Variable Interpretation of the Dystonia Consensus Classification Items Compromises Its Solidity

Anatomical categorization of isolated non-focal dystonia: novel and existing patterns using a data-driven approach

According to expert consensus, dystonia can be classified as focal, segmental, multifocal, and generalized, based on the affected body distribution. To provide an empirical and data-driven approach to categorizing these distributions, we used a data-driven clustering approach to compare frequency and co-occurrence rates of non-focal dystonia in pre-defined body regions using the Dystonia Coalition (DC) dataset. We analyzed 1,618 participants with isolated non-focal dystonia from the DC database. The analytic approach included construction of frequency tables, variable-wise analysis using hierarchical clustering and independent component analysis (ICA), and case-wise consensus hierarchical clustering to describe associations and clusters for dystonia affecting any combination of eighteen pre-defined body regions. Variable-wise hierarchical clustering demonstrated closest relationships between bilateral upper legs (distance = 0.40), upper and lower face (distance = 0.45), bilateral hands (distance = 0.53), and bilateral feet (distance = 0.53). ICA demonstrated clear grouping for the a) bilateral hands, b) neck, and c) upper and lower face. Case-wise consensus hierarchical clustering at k = 9 identified 3 major clusters. Major clusters consisted primarily of a) cervical dystonia with nearby regions, b) bilateral hand dystonia, and c) cranial dystonia. Our data-driven approach in a large dataset of isolated non-focal dystonia reinforces common segmental patterns in cranial and cervical regions. We observed unexpectedly strong associations between bilateral upper or lower limbs, which suggests that symmetric multifocal patterns may represent a previously underrecognized dystonia subtype.

Diagnosis and classification of blepharospasm: Recommendations based on empirical evidence

BACKGROUND

Blepharospasm is one of the most common subtypes of dystonia, and often spreads to other body regions. Despite published guidelines, the approach to diagnosis and classification of affected body regions varies among clinicians.

OBJECTIVE

To delineate the clinical features used by movement disorder specialists in the diagnosis and classification of blepharospasm according to body regions affected, and to develop recommendations for a more consistent approach.

METHODS

Cross-sectional data for subjects diagnosed with all types of isolated dystonia were acquired from the Dystonia Coalition, an international, multicenter collaborative research network. Data were evaluated to determine how examinations recorded by movement disorder specialists were used to classify blepharospasm as focal, segmental, or multifocal.

RESULTS

Among all 3222 participants with isolated dystonia, 210 (6.5%) had a diagnosis of focal blepharospasm. Among these 210 participants, 34 (16.2%) had dystonia outside of upper face region. Factors such as dystonia severity across different body regions and number of body regions affected influenced the classification of blepharospasm as focal, segmental, or multifocal.

CONCLUSIONS

Although focal blepharospasm is the second most common type of dystonia, a high percentage of individuals given this diagnosis had dystonia outside of the eye/upper face region. These findings are not consistent with existing guidelines for the diagnosis and classification of focal blepharospasm, and point to the need for more specific guidelines for more consistent application of existing recommendations for diagnosis and classification.

Dystonia Management: What to Expect From the Future? The Perspectives of Patients and Clinicians Within DystoniaNet Europe

Improved care for people with dystonia presents a number of challenges. Major gaps in knowledge exist with regard to how to optimize the diagnostic process, how to leverage discoveries in pathophysiology into biomarkers, and how to develop an evidence base for current and novel treatments. These challenges are made greater by the realization of the wide spectrum of symptoms and difficulties faced by people with dystonia, which go well-beyond motor symptoms. A network of clinicians, scientists, and patients could provide resources to facilitate information exchange at different levels, share mutual experiences, and support each other's innovative projects. In the past, collaborative initiatives have been launched, including the American Dystonia Coalition, the European Cooperation in Science and Technology (COST-which however only existed for a limited time), and the Dutch DystonieNet project. The European Reference Network on Rare Neurological Diseases includes dystonia among other rare conditions affecting the central nervous system in a dedicated stream. Currently, we aim to broaden the scope of these initiatives to a comprehensive European level by further expanding the DystoniaNet network, in close collaboration with the ERN-RND. In line with the ERN-RND, the mission of DystoniaNet Europe is to improve care and quality of life for people with dystonia by, among other endeavors, facilitating access to specialized care, overcoming the disparity in education of medical professionals, and serving as a solid platform to foster international clinical and research collaborations. In this review, both professionals within the dystonia field and patients and caregivers representing Dystonia Europe highlight important unsolved issues and promising new strategies and the role that a European network can play in activating them.

Challenges in Clinicogenetic Correlations: One Phenotype - Many Genes

Background

In the field of movement disorders, what you see (phenotype) is seldom what you get (genotype). Whereas 1 phenotype was previously associated to 1 gene, the advent of next‐generation sequencing (NGS) has facilitated an exponential increase in disease‐causing genes and genotype–phenotype correlations, and the “one‐phenotype‐many‐genes” paradigm has become prominent.

Objectives

To highlight the “one‐phenotype‐many‐genes” paradigm by discussing the main challenges, perspectives on how to address them, and future directions.

Methods

We performed a scoping review of the various aspects involved in identifying the underlying molecular cause of a movement disorder phenotype.

Results

The notable challenges are (1) the lack of gold standards, overlap in clinical spectrum of different movement disorders, and variability in the interpretation of classification systems; (2) selecting which patients benefit from genetic tests and the choice of genetic testing; (3) problems in the variant interpretation guidelines; (4) the filtering of variants associated with disease; and (5) the lack of standardized, complete, and up‐to‐date gene lists. Perspectives to address these include (1) deep phenotyping and genotype–phenotype integration, (2) adherence to phenotype‐specific diagnostic algorithms, (3) implementation of current and complementary bioinformatic tools, (4) a clinical‐molecular diagnosis through close collaboration between clinicians and genetic laboratories, and (5) ongoing curation of gene lists and periodic reanalysis of genetic sequencing data.

Conclusions

Despite the rapidly emerging possibilities of NGS, there are still many steps to take to improve the genetic diagnostic yield. Future directions, including post‐NGS phenotyping and cohort analyses enriched by genotype–phenotype integration and gene networks, ought to be pursued to accelerate identification of disease‐causing genes and further improve our understanding of disease biology.

Essential tremor-plus: a controversial new concept

In addition to redefining essential tremor (ET), the 2018 consensus statement of the Movement Disorder Society on tremor coined a new term: essential tremor-plus (ET-plus). This term is uncertainly defined as tremor with the characteristics of ET, with additional neurological signs of uncertain clinical significance. If ET-plus had been defined on the basis of a difference in underlying pathology or an appreciable difference in prognosis, it would have a valid, scientific rationale, as does the term Parkinson-plus. However, there is no such evidence, so the basis for the term is questionable. In fact, ET-plus might only represent a state condition (ie, patients with ET might develop these additional clinical features when the disease is at a more advanced stage). We caution against coining new terms that are not supported by a firm scientific basis and encourage research into the creation of essential tremor subsets that are defined with respect to differences in underlying causes or pathophysiology.