Symptom-severity-related brain connectivity alterations in functional movement disorders

Background Functional movement disorders, a common cause of neurological disabilities, can occur with heterogeneous motor manifestations including functional weakness. However, the underlying mechanisms related to brain function and connectivity are unknown. Objective To identify brain connectivity alterations related to functional weakness we assessed network centrality changes in a group of patients with heterogeneous motor manifestations using task-free functional MRI in combination with different network centrality approaches. Methods Task-free functional MRI was performed in 48 patients with heterogeneous motor manifestations including 28 patients showing functional weakness and 65 age- and sex-matched healthy controls. Functional connectivity differences were assessed using different network centrality approaches, i.e. global correlation, eigenvector centrality, and intrinsic connectivity. Motor symptom severity was assessed using The Simplified Functional Movement Disorders Rating Scale and correlated with network centrality. Results Comparing patients with and without functional weakness showed significant network centrality differences in the left temporoparietal junction and precuneus. Patients with functional weakness showed increased centrality in the same anatomical regions when comparing functional weakness with healthy controls. Moreover, in the same regions, patients with functional weakness showed a positive correlation between motor symptom severity and network centrality. This correlation was shown to be specific to functional weakness with an interaction analysis, confirming a significant difference between patients with and without functional weakness. Conclusions We identified the temporoparietal junction and precuneus as key regions involved in brain connectivity alterations related to functional weakness. We propose that both regions may be promising targets for phenotype-specific non-invasive brain stimulation

Multi-centre classification of functional neurological disorders based on resting-state functional connectivity.

Patients suffering from functional neurological disorder (FND) experience disabling neurological symptoms not caused by an underlying classical neurological disease (such as stroke or multiple sclerosis). The diagnosis is made based on reliable positive clinical signs, but clinicians often require additional time- and cost consuming medical tests and examinations. Resting-state functional connectivity (RS FC) showed its potential as an imaging-based adjunctive biomarker to help distinguish patients from healthy controls and could represent a "rule-in" procedure to assist in the diagnostic process. However, the use of RS FC depends on its applicability in a multi-centre setting, which is particularly susceptible to inter-scanner variability. The aim of this study was to test the robustness of a classification approach based on RS FC in a multi-centre setting. This study aimed to distinguish 86 FND patients from 86 healthy controls acquired in four different centres using a multivariate machine learning approach based on whole-brain resting-state functional connectivity. First, previously published results were replicated in each centre individually (intra-centre cross-validation) and its robustness across inter-scanner variability was assessed by pooling all the data (pooled cross-validation). Second, we evaluated the generalizability of the method by using data from each centre once as a test set, and the data from the remaining centres as a training set (inter-centre cross-validation). FND patients were successfully distinguished from healthy controls in the replication step (accuracy of 74%) as well as in each individual additional centre (accuracies of 73%, 71% and 70%). The pooled cross validation confirmed that the classifier was robust with an accuracy of 72%. The results survived post-hoc adjustment for anxiety, depression, psychotropic medication intake, and symptom severity. The most discriminant features involved the angular- and supramarginal gyri, sensorimotor cortex, cingular- and insular cortex, and hippocampal regions. The inter-centre validation step did not exceed chance level (accuracy below 50%). The results demonstrate the applicability of RS FC to correctly distinguish FND patients from healthy controls in different centres and its robustness against inter-scanner variability. In order to generalize its use across different centres and aim for clinical application, future studies should work towards optimization of acquisition parameters and include neurological and psychiatric control groups presenting with similar symptoms

Weight Gain Is Associated with Medial Contact Site of Subthalamic Stimulation in Parkinson's Disease

The aim of our study was to assess changes in body-weight in relation to active electrode contact position in the subthalamic nucleus. Regular body weight measurements were done in 20 patients with advanced Parkinson's disease within a period of 18 months after implantation. T1-weighted (1.5T) magnetic resonance images were used to determine electrode position in the subthalamic nucleus and the Unified Parkinson's disease rating scale (UPDRS-III) was used for motor assessment. The distance of the contacts from the wall of the third ventricle in the mediolateral direction inversely correlated with weight gain (r = −0.55, p<0.01) and with neurostimulation-related motor condition expressed as the contralateral hemi-body UPDRS-III (r = −0.42, p<0.01). Patients with at least one contact within 9.3 mm of the wall experienced significantly greater weight gain (9.4±(SD)4.4 kg, N = 11) than those with both contacts located laterally (3.9±2.7 kg, N = 9) (p<0.001). The position of the active contact is critical not only for motor outcome but is also associated with weight gain, suggesting a regional effect of subthalamic stimulation on adjacent structures involved in the central regulation of energy balance, food intake or reward

Correction to: Myoclonic dystonia phenotype related to a novel calmodulin-binding transcription activator 1 sequence variant.

The affiliation of author Robert Jech was incorrectly indicated in the originally published version of this paper

Disconnected SMA and midcingulate in Functional movement disorders: a resting state fMRI study

Introduction: Patients with functional (psychogenic) movement disorders (FMD) can have various motor and non-motor symptoms including anxiety and depression. An aberrant integration of the sensorimotor and affective processing, and a dysfunctional sense of agency have been proposed as the key mechanisms involved in FMD development suggesting that FMD have features of a multiple network disorder. Therefore, exploration of brain connectivity mapping could provide important insights in the pathophysiology of FMD. The aim of this study was to analyze resting state fMRI to avoid variability related to aberrant movements or somatosensory misperception while taking into account anxiety and depression as confounding factors. To avoid selection bias, we used the eigen-vector centrality (EC) mapping to allow data-driven detection of connectivity hubs with rich connections to other regions of the brain that are highly connected. Methods: Forty-four patients with FMD (34F, age 45±(SD)9 years, disease duration 8.4±5,6 years) with heterogeneous motor phenotypes were compared to 44 matched control subjects (33F, 44±10y). The anxiety state (STAIX-1) and trait (STAIX-2) and Beck depression inventory (BDI-II) were recorded. All subjects were instructed to watch a cross for 10 minutes during rs-fMRI acquisition (3T, Siemens, Skyra: T2*-weighted gradient echo echo-planar imaging, TR=2s, TE=30ms, FA=90, 300 scans). The preprocessing and statistics were performed with the SPM12 software (London, UK). General connectivity was derived from EC mapping (Lohmann et al., 2010) with a new correlation metric called ReLU correlation (Lohmann et al., 2018). For comparison, we also computed the EC with three other correlation metrics. Group analysis was based on a GLM implementing the contrast between both groups of subjects including 'STAIX-2', 'age', 'gender', and 'antidepressant drugs' as additional covariates. For selective connectivity, voxel-wise correlations using seeds derived from the results of the group EC analysis were computed in each subject. Group results were obtained with non-parametric statistics based on threshold-free cluster enhancement (TFCE toolbox, Jena, Germany) using the family-wise error correction at p<0.05. Results: FMD patients in comparison with controls showed decreased general connectivity in the SMA and midcingulate bilaterally and in the right superior frontal gyrus and right insula. This result became significant if the STAIX-2 was used as the nuisance covariate in the model (Figure 1). Selective connectivity from the seeds in the SMA and midcingulate showed disconnections in FMD patients in comparison with controls in multiple regions involving Rolandic areas, superior temporal gyri, posterior cingulate, insula, inferolateral prefrontal cortex, visual cortex and cerebellum (Figure 2). We obtained similar results with all correlation metrics, however, the RLC approach appeared to be most sensitive for the detection of EC differences between both groups. Conclusions: Despites motor symptoms variability, the brain of FMD patients exhibited a uniform connectivity pattern involving the SMA and midcingulate, which were generally less connected with all other cortical and subcortical regions than in controls. The results are in line with previous reports (Roelofs et al., 2019) using different approaches to rs-fMRI or brain morphometry analyses and fit well to our knowledge of the functional role of these regions and their possible malfunctions. Disconnected SMA is potentially associated with dysfunctional planning of voluntary movements or with insufficient suppression of unwanted actions (Nachev et al., 2008; Ruan et al., 2018). Disconnection of the midcingulate may affect multisensory orientation, nociceptive processing or nocifensive behavior (Vogt, 2016; Ospina et al., 2019). Our findings thus support FMD as a network disorder affecting hubs connecting motor and non-motor networks. Supported by the grant AZV 16-29651A

Myoclonic dystonia phenotype related to a novel calmodulin-binding transcription activator 1 sequence variant.

Intragenic rearrangements and sequence variants in the calmodulin-binding transcription activator 1 gene (CAMTA1) can result in a spectrum of clinical presentations, most notably congenital ataxia with or without intellectual disability. We describe for the first time a myoclonic dystonia-predominant phenotype associated with a novel CAMTA1 sequence variant. Furthermore, by identifying an additional, recurrent CAMTA1 sequence variant in an individual with a more typical neurodevelopmental disease manifestation, we contribute to the elucidation of phenotypic variability associated with CAMTA1 gene mutations

Centrality and seed-based correlation maps obtained with functional MRI

The data set offers individual brain connectivity maps of 48 patients with functional movement disorder (FMD) and 65 healthy controls obtained with functional MRI. For each participant, the data set provides five variants of network centrality maps and two types of seed-based correlation maps using the precuneus and the left temporoparietal junction (TPJ) as seed regions

Prepulse inhibition of the blink reflex is abnormal in functional movement disorders.

BACKGROUND: Patients with functional movement disorders also typically have functional somatic symptoms, including pain, fatigue, and sensory disturbance. A potentially unifying mechanism for such symptoms is a failure in processing of sensory inputs. Prepulse inhibition is a neurophysiological method that allows for the study of preconscious somatosensory processing. OBJECTIVE: The objective of this study was to assess prepulse inhibition in patients with functional movement disorders and healthy control subjects. METHODS: We analyzed the effect of a weak electrical stimulus to the index finger (prepulse) on the magnitude of the R2 response of the blink reflex induced by electrical stimuli delivered to the supraorbital nerve in 22 patients with clinically established functional movement disorders and 22 matched controls. Pain, depression, anxiety, and obsessive-compulsive symptoms were assessed using self-rated questionnaires. In addition, in patients we assessed motor symptom severity. RESULTS: Prepulses suppressed the R2 response of the blink reflex in both groups, by 36.4% (standard deviation: 25.6) in patients and by 67.3% (standard deviation: 16.4) in controls. This difference was significant (P < 0.001). There was no significant correlation between motor and nonmotor symptom measures and prepulse inhibition size. CONCLUSIONS: Impaired prepulse inhibition of the blink reflex suggests an abnormal preconscious processing of somatosensory inputs, which can be interpreted within predictive coding accounts of both functional movement disorders and functional somatic syndromes. Our results, along with previous findings of a reduced prepulse inhibition in fibromyalgia syndrome, support a possible unified pathophysiology across functional neurological and somatic syndromes with noteworthy implications for diagnostic classification and development of novel biomarkers and treatments. © 2019 International Parkinson and Movement Disorder Society

Scoring algorithm-based genomic testing in dystonia: A prospective validation study.

BACKGROUND: Despite the established value of genomic testing strategies, practice guidelines for their use do not exist in many indications. OBJECTIVES: We sought to validate a recently introduced scoring algorithm for dystonia, predicting the diagnostic utility of whole-exome sequencing (WES) based on individual phenotypic aspects (age-at-onset, body distribution, presenting comorbidity). METHODS: We prospectively enrolled a set of 209 dystonia-affected families and obtained summary scores (0-5 points) according to the algorithm. Singleton (N = 146), duo (N = 11), and trio (N = 52) WES data were generated to identify genetic diagnoses. RESULTS: Diagnostic yield was highest (51%) among individuals with a summary score of 5, corresponding to a manifestation of early-onset segmental or generalized dystonia with coexisting non-movement disorder-related neurological symptoms. Sensitivity and specificity at the previously suggested threshold for implementation of WES (3 points) was 96% and 52%, with area under the curve of 0.81. CONCLUSIONS: The algorithm is a useful predictive tool and could be integrated into dystonia routine diagnostic protocols

Clinically relevant copy-number variants in exome sequencing data of patients with dystonia.

Introduction: Next-generation sequencing is now used on a routine basis for molecular testing but studies on copy-number variant (CNV) detection from next-generation sequencing data are underrepresented. Utilizing an existing whole-exome sequencing (WES) dataset, we sought to investigate the contribution of rare CNVs to the genetic causality of dystonia. Methods: The CNV read-depth analysis tool ExomeDepth was applied to the exome sequences of 953 unrelated patients with dystonia (600 with isolated dystonia and 353 with combined dystonia; 33% with additional neurological involvement). We prioritized rare CNVs that affected known disease genes and/or were known to be associated with defined microdeletion/microduplication syndromes. Pathogenicity assessment of CNVs was based on recently published standards of the American College of Medical Genetics and Genomics and the Clinical Genome Resource. Results: We identified pathogenic or likely pathogenic CNVs in 14 of 953 patients (1.5%). Of the 14 different CNVs, 12 were deletions and 2 were duplications, ranging in predicted size from 124bp to 17 Mb. Within the deletion intervals, BRPF1, CHD8, DJ1, EFTUD2, FGF14, GCH1, PANK2, SGCE, UBE3A, VPS16, WARS2, and WDR45 were determined as the most clinically relevant genes. The duplications involved chromosomal regions 6q21-q22 and 15q11-q13. CNV analysis increased the diagnostic yield in the total cohort from 18.4% to 19.8%, as compared to the assessment of single-nucleotide variants and small insertions and deletions alone. Conclusions: WES-based CNV analysis in dystonia is feasible, increases the diagnostic yield, and should be combined with the assessment of single-nucleotide variants and small insertions and deletions