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Review
. 2018;8(s1):S25-S30.
doi: 10.3233/JPD-181505.

MDSGene: Closing Data Gaps in Genotype-Phenotype Correlations of Monogenic Parkinson's Disease

Christine Klein  1 , Nobutaka Hattori  2 , Connie Marras  3
Affiliations
Review

MDSGene: Closing Data Gaps in Genotype-Phenotype Correlations of Monogenic Parkinson's Disease

Christine Klein et al. J Parkinsons Dis. 2018.

Abstract

Given the rapidly increasing number of reported movement disorder genes and clinical-genetic desciptions of mutation carriers, the International Parkinson's Disease and Movement Disorder Society Gene Database (MDSGene) initiative has been launched in 2016 and grown to become a large international project (http://www.mdsgene.org). MDSGene currently contains >1150 variants described in ∼5700 movement disorder patients in almost 1000 publications including monogenic forms of PD clinically resembling idiopathic (PARK-PINK1, PARK-Parkin, PARK-DJ-1, PARK-SNCA, PARK-VPS35, PARK-LRRK2), as well as of atypical PD (PARK-SYNJ1, PARK-DNAJC6, PARK-ATP13A2, PARK-FBXO7). Inclusion of genes is based on standardized published criteria for determining causation. Clinical and genetic information can be filtered according to demographic, clinical or genetic criteria and summary statistics are automatically generated by the MDSGene online tool. Despite MDSGene's novel approach and features, it also faces several challenges: i) The criteria for designating genes as causative will require further refinement, as well as time and support to replace the faulty list of 'PARKs'. ii) MDSGene has uncovered extensive clinical data gaps. iii) The quickly growing body of clinical and genetic data require a large number of experts worldwide posing logistic challenges. iv) MDSGene currently captures published data only, i.e., a small fraction of the available information on monogenic PD available. Thus, an important future aim is to extend MDSGene to unpublished cases in order to provide the broad data base to the PD community that is necessary to comprehensively inform genetic counseling, therapeutic approaches and clinical trials, as well as basic and clinical research studies in monogenic PD.

Keywords: MDSGene; Parkinson’s disease; data gaps; database; genotype-phenotyp correlation.

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Figures

Fig.1
Fig.1
Output file of the summary statistics tool of the MDSGene database using PARK-LRRK2 as an example. The following analyses are generated: frequency of clinical features (red bars – symptom or sign is present; blue bars – symptom or sign is absent; gray bars – no information available), age-at-onset distribution, information on initial signs and symptoms, levodopa response, frequency of mutations, and ethnic background as well as country of origin.
See this image and copyright information in PMC

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