Structural and functional brain alterations in laryngeal dystonia: A coordinate-based activation likelihood estimation meta-analysis.

Laryngeal dystonia (LD) is an isolated, task-specific, focal dystonia characterized by intermittent spasms of laryngeal muscles impairing speech production. Although recent studies have demonstrated neural alterations in LD, the consistency of findings across studies is not well-established, limiting their translational applicability. We conducted a systematic literature search to identify studies reporting stereotactic coordinates of peak structural and functional abnormalities in LD patients compared to healthy controls, followed by a coordinate-based activation likelihood estimation meta-analysis. A total of 21 functional and structural neuroimaging studies, including 31 experiments in 521 LD patients and 448 healthy controls, met the study inclusion criteria. The multimodal meta-analysis of these studies identified abnormalities in the bilateral primary motor cortices, the left inferior parietal lobule and striatum, the right insula, and the supplementary motor area in LD patients compared to healthy controls. The meta-analytical findings reinforce the current view of dystonia as a neural network disorder and consolidate evidence for future investigations probing these targets with new therapies.

Houston, We Have AI Problem! Quality Issues with Neuroimaging-Based Artificial Intelligence in Parkinson's Disease: A Systematic Review.

In recent years, many neuroimaging studies have applied artificial intelligence (AI) to facilitate existing challenges in Parkinson's disease (PD) diagnosis, prognosis, and intervention. The aim of this systematic review was to provide an overview of neuroimaging-based AI studies and to assess their methodological quality. A PubMed search yielded 810 studies, of which 244 that investigated the utility of neuroimaging-based AI for PD diagnosis, prognosis, or intervention were included. We systematically categorized studies by outcomes and rated them with respect to five minimal quality criteria (MQC) pertaining to data splitting, data leakage, model complexity, performance reporting, and indication of biological plausibility. We found that the majority of studies aimed to distinguish PD patients from healthy controls (54%) or atypical parkinsonian syndromes (25%), whereas prognostic or interventional studies were sparse. Only 20% of evaluated studies passed all five MQC, with data leakage, non-minimal model complexity, and reporting of biological plausibility as the primary factors for quality loss. Data leakage was associated with a significant inflation of accuracies. Very few studies employed external test sets (8%), where accuracy was significantly lower, and 19% of studies did not account for data imbalance. Adherence to MQC was low across all observed years and journal impact factors. This review outlines that AI has been applied to a wide variety of research questions pertaining to PD; however, the number of studies failing to pass the MQC is alarming. Therefore, we provide recommendations to enhance the interpretability, generalizability, and clinical utility of future AI applications using neuroimaging in PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genetic Risk Factors in Isolated Dystonia Escape Genome-Wide Association Studies.

BACKGROUND: Despite considerable heritability, previous smaller genome-wide association studies (GWASs) have not identified any robust genetic risk factors for isolated dystonia. OBJECTIVE: The objective of this study was to perform a large-scale GWAS in a well-characterized, multicenter sample of >6000 individuals to identify genetic risk factors for isolated dystonia. METHODS: Array-based GWASs were performed on autosomes for 4303 dystonia participants and 2362 healthy control subjects of European ancestry with subgroup analysis based on age at onset, affected body regions, and a newly developed clinical score. Another 736 individuals were used for validation. RESULTS: This GWAS identified no common genome-wide significant loci that could be replicated despite sufficient power to detect meaningful effects. Power analyses imply that the effects of individual variants are likely very small. CONCLUSIONS: Moderate single-nucleotide polymorphism-based heritability indicates that common variants do not contribute to isolated dystonia in this cohort. Sequence-based GWASs (eg, by whole-genome sequencing) might help to better understand the genetic basis. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Failure to breathe persists without air hunger or alarm following amygdala seizures.

Postictal apnea is thought to be a major cause of sudden unexpected death in epilepsy (SUDEP). However, the mechanisms underlying postictal apnea are unknown. To understand causes of postictal apnea, we used a multimodal approach to study brain mechanisms of breathing control in 20 patients (ranging from pediatric to adult) undergoing intracranial electroencephalography for intractable epilepsy. Our results indicate that amygdala seizures can cause postictal apnea. Moreover, we identified a distinct region within the amygdala where electrical stimulation was sufficient to reproduce prolonged breathing loss persisting well beyond the end of stimulation. The persistent apnea was resistant to rising CO2 levels, and air hunger failed to occur, suggesting impaired CO2 chemosensitivity. Using es-fMRI, a potentially novel approach combining electrical stimulation with functional MRI, we found that amygdala stimulation altered blood oxygen level-dependent (BOLD) activity in the pons/medulla and ventral insula. Together, these findings suggest that seizure activity in a focal subregion of the amygdala is sufficient to suppress breathing and air hunger for prolonged periods of time in the postictal period, likely via brainstem and insula sites involved in chemosensation and interoception. They further provide insights into SUDEP, may help identify those at greatest risk, and may lead to treatments to prevent SUDEP.

Temporal Signature of Task-Specificity in Isolated Focal Laryngeal Dystonia.

BACKGROUND AND OBJECTIVE: Laryngeal dystonia (LD) is focal task-specific dystonia, predominantly affecting speech but not whispering or emotional vocalizations. Prior neuroimaging studies identified brain regions forming a dystonic neural network and contributing to LD pathophysiology. However, the underlying temporal dynamics of these alterations and their contribution to the task-specificity of LD remain largely unknown. The objective of the study was to identify the temporal-spatial signature of altered cortical oscillations associated with LD pathophysiology. METHODS: We used high-density 128-electrode electroencephalography (EEG) recordings during symptomatic speaking and two asymptomatic tasks, whispering and writing, in 24 LD patients and 22 healthy individuals to investigate the spectral dynamics, spatial localization, and interregional effective connectivity of aberrant cortical oscillations within the dystonic neural network, as well as their relationship with LD symptomatology. RESULTS: Symptomatic speaking in LD patients was characterized by significantly increased gamma synchronization in the middle/superior frontal gyri, primary somatosensory cortex, and superior parietal lobule, establishing the altered prefrontal-parietal loop. Hyperfunctional connectivity from the left middle frontal gyrus to the right superior parietal lobule was significantly correlated with the age of onset and the duration of LD symptoms. Asymptomatic whisper in LD patients had not no statistically significant changes in any frequency band, whereas asymptomatic writing was characterized by significantly decreased synchronization of beta-band power localized in the right superior frontal gyrus. CONCLUSION: Task-specific oscillatory activity of prefrontal-parietal circuitry is likely one of the underlying mechanisms of aberrant heteromodal integration of information processing and transfer within the neural network leading to dystonic motor output. © 2023 International Parkinson and Movement Disorder Society.

Sodium Oxybate in Alcohol-Responsive Essential Tremor of Voice: An Open-Label Phase II Study.

BACKGROUND: Essential tremor of voice (ETv) is characterized by involuntary oscillations of laryngeal and upper airway muscles, causing rhythmic alterations in pitch and loudness during both passive breathing and active laryngeal tasks, such as speaking and singing. Treatment of ETv is challenging and typically less effective compared with treatment of ET affecting extremities. OBJECTIVE: We conducted a proof-of-concept, open-label phase II study to examine the efficacy and central effects of sodium oxybate in patients with alcohol-responsive ETv. METHODS: All subjects received 1.0 to 1.5 g of oral sodium oxybate and underwent brain functional magnetic resonance imaging. The primary endpoint was the number of patients (% from total) with reduced ETv symptoms by at least 10% at about 40 to 45 minutes after sodium oxybate intake based on the combined visual analog scale score of ETv symptom severity. The secondary endpoint included changes in brain activity after sodium oxybate intake compared to baseline. RESULTS: Sodium oxybate reduced ETv symptoms on average by 40.8% in 92.9% of patients. Drug effects were observed about 40 to 45 minutes after intake, lasting about 3.5 hours, and gradually wearing off by the end of the fifth hour. The central effects of sodium oxybate were associated with normalized activity in the cerebellum, inferior/superior parietal lobules, inferior frontal gyrus, and insula and re-established functional relationships between these regions. CONCLUSIONS: Sodium oxybate showed high efficacy in ETv patients, with a likely central action on disorder pathophysiology. Sodium oxybate may be an effective novel oral drug for treatment of alcohol-responsive ETv patients. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Parkinson's disease speech production network as determined by graph-theoretical network analysis.

Parkinson's disease (PD) can affect speech as well as emotion processing. We employ whole-brain graph-theoretical network analysis to determine how the speech-processing network (SPN) changes in PD, and assess its susceptibility to emotional distraction. Functional magnetic resonance images of 14 patients (aged 59.6 ± 10.1 years, 5 female) and 23 healthy controls (aged 64.1 ± 6.5 years, 12 female) were obtained during a picture-naming task. Pictures were supraliminally primed by face pictures showing either a neutral or an emotional expression. PD network metrics were significantly decreased (mean nodal degree, p < 0.0001; mean nodal strength, p < 0.0001; global network efficiency, p < 0.002; mean clustering coefficient, p < 0.0001), indicating an impairment of network integration and segregation. There was an absence of connector hubs in PD. Controls exhibited key network hubs located in the associative cortices, of which most were insusceptible to emotional distraction. The PD SPN had more key network hubs, which were more disorganized and shifted into auditory, sensory, and motor cortices after emotional distraction. The whole-brain SPN in PD undergoes changes that result in (a) decreased network integration and segregation, (b) a modularization of information flow within the network, and (c) the inclusion of primary and secondary cortical areas after emotional distraction.

Clinical Implications of Dystonia as a Neural Network Disorder.

Isolated dystonia is a neurological disorder of diverse etiology, multifactorial pathophysiology, and wide spectrum of clinical presentations. We review the recent neuroimaging advances that led to the conceptualization of dystonia as a neural network disorder and discuss how current knowledge is shaping the identification of biomarkers of dystonia and the development of novel pharmacological therapies.

Sensory processing in the auditory and olfactory domains is normal in laryngeal dystonia.

Abnormal sensory discriminatory processing has been implicated as an endophenotypic marker of isolated dystonia. However, the extent of alterations across the different sensory domains and their commonality in different forms of dystonia are unclear. Based on the previous findings of abnormal temporal but not spatial discrimination in patients with laryngeal dystonia, we investigated sensory processing in the auditory and olfactory domains as potentially additional contributors to the disorder pathophysiology. We tested auditory temporal discrimination and olfactory function, including odor identification, threshold, and discrimination, in 102 laryngeal dystonia patients and 44 healthy controls, using dichotically presented pure tones and the extended Sniffin' Sticks smell test protocol, respectively. Statistical significance was assessed using analysis of variance with non-parametric bootstrapping. Patients had a lower mean auditory temporal discrimination threshold, with abnormal values found in three patients. Hyposmia was found in 64 patients and anosmia in 2 patients. However, there were no statistically significant differences in either auditory temporal discrimination threshold or olfactory identification, threshold, and discrimination between the groups. A significant positive relationship was found between olfactory threshold and disorder severity based on the Burke-Fahn-Marsden dystonia rating scale. Our findings demonstrate that, contrary to altered visual temporal discrimination, auditory temporal discrimination and olfactory function are likely not candidate endophenotypic markers of laryngeal dystonia.

Graph-theoretical insights into the effects of aging on the speech production network.

Speech production relies on the interplay of different brain regions. Healthy aging leads to complex changes in speech processing and production. Here, we investigated how the whole-brain functional connectivity of healthy elderly individuals differs from that of young individuals. In total, 23 young (aged 24.6 ± 2.2 years) and 23 elderly (aged 64.1 ± 6.5 years) individuals performed a picture naming task during functional magnetic resonance imaging. We determined whole-brain functional connectivity matrices and used them to compute group averaged speech production networks. By including an emotionally neutral and an emotionally charged condition in the task, we characterized the speech production network during normal and emotionally challenged processing. Our data suggest that the speech production network of elderly healthy individuals is as efficient as that of young participants, but that it is more functionally segregated and more modularized. By determining key network regions, we showed that although complex network changes take place during healthy aging, the most important network regions remain stable. Furthermore, emotional distraction had a larger influence on the young group's network than on the elderly's. We demonstrated that, from the neural network perspective, elderly individuals have a higher capacity for emotion regulation based on their age-related network re-organization.

DystoniaBoTXNet: Novel Neural Network Biomarker of Botulinum Toxin Efficacy in Isolated Dystonia.

OBJECTIVE: Isolated dystonia is characterized by abnormal, often painful, postures and repetitive movements due to sustained or intermittent involuntary muscle contractions. Botulinum toxin (BoTX) injections into the affected muscles are the first line of therapy. However, there are no objective predictive markers or standardized tests of BoTX efficacy that can be utilized for appropriate candidate selection prior to treatment initiation. METHODS: We developed a deep learning algorithm, DystoniaBoTXNet, which uses a 3D convolutional neural network architecture and raw structural brain magnetic resonance images (MRIs) to automatically discover and test a neural network biomarker of BoTX efficacy in 284 patients with 4 different forms of focal dystonia, including laryngeal dystonia, blepharospasm, cervical dystonia, and writer's cramp. RESULTS: DystoniaBoTXNet identified clusters in superior parietal lobule, inferior and middle frontal gyri, middle orbital gyrus, inferior temporal gyrus, corpus callosum, inferior fronto-occipital fasciculus, and anterior thalamic radiation as components of the treatment biomarker. These regions are known to contribute to both dystonia pathophysiology across a broad clinical spectrum of disorder and the central effects of botulinum toxin treatment. Based on its biomarker, DystoniaBoTXNet achieved an overall accuracy of 96.3%, with 100% sensitivity and 86.1% specificity, in predicting BoTX efficacy in patients with isolated dystonia. The algorithmic decision was computed in 19.2 seconds per case. INTERPRETATION: DystoniaBoTXNet and its treatment biomarker have a high translational potential as an objective, accurate, generalizable, fast, and cost-effective algorithmic platform for enhancing clinical decision making for BoTX treatment in patients with isolated dystonia. ANN NEUROL 2023;93:460-471.

Multimodal collaborative brain-computer interfaces aid human-machine team decision-making in a pandemic scenario.

Objective.Critical decisions are made by effective teams that are characterized by individuals who trust each other and know how to best integrate their opinions. Here, we introduce a multimodal brain-computer interface (BCI) to help collaborative teams of humans and an artificial agent achieve more accurate decisions in assessing danger zones during a pandemic scenario.Approach.Using high-resolution simultaneous electroencephalography/functional MRI (EEG/fMRI), we first disentangled the neural markers of decision-making confidence and trust and then employed machine-learning to decode these neural signatures for BCI-augmented team decision-making. We assessed the benefits of BCI on the team's decision-making process compared to the performance of teams of different sizes using the standard majority or weighing individual decisions.Main results.We showed that BCI-assisted teams are significantly more accurate in their decisions than traditional teams, as the BCI is capable of capturing distinct neural correlates of confidence on a trial-by-trial basis. Accuracy and subjective confidence in the context of collaborative BCI engaged parallel, spatially distributed, and temporally distinct neural circuits, with the former being focused on incorporating perceptual information processing and the latter involving action planning and executive operations during decision making. Among these, the superior parietal lobule emerged as a pivotal region that flexibly modulated its activity and engaged premotor, prefrontal, visual, and subcortical areas for shared spatial-temporal control of confidence and trust during decision-making.Significance.Multimodal, collaborative BCIs that assist human-artificial agent teams may be utilized in critical settings for augmented and optimized decision-making strategies.

Brain-Computer Interfaces for Treatment of Focal Dystonia.

Task-specificity in isolated focal dystonias is a powerful feature that may successfully be targeted with therapeutic brain-computer interfaces. While performing a symptomatic task, the patient actively modulates momentary brain activity (disorder signature) to match activity during an asymptomatic task (target signature), which is expected to translate into symptom reduction.

Short- and Long-term Central Action of Botulinum Neurotoxin Treatment in Laryngeal Dystonia.

BACKGROUND AND OBJECTIVES: Laryngeal dystonia (LD) is isolated task-specific focal dystonia selectively impairing speech production. The first choice of LD treatment is botulinum neurotoxin (BoNT) injections into the affected laryngeal muscles. However, whether BoNT has a lasting therapeutic effect on disorder pathophysiology is unknown. We investigated short-term and long-term effects of BoNT treatment on brain function in patients with LD. METHODS: A total of 161 participants were included in the functional MRI study. Statistical analyses examined central BoNT effects in patients with LD who were stratified based on the effectiveness and duration of treatment. RESULTS: Patients with LD who were treated and benefited from BoNT injections had reduced activity in the left precuneus compared with BoNT-naive and treatment nonbenefiting patients. In addition, BoNT-treated patients with adductor LD had decreased activity in the right thalamus, whereas BoNT-treated abductor patients with LD had reduced activity in the left inferior frontal cortex. No statistically significant differences in brain activity were found between patients with shorter (1-5 years) and longer (13-28 years) treatment durations. However, patients with intermediate treatment duration of 6-12 years showed reduced activity in the right cerebellum compared with patients with both shorter and longer treatment durations and reduced activity in the right prefrontal cortex compared with patients with shorter treatment duration. DISCUSSION: Our findings suggest that the left precuneus is the site of short-term BoNT central action in patients with LD, whereas the prefrontal-cerebellar axis is engaged in the BoNT response in patients with intermediate treatment duration of 6-12 years. Involvement of these structures points to indirect action of BoNT treatment on the dystonic sensorimotor network through modulation of motor sequence planning and coordination.

Functional Neural Networks in Writer's Cramp as Determined by Graph-Theoretical Analysis.

Dystonia, a debilitating neurological movement disorder, is characterized by involuntary muscle contractions and develops from a complex pathophysiology. Graph theoretical analysis approaches have been employed to investigate functional network changes in patients with different forms of dystonia. In this study, we aimed to characterize the abnormal brain connectivity underlying writer's cramp, a focal hand dystonia. To this end, we examined functional magnetic resonance scans of 20 writer's cramp patients (11 females/nine males) and 26 healthy controls (10 females/16 males) performing a sequential finger tapping task with their non-dominant (and for patients non-dystonic) hand. Functional connectivity matrices were used to determine group averaged brain networks. Our data suggest that in their neuronal network writer's cramp patients recruited fewer regions that were functionally more segregated. However, this did not impair the network's efficiency for information transfer. A hub analysis revealed alterations in communication patterns of the primary motor cortex, the thalamus and the cerebellum. As we did not observe any differences in motor outcome between groups, we assume that these network changes constitute compensatory rerouting within the patient network. In a secondary analysis, we compared patients with simple writer's cramp (only affecting the hand while writing) and those with complex writer's cramp (affecting the hand also during other fine motor tasks). We found abnormal cerebellar connectivity in the simple writer's cramp group, which was less prominent in complex writer's cramp. Our preliminary findings suggest that longitudinal research concerning cerebellar connectivity during WC progression could provide insight on early compensatory mechanisms in WC.

The dynamic connectome of speech control.

Speech production relies on the orchestrated control of multiple brain regions. The specific, directional influences within these networks remain poorly understood. We used regression dynamic causal modelling to infer the whole-brain directed (effective) connectivity from functional magnetic resonance imaging data of 36 healthy individuals during the production of meaningful English sentences and meaningless syllables. We identified that the two dynamic connectomes have distinct architectures that are dependent on the complexity of task production. The speech was regulated by a dynamic neural network, the most influential nodes of which were centred around superior and inferior parietal areas and influenced the whole-brain network activity via long-ranging coupling with primary sensorimotor, prefrontal, temporal and insular regions. By contrast, syllable production was controlled by a more compressed, cost-efficient network structure, involving sensorimotor cortico-subcortical integration via superior parietal and cerebellar network hubs. These data demonstrate the mechanisms by which the neural network reorganizes the connectivity of its influential regions, from supporting the fundamental aspects of simple syllabic vocal motor output to multimodal information processing of speech motor output. This article is part of the theme issue 'Vocal learning in animals and humans'.

Laryngeal Dystonia: Multidisciplinary Update on Terminology, Pathophysiology, and Research Priorities.

OBJECTIVE: To delineate research priorities for improving clinical management of laryngeal dystonia, the NIH convened a multidisciplinary panel of experts for a 1-day workshop to examine the current progress in understanding its etiopathophysiology and clinical care. METHODS: The participants reviewed the current terminology of disorder and discussed advances in understanding its pathophysiology since a similar workshop was held in 2005. Clinical and research gaps were identified, and recommendations for future directions were delineated. RESULTS: The panel unanimously agreed to adopt the term "laryngeal dystonia" instead of "spasmodic dysphonia" to reflect the current progress in characterizations of this disorder. Laryngeal dystonia was recognized as a multifactorial, phenotypically heterogeneous form of isolated dystonia. Its etiology remains unknown, whereas the pathophysiology likely involves large-scale functional and structural brain network disorganization. Current challenges include the lack of clinically validated diagnostic markers and outcome measures and the paucity of therapies that address the disorder pathophysiology. CONCLUSION: Research priorities should be guided by challenges in clinical management of laryngeal dystonia. Identification of disorder-specific biomarkers would allow the development of novel diagnostic tools and unified measures of treatment outcome. Elucidation of the critical nodes within neural networks that cause or modulate symptoms would allow the development of targeted therapies that address the underlying pathophysiology. Given the rarity of laryngeal dystonia, future rapid research progress may be facilitated by multicenter, national and international collaborations.

Association of Sinonasal Inflammation With Functional Brain Connectivity.

Importance: In recent years, there have been several meaningful advances in the understanding of the cognitive effects of chronic rhinosinusitis. However, an investigation exploring the potential link between the underlying inflammatory disease and higher-order neural processing has not yet been performed. Objective: To describe the association of sinonasal inflammation with functional brain connectivity (Fc), which may underlie chronic rhinosinusitis-related cognitive changes. Design, Setting, and Participants: This is a case-control study using the Human Connectome Project (Washington University-University of Minnesota Consortium of the Human Connectome Project 1200 release), an open-access and publicly available data set that includes demographic, imaging, and behavioral data for 1206 healthy adults aged 22 to 35 years. Twenty-two participants demonstrated sinonasal inflammation (Lund-Mackay score [LMS] ≥ 10) and were compared with age-matched and sex-matched healthy controls (LMS = 0). These participants were further stratified into moderate (LMS < 14, n = 13) and severe (LMS ≥ 14, n = 9) inflammation groups. Participants were screened and excluded if they had a history of psychiatric disorder and/or neurological or genetic diseases. Participants with diabetes or cardiovascular disease were also excluded, as these conditions may affect neuroimaging quality. The data were accessed between October 2019 and August 2020. Data analysis was performed between May 2020 and August 2020. Main Outcomes and Measures: The primary outcome was the difference in resting state Fc within and between the default mode, frontoparietal, salience, and dorsal attention brain networks. Secondary outcomes included assessments of cognitive function using the National Institutes of Health Toolbox Cognition Battery. Results: A total of 22 patients with chronic rhinosinusitis and 22 healthy controls (2 [5%] were aged 22-25 years, 26 [59%] were aged 26-30 years, and 16 [36%] were aged 31-35 years; 30 [68%] were men) were included in the analysis. Participants with sinonasal inflammation showed decreased Fc within the frontoparietal network, in a region involving bilateral frontal medial cortices. This region demonstrated increased Fc to 2 nodes within the default-mode network and decreased Fc to 1 node within the salience network. The magnitude of these differences increased with inflammation severity (dose dependent). There were no significant associations seen on cognitive testing. Conclusions and Relevance: In this case-control study, participants with sinonasal inflammation showed decreased brain connectivity within a major functional hub with a central role in modulating cognition. This region also shows increased connectivity to areas that are activated during introspective and self-referential processing and decreased connectivity to areas involved in detection and response to stimuli. Future prospective studies are warranted to determine the applicability of these findings to a clinical chronic rhinosinusitis population.

Suicidal Ideations and Attempts in Patients With Isolated Dystonia.

OBJECTIVE: To evaluate the hypothesis that individuals with isolated dystonia are at an increased risk for suicidal behavior, we administered an anonymous electronic survey to patients with dystonia, asking them about their history of suicidal ideations and suicide attempt. METHODS: A total of 542 patients with dystonia completed an online 97-question survey, which captured the demographics of suicidal behavior and major psychiatric disorders. Statistical analyses examined the prevalence of suicidal behavior in patients with dystonia compared to the prevalence of suicidal ideations and attempt in the general global population and assessed the significance of risk associations between suicidality and psychiatric history in these patients. RESULTS: Overall, 32.3% of patients with isolated dystonia reported a lifetime history of suicidal behavior, which was significantly different from the reported rates of suicidal ideation (9.2%) and attempt (2.7%) in the general global population. The prevalence of suicidality was higher in patients with multifocal/segmental and generalized forms of dystonia (range of 46%-50%) compared to patients with focal dystonias (range of 26.1%-33.3%). The highest suicidal ideation-to-attempt ratio of 4:1 was found in patients with generalized dystonia. Suicidality in patients with focal dystonia was significantly associated with history of depression and anxiety disorders. CONCLUSION: Patients with isolated dystonia have an increased, albeit unrecognized, prevalence of suicidal behavior compared to the general global population. Screening for suicidal risk should be incorporated as part of the clinical evaluation of patients with dystonia to prevent their suicide-induced injury and death.

Neural endophenotypes and predictors of laryngeal dystonia penetrance and manifestation.

Focal dystonias are the most common forms of isolated dystonia; however, the etiopathophysiological signatures of disorder penetrance and clinical manifestation remain unclear. Using an imaging genetics approach, we investigated functional and structural representations of neural endophenotypes underlying the penetrance and manifestation of laryngeal dystonia in families, including 21 probands and 21 unaffected relatives, compared to 32 unrelated healthy controls. We further used a supervised machine-learning algorithm to predict the risk for dystonia development in susceptible individuals based on neural features of identified endophenotypes. We found that abnormalities in prefrontal-parietal cortex, thalamus, and caudate nucleus were commonly shared between patients and their unaffected relatives, representing an intermediate endophenotype of laryngeal dystonia. Machine learning classified 95.2% of unaffected relatives as patients rather than healthy controls, substantiating that these neural alterations represent the endophenotypic marker of dystonia penetrance, independent of its symptomatology. Additional abnormalities in premotor-parietal-temporal cortical regions, caudate nucleus, and cerebellum were present only in patients but not their unaffected relatives, likely representing a secondary endophenotype of dystonia manifestation. Based on alterations in the parietal cortex and caudate nucleus, the machine learning categorized 28.6% of unaffected relative as patients, indicating their increased lifetime risk for developing clinical manifestation of dystonia. The identified endophenotypic neural markers may be implemented for screening of at-risk individuals for dystonia development, selection of families for genetic studies of novel variants based on their risk for disease penetrance, or stratification of patients who would respond differently to a particular treatment in clinical trials.