Impact of COVID-19 and vaccination on first and second trimester screening results.

COVID-19 has been shown to affect pregnant women. Since pregnant women are at risk of this infection, vaccination against COVID-19 has been suggested as an imperative way to diminish rate of COVID-19 in this population. In the current observational study, we have collected data of first and second trimester screening (FTS and STS) from pregnant women who were infected with SARS-CoV-2 and/or vaccinated against COVID-19 during their pregnancy, and compared this data with a group of control pregnant women. The cohort included 4612 and 2426 women referred for FTS and STS, respectively. There was no significant difference in median values of Pregnancy-associated plasma protein A (PAPP-A) and human chorionic gonadotropin-beta subunit (ßHCG) between infected women and controls. Moreover, these levels were not different between "Infected + vaccinated" and "Only vaccinated" groups. However, median values of PAPP-A and ßHCG were higher in "Infected + vaccinated" and "Only vaccinated" groups compared with "Infected" and "Control" groups (P < 0.001). Median values of unconjugated Estriol (uE3) and ßHCG markers were not different between "Only vaccinated" and "Control" groups, yet both markers were elevated in "Infected" and "Infected + vaccinated" groups compared with other groups. AFP values were higher in "Infected" group (P = 0.012). However, multiple of the median (MoM) and risk of open spina bifida (OSB) were not affected. Finally, median of calculated risk of trisomy 18 was lower in "Infected" and "Vaccinated" groups compared with controls (P = 0.007). Moreover, AstraZeneca and Sinopharm vaccines were associated with elevation of the calculated risk values of trisomy 21 and trisomy 18 (P < 0.001). While Sinopharm did not affect nuchal translucency (NT) and NT MoM (P = 0.13), AstraZeneca and Barakat increased and decreased these values, respectively (P values = 0.0027 and 0.015, respectively). Taken together, COVID-19 during pregnancy might be associated with some adverse obstetric outcomes. Besides, vaccination against this infection might affect the results of STS or FTS.

Identification of key differentially expressed genes in SARS-CoV-2 using RNA-seq analysis with a systems biology approach.

COVID-19 is associated with dysregulation of several genes and signaling pathways. Based on the importance of expression profiling in identification of the pathogenesis of COVID-19 and proposing novel therapies for this disorder, we have employed an in silico approach to find differentially expressed genes between COVID-19 patients and healthy controls and their relevance with cellular functions and signaling pathways. We obtained 630 DEmRNAs, including 486 down-regulated DEGs (such as CCL3 and RSAD2) and 144 up-regulated DEGs (such as RHO and IQCA1L), and 15 DElncRNAs, including 9 down-regulated DElncRNAs (such as PELATON and LINC01506) and 6 up-regulated DElncRNAs (such as AJUBA-DT and FALEC). The PPI network of DEGs showed the presence of a number immune-related genes such as those coding for HLA molecules and interferon regulatory factors. Taken together, these results highlight the importance of immune-related genes and pathways in the pathogenesis of COVID-19 and suggest novel targets for treatment of this disorder.

A Concise Review on Dysregulation of LINC00665 in Cancers.

Long Intergenic Non-Protein Coding RNA 665 (LINC00665) is an RNA gene located on the minus strand of chromosome 19. This lncRNA acts as a competing endogenous RNA for miR-4458, miR-379-5p, miR-551b-5p, miR-3619-5p, miR-424-5p, miR-9-5p, miR-214-3p, miR-126-5p, miR-149-3p, miR-379-5p, miR-665, miR-34a-5p, miR-186-5p, miR-138-5p, miR-181c-5p, miR-98, miR-195-5p, miR-224-5p, miR-3619, miR-708, miR-101, miR-1224-5p, miR-34a-5p, and miR-142-5p. Via influencing expression of these miRNAs, it can enhance expression of a number of oncogenes. Moreover, LINC00665 can influence activity of Wnt/ß-Catenin, TGF-ß, MAPK1, NF-κB, ERK, and PI3K/AKT signaling. Function of this lncRNA has been assessed through gain-of-function tests and/or loss-of-function studies. Furthermore, diverse research groups have evaluated its expression levels in tissue samples using microarray and RT-qPCR techniques. In this manuscript, we have summarized the results of these studies and categorized them in three sections, i.e., cell line studies, animal studies, and investigations in clinical samples.

miRNA expression in COVID-19.

Coronavirus disease 2019 (COVID-19) is regarded as a challenge in health system. Several studies have assessed the immune-related aspect of this disorder to identify the host-related factors that affect the course of COVID-19. microRNAs (miRNAs) as potent regulators of immune responses have gained much attention in this regard. Recent studies have shown aberrant expression of miRNAs in COVID-19 in association with disease course. Differentially expressed miRNAs have been enriched in pathways related with inflammation and antiviral immune response. miRNAs have also been regarded as potential therapeutic targets in COVID-19, particularly for management of pathological consequences of COVID-19. In the current review, we summarize the data about dysregulation of miRNAs in COVID-19.

Investigation of maternal and perinatal outcome in a population of Iranian pregnant women infected with COVID-19.

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in pregnant women might affect both maternal and neonatal outcomes. Based on the inconsistency between the results of the previous studies and the lack of data about the possible vertical transmission of SARS-CoV-2, we designed the present study to investigate the maternal and perinatal outcomes in 182 Iranian pregnant women infected with COVID-19. Among 40 PCR tests conducted on neonatal throat samples, 11 tests were positive. Among the assessed women, 22 women needed ICU admission and 30 premature labors occurred. There were significant associations between ICU admission and many parameters such as the presence of dyspnea (P < 0.001), COVID-19-related CT scan findings (P = 0.003), need for a ventilator (P < 0.001), and low O2 saturation (P < 0.001), all of which indicate the critical situation of patients. Notably, the cause of delivery was significantly different in both groups, with labor pain and fetal distress being the most frequent causes of delivery in non-ICU and ICU-admitted patients, respectively. Moreover, delivery route (P = 0.003), frequencies of IUGR (P = 0.042), neonatal death (P = 0.008) and asphyxia (P = 0.016), Apgar score (P = 0.003), and gestational age at delivery (P = 0.009) have been associated with ICU admission. The present investigation exhibits association between the critical situation of pregnant women affected with COVID-19 and some adverse neonatal outcomes.

Expression analysis of IFNAR1 and TYK2 transcripts in COVID-19 patients.

As a member of JAK family of non-receptor tyrosine kinases, TYK2 has a crucial role in regulation of immune responses. This protein has a crucial role in constant expression of IFNAR1 on surface of cells and initiation of type I IFN signaling. In the current study, we measured expression of IFNAR1 and TYK2 levels in venous blood samples of COVID-19 patients and matched controls. TYK2 was significantly down-regulated in male patients compared with male controls (RME = 0.34, P value = 0.03). Though, levels of TYK2 were not different between female cases and female controls, or between ICU-admitted and non-ICU-admitted cases. Expression of IFNAR1 was not different either between COVID-19 cases and controls or between patients required ICU admission and non-ICU-admitted cases. However, none of these transcripts can properly diffrentiate COVID-19 cases from controls or separate patients based on disease severity. The current study proposes down-regulation of TYK2 as a molecular mechanism for incapacity of SARS-CoV-2 in induction of a competent IFN response.

COVID-19 pandemic: Insights into genetic susceptibility to SARS-CoV-2 and host genes implications on virus spread, disease severity and outcomes.

The outbreak of the newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) all over the world has caused global public health emergencies, international concern and economic crises. The systemic SARS-CoV-2 disease (COVID-19) can lead to death through causing unrestrained cytokines-storm and subsequent pulmonary shutdown among the elderly and patients with pre-existing comorbidities. Additionally, in comparison with poor nations without primary health care services, in developed countries with advanced healthcare system we can witness higher number of infections per one million people. In this review, we summarize the latest studies on genes associated with SARS-CoV-2 pathogenesis and propose possible mechanisms of the virus replication cycle and its triggered signaling pathways to encourage researchers to investigate genetic and immune profiles of the disease and try strategies for its treatment. Our review shows that immune response in people with different genetic background might vary as African and then Asian populations have lowest number of affected cases compared with European and American nations. Considering SARS-CoV-2 pathogenesis, we put forward some potentially important genetic gateways to COVID-19 infection including genes involved in the entry and replication of SARS-CoV-2 and the regulation of host immune response which might represent explanation for its spread, severity, and morality. Finally, we suggest that genetic alterations within these gateways could be critical factors in influencing geographical discrepancies of the virus, so it is essential to fully study them and design appropriated and reliable therapeutic agents against COVID-19.

A comprehensive overview of identified mutations in SARS CoV-2 spike glycoprotein among Iranian patients.

Since late 2019, when SARS-CoV-2 was reported at Wuhan, several sequence analyses have been performed and SARS-CoV-2 genome sequences have been submitted in various databases. Moreover, the impact of these variants on infectivity and response to neutralizing antibodies has been assessed. In the present study, we retrieved a total number of 176 complete and high-quality S glycoprotein sequences of Iranian SARS-COV-2 in public database of the GISAID and GenBank from April 2020 up to May 2021. Then, we identified the number of variables, singleton and parsimony informative sites at both gene and protein levels and discussed the possible functional consequences of important mutations on the infectivity and response to neutralizing antibodies. Phylogenetic tree was constructed to represent the relationship between Iranian SARS-COV2 and variants of concern (VOC), variants of interest (VOI) and reference sequence. We found that the four current VOCs - Alpha, Beta, Gamma and Delta - are circulated in different regions in Iran. The Delta variant is notably more transmissible than other variants, and is expected to become a dominant variant. However, some of the Delta variants in Iran carry an additional mutation, namely E1202Q in the HR2 subdomain that might confer an advantage to viral/cell membrane fusion process. We also observed some more common mutations such as an N-terminal domain (NTD) deletion at position I210 and P863H in fusion peptide-heptad repeat 1 span region in Iranian SARS-COV-2. The reported mutations in the current project have practical significance in prediction of disease spread as well as design of vaccines and drugs.

Abnormal Transcript Levels of Cytokines Among Iranian COVID-19 Patients.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 and the related disorder i.e. "coronavirus disease 2019" (COVID-19) has encouraged researchers to unravel the molecular mechanism of disease severity. Several lines of evidence support the impact of "cytokine storm" in the pathogenesis of severe forms of the disorder. We aimed to assess expression levels of nine cytokine coding genes in COVID-19 patients admitted in a hospital. We collected clinical data of patients from their medical reports. Then, we assessed expression of genes using real-time PCR. Expression levels of IFN-G, IL-2, IL-4, IL-6, IL-17, TGF-B, IL-8, and IL-1B were significantly higher in COVID-19 patients compared with healthy controls and in both female and male patients compared with sex-matched controls. However, expression level of TNF-A was not different between COVID-19 patients and healthy controls. Expression of none of these cytokines was different between ICU-admitted patients and other patients except for IL-6 whose expression was lower in the former group compared with the latter (ratio of means = 0.33, P value = 4.82E-02). Then, we assessed diagnostic power of cytokine coding genes in differentiating between COVID-19 patients and controls. The area under curve (AUC) values ranged from 0.94 for IFN-G to 1.0 for IL-2 and IL-1B. After combining the transcript levels of all cytokines, AUC, sensitivity, and specificity values reached 100%, 100%, and 99%, respectively. For differentiation between ICU-admitted patients and other patients, IL-4 with AUC value of 0.68 had the best diagnostic power among cytokine coding genes. Expression of none of cytokine coding genes was correlated with the available clinical/demographic data including age, gender, ICU admission, or erythrocyte sedimentation rate (ESR)/C-reactive protein (CRP) levels. This study provides further evidence for contribution of "cytokine storm" in the pathobiology of moderate/severe forms of COVID-19.

Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review.

COVID-19 has produced a global pandemic affecting all over of the world. Prediction of the rate of COVID-19 spread and modeling of its course have critical impact on both health system and policy makers. Indeed, policy making depends on judgments formed by the prediction models to propose new strategies and to measure the efficiency of the imposed policies. Based on the nonlinear and complex nature of this disorder and difficulties in estimation of virus transmission features using traditional epidemic models, artificial intelligence methods have been applied for prediction of its spread. Based on the importance of machine and deep learning approaches in the estimation of COVID-19 spreading trend, in the present study, we review studies which used these strategies to predict the number of new cases of COVID-19. Adaptive neuro-fuzzy inference system, long short-term memory, recurrent neural network and multilayer perceptron are among the mostly used strategies in this regard. We compared the performance of several machine learning methods in prediction of COVID-19 spread. Root means squared error (RMSE), mean absolute error (MAE), R2 coefficient of determination (R2), and mean absolute percentage error (MAPE) parameters were selected as performance measures for comparison of the accuracy of models. R2 values have ranged from 0.64 to 1 for artificial neural network (ANN) and Bidirectional long short-term memory (LSTM), respectively. Adaptive neuro-fuzzy inference system (ANFIS), Autoregressive Integrated Moving Average (ARIMA) and Multilayer perceptron (MLP) have also have R2 values near 1. ARIMA and LSTM had the highest MAPE values. Collectively, these models are capable of identification of learning parameters that affect dissimilarities in COVID-19 spread across various regions or populations, combining numerous intervention methods and implementing what-if scenarios by integrating data from diseases having analogous trends with COVID-19. Therefore, application of these methods would help in precise policy making to design the most appropriate interventions and avoid non-efficient restrictions.

Assessment of ACE1 variants and ACE1/ACE2 expression in COVID-19 patients.

Contribution of the renin-angiotensinogen system in the risk of COVID-19 and related complications have been assessed by several groups. However, the results are not consistent. We examined levels of ACE1 and ACE2 in the circulation of two groups of COVID-19 patients (ICU-admitted and general ward-admitted patients) compared with healthy controls. We also genotyped two polymorphisms in ACE1 gene (the ACE1-I/D polymorphism rs1799752 and rs4359) to appraise their association with expression levels of ACE1 and ACE2. Expression level of ACE1 was significantly higher in ICU patients compared with non-ICU patients (P value = 0.02). However, its expression was not significantly different between total COVID-19 patients and total controls (P value = 0.34). ACE2 expression was not different ether between two groups of COVID-19 patients (P value = 0.12) or between total COVID-19 patients and total controls (P value = 0.79). While distribution of rs1799752 and rs4359 alleles was similar between study groups, genotype frequencies of rs1799752 were differently distributed among total COVID-19 patients and controls (P value = 0.00001). Moreover, genotypes of the other polymorphism tended to be distinctively distributed among these two groups (P value = 0.06). In the total population of patients and controls, different ACE1 mRNA levels were observed among carriers of different rs1799752 genotypes; of note, ID genotype carriers showed a higher expression of ACE1 compared with II genotype carriers (P = 0.01). ACE1 polymorphisms might affect risk of COVID-19 and expression of ACE transcripts.

Angiotensin converting enzyme: A review on expression profile and its association with human disorders with special focus on SARS-CoV-2 infection

Angiotensin-converting enzyme (ACE) and its homologue, ACE2, have been mostly associated with hypertensive disorder. However, recent pandemia of SARS-CoV-2 has put these proteins at the center of attention, as this virus has been shown to exploit ACE2 protein to enter cells. Clear difference in the response of affected patients to this virus has urged researchers to find the molecular basis and pathophysiology of the cell response to this virus. Different levels of expression and function of ACE proteins, underlying disorders, consumption of certain medications and the existence of certain genomic variants within ACE genes are possible explanations for the observed difference in the response of individuals to the SARS-CoV-2 infection. In the current review, we discuss the putative mechanisms for this observation.

Evaluation of expression of VDR-associated lncRNAs in COVID-19 patients.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been shown to cause serious health problems among them is the Acute Respiratory Distress syndrome (ARDS). Vitamin D receptor (VDR) signaling possibly partakes in the pathophysiology of this devastating complication. METHODS: In the current project, we have appraised expression levels of VDR, CYP27B1 and a number of associated lncRNAs in the circulation of COVID-19 patients versus healthy subjects using real-time PCR method. RESULTS: Expression of SNHG6 was considerably lower in COVID-19 patients compared with control subjects (Ratio of mean expression (RME) = 0.22, P value = 7.04E-05) and in both female and male COVID-19 patients compared with sex-matched unaffected individuals (RME = 0.32, P value = 0.04 and RME = 0.16, P value = 0.000679683, respectively). However, its expression was similar among ICU-hospitalized and non-ICU patients. Similarly, expression of SNHG16 was lower in in COVID-19 patients compared with controls (RME = 0.20, P value = 5.94E-05) and in both female and male patients compared with sex-matched controls (RME = 0.32, P value = 0.04 and RME = 0.14, P value = 0.000496435, respectively) with no significant difference among ICU-hospitalized and non-ICU hospitalized patients. Expression of VDR was lower in COVID-19 patients compared with controls (RME = 0.42, P value = 0.04) and in male patients compared with male controls (RME = 0.27, P value = 0.02). Yet, expression of VDR was statistically similar between female subgroups and between ICU-hospitalized and non-ICU hospitalized patients. Expression levels CYP27B, Linc00511 and Linc00346 were similar among COVID-19 patients and healthy subjects or between their subgroups. Significant correlations have been detected between expression levels of VDR, CYP27B and SNHG6, SNHG16, Linc00511 and Linc00346 lncRNAs both among COVID-19 patients and among healthy controls with the most significant ones being SNHG6 and SNHG16 (r = 0.74, P value = 3.26e-17 and r = 0.81, P = 1.54e-22, respectively). CONCLUSION: Combination of transcript levels of VDR, CYP27B and SNHG6, SNHG16, Linc00511 and Linc00346 could differentiate patients from controls with AUC = 0.76, sensitivity = 0.62 and specificity = 0.81. The current data potentiate SNHG6, SNHG16 and VDR as possible contributors in COVID-19 infection but not in the severity of ARDS.

Application of Machine Learning in Diagnosis of COVID-19 Through X-Ray and CT Images: A Scoping Review.

Coronavirus disease, first detected in late 2019 (COVID-19), has spread fast throughout the world, leading to high mortality. This condition can be diagnosed using RT-PCR technique on nasopharyngeal and throat swabs with sensitivity values ranging from 30 to 70%. However, chest CT scans and X-ray images have been reported to have sensitivity values of 98 and 69%, respectively. The application of machine learning methods on CT and X-ray images has facilitated the accurate diagnosis of COVID-19. In this study, we reviewed studies which used machine and deep learning methods on chest X-ray images and CT scans for COVID-19 diagnosis and compared their performance. The accuracy of these methods ranged from 76% to more than 99%, indicating the applicability of machine and deep learning methods in the clinical diagnosis of COVID-19.

Identification of FDA approved drugs against SARS-CoV-2 RNA dependent RNA polymerase (RdRp) and 3-chymotrypsin-like protease (3CLpro), drug repurposing approach.

The RNA-dependent RNA polymerase (RdRp) and 3C-like protease (3CLpro) from SARS-CoV-2 play crucial roles in the viral life cycle and are considered the most promising targets for drug discovery against SARS-CoV-2. In this study, FDA-approved drugs were screened to identify the probable anti-RdRp and 3CLpro inhibitors by molecular docking approach. The number of ligands selected from the PubChem database of NCBI for screening was 1760. Ligands were energy minimized using Open Babel. The RdRp and 3CLpro protein sequences were retrieved from the NCBI database. For Homology Modeling predictions, we used the Swiss model server. Their structure was then energetically minimized using SPDB viewer software and visualized in the CHIMERA UCSF software. Molecular dockings were performed using AutoDock Vina, and candidate drugs were selected based on binding affinity (∆G). Hydrogen bonding and hydrophobic interactions between ligands and proteins were visualized using Ligplot and the Discovery Studio Visualizer v3.0 software. Our results showed 58 drugs against RdRp, which had binding energy of - 8.5 or less, and 69 drugs to inhibit the 3CLpro enzyme with a binding energy of - 8.1 or less. Six drugs based on binding energy and number of hydrogen bonds were chosen for the next step of molecular dynamics (MD) simulations to investigate drug-protein interactions (including Nilotinib, Imatinib and dihydroergotamine for 3clpro and Lapatinib, Dexasone and Relategravir for RdRp). Except for Lapatinib, other drugs-complexes were stable during MD simulation. Raltegravir, an anti-HIV drug, was observed to be the best compound against RdRp based on docking binding energy (-9.5 kcal/mole) and MD results. According to the MD results and binding energy, dihydroergotamine is a suitable candidate for 3clpro inhibition (-9.6 kcal/mol). These drugs were classified into several categories, including antiviral, antibacterial, anti-inflammatory, anti-allergic, cardiovascular, anticoagulant, BPH and impotence, antipsychotic, antimigraine, anticancer, and so on. The common prescription-indications for some of these medication categories appeared somewhat in line with manifestations of COVID-19. We hope that they can be beneficial for patients with certain specific symptoms of SARS-CoV-2 infection, but they can also probably inhibit viral enzymes. We recommend further experimental evaluations in vitro and in vivo on these FDA-approved drugs to assess their potential antiviral effect on SARS-CoV-2.

Clinical and demographic characteristics of patients with COVID-19 infection: Statistics from a single hospital in Iran.

Coronavirus disease 2019 (COVID-19) has caused a global pandemic in early 2020. This infectious disorder has a heterogeneous course ranging from asymptomatic disorder to a critical situation needing intensive cares. In the current study, we present a report of affected patients admitted in a single hospital in Iran. Eighty-two hospitalized patients with COVID-19 were assessed. Demographic, clinical, and paraclinical parameters were gathered and statistically analyzed. The median age (IQR) of the patients was 57.32 (45.75, 70) years. At primary evaluation, fever was present in 45.12% of the affected individuals. The most common clinical symptoms were dyspnea (81.71%) and cough (65.85%). Totally, 12 (14.63%) and 14 (17.07%) of patients had low and high WBC counts, respectively. Lymphopenia was detected in 36 (43.9%) of patients, while 6 (7.32%) of patients had lymphocytosis. High levels of Il-6 were detected in 4 (4.88%) of patients. CRP levels were elevated in 69 (84.1%) of patients. The median (IQR) of hospitalization was 7 (5, 9) days. Totally, 26 patients (31%) were hospitalized in ICU. All patients were discharged with good health conditions except for one patient who died. The current study shows the heterogeneous clinical manifestations and paraclinical parameters of COVID-19 patients.

Effects of host genetic variations on response to, susceptibility and severity of respiratory infections.

The recent outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a global crisis, necessitating the identification of genetic factors that modulate the risk of disorder or its severity. The current data about the role of genetic risk factors in determination of rate of SARS-CoV-2 infection in each ethnic group and the severity of disorder is limited. Moreover, several confounding parameters such as the number of tests performed in each country, the structure of the population especially the age distribution, the presence of risk factors for respiratory disorders such as smoking and other environmental factors might be involved in the variability in disease course or prevalence of infection among different ethnic groups. However, assessment of the role of genetic variants in determination of the course of other respiratory infections might help in recognition of possible candidate for further analysis in patients affected with SARS-CoV-2. In the current review, we summarize the data showing the association between genomic variants and risk of acute respiratory distress syndrome, respiratory infections or severity of these conditions with an especial focus on the SARS-CoV-2.

Altered cytokine levels and immune responses in patients with SARS-CoV-2 infection and related conditions.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic in early 2020. The infection has been associated with a wide range of clinical symptoms. In the severely affected patients, it has caused dysregulation of immune responses including over-secretion of inflammatory cytokines and imbalances in the proportion of naïve helper T cells, memory helper T cells and regulatory T cells. Identification of the underlying mechanism of such aberrant function of immune system would help in the prediction of disease course and selection of susceptible patients for more intensive cares. In the current review, we summarize the results of studies which reported alterations in cytokine levels and immune cell functions in patients affected with SARS-CoV-2 and related viruses.