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Integrated systems biology approach identifies gene targets for endothelial dysfunction

Authors: Iguaracy Pinheiro‐de‐Sousa; Miriam Helena Fonseca‐Alaniz; Girolamo Giudice; Iuri Cordeiro Valadão; Silvestre Massimo Modestia; Sarah Viana Mattioli; Ricardo Rosa Junior; +4 Authors

Integrated systems biology approach identifies gene targets for endothelial dysfunction

Abstract

Abstract Endothelial dysfunction (ED) is critical in the development and progression of cardiovascular (CV) disorders, yet effective therapeutic targets for ED remain elusive due to limited understanding of its underlying molecular mechanisms. To address this gap, we employed a systems biology approach to identify potential targets for ED. Our study combined multi omics data integration, with siRNA screening, high content imaging and network analysis to prioritise key ED genes and identify a pro‐ and anti‐ED network. We found 26 genes that, upon silencing, exacerbated the ED phenotypes tested, and network propagation identified a pro‐ED network enriched in functions associated with inflammatory responses. Conversely, 31 genes ameliorated ED phenotypes, pointing to potential ED targets, and the respective anti‐ED network was enriched in hypoxia, angiogenesis and cancer‐related processes. An independent screen with 17 drugs found general agreement with the trends from our siRNA screen and further highlighted DUSP1 , IL6 and CCL2 as potential candidates for targeting ED. Overall, our results demonstrate the potential of integrated system biology approaches in discovering disease‐specific candidate drug targets for endothelial dysfunction.

Keywords

Medicine (General), QH301-705.5, Systems Biology, network, RWR, ED diffusion, propagation, systems biology, Articles, endothelial dysfunction, R5-920, drug targets, Biology (General), RNA, Small Interfering, data integration, network analysis

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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