ArticleScientific reports2016
Uncovering disease mechanisms through network biology in the era of Next Generation Sequencing.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 37 citations in OpenAlex.
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- Gene Set Enrichment Analysis of Interaction Networks Weighted by Node Centrality.Frontiers in genetics · 2021Article
- Centrality Analysis of Protein-Protein Interaction Networks and Molecular Docking Prioritize Potential Drug-Targets in Type 1 Diabetes.Iranian journal of pharmaceutical research : IJPR · 2020Article
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- Integrating molecular networks with genetic variant interpretation for precision medicine.Wiley interdisciplinary reviews. Systems biology and medicine · 2019Review
- Network Medicine in the Age of Biomedical Big Data.Frontiers in genetics · 2019Review
- NUP155 insufficiency recalibrates a pluripotent transcriptome with network remodeling of a cardiogenic signaling module.BMC systems biology · 2018Article
- Inborn errors of metabolism and the human interactome: a systems medicine approach.Journal of inherited metabolic disease · 2018Review
- PedAM: a database for Pediatric Disease Annotation and Medicine.Nucleic acids research · 2018Article
- eRAM: encyclopedia of rare disease annotations for precision medicine.Nucleic acids research · 2018Article
- Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response.Frontiers in genetics · 2018Article
- A semi-synchronous label propagation algorithm with constraints for community detection in complex networks.Scientific reports · 2017Article
- The OncoPPi network of cancer-focused protein-protein interactions to inform biological insights and therapeutic strategies.Nature communications · 2017Article
- DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants.Nucleic acids research · 2017Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Characterizing the behavior of disease genes in the context of biological networks has the potential to shed light on disease mechanisms, and to reveal both new candidate disease genes and therapeutic targets. Previous studies addressing the network properties of disease genes have produced contradictory results. Here we have explored the causes of these discrepancies and assessed the relationship between the network roles of disease genes and their tolerance to deleterious germline variants in human populations leveraging on: the abundance of interactome resources, a comprehensive catalog of disease genes and exome variation data. We found that the most salient network features of disease genes are driven by cancer genes and that genes related to different types of diseases play network roles whose centrality is inversely correlated to their tolerance to likely deleterious germline mutations. This proved to be a multiscale signature, including global, mesoscopic and local network centrality features. Cancer driver genes, the most sensitive to deleterious variants, occupy the most central positions, followed by dominant disease genes and then by recessive disease genes, which are tolerant to variants and isolated within their network modules.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.