Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis

Background: Angiogenesis is regulated by multiple genes whose variants can lead to different disorders. Among them, rare diseases are a heterogeneous group of pathologies, most of them genetic, whose information may be of interest to determine the still unknown genetic and molecular causes of other diseases. In this work, we use the information on rare diseases dependent on angiogenesis to investigate the genes that are associated with this biological process and to determine if there are interactions between the genes involved in its deregulation. Results: We propose a systemic approach supported by the use of pathological phenotypes to group diseases by semantic similarity. We grouped 158 angiogenesis-related rare diseases in 18 clusters based on their phenotypes. Of them, 16 clusters had traceable gene connections in a high-quality interaction network. These disease clusters are associated with 130 different genes. We searched for genes associated with angiogenesis througth ClinVar pathogenic variants. Of the seven retrieved genes, our system confirms six of them. Furthermore, it allowed us to identify common affected functions among these disease clusters.

Automated summary

This study investigates the genes associated with angiogenesis and their interactions using information from rare diseases. By analyzing pathological phenotypes, the study identifies 18 clusters of angiogenesis-related diseases, with 16 of them having traceable gene connections in an interaction network. A total of 130 different genes are associated with these disease clusters, and six of them are confirmed to be involved in angiogenesis.