ArticleBMC medical genomics2017
Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis.
Article in BMC medical genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 24 citations in OpenAlex.
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- A Multi-Objective Approach for Drug Repurposing in Preeclampsia.Molecules (Basel, Switzerland) · 2021Article
- Distinct placental molecular processes associated with early-onset and late-onset preeclampsia.Theranostics · 2021Article
- Collagen I Induces Preeclampsia-Like Symptoms by Suppressing Proliferation and Invasion of Trophoblasts.Frontiers in endocrinology · 2021Article
- Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks.Scientific reports · 2020Article
- OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine.Scientific reports · 2020Article
- Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis.International journal of molecular sciences · 2020Article
- Comprehensive Analysis of Differently Expressed and Methylated Genes in Preeclampsia.Computational and mathematical methods in medicine · 2020Article
- Overexpression of Collapsin Response Mediator Protein 1 Inhibits Human Trophoblast Cells Proliferation, Migration, and Invasion.Reproductive sciences (Thousand Oaks, Calif.) · 2019Article
- NFBTA: A Potent Cytotoxic Agent against Glioblastoma.Molecules (Basel, Switzerland) · 2019Article
- Analysis of organizational power networks through a holistic approach using consensus strategies.Heliyon · 2019Article
- Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis.Scientific reports · 2018Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPreeclampsia is a multifactorial disease with unknown pathogenesis. Even when recent studies explored this disease using several bioinformatics tools, the main objective was not directed to pathogenesis. Additionally, consensus prioritization was proved to be highly efficient in the recognition of genes-disease association. However, not information is available about the consensus ability to early recognize genes directly involved in pathogenesis. Therefore our aim in this study is to apply several theoretical approaches to explore preeclampsia; specifically those genes directly involved in the pathogenesis.
methodsWe firstly evaluated the consensus between 12 prioritization strategies to early recognize pathogenic genes related to preeclampsia. A communality analysis in the protein-protein interaction network of previously selected genes was done including further enrichment analysis. The enrichment analysis includes metabolic pathways as well as gene ontology. Microarray data was also collected and used in order to confirm our results or as a strategy to weight the previously enriched pathways.
resultsThe consensus prioritized gene list was rationally filtered to 476 genes using several criteria. The communality analysis showed an enrichment of communities connected with VEGF-signaling pathway. This pathway is also enriched considering the microarray data. Our result point to VEGF, FLT1 and KDR as relevant pathogenic genes, as well as those connected with NO metabolism.
conclusionOur results revealed that consensus strategy improve the detection and initial enrichment of pathogenic genes, at least in preeclampsia condition. Moreover the combination of the first percent of the prioritized genes with protein-protein interaction network followed by communality analysis reduces the gene space. This approach actually identifies well known genes related with pathogenesis. However, genes like HSP90, PAK2, CD247 and others included in the first 1% of the prioritized list need to be further explored in preeclampsia pathogenesis through experimental approaches.
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