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Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea
BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent, but frequently undiagnosed. The existing biomarkers of OSA are relatively insensitive and inaccurate. Long non-coding RNAs (lncRNAs) have no protein-coding ability but have a role in regulating gene expression. They are stably expressed...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511177/ https://www.ncbi.nlm.nih.gov/pubmed/36172105 http://dx.doi.org/10.21037/atm-22-3818 |
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author | Chen, Xunxun Liu, Hongbing Huang, Rong Wei, Ran Zhao, Yuchuan Li, Taoping |
author_facet | Chen, Xunxun Liu, Hongbing Huang, Rong Wei, Ran Zhao, Yuchuan Li, Taoping |
author_sort | Chen, Xunxun |
collection | PubMed |
description | BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent, but frequently undiagnosed. The existing biomarkers of OSA are relatively insensitive and inaccurate. Long non-coding RNAs (lncRNAs) have no protein-coding ability but have a role in regulating gene expression. They are stably expressed in exosomes, easily and rapidly measurable. Changes in expression of exosomal lncRNAs can be useful for disease diagnoses. However, there are few reports on the association of exosomal lncRNAs with OSA. We aimed to investigate the exosomal lncRNA profiles to establish the differences between non-OSA, OSA with or without hypertension (HTN) and serve as a potential diagnostic biomarker. METHODS: This diagnostic test included 63 participants: [normal control (NC) =25], (OSA =23), and (HTN-OSA =15). Expression profiling of lncRNAs in isolated exosomes was performed through high-throughput sequencing in 9 participants. Subsequently, OSA/HTN-OSA related lncRNAs were selected for validation by droplet digital polymerase chain reaction (ddPCR), receiver operating characteristic (ROC) curves were used to determine the diagnostic value. The reliabilities of the screened gene were further validated in another independent cohort: (NC =10), (OSA mild =10), (OSA moderate =11), and (OSA severe =10), the correlation between clinical features and its expression was analyzed. The MiRanda software was used to predict the binding sites of interaction between microRNA (miRNA) and target genes regulated by screened lncRNA. RESULTS: We identified the differentially expressed lncRNAs and mRNAs in plasma exosomes of the NC, OSA, HTN-OSA groups. Most pathways enriched in differentially expressed lncRNAs and mRNAs had previously been linked to OSA. Among them, ENST00000592016 enables discrimination between NC and OSA individuals [area under curve (AUC) =0.846, 95% confidence interval (CI): 0.72–0.97]. The severity of OSA was associated with changes in the ENST00000592016 expression. Furthermore, ENST00000592016 affected the PI3K-Akt, MAPK, and TNF pathways by regulating miRNA expressions. CONCLUSIONS: This is the first report about differential expression of lncRNA in OSA and HTN-OSA exosomes. ENST00000592016 enables discrimination between NC and OSA individuals. This work enabled characterization of OSA and provided the preliminary work for the study of biomarker of OSA. |
format | Online Article Text |
id | pubmed-9511177 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-95111772022-09-27 Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea Chen, Xunxun Liu, Hongbing Huang, Rong Wei, Ran Zhao, Yuchuan Li, Taoping Ann Transl Med Original Article BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent, but frequently undiagnosed. The existing biomarkers of OSA are relatively insensitive and inaccurate. Long non-coding RNAs (lncRNAs) have no protein-coding ability but have a role in regulating gene expression. They are stably expressed in exosomes, easily and rapidly measurable. Changes in expression of exosomal lncRNAs can be useful for disease diagnoses. However, there are few reports on the association of exosomal lncRNAs with OSA. We aimed to investigate the exosomal lncRNA profiles to establish the differences between non-OSA, OSA with or without hypertension (HTN) and serve as a potential diagnostic biomarker. METHODS: This diagnostic test included 63 participants: [normal control (NC) =25], (OSA =23), and (HTN-OSA =15). Expression profiling of lncRNAs in isolated exosomes was performed through high-throughput sequencing in 9 participants. Subsequently, OSA/HTN-OSA related lncRNAs were selected for validation by droplet digital polymerase chain reaction (ddPCR), receiver operating characteristic (ROC) curves were used to determine the diagnostic value. The reliabilities of the screened gene were further validated in another independent cohort: (NC =10), (OSA mild =10), (OSA moderate =11), and (OSA severe =10), the correlation between clinical features and its expression was analyzed. The MiRanda software was used to predict the binding sites of interaction between microRNA (miRNA) and target genes regulated by screened lncRNA. RESULTS: We identified the differentially expressed lncRNAs and mRNAs in plasma exosomes of the NC, OSA, HTN-OSA groups. Most pathways enriched in differentially expressed lncRNAs and mRNAs had previously been linked to OSA. Among them, ENST00000592016 enables discrimination between NC and OSA individuals [area under curve (AUC) =0.846, 95% confidence interval (CI): 0.72–0.97]. The severity of OSA was associated with changes in the ENST00000592016 expression. Furthermore, ENST00000592016 affected the PI3K-Akt, MAPK, and TNF pathways by regulating miRNA expressions. CONCLUSIONS: This is the first report about differential expression of lncRNA in OSA and HTN-OSA exosomes. ENST00000592016 enables discrimination between NC and OSA individuals. This work enabled characterization of OSA and provided the preliminary work for the study of biomarker of OSA. AME Publishing Company 2022-09 /pmc/articles/PMC9511177/ /pubmed/36172105 http://dx.doi.org/10.21037/atm-22-3818 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Chen, Xunxun Liu, Hongbing Huang, Rong Wei, Ran Zhao, Yuchuan Li, Taoping Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea |
title | Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea |
title_full | Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea |
title_fullStr | Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea |
title_full_unstemmed | Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea |
title_short | Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea |
title_sort | screening of plasma exosomal lncrnas to identify potential biomarkers for obstructive sleep apnea |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511177/ https://www.ncbi.nlm.nih.gov/pubmed/36172105 http://dx.doi.org/10.21037/atm-22-3818 |
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