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Coronavirus disease is caused by SARS-CoV-2, known as 2019 novel coronavirus (2019-nCoV). To date has caused a large number of deaths causing serious respiratory illness such as pneumonia and lung failure, therefore representing a serious threat to public health. The etiological agent belongs to the subfamily Orthocoronavirinae in the family Coronaviridae, Order Nidovirales. The genome of coronaviruses is composed of an enveloped, positive-sense, single-stranded RNA with a size varying between 26 kb and 32 kb, becoming the largest genome of known RNA viruses so far. Similar to RNA viruses, this family is characterized by genetic variability and high recombination rate that enable them to be easily distributed among humans and animals worldwide. Considering the huge impact of the pandemic, it is urgent to gain understanding and to build strategies to contain the viral spread. To date, different diagnostic kits for testing the illness are available. Besides diagnosis, the prediction of the severity and prognosis of COVID-19 is essential to stratify patients and allocate them in the adequate medical facilities so as to reduce mortality rates. It has been reported that microRNAs (miRNAs) are valuable biomarkers for disease diagnosis, prognosis and classification. MiRNAs are defined as a class of non-coding RNAs that are able to regulate gene expression by specific binding to complementary regions in coding messenger RNAs, leading to translational repression or decay. Not only that, but also they can be important modulators of viral infections.Previous studies have revealed the presence of miRNA-like small RNAs (milRNAs), which can be encoded by RNA viruses and can actively disrupt the host innate immune responses in order to create a favourable environment for viral replication. On the other side, cellular miRNAs can also play a role on virus replication and pathogenesis.In this case, this pilot project is aimed at their valuable diagnostic potential, in order to diagnose and stratify patients under viral infection. The project came up after receiving information from a Chinese research group, requesting their results to be replicated in Caucasian population. The ROC curves were constructed to demonstrate the accuracy of this specific miRNA in COVID-19 patient stratification and discerning between severe patients from healthy controls. Both ROC curves suggested the miRNA as precise biomarker for differential diagnosis and prognosis of disease severity.
It will include 120 patients with and without COVID-19 According to the World Health Organization guidance, all patients with COVID-19 enrolled in the study were diagnosed bythe throat swab and RT-PCR method. Patient information was collected from medical records.Total RNA content will be extracted from plasma samples by methods aimed at preserving and isolating small RNA molecules. The kit used will be. mirVANATM PARISTM Isolation Kit (Applied Biosystems, Darmstadt, Germany). The mirVANATM PARISTM Kit begins with homogenization of samples with a special cell disruption buffer and RNA isolation is performed using a procedure that combines the advantages of organic and solid-phase extraction. Once extracted, a fixed volume of RNA solution will be used as the input for the reverse transcription reaction using the TaqMan™ MicroRNA Reverse Transcription Kit (Applied Biosystems, Darmstadt, Germany). The product will be further amplified by real-time PCR using specific primers for the detection of the milRNA previously validated by means of the LightCycler® 480 Real-Time PCR System (Roche Diagnostics, Barcelona, Spain).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients with COVID-19 | Other | blood sampling for miRNA analysis |
|
| Patients without COVID-19 | Other | blood sampling for miRNA analysis |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| miRNA analysis in plasma | Diagnostic Test | blood sample |
|
| Measure | Description | Time Frame |
|---|---|---|
| miRNA analysis in plasma | Replicate in our Caucasian cohort previous findings which are under revision in The New England Journal of Medicine, where a miRNA-like small RNA encoded by SARSCoV- 2, has been reported to distinguish severe patients from mild ones and predict the prognosis of COVID-19 | 1 year |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| geltrude mingrone, professor | Policlinico A. Gemelli IRCCS | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Mingrone Geltrude | Roma | 00168 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32397911 | Background | Amawi H, Abu Deiab GI, A Aljabali AA, Dua K, Tambuwala MM. COVID-19 pandemic: an overview of epidemiology, pathogenesis, diagnostics and potential vaccines and therapeutics. Ther Deliv. 2020 Apr;11(4):245-268. doi: 10.4155/tde-2020-0035. Epub 2020 May 12. | |
| 32234466 | Background | Li H, Liu SM, Yu XH, Tang SL, Tang CK. Coronavirus disease 2019 (COVID-19): current status and future perspectives. Int J Antimicrob Agents. 2020 May;55(5):105951. doi: 10.1016/j.ijantimicag.2020.105951. Epub 2020 Mar 29. |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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| 32290293 | Background | Tu YF, Chien CS, Yarmishyn AA, Lin YY, Luo YH, Lin YT, Lai WY, Yang DM, Chou SJ, Yang YP, Wang ML, Chiou SH. A Review of SARS-CoV-2 and the Ongoing Clinical Trials. Int J Mol Sci. 2020 Apr 10;21(7):2657. doi: 10.3390/ijms21072657. |
| 32286245 | Background | Henry BM, de Oliveira MHS, Benoit S, Plebani M, Lippi G. Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis. Clin Chem Lab Med. 2020 Jun 25;58(7):1021-1028. doi: 10.1515/cclm-2020-0369. |
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| 18668037 | Background | Baek D, Villen J, Shin C, Camargo FD, Gygi SP, Bartel DP. The impact of microRNAs on protein output. Nature. 2008 Sep 4;455(7209):64-71. doi: 10.1038/nature07242. Epub 2008 Jul 30. |
| 32420944 | Background | Canatan D, De Sanctis V. The impact of MicroRNAs (miRNAs) on the genotype of coronaviruses. Acta Biomed. 2020 May 11;91(2):195-198. doi: 10.23750/abm.v91i2.9534. |
| 15118162 | Background | Pfeffer S, Zavolan M, Grasser FA, Chien M, Russo JJ, Ju J, John B, Enright AJ, Marks D, Sander C, Tuschl T. Identification of virus-encoded microRNAs. Science. 2004 Apr 30;304(5671):734-6. doi: 10.1126/science.1096781. |
| 28216251 | Background | Morales L, Oliveros JC, Fernandez-Delgado R, tenOever BR, Enjuanes L, Sola I. SARS-CoV-Encoded Small RNAs Contribute to Infection-Associated Lung Pathology. Cell Host Microbe. 2017 Mar 8;21(3):344-355. doi: 10.1016/j.chom.2017.01.015. Epub 2017 Feb 16. |
| D014777 |
| Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |