ArticleMetabolites2020
Identifying Protein-metabolite Networks Associated with COPD Phenotypes.
Article in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 33 citations in OpenAlex.
- Article
- Triglyceride-glucose index as a predictor of the risk of sarcopenia in elderly patients with OSA: a multicenter study.Diabetology & metabolic syndrome · 2025Article
- Metabolomic Plasma Profile of Chronic Obstructive Pulmonary Disease Patients.International journal of molecular sciences · 2025Article
- A generalized higher-order correlation analysis framework for multi-omics network inference.PLoS computational biology · 2025Article
- Validation of Systemic Complement Signatures in the Progression of Chronic Obstructive Pulmonary Disease.American journal of respiratory and critical care medicine · 2024Article
- Smccnet 2.0: a comprehensive tool for multi-omics network inference with shiny visualization.BMC bioinformatics · 2024Article
- Review
- SmCCNet 2.0: A Comprehensive Tool for Multi-omics Network Inference with Shiny Visualization.bioRxiv : the preprint server for biology · 2024Article
- PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration.PLoS computational biology · 2024Article
- PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration.bioRxiv : the preprint server for biology · 2024Article
- Update on metabolomic findings in COPD patients.ERJ open research · 2023Review
- Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate Chronic Obstructive Pulmonary Disease.American journal of respiratory cell and molecular biology · 2023Article
- A blood and bronchoalveolar lavage protein signature of rapid FEVScientific reports · 2023Article
- Article
- NetSHy: network summarization via a hybrid approach leveraging topological properties.Bioinformatics (Oxford, England) · 2023Article
- Effective Subject Representation based on Multi-omics Disease Networks using Graph Embedding.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
- sJIVE: Supervised Joint and Individual Variation Explained.Computational statistics & data analysis · 2022Article
- Air pollution, metabolites and respiratory health across the life-course.European respiratory review : an official journal of the European Respiratory Society · 2022Review
- Metabolome Features of COPD: A Scoping Review.Metabolites · 2022Article
- Significant Subgraph Detection in Multi-omics Networks for Disease Pathway Identification.Frontiers in big data · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Chronic obstructive pulmonary disease (COPD) is a disease in which airflow obstruction in the lung makes it difficult for patients to breathe. Although COPD occurs predominantly in smokers, there are still deficits in our understanding of the additional risk factors in smokers. To gain a deeper understanding of the COPD molecular signatures, we used Sparse Multiple Canonical Correlation Network (SmCCNet), a recently developed tool that uses sparse multiple canonical correlation analysis, to integrate proteomic and metabolomic data from the blood of 1008 participants of the COPDGene study to identify novel protein-metabolite networks associated with lung function and emphysema. Our aim was to integrate -omic data through SmCCNet to build interpretable networks that could assist in the discovery of novel biomarkers that may have been overlooked in alternative biomarker discovery methods. We found a protein-metabolite network consisting of 13 proteins and 7 metabolites which had a -0.34 correlation (
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What OpenQuestion holds
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.