A Network Imaging Biomarker of X-Linked Dystonia-Parkinsonism.

OBJECTIVE: The purpose of this study was to characterize a metabolic brain network associated with X-linked dystonia-parkinsonism (XDP). METHODS: Thirty right-handed Filipino men with XDP (age = 44.4 ± 8.5 years) and 30 XDP-causing mutation negative healthy men from the same population (age = 37.4 ± 10.5 years) underwent [18 F]-fluorodeoxyglucose positron emission tomography. Scans were analyzed using spatial covariance mapping to identify a significant XDP-related metabolic pattern (XDPRP). Patients were rated clinically at the time of imaging according to the XDP-Movement Disorder Society of the Philippines (MDSP) scale. RESULTS: We identified a significant XDPRP topography from 15 randomly selected subjects with XDP and 15 control subjects. This pattern was characterized by bilateral metabolic reductions in caudate/putamen, frontal operculum, and cingulate cortex, with relative increases in the bilateral somatosensory cortex and cerebellar vermis. Age-corrected expression of XDPRP was significantly elevated (p < 0.0001) in XDP compared to controls in the derivation set and in the remaining 15 patients (testing set). We validated the XDPRP topography by identifying a similar pattern in the original testing set (r = 0.90, p < 0.0001; voxel-wise correlation between both patterns). Significant correlations between XDPRP expression and clinical ratings for parkinsonism-but not dystonia-were observed in both XDP groups. Further network analysis revealed abnormalities of information transfer through the XDPRP space, with loss of normal connectivity and gain of abnormal functional connections linking network nodes with outside brain regions. INTERPRETATION: XDP is associated with a characteristic metabolic network associated with abnormal functional connectivity among the basal ganglia, thalamus, motor regions, and cerebellum. Clinical signs may relate to faulty information transfer through the network to outside brain regions. ANN NEUROL 2023;94:684-695.

Disordered network structure and function in dystonia: pathological connectivity vs. adaptive responses.

Primary dystonia is thought to emerge through abnormal functional relationships between basal ganglia and cerebellar motor circuits. These interactions may differ across disease subtypes and provide a novel biomarker for diagnosis and treatment. Using a network mapping algorithm based on resting-state functional MRI (rs-fMRI), a method that is readily implemented on conventional MRI scanners, we identified similar disease topographies in hereditary dystonia associated with the DYT1 or DYT6 mutations and in sporadic patients lacking these mutations. Both networks were characterized by contributions from the basal ganglia, cerebellum, thalamus, sensorimotor areas, as well as cortical association regions. Expression levels for the two networks were elevated in hereditary and sporadic dystonia, and in non-manifesting carriers of dystonia mutations. Nonetheless, the distribution of abnormal functional connections differed across groups, as did metrics of network organization and efficiency in key modules. Despite these differences, network expression correlated with dystonia motor ratings, significantly improving the accuracy of predictions based on thalamocortical tract integrity obtained with diffusion tensor MRI (DTI). Thus, in addition to providing unique information regarding the anatomy of abnormal brain circuits, rs-fMRI functional networks may provide a widely accessible method to help in the objective evaluation of new treatments for this disorder.

Adaptive and pathological connectivity responses in Parkinson's disease brain networks.

Functional imaging has been used extensively to identify and validate disease-specific networks as biomarkers in neurodegenerative disorders. It is not known, however, whether the connectivity patterns in these networks differ with disease progression compared to the beneficial adaptations that may also occur over time. To distinguish the 2 responses, we focused on assortativity, the tendency for network connections to link nodes with similar properties. High assortativity is associated with unstable, inefficient flow through the network. Low assortativity, by contrast, involves more diverse connections that are also more robust and efficient. We found that in Parkinson's disease (PD), network assortativity increased over time. Assoratitivty was high in clinically aggressive genetic variants but was low for genes associated with slow progression. Dopaminergic treatment increased assortativity despite improving motor symptoms, but subthalamic gene therapy, which remodels PD networks, reduced this measure compared to sham surgery. Stereotyped changes in connectivity patterns underlie disease progression and treatment responses in PD networks.

LRRK2 and GBA Variants Exert Distinct Influences on Parkinson's Disease-Specific Metabolic Networks.

The natural history of idiopathic Parkinson's disease (PD) varies considerably across patients. While PD is generally sporadic, there are known genetic influences: the two most common, mutations in the LRRK2 or GBA1 gene, are associated with slower and more aggressive progression, respectively. Here, we applied graph theory to metabolic brain imaging to understand the effects of genotype on the organization of previously established PD-specific networks. We found that closely matched PD patient groups with the LRRK2-G2019S mutation (PD-LRRK2) or GBA1 variants (PD-GBA) expressed the same disease networks as sporadic disease (sPD), but PD-LRRK2 and PD-GBA patients exhibited abnormal increases in network connectivity that were not present in sPD. Using a community detection strategy, we found that the location and modular distribution of these connections differed strikingly across genotypes. In PD-LRRK2, connections were gained within the network core, with the formation of distinct functional pathways linking the cerebellum and putamen. In PD-GBA, by contrast, the majority of functional connections were formed outside the core, involving corticocortical pathways at the network periphery. Strategically localized connections within the core in PD-LRRK2 may maintain PD network activity at lower levels than in PD-GBA, resulting in a less aggressive clinical course.

Molecular imaging to track Parkinson's disease and atypical parkinsonisms: New imaging frontiers.

Molecular imaging has proven to be a powerful tool for investigation of parkinsonian disorders. One current challenge is to identify biomarkers of early changes that may predict the clinical trajectory of parkinsonian disorders. Exciting new tracer developments hold the potential for in vivo markers of underlying pathology. Herein, we provide an overview of molecular imaging advances and how these approaches help us to understand PD and atypical parkinsonisms. © 2016 International Parkinson and Movement Disorder Society.

Current Opinions and Areas of Consensus on the Role of the Cerebellum in Dystonia.

A role for the cerebellum in causing ataxia, a disorder characterized by uncoordinated movement, is widely accepted. Recent work has suggested that alterations in activity, connectivity, and structure of the cerebellum are also associated with dystonia, a neurological disorder characterized by abnormal and sustained muscle contractions often leading to abnormal maintained postures. In this manuscript, the authors discuss their views on how the cerebellum may play a role in dystonia. The following topics are discussed: The relationships between neuronal/network dysfunctions and motor abnormalities in rodent models of dystonia. Data about brain structure, cerebellar metabolism, cerebellar connections, and noninvasive cerebellar stimulation that support (or not) a role for the cerebellum in human dystonia. Connections between the cerebellum and motor cortical and sub-cortical structures that could support a role for the cerebellum in dystonia. Overall points of consensus include: Neuronal dysfunction originating in the cerebellum can drive dystonic movements in rodent model systems. Imaging and neurophysiological studies in humans suggest that the cerebellum plays a role in the pathophysiology of dystonia, but do not provide conclusive evidence that the cerebellum is the primary or sole neuroanatomical site of origin.

The visual perception of natural motion: abnormal task-related neural activity in DYT1 dystonia.

Although primary dystonia is defined by its characteristic motor manifestations, non-motor signs and symptoms have increasingly been recognized in this disorder. Recent neuroimaging studies have related the motor features of primary dystonia to connectivity changes in cerebello-thalamo-cortical pathways. It is not known, however, whether the non-motor manifestations of the disorder are associated with similar circuit abnormalities. To explore this possibility, we used functional magnetic resonance imaging to study primary dystonia and healthy volunteer subjects while they performed a motion perception task in which elliptical target trajectories were visually tracked on a computer screen. Prior functional magnetic resonance imaging studies of healthy subjects performing this task have revealed selective activation of motor regions during the perception of 'natural' versus 'unnatural' motion (defined respectively as trajectories with kinematic properties that either comply with or violate the two-thirds power law of motion). Several regions with significant connectivity changes in primary dystonia were situated in proximity to normal motion perception pathways, suggesting that abnormalities of these circuits may also be present in this disorder. To determine whether activation responses to natural versus unnatural motion in primary dystonia differ from normal, we used functional magnetic resonance imaging to study 10 DYT1 dystonia and 10 healthy control subjects at rest and during the perception of 'natural' and 'unnatural' motion. Both groups exhibited significant activation changes across perceptual conditions in the cerebellum, pons, and subthalamic nucleus. The two groups differed, however, in their responses to 'natural' versus 'unnatural' motion in these regions. In healthy subjects, regional activation was greater during the perception of natural (versus unnatural) motion (P < 0.05). By contrast, in DYT1 dystonia subjects, activation was relatively greater during the perception of unnatural (versus natural) motion (P < 0.01). To explore the microstructural basis for these functional changes, the regions with significant interaction effects (i.e. those with group differences in activation across perceptual conditions) were used as seeds for tractographic analysis of diffusion tensor imaging scans acquired in the same subjects. Fibre pathways specifically connecting each of the significant functional magnetic resonance imaging clusters to the cerebellum were reconstructed. Of the various reconstructed pathways that were analysed, the ponto-cerebellar projection alone differed between groups, with reduced fibre integrity in dystonia (P < 0.001). In aggregate, the findings suggest that the normal pattern of brain activation in response to motion perception is disrupted in DYT1 dystonia. Thus, it is unlikely that the circuit changes that underlie this disorder are limited to primary sensorimotor pathways.

Thalamocortical Connectivity Correlates with Phenotypic Variability in Dystonia.

Dystonia is a brain disorder characterized by abnormal involuntary movements without defining neuropathological changes. The disease is often inherited as an autosomal-dominant trait with incomplete penetrance. Individuals with dystonia, whether inherited or sporadic, exhibit striking phenotypic variability, with marked differences in the somatic distribution and severity of clinical manifestations. In the current study, we used magnetic resonance diffusion tensor imaging to identify microstructural changes associated with specific limb manifestations. Functional MRI was used to localize specific limb regions within the somatosensory cortex. Microstructural integrity was preserved when assessed in subrolandic white matter regions somatotopically related to the clinically involved limbs, but was reduced in regions linked to clinically uninvolved (asymptomatic) body areas. Clinical manifestations were greatest in subjects with relatively intact microstructure in somatotopically relevant white matter regions. Tractography revealed significant phenotype-related differences in the visualized thalamocortical tracts while corticostriatal and corticospinal pathways did not differ between groups. Cerebellothalamic microstructural abnormalities were also seen in the dystonia subjects, but these changes were associated with genotype, rather than with phenotypic variation. The findings suggest that the thalamocortical motor system is a major determinant of dystonia phenotype. This pathway may represent a novel therapeutic target for individuals with refractory limb dystonia.

A disease-specific metabolic brain network associated with corticobasal degeneration.

Corticobasal degeneration is an uncommon parkinsonian variant condition that is diagnosed mainly on clinical examination. To facilitate the differential diagnosis of this disorder, we used metabolic brain imaging to characterize a specific network that can be used to discriminate corticobasal degeneration from other atypical parkinsonian syndromes. Ten non-demented patients (eight females/two males; age 73.9 ± 5.7 years) underwent metabolic brain imaging with (18)F-fluorodeoxyglucose positron emission tomography for atypical parkinsonism. These individuals were diagnosed clinically with probable corticobasal degeneration. This diagnosis was confirmed in the three subjects who additionally underwent post-mortem examination. Ten age-matched healthy subjects (five females/five males; age 71.7 ± 6.7 years) served as controls for the imaging studies. Spatial covariance analysis was applied to scan data from the combined group to identify a significant corticobasal degeneration-related metabolic pattern that discriminated (P < 0.001) the patients from the healthy control group. This pattern was characterized by bilateral, asymmetric metabolic reductions involving frontal and parietal cortex, thalamus, and caudate nucleus. These pattern-related changes were greater in magnitude in the cerebral hemisphere opposite the more clinically affected body side. The presence of this corticobasal degeneration-related metabolic topography was confirmed in two independent testing sets of patient and control scans, with elevated pattern expression (P < 0.001) in both disease groups relative to corresponding normal values. We next determined whether prospectively computed expression values for this pattern accurately discriminated corticobasal degeneration from multiple system atrophy and progressive supranuclear palsy (the two most common atypical parkinsonian syndromes) on a single case basis. Based upon this measure, corticobasal degeneration was successfully distinguished from multiple system atrophy (P < 0.001) but not progressive supranuclear palsy, presumably because of the overlap (∼ 24%) that existed between the corticobasal degeneration- and the progressive supranuclear palsy-related metabolic topographies. Nonetheless, excellent discrimination between these disease entities was achieved by computing hemispheric asymmetry scores for the corticobasal degeneration-related pattern on a prospective single scan basis. Indeed, a logistic algorithm based on the asymmetry scores combined with separately computed expression values for a previously validated progressive supranuclear palsy-related pattern provided excellent specificity (corticobasal degeneration: 92.7%; progressive supranuclear palsy: 94.1%) in classifying 58 testing subjects. In conclusion, corticobasal degeneration is associated with a reproducible disease-related metabolic covariance pattern that may help to distinguish this disorder from other atypical parkinsonian syndromes.

Longitudinal Network Changes and Phenoconversion Risk in Isolated REM Sleep Behavior Disorder.

Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal syndrome for Parkinson's disease (PD) and related α-synucleinopathies. We conducted a longitudinal imaging study of network changes in iRBD and their relationship to phenoconversion. Expression levels for the PD-related motor and cognitive networks (PDRP and PDCP) were measured at baseline, 2 and 4 years, along with dopamine transporter (DAT) binding. PDRP and PDCP expression increased over time, with higher values in the former network. While abnormal functional connections were identified initially within the PDRP, others bridging the two networks appeared later. A model based on the rates of PDRP progression and putamen dopamine loss predicted phenoconversion within 1.2 years in individuals with iRBD. In aggregate, the data suggest that maladaptive reorganization of brain networks takes place in iRBD years before phenoconversion. Network expression and DAT binding measures can be used together to assess phenoconversion risk in these individuals.

Deep brain stimulation of the subthalamic nucleus for Parkinson's disease: A network imaging marker of the treatment response.

Subthalamic nucleus deep brain stimulation (STN-DBS) alleviates motor symptoms of Parkinson's disease (PD), thereby improving quality of life. However, quantitative brain markers to evaluate DBS responses and select suitable patients for surgery are lacking. Here, we used metabolic brain imaging to identify a reproducible STN-DBS network for which individual expression levels increased with stimulation in proportion to motor benefit. Of note, measurements of network expression from metabolic and BOLD imaging obtained preoperatively predicted motor outcomes determined after DBS surgery. Based on these findings, we computed network expression in 175 PD patients, with time from diagnosis ranging from 0 to 21 years, and used the resulting data to predict the outcome of a potential STN-DBS procedure. While minimal benefit was predicted for patients with early disease, the proportion of potential responders increased after 4 years. Clinically meaningful improvement with stimulation was predicted in 18.9 - 27.3% of patients depending on disease duration.

Parkinson's disease cognitive network correlates with caudate dopamine.

Prior evidence has suggested a link between caudate dopaminergic functioning and cognition in Parkinson's disease (PD). In this dual tracer study we analyzed the relationship between nigrostriatal dopaminergic dysfunction and the expression of the previously validated PD cognition-related metabolic pattern (PDCP). In this study, 17 non-demented PD patients underwent positron emission tomography (PET) imaging with [(18)F]-fluorodeoxyglucose to measure PDCP expression, and [(18)F]-fluoropropyl-ß-CIT (FPCIT) to measure dopamine transporter (DAT) binding. Automated voxel-by-voxel searches of the FPCIT PET volumes were performed to identify regions in which DAT binding significantly correlated with PDCP expression values. The findings were validated using prespecified anatomical regions-of-interest (ROIs). Voxel-wise interrogation of the FPCIT PET scans revealed a single significant cluster in which DAT binding correlated with PDCP expression (p<0.05, corrected). This cluster was localized to the left caudate nucleus; an analogous correlation (r=-0.63, p<0.01) was also present in the "mirror" region of the right hemisphere. These findings were confirmed by the presence of a significant correlation (r=-0.67, p<0.005) between PDCP expression and DAT binding in caudate ROIs, which survived adjustment for age, disease duration, and clinical severity ratings. Correlation between caudate DAT binding and subject expression of the PD motor-related metabolic pattern was not significant (p>0.21). In summary, this study demonstrates a significant relationship between loss of dopaminergic input to the caudate nucleus and the expression of a cognition-related disease network in unmedicated PD patients. These baseline measures likely function in concert to determine the cognitive effects of dopaminergic therapy in PD.

Metabolic brain networks in translational neurology: concepts and applications.

Over the past 2 decades, functional imaging techniques have become commonplace in the study of brain disease. Nevertheless, very few validated analytical methods have been developed specifically to identify and measure systems-level abnormalities in living patients. Network approaches are particularly relevant for translational research in the neurodegenerative disorders, which often involve stereotyped abnormalities in brain organization. In recent years, spatial covariance mapping, a multivariate analytical tool applied mainly to metabolic images acquired in the resting state, has provided a useful means of objectively assessing brain disorders at the network level. By quantifying network activity in individual subjects on a scan-by-scan basis, this technique makes it possible to objectively assess disease progression and the response to treatment on a system-wide basis. To illustrate the utility of network imaging in neurological research, we review recent applications of this approach in the study of Parkinson disease and related movement disorders. Novel uses of the technique are discussed, including the prediction of cognitive responses to dopaminergic therapy, evaluation of the effects of placebo treatment on network activity, assessment of preclinical disease progression, and the use of automated pattern-based algorithms to enhance diagnostic accuracy.

Understanding the anatomy of dystonia: determinants of penetrance and phenotype.

The dystonias comprise a group of syndromes characterized by prolonged involuntary muscle contractions resulting in repetitive movements and abnormal postures. Primary dystonia has been associated with over 14 different genotypes, most of which follow an autosomal dominant inheritance pattern with reduced penetrance. Independent of etiology, the disease is characterized by extensive variability in disease phenotype and clinical severity. Recent neuroimaging studies investigating this phenomenon in manifesting and non-manifesting genetic carriers of dystonia have discovered microstructural integrity differences in the cerebello-thalamo-cortical tract in both groups related to disease penetrance. Further study suggests these differences to be specific to subrolandic white matter regions somatotopically related to clinical phenotype. Clinical severity was correlated to the degree of microstructural change. These findings suggest a mechanism for the penetrance and clinical variability observed in dystonia and may represent a novel therapeutic target for patients with refractory limb symptoms.

Differential spatiotemporal gait effects with frequency and dopaminergic modulation in STN-DBS.

Objective: The spatiotemporal gait changes in advanced Parkinson's disease (PD) remain a treatment challenge and have variable responses to L-dopa and subthalamic deep brain stimulation (STN-DBS). The purpose of this study was to determine whether low-frequency STN-DBS (LFS; 60 Hz) elicits a differential response to high-frequency STN-DBS (HFS; 180 Hz) in spatiotemporal gait kinematics. Methods: Advanced PD subjects with chronic STN-DBS were evaluated in both the OFF and ON medication states with LFS and HFS stimulation. Randomization of electrode contact pairs and frequency conditions was conducted. Instrumented Stand and Walk assessments were carried out for every stimulation/medication condition. LM-ANOVA was employed for analysis. Results: Twenty-two PD subjects participated in the study, with a mean age (SD) of 63.9 years. Significant interactions between frequency (both LFS and HFS) and electrode contact pairs (particularly ventrally located contacts) were observed for both spatial (foot elevation, toe-off angle, stride length) and temporal (foot speed, stance, single limb support (SLS) and foot swing) gait parameters. A synergistic effect was also demonstrated with L-dopa and both HFS and LFS for right SLS, left stance, left foot swing, right toe-off angle, and left arm range of motion. HFS produced significant improvement in trunk and lumbar range of motion compared to LFS. Conclusion: The study provides evidence of synergism of L-dopa and STN-DBS on lower limb spatial and temporal measures in advanced PD. HFS and LFS STN-DBS produced equivalent effects among all other tested lower limb gait features. HFS produced significant trunk and lumbar kinematic improvements.

Prospective F-18 FDOPA PET Imaging Study in Human PD.

Purpose: We present the findings of our final prospective study submitted to the U.S. Food and Drug Administration (FDA) for New Drug Application (NDA) approval for the use of 3,4-dihydroxy-6-[18F]fluoro-l-phenylalanine (F-18 FDOPA) positron emission tomography (PET) imaging for Parkinson's disease (PD). The primary aim was to determine the sensitivity, specificity, and predictive values of F-18 FDOPA PET in parkinsonian patients with respect to clinical standard-of-truth (SOT). Secondary outcomes included the inter-rater reliability, and correlation of quantitative measures for PET with dopaminergic status. Methods: In 68 parkinsonian subjects, F-18 FDOPA PET scan from 80 to 100 min was acquired following a CT scan. Scan images were presented to one expert in F-18 FDOPA image interpretation and two physicians with prior experience in I-123 FPCIT single-photon emission computed tomography image interpretation. Fifty-six subjects completed the study with a follow-up for SOT determination. Image readers were blind to the clinical/quantitative data; SOT clinician was blind to the image data. Results: For 47 of the 56 patients, SOT was in agreement with the PET scan results. For nine patients, SOT suggested dopaminergic deficit, whereas the imaging showed normal uptake. The specificity and positive predictive values are 91% and 92%, respectively, suggesting high probability that those who test positive by the PET scan truly have dopaminergic degeneration. The sensitivity was 73%. Inter-rater agreement was 0.6-0.8 between the different readers. Conclusion: Our prospective study demonstrates high specificity and moderate sensitivity of F-18 FDOPA PET for PD. We received NDA approval in October 2019. Supplementary Information: The online version contains supplementary material available at 10.1007/s13139-022-00748-4.

Hereditary dystonia as a neurodevelopmental circuit disorder: Evidence from neuroimaging.

Primary dystonia has traditionally been viewed as a basal ganglia disorder, but recent studies suggest that the cerebellum plays a crucial role in the disease. Primary dystonia is associated with several genotypes. Among those, DYT1 and DYT6 are inherited in autosomal dominant fashion with reduced penetrance. Extensive structural and functional imaging studies have been performed on manifesting and non-manifesting carriers of these mutations. The results suggest that primary dystonia can be viewed as a neurodevelopmental circuit disorder, involving the cortico-striato-pallido-thalamo-cortical and cerebello-thalamo-cortical pathways. Anatomical disruption of the cerebellar outflow is found in non-manifesting and manifesting mutation carriers, and a second downstream disruption in thalamo-cortical projections appears clinically protective in non-manifesting carriers. The microstructural deficits in cerebellar outflow are linked to an abnormally elevated sensorimotor network (NMRP) in dystonia patients. Abnormal expression of this network is reduced by successful treatment with deep brain stimulation. This article is part of a Special Issue entitled "Advances in dystonia".

Cerebellothalamocortical connectivity regulates penetrance in dystonia.

Dystonia is a brain disorder characterized by sustained involuntary muscle contractions. It is typically inherited as an autosomal dominant trait with incomplete penetrance. While lacking clear degenerative neuropathology, primary dystonia is thought to involve microstructural and functional changes in neuronal circuitry. In the current study, we used magnetic resonance diffusion tensor imaging and probabilistic tractography to identify the specific circuit abnormalities that underlie clinical penetrance in carriers of genetic mutations for this disorder. This approach revealed reduced integrity of cerebellothalamocortical fiber tracts, likely developmental in origin, in both manifesting and clinically nonmanifesting dystonia mutation carriers. In these subjects, reductions in cerebellothalamic connectivity correlated with increased motor activation responses, consistent with loss of inhibition at the cortical level. Nonmanifesting mutation carriers were distinguished by an additional area of fiber tract disruption situated distally along the thalamocortical segment of the pathway, in tandem with the proximal cerebellar outflow abnormality. In individual gene carriers, clinical penetrance was determined by the difference in connectivity measured at these two sites. Overall, these findings point to a novel mechanism to explain differences in clinical expression in carriers of genes for brain disease.

Network Imaging in Parkinsonian and Other Movement Disorders: Network Dysfunction and Clinical Correlates.

Parkinson's disease (PD) is classically defined as a disease of progressive dopaminergic dysfunction, thus explaining many of the levodopa-responsive motor features. However, even early in the disease, non-motor symptoms can appear, affecting sleep, cognition, and behavior. This implies the involvement of more widespread circuitry beyond the basal ganglia. In addition, the varied clinical presentation and the clinical overlap between PD and other diseases of dopamine degeneration (referred to as atypical parkinsonian syndromes), particularly early in the disease, have complicated diagnosis, treatment, and clinical trials. The increased use of functional imaging techniques, which can identify and quantify widespread functional networks, has provided insights into understanding these disorders beyond dopaminergic degeneration. In this chapter, we summarize such work as it relates to pathophysiology, diagnosis, progression, and treatment of parkinsonian disorders. We also briefly highlight findings in another neurodegenerative disorder, Huntington's disease.

Gene therapy reduces Parkinson's disease symptoms by reorganizing functional brain connectivity.

Gene therapy is emerging as a promising approach for treating neurological disorders, including Parkinson's disease (PD). A phase 2 clinical trial showed that delivering glutamic acid decarboxylase (GAD) into the subthalamic nucleus (STN) of patients with PD had therapeutic effects. To determine the mechanism underlying this response, we analyzed metabolic imaging data from patients who received gene therapy and those randomized to sham surgery, all of whom had been scanned preoperatively and at 6 and 12 months after surgery. Those who received GAD gene therapy developed a unique treatment-dependent polysynaptic brain circuit that we termed as the GAD-related pattern (GADRP), which reflected the formation of new polysynaptic functional pathways linking the STN to motor cortical regions. Patients in both the treatment group and the sham group expressed the previously reported placebo network (the sham surgery-related pattern or SSRP) when blinded to the treatment received. However, only the appearance of the GADRP correlated with clinical improvement in the gene therapy-treated subjects. Treatment-induced brain circuits can thus be useful in clinical trials for isolating true treatment responses and providing insight into their underlying biological mechanisms.