While rare diseases (RDs) are by definition of low prevalence, the total number of patients suffering from an RD is high, and the majority of them have neurologic manifestations, involving central, peripheral nerve, and muscle. In 2017, 24 European Reference Networks (ERNs), each focusing on a specific group of rare or low-prevalence complex diseases, were formed to improve the care for patients with an RD. One major aim is to have “the knowledge travel instead of the patient,” which has been put into practice by the implementation of the Clinical Patient Management System (CPMS) that enables clinicians to perform pan-European virtual consultations. The European Reference Network for Rare Neurological Diseases (ERN-RND) provides an infrastructure for knowledge sharing and care coordination for patients affected by a rare neurological disease (RND) involving the most common central nervous system pathological conditions. It covers the following disease groups: (i) Cerebellar Ataxias and Hereditary Spastic Paraplegias; (ii) Huntington's disease and Other Choreas; (iii) Frontotemporal dementia; (iv) Dystonia, (non-epileptic) paroxysmal disorders, and Neurodegeneration with Brain Iron Accumulation; (v) Leukoencephalopathies; and (vi) Atypical Parkinsonian Syndromes. At the moment, it unites 32 expert centers and 10 affiliated partners in 21 European countries, as well as patient representatives, but will soon cover nearly all countries of the European Union as a result of the ongoing expansion process. Disease expert groups developed and consented on diagnostic flowcharts and disease scales to assess the different aspects of RNDs. ERN-RND has started to discuss diagnostically unclear patients in the CPMS, is one of four ERNs that serve as foundation of Solve-RD, and has established an RND training and education program. The network will facilitate trial readiness through the establishment of an ERN-RND registry with a minimal data of all patients seen at the ERN-RND centers, thus providing a unique overview of existing genotype-based cohorts. The overall aim of the ERNs is to improve access for patients with RDs to quality diagnosis, care, and treatment. Based on this objective, ERNs are monitored by the European Commission on a regular basis to provide transparency and reassurance to the RD community and the general public.
Background and Objectives. Neurofilament light (NfL) appears a promising fluid biomarker in repeat-expansion spinocerebellar ataxias (SCAs), with piloting studies in mixed SCA cohorts suggesting that NfL might be increased at the ataxic stage of spinocerebellar ataxia type 1 (SCA1). We here hypothesised that NfL is increased not only at the ataxic stage of SCA1, but also at its - likely most treatment-relevant - preataxic stage.
Methods. We assessed serum (sNfL) and cerebrospinal fluid (cNfL) levels of NfL in both preataxic and ataxic SCA1, leveraging a multicentric cohort of 40 SCA1 carriers (23 preataxic, 17 ataxic) and >80 controls, and clinical follow-up data including actually observed (rather than only predicted) conversion to the ataxic stage (11 carriers).
Results. sNfL levels were increased with high age-corrected effect sizes at the preataxic (r=0.62) and ataxic stage (r=0.63), paralleling increases of cNfL levels. In preataxic subjects, sNfL levels increased with proximity to predicted ataxia onset, with significant sNfL elevations already 5 years before onset, and confirmed in preataxic subjects with actually observed ataxia onset. sNfL increases were detected already in preataxic SCA1 subjects without volumetric atrophy of cerebellum or pons, suggesting that sNfL might be more sensitive to early preataxic neurodegeneration than the currently known most change-sensitive regions in volumetric MRI. Using longitudinal sNfL measurements, we estimated sample sizes for clinical trials using the reduction of sNfL as endpoint.
Conclusions. sNfL levels might thus provide easily accessible peripheral biomarkers in both preataxic and ataxic SCA1, allowing stratification of preataxic subjects regarding proximity-to-onset, early detection of neurodegeneration even before volumetric MRI alterations, and potentially capture of treatment response in clinical trials.
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