Huntington’s disease (HD) is very complex, and one of the only simple aspects of it is that, in most cases, it is passed down genetically. The idea behind the Huntington’s Disease Network DataBase (HDNetDB) is that it will potentially reduce the complexity by allowing scientists to freely share data.
Per data published in Scientific Reports
, the network is effective and helpful in discovering drug targets that could potentially prevent the neuronal cell death observed in the progressive and fatal neurodegenerative disease.
Primary symptoms in HD include Chorea, or involuntary, random and sudden, twisting and/or writhing movements. Additionally, patients experience an array of cognitive and mental health obstacles. Impaired nerve cells in patients can result in the deterioration of several areas of the brain.
“Huntington’s disease is especially devastating for affected families, since we can nowadays exactly predict who will be affected later in life, but we cannot yet provide any cure,” Matthias Futschik, the project’s leader and professor in Bioinformatics at the University’s School of Biomedical and Healthcare Sciences, said.
“In HDNetDB we have developed a computational tool which allows scientists free and open access, helping them to identify new molecular targets for the development of new drug strategies for the disease. We believe that our approach can be applied to other neurodegenerative disorders such as Alzheimer’s and Parkinson’s disease.”
The database was created with the hopes of assisting researchers in the ongoing detection and understanding of disease mechanisms, and eventually categorizing novel drug targets for HD. The helpful platform incorporates several levels of data ranging from protein-protein interactions, regulatory interactions (microRNA-target gene and transcription factor-target gene), and gene expression to drug-target information about gene, gene ontology and pathway information to phenotype data pertaining to HD.
According to researchers, HDNetDB will allow for users to obtain, envision and prioritize molecular interaction networks using HD-related gene expression and other types of data acquired from human samples and other sources.
To illustrate how the network can help, a report in Nature
by Kalathur and colleagues used it to find a link between HD and the unfolded protein response that could lead to a possible treatment solution using existing drugs.
Aside from serving as a central resource for cohesive data and information, HDNetDB also provides users with numerous querying and visualization options for HD-related networks. HDNetDB is easily accessible at no cost at http://hdnetdb.sysbiolab.eu
. The site requires no login.
For more on HDNetDB and other HD research efforts, follow Rare Disease Report