Phenotyping Dystonia

Clinical examinations are the cornerstone of diagnosing and describing dystonia phenotypes in humans. However, the heterogeneous clinical appearance and diverse etiologies of dystonia, together with the reliance on expert clinical assessment, can contribute to substantial delays between symptom onset and diagnosis. Standardized rating scales, such as the Burke-Fahn-Marsden Dystonia Rating Scale and the Toronto Western Spasmodic Torticollis Rating Scale provide measures of dystonic symptom severity. Nevertheless, clinical rating scales have known limitations. They are coarse, dependent on examiner expertise and liable to substantial inter-rater variability. Precise and reliable rating scales are important for dystonia treatment, such as botulinum toxin injections or deep brain stimulation. Due to these limitations, other approaches of phenotyping dystonia have received increasing attention in recent years. Wearable sensors, advances in computer vision and machine learning name just a few new opportunities to detect and quantify dystonia.

Phenotyping dystonia is even more challenging in animal models. Identifying whether an animal model can meet both face and construct validity is important in the continued effort to understand dystonia pathophysiology. However, the clinical criteria applied to dystonia patients cannot be easily transferred to rodents. The classic behavioral assessments such as the open field and Rotarod test quantify general motor performance and coordination, but the impairments revealed by them are not specific to dystonia. In an effort to capture the phenotype, dystonia-oriented observational scales for rodents have been developed. In recent years, markerless pose estimation (e.g., DeepLabCut), combined with automated segmentation of behavior, has made tracking of individual body parts possible, allowing for an observer-independent assessment of abnormal movements. EMG recordings have been used to capture physiological features characteristic of dystonia. Despite these advances, a common phenotyping framework for experimental models is still lacking and a shared, quantitative language for describing dystonia across species is still missing.

This Special Issue invites contributions that advance the phenotyping of dystonia across scales, from clinical assessment and novel measurement technologies in patients to behavioral and physiological characterization of animal models. We welcome original research, methods papers, reviews and perspectives, and particularly encourage work that bridges species or opens new ways of defining and measuring the disorder. Our aim is to move toward objective, reproducible and translatable phenotyping that supports earlier diagnosis, better-targeted treatment and a mechanistic understanding of dystonia.

Article types and fees

This Special Issue accepts the following article types, unless otherwise specified in the Special Issue description:

• Brief Research Report
• Case Report
• Commentary
• Editorial
• Letter to the Editor
• Mini Review
• Opinion
• Original Research
• Review

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Special Issue accepts the following article types, unless otherwise specified in the Special Issue description:

• Brief Research Report
• Case Report
• Commentary
• Editorial
• Letter to the Editor
• Mini Review
• Opinion
• Original Research
• Review

Keywords: Dystonia phenotyping, Animal models, Markerless pose estimation, Translational biomarkers, Electromyography (EMG)