Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expression
Abstract Background Overstretching of lung parenchyma may lead to injury, especially during mechanical ventilation. To date, there are no specific biomarkers of lung stretch, but transcriptomic signatures have not been explored. Our objective was to identify stretch-specific signatures using micro-R...
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SpringerOpen
2025-06-01
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| Series: | Intensive Care Medicine Experimental |
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| Online Access: | https://doi.org/10.1186/s40635-025-00768-2 |
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| author | Cecilia López-Martínez Paula Martín-Vicente Laura Amado-Rodríguez Inés López-Alonso Margarita Fernández-Rodríguez Adrián González-López Pablo Martínez-Camblor Juan Gómez Andrew J. Boyle Cecilia M. O’Kane Daniel F. McAuley James N. Tsoporis Claudia dos Santos Guillermo M. Albaiceta |
| author_facet | Cecilia López-Martínez Paula Martín-Vicente Laura Amado-Rodríguez Inés López-Alonso Margarita Fernández-Rodríguez Adrián González-López Pablo Martínez-Camblor Juan Gómez Andrew J. Boyle Cecilia M. O’Kane Daniel F. McAuley James N. Tsoporis Claudia dos Santos Guillermo M. Albaiceta |
| author_sort | Cecilia López-Martínez |
| collection | DOAJ |
| description | Abstract Background Overstretching of lung parenchyma may lead to injury, especially during mechanical ventilation. To date, there are no specific biomarkers of lung stretch, but transcriptomic signatures have not been explored. Our objective was to identify stretch-specific signatures using micro-RNA and gene expression. Methods Data on micro-RNA and RNA expression in response to stretch in experimental models were systematically pooled. Signatures were identified as those micro-RNAs or genes with differential expression in samples from stretched cells or tissues, and optimized using a greedy algorithm. Expression data was used to calculate transcriptomic scores. The accuracy of these scores was validated in animal models of lung injury, ex vivo mechanically ventilated human lungs, and bronchoalveolar lavage fluid (BALF, n = 7) and in serum samples (n = 31) of mechanically ventilated patients. Results Six micro-RNAs (mir-383, mir-877, mir-130b; mir-146b, mir-181b, and mir-26b) were differentially expressed in stretched cell cultures (n = 24). Amongst the genes regulated by these micro-RNAs, a 451-gene signature was identified in vitro (n = 106) and refined using data from animal models (n = 143) to obtain a 6-gene signature (Lims1, Atp6v1c1, Dedd, Bclb7, Ppp1r2 and F3). Transcriptomic scores were significantly higher in samples submitted to stretch or injurious mechanical ventilation. The microRNA and RNA signatures were validated in human tissue, BALF and serum, with areas under the ROC curve between 0.7 and 1 to identify lung overdistention. Conclusions Lung cell stretch induces the expression of specific micro-RNA and genes. The potential of these signatures to identify lung stretch in a clinical setting must be explored. |
| format | Article |
| id | doaj-art-b07c63bb1bca4b8ab33d8b1cf04d7fca |
| institution | DOAJ |
| issn | 2197-425X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | SpringerOpen |
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| series | Intensive Care Medicine Experimental |
| spelling | doaj-art-b07c63bb1bca4b8ab33d8b1cf04d7fca2025-08-20T03:10:38ZengSpringerOpenIntensive Care Medicine Experimental2197-425X2025-06-0113111310.1186/s40635-025-00768-2Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expressionCecilia López-Martínez0Paula Martín-Vicente1Laura Amado-Rodríguez2Inés López-Alonso3Margarita Fernández-Rodríguez4Adrián González-López5Pablo Martínez-Camblor6Juan Gómez7Andrew J. Boyle8Cecilia M. O’Kane9Daniel F. McAuley10James N. Tsoporis11Claudia dos Santos12Guillermo M. Albaiceta13Centro de Investigación Biomédica en Red (CIBER)-Enfermedades Respiratorias, Instituto de Salud Carlos IIICentro de Investigación Biomédica en Red (CIBER)-Enfermedades Respiratorias, Instituto de Salud Carlos IIICentro de Investigación Biomédica en Red (CIBER)-Enfermedades Respiratorias, Instituto de Salud Carlos IIICentro de Investigación Biomédica en Red (CIBER)-Enfermedades Respiratorias, Instituto de Salud Carlos IIIInstituto de Investigación Sanitaria del Principado de AsturiasCentro de Investigación Biomédica en Red (CIBER)-Enfermedades Respiratorias, Instituto de Salud Carlos IIIDepartment of Biomedical Data Sciences, Geisel School of Medicine, Dartmouth CollegeCentro de Investigación Biomédica en Red (CIBER)-Enfermedades Respiratorias, Instituto de Salud Carlos IIIWellcome-Wolfson Institute for Experimental Medicine, School of Medicine Dentistry and Biomedical Science, Queen’s UniversityWellcome-Wolfson Institute for Experimental Medicine, School of Medicine Dentistry and Biomedical Science, Queen’s UniversityWellcome-Wolfson Institute for Experimental Medicine, School of Medicine Dentistry and Biomedical Science, Queen’s UniversityKeenan Research Centre for Biomedical Science, St Michael’s Hospital, University of TorontoKeenan Research Centre for Biomedical Science, St Michael’s Hospital, University of TorontoCentro de Investigación Biomédica en Red (CIBER)-Enfermedades Respiratorias, Instituto de Salud Carlos IIIAbstract Background Overstretching of lung parenchyma may lead to injury, especially during mechanical ventilation. To date, there are no specific biomarkers of lung stretch, but transcriptomic signatures have not been explored. Our objective was to identify stretch-specific signatures using micro-RNA and gene expression. Methods Data on micro-RNA and RNA expression in response to stretch in experimental models were systematically pooled. Signatures were identified as those micro-RNAs or genes with differential expression in samples from stretched cells or tissues, and optimized using a greedy algorithm. Expression data was used to calculate transcriptomic scores. The accuracy of these scores was validated in animal models of lung injury, ex vivo mechanically ventilated human lungs, and bronchoalveolar lavage fluid (BALF, n = 7) and in serum samples (n = 31) of mechanically ventilated patients. Results Six micro-RNAs (mir-383, mir-877, mir-130b; mir-146b, mir-181b, and mir-26b) were differentially expressed in stretched cell cultures (n = 24). Amongst the genes regulated by these micro-RNAs, a 451-gene signature was identified in vitro (n = 106) and refined using data from animal models (n = 143) to obtain a 6-gene signature (Lims1, Atp6v1c1, Dedd, Bclb7, Ppp1r2 and F3). Transcriptomic scores were significantly higher in samples submitted to stretch or injurious mechanical ventilation. The microRNA and RNA signatures were validated in human tissue, BALF and serum, with areas under the ROC curve between 0.7 and 1 to identify lung overdistention. Conclusions Lung cell stretch induces the expression of specific micro-RNA and genes. The potential of these signatures to identify lung stretch in a clinical setting must be explored.https://doi.org/10.1186/s40635-025-00768-2Lung stretchTranscriptomicsMicro-RNAsOverdistension |
| spellingShingle | Cecilia López-Martínez Paula Martín-Vicente Laura Amado-Rodríguez Inés López-Alonso Margarita Fernández-Rodríguez Adrián González-López Pablo Martínez-Camblor Juan Gómez Andrew J. Boyle Cecilia M. O’Kane Daniel F. McAuley James N. Tsoporis Claudia dos Santos Guillermo M. Albaiceta Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expression Intensive Care Medicine Experimental Lung stretch Transcriptomics Micro-RNAs Overdistension |
| title | Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expression |
| title_full | Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expression |
| title_fullStr | Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expression |
| title_full_unstemmed | Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expression |
| title_short | Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expression |
| title_sort | prediction of lung overdistension during mechanical ventilation using micro rna and gene expression |
| topic | Lung stretch Transcriptomics Micro-RNAs Overdistension |
| url | https://doi.org/10.1186/s40635-025-00768-2 |
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