ArticleJournal of the American Medical Informatics Association : JAMIA
Network models of genome-wide association studies uncover the topological centrality of protein interactions in complex diseases.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Precision drug repurposing via convergent eQTL-based molecules and pathway targeting independent disease-associated polymorphisms.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019Article
- Genome-Wide Association Study in African Americans with Acute Respiratory Distress Syndrome Identifies the Selectin P Ligand Gene as a Risk Factor.American journal of respiratory and critical care medicine · 2018Article
- Population-dependent Intron Retention and DNA Methylation in Breast Cancer.Molecular cancer research : MCR · 2018Article
- Convergent downstream candidate mechanisms of independent intergenic polymorphisms between co-classified diseases implicate epistasis among noncoding elements.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
- Genotype-driven identification of a molecular network predictive of advanced coronary calcium in ClinSeq® and Framingham Heart Study cohorts.BMC systems biology · 2017Article
- Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.Computational and mathematical methods in medicine · 2017Article
- Network Analysis of Genome-Wide Selective Constraint Reveals a Gene Network Active in Early Fetal Brain Intolerant of Mutation.PLoS genetics · 2016Article
- Complex genetics of pulmonary diseases: lessons from genome-wide association studies and next-generation sequencing.Translational research : the journal of laboratory and clinical medicine · 2016Review
- eQTL networks unveil enriched mRNA master integrators downstream of complex disease-associated SNPs.Journal of biomedical informatics · 2015Article
- Profiling phenome-wide associations: a population-based observational study.Journal of the American Medical Informatics Association : JAMIA · 2015Observational
- Comparative analysis of a novel disease phenotype network based on clinical manifestations.Journal of biomedical informatics · 2015Article
- CEBPA exerts a specific and biologically important proapoptotic role in pancreatic β cells through its downstream network targets.Molecular biology of the cell · 2014Article
- Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis.Arthritis research & therapy · 2014Article
- Multi-omic landscape of rheumatoid arthritis: re-evaluation of drug adverse effects.Frontiers in cell and developmental biology · 2014Article
- COPD Hospitalization Risk Increased with Distinct Patterns of Multiple Systems Comorbidities Unveiled by Network Modeling.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- Beyond modules and hubs: the potential of gene coexpression networks for investigating molecular mechanisms of complex brain disorders.Genes, brain, and behavior · 2014Review
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Abstract
backgroundWhile genome-wide association studies (GWAS) of complex traits have revealed thousands of reproducible genetic associations to date, these loci collectively confer very little of the heritability of their respective diseases and, in general, have contributed little to our understanding the underlying disease biology. Physical protein interactions have been utilized to increase our understanding of human Mendelian disease loci but have yet to be fully exploited for complex traits.
methodsWe hypothesized that protein interaction modeling of GWAS findings could highlight important disease-associated loci and unveil the role of their network topology in the genetic architecture of diseases with complex inheritance.
resultsNetwork modeling of proteins associated with the intragenic single nucleotide polymorphisms of the National Human Genome Research Institute catalog of complex trait GWAS revealed that complex trait associated loci are more likely to be hub and bottleneck genes in available, albeit incomplete, networks (OR=1.59, Fisher's exact test p < 2.24 × 10(-12)). Network modeling also prioritized novel type 2 diabetes (T2D) genetic variations from the Finland-USA Investigation of Non-Insulin-Dependent Diabetes Mellitus Genetics and the Wellcome Trust GWAS data, and demonstrated the enrichment of hubs and bottlenecks in prioritized T2D GWAS genes. The potential biological relevance of the T2D hub and bottleneck genes was revealed by their increased number of first degree protein interactions with known T2D genes according to several independent sources (p<0.01, probability of being first interactors of known T2D genes).
conclusionVirtually all common diseases are complex human traits, and thus the topological centrality in protein networks of complex trait genes has implications in genetics, personal genomics, and therapy.
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