Approved Research

Integration of omics data and imaging features for Multiple Sclerosis towards more precise diagnostic and therapeutic approaches

Lay summary

At first, we will focus on Multiple Sclerosis (MS), which is a chronic inflammatory, demyelinating and degenerative disorder affecting both the brain and the spinal cord. There is a need for the identification of new diagnostic, prognostic and predictive biomarkers, that will enable the faster diagnosis of MS patients, and their classification based on their disease state and progression. This in turn will facilitate the development of more tailored treatment options for each individual that will improve the patients' living conditions. In the sequel, we will repeat the multi-layer integration for comparative analysis for the composite disease profiling on three other neurological diseases (Epilepsy, Alzheimer's and Parkinson's). Therefore, all the available participants with these specific diagnoses and with overlapping measures of imaging data, genetics, metabolomics, other clinical data and risk factors will provide a uniquely powerful opportunity to better understand common and exclusive pathophysiological mechanisms.

This research project aims to develop a computational framework that hosts a pool of multi-level/multi-source data integration methods/tools as well as network-based analytics. This framework will combine brain imaging data, high throughput sequencing data, electronic health record data and rich biological knowledge in order to exploit synergies between them and various complex neurological disorders. More specifically, it is crucial to collect and analyse different modalities from the same patients since we can explore the power of integration of two or more types of data together rather than analysing each data type separately. Therefore, this will result in the formation of an even better profile with better classification, prognosis and diagnosis.

The ability to integrate this multi-source information together is a great challenge yet, it can help understand better the underlying mechanisms of a disease and detect crucial indicators in the entire process.

Currently, great progress has been made in the field of bioinformatics, and together with the great impact of imaging techniques emerging, they can be used together in a multi-omics biological framework as a great tool to delineate the phenotype of a specific disease (radiogenomics).

This research project presents a unique and timely opportunity to combine advancements in computer science to contribute to the vision of Precision Medicine, through a proper integration framework for imaging and molecular data.

The duration of the project will be up to 36 months.