In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity

(1) Background: The coronavirus (COVID-19) pandemic is still a major global health problem, despite the development of several vaccines and diagnostic assays. Moreover, the broad symptoms, from none to severe pneumonia, and the various responses to vaccines and the assays, make infection control cha...

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Autores principales:	Sara H. A. Agwa, Hesham Elghazaly, Mahmoud Shawky El Meteini, Sherif M. Shawky, Marwa Ali, Aya M. Abd Elsamee, Safa Matbouly Sayed, Nadine Sherif, Howida M. Sharaf, Mohamed A. Alhadidy, Marwa Matboli
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	circulating RNAs bioinformatics SARS-COV-2 infection severity prediction interleukins genetic network coding and non-coding RNAs COVID-19 infection potential biomarker Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/d6b2f479fadb417bb78d035b98c4fa02
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spelling	oai:doaj.org-article:d6b2f479fadb417bb78d035b98c4fa022021-11-25T17:11:29ZIn Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity10.3390/cells101130982073-4409https://doaj.org/article/d6b2f479fadb417bb78d035b98c4fa022021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4409/10/11/3098https://doaj.org/toc/2073-4409(1) Background: The coronavirus (COVID-19) pandemic is still a major global health problem, despite the development of several vaccines and diagnostic assays. Moreover, the broad symptoms, from none to severe pneumonia, and the various responses to vaccines and the assays, make infection control challenging. Therefore, there is an urgent need to develop non-invasive biomarkers to quickly determine the infection severity. Circulating RNAs have been proven to be potential biomarkers for a variety of diseases, including infectious ones. This study aimed to develop a genetic network related to cytokines, with clinical validation for early infection severity prediction. (2) Methods: Extensive analyses of in silico data have established a novel IL11RA molecular network (IL11RNA mRNA, LncRNAs RP11-773H22.4 and hsa-miR-4257). We used different databases to confirm its validity. The differential expression within the retrieved network was clinically validated using quantitative RT-PCR, along with routine assessment diagnostic markers (CRP, LDH, D-dimmer, procalcitonin, Ferritin), in100 infected subjects (mild and severe cases) and 100 healthy volunteers. (3) Results: IL11RNA mRNA and LncRNA RP11-773H22.4, and the IL11RA protein, were significantly upregulated, and there was concomitant downregulation of hsa-miR-4257, in infected patients, compared to the healthy controls, in concordance with the infection severity. (4) Conclusion: The in-silico data and clinical validation led to the identification of a potential RNA/protein signature network for novel predictive biomarkers, which is in agreement with ferritin and procalcitonin for determination of COVID-19 severity.Sara H. A. AgwaHesham ElghazalyMahmoud Shawky El MeteiniSherif M. ShawkyMarwa AliAya M. Abd ElsameeSafa Matbouly SayedNadine SherifHowida M. SharafMohamed A. AlhadidyMarwa MatboliMDPI AGarticlecirculating RNAsbioinformaticsSARS-COV-2 infection severity predictioninterleukins genetic networkcoding and non-coding RNAsCOVID-19 infection potential biomarkerBiology (General)QH301-705.5ENCells, Vol 10, Iss 3098, p 3098 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	circulating RNAs bioinformatics SARS-COV-2 infection severity prediction interleukins genetic network coding and non-coding RNAs COVID-19 infection potential biomarker Biology (General) QH301-705.5
spellingShingle	circulating RNAs bioinformatics SARS-COV-2 infection severity prediction interleukins genetic network coding and non-coding RNAs COVID-19 infection potential biomarker Biology (General) QH301-705.5 Sara H. A. Agwa Hesham Elghazaly Mahmoud Shawky El Meteini Sherif M. Shawky Marwa Ali Aya M. Abd Elsamee Safa Matbouly Sayed Nadine Sherif Howida M. Sharaf Mohamed A. Alhadidy Marwa Matboli In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity
description	(1) Background: The coronavirus (COVID-19) pandemic is still a major global health problem, despite the development of several vaccines and diagnostic assays. Moreover, the broad symptoms, from none to severe pneumonia, and the various responses to vaccines and the assays, make infection control challenging. Therefore, there is an urgent need to develop non-invasive biomarkers to quickly determine the infection severity. Circulating RNAs have been proven to be potential biomarkers for a variety of diseases, including infectious ones. This study aimed to develop a genetic network related to cytokines, with clinical validation for early infection severity prediction. (2) Methods: Extensive analyses of in silico data have established a novel IL11RA molecular network (IL11RNA mRNA, LncRNAs RP11-773H22.4 and hsa-miR-4257). We used different databases to confirm its validity. The differential expression within the retrieved network was clinically validated using quantitative RT-PCR, along with routine assessment diagnostic markers (CRP, LDH, D-dimmer, procalcitonin, Ferritin), in100 infected subjects (mild and severe cases) and 100 healthy volunteers. (3) Results: IL11RNA mRNA and LncRNA RP11-773H22.4, and the IL11RA protein, were significantly upregulated, and there was concomitant downregulation of hsa-miR-4257, in infected patients, compared to the healthy controls, in concordance with the infection severity. (4) Conclusion: The in-silico data and clinical validation led to the identification of a potential RNA/protein signature network for novel predictive biomarkers, which is in agreement with ferritin and procalcitonin for determination of COVID-19 severity.
format	article
author	Sara H. A. Agwa Hesham Elghazaly Mahmoud Shawky El Meteini Sherif M. Shawky Marwa Ali Aya M. Abd Elsamee Safa Matbouly Sayed Nadine Sherif Howida M. Sharaf Mohamed A. Alhadidy Marwa Matboli
author_facet	Sara H. A. Agwa Hesham Elghazaly Mahmoud Shawky El Meteini Sherif M. Shawky Marwa Ali Aya M. Abd Elsamee Safa Matbouly Sayed Nadine Sherif Howida M. Sharaf Mohamed A. Alhadidy Marwa Matboli
author_sort	Sara H. A. Agwa
title	In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity
title_short	In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity
title_full	In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity
title_fullStr	In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity
title_full_unstemmed	In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity
title_sort	in silico identification and clinical validation of a novel long non-coding rna/mrna/mirna molecular network for potential biomarkers for discriminating sars cov-2 infection severity
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d6b2f479fadb417bb78d035b98c4fa02
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In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity

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