Abstract
Objective: Establish a web resource summarizing literature-based genetic information on levodopa-induced dyskinesia in an easily accessible and consistent way.
Background: Levodopa induced dyskinesia (LID) is a very disabling side effect of therapy in patients with Parkinson’s disease (PD). LID can appear either very early or later in the disease history following initiation of levodopa therapy, and this inter-individual heterogeneity can be partly explained by genetic predisposition. To date, only few publications have investigated the potential genetic predisposition and no central resource is available online to guide the planning of genetic studies.
Methods: An extensive literature search was performed in MEDLINE. Data regarding authors, sample size, age at PD onset, race and type of dyskinesia were extracted from the relevant publications. Genetic variations and the associated genes were annotated with their dbSNP and HGNC identifiers. An online resource was developed to present those curated LID data.
Results: The core of the web resource, thirty-two genes and associated variations, is presented in a textual and tabular form. A complementary visualization of the genes in an integrated dyskinesia network was generated by combining associations from protein-protein interactions, metabolic and signaling pathways, and functional annotations. This network model captures the different types of relationships between these relevant genes or their respective gene products, and helps identify potential functional modules. Furthermore, users can upload their own lists of genetic variants or genes for analysis. In addition to incorporating the user-defined genes into the aforementioned LID network, the genes with the strongest associations to known LID genes can be identified by means of disease gene prioritization. All the results and the curated data are freely available for download.
Conclusions: We present the first online resource summarizing published variants and genes related to LID. The resource allows researchers and clinicians to easily retrieve information on LID genetics and verify whether certain mutations or genes of interest have been previously identified or linked to LID. In addition, it provides information on the functional context of those variants and the associated genes. These data may also help to further the understanding of molecular mechanisms that underlie LID.