ArticleBMC systems biology2008
Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome.
Article in BMC systems biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers, 1 of them a synthesis that pooled it.
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Who cites it
106 citing papers in PubMed, 1 synthesis or guideline pooled it, 211 citations in OpenAlex.
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- Trial
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- The Chronic Effects of a Single Low-Intensity Blast Exposure on Phosphoproteome Networks and Cognitive Function Influenced by Mutant Tau Overexpression.International journal of molecular sciences · 2024Article
- k-Clique counting on large scale-graphs: a survey.PeerJ. Computer science · 2024Article
- Systems genetics approaches for understanding complex traits with relevance for human disease.eLife · 2023Review
- Single-cell transcriptomics of hepatic stellate cells uncover crucial pathways and key regulators involved in non-alcoholic steatohepatitis.Endocrine connections · 2023Article
- Heterogenous circulating miRNA changes in ME/CFS converge on a unified cluster of target genes: A computational analysis.PloS one · 2023Article
- Identification of Hub Genes Associated with Abnormal Endothelial Function in Early Coronary Atherosclerosis.Biochemical genetics · 2022Article
- Gene Co-expression Analysis of the Human Substantia Nigra Identifies ZNHIT1 as an SNCA Co-expressed Gene that Protects Against α-Synuclein-Induced Impairments in Neurite Growth and Mitochondrial Dysfunction in SH-SY5Y Cells.Molecular neurobiology · 2022Article
- miR-155-5p regulates hypoxia-induced pulmonary artery smooth muscle cell function by targeting PYGL.Bioengineered · 2022Article
- Identification of key pathways and genes that regulate cashmere development in cashmere goats mediated by exogenous melatonin.Frontiers in veterinary science · 2022Article
- Construction of a lncRNA-mRNA Co-Expression Network for Nasopharyngeal Carcinoma.Frontiers in oncology · 2022Article
- Prognostic analysis of m6A-related genes as potential biomarkers in idiopathic pulmonary fibrosis.Frontiers in genetics · 2022Article
- Identification of Potential Molecular Mechanism Related to Infertile Endometriosis.Frontiers in veterinary science · 2022Article
46 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundSystems biologic approaches such as Weighted Gene Co-expression Network Analysis (WGCNA) can effectively integrate gene expression and trait data to identify pathways and candidate biomarkers. Here we show that the additional inclusion of genetic marker data allows one to characterize network relationships as causal or reactive in a chronic fatigue syndrome (CFS) data set.
resultsWe combine WGCNA with genetic marker data to identify a disease-related pathway and its causal drivers, an analysis which we refer to as "Integrated WGCNA" or IWGCNA. Specifically, we present the following IWGCNA approach: 1) construct a co-expression network, 2) identify trait-related modules within the network, 3) use a trait-related genetic marker to prioritize genes within the module, 4) apply an integrated gene screening strategy to identify candidate genes and 5) carry out causality testing to verify and/or prioritize results. By applying this strategy to a CFS data set consisting of microarray, SNP and clinical trait data, we identify a module of 299 highly correlated genes that is associated with CFS severity. Our integrated gene screening strategy results in 20 candidate genes. We show that our approach yields biologically interesting genes that function in the same pathway and are causal drivers for their parent module. We use a separate data set to replicate findings and use Ingenuity Pathways Analysis software to functionally annotate the candidate gene pathways.
conclusionWe show how WGCNA can be combined with genetic marker data to identify disease-related pathways and the causal drivers within them. The systems genetics approach described here can easily be used to generate testable genetic hypotheses in other complex disease studies.
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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.