Integrative Data Semantics for Neurodegenerative research
Neurodegenerative disorders such as Alzheimer's disease are among the greatest societal challenges facing developed societies; the total global cost of these diseases in 2015 was more than $800 billion, or about 1% of global economic output [1]. In Germany, the number of dementia patients is expected to double by 2050. In response to this challenge, researchers from the Fraunhofer Institute SCAI, the German Center for Neurodegenerative Diseases (DZNE)and the University Hospital Bonn (UKB). are collaborating to support the development of new preventive and therapeutic strategies.
The main goal of the Integrative Data Semantics in Neurodegeneration Research (IDSN) project is the development of 'integrative data semantics' to support application-oriented systems biology for translational neurodegenerative disease research. One of the outstanding requirements is to link primary data from different model systems and technology platforms with secondary data from public databases and publications. For this purpose, semantic layers are developed in IDSN that provide interpreted data from the different systems. Furthermore, it is quite important to also focus on the integration of clinical routine data that is generated in our clinics daily. Therefore, an information extraction platform is being built at the University Hospital Bonn (UKB) to structure patient data in the field of neurodegeneration.
The resulting IDSN integration platform allows researchers from UKB and DZNE to analyze these heterogeneous datasets together to improve early detection of neurodegeneration, better stratify patients, identify prognostic factors, and contribute to the development of new therapies.
In these approaches, data protection has the highest priority. Data will only be analyzed anonymized or, if a patient consent is available, pseudonymized. Platform components are available as web services, or as software packages. Data analysis results achieved in IDSN are published. The data integrated within the IDSN platform is partly published as well but especially clinical routine data, even anonymized, cannot be shared.