Responsiveness of the Scale for the Assessment and Rating of Ataxia and Natural History in 884 Recessive and Early Onset Ataxia Patients

The Scale for the Assessment and Rating of Ataxia (SARA) is the most widely applied clinical outcome assessment (COA) for genetic ataxias, but presents metrological and regulatory challenges. To facilitate trial planning, we characterize its responsiveness (including subitem-level relations to ataxia severity and patient-focused outcomes) across a large number of ataxias, and provide first natural history data for several of them.Subitem-level correlation- and distribution-based analysis of 1637 SARA assessments in 884 patients with autosomal-recessive/early-onset ataxia (370 with 2-8 longitudinal assessments), complemented by linear mixed-effects modeling to estimate progression and sample sizes.While SARA subitem responsiveness varied between ataxia severities, gait/stance showed a robust granular linear scaling across the broadest range (SARA25; 2.7-fold sample size). Use of a novel rank-optimized SARA without subitems finger-chase and nose-finger reduces sample sizes by 20-25%.This study comprehensively characterizes COA properties and annualized changes of the SARA across and within a large number of ataxias. It suggests specific approaches for optimizing its responsiveness that might facilitate regulatory qualification and trial design. This article is protected by copyright. All rights reserved

The ARCA Registry: A Collaborative Global Platform for Advancing Trial Readiness in Autosomal Recessive Cerebellar Ataxias.

Autosomal recessive cerebellar ataxias (ARCAs) form an ultrarare yet expanding group of neurodegenerative multisystemic diseases affecting the cerebellum and other neurological or non-neurological systems. With the advent of targeted therapies for ARCAs, disease registries have become a precious source of real-world quantitative and qualitative data complementing knowledge from preclinical studies and clinical trials. Here, we review the ARCA Registry, a global collaborative multicenter platform (>15 countries, >30 sites) with the overarching goal to advance trial readiness in ARCAs. It presents a good clinical practice (GCP)- and general data protection regulation (GDPR)-compliant professional-reported registry for multicenter web-based capture of cross-center standardized longitudinal data. Modular electronic case report forms (eCRFs) with core, extended, and optional datasets allow data capture tailored to the participating site's variable interests and resources. The eCRFs cover all key data elements required by regulatory authorities [European Medicines Agency (EMA)] and the European Rare Disease (ERD) platform. They capture genotype, phenotype, and progression and include demographic data, biomarkers, comorbidity, medication, magnetic resonance imaging (MRI), and longitudinal clinician- or patient-reported ratings of ataxia severity, non-ataxia features, disease stage, activities of daily living, and (mental) health status. Moreover, they are aligned to major autosomal-dominant spinocerebellar ataxia (SCA) and sporadic ataxia (SPORTAX) registries in the field, thus allowing for joint and comparative analyses not only across ARCAs but also with SCAs and sporadic ataxias. The registry is at the core of a systematic multi-component ARCA database cluster with a linked biobank and an evolving study database for digital outcome measures. Currently, the registry contains more than 800 patients with almost 1,500 visits representing all ages and disease stages; 65% of patients with established genetic diagnoses capture all the main ARCA genes, and 35% with unsolved diagnoses are targets for advanced next-generation sequencing. The ARCA Registry serves as the backbone of many major European and transatlantic consortia, such as PREPARE, PROSPAX, and the Ataxia Global Initiative, with additional data input from SPORTAX. It has thus become the largest global trial-readiness registry in the ARCA field

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Peripheral inflammatory immune response differs among sporadic and familial Parkinson’s disease

Peripheral inflammatory immune responses are thought to play a major role in the pathogenesis of Parkinson’s disease (PD). The neutrophil-to-lymphocyte ratio (NLR), a biomarker of systemic inflammation, has been reported to be higher in patients with PD than in healthy controls (HCs). The present study was aimed at determining if the peripheral inflammatory immune response could be influenced by the genetic background of patients with PD. We included a discovery cohort with 222 patients with PD (132 sporadic PD, 44 LRRK2-associated PD (with p.G2019S and p.R1441G variants), and 46 GBA-associated PD), as well as 299 HCs. Demographic and clinical data were recorded. Leukocytes and their subpopulations, and the NLR were measured in peripheral blood. Multivariate lineal regression and post-hoc tests were applied to determine the differences among the groups. Subsequently, a replication study using the Parkinson’s Progression Markers Initiative cohort was performed which included 401 patients with PD (281 sPD patients, 66 LRRK2-PD patients, 54 GBA-PD patients) and a group of 174 HCs. Patients with sporadic PD and GBA-associated PD showed a significantly lower lymphocyte count, a non-significantly higher neutrophil count and a significantly higher NLR than HCs. The peripheral inflammatory immune response of patients with LRRK2-associated PD did not differ from HCs. Our study supports the involvement of a peripheral inflammatory immune response in the pathophysiology of sPD and GBA-associated PD. However, this inflammatory response was not found in LRRK2-associated PD, probably reflecting different pathogenic inflammatory mechanisms

Clinical, genetic and neuropathological characterization of spinocerebellar ataxia type 37.

The autosomal dominant spinocerebellar ataxias (SCAs) consist of a highly heterogeneous group of rare movement disorders characterized by progressive cerebellar ataxia variably associated with ophthalmoplegia, pyramidal and extrapyramidal signs, dementia, pigmentary retinopathy, seizures, lower motor neuron signs, or peripheral neuropathy. Over 41 different SCA subtypes have been described evidencing the high clinical and genetic heterogeneity. We previously reported a novel spinocerebellar ataxia type subtype, SCA37, linked to an 11-Mb genomic region on 1p32, in a large Spanish ataxia pedigree characterized by ataxia and a pure cerebellar syndrome distinctively presenting with early-altered vertical eye movements. Here we demonstrate the segregation of an unstable intronic ATTTC pentanucleotide repeat mutation within the 1p32 5' non-coding regulatory region of the gene encoding the reelin adaptor protein DAB1, implicated in neuronal migration, as the causative genetic defect of the disease in four Spanish SCA37 families. We describe the clinical-genetic correlation and the first SCA37 neuropathological findings caused by dysregulation of cerebellar DAB1 expression. Post-mortem neuropathology of two patients with SCA37 revealed severe loss of Purkinje cells with abundant astrogliosis, empty baskets, occasional axonal spheroids, and hypertrophic fibres by phosphorylated neurofilament immunostaining in the cerebellar cortex. The remaining cerebellar Purkinje neurons showed loss of calbindin immunoreactivity, aberrant dendrite arborization, nuclear pathology including lobulation, irregularity, and hyperchromatism, and multiple ubiquitinated perisomatic granules immunostained for DAB1. A subpopulation of Purkinje cells was found ectopically mispositioned within the cerebellar cortex. No significant neuropathological alterations were identified in other brain regions in agreement with a pure cerebellar syndrome. Importantly, we found that the ATTTC repeat mutation dysregulated DAB1 expression and induced an RNA switch resulting in the upregulation of reelin-DAB1 and PI3K/AKT signalling in the SCA37 cerebellum. This study reveals the unstable ATTTC repeat mutation within the DAB1 gene as the underlying genetic cause and provides evidence of reelin-DAB1 signalling dysregulation in the spinocerebellar ataxia type 37

Perspectives of Implementation of Closed-Loop Deep Brain Stimulation: From Neurological to Psychiatric Disorders.

BACKGROUND Deep brain stimulation (DBS) is a highly efficient, evidence-based therapy to alleviate symptoms and improve quality of life in movement disorders such as Parkinson's disease, essential tremor, and dystonia, which is also being applied in several psychiatric disorders, such as obsessive-compulsive disorder and depression, when they are otherwise resistant to therapy. SUMMARY At present, DBS is clinically applied in the so-called open-loop approach, with fixed stimulation parameters, irrespective of the patients' clinical state(s). This approach ignores the brain states or feedback from the central nervous system or peripheral recordings, thus potentially limiting its efficacy and inducing side effects by stimulation of the targeted networks below or above the therapeutic level. KEY MESSAGES The currently emerging closed-loop (CL) approaches are designed to adapt stimulation parameters to the electrophysiological surrogates of disease symptoms and states. CL-DBS paves the way for adaptive personalized DBS protocols. This review elaborates on the perspectives of the CL technology and discusses its opportunities as well as its potential pitfalls for both clinical and research use in neuropsychiatric disorders