SynthesisPloS one2017
Meta-analysis of peripheral blood gene expression modules for COPD phenotypes.
Synthesis in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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.
The trial behind it
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
15 citing papers in PubMed.
- Advances in Traditional Chinese Medicine for chronic obstructive pulmonary disease through multi-omics approaches.Frontiers in cell and developmental biology · 2026Review
- An integrative network-based approach to identify driving gene communities in chronic obstructive pulmonary disease.NPJ systems biology and applications · 2024Article
- Pathophysiology and genomics of bronchiectasis.European respiratory review : an official journal of the European Respiratory Society · 2024Review
- Article
- Significant Subgraph Detection in Multi-omics Networks for Disease Pathway Identification.Frontiers in big data · 2022Article
- Large-scale plasma proteomics can reveal distinct endotypes in chronic obstructive pulmonary disease and severe asthma.Clinical and translational allergy · 2021Article
- Analysis of the polarization states of the alveolar macrophages in chronic obstructive pulmonary disease samples based on miRNA-mRNA network signatures.Annals of translational medicine · 2021Article
- Exploring PI3Kδ Molecular Pathways in Stable COPD and Following an Acute Exacerbation, Two Randomized Controlled Trials.International journal of chronic obstructive pulmonary disease · 2021Article
- Assessing the Role of Long Noncoding RNA in Nucleus Accumbens in Subjects With Alcohol Dependence.Alcoholism, clinical and experimental research · 2020Article
- Omics and the Search for Blood Biomarkers in Chronic Obstructive Pulmonary Disease. Insights from COPDGene.American journal of respiratory cell and molecular biology · 2019Review
- Use of autologousThorax · 2019Article
- FKBP5 rs4713916: A Potential Genetic Predictor of Interindividual Different Response to Inhaled Corticosteroids in Patients with Chronic Obstructive Pulmonary Disease in a Real-Life Setting.International journal of molecular sciences · 2019Article
- RNA-sequencing across three matched tissues reveals shared and tissue-specific gene expression and pathway signatures of COPD.Respiratory research · 2019Article
- Gene expression microarray public dataset reanalysis in chronic obstructive pulmonary disease.PloS one · 2019Article
- Lung Dendritic Cells Drive Natural Killer Cytotoxicity in Chronic Obstructive Pulmonary Disease via IL-15Rα.American journal of respiratory and critical care medicine · 2018Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Chronic obstructive pulmonary disease (COPD) occurs typically in current or former smokers, but only a minority of people with smoking history develops the disease. Besides environmental factors, genetics is an important risk factor for COPD. However, the relationship between genetics, environment and phenotypes is not well understood. Sample sizes for genome-wide expression studies based on lung tissue have been small due to the invasive nature of sample collection. Increasing evidence for the systemic nature of the disease makes blood a good alternative source to study the disease, but there have also been few large-scale blood genomic studies in COPD. Due to the complexity and heterogeneity of COPD, examining groups of interacting genes may have more relevance than identifying individual genes. Therefore, we used Weighted Gene Co-expression Network Analysis to find groups of genes (modules) that are highly connected. However, module definitions may vary between individual data sets. To alleviate this problem, we used a consensus module definition based on two cohorts, COPDGene and ECLIPSE. We studied the relationship between the consensus modules and COPD phenotypes airflow obstruction and emphysema. We also used these consensus module definitions on an independent cohort (TESRA) and performed a meta analysis involving all data sets. We found several modules that are associated with COPD phenotypes, are enriched in functional categories and are overrepresented for cell-type specific genes. Of the 14 consensus modules, three were strongly associated with airflow obstruction (meta p ≤ 0.0002), and two had some association with emphysema (meta p ≤ 0.06); some associations were stronger in the case-control cohorts, and others in the cases-only subcohorts. Gene Ontology terms that were overrepresented included "immune response" and "defense response." The cell types whose type-specific genes were overrepresented in modules (p < 0.05) included natural killer cells, dendritic cells, and neutrophils. Together, this is the largest investigation of gene blood expression in COPD with 469 cases in COPDGene, ECLIPSE and TESRA combined, with 6267 genes common to all data sets. Additional, we have 42 and 83 controls in COPDGene and ECLIPSE, respectively.
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