Progression Of Coronavirus Disease 2019 Research Articles

Lipidome is a valuable tool for the severity prediction of coronavirus disease 2019.

To describe the lipid metabolic profile of different patients with coronavirus disease 2019 (COVID-19) and contribute new evidence on the progression and severity prediction of COVID-19. This case-control study was conducted in Peking University Third Hospital, China. The laboratory-confirmed COVID-19 patients aged ≥18 years old and diagnosed as pneumonia from December 2022 to January 2023 were included. Serum lipids were detected. The discrimination ability was calculated with the area under the curve (AUC). A random forest (RF) model was conducted to determine the significance of different lipids. Totally, 44 COVID-19 patients were enrolled with 16 mild and 28 severe patients. The top 5 super classes were triacylglycerols (TAG, 55.9%), phosphatidylethanolamines (PE, 10.9%), phosphatidylcholines (PC, 6.8%), diacylglycerols (DAG, 5.9%) and free fatty acids (FFA, 3.6%) among the 778 detected lipids from the serum of COVID-19 patients. Certain lipids, especially lysophosphatidylcholines (LPCs), turned to have significant correlations with certain immune/cytokine indexes. Reduced level of LPC 20:0 was observed in severe patients particularly in acute stage. The AUC of LPC 20:0 reached 0.940 in discriminating mild and severe patients and 0.807 in discriminating acute and recovery stages in the severe patients. The results of RF models also suggested the significance of LPCs in predicting the severity and progression of COVID-19. Lipids probably have the potential to differentiate and forecast the severity, progression, and clinical outcomes of COVID-19 patients, with implications for immune/inflammatory responses. LPC 20:0 might be a potential target in predicting the progression and outcome and the treatment of COVID-19.

Is it possible to identify COVID-19 infection-related biomarkers during pregnancy?: A prospective study in Turkish population.

The coronavirus disease 2019 (COVID-19) has raised concerns about the potential complications it may cause in pregnant women. Therefore, biomarkers that can predict the course of COVID-19 in pregnant women may be of great benefit as they would provide valuable insights into the prognosis and, thus, the management of the disease. In this context, the objective of this study is to identify the biomarkers that can predict COVID-19 progression in pregnant women, focusing on composite hemogram parameters and systemic inflammatory and spike markers. The population of this single-center prospective case-control study consisted of all consecutive pregnant women with single healthy fetuses who tested positive for COVID-19 and who were admitted to Bakirköy Dr Sadi Konuk Training and Research Hospital in Istanbul, Turkey, a COVID-19 referral hospital, between April 2020 and March 2021, with an obstetric indication, during their second or third trimester. The control group consisted of consecutive pregnant women with a single healthy fetus who were admitted to the same hospital within the same date range, had demographic and obstetric characteristics matching the patient group, but tested negative for COVID-19. The patient and control groups were compared in terms of platelet-to-lymphocyte ratio (PLR), platelet-to-neutrophil ratio (PNR), and neutrophil-to-lymphocyte ratio (NLR), and systemic inflammatory and spike markers, including C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-10 (IL-10), cluster of differentiation 26 (CD26), and B7 homolog 4 (B7H4). There were 45 (51.1%) and 43 (48.8%) pregnant women in the patient and control groups, respectively. There was no significant difference between the groups in demographic and obstetric characteristics (P > .05). The PNR, PLR, and CRP values were significantly higher in the patient group than in the control group (P < .05). On the other hand, there was no significant difference between the groups in IL-6, IL-10, CD26, and B7H4 levels (P > .05). The findings of our study showed that specific inflammatory markers, such as CRP, PLR, and PNR, can potentially predict the course of COVID-19 in pregnant women. However, more comprehensive, well-controlled studies are needed to corroborate our study's findings and investigate other potential inflammatory markers.

The correlation between neutrophil lymphocyte ratio in pregnant women with COVID-19 and neonatal outcome

Background and objectives. Coronavirus Disease 2019 (COVID-19) in pregnancy periods can adversely affect the neonatal outcomes. Neutrophil Lymphocyte Ratio (NLR) were reported as sensitive markers and good predictor of COVID-19 progression in symptomatic pregnant women. The aim of this study to find correlation on NLR value of the pregnant women with COVID-19 to the neonatal outcome. Materials and methods. We retrospectively included neonates who was delivered from pregnant women with COVID-19 at Dr. Soetomo Hospital from June 2021 to July 2022. NLR value of the pregnant women were calculated. Demographic data and clinical characteristic were taken from medical records. The diagnosis of COVID-19 in pregnant women is confirmed by PCR nasopharyngeal swab, as well as in the neonates who undergo nasopharyngeal swab a maximum of 24 hours after birth. Results. Total of 1058 births delivered between June 2021- July 2022, 224 neonates (21.17%) met inclusion criteria. We analyzed the severity of maternal factors described by NLR and correlated with neonate outcomes, such as mortality, Apgar Score (AS), birth weight, gestational age, type of delivery and Polymerase Chain Reaction (PCR) swab of the neonates. the results of our analysis, the maternal NLR was correlated with the birth weight (p=0.005). However, NLR of the pregnant women are not correlated with mortality of the neonates (p=0.681), type of delivery (p= 1), AS at 1 minute (p= 0.158), AS at 5 minutes (p= 0.158), gestational age (p= 0.110) length of stay (LOS) (p=0,258) and PCR swab of the neonates (p= 1). Conclusions. NLR value in the majority of pregnant women with COVID-19 was found to be increasing, but these results are not related for the neonatal outcome except the birth weight.

Retrospective study of the impact of diabetes on the severity and prognosis of COVID‑19.

Patients with diabetes coexisting with viral infection tend to have poor outcomes, but the association between diabetes and coronavirus disease 2019 (COVID-19) prognosis is controversial at present. The present study reviewed and analyzed the data of 1,892 patients with COVID-19 admitted to Shaanxi Provincial People's Hospital (Xi'an, China). Demographic, clinical, laboratory and treatment data as well as clinical outcomes were extracted from the electronic medical records and compared between patients with and without diabetes. Multivariate logistic regression analysis was used to determine the risk factors affecting the prognosis of COVID-19. Compared with patients without diabetes, the levels of glucose, C-reactive protein, procalcitonin, creatinine, total bilirubin and plasma D-dimer were significantly increased in patients with diabetes, while the levels of lymphocytes and albumin were significantly decreased (P<0.05). Multivariate logistic regression analysis revealed that platelet count, albumin, total bilirubin and lymphocytes were significantly correlated with the severity of COVID-19. Diabetes mellitus was an independent prognostic factor that affected the mortality outcome of patients with COVID-19. Additionally, an age of ≥80 years, male sex, cerebral infarction complications and a critical diagnosis of COVID-19 at admission were risk factors for critical illness during hospitalization. The results of the present study suggest that diabetes may be a risk factor for the rapid progression and poor prognosis of COVID-19. Therefore, further attention should be paid to individuals with diabetes in order to prevent rapid deterioration.

High-resolution short-term prediction of the COVID-19 epidemic based on spatial-temporal model modified by historical meteorological data

In the global challenge of Coronavirus disease 2019 (COVID-19) pandemic, accurate prediction of daily new cases is crucial for epidemic prevention and socioeconomic planning. In contrast to traditional local, one-dimensional time-series data-based infection models, the study introduces an innovative approach by formulating the short-term prediction problem of new cases in a region as multidimensional, gridded time series for both input and prediction targets. A spatial-temporal depth prediction model for COVID-19 (ConvLSTM) is presented, and further ConvLSTM by integrating historical meteorological factors (Meteor-ConvLSTM) is refined, considering the influence of meteorological factors on the propagation of COVID-19. The correlation between 10 meteorological factors and the dynamic progression of COVID-19 was evaluated, employing spatial analysis techniques (spatial autocorrelation analysis, trend surface analysis, etc.) to describe the spatial and temporal characteristics of the epidemic. Leveraging the original ConvLSTM, an artificial neural network layer is introduced to learn how meteorological factors impact the infection spread, providing a 5-day forecast at a 0.01° × 0.01° pixel resolution. Simulation results using real dataset from the 3.15 outbreak in Shanghai demonstrate the efficacy of Meteor-ConvLSTM, with reduced RMSE of 0.110 and increased R2 of 0.125 (original ConvLSTM: RMSE = 0.702, R2 = 0.567; Meteor-ConvLSTM: RMSE = 0.592, R2 = 0.692), showcasing its utility for investigating the epidemiological characteristics, transmission dynamics, and epidemic development.

Zinc deficiency is a potential risk factor for COVID-19 progression to pneumonia requiring oxygen therapy

IntroductionVarious risk factors for developing severe coronavirus disease 2019 (COVID-19) have been reported. However, studies on the nutritional-related risk factors are limited. In this study, we investigated the effects of serum zinc deficiency on the severity of COVID-19. MethodsThe study included a total of 60 COVID-19 patients who were admitted to Tsuyama Chuo Hospital between March 2020 and April 2021. We divided the patients into two categories based on serum levels of zinc (normal and latent zinc deficiency vs. zinc deficiency [<60 μg/dL]) at the time of diagnosis. Severity of COVID-19 was defined as the most exaggerated disease status during admission. The associations between serum zinc deficiency and the severity of COVID-19 were examined using a logistic regression model adjusted for potential confounders. ResultsPatients who required oxygen therapy had a higher prevalence of comorbidities and poorer nutritional status, including zinc deficiency, than those who did not require oxygen therapy. Zinc deficiency was associated with an increased risk of COVID-19 severity, with an adjusted odds ratio of 7.29 (95% confidence interval: 1.70–31.18). This result remained significant in the sensitivity analyses conducted after adjusting for patient background factors. ConclusionsZinc deficiency at the time of COVID-19 diagnosis is an independent risk factor for severe disease. Our findings need to be validated in external studies.

Stimulation of PSTPIP1 to trigger proinflammatory responses in asymptomatic SARS-CoV-2 infections

BackgroundA hyperinflammatory response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection gravely worsens the clinical progression of coronavirus disease 2019 (COVID-19). Although the undesirable effects of inflammasome activation have been correlated to the severity of COVID-19, the mechanisms of this process in the asymptomatic infection and disease progression have not yet been clearly elucidated. MethodsWe performed strand-specific RNA sequencing in 39 peripheral blood mononuclear cell (PBMC) samples from asymptomatic individuals（n = 10）, symptomatic patients（n = 16） and healthy donors（n = 13）. ResultsDysregulation of pyrin inflammasomes along with the proline-serine-threonine phosphatase-interacting protein 1 (PSTPIP1) gene was identified in SARS-COV-2 infection. Notably, the PSTPIP1 expression level showed a significant negative correlation with an adjacent long-noncoding RNA (lncRNA) RP11-797A18.6 in the asymptomatic individuals compared with the healthy controls. In addition, a decline in the nuclear factor kappa B subunit 1 (NFKB1) gene expression was observed in asymptomatic infection, followed by a rise in the mild and moderate disease stages, suggesting that altered NFKB1 expression and associated proinflammatory signals may trigger a disease progression. ConclusionsOverall, our results indicate that PSTPIP1-dependent pyrin inflammasomes-mediated pyroptosis and NF-κB activation might be potential preventive targets for COVID-19 disease development and progression.

Elevated hyaluronic acid levels in severe SARS-CoV-2 infection in the post-COVID-19 era.

Human identical sequences of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) promoted the coronavirus disease 2019 (COVID-19) progression by upregulating hyaluronic acid (HA) via NamiRNA-enhancer network, based on previous experimental research. This study aimed to investigate the predictive value of HA for the severity of SARS-CoV-2 infection in the post-COVID-19 era. A total of 217 consecutive patients with COVID-19 were enrolled at Beijing Ditan Hospital between July 2023 and October 2023. HA levels were analyzed using biochemical detector. Logistic regression analysis was used to screen independent factors for severe COVID-19. The predictive performance of HA for severe infection was assessed by ROC curve. Furthermore, the relationship between HA levels and COVID-19 severity was investigated using multivariate logistic regression models after adjustment for potential confounders. According to the cut-off value of HA, COVID-19 patients were divided into HA < 90 ng/mL group (80 cases) and HA ≥ 90 ng/mL group (137 cases). High HA levels were positively associated with the severe SARS-CoV-2 infection, including elevated inflammatory indicators, severe lung involvement, prolonged clinical course, and higher incidence of respiratory failure and death (P < 0.05). Logistic regression analysis suggested that HA was an independent predictor of severe COVID-19 (OR = 4.540, 95% CI = 2.105-9.790, P < 0.001). ROC curve analysis showed that the AUC of HA for severe infection was 0.724. HA levels were significantly higher in COVID-19 cases compared to the healthy population (123.9 (82.6, 174.1) vs. 50.5 (37.8, 66.8), P < 0.001), but similar to those with non-SARS-CoV-2 lung infection (121.6 (78.5, 175.6) vs. 106.0 (66.5, 149.7), P = 0.244). We also found that the first COVID-19 infections had higher HA levels (118.8 (79.5, 174.3) vs. 85.0 (61.1, 128.8), P < 0.001) and a higher proportion of severe infection (37.1% vs. 21.3%, P = 0.043) than re-infections. However, HA expression failed to fully return to normal levels with infection recovery (204.7 (152.9, 242.2) vs. 97.0 (69.3, 137.3), P < 0.001). HA was associated with severe SARS-CoV-2 infection and could be used as a novel serum biomarker to predict the risk of COVID-19 progression in the post-COVID-19 era.

Indicators of stress hematopoiesis in the blood predict COVID-19 progression in patients over 65 years old

ABSTRACT Objectives Advanced age is a well-established risk factor for severe coronavirus disease 2019 (COVID-19). Exacerbated inflammation affects multiple organs, among which hematopoiesis responds by increased output of various cells. We aimed to determine the association between COVID-19 progression and large immature cell (LIC) counts, changes in erythrocyte and platelet distribution widths (RDW, PDW) with reference to patients’ age. Methods A total of 755 patients with complete blood cell (CBC) analysis in the first 24 h of hospitalization were enrolled. Patients were divided into two groups: under and above 65 years of age. Results The LIC counts were different in both groups (p < 0.003). However, only the senior patients had markedly different values of RDW and PDW (p < 0.001). The receiver operating characteristic (ROC) curve analysis provided increased LIC (AUC = 0.600), RDW (AUC = 0.609), PDW (AUC = 0.556), and platelet to LIC ratio (AUC = 0.634) as significant in discriminating outcome in the older group. Importantly, these results were not repeated in the younger patients. In the elderly, the progression was predicted with LIC cut-off at ≥ 0.305 × 109/L (OR = 3.166) and RDW over 12.15% (OR = 2.081). Discussion Aging is characterized by a decline in immunological competence with a compromised control of inflammation leading to a proinflammatory state. This background together with the actions of pathogens may lead to emergency myelopoiesis. Conclusion Our results point to the important differences between age groups regarding CBC-related parameters of stress hematopoiesis during severe infection. Higher LIC, RDW and PDW levels were reliable in the early identification of COVID-19 progression only in the elderly.

Description of Thorax X-ray and Brixia Score in Pregnancy with COVID-19 Infection

BACKGROUND: Based on data until December 31, 2020, confirmed cases of coronavirus disease 2019 (COVID-19) have been reached nearly 750,000 cases, COVID-19 can infect pregnant women because a reduction in the immune receptor and increase in another pro-inflammatory factor. Complications include fetal distress, premature rupture of membranes, fetal death, chorioamnionitis, preeclampsia, sepsis, renal failure, and disseminated intravascular coagulation. A serial chest X-ray is used as a basis for assessing COVID-19 progression. An experimental study in Italy proposed a scoring system known as the Brixia score divides the chest X-ray image posteroanterior or anteroposterior into 3 zones, namely, the upper, middle, and lower zones labeled as A to F, then assess the abnormalities that exist in each area with a score of 0–3, a score of ranges from 0 to 18. This score can be used to assess the severity of symptoms suffered by confirmed patients and determine the patient’s prognosis. AIM: This study aims to determine the characteristics of the chest X-ray and Brixia score in pregnancy with COVID-19 infection. METHODS: This descriptive research aims to describe the characteristics of the chest X-ray and the Brixia score in pregnancy with COVID-19 infection in pregnancy at the Department/KSM Obstetrics and Gynecology FK Udayana/Sanglah Hospital, Denpasar. This research carried out from April 2020 to March 2021. The sample of this study was all pregnant women with confirmed COVID-19 at Sanglah Hospital Denpasar during the period April 2020–March 2021. Data collected are all pregnant women who are confirmed to have COVID-19 and met the inclusion and exclusion criteria of the study. Data recorded and data tabulation is carried out according to characteristics that have been determined, then data processing is carried out descriptive. RESULTS: In pregnant patients with confirmed COVID-19 in the period from April 2020 to March 2021, there were 95 people. The highest proportion of mothers pregnant with COVID-19 infection performs antenatal care checks at midwives and Obstetric Gynecologist (47.4%) with age 20–35 years (86.3%), primipara (41.1%), age term pregnancy (74.7%), and using the abdominal method for delivery (87.4%). X-ray results that it was found that from 95 pregnant women, there were 56 pregnant women with thorax abnormal and 39 with normal conditions. The highest proportion of the X-ray results was obtained pregnant with COVID-19 infection with abnormal thorax consolidation lesions found (94.6%) and the distribution of the lesions on the right lung side (39.3%). Based on the cross-tabulated analysis, it can be seen that the consolidation lesion is found in all Brixia scores with the highest proportion in the 0–5 category, which is 80.3%. Results chest X-ray of pregnant women with COVID-19 infection with Brixia score 0–5 had the same values including pleural effusion lesions 1.8%, pulmonary edema 1.8%, and fibrotic by 1.8%. CONCLUSION: Following conclusions can be drawn: Overview of the characteristics of pregnant women with the most COVID-19 infections is at the age of 20–35 years with a primiparous pregnancy. Gestational age term gave birth by the abdominal method; abnormal chest X-ray images are more often found in patients with COVID-19 in pregnancy with consolidated lesions as well as diffuse distribution mostly on the right side of the lung; Brixia score in pregnancy with COVID-19 infection with proportion the highest is in parameter 0–5 as much as 85.7%.

Plasma of COVID-19 Patients Does Not Alter Electrical Resistance of Human Endothelial Blood-Brain Barrier In Vitro

Abstract The pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 instigated the most serious global health crisis. Clinical presentation of COVID-19 frequently includes severe neurological and neuropsychiatric symptoms. However, it is presently unknown whether and to which extent pathological impairment of blood-brain barrier (BBB) contributes to the development of neuropathology during COVID-19 progression. In the present study, we used human induced pluripotent stem cells-derived brain endothelial cells (iBECs) to study the effects of blood plasma derived from COVID-19 patients on the BBB integrity in vitro. We also performed a comprehensive analysis of the cytokine and chemokine profiles in the plasma of COVID-19 patients, healthy and recovered individuals. We found significantly increased levels of interferon γ-induced protein 10 kDa, hepatocyte growth factor, and interleukin-18 in the plasma of COVID-19 patients. However, blood plasma from COVID-19 patients did not affect transendothelial electrical resistance in iBEC monolayers. Our results demonstrate that COVID-19-associated blood plasma inflammatory factors do not affect BBB paracellular pathway directly and suggest that pathological remodeling (if any) of BBB during COVID-19 may occur through indirect or yet unknown mechanisms.

Quantitative Computed Tomography Lung COVID Scores with Laboratory Markers: Utilization to Predict Rapid Progression and Monitor Longitudinal Changes in Patients with Coronavirus 2019 (COVID-19) Pneumonia.

Coronavirus disease 2019 (COVID-19), is an ongoing issue in certain populations, presenting rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression using radiographic scores and laboratory markers and present longitudinal changes. This retrospective study included 218 COVID-19 pneumonia patients admitted at the Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring mechanical ventilation within one week of hospitalization. Quantitative COVID (QCOVID) scores were derived from high-resolution computed tomography (CT) analyses: (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). Laboratory data, including inflammatory markers, were obtained from electronic medical records. Rapid progression was observed in 9.6% of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (AUC = 0.813). In multivariate analyses, the QMD score and interleukin(IL)-6 level were important predictors for rapid progression (AUC = 0.864). With >2 months follow-up CT, remained lung lesions were observed in 21 subjects, even after several weeks of negative reverse transcription polymerase chain reaction test. AI-driven quantitative CT scores in conjugation with laboratory markers can be useful in predicting the rapid progression and monitoring of COVID-19.

Impact of prior use of antiplatelets on COVID-19 susceptibility, progression, and severity: a population-based study

Introduction and objectivesHypercoagulability and thromboembolism are processes that arise from severe acute respiratory syndrome coronavirus 2 infection and are responsible for a high degree of coronavirus disease 2019 (COVID-19)-related morbidity and mortality. This study sought to assess the effect of antiplatelet drugs on COVID-19 severity (risk of hospitalization and mortality), susceptibility to severe acute respiratory syndrome coronavirus 2 infection, and progression to severe COVID-19. MethodsWe conducted a population-based case-control study in a northwestern region of Spain in 2020. The study involved 3060 participants with a positive polymerase chain reaction test who were hospitalized, 26 757 participants with a positive polymerase chain reaction test who were not hospitalized, and 56 785 healthy controls. ResultsTriflusal seemed to be associated with a significant increase in risk of hospitalization (aOR, 1.97; 95%CI, 1.27-3.04) and susceptibility to infection (OR, 1.45; 95%CI, 1.07-1.96). It also appeared to lead to a nonsignificant increase in the risk of mortality (OR, 2.23; 95%CI, 0.89-5.55) and/or progression to more severe disease stages (OR, 1.42; 95%CI, 0.8-2.51). Aspirin seemed to be associated with a statistically significant decrease in susceptibility to severe acute respiratory syndrome coronavirus 2 infection (OR, 0.92; 95%CI, 0.86-0.98). ConclusionsTriflusal use appears to increase the risk of susceptibility to COVID-19 infection and an even higher risk of hospitalization, whereas the other antiplatelets could be associated with a reduction in the risk of the various outcomes or have no effect on risk. These findings could support reconsideration of triflusal prescription in COVID-19 pandemic situations.

Global properties of delayed models for SARS-CoV-2 infection mediated by ACE2 receptor with humoral immunity

&lt;abstract&gt;&lt;p&gt;The coronavirus disease 2019 (COVID-19) is caused by a new coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 infects the epithelial (target) cells by binding its spike protein, S, to the angiotensin-converting enzyme 2 (ACE2) receptor on the surface of epithelial cells. During the process of SARS-CoV-2 infection, ACE2 plays an important mediating role. In this work, we develop two models which describe the within-host dynamics of SARS-CoV-2 under the effect of humoral immunity, and considering the role of the ACE2 receptor. We consider two discrete (or distributed) delays: (ⅰ) Delay in the SARS-CoV-2 infection of epithelial cells, and (ⅱ) delay in the maturation of recently released SARS-CoV-2 virions. Five populations are considered in the models: Uninfected epithelial cells, infected cells, SARS-CoV-2 particles, ACE2 receptors and antibodies. We first address the fundamental characteristics of the delayed systems, then find all possible equilibria. On the basis of two threshold parameters, namely the basic reproduction number, $ \Re_{0} $, and humoral immunity activation number, $ \Re_{1} $, we prove the existence and stability of the equilibria. We establish the global asymptotic stability for all equilibria by constructing suitable Lyapunov functions and using LaSalle's invariance principle. To illustrate the theoretical results, we perform numerical simulations. We perform sensitivity analysis and identify the most sensitive parameters. The respective influences of humoral immunity, time delays and ACE2 receptors on the SARS-CoV-2 dynamics are discussed. It is shown that strong stimulation of humoral immunity may prevent the progression of COVID-19. It is also found that increasing time delays can effectively decrease $ \Re_{0} $ and then inhibit the SARS-CoV-2 replication. Moreover, it is shown that $ \Re_{0} $ is affected by the proliferation and degradation rates of ACE2 receptors, and this may provide worthy input for the development of possible receptor-targeted vaccines and drugs. Our findings may thus be helpful for developing new drugs, as well as for comprehending the dynamics of SARS-CoV-2 infection inside the host.&lt;/p&gt;&lt;/abstract&gt;

Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach.

The coronavirus disease 2019 (COVID-19) pandemic, stemming from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has persistently threatened the global health system. Meanwhile, tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) still continues to be endemic in various regions of the world. There is a certain degree of similarity between the clinical features of COVID-19 and TB, but the underlying common pathogenetic processes between COVID-19 and TB are not well understood. To elucidate the common pathogenetic processes between COVID-19 and TB, we implemented bioinformatics and systematic research to obtain shared pathways and molecular biomarkers. Here, the RNA-seq datasets (GSE196822 and GSE126614) are used to extract shared differentially expressed genes (DEGs) of COVID-19 and TB. The common DEGs were used to identify common pathways, hub genes, transcriptional regulatory networks, and potential drugs. A total of 96 common DEGs were selected for subsequent analyses. Functional enrichment analyses showed that viral genome replication and immune-related pathways collectively contributed to the development and progression of TB and COVID-19. Based on the protein-protein interaction (PPI) network analysis, we identified 10 hub genes, including IFI44L, ISG15, MX1, IFI44, OASL, RSAD2, GBP1, OAS1, IFI6, and HERC5. Subsequently, the transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory network identified 61 TFs and 29 miRNAs. Notably, we identified 10 potential drugs to treat TB and COVID-19, namely suloctidil, prenylamine, acetohexamide, terfenadine, prochlorperazine, 3'-azido-3'-deoxythymidine, chlorophyllin, etoposide, clioquinol, and propofol. This research provides novel strategies and valuable references for the treatment of tuberculosis and COVID-19.

Neutralizing monoclonal antibodies for the prevention of severe COVID-19: a retrospective study during Omicron BA.1 variant surge

Among treatment options for Coronavirus disease 2019 (COVID-19), monoclonal antibodies (mAbs) showed to be effective in preventing disease progression, but real-world data during the Omicron variant surge are still lacking. Multicentre retrospective study evaluating the effectiveness of sotrovimab and casirivimab-imdevimab in fragile patients with mild SARS-CoV-2 infection between November 2021 and March 2022. Unfavourable outcome was defined as increased need for oxygen supplementation and/or death. Of 268 study-participants, 12 (4.48%) previously needed supplemental oxygen, while 6 (2.24%) had active solid neoplasia (2.24%); 186 (69%) have previously received SARS-CoV-2 vaccination. Overall, 22 (8%) had unfavourable outcomes (42% versus 6% of patients with and without previous oxygen need and 50% versus 7% of patients with and without active solid neoplasia). Both supplemental oxygen therapy before SARS-CoV-2 infection and solid malignant tumour have shown to be risk factors for treatment failure. Log-rank test did not identify differences between sotrovimab and casirivimab-imdevimab treatment. Despite diffusion of Omicron variant, the rate of unfavourable outcome was higher than expected. The presence of underlying risk factors, including solid cancer and previous oxygen therapy are independently associated with risk of COVID-19 progression, suggesting the need for antiviral treatments not limited to mAbs and implementation of vaccine campaign.

The immune inflammation factors associated with disease severity and poor prognosis in patients with COVID-19: A retrospective cohort study

Coronavirus disease 2019 (COVID-19) is associated with immune dysregulation and cytokine storm. It is essential to explore the immune response characteristics of peripheral circulation in COVID-19 patients to reveal pathogenesis and predict disease progression. In this study, the levels of total immunoglobulins (IgG, IgM, IgA), complement (C3, C4)，lymphocyte subsets (CD3+ cell，CD4+ cell，CD8+ cell, NK cell, CD19+ cell and CD45+ cell) and cytokines (IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-17, IL-12p, IL-1β, TNF-α, IFN-α and IFN-γ) were retrospectively analyzed in COVID-19 patients. A total of 513 patients were enrolled in this study, cases were distributed according to clinical status as mild or moderate (n = 212), severe survivors (n = 197) and severe non-survivors (n = 104). IL-6, IL-8, IL-10 and IFN-γ were increased in severe patients compared with non-severe patients, despite decreased CD45+ cell, CD3+ cell, CD4+ cell, CD8+ cell, CD19+ cell, and NK cell. Compared with severe survivors, the levels of L-6, IL-8 and IL-10 in non-survivors increased significantly, and levels of C3, CD45+ cell, CD3+ cell，CD4+ cell，CD8+ cell, and NK cell decreased. Moreover, age, IL-8, IL-10, CD8+cells and NK cell were independent risk factors for the severity of COVID-19. Multivariable regression showed increasing odds ratio of in-hospital death associated with tumor, older age, higher IL-8 level, and decreasing odds ratio of in-hospital death associated with increased levels of CD8+cell and NK cell. Finally, patients with tumor, or high IL-6 or high IL-10 expression and lower CD8+ or lower NK levels exhibited a significantly shorter survival time. In conclusion, our study provides findings of the immunological characteristics associated with disease severity to predict the progression of COVID-19. The immune inflammation factors, such as IL-6, IL-8, IL-10, CD8+ cell and NK cell, could serve as excellent biomarkers for monitoring or predicting COVID-19 progression therapeutic to COVID-19 patients.

Assessment of some hematological factors in patients with COVID-19 and vaccinated individuals in Kirkuk city

Abstract Background: The severe acute respiratory syndrome-coronavirus-2 (SARS-COV-2), which is considered to be the main reason of coronavirus disease-2019 (COVID-19), initiates a multisystem inflammatory condition. The COVID-19 progression is thought to be influenced by hematological abnormalities. A complete blood count (CBC) is a repeatedly used, reasonably priced, and promptly performed testing technique that may be helpful in those processes. The predominance of deep vein thrombosis and pulmonary embolism is determined by d-dimer values. Objective: The aim of this study was to assess the hematological factors in patients with COVID-19 and vaccinated individuals in Kirkuk city. Subject and Methods: Samples were taken from 167 participants aged 20 to 45 years, including men and women, from December 2021 to March 2022; these samples were taken randomly from patients with COVID-19 who were hospitalized and nonhospitalized, those who had received vaccine, and a control group (healthy people who do not have diseases). Samples of nasopharyngeal swabs were also collected from outpatients infected with COVID-19, and the infection was verified using real-time polymerase chain reaction (PCR). Also, PCR was done for control group and performed CBC and d-dimer tests for all samples. Results: Concerning to hematological tests, the outcomes have revealed significant results between study groups with WBC (P &lt; 0.0001), RBC (P &lt; 0.0001), lymphocyte (P &lt; 0.0001), granulocyte (P &lt; 0.0001), HB (P &lt; 0.0001), HCT (P &lt; 0.0001), MCH (P &lt; 0.0017), PLT (P &lt; 0.0455), and d-dimer (P &lt; 0.0001). Conclusion: Patients with COVID-19 have a reliable pattern of CBC parameter changes and normal values in the vaccinated individual.

Active ingredient and mechanistic analysis of traditional Chinese medicine formulas for the prevention and treatment of COVID-19: Insights from bioinformatics and in vitro experiments.

Coronavirus disease 2019 (COVID-19) is an acute infectious disease caused by a novel coronavirus. Traditional Chinese medicine (TCM) has been proven to have a potential curative effect on COVID-19. This study preliminarily analyzed the existing TCM prescription's key components and action mechanisms for preventing and treating COVID-19 using bioinformatic and experimental methods. Association and clustering analysis reveals that the "HQ + FF + BZ" drug combination had a strong correlation and confidence in 93 TCM prescriptions and may affect the progression of COVID-19 through inflammatory pathways such as the TNF signaling pathway. Further molecular docking revealed that quercetin has a higher affinity for IL6 and IL10 in the TNF signaling pathway associated with COVID-19. In vitro experiments demonstrated that quercetin could effectively reduce the levels of the inflammatory factor IL-6 and increase the anti-inflammatory factor IL-10, alleviating inflammation impact on cells. Our results provide a new understanding of the molecular mechanism of TCM prevention and treatment of COVID-19, which is helpful to the development of new diagnosis and treatment schemes for COVID-19.

The correlation of lymphocytes with disease progression of COVID-19.

The aim of this study is to evaluate the potential of lymphocytes as biomarkers to predict the decline of coronavirus disease 2019 (COVID-19). Lymphocytes were counted in 164 moderate COVID-19 patients in Shenzhen, China. Among the moderate infected patients, 12.2% (20/164) progressed to severe cases after admission. Compared with the stable patients, the counts of lymphocytes, both total T lymphocytes and CD4+ T lymphocytes, in the severe patients, were lower. The aggravation of moderate infected patients was significantly associated with lymphocyte count (hazard ratio [HR] = 0.91; 95% confidence interval [CI]: 0.84-0.99), total T lymphocyte count (HR = 0.91; 95% CI: 0.84-0.99), and CD4+ T lymphocyte count (HR = 0.91; 95% CI: 0.85-0.98). Total T lymphocytes and CD4+ T lymphocytes could be important biomarkers to evaluate the risk of aggravation for moderate infected COVID-19 patients. The patients with low percentages of total T lymphocytes and CD4+ T lymphocytes need more attention.