Pillar 4: Cross-omics (COMICS)

In the first three projects (Neuron-Glia, PSYNA, and Brain Barriers), we investigate our research questions in different models (cell cultures, animal models, human tissue), on different levels (genes, proteins, cells), and in different materials (brain tissue, cerebrospinal fluid, blood plasma). This is great, as this generates tremendous amounts of data in different disciplines, but it also misses overlap in the type of data. As a result, data will stay "separated", as different parameters are being measured, although it is one of our greatest ambitions within MODEM to integrate all the knowledge we have and generate. Combining and integrating all of this data is a grand task, but these kinds of analyses can teach us a lot about new associations between the disease progression, new biomarkers or targets, and more. In these large scale data analyses, we can combine all of the data we have and see if there are any associations between the different levels, materials, and models. We call this "omics" (i.e. "genomics", "proteomics", "lipidomics"), and they contain so much information that we could not have gathered from researching it in the lab, as the data we will have is enormous. In data science, or bioinformatics, we can ask ourselves questions such as:

How are genetic risks and protective factors associated with the beginning of the disease in AD and FTD?

To what extent do proteomics in different levels, modeks, and materials show distinct moleculra processes in AD and FTD?

As these questions can be rather complex and hard to interprete, it will be even more interesting and valuable that we tackle these kind of questions to the very best of our abilities.

Who are involved?

This project is led by prof. Pieter Jelle Visser (AUMC) and dr. Betty Tijms (AUMC), as they work together with prof. Guus Smit (VU), dr. Jeroen van Rooij (Erasmus MC), dr. Harro Seelaar (Erasmus MC), and prof. Mohsen Ghanbari (Erasmus MC). Together, they will supervise PhD students, postdocs, and other (non-)scientific staff.