MDSGene and the Global Parkinson’s Genetics Program (GP2): Towards a comprehensive resource for genetic movement disorders 

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The landscape of genetic movement disorders is rapidly changing thanks to international collaboration, advances in sequencing, and an expanding spectrum of disease-associated genes. Yet, as clinicians and researchers are acutely aware, extracting actionable insights from thousands of disparate case reports and studies remains a major hurdle. Addressing this need, the International Parkinson and Movement Disorder Society’s (MDS) genetic database MDSGene provides high-quality, standardized curation of demographic, phenotypic, and genotypic information on patients with inherited movement disorders, while global genotyping efforts such as the Global Parkinson’s Genetics Program (GP2) vastly expand genetic discovery and data accessibility. 

What Is MDSGene? 

MDSGene is an open-access database, based on an international initiative, launched in 2016, designed to systematically collect and catalog demographic, clinical, and genetic data on patients with confirmed monogenic forms of movement disorders, including Parkinson’s disease, dystonia, ataxia, and related conditions. By employing rigorous curation and data harmonization protocols, currently using data from peer-reviewed publications in the English language, MDSGene bridges the gap between burgeoning genetic data and the nuanced, often incomplete clinical descriptions found in the literature, and clinicians and researchers seeking to gain insights from it. As of September 2025, MDSGene contains data on more than 20,000 movement disorder patients, capturing several thousand genetic variants sourced from more than 2,000 relevant publications.  

Database features include:

Comprehensive filtering by demographic data (e.g., sex, ethnicity), clinical signs and symptoms, or genetic variant. Pathogenicity scoring based on variant frequency in large population databases, co-segregation, in silico predictions, and published functional evidence.  Summary statistics and visualization through auto-generated frequency charts, age-at-onset distributions, and phenotypic summaries, along with mutation maps. Lists of relevant publications with hyperlinks to PubMed

Despite its breadth, gaps due to publication bias remain, particularly regarding nonmotor symptoms and data from non-European populations. 

MDSGene’s latest additions 

Three major updates include:

The PARK-LRRK2 entry now features detailed, variant-level data from more than 3,300 Parkinson’s disease patients with more than 200 potentially pathogenic variants, along with updated pathogenicity scoring, functional annotations from LRRK2´s kinase activity, and phenotype correlations. GBA1, recognized as an important risk factor for Parkinson’s disease, has been added to MDSGene, covering approximately 28,000 patients carrying GBA1 variants from more than 1000 publications with around 800 variants, including more than 13,000 patients with PD or other forms of parkinsonism. The Global Genetic Ataxia Resource reflects an expansion of the initial MDSGene database. It aggregates epidemiological, genotypic, and clinical testing information on about 550 genetically defined ataxias across more than 100 countries.

Strategic partnership with the Global Parkinson’s Genetics Program (GP2) 

MDS and GP2 have entered a strategic partnership of standardized data collection using MDS rating scales, genetic testing recommendations, and training. The GP2 initiative represents a paradigm shift in the genetics of Parkinson’s disease research, prioritizing scale, diversity, and accessibility. With a goal of collecting and analyzing data from 250,000 participants worldwide, GP2 is inclusive of populations historically underrepresented in genetic studies — spanning Africa, Asia, Latin America, and beyond. 

MDSGene’s road ahead 

The future of genetic movement disorder research depends on broad, international cooperation and practical strategies for managing large datasets. GP2 is pioneering this field and promoting open access to data. Increasingly, valuable genetic and clinical information comes not only from peer-reviewed publications but also from clinical trials with genetically characterized patients, industry sequencing projects, public biobanks, and routine clinical registries. Effectively using these complex and varied data sources will require systematic integration and the use of artificial intelligence (AI), which can help identify meaningful associations faster and more reliably than traditional methods. Looking further ahead, coordinated global initiatives, similar to GP2, should be extended to other inherited movement disorders, including dystonia and ataxia. 

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