MicroRNAs - a promising tool for asthma diagnosis and severity assessment: a systematic review
MicroRNAs - a promising tool for asthma diagnosis and severity assessment: a systematic review
Micro RNAs (miRNAs) are short, non-coding RNAs (Ribonucleic acids) with regulatory functions that could prove useful as biomarkers for asthma diagnosis and asthma severity-risk stratification. The objective of this systematic review is to identify panels of miRNAs that can be used to support asthma diagnosis and severity-risk assessment. Three databases (Medline, Embase, and SCOPUS) were searched up to 15 September 2020 to identify studies reporting differential expression of specific miRNAs in the tissues of adults and children with asthma. Studies reporting miRNAs associations in animal models that were also studied in humans were included in this review. We identified 75 studies that met our search criteria. Of these, 66 studies reported more than 200 miRNAs that are differentially expressed in asthma patients when compared to non-asthmatic controls. In addition, 16 studies reported 17 miRNAs that are differentially expressed with differences in asthma severity. We were able to construct two panels of miRNAs that are expressed in blood and can serve as core panels to further investigate the practicality and efficiency of using miRNAs as non-invasive biomarkers for asthma diagnosis and severity-risk assessment, respectively.
asthma, asthma severity, biomarker, diagnosis, micro RNA
Kyyaly, Mohammed Aref
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Vorobeva, Elena Vladimirovna
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Kothalawala, Dilini M
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Fong, Wei Chern Gavin
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He, Peijun
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Sones, Collin L
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Al-Zahrani, Mohammad
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Sanchez-Elsner, Tilman
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Arshad, Syed Hasan
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Kurukulaaratchy, Ramesh J
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29 March 2022
Kyyaly, Mohammed Aref
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Vorobeva, Elena Vladimirovna
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Kothalawala, Dilini M
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Fong, Wei Chern Gavin
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He, Peijun
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Sones, Collin L
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Al-Zahrani, Mohammad
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Sanchez-Elsner, Tilman
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Arshad, Syed Hasan
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Kurukulaaratchy, Ramesh J
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Kyyaly, Mohammed Aref, Vorobeva, Elena Vladimirovna, Kothalawala, Dilini M, Fong, Wei Chern Gavin, He, Peijun, Sones, Collin L, Al-Zahrani, Mohammad, Sanchez-Elsner, Tilman, Arshad, Syed Hasan and Kurukulaaratchy, Ramesh J
(2022)
MicroRNAs - a promising tool for asthma diagnosis and severity assessment: a systematic review.
Journal of Personalized Medicine, 12 (4), [543].
(doi:10.3390/jpm12040543).
Abstract
Micro RNAs (miRNAs) are short, non-coding RNAs (Ribonucleic acids) with regulatory functions that could prove useful as biomarkers for asthma diagnosis and asthma severity-risk stratification. The objective of this systematic review is to identify panels of miRNAs that can be used to support asthma diagnosis and severity-risk assessment. Three databases (Medline, Embase, and SCOPUS) were searched up to 15 September 2020 to identify studies reporting differential expression of specific miRNAs in the tissues of adults and children with asthma. Studies reporting miRNAs associations in animal models that were also studied in humans were included in this review. We identified 75 studies that met our search criteria. Of these, 66 studies reported more than 200 miRNAs that are differentially expressed in asthma patients when compared to non-asthmatic controls. In addition, 16 studies reported 17 miRNAs that are differentially expressed with differences in asthma severity. We were able to construct two panels of miRNAs that are expressed in blood and can serve as core panels to further investigate the practicality and efficiency of using miRNAs as non-invasive biomarkers for asthma diagnosis and severity-risk assessment, respectively.
Text
jpm-12-00543-v3
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Accepted/In Press date: 25 March 2022
Published date: 29 March 2022
Additional Information:
Funding Information:
This work was supported by an Asthma UK?BLF research grant (AUK?PG?2019?419).
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.
Keywords:
asthma, asthma severity, biomarker, diagnosis, micro RNA
Identifiers
Local EPrints ID: 457180
URI: http://eprints.soton.ac.uk/id/eprint/457180
ISSN: 2075-4426
PURE UUID: aeb02c60-71b2-4570-a3dd-e4656fb6ac52
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Date deposited: 25 May 2022 17:11
Last modified: 30 Apr 2024 01:45
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Contributors
Author:
Elena Vladimirovna Vorobeva
Author:
Dilini M Kothalawala
Author:
Wei Chern Gavin Fong
Author:
Peijun He
Author:
Collin L Sones
Author:
Mohammad Al-Zahrani
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