ArticlePLoS computational biology2011
Identifying causal genes and dysregulated pathways in complex diseases.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 2 of them syntheses that pooled it.
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Who cites it
93 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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- Genome-wide association study in a Chinese population identifies a susceptibility locus for type 2 diabetes at 7q32 near PAX4.Diabetologia · 2013Pooled it
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- Skin Gene Expression Profiles in Systemic Sclerosis: From Clinical Stratification to Precision Medicine.International journal of molecular sciences · 2023Review
- Integrating multiomics and prior knowledge: a study of the Graphnet penalty impact.Bioinformatics (Oxford, England) · 2023Article
- Multi-omics integration to identify the genetic expression and protein signature of dilated and ischemic cardiomyopathy.Frontiers in cardiovascular medicine · 2023Article
- Validating methods for testing natural molecules on molecular pathways of interest in silico and in vitro.Journal of preventive medicine and hygiene · 2022Article
- Identifying individualized risk subpathways reveals pan-cancer molecular classification based on multi-omics data.Computational and structural biotechnology journal · 2022Article
- Integration of peripheral transcriptomics, genomics, and interactomics following trauma identifies causal genes for symptoms of post-traumatic stress and major depression.Molecular psychiatry · 2021Observational
- Robust inference of kinase activity using functional networks.Nature communications · 2021Article
- ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets.Computational and structural biotechnology journal · 2021Article
- ACE2 Interaction Networks in COVID-19: A Physiological Framework for Prediction of Outcome in Patients with Cardiovascular Risk Factors.Journal of clinical medicine · 2020Article
- Identifying Drug Sensitivity Subnetworks with NETPHIX.iScience · 2020Article
- Learning gene networks underlying clinical phenotypes using SNP perturbation.PLoS computational biology · 2020Article
- Computational/in silico methods in drug target and lead prediction.Briefings in bioinformatics · 2020Review
- Network-based modeling of drug effects on disease module in systemic sclerosis.Scientific reports · 2020Article
33 more citing papers are in PubMed but not listed here.
Corrections and comments
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3 authors.
Funding
Abstract
In complex diseases, various combinations of genomic perturbations often lead to the same phenotype. On a molecular level, combinations of genomic perturbations are assumed to dys-regulate the same cellular pathways. Such a pathway-centric perspective is fundamental to understanding the mechanisms of complex diseases and the identification of potential drug targets. In order to provide an integrated perspective on complex disease mechanisms, we developed a novel computational method to simultaneously identify causal genes and dys-regulated pathways. First, we identified a representative set of genes that are differentially expressed in cancer compared to non-tumor control cases. Assuming that disease-associated gene expression changes are caused by genomic alterations, we determined potential paths from such genomic causes to target genes through a network of molecular interactions. Applying our method to sets of genomic alterations and gene expression profiles of 158 Glioblastoma multiforme (GBM) patients we uncovered candidate causal genes and causal paths that are potentially responsible for the altered expression of disease genes. We discovered a set of putative causal genes that potentially play a role in the disease. Combining an expression Quantitative Trait Loci (eQTL) analysis with pathway information, our approach allowed us not only to identify potential causal genes but also to find intermediate nodes and pathways mediating the information flow between causal and target genes. Our results indicate that different genomic perturbations indeed dys-regulate the same functional pathways, supporting a pathway-centric perspective of cancer. While copy number alterations and gene expression data of glioblastoma patients provided opportunities to test our approach, our method can be applied to any disease system where genetic variations play a fundamental causal role.
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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.