Research into the molecular causes of Huntington's Disease has delivered a wealth of data. Although these data have the potential to give us many new insights into disease-relevant mechanisms, their immediate interpretation remains challenging. This is especially the case for large amount data that have been generated by high-throughput technologies monitoring the abundance of thousands of genes or proteins simultaneously. In contrast, the relations between these genes or proteins are not or only poorly known. As many phenotypic changes are, however, not simply due to the change of activity of individual genes, but are caused by cohesive alterations in complex molecular networks, the lack of knowledge of the underlying network has severely restricted the ability of researchers to fully utilize the generated data.
Thus, to facilitate researchers' interpretation and utilization of biological data, we will develop a software package for the query and visualization of Huntington's Disease (HD)-related molecular networks. The developed software (HDNetDB) will provide HD researchers an easy but powerful tool for visualisation of molecular networks and identification of potential targets for therapeutic intervention. The advantages for researchers are that i) complex network information is more readily accessible, ii) HD-related molecular processes can be presented in a more comprehensive manner, iii) additional data e.g. from drug screens can immediately placed in the molecular context, and iv) potential causes and effects can more easily distinguished. Notably, we will customize this interface to needs of HD researchers, especially with respect to identification of disease processes and new drug targets.
Additionally, we will perform computational analyses of HD-related molecular mechanisms. Although Huntington's Disease is a classical Mendelian disorder, various processes are involved on the molecular level. The large variability in the pathogenesis of Huntington's Disease strongly indicates that – apart from the disease-causing poly-Q expansion - other modifying factors exist. Such potential modifiers will be elucidated an integrative network-based strategy. A special focus of the computational analyses will be on the Unfolded Protein Response (UPR) and its potential implication in Huntington's Disease.
Ravi Kalathur, Miguel Hernandez-Prieto and Matthias E. Futschik (2012) Huntington´s Disease and its target genes: A global functional profile based on the HD Research Crossroads database, BMC Neurology (abstract, Supplementary Material))
Ravi Kalathur, Kameshwar Ayasolla and Matthias Futschik (2012) The Unfolded Protein Response and its potential role in Huntington's disease; Nature Precedings; dx.doi.org/10.1038/npre.2012.7145.1 (html)Matthias Futschik (2010) Chorea Huntington: A thousand changes due to a single mutation, Contributed Talk, 2nd Meeting of the Institute for Biotechnology and Bioengineering, Universidade do Minho, Braga, Portugal (pdf) Ravi K Kalathur and Matthias.E. Futschik (2010) Network-based analyses of Huntington's disease; Nature Precedings; dx.doi.org/10.1038/npre.2012.7078.1 (html)
Kameshwar Ayasolla, Ravi Kalathur and Matthias Futschik (2010) A systems biology approach towards deciphering the unfolded protein response in Huntington's disease; Nature Precedings; dx.doi.org/10.1038/npre.2012.7078.1 (html)
Kameshwar Ayasolla, Ravi Kalathurand Matthias Futschik (2010) ER stress: an initiator of neuroinflammation in Huntington's disease? J Neurol Neurosurg Psychiatry 81:A5 doi:10.1136/jnnp.2010.222570.16 (abstract)Ravi K Kalathur,Gautam Chaurasia, Erich Wanker and Matthias.E. Futschik (2010) Molecular interaction networks in Huntington´s Disease, SINAL 2010, Faro, Portugal