About his PhD project

Mendelian diseases show discrete phenotypes triggered usually by monogenic mutations, whereas common diseases show continuous phenotypes, which depend on numerous weak polygenic variations. However, Mendelian and common diseases share both molecular and phenotypic features, leading to comorbidity relationships [1]. For instance, mutations in the transcription factor (TF) GATA5 cause congenital heart defects (CHD), and SNPs variations around the same gene are involved in hypertension [2]. Hypertension is also a classical complication of CHD. We propose here to study these relationships between Mendelian and common diseases, but from a biological interaction network point of view. To this goal, we will map disease features (e.g., SNP variations, mutations, phenotypes) features to networks containing interactions between diseases, between genes/proteins but also interactions with non-coding genomic regions, and develop innovative algorithms to extract comorbidity subnetworks from these multiplex multipartite networks.