Author Correction: The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson’s disease data

Correction to: npj Parkinson’s Disease https://doi.org/10.1038/s41531-023-00472-6, published online 04 March 2023// In this article the affiliation details for Alastair J Noyce, Jonggeol Jeff Kim, Isabelle Francesca Foote, Sumit Dey were incorrectly given as ‘Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, New York, NY 10029, USA,’ but should have been ‘Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK’.// The affiliation details for Prabhjyot Saini were incorrectly given as ‘Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK’ but should have been ‘The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada’. The original article has been corrected

Genome-wide association study of REM sleep behavior disorder identifies polygenic risk and brain expression effects

Rapid-eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies and defines a more severe subtype. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we perform a genome-wide association study of RBD, identifying five RBD risk loci near SNCA, GBA, TMEM175, INPP5F, and SCARB2. Expression analyses highlight SNCA-AS1 and potentially SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Polygenic risk score, pathway analysis, and genetic correlations provide further insights into RBD genetics, highlighting RBD as a unique alpha-synucleinopathy subpopulation that will allow future early intervention

The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson’s disease data

Open science and collaboration are necessary to facilitate the advancement of Parkinson's disease (PD) research. Hackathons are collaborative events that bring together people with different skill sets and backgrounds to generate resources and creative solutions to problems. These events can be used as training and networking opportunities, thus we coordinated a virtual 3-day hackathon event, during which 49 early-career scientists from 12 countries built tools and pipelines with a focus on PD. Resources were created with the goal of helping scientists accelerate their own research by having access to the necessary code and tools. Each team was allocated one of nine different projects, each with a different goal. These included developing post-genome-wide association studies (GWAS) analysis pipelines, downstream analysis of genetic variation pipelines, and various visualization tools. Hackathons are a valuable approach to inspire creative thinking, supplement training in data science, and foster collaborative scientific relationships, which are foundational practices for early-career researchers. The resources generated can be used to accelerate research on the genetics of PD

Genome-wide association study of {REM} sleep behavior disorder identifies polygenic risk and brain expression effects

AbstractRapid-eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies and defines a more severe subtype. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we perform a genome-wide association study of RBD, identifying five RBD risk loci near SNCA, GBA, TMEM175, INPP5F, and SCARB2. Expression analyses highlight SNCA-AS1 and potentially SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Polygenic risk score, pathway analysis, and genetic correlations provide further insights into RBD genetics, highlighting RBD as a unique alpha-synucleinopathy subpopulation that will allow future early intervention

The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson's disease data

Open science and collaboration are necessary to facilitate the advancement of Parkinson's disease (PD) research. Hackathons are collaborative events that bring together people with different skill sets and backgrounds to generate resources and creative solutions to problems. These events can be used as training and networking opportunities, thus we coordinated a virtual 3-day hackathon event, during which 49 early-career scientists from 12 countries built tools and pipelines with a focus on PD. Resources were created with the goal of helping scientists accelerate their own research by having access to the necessary code and tools. Each team was allocated one of nine different projects, each with a different goal. These included developing post-genome-wide association studies (GWAS) analysis pipelines, downstream analysis of genetic variation pipelines, and various visualization tools. Hackathons are a valuable approach to inspire creative thinking, supplement training in data science, and foster collaborative scientific relationships, which are foundational practices for early-career researchers. The resources generated can be used to accelerate research on the genetics of PD.This project was supported by the Global Parkinson’s Genetics Program (GP2). GP2 is funded by the Aligning Science Against Parkinson’s (ASAP) initiative and implemented by The Michael J. Fox Foundation for Parkinson’s Research (https://gp2.org).Open Access funding provided by the National Institutes of Health (NIH).This research was supported in part by the Intramural Research Program of the NIH, National Institute on Aging (NIA), National Institutes of Health, Department of Health and Human Services; project numbers ZO1 AG000535 and ZO1 AG000949, as well as the National Institute of Neurological Disorders and StrokePeer reviewe

Multi-ancestry genome-wide association meta-analysis of Parkinson?s disease

Although over 90 independent risk variants have been identified for Parkinson’s disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson’s disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations

Genome-wide association study of REM sleep behavior disorder identifies polygenic risk and brain expression effects

Rapid-eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies and defines a more severe subtype. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we perform a genome-wide association study of RBD, identifying five RBD risk loci near SNCA, GBA, TMEM175, INPP5F, and SCARB2. Expression analyses highlight SNCA-AS1 and potentially SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Polygenic risk score, pathway analysis, and genetic correlations provide further insights into RBD genetics, highlighting RBD as a unique alpha-synucleinopathy subpopulation that will allow future early intervention

Glutathione S-transferase alpha 4 prevents dopamine neurodegeneration in a rat alpha-synuclein model of Parkinson's disease

Parkinson's disease (PD) is a common, progressive neurodegenerative disease, which typically presents itself with a range of motor symptoms, like resting tremor, bradykinesia, and rigidity, but also non-motor symptoms such as fatigue, constipation, and sleep disturbance. Neuropathologically, PD is characterized by loss of dopaminergic cells in the substantia nigra pars compacta (SNpc) and Lewy bodies, neuronal inclusions containing a-synuclein (a-syn). Mutations and copy number variations of SNCA, the gene encoding a-syn, are linked to familial PD and common SNCA gene variants are associated to idiopathic PD. Large-scale genome-wide association studies have identified risk variants across another 40 loci associated to idiopathic PD. These risk variants do not, however, explain all the genetic contribution to idiopathic PD. The rat Vra1 locus has been linked to neuroprotection after nerve- and brain injury in rats. Vra1 includes the glutathione S-transferase alpha 4 (Gsta4) gene, which encodes a protein involved in clearing lipid peroxidation by-products. The DA.VRA1 congenic rat strain, carrying PVG alleles in Vra1 on a DA strain background, was recently reported to express higher levels of Gsta4 transcripts and to display partial neuroprotection of SNpc dopaminergic neurons in a 6-hydroxydopamine (6-OHDA) induced model for PD. Since a-syn expression increases the risk for PD in a dose-dependent manner, we assessed the neuroprotective effects of Vra1 in an a-syn-induced PD model. Human wild-type a-syn was overexpressed by unilateral injections of the rAAV6-a-syn vector in the SNpc of DA and DA.VRA1 congenic rats. Gsta4 gene expression levels were significantly higher in the striatum and midbrain of DA.VRA1 compared to DA rats at 3 weeks post surgery, in both the ipsilateral and contralateral sides. At 8 weeks post surgery, DA.VRA1 rats suffered significantly lower fiber loss in the striatum and lower loss of dopaminergic neurons in the SNpc compared to DA. Immunofluorescent stainings showed co-expression of Gsta4 with Gfap at 8 weeks suggesting that astrocytic expression of Gsta4 underlies Vra1-mediated neuroprotection to a-syn induced pathology. This is the second PD model in which Vra1 is linked to protection of the nigrostriatal pathway, solidifying Gsta4 as a potential therapeutic target in PD

Insights on Genetic and Environmental Factors in Parkinson's Disease from a Regional Swedish Case-Control Cohort

BACKGROUND: Risk factors for Parkinson's disease (PD) can be more or less relevant to a population due to population-specific genetic architecture, local lifestyle habits, and environmental exposures. Therefore, it is essential to study PD at a local, regional, and continental scale in order to increase the knowledge on disease etiology.OBJECTIVE: We aimed to investigate the contribution of genetic and environmental factors to PD in a new Swedish case-control cohort.METHODS: PD patients (n = 929) and matched population-based controls (n = 935) from the southernmost county in Sweden were included in the cohort. Information on environmental exposures was obtained using questionnaires at inclusion. Genetic analyses included a genome-wide association study (GWAS), haplotype assessment, and a risk profile analysis using cumulative genetic risk scores.RESULTS: The cohort is a representative PD case-control cohort (64% men, mean age at diagnosis = 67 years, median Hoehn and Yahr score 2.0), in which previously reported associations between PD and environmental factors, such as tobacco, could be confirmed. We describe the first GWAS of PD solely composed of PD patients from Sweden, and confirm associations to well-established risk alleles in SNCA. In addition, we nominate an unconfirmed and potentially population-specific genome-wide significant association in the PLPP4 locus (rs12771445).CONCLUSION: This work provides an in-depth description of a new PD case-control cohort from southern Sweden, giving insights into environmental and genetic risk factors for PD in the Swedish population