More and more scientists are convinced that to conquer a prediction and an efficient and comprehensive diagnosis of a disease, a more integrative approach is needed in which all contextual factors are taken into account. The participating teams are already in a great deal working within this new paradigm. The aim of the proposed interdisciplinary network is to combine their efforts to study persons with inherited genetic diseases in a multi- perspective way, including clinical-physiological, genomic, psycho-social and environmental factors.
The ultimate goal of the aforementioned research proposal is to enable researchers for analyzing and predicting complex inherited (and later on acquired) genetic diseases in a multi-dimensional data integrative platform. COMO-AI lab along with CMG, VUB-UZ Brussel have already developed a platform (in the Innoviris supported BridgeIRIS project) for storage and analysis of patients' genomic and clinical/phenotypic data for a cardiac arrhythmia, namely the Brugada syndrome [Sengupta et al., 2015]. The monogenic nature of this syndrome with incomplete genetic penetrance and various expression has been questioned, and more support has recently been gained for the hypothesis of a complex, oligo- over polygenic inheritance to even a multifactorial disease [Bezzina et al. 2013; Béziau et al. 2014]. Therefore, the Brugada syndrome will be an ideal model to accomplish the general aims of this project. The focus shall be laid on this inherited complex, multifactorial syndrome, since not only genetic susceptibility, but also clinical-physiological, psycho-social and environmental factors might influence the development of disease as well as the appropriate treatment. This aim will be envisioned by further enrichment of the platform towards these physiological, psycho-social and environmental dimensions. We also aim to enrich the platform with information discovery feature based on ensemble approaches (black box + white box) to analyse the multi-dimensional data and build a predictive model.
The flexible architecture of the CliniPhenome database will allow easy expansion of the platform in the future towards other inherited and acquired genetic disease information and implementation of such integrative research aiming at a personalized medical approach, for i.e. cancer patients.