ELSIE

We are happy to announce that we received a University Utrecht Special Interest Group seeding grant of €5,000 for our proposal entitled ELSIE: EvoLutionary Selection In Epigenetics in collaboration with Daniel Oberski and Alejandro Lopez Rincon.

Executive summary

Chronic inflammation, due to autoimmune diseases, is correlated to Chronic Fatigue Syndrome (CFS), as well as cardiovascular diseases, specifically coronary artery disease (CAD) and ischemic stroke (IS). DNA methylation and gene expression are intrinsically correlated, and we hypothesize that gene regulatory networks overlap between the aforementioned diseases. Taking advantage of publicly available datasets in the Gene Expression Omnibus (GEO) repository and in-house available datasets, we want to find the overlapping DNA methylation sites (CpG sites) and effects in gene expression for different autoimmune diseases, with special attention to CFS, CAD and IS.

Thus, we will make the analysis of several datasets with DNA methylation and gene expression to compare them in relation to CFS, CAD, and IS status. However, the arrays commonly used to measure DNA methylation have a large number of probes (450,000 to 860,000). This creates a very large search space for any algorithm. For this task, we will use a Machine Learning Based Recursive Ensemble Feature Selection. The procedure will try to improve the classification accuracy, using classifiers with distinct topologies.

Finally, from the results we will make a bibliographic and biological pathway analysis to get a better understanding of the underlying mechanisms of the different diseases.