Progressive Ataxia with Hemiplegic Migraines: a Phenotype of CACNA1A Missense Mutations, Not CAG Repeat Expansions

Progressive Ataxia due to de novo Missense Variants in the CACNA1A Gene

The CACNA1A gene encodes the alpha-1A subunit of P/Q type voltage-gated calcium channel Cav2.1, which is associated with a broad clinical spectrum and variable symptomatology. While few patients with progressive ataxia caused by CACNA1A missense variants have been reported, here we report three unrelated Chinese patients with progressive ataxia due to de novo missense variants in the CACNA1A gene, including a novel pathogenic variant (c.4999C > G) and a previously reported pathogenic variant (c.4037G > A). Our findings and a systematic literature review show the unique phenotype of progressive ataxia caused by missense variants and enlarge the genetic and clinical spectrum of CACNA1A. This suggests that in addition to routine screening for dynamic mutations, screening for CACNA1A variants is important for clinicians facing patients with progressive ataxia.

Three decades of gait index development: A comparative review of clinical and research gait indices

BACKGROUND

A wide variety of indices have been developed to quantify gait performance markers and associate them with their respective pathologies. Indices scores have enabled better decisions regarding patient treatments and allowed for optimized monitoring of the evolution of their condition. The extensive range of human gait indices presented over the last 30 years is evaluated and summarized in this narrative literature review exploring their application in clinical and research environments.

METHODS

The analysis will explore historical and modern gait indices, focusing on the clinical efficacy with respect to their proposed pathology, age range, and associated parameter limits. Features, methods, and clinically acceptable errors are discussed while simultaneously assessing indices advantages and disadvantages. This review analyses all indices published between 1994 and February 2021 identified using the Medline, PubMed, ScienceDirect, CINAHL, EMBASE, and Google Scholar databases.

FINDINGS

A total of 30 indices were identified as noteworthy for clinical and research purposes and another 137 works were included for discussion. The indices were divided in three major groups: observational (13), instrumented (16) and hybrid (1). The instrumented indices were further sub-divided in six groups, namely kinematic- (4), spatiotemporal- (5), kinetic- (2), kinematic- and kinetic- (2), electromyographic- (1) and Inertial Measurement Unit-based indices (2).

INTERPRETATION

This work is one of the first reviews to summarize observational and instrumented gait indices, exploring their applicability in research and clinical contexts. The aim of this review is to assist members of these communities with the selection of the proper index for the group in analysis.

The complexities of CACNA1A in clinical neurogenetics

Variants in CACNA1A are classically related to episodic ataxia type 2, familial hemiplegic migraine type 1, and spinocerebellar ataxia type 6. Over the years, CACNA1A has been associated with a broader spectrum of phenotypes. Targeted analysis and unbiased sequencing of CACNA1A result not only in clear molecular diagnoses, but also in large numbers of variants of uncertain significance (VUS), or likely pathogenic variants with a phenotype that does not directly match the CACNA1A spectrum. Over the last years, targeted and clinical exome sequencing in our center has identified 41 CACNA1A variants. Ultimately, variants were considered pathogenic or likely pathogenic in 23 cases, with most phenotypes ranging from episodic or progressive ataxia to more complex ataxia syndromes, as well as intellectual disability and epilepsy. In two cases, the causality of the variant was discarded based on non-segregation or an alternative diagnosis. In the remaining 16 cases, the variant was classified as uncertain, due to lack of opportunities for segregation analysis or uncertain association with a non-classic phenotype. Phenotypic variability and the large number of VUS make CACNA1A a challenging gene for neurogenetic diagnostics. Accessible functional read-outs are clearly needed, especially in cases with a non-classic phenotype.

Paroxysmal Movement Disorders

Paroxysmal movement disorders (PxMDs) are a clinical and genetically heterogeneous group of movement disorders characterized by episodic involuntary movements (dystonia, dyskinesia, chorea and/or ataxia). Historically, PxMDs were classified clinically (triggers and characteristics of the movements) and this directed single-gene testing. With the advent of next-generation sequencing (NGS), how we classify and investigate PxMDs has been transformed. Next-generation sequencing has enabled new gene discovery (RHOBTB2, TBC1D24), expansion of phenotypes in known PxMDs genes and a better understanding of disease mechanisms. However, PxMDs exhibit phenotypic pleiotropy and genetic heterogeneity, making it challenging to predict genotype based on the clinical phenotype. For example, paroxysmal kinesigenic dyskinesia is most commonly associated with variants in PRRT2 but also variants identified in PNKD, SCN8A, and SCL2A1. There are no radiological or biochemical biomarkers to differentiate genetic causes. Even with NGS, diagnosis rates are variable, ranging from 11 to 51% depending on the cohort studied and technology employed. Thus, a large proportion of patients remain undiagnosed compared to other neurological disorders such as epilepsy, highlighting the need for further genomic research in PxMDs. Whole-genome sequencing, deep-sequencing, copy number variant analysis, detection of deep-intronic variants, mosaicism and repeat expansions, will improve diagnostic rates. Identifying the underlying genetic cause has a significant impact on patient care, modification of treatment, long-term prognostication and genetic counseling. This paper provides an update on the genetics of PxMDs, description of PxMDs classified according to causative gene rather than clinical phenotype, highlighting key clinical features and providing an algorithm for genetic testing of PxMDs.