type 5 (mGluR5) expression in healthy subjects and subjects with Huntington disease (HD). Neurotherapeutics 2010, 7, 142. [Google Scholar] [CrossRef]
  35. Russell, D.S.; Jennings, D.L.; Tamagnan, G.; Alagilles, D.; Carson, R.E.; Barret, O.; Batis, J.; Koren, A.; Zubal, G.; Seibyl, J.P.; et al. Evaluation of novel radiotracers targeting non-dopaminergic striatal biomarkers in HD: [18F] FPEB and PET imaging for metabotrophic glutamate receptor type 5 (mGluR5) in healthy subjects and subjects with Huntington’s disease (HD). Mov. Disord. 2010, 25 (Suppl. 2), S391–S392. [Google Scholar] [CrossRef]
  36. Russell, D.; Tamagnan, G.; Barrett, O.; Seibyl, J.; Marek, K. Evaluation of mGluR5 in early Parkinson’s disease using 18F-FPEB PET imaging. Mov. Disord. 2010, 25 (Suppl. 2), S383–S384. [Google Scholar]
  37. Wang, J.Q.; Tueckmantel, W.; Zhu, A.J.; Pellegrino, D.; Brownell, A.L. Synthesis and preliminary biological evaluation of 3-[F-18]fluoro-5-(2-pyridinylethynyl)benzonitrile as a PET radiotracer for imaging metabotropic glutamate receptor subtype 5. Synapse 2007, 61, 951–961. [Google Scholar] [CrossRef] [PubMed]
  38. Seibyl, J.; Russell, D.; Jennings, D.; Marek, K. Neuroimaging over the course of Parkinson’s disease: From early detection of the at-risk patient to improving pharmacotherapy of later-stage disease. Semin. Nucl. Med. 2012, 42, 406–414. [Google Scholar] [CrossRef] [PubMed]
  39. Berry-Kravis, E.; Des Portes, V.; Hagerman, R.; Jacquemont, S.; Charles, P.; Visootsak, J.; Brinkman, M.; Rerat, K.; Koumaras, B.; Zhu, L.; et al. Mavoglurant in fragile X syndrome: Results of two randomized, double-blind, placebo-controlled trials. Sci. Transl. Med. 2016, 8, 321ra5. [Google Scholar] [CrossRef]
  40. Berry-Kravis, E.; Hagerman, R.; Visootsak, J.; Budimirovic, D.; Kaufmann, W.E.; Cherubini, M.; Zarevics, P.; Walton-Bowen, K.; Wang, P.; Bear, M.F.; et al. Arbaclofen in fragile X syndrome: Results of phase 3 trials. J. Neurodev. Disord. 2017, 9, 3. [Google Scholar] [CrossRef]
  41. Berry-Kravis, E.; Hessl, D.; Coffey, S.; Hervey, C.; Schneider, A.; Yuhas, J.; Hutchison, J.; Snape, M.; Tranfaglia, M.; Nguyen, D.V.; et al. A pilot open label, single dose trial of fenobam in adults with fragile X syndrome. J. Med. Genet. 2009, 46, 266–271. [Google Scholar] [CrossRef]
  42. Berry-Kravis, E.M.; Hessl, D.; Rathmell, B.; Zarevics, P.; Cherubini, M.; Walton-Bowen, K.; Mu, Y.; Nguyen, D.V.; Gonzalez-Heydrich, J.; Wang, P.P.; et al. Effects of STX209 (arbaclofen) on neurobehavioral function in children and adults with fragile X syndrome: A randomized, controlled, phase 2 trial. Sci. Transl. Med. 2012, 4, 152ra127. [Google Scholar] [CrossRef]
  43. Berry-Kravis, E.; Hessl, D.; Abbeduto, L.; Reiss, A.L.; Beckel-Mitchener, A.; Urv, T.K. Outcome measures for clinical trials in fragile X syndrome. J. Dev. Behav. Pediatr. 2013, 34, 508–522. [Google Scholar] [CrossRef]
  44. Berry-Kravis, E.M.; Lindemann, L.; Jønch, A.E.; Apostol, G.; Bear, M.F.; Carpenter, R.L.; Crawley, J.N.; Curie, A.; Des Portes, V.; Hossain, F.; et al. Drug development for neurodevelopmental disorders: Lessons learned from fragile X syndrome. Nat. Rev. Drug Discov. 2018, 17, 280–299. [Google Scholar] [CrossRef]
  45. Budimirovic, D.B.; Duy, P.Q. Neurobehavioral features and targeted treatments in fragile X syndrome: Current insights and future directions. Engrami 2015, 37, 5–19. [Google Scholar] [CrossRef]
  46. Budimirovic, D.B.; Duy, P.Q. Challenges in translating therapeutic frontiers in clinical trials: Where are we now and what’s next? Madridge J. Neuroscience 2016, 1, e1–e3. [Google Scholar] [CrossRef]
  47. Duy, P.Q.; Budimirovic, D.B. Fragile X syndrome: Lessons learned from the most translated neurodevelopmental disorder in clinical trials. Transl. Neurosci. 2017, 8, 7–8. [Google Scholar] [CrossRef] [PubMed]
  48. Erickson, C.A.; Davenport, M.H.; Schaefer, T.L.; Wink, L.K.; Pedapati, E.V.; Sweeney, J.A.; Fitzpatrick, S.E.; Brown, W.T.; Budimirovic, D.; Hagerman, R.J.; et al. Fragile X targeted pharmacotherapy: Lessons learned and future directions. J. Neurodev. Disord. 2017, 9, 7. [Google Scholar] [CrossRef] [PubMed]
  49. Jønch, A.E.; Jacquemont, S. Reflections on clinical trials in fragile X syndrome. In Fragile X Syndrome: From Genetics to Targeted Treatment; Willemsen, R., Kooy, R.F., Eds.; Academic: London, UK, 2017; pp. 419–441. [Google Scholar]
  50. Ligsay, A.; Hagerman, R.; Berry-Kravis, E. Overview of targeted double-blind, placebo-controlled clinical trials in fragile X syndrome. In Fragile X Syndrome: From Genetics To Targeted Treatment; Willemsen, R., Kooy, R.F., Eds.; Academic: London, UK, 2017; pp. 401–418. [Google Scholar]
  51. Ligsay, A.; Van Dijck, A.; Nguyen, D.V.; Lozano, R.; Chen, Y.; Bickel, E.S.; Hessl, D.; Schneider, A.; Angkustsir, K.; Tassone, F.; et al. A randomized double-blind, placebo controlled trial of ganaxolone in children and adolescents with fragile X syndrome. J. Neurodev. Disord. 2017, 9, 26. [Google Scholar] [CrossRef]
  52. Russell, D. A PET Brain Imaging Study of mGluR5 in Subjects with Neuropsychiatric Conditions (FPEB). ClinicalTrials.gov Identifier: NCT00870974 2017. Available online: https://clinicaltrials.gov/ct2/show/NCT00870974 (accessed on 21 November 2020).
  53. World Medical Association. Declaration of Helsinki: Medical Research Involving Human Subjects. 2013. Available online: https://www.wma.net/what-we-do/medical-ethics/declaration-of-helsinki/ (accessed on 21 November 2020).
  54. International Committee of Medical Journal Editors (ICMJE). Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. 2019. Available online: http://www.icmje.org/icmje-recommendations.pdf (accessed on 21 November 2020).
  55. Brasic, J.R.; Nandi, A.; Russell, D.S.; Jennings, D.; Barret, O.; Mathur, A.; Slifer, K.; Sedlak, T.; Martin, S.D.; Brinson, Z.; et al. Dataset of Reduced cerebral expression of metabotropic glutamate receptor subtype 5 in men with fragile X syndrome. Available online: https://doi.org/10.5281/zenodo.4279744 (accessed on 23 November 2020).
  56. Deb, S.; Hare, M.; Prior, L.; Bhaumick, S. Dementia Screening Questionnaire for Individuals with Intellectual Disabilities. Br. J. Psychiatry 2007, 190, 440–444. [Google Scholar] [CrossRef]
  57. Roid, G.H. Stanford-Binet Intelligence Scales, 5th ed.; (SB-5); Western Psychological Services (WPS): Torrance, CA, USA, 2003. [Google Scholar]
  58. Hessl, D.; Nguyen, D.V.; Green, C.; Chavez, A.; Tassone, F.; Hagerman, R.J.; Senturk, D.; Schneider, A.; Lightbody, A.; Reiss, A.L.; et al. A solution to limitations of cognitive testing in children with intellectual disabilities: The case of fragile X syndrome. J. Neurodev. Disord. 2009, 1, 33–45. [Google Scholar] [CrossRef]
  59. Sparrow, S.S.; Cicchetti, D.V.; Saulnier, C.A. Vineland Adaptive Behavior Scales, 3rd ed.; (Vineland-3); Pearson: San Antonio, TX, USA, 2020. [Google Scholar]
  60. Brašić, J.R.; Zhou, Y.; Musachio, J.L.; Hilton, J.; Fan, H.; Crabb, A.; Endres, C.J.; Reinhardt, M.J.; Dogan, A.S.; Alexander, M.; et al. Single photon emission computed tomography experience with (S)5-[123I]iodo-3-(2-azetidinylmethoxy)pyridine in the living human brain of smokers and nonsmokers. Synapse 2009, 63, 339–358. [Google Scholar] [CrossRef]
  61. Wienhard, K.; Dahlbom, M.; Eriksson, L.; Michel, C.; Bruckbauer, T.; Pietrzyk, U.; Heiss, W.-D. The ECAT EXACT HR: Performance of a new high resolution positron scanner. J. Comput. Assist. Tomogr. 1994, 18, 110–118. [Google Scholar] [CrossRef]
  62. Cox, A.D.; Virues-Ortega, J.; Julio, F.; Martin, T.L. Establishing motion control in children with autism and intellectual disability: Applications for anatomical and functional MRI. J. Appl. Behav. Anal. 2017, 50, 8–26. [Google Scholar] [CrossRef]
  63. Slifer, K.J.; Cataldo, M.F.; Cataldo, M.D.; Llorente, A.M.; Gerson, A.C. Behavior analysis of motion control for pediatric neuroimaging. J. Appl. Behav. Anal. 1993, 26, 469–470. [Google Scholar] [CrossRef]
  64. Slifer, K.J.; Koontz, K.L.; Cataldo, F. Operant-contingency-based preparation of children for functional magnetic resonance imaging. J. Appl. Behav. Anal. 2002, 35, 191–194. [Google Scholar] [CrossRef] [PubMed]
  65. Brašić, J.R.; Bibat, G.; Kumar, A.; Zhou, Y.; Hilton, J.; Yablonski, M.E.; Dogan, A.S.; Guevara, M.R.; Stephane, M.; Johnston, M.; et al. Correlation of the vesicular acetylcholine transporter densities in the striata to the clinical abilities of women with Rett syndrome. Synapse 2012, 66, 471–482. [Google Scholar] [CrossRef] [PubMed]
  66. Brašić, J.R.; Cascella, N.; Kumar, A.; Zhou, Y.; Hilton, J.; Raymont, V.; Crabb, A.; Guevara, M.R.; Horti, A.G.; Wong, D.F. Positron emission tomography (PET) experience with 2-[18F]fluoro-3-(2(S)-azetidinylmethoxy)pyridine (2-[18F]FA) in the living human brain of smokers with paranoid schizophrenia. Synapse 2012, 66, 352–368. [Google Scholar] [CrossRef] [PubMed]
  67. Rahmim, A.; Cheng, J.-C.; Blinder, S.; Camborde, M.-L.; Sossi, V. Statistical dynamic image reconstruction in state-of-the-art high-resolution PET. Phys. Med. Biol. 2005, 50, 4887–4912. [Google Scholar] [CrossRef] [PubMed]
  68. Sossi, V.; de Jong, H.W.A.M.; Barker, W.C.; Bloomfield, P.; Burbar, Z.; Camborde, M.-L.; Comtat, C.; Eriksson, L.A.; Houle, S.; Keator, D.; et al. The second generation HRRT—A multi-centre scanner performance investigation. IEEE Nucl. Sci. Symp. Conf. Ref. 2005, 4, 2195–2199. [Google Scholar]
  69. Fischl, B.; van der Kouwe, A.; Destrieux, C.; Halgren, E.; Ségonne, F.; Salat, D.H.; Busa, E.; Seidman, L.J.; Goldstein, J.; Kennedy, D.; et al. Automatically parcellating the human cerebral cortex. Cereb. Cortex 2004, 14, 11–22. [Google Scholar] [CrossRef]
  70. Hoopes, A. (Ed.) FreeSurfer Download and Install. 2020. Available online: https://surfer.nmr.mgh.harvard.edu/fswiki/DownloadAndInstall (accessed on 21 November 2020).
  71. Jenkinson, M.; Beckmann, C.F.; Behrens, T.E.J.; Woolrich, M.W.; Smith, S.M. FSL. Neuroimage 2012, 62, 782–790. [Google Scholar] [CrossRef]
  72. Patenaude, B.; Smith, S.M.; Kennedy, D.N.; Jenkinson, M. A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage 2011, 56, 907–922. [Google Scholar] [CrossRef]
  73. Woolrich, M.W.; Jbabdi, S.; Patenaude, B.; Chappell, M.; Makni, S.; Behrens, T.; Beckmann, C.; Jenkinson, M.; Smith, S.M. Bayesian analysis of neuroimaging data in FSL. Neuroimage 2009, 45 (Suppl. 1), S173–S186. [Google Scholar] [CrossRef] [PubMed]
  74. Ashburner, J.; Friston, K.J. High-dimensional image warping. In Human Brain Function, 2nd ed.; Frackowiak, R.S.J., Ashburner, J., Penny, W.D., Zeki, S., Friston, K.J., Frith, C., Dolan, R., Price, C.J., Eds.; Academic: Waltham, MA, USA, 2004; pp. 656–673. [Google Scholar]
  75. Ashburner, J.; Friston, K.J. Rigid body registration. In Human Brain Function, 2nd ed.; Frackowiak, R.S.J., Ashburner, J., Penny, W.D., Zeki, S., Friston, K.J., Frith, C., Dolan, R., Price, C.J., Eds.; Academic: Waltham, MA, USA, 2004; pp. 635–654. [Google Scholar]
  76. Logan, J.; Volkow, N.D.; Wang, G.J.; Ding, Y.S.; Alexoff, D.L. Distribution volume ratios without blood sampling from graphical analysis of PET data. J. Cerebral. Blood Flow Metab. 1996, 16, 834–840. [Google Scholar] [CrossRef]
  77. Logan, J.; Alexoff, D.; Fowler, J.S. The use of alternative forms of graphical analysis to balance bias and precision in PET images. J. Cereb. Blood Flow Metab. 2011, 31, 535–546. [Google Scholar] [CrossRef]
  78. Carson, R.E. Tracer kinetic modeling in PET. In Positron Emission Tomography: Basic Science and Clinical Practice; Valk, P.E., Bailey, D.L., Townsend, D.W., Maisey, M.N., Eds.; Springer: London, UK, 2003; pp. 147–179. [Google Scholar]
  79. Wickham, H. ggplot2: Elegant Graphics for Data Analysis; Springer: New York, NY, USA, 2009. [Google Scholar]
  80. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2017; Available online: https:www.R-project-org (accessed on 29 September 2020).
  81. Catana, C. Principles of simultaneous PET/MR imaging. Magn. Reson. Imaging Clin. N. Am. 2017, 25, 231–243. [Google Scholar] [CrossRef]
  82. Trivedi, R.R.; Bhattacharyya, S. Constitutive internalization and recycling of metabotropic glutamate receptor 5 (mGluR5). Biochem. Biophys. Res. Commun. 2012, 427, 185–190. [Google Scholar] [CrossRef]
  83. Castañeda, T.R.; de Prado, B.M.; Prieto, D.; Mora, F. Circadian rhythms of dopamine, glutamate and GABA in the striatum and nucleus accumbens of the awake rat: Modulation by light. J. Pineal Res. 2004, 36, 177–185. [Google Scholar] [CrossRef] [PubMed]
  84. Fuller, P.M.; Gooley, J.J.; Saper, C.B. Neurobiology of the sleep-wake cycle: Sleep architecture, circadian regulation, and regulatory feedback. J. Biol. Rhythm. 2006, 21, 482–493. [Google Scholar] [CrossRef] [PubMed]
  85. Meng, T.; Yuan, S.; Zheng, Z.; Liu, T.; Lin, L. Effects of endogenous melatonin on glutatmate and GABA rhythms in the striatum of unilateral 6-hydroxydopamine-lesioned rats. Neuroscience 2015, 286, 308–315. [Google Scholar] [CrossRef] [PubMed]
  86. Brasic, J.; Budimirovic, D.; Mathur, A.; Nandi, A.; Mahone, E.; Slifer, K.; Brinson, Z.; Sedlak, T.; Ryan, M.; Landa, R.; et al. Metabotropic Glutamate Receptor Subtype 5 Function in Fragile X Syndrome. J. Nucl. Med. 2020, 61 (Suppl. 1), 1552. Available online: http://jnm.snmjournals.org/content/61/supplement_1/1552.abstract?sid=7a58a0b9-ec27-42f3-b06e-7ded1f2dc2c8 (accessed on 21 November 2020).
  87. Darnell, R.B. The genetic control of stoichiometry underlying autism. Annu. Rev. Neurosci. 2020, 43, 509–533. [Google Scholar] [CrossRef] [PubMed]
  88. Jacquemont, S.; Pacini, L.; Jønch, A.E.; Cencelli, G.; Rozenberg, I.; He, Y.; D’Andrea, L.; Pedini, G.; Eldeeb, M.; Willemsen, R.; et al. Protein synthesis levels are increased in a subset of individuals with fragile X syndrome. Hum. Mol. Genet. 2018, 27, 2039–2051, Erratum in: Hum. Mol. Genet. 2018, 27. [Google Scholar] [CrossRef]
  89. Schmidt, K.C.; Loutaev, I.; Quezado, Z.; Sheeler, C.; Smith, C.B. Regional rates of brain protein synthesis are unaltered in dexmedetomidine sedated young men with fragile X syndrome: A L-[1-11C]leucine PET study. Neurobiol. Dis. 2020, 143, 104978. [Google Scholar] [CrossRef]
  90. Razak, K.A.; Dominick, K.C.; Erickson, C.A. Developmental studies in fragile X syndrome. J. Neurodev. Disord. 2020, 12, 13. [Google Scholar] [CrossRef]
  91. Li, W.; Kutas, M.; Gray, J.A.; Hagerman, R.H.; Olichney, J.M. The role of glutamate in language and language disorders—Evidence from ERP and pharmacological studies. Neurosci. Biobehav. Rev. 2020, 119, 217–241. [Google Scholar] [CrossRef] [PubMed]
  92. McKay, G.N.; Harrigan, T.P.; Brasic, J.R. A low-cost quantitative continuous measurement of movements in the extremities of people with Parkinson’s disease. MethodsX 2019, 6, 169–189. [Google Scholar] [CrossRef] [PubMed]
  93. Zafarullah, M.; Tassone, F. Molecular biomarkers in fragile X syndrome. Brain Sci. 2019, 9, 96. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Transaxial (A) and sagittal (B) non-displaceable binding potential (BPND) [32] images of [18F]FPEB (top) and matching magnetic resonance (MR) images (bottom) in statistical parametric mapping (SPM) [33] standard space. Regions with high BPND values, namely insular (In), temporal (Tp), and cingulate (Cg) cortices, are indicated on co-registered MR images [30]. This research was originally published in JNM. Wong DF, Waterhouse R, Kuwabara H, Kim J, Brašić JR, Chamroonrat W, Stabins M, Holt DP, Dannals RF, Hamill TG, Mozley PD. 18F-FPEB, a PET radiopharmaceutical for quantifying metabotropic glutamate 5 receptors: a first-in-human study of radiochemical safety, biokinetics, and radiation dosimetry. J Nucl Med. 2013;54:388-396. © SNMMI [30].
Figure 1. Transaxial (A) and sagittal (B) non-displaceable binding potential (BPND) [32] images of [18F]FPEB (top) and matching magnetic resonance (MR) images (bottom) in statistical parametric mapping (SPM) [33] standard space. Regions with high BPND values, namely insular (In), temporal (Tp), and cingulate (Cg) cortices, are indicated on co-registered MR images [30]. This research was originally published in JNM. Wong DF, Waterhouse R, Kuwabara H, Kim J, Brašić JR, Chamroonrat W, Stabins M, Holt DP, Dannals RF, Hamill TG, Mozley PD. 18F-FPEB, a PET radiopharmaceutical for quantifying metabotropic glutamate 5 receptors: a first-in-human study of radiochemical safety, biokinetics, and radiation dosimetry. J Nucl Med. 2013;54:388-396. © SNMMI [30].
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Figure 2. Dot plots of the ratio of densities of mGluR5 in volumes of interest (VOIs) to whole cerebellum for participants from the Institute for Neurodegenerative Disorders (IND) with FXS (N = 7) and TD (N = 3) who received intravenous bolus injections of 185 MBqs (5 mCis) of [18F]FPEB [55,79].
Figure 2. Dot plots of the ratio of densities of mGluR5 in volumes of interest (VOIs) to whole cerebellum for participants from the Institute for Neurodegenerative Disorders (IND) with FXS (N = 7) and TD (N = 3) who received intravenous bolus injections of 185 MBqs (5 mCis) of [18F]FPEB [55,79].
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Figure 3. Dot plot of non-displaceable binding potential (BPND) [32] images by reference tissue graphical analysis (RTGA) [76,77] of volumes of interest on positron emission tomography (PET) for 90 min of participants with FXS and ID (N = 2) and TD (N = 5) who received intravenous bolus injections of 185 MBqs (5 mCis) of [18F]FPEB [25,30,55,79].
Figure 3. Dot plot of non-displaceable binding potential (BPND) [32] images by reference tissue graphical analysis (RTGA) [76,77] of volumes of interest on positron emission tomography (PET) for 90 min of participants with FXS and ID (N = 2) and TD (N = 5) who received intravenous bolus injections of 185 MBqs (5 mCis) of [18F]FPEB [25,30,55,79].
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Figure 4. Dot plot of estimated binding potential (BP) [32] images by positron emission tomography after intravenous bolus injections of 185 MBqs (5 mCis) of [18F]FPEB [25,30] for men with fragile X syndrome (N = 9) and age-matched men with typical development (N = 8) from the IND and JHU [52,55,79].
Figure 4. Dot plot of estimated binding potential (BP) [32] images by positron emission tomography after intravenous bolus injections of 185 MBqs (5 mCis) of [18F]FPEB [25,30] for men with fragile X syndrome (N = 9) and age-matched men with typical development (N = 8) from the IND and JHU [52,55,79].
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Table 1. Characterization of MRI sequences of the brain.
Table 1. Characterization of MRI sequences of the brain.
FormatTime to Repetition (TR) (ms)Time to Echo (TE) (ms)Thickness (mm)Number of Slices
T1 sagittal50085.021
T1 SPGR recalled acquisition in the steady-state axial3561.5124
T2 oblique5900955.027
DTI12,100882.072
Reproduced with permission [60]. The parameters of DTI include a slice thickness of 2 × 2 × 2 mm, field of view of 240 mm, iPAT (acceleration factor) of 2, 30 directions, and a b value of 1000 s/mm2. Abbreviations: MRI, magnetic resonance imaging; DTI, diffusion tensor imaging; SPGR, spoiled gradient.
Table 2. Analysis of variance of estimates of mGluR5 expression by positron emission tomography after intravenous bolus injections of 185 MBqs (5 mCis) of [18F]FPEB in cortical and subcortical regions in the combined sample of men with fragile X syndrome (N = 9) and age-matched men with typical development (N = 8).
Table 2. Analysis of variance of estimates of mGluR5 expression by positron emission tomography after intravenous bolus injections of 185 MBqs (5 mCis) of [18F]FPEB in cortical and subcortical regions in the combined sample of men with fragile X syndrome (N = 9) and age-matched men with typical development (N = 8).
RegionTermdfSum of SquaresF Statisticp-Value
Anterior CingulateDiagnosis15.6915.10.00165
Source15.9315.70.00141
CaudateDiagnosis14.9310.60.00569
Source11.222.620.128
OccipitalDiagnosis14.3723.10.000279
Source14.92260.000163
ParietalDiagnosis15.3218.90.000675
Source18.5830.40.000076
Posterior CingulateDiagnosis13.1817.60.000906
Source17.0438.92.18E-05
PutamenDiagnosis15.418.40.000753
Source13.110.60.00583
TemporalDiagnosis17.0717.90.000834
Source15.92150.00169
ThalamusDiagnosis13.3223.70.000249
Source11.067.550.0157
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