The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Gene expression networks in COPD: microRNA and mRNA regulation
Open accessAbstract
BACKGROUND: The mechanisms underlying chronic obstructive pulmonary disease (COPD) remain unclear. MicroRNAs (miRNAs or miRs) are small non-coding RNA molecules that modulate the levels of specific genes and proteins. Identifying expression patterns of miRNAs in COPD may enhance our understanding of the mechanisms of disease. A study was undertaken to determine if miRNAs are differentially expressed in the lungs of smokers with and without COPD. miRNA and mRNA expression were compared to enrich for biological networks relevant to the pathogenesis of COPD. METHODS: Lung tissue from smokers with no evidence of obstructive lung disease (n=9) and smokers with COPD (n=26) was examined for miRNA and mRNA expression followed by validation. We then examined both miRNA and mRNA expression to enrich for relevant biological pathways. RESULTS: 70 miRNAs and 2667 mRNAs were differentially expressed between lung tissue from subjects with COPD and smokers without COPD. miRNA and mRNA expression profiles enriched for biological pathways that may be relevant to the pathogenesis of COPD including the transforming growth factor β, Wnt and focal adhesion pathways. miR-223 and miR-1274a were the most affected miRNAs in subjects with COPD compared with smokers without obstruction. miR-15b was increased in COPD samples compared with smokers without obstruction and localised to both areas of emphysema and fibrosis. miR-15b was differentially expressed within GOLD classes of COPD. Expression of SMAD7, which was validated as a target for miR-15b, was decreased in bronchial epithelial cells in COPD. CONCLUSIONS: miRNA and mRNA are differentially expressed in individuals with COPD compared with smokers without obstruction. Investigating these relationships may further our understanding of the mechanisms of disease.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
The functions of animal microRNAs
Ambros, V. (2004) · Nature · doi:10.1038/nature02871 · Cited by 10,728
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,266
Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs
Lim, L. P., Lau, N. C., Garrett-Engele, P., Grimson, A., Schelter, J. M., Castle, J., Bartel, D. P., Linsley, P. S., & Johnson, J. M. (2005) · Nature · doi:10.1038/nature03315 · Cited by 4,755
Chronic obstructive pulmonary disease: molecular and cellularmechanisms
Barnes, P. J., Shapiro, S. D., & Pauwels, R. A. (2003) · European Respiratory Journal · doi:10.1183/09031936.03.00040703 · Cited by 1,439
Global Strategy for the Diagnosis, Management and Prevention of COPD: 2003 update
Fabbri, L. M., & Hurd, S. S. (2003) · European Respiratory Journal · doi:10.1183/09031936.03.00063703 · Cited by 1,277
Cited by
Hsu, S.-D., Tseng, Y.-T., Shrestha, S., Lin, Y.-L., Khaleel, A., Chou, C.-H., Chu, C.-F., Huang, H.-Y., Lin, C.-M., Ho, S.-Y., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1266 · Cited by 1,041
Selman, M., & Pardo, A. (2014) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201312-2221pp · Cited by 454
Methodological challenges in utilizing mi RNA s as circulating biomarkers
Moldovan, L., Batte, K. E., Trgovcich, J., Wisler, J., Marsh, C. B., & Piper, M. (2014) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.12236 · Cited by 436
Self-citationA Systematic Review of Global Desert Dust and Associated Human Health Effects
Zhang, X., Zhao, L., Tong, D., Wu, G., Dan, M., & Teng, B. (2016) · Atmosphere · doi:10.3390/atmos7120158 · Cited by 236
Li, N., Pan, X., Zhang, J., Ma, A., Yang, S., Ma, J., & Xie, A. (2017) · Neurological Sciences · doi:10.1007/s10072-017-2841-9 · Cited by 97
Metadata
- Authors
- Ezzie, M. E., Crawford, M., Cho, J.-H., Orellana, R., Zhang, S., Gelinas, R., Batte, K., Yu, L., Nuovo, G., Galas, D., Diaz, P., Wang, K., & Nana-Sinkam, S. P.
- Venue
- Thorax
- Publisher
- BMJ
- Published
- 2011-09-22
- Volume
- 67
- Issue
- 2
- Pages
- 122-131
- ISSN
- 0040-6376 (ISSN-L)
- 1468-3296
- OpenAlex
- W2101411920
- Cited by
- 349
- References
- 38
- FWCI
- 16.08
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Gene expression networks in COPD: microRNA and mRNA regulation. https://app.cochat.ai/papers/10.1136/thoraxjnl-2011-200089
- The paper
- Ezzie, M. E., Crawford, M., Cho, J.-H., Orellana, R., Zhang, S., Gelinas, R., Batte, K., Yu, L., Nuovo, G., Galas, D., Diaz, P., Wang, K., & Nana-Sinkam, S. P. (2012). Gene expression networks in COPD: microRNA and mRNA regulation. Thorax. https://doi.org/10.1136/thoraxjnl-2011-200089
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.