Age-related macular degeneration (AMD) is a major cause of blindness among patients over the age of 55 years worldwide. Angiogenesis plays an important role in neovascular AMD and cancer. Vascular system is a highly branched network lined by endothelial cells (ECs), it supplies tissues with oxygen (O2) and nutrients. During angiogenesis, ECs must increase their metabolic activity to facilitate incorporation of nutrients into biomass. Understanding EC metabolism reveals new perspectives on disease mechanisms in the vascular system and provides new therapeutic approaches for disorders with aberrant vessel growth. Metabolic pathways, such as glycolysis have distinct, essential roles during vessel formation. In adults, most ECs are quiescent for extended periods, however, they rapidly switch to growth upon proangiogenic stimulation. Signaling pathways that control angiogenic switch control EC metabolism, eliciting a metabolic state permissive for growth and proliferation. Interfering with these metabolic adaptions renders ECs less sensitive to angiogenic signals. Another compensatory mechanism to hypoxia is metabolic symbiosis, a process in which cells in the oxygenated region use lactate to produce ATP, which is associated with the activation of glycolytic genes.

In this study, we investigate the association between angiogenesis, metabolic symbiosis and endothelia cell metabolism pathways using protein-protein interaction, gene-gene interaction and text mining approach by bioinformatics tools. By recruiting the markers of angiogenesis, metabolic symbiosis and endothelial cell metabolism in AMD, we designed an intersection network that includes information on how these three biological phenomena are linked.

We selected 92 important genes from multiple signaling pathways. The network of those genes was visualized using the Cytoscape software. In this network, highly interconnected regions (clusters) and hub nodes with the highest degree and betweenness value were identified by using Molecular Complex Detection (MCODE) and jActiveModules respectively.

The results are leading to promising new directions in revealing AMD mechanisms and development of possible new treatments