ArticleeLife2019
Genetic and environmental perturbations lead to regulatory decoherence.
Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
34 citing papers in PubMed.
- Mepolizumab alters gene regulatory networks of nasal airway type-2 and epithelial inflammation in urban children with asthma.Nature communications · 2025Trial
- Regulatory Responses of Ectothermic Embryos to Predicted Heat Stresses Under Near-Future Climate Change.Molecular ecology · 2026Article
- A powerful framework for differential co-expression analysis of general risk factors.Bioinformatics (Oxford, England) · 2025Article
- Genotype by Environment Interactions in Gene Regulation Underlie the Response to Soil Drying in the Model Grass Brachypodium distachyon.Molecular biology and evolution · 2025Article
- Developmentally cascading structures do not lose evolutionary potential, but compound developmental instability in rat molars.bioRxiv : the preprint server for biology · 2025Article
- Evolutionary divergence between homologous X-Y chromosome genes shapes sex-biased biology.Nature ecology & evolution · 2025Article
- Article
- Systems genomics of salinity stress response in rice.bioRxiv : the preprint server for biology · 2024Article
- SCAMPI: A scalable statistical framework for genome-wide interaction testing harnessing cross-trait correlations.bioRxiv : the preprint server for biology · 2024Article
- A robust model for cell type-specific interindividual variation in single-cell RNA sequencing data.Nature communications · 2024Article
- MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data.Briefings in bioinformatics · 2024Article
- Identifying latent genetic interactions in genome-wide association studies using multiple traits.Genome medicine · 2024Article
- Article
- Gene co-expression networks reveal sex-biased differences in musculoskeletal ageing.Frontiers in aging · 2024Article
- Increasing diversity of functional genetics studies to advance biological discovery and human health.American journal of human genetics · 2023Article
- MATTE: a pipeline of transcriptome module alignment for anti-noise phenotype-gene-related analysis.Briefings in bioinformatics · 2023Article
- Characterizing the landscape of gene expression variance in humans.PLoS genetics · 2023Article
- A robust model for cell type-specific interindividual variation in single-cell RNA sequencing data.bioRxiv : the preprint server for biology · 2023Article
- Isolation disrupts social interactions and destabilizes brain development in bumblebees.Current biology : CB · 2022Article
- Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Correlation among traits is a fundamental feature of biological systems that remains difficult to study. To address this problem, we developed a flexible approach that allows us to identify factors associated with inter-individual variation in correlation. We use data from three human cohorts to study the effects of genetic and environmental variation on correlations among mRNA transcripts and among NMR metabolites. We first show that environmental exposures (infection and disease) lead to a systematic loss of correlation, which we define as 'decoherence'. Using longitudinal data, we show that decoherent metabolites are better predictors of whether someone will develop metabolic syndrome than metabolites commonly used as biomarkers of this disease. Finally, we demonstrate that correlation itself is under genetic control by mapping hundreds of 'correlation quantitative trait loci (QTLs)'. Together, this work furthers our understanding of how and why coordinated biological processes break down, and points to a potential role for decoherence in disease. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
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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.