Modulation of Abnormal Metabolic Brain Networks by Experimental Therapies in a Nonhuman Primate Model of Parkinson Disease: An Application to Human Retinal Pigment Epithelial Cell Implantation

Clinical considerations in Parkinson's disease cell therapy

Cell replacement therapy is an area of increasing interest for treating Parkinson's disease (PD). However, to become a clinically practical option for PD patients, it must first overcome significant barriers, including establishment of safe and standardized surgical procedures, determination of appropriate perioperative medication regimens, demonstration of long-term graft survival and incorporation, and standardized, clinically meaningful follow-up measures. In this review, we will describe the current status of cell therapy for PD with special attention to these critical requirements, to define guideposts on the road to bring the benefit of this therapy to the Parkinson's clinic.

Selecting the Best Animal Model of Parkinson's Disease for Your Research Purpose: Insight from in vivo PET Imaging Studies

Parkinson's disease (PD) is a debilitating neurodegenerative multisystem disorder leading to motor and non-motor symptoms in millions of individuals. Despite intense research, there is still no cure, and early disease biomarkers are lacking. Animal models of PD have been inspired by basic elements of its pathogenesis, such as dopamine dysfunction, alpha-synuclein accumulation, neuroinflammation and disruption of protein degradation, and these have been crucial for a deeper understanding of the mechanisms of pathology, the identification of biomarkers, and evaluation of novel therapies. Imaging biomarkers are non-invasive tools to assess disease progression and response to therapies; their discovery and validation have been an active field of translational research. Here, we highlight different considerations of animal models of PD that can be applied to future research, in terms of their suitability to answer different research questions. We provide the reader with important considerations of the best choice of model to use based on the disease features of each model, including issues related to different species. In addition, positron emission tomography studies conducted in PD animal models in the last 5 years are presented. With a variety of different species, interventions and genetic information, the choice of the most appropriate model to answer research questions can be daunting, especially since no single model recapitulates all aspects of this complex disorder. Appropriate animal models in conjunction with in vivo molecular imaging tools, if selected properly, can be a powerful combination for the assessment of novel therapies and developing tools for early diagnosis.

Neuroimaging evaluation of deep brain stimulation in the treatment of representative neurodegenerative and neuropsychiatric disorders

Brain stimulation technology has become a viable modality of reversible interventions in the effective treatment of many neurological and psychiatric disorders. It is aimed to restore brain dysfunction by the targeted delivery of specific electronic signal within or outside the brain to modulate neural activity on local and circuit levels. Development of therapeutic approaches with brain stimulation goes in tandem with the use of neuroimaging methodology in every step of the way. Indeed, multimodality neuroimaging tools have played important roles in target identification, neurosurgical planning, placement of stimulators and post-operative confirmation. They have also been indispensable in pre-treatment screen to identify potential responders and in post-treatment to assess the modulation of brain circuitry in relation to clinical outcome measures. Studies in patients to date have elucidated novel neurobiological mechanisms underlying the neuropathogenesis, action of stimulations, brain responses and therapeutic efficacy. In this article, we review some applications of deep brain stimulation for the treatment of several diseases in the field of neurology and psychiatry. We highlight how the synergistic combination of brain stimulation and neuroimaging technology is posed to accelerate the development of symptomatic therapies and bring revolutionary advances in the domain of bioelectronic medicine.

Dynamic 18F-FPCIT PET: Quantification of Parkinson's disease metabolic networks and nigrostriatal dopaminergic dysfunction in a single imaging session

Previous multi-center imaging studies with 18F-FDG PET have established the presence of Parkinson's disease motor- and cognition-related metabolic patterns termed PDRP and PDCP in patients with this disorder. Given that in PD cerebral perfusion and glucose metabolism are typically coupled in the absence of medication, we determined whether subject expression of these disease networks can be quantified in early-phase images from dynamic 18F-FPCIT PET scans acquired to assess striatal dopamine transporter (DAT) binding. Methods: We studied a cohort of early-stage PD patients and age-matched healthy control subjects who underwent 18F-FPCIT at baseline; scans were repeated 4 years later in a smaller subset of patients. The early 18F-FPCIT frames, which reflect cerebral perfusion, were used to compute PDRP and PDCP expression (subject scores) in each subject, and compared to analogous measures computed based on 18F-FDG PET scan when additionally available. The late 18F-FPCIT frames were used to measure caudate and putamen DAT binding in the same individuals. Results: PDRP subject scores from early-phase 18F-FPCIT and 18F-FDG scans were elevated and striatal DAT binding reduced in PD versus healthy subjects. The PDRP scores from 18F-FPCIT correlated with clinical motor ratings, disease duration, and with corresponding measures from 18F-FDG PET. In addition to correlating with disease duration and analogous 18F-FDG PET values, PDCP scores correlated with DAT binding in the caudate/anterior putamen. PDRP and PDCP subject scores using either method rose over 4 years whereas striatal DAT binding declined over the same time period. Conclusion: Early-phase images obtained with 18F-FPCIT PET can provide an alternative to 18F-FDG PET for PD network quantification. This technique therefore allows PDRP/PDCP expression and caudate/putamen DAT binding to be evaluated with a single tracer in one scanning session.

Comparative test-retest variability of outcome parameters derived from brain [18F]FDG PET studies in non-human primates

INTRODUCTION

Knowledge of the repeatability of quantitative parameters derived from [18F]FDG PET images is essential to define the group size and allow correct interpretation. Here we tested repeatability and accuracy of different [18F]FDG absolute and relative quantification parameters in a standardized preclinical setup in nonhuman primates (NHP).

MATERIAL AND METHODS

Repeated brain [18F]FDG scans were performed in 6 healthy NHP under controlled experimental factors likely to account for variability. Regional cerebral metabolic rate of glucose (CMRglu) was calculated using a Patlak plot with blood input function Semi-quantitative approaches measuring standard uptake values (SUV, SUV×glycemia and SUVR (SUV Ratio) using the pons or cerebellum as a reference region) were considered. Test-retest variability of all quantification parameters were compared in different brain regions in terms of absolute variability and intra-and-inter-subject variabilities. In an independent [18F]FDG PET experiment, robustness of these parameters was evaluated in 4 naive NHP.

RESULTS

Experimental conditions (injected dose, body weight, animal temperature) were the same at both imaging sessions (p >0.4). No significant difference in the [18F]FDG quantification parameters was found between test and retest sessions. Absolute variability of CMRglu, SUV, SUV×glycemia and normalized SUV ranged from 25 to 43%, 16 to 21%, 23 to 28%, and 7 to 14%, respectively. Intra-subject variability largely explained the absolute variability of all quantitative parameters. They were all significantly correlated to each other and they were all robust. Arterial and venous glycemia were highly correlated (r = 0.9691; p<0.0001).

CONCLUSION

[18F]FDG test-retest studies in NHP protocols need to be conducted under well-standardized experimental conditions to assess and select the most reliable and reproducible quantification approach. Furthermore, the choice of the quantification parameter has to account for the transversal or follow-up study design. If pons and cerebellum regions are not affected, non-invasive SUVR is the most favorable approach for both designs.

Shared cerebral metabolic pathology in non-transgenic animal models of Alzheimer's and Parkinson's disease

Parkinson's disease (PD) and Alzheimer's disease (AD) are the most common chronic neurodegenerative disorders, characterized by motoric dysfunction or cognitive decline in the early stage, respectively, but often by both symptoms in the advanced stage. Among underlying molecular pathologies that PD and AD patients have in common, more attention is recently paid to the central metabolic dysfunction presented as insulin resistant brain state (IRBS) and altered cerebral glucose metabolism, both also explored in animal models of these diseases. This review aims to compare IRBS and alterations in cerebral glucose metabolism in representative non-transgenic animal PD and AD models. The comparison is based on the selectivity of the neurotoxins which cause experimental PD and AD, towards the cellular membrane and intracellular molecular targets as well as towards the selective neurons/non-neuronal cells, and the particular brain regions. Mitochondrial damage and co-expression of insulin receptors, glucose transporter-2 and dopamine transporter on the membrane of particular neurons as well as astrocytes seem to be the key points which are further discussed in a context of alterations in insulin signalling in the brain and its interaction with dopaminergic transmission, particularly regarding the time frame of the experimental AD/PD pathology appearance and the correlation with cognitive and motor symptoms. Such a perspective provides evidence on IRBS being a common underlying metabolic pathology and a contributor to neurodegenerative processes in representative non-transgenic animal PD and AD models, instead of being a direct cause of a particular neurodegenerative disorder.

Network Structure and Function in Parkinson's Disease

Little is known of the structural and functional properties of abnormal brain networks associated with neurological disorders. We used a social network approach to characterize the properties of the Parkinson's disease (PD) metabolic topography in 4 independent patient samples and in an experimental non-human primate model. The PD network exhibited distinct features. Dense, mutually facilitating functional connections linked the putamen, globus pallidus, and thalamus to form a metabolically active core. The periphery was formed by weaker connections linking less active cortical regions. Notably, the network contained a separate module defined by interconnected, metabolically active nodes in the cerebellum, pons, frontal cortex, and limbic regions. Exaggeration of the small-world property was a consistent feature of disease networks in parkinsonian humans and in the non-human primate model; this abnormality was only partly corrected by dopaminergic treatment. The findings point to disease-related alterations in network structure and function as the basis for faulty information processing in this disorder.

Identifying a glucose metabolic brain pattern in an adeno-associated viral vector based rat model for Parkinson's disease using 18F-FDG PET imaging

We investigated the glucose metabolism in an adeno-associated viral vector based alpha-synuclein rat model for Parkinson’s disease (PD) using longitudinal ¹⁸F-FDG PET imaging, which resulted in an improved characterization of this animal model. We generated a PD specific pattern (PDSP) based on a multivariate classification approach to differentiate between a PD and control group at a late disease stage, where the neurodegeneration is considered nearly complete. In particular, we applied a principal component analysis prior to classification by a support vector machine (SVM). Moreover, by using a SVM for regression to predict corresponding motor scores, a PD motor pattern (PDMP) was derived as well. The PDSP mainly corresponds to the PDMP and overlaps to a large extent with the human pattern. We were able to quantify disease expression at previous time points by projecting onto the PDSP and PDMP. While a univariate analysis indicated metabolic changes which did not persist through time, both PDSP and PDMP were able to differentiate significantly (p-value < 0.05) between the PD and control group at week 4, 6 and 9 post injection, while no significant differences were obtained at baseline and at week 3, which is in accordance with the animal model.

Network imaging biomarkers: insights and clinical applications in Parkinson's disease

Parkinson's disease presents several practical challenges: it can be difficult to distinguish from atypical parkinsonian syndromes, clinical ratings can be insensitive as markers of disease progression, and its non-motor manifestations are not readily assessed in animal models. These challenges, along with others, are beginning to be addressed by innovative imaging methods to characterise Parkinson's disease-specific functional networks across the whole brain and measure their expression in each patient. These signatures can help improve differential diagnosis, guide selection of patients for clinical trials, and quantify treatment responses and placebo effects in individual patients. The primary Parkinson's disease-related metabolic pattern has been replicated in multiple patient populations and used as an outcome measure in clinical trials. It can also be used as a predictor of near-term phenoconversion in prodromal syndromes, such as rapid eye movement sleep behaviour disorder. Functional network imaging holds great promise for future clinical use in the management of neurodegenerative disorders.

The effects of image reconstruction algorithms on topographic characteristics, diagnostic performance and clinical correlation of metabolic brain networks in Parkinson's disease

PURPOSE

The purpose of this study was to evaluate the effects of different image reconstruction algorithms on topographic characteristics and diagnostic performance of the Parkinson's disease related pattern (PDRP).

METHODS

FDG-PET brain scans of 20 Parkinson's disease (PD) patients and 20 normal controls (NC) were reconstructed with six different algorithms in order to derive six versions of PDRP. Additional scans of 20 PD, 25 atypical parkinsonism (AP) patients and 20 NC subjects were used for validation. PDRP versions were compared by assessing differences in topographies, individual subject scores and correlations with patient's clinical ratings. Discrimination of PD from NC and AP subjects was evaluated across cohorts.

RESULTS

The region weights of the six PDRPs highly correlated (R ≥ 0.991; p < 0.0001). All PDRPs' expressions were significantly elevated in PD relative to NC and AP subjects (p < 0.0001) and correlated with clinical ratings (R ≥ 0.47; p < 0.05). Subject scores of the six PDRPs highly correlated within each of individual healthy and parkinsonian groups (R ≥ 0.972, p < 0.0001) and were consistent across the algorithms when using the same reconstruction methods in PDRP derivation and validation. However, when derivation and validation reconstruction algorithms differed, subject scores were notably lower compared to the reference PDRP, in all subject groups.

CONCLUSION

PDRP proves to be highly reproducible across FDG-PET image reconstruction algorithms in topography, ability to differentiate PD from NC and AP subjects and clinical correlation. When calculating PDRP scores in scans that have different reconstruction algorithms and imaging systems from those used for PDRP derivation, a calibration with NC subjects is advisable.

Levodopa-induced abnormal involuntary movements correlate with altered permeability of the blood-brain-barrier in the basal ganglia

Chronic levodopa treatment leads to the appearance of dyskinesia in the majority of Parkinson’s disease patients. Neurovascular dysregulation in putaminal and pallidal regions is thought to be an underlying feature of this complication of treatment. We used microPET to study unilaterally lesioned 6-hydroxydopamine rats that developed levodopa-induced abnormal involuntary movements (AIMs) after three weeks of drug treatment. Animals were scanned with [¹⁵O]-labeled water and [¹⁸F]-fluorodeoxyglucose, to map regional cerebral blood flow and glucose metabolism, and with [¹¹C]-isoaminobutyric acid (AIB), to assess blood-brain-barrier (BBB) permeability, following separate injections of levodopa or saline. Multitracer scan data were acquired in each animal before initiating levodopa treatment, and again following the period of daily drug administration. Significant dissociation of vasomotor and metabolic levodopa responses was seen in the striatum/globus pallidus (GP) of the lesioned hemisphere. These changes were accompanied by nearby increases in [¹¹C]-AIB uptake in the ipsilateral GP, which correlated with AIMs scores. Histopathological analysis revealed high levels of microvascular nestin immunoreactivity in the same region. The findings demonstrate that regional flow-metabolism dissociation and increased BBB permeability are simultaneously induced by levodopa within areas of active microvascular remodeling, and that such changes correlate with the severity of dyskinesia.

Transplantation in the nonhuman primate MPTP model of Parkinson's disease: update and perspectives

In order to calibrate stem cell exploitation for cellular therapy in neurodegenerative diseases, fundamental and preclinical research in NHP (nonhuman primate) models is crucial. Indeed, it is consensually recognized that it is not possible to directly extrapolate results obtained in rodent models to human patients. A large diversity of neurological pathologies should benefit from cellular therapy based on neural differentiation of stem cells. In the context of this special issue of Primate Biology on NHP stem cells, we describe past and recent advances on cell replacement in the NHP model of Parkinson's disease (PD). From the different grafting procedures to the various cell types transplanted, we review here diverse approaches for cell-replacement therapy and their related therapeutic potential on behavior and function in the NHP model of PD.