Distinct Stress Response and Altered Striatal Transcriptome in Alpha-Synuclein Overexpressing Mice

Parkinson’s disease (PD) is a progressive neurodegenerative disorder with motor symptoms and a plethora of non-motor and neuropsychiatric features that accompany the disease from prodromal to advanced stages. While several genetic defects have been identified in familial forms of PD, the predominance of cases are sporadic and result from a complex interplay of genetic and non-genetic factors. Clinical evidence, moreover, indicates a role of environmental stress in PD, supported by analogies between stress-induced pathological consequences and neuronal deterioration observed in PD. From this perspective, we set out to investigate the effects of chronic stress exposure in the context of PD by using a genetic mouse model that overexpresses human wildtype SNCA. Mimicking chronic stress was achieved by adapting a chronic unpredictable mild stress protocol (CUMS) comprising eight different stressors that were applied randomly over a period of eight weeks starting at an age of four months. A distinctive stress response with an impact on anxiety-related behavior was observed upon SNCA overexpression and CUMS exposure. SNCA-overexpressing mice showed prolonged elevation of cortisol metabolites during CUMS exposure, altered anxiety-related traits, and declined motor skills surfacing with advanced age. To relate our phenotypic observations to molecular events, we profiled the striatal and hippocampal transcriptome and used a 2 × 2 factorial design opposing genotype and environment to determine differentially expressed genes. Disturbed striatal gene expression and minor hippocampal gene expression changes were observed in SNCA-overexpressing mice at six months of age. Irrespective of the CUMS-exposure, genes attributed to the terms neuroinflammation, Parkinson’s signaling, and plasticity of synapses were altered in the striatum of SNCA-overexpressing mice

Impaired dopamine- and adenosine-mediated signaling and plasticity in a novel rodent model for DYT25 dystonia

Abstract Dystonia is a neurological movement disorder characterized by sustained or intermittent involuntary muscle contractions. Loss-of-function mutations in the GNAL gene have been identified to be the cause of "isolated" dystonia DYT25. The GNAL gene encodes for the guanine nucleotide-binding protein G(olf) subunit alpha (Gαolf), which is mainly expressed in the olfactory bulb and the striatum and functions as a modulator during neurotransmission coupling with D1R and A2AR. Previously, heterozygous Gαolf -deficient mice (Gnal+/−) have been generated and showed a mild phenotype at basal condition. In contrast, homozygous deletion of Gnal in mice (Gnal−/−) resulted in a significantly reduced survival rate. In this study, using the CRISPR-Cas9 system we generated and characterized heterozygous Gnal knockout rats (Gnal+/−) with a 13 base pair deletion in the first exon of the rat Gnal splicing variant 2, a major isoform in both human and rat striatum. Gnal+/− rats showed early-onset phenotypes associated with impaired dopamine transmission, including reduction in locomotor activity, deficits in rotarod performance and an abnormal motor skill learning ability. At cellular and molecular level, we found down-regulated Arc expression, increased cell surface distribution of AMPA receptors, and the loss of D2R-dependent corticostriatal long-term depression (LTD) in Gnal+/− rats. Based on the evidence that D2R activity is normally inhibited by adenosine A2ARs, co-localized on the same population of striatal neurons, we show that blockade of A2ARs restores physiological LTD. This animal model may be a valuable tool for investigating Gαolf function and finding a suitable treatment for dystonia associated with deficient dopamine transmission

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient\u27s data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together \u3e300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of \u3e19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Solving unsolved rare neurological diseases-a Solve-RD viewpoint.

Funder: Durch Princess Beatrix Muscle Fund Durch Speeren voor Spieren Muscle FundFunder: University of Tübingen Medical Faculty PATE programFunder: European Reference Network for Rare Neurological Diseases | 739510Funder: European Joint Program on Rare Diseases (EJP-RD COFUND-EJP) | 44140962

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Distinct impacts of alpha-synuclein overexpression on the hippocampal epigenome of mice in standard and enriched environments

Elevated alpha-synuclein (SNCA) gene expression is associated with transcriptional deregulation and increased risk of Parkinson's disease, which may be partially ameliorated by environmental enrichment. At the molecular level, there is emerging evidence that excess alpha-synuclein protein (aSyn) impacts the epigenome through direct and/or indirect mechanisms. However, the extents to which the effects of both aSyn and the environment converge at the epigenome and whether epigenetic alterations underpin the preventive effects of environmental factors on transcription remain to be elucidated. Here, we profiled five DNA and histone modifications in the hippocampus of wild-type and transgenic mice overexpressing human SNCA. Mice of each genotype were housed under either standard conditions or in an enriched environment (EE) for 12 months. SNCA overexpression induced hippocampal CpG hydroxymethylation and histone H3K27 acetylation changes that associated with genotype more than environment. Excess aSyn was also associated with genotype- and environment-dependent changes in non-CpG (CpH) DNA methylation and H3K4 methylation. These H3K4 methylation changes included loci where the EE ameliorated the impacts of the transgene as well as loci resistant to the effects of environmental enrichment in transgenic mice. In addition, select H3K4 monomethylation alterations were associated with changes in mRNA expression. Our results suggested an environment-dependent impact of excess aSyn on some functionally relevant parts of the epigenome, and will ultimately enhance our understanding of the molecular etiology of Parkinson's disease and other synucleinopathies