Integrated systems biology approach identifies gene targets for endothelial dysfunction

• Published in: Molecular systems biology 2023-12, Vol.19 (12), p.e11462-n/a
• Main Authors: Pinheiro‐de‐Sousa, Iguaracy, Fonseca‐Alaniz, Miriam Helena, Giudice, Girolamo, Valadão, Iuri Cordeiro, Modestia, Silvestre Massimo, Mattioli, Sarah Viana, Junior, Ricardo Rosa, Zalmas, Lykourgos‐Panagiotis, Fang, Yun, Petsalaki, Evangelia, Krieger, José Eduardo
• Format: Article
• Language: English
• Subjects: Angiogenesis; Biology; Data integration; Drug development; drug targets; endothelial dysfunction; Endothelium; Epigenetics; Gene expression; Gene silencing; Genes; Genetic screening; Genomes; Hypoxia; Inflammation; Molecular modelling; Monocyte chemoattractant protein 1; Network analysis; Oxidative stress; Phenotypes; Principal components analysis; Risk factors; RNA, Small Interfering; Shear stress; siRNA; Systems Biology; Target recognition; Therapeutic targets; Transcription factors
• ISSN: 1744-4292; 1744-4292
• DOI: 10.15252/msb.202211462

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. Synopsis Multi‐omics data integration, genetic and pharmacological perturbations, and network analysis on endothelial cells are combined to identify endothelial dysfunction network signatures and prioritise candidate therapeutic targets. Multi‐omics data integration of endothelial cells treated with mimics of major cardiovascular disease factors identified 81 putative endothelial dysfunction (ED) genes. Upon siRNA‐mediated gene knockdown, 83% of ED gene candidates affected at least one ED phenotype (26 exacerbating and 31 ameliorating the ED phenotypes). The analyses reveal emergent properties of disease networks, distinguishing between adaptation and rewiring for survival and those associated with deregulation that can be targeted for ED treatment. An orthogonal drug screen on treated endothelial cells provided additional support for DUSP1, IL6 and CCL2 as putative targets for ED. Multi‐omics data integration, genetic and pharmacological perturbations, and network analysis on endothelial cells are combined to identify endothelial dysfunction network signatures and prioritise candidate therapeutic targets.