Evaluation of miRNA-16–2-3P, miRNA-618 levels and their diagnostic and prognostic value in the regulation of immune response during SARS Cov-2 infection

Following the announcement of the pandemic of COVID-19 in December 2019, several studies focused on how to early predict the severity of the disease in symptomatic and asymptomatic patients. Many cytokines including interleukin-6, interleukin-8, and tumor necrotic factors have been concluded as strong indicators for COVID-19 infection. Additionally, miRNAs have been associated with dysregulation in the immune system. The aim of this study are the following: (1) to estimate the level of miRNA-16–2-3P, miRNA-618, IL-8, IL-1β as predictors for SARS-CoV-2 complications in PCR negative and positive patients; (2) to assess the biological role and effect of these miRNAs on SARS-CoV-2 pathogenicity. Our study showed that the level of IL-1β had been significantly associated with patient who need hospitalization, also the alteration of the level of miRNA-16–2-3P, miRNA-618 is positively correlated with the admission of these patients and influence the outcomes of SARS-cov-2 infection. Measurement of miRNA-16–2-3P, miRNA-618, IL-1β could be a good predictor of COVID-19 patient outcome. However the measurement of IL-8 levels during immune responses in the admitted and in ICU patients could have a prognostic value.


Introduction
As of February 2021, the COVID-19 pandemic, caused by infection with severe acute respiratory syndrome-associated coronavirus-2 (SARS-CoV-2), has resulted in over 107 million cases and 2.35 million deaths worldwide (Farr et al. 2021). In Egypt, starting from the 3rd of January 2020 to the 21st of February 2022, 469,457 recorded cases of COVID-19 with 23,752 deaths have been detected (WHO 2022). The outcome of SARS-CoV-2 infection varies widely from asymptomatic to severe disease associated with acute respiratory distress syndrome (ARDS) and death (Wu et al. 2020). Several studies have established that host responses to infection play a critical role in determining disease outcomes in infected patients.
A significant decrease in lymphocytes were lower than 20% in severe cases has been detected (Del Valle et al. 2020), specifically, CD4 + T, CD8 + T, natural killer (NK) cells, and B cell number (Fara et al. 2020;Huang et al. 2020).
Many reviews have evaluated the associated inflammatory mediators with COVID-19. For example, hyperinflammatory responses including high levels of circulating cytokines and chemokines (particularly interleukin (IL)-6, IL-8, and tumor necrosis factor (TNF)-α) ), IL-10 and C-reactive protein (Del Valle et al. 2020), IL-17 (Darif et al. 2021), and IL-18 (Valizadeh et al. 2020); lymphopenia and immune cell infiltration in infected organs are considered major determinants of COVID-19 severity 1 3 .  is an effective proinflammatory cytokine that has been associated with the enrollment and activation of neutrophils during inflammation. Therefore, detected neutrophilia detected in COVID-19 patients can contribute to the pathophysiology of the disease (Feldmann et al. 2020).
The characterization of host factors associated with SARS-CoV-2 pathogenesis is critically important for the design of novel therapies.
MicroRNAs (miRNAs) are a class of non-coding RNAs that regulate endogenous gene expression at the post-transcriptional level. In most instances, miRNAs function by interacting with the 3′ untranslated region (3′ UTR) of target mRNAs to induce degradation and translational repression (Bartel 2018). There are currently over 2600 human miRNAs listed in the miRNA registry (miRBase, version 22), which are estimated to collectively regulate 60% of all human protein-coding genes (Farr et al. 2021).
Some studies have revealed that the viral miRNAs can modify some of the host inflammatory responses to constrain secure damage to susceptible organs including-lungs (Panda et al. 2022). On the other hand, the host miRNAs have been proved to inhibit viral replication via self-attachment at 3′UTR region of the viral genome or the cellular targeting receptor or blocking the structural and non-structural proteins of SARS-CoV-2 without disturbing the expression of the human genome (Chow and Salmena 2020). Therefore, miRNAs could modulate the immune response of the severely infected COVID-19 patients via different mechanisms. Li et al. (2020) data analysis suggests that, 35 miRNAs were upregulated and 38 miRNAs were downregulated in the human patients with COVID-19. The top genes were as follows: miR-16-2-3p, miR-6501-5p, and miR-618 were highly expressed in COVID-19 patients and that miR-183-5p, miR-627-5p, and miR-144-3p were less expressed in COVID-19 patients.
The scientific rationale for investigating miRNAs during viral infections is two-fold. Firstly, miRNA profiles offer unique insight into cellular pathways associated with virus replication and pathogenesis. For instance, the human coronavirus OC43 potentiates NF-kB activation during infection by binding and sequestering miR-9, a negative regulator of NF-kB (Lai et al. 2014). There is also evidence that coronaviruses co-opt the host miRNAs response to subvert antiviral immune responses. Infection by the, Alpha Corona Virus transmissible gastroenteritis virus (TGEV), downregulates miR-30a-5p expression, which disrupts the type I interferon response against TGEV (Ma et al. 2018).
Secondly, the characterization of host miRNAs responses to virus infection informs the development of biomarkers for improved disease detection and forecasting of disease outcome (Tribolet et al. 2020). Several pathogenic viruses, including SARS-CoV-1, induce changes to the circulating host miRNA profile (Tambyah et al. 2013). Viral infection can regulate miRNA expression and that can cause other genes to regulate the host immune response to viral infection. MicroRNAs effect is on virus replication and they have recently emerged as important modulators of viral infections (Canatan and Sanctis 2020).
While it is recognized that the host response to infection plays a critical role in determining the severity and outcome of COVID-19, the host microRNA (miRNA) response to SARS-CoV-2 infection is poorly defined. The host response to SARS-CoV-2 infection provides insights into both viral pathogenesis and patient management (Farr et al. 2021). All groups under study have been subjected for the following:

Patient methods and subject study
-Complete blood count (CBC) has been done on automated cell analyzer DXH 520 (Beckman Coulter). -Biochemical tests (including renal function tests (urea and creatinine) and liver function tests (bilirubin (T and D), proteins (total and albumin), AST, ALT, ALP, and GGt) have been done on automated chemistry analyzer AU480 (Beckman Coulter) and electrolytes (Na and K) on ion selective electrode analyzer. -Laboratory investigation to assess the severity of COVID-19 • Ferritin, by chemiluminescent assay cobas e411 (Roche) • CRP, turbidmetric assay on automated chemistry analyzer AU480 (Beckman Coulter) • D-Dimer, by chemiluminescent enzyme immunoassay for the quantitative measurement of D-Dimer concentration on PATHFAST instrument -Inflammatory cytokines (IL-1B and IL-8) using the Enzyme-Linked Immunosorbent Assay (ELISA) technique. Supplied kits from the Elabscience Biotechnology Inc. USA -Human IL-1β and IL-8 by ELISA technique: -Sample: Serum -Assay procedure -100 μL standard and sample added to each well. Incubated for 90 min at 37 ℃ -Liquid removed. Aspirated and washed 5 times -100 μL Biotinylated Detection Ab has been added.
Incubated for 1 h at 37 ℃ -Aspirated and washed 5 times -100 μL HRP conjugate added. Intubated for 30 min at 37 ℃ -Aspirated and washed 5 times -90 μL substrate reagent added. Incubated for 15 min at 37 ℃ -50 μL stop solution added and read the standard and sample absorbance at 450 nm -Plotting the standard curve -Calculation of the results using standard curve -MicroRNAs (miRNA-16-2-3p and miRNA-618) were assessed using Real Time-PCR.

RNA extraction and reverse transcription
-Total RNA, containing miRNA, was extracted from plasma samples (200 µl plasma) using the Qiagen miRNeasy Mini Mix. Then we add 2.5 μL of forward primer, 2.5 μL reverse primers, and 5 μL RNase-free water in a final volume of 25 μL in each strip tube. The reactivity conditions: initial activation step at 95 °C for 15 min, followed by 3-step cycling: 1-denaturation 94 °C for 15 s, 2-annealing 55 °C for 30 s, 3-extension 70 °C for 34 s. The three steps cycle has been repeated for 40 cycles.. After reaction, the threshold cycle of fluorescence (Ct) was calculated to further analyze the expression level of miRNA in specimens utilizing endogenous control. A housekeeping gene was added to each sample as an internal negative control (Catalog no. 00033712). The relative expression was expressed by 2-ΔCT (ΔCT = CT target gene-CT reference gene). The relative quantification of each of miRNA-16-2-3P and miRNA-618 was performed using quantitative real-time (qRT)-PCR according to the manufacturer's instructions. The ΔCt value was used to represent the relative level of expression of a single miRNA.

Statistical analysis
Data were verified, coded by the researcher, and analyzed using the IBM-SPSS 24.0 (IBM-SPSS Inc., Chicago, IL, USA

Results
The demographic data of the two studied groups has been demonstrated in Table (1). There was no significant difference between the positive PCR COVID-19 group and negative group as regards the presence of the following diseases: asthma, chronic obstructive airway disease (COPD), hypertension (HTN), diabetes mellitus (DM), chronic kidney disease (CKD), ischemic heart disease (IHD), rheumatic heart disease (RHD), or cancer (Table 1). Laboratory investigations of both groups revealed a significant difference regarding ALT, CRP, miRNA-618, and miRNA-16-2-3P in favor to positive PCR for COVID-19 group, as presented in Table 2.
A multivariable logistic regression model revealed that odd for detecting the COVID-19 infection by PCR increased to almost 3 times if the patient have COPD. Cyanosis showed 3.5 times increase in incidence for predicting the infection (P < 0.029), while presence of myalgia showed almost 4 times increase incidence for predicting COVID-19 infection positive PCR compared with the negative PCR cases (Table 3). Also, the incidence for prediction of COVID-19 infection increase 4 times with the level of miRNA-618 and 9 times with miRNA-16-2-3p. This may suggests that the presence of these signs or symptoms may be associated with increase viral load in the nasopharynex.

P-value
Laboratory findings HGB (mean ± SD) 11.84 ± 1.6 11.53 ± 1.8 0.656* WBCs (median (IQR)) 7.8 (5) 6.9 (  Regarding laboratory biomarkers and their association with ICU admission, ICU admitted cases show a significantly high IL-1β level in comparison to patients not in need for ICU admission. However, IL-8 level shows the reverse with a significantly high level in patients not in need for ICU admission in comparison to ICU admitted patients. Similarly, miRNA-618 level shows significant increase level in non ICU admitted patients in comparison to ICU admitted patients, while there was a marginal significant increase in the level of miRNA-16-2-3P in non ICU admitted patients. No significant difference was detected with serum iron or lead (Table 4). These biomarkers could have a prognostic value in COVID-19 infected patients.

Discussion
A negative COVID-19 test means the test did not detect the virus, but this does not rule out that you could have an infection. If you have symptoms you may have COVID-19, but tested before the virus was detectable, or you may have another illness.
In our study, positive PCR patients for COVID-19 showed no significant difference regarding clinical symptoms as sore throat, cough, fatigue, vomiting, nausea, and chills when compared to the negative PCR group for COVID-19. Although most of the cases suffered these symptoms, only myalgia and anosmia show a mild significant increase in the positive PCR group for COVID-19 in comparison to the negative PCR one; 28% of the positive PCR group had anosmia compared to non in the negative PCR group. Additionally, 32.5% of the positive PCR group had myalgia when compared to 10% of the negative PCR group (P < 0.05). Early studied meta-analyses assessing the impact of comorbidities on the course and clinical outcome of COVID-19 found that about 31% of adult patients had comorbidities. Hypertension being the most prevalent condition (20.93%) followed by heart failure (10.5%), diabetes mellitus (10.4%), and coronary heart disease (8.5%) (Jutzeler et al. 2020). These pre-existing comorbidities were found to be linked with the severity of the COVID-19.
Comparison between different laboratory tests revealed a significant difference regarding only ALT and CRP in favor to cases group with no differences regarding comorbidities. In addition, the presence of COPD (OR: 3, P < 0.04), cyanosis (OR: 3.5, P < 0.029), epigastric pain had 9% chance of predicting the COVID-19 infection (P < 0.047) while myalgia increased the odd for prediction to almost 4 times compared with the negative cases.
Using the multivariable logistic regression model of analysis, it has been found that presence of the clinical symptoms and signs, COPD, cyanosis, epigastric pain, and myalgia, is a good predictor for COVID-19 (P < 0.05). Farr et al. (2021) study stated that the host response to SARS-CoV-2 infection provides insights into both viral pathogenesis and patient management. Cytokine storm is an activation cascade of auto-amplifying cytokine production and leads to excessive activation of immune cells and the generation of pro-inflammatory cytokines (Tisoncik et al. 2012).
To lower mortality due to cytokine storm, we have to discover and find good predictors for this aggressive inflammatory response, even before its development. Several clinical studies report the infiltration of monocytes and macrophages into the lungs of the COVID-19 patients contribute to the production of pro-inflammatory cytokines and chemokines that result in cytokine storm leading to tissue damage, organ system dysfunction, and progression to ARDS as well as mortality (Costela-Ruiz et al. 2020;Gómez-Rial et al. 2020).
It has been proved that the higher the level of cytokines the poor the prognosis Guohua et al. 2020). Narożna and Rubiś (2021) suggesting that COVID-2 inhibits the IFN receptor's activation, which reduces the antiviral effect while allowing cytokine storm syndrome (i.e., IL-1, IL-6, IL-8) release. Additional study reveals a significant difference between the disease stages and different levels of IL-8 and IL-6. Also, a significant negative correlation was detected between IL-6 and IL-8 levels and SpO2, PaO2, which indicate respiratory failure. Furthermore, positive correlation between IL-8 and IL-6 and CRP was detected. The study has concluded that IL-6 and IL-8 can act as predictive biomarkers for the COVID-19 infection and severity .
Evidence suggests that excessive inflammatory process activation leads to abundant interleukin-1β (IL-1β) release and subsequent aggravation of pulmonary injury and induce hypercoagulability, favoring progression to respiratory failure and widespread thrombosis eventually leading to multiorgan failure and death (Nicola et al. 2022).
Our data reveals that IL-1β level was significantly increase in the COVID-19 positive patients, and this level significantly increases in ICU admitted patients; this makes IL-1β a good predictor of the disease severity and patient's outcome. In the same line with IL-1β the level of IL-8, miRNA-618 and miRNA-16-2-3p show a significantly increase level in the COVID-19 positive patients. However, the level of these parameters, , are significantly decrease in the COVID-19 ICU admitted patients in comparison to non ICU admitted one. Our data demonstrates that the level of IL-8 significantly increase in the Covid-19 infected patients, but this level was found to decrease in ICU admitted patient in comparison to non ICU admitted patients, and these results against the recorded results by many authors who demonstrates a positive correlation between the level of IL-8 and the severity of the disease (Nagant et al. 2020;. Also, Del Valle et al. (2020) found an association between the level of IL-8 and decrease or worse survival. Our controversies results may be due to the included ICU admitted patients who are under treatment that may improve the condition and causes decrease in IL-8 level, we did not include any type of treatment in our study. So, further study includes the type of treatment and correlates this with IL-8 level may help in prediction and follow up response of the patients.
Our statistical data analysis reveals that IL-1β has a bad predictability for the COVID-19 infection. However IL-8 has a sensitivity of 70% with more specificity 79% than IL-1β with 77% PPV and 72.5% NPV. This makes IL-8 has a more diagnostic predictor for the COVID-19 patients, with an accuracy of 74.5% at a cut off value of 17 pg/ml.miRNAs are known to regulate numerous physiological pathways and biological processes including cell development, maturation, differentiation, and activation. miRNAs are vital for the regulation and elimination of undesired or malformed mRNA. miRNAs can act as anti-viral tool within the host cell as an entry for the diffusion of the virus (Abu-Izneid et al. 2021).
In our study, we compare the level of miRNA-618 and miRNA-16-2-3p between the two symptomatic groups, one with proved Covid-19 by PCR and the other group is negative for COVID-19 by PCR.
Our data analysis of the miRNA-618 and miRNA-16-2-3p levels shows a significant increase in its level in the positive PCR group in comparison to the negative PCR group (P < 0.05).
In one study, COVID-19 patients displayed 200 significant differentially expressed (SDE) miRNAs. Around 75 miRNAs were detected in asymptomatic patients compared to symptomatic patients who showed platelet aggregation and cytokine pathways. Moreover, the study has found that miRNAs were significantly correlated with inflammatory cytokines (Fernández-Pato et al. 2022).
One study has revealed that miRNA-618 highly expressed in patients with COVID-19 and it increased to 1.5 fold in symptomatic patients with COVID-19 compared to healthy volunteers .
Statistical analysis of our laboratory data reveals that miRNA-618 and miRNA-16-2-3p level shows a significant increase in its level in the positive PCR for the Covid-19 group in comparison to negative PCR for the COVID-19 group (P < 0.05). In agreement with our results, Li et al. (2020) study reveals that miR-16-2-3p, miR-6501-5p, and miR-618 were more highly expressed in COVID-19 patients than in healthy controls.
Our study reveals that miRNA-618 and miRNA-16-2-3p level was low in ICU admitted patients in comparison to non-ICU admitted patients; however, this low level were statistically significant in miRNA-618 only (P = 0.042) not with miRNA-16-2-3p (P = 0.051). That means there is a down regulation of the miRNA-618 and miRNA-16-2-3p, and this downregulation increase with the severity of the disease and the need for ICU.
From our study we suggest that measurement of the IL-1β, IL-8, and host miRNA response could improve COVID-19 detection, outcome prediction and this potentially useful tool for early management of patients with severe forms.
Nevertheless, our study has several limitations. First, our negative PCR patients not tested for other viruses that could be the cause of symptoms. Also the number of symptomatic negative PCR cases included is low relative to positive PCR cases. Further studies would be needed to explore how the duration of illness influences the Interleukins or microRNAs level. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.