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Dryad

Natural history, phenotypic spectrum, and discriminative features of multisystemic RFC1-disease

Cite this dataset

Traschütz, Andreas et al. (2020). Natural history, phenotypic spectrum, and discriminative features of multisystemic RFC1-disease [Dataset]. Dryad. https://doi.org/10.5061/dryad.1vhhmgqrd

Abstract

Objective: To delineate the full phenotypic spectrum, discriminative features, piloting longitudinal progression data, and sample size calculations of RFC1-repeat expansions, recently identified as causing cerebellar ataxia, neuropathy, vestibular areflexia syndrome (CANVAS).

Methods: Multimodal RFC1 repeat screening (PCR, southern blot, whole-exome/genome (WES/WGS)-based approaches) combined with cross-sectional and longitudinal deep-phenotyping in (i) cross-European cohort A (70 families) with ≥2 features of CANVAS and/or ataxia-with-chronic-cough (ACC); and (ii) Turkish cohort B (105 families) with unselected late-onset ataxia.

Results: Prevalence of RFC1-disease was 67% in cohort A, 14% in unselected cohort B, 68% in clinical CANVAS, and 100% in ACC. RFC1-disease was also identified in Western and Eastern Asians, and even by WES. Visual compensation, sensory symptoms, and cough were strong positive discriminative predictors (>90%) against RFC1-negative patients. The phenotype across 70 RFC1-positive patients was mostly multisystemic (69%), including dysautonomia (62%) and bradykinesia (28%) (=overlap with cerebellar-type multiple system atrophy [MSA-C]), postural instability (49%), slow vertical saccades (17%), and chorea and/or dystonia (11%). Ataxia progression was ~1.3 SARA points/year (32 cross-sectional, 17 longitudinal assessments, follow-up ≤9 years [mean 3.1]), but also included early falls, variable non-linear phases of MSA-C-like progression (SARA 2.5-5.5/year), and premature death. Treatment trials require 330 (1-year-trial) and 132 (2-year-trial) patients in total to detect 50% reduced progression.

Conclusions: RFC1-disease is frequent and occurs across continents, with CANVAS and ACC as highly diagnostic phenotypes, yet as variable, overlapping clusters along a continuous multisystemic disease spectrum, including MSA-C-overlap. Our natural history data help to inform future RFC1-treatment trials.

Methods

All patients and/or records were systematically re-assessed by the local physician according to a common comprehensive standardized data sheet developed by our RFC1 study group. All patients had at least one neurological examination; longitudinal data with ≥2 prospective examinations were available from 31 patients. Classification as CANVAS required clinical evidence of cerebellar, neuropathic (abnormal vibration sense with or without abnormal ankle reflex) and bilateral vestibular (vestibulo-ocular reflex by head-impulse test or video-oculography) damage to increase the sensitivity of our screening and to allow capturing patients from various centers across Europe (rather than electrophysiological evidence of e.g. sensory neuropathy, as required by the proposed diagnostic criteria of CANVAS). The phenotype was classified as “multisystemic” if any additional feature was present in addition to the CANVAS systems’ features: e.g. hypokinetic or hyperkinetic movement disorders, pyramidal signs , slow saccades, cognitive impairment, and/or signs of autonomic dysfunction. Ataxia severity was assessed by the Scale for the Assessment and Rating of Ataxia (SARA). Functional impairment was rated with the Spinocerebellar Degeneration Functional Score (SDFS) based on patient history and clinical examinations.

In a small independent exploratory analysis, we aimed to investigate whether the intronic AAGGG repeat motif can also be detected in WGS and in particular even WES datasets. We developed a data screening algorithm that first searched for sequence reads mapping within the chromosomal position of the RFC1 repeat expansion and then displayed the AAGGG motif in soft-clipped reads, in WES leveraging unintended off-target reads incidentally overlapping the repeat locus.

Usage notes

Missing values in Excel sheet reflect missing clinical data that could not be extracted from the records, probably indicating that the corresponding feature had not been asked or clinically examined.