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LC-MS/MS: A sensitive and selective analytical technique to detect COVID-19 protein biomarkers in the early disease stage
Abstract
Introduction:
The COVID-19 outbreak has put enormous pressure on the scientific community to detect infection rapidly, identify the status of disease severity, and provide an immediate vaccine/drug for the treatment. Relying on immunoassay and a real-time reverse transcription polymerase chain reaction (rRT-PCR) led to many false-negative and false-positive reports. Therefore, detecting biomarkers is an alternative and reliable approach for determining the infection, its severity, and disease progression. Recent advances in liquid chromatography and mass spectrometry (LC-MS/MS) enable the protein biomarkers even at low concentrations, thus facilitating clinicians to monitor the treatment in hospitals.
Areas covered:
This review highlights the role of LC-MS/MS in identifying protein biomarkers and discusses the clinically significant protein biomarkers such as Serum amyloid A, Interleukin-6, C-Reactive Protein, Lactate dehydrogenase, D-dimer, cardiac troponin, ferritin, Alanine transaminase, Aspartate transaminase, gelsolin and galectin-3-binding protein in COVID-19, and their analysis by LC-MS/MS in the early stage.
Expert opinion:
Clinical doctors monitor significant biomarkers to understand, stratify, and treat patients according to disease severity. Knowledge of clinically significant COVID-19 protein biomarkers is critical not only for COVID-19 caused by the coronavirus but also to prepare us for future pandemics of other diseases in detecting by LC-MS/MS at the early stages.
Coronavirus disease of 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an ongoing outbreak, disrupting human life worldwide. Vaccine development was prioritized to obtain a biological substance for combating the viral pathogen and lessening disease severity. In vaccine production, biological origin and relevant materials must be carefully examined for potential contaminants in conformity with good manufacturing practice. Due to fast mutation, several SARS-CoV-2 variants and sublineages have been identified. Currently, most of COVID-19 vaccines are developed based on the protein sequence of the Wuhan wild type strain. New vaccines specific for emerging SARS-CoV-2 strains are continuously needed to tackle the incessant evolution of the virus. Therefore, in vaccine development and production, a reliable method to identify the nature of subunit vaccines is required to avoid cross-contamination. In this study, liquid chromatography-mass spectrometry using quadrupole-time of flight along with tryptic digestion was developed for distinguishing protein materials derived from different SARS-CoV-2 strains. After analyzing the recombinantly produced receptor-binding domain (RBD) of the SARS-CoV-2 spike protein, nine characteristic peptides were identified with acceptable limits of detection. They can be used together to distinguish 14 SARS-CoV-2 strains, except Kappa and Epsilon. Plant-produced RBD-Fc protein derived from Omicron strains can be easily distinguished from the others with 4–5 unique peptides. Eventually, a peptide key was developed based on the nine peptides, offering a prompt and precise flowchart to facilitate SARS-CoV-2 strain identification in COVID-19 vaccine manufacturing.
The D-dimer is a sensitive indicator of coagulation and fibrinolysis activation, especially valuable as a biomarker of intravascular thrombosis. Measurement of plasma D-dimer levels plays a crucial role in the diagnosis and monitoring of conditions such as deep vein thrombosis, pulmonary embolism, and disseminated intravascular coagulation. A variety of immunoassays, including enzyme-linked immunosorbent assays, latex-enhanced immunoturbidimetric assays, whole-blood aggregation analysis, and immunochromatography assays, are widely used in clinical settings to determine D-dimer levels. However, the results obtained from different D-dimer assays vary significantly. These assays exhibit intra-method coefficients of variation ranging from 6.4% to 17.7%, and the measurement discrepancies among different assays can be as high as 20-fold. The accuracy and reliability of D-dimer testing cannot be guaranteed due to the lack of an internationally endorsed reference measurement system (including reference materials and reference measurement procedures), which may lead to misdiagnosis and underdiagnosis, limiting its full clinical application. In this review, we present an in-depth analysis of clinical D-dimer testing, summarizing the existing challenges, the current state of metrology, and progress towards harmonization. We also review the latest advancements in D-dimer detection techniques, which include mass spectrometry and electrochemical and optical immunoassays. By comparing the basic principles, the definition of the measurand, and analytical performance of these methods, we provide an outlook on the potential improvements in D-dimer clinical testing.
Curcuma wenyujin is a member of the Curcuma zedoaria (zedoary, Zingiberaceae) family, which has a long history in traditional Chinese medicine (TCM) due to its abundant biologically active constituents. Curcumenol, a component of Curcuma wenyujin, has several biological activities. At present, despite different pharmacological activities being reported, the clinical usage of curcu-menol remains under investigation. To further determine the characteristics of curcumenol, the extraction , determination, and bioactivity of the compound are summarized in this review. Existing research has reported that curcumenol exerts different pharmacological effects in regard to a variety of diseases, including anti-inflammatory, anti-oxidant, anti-bactericidal, anti-diabetic, and anti-cancer activity, and also ameliorates osteoporosis. This review of curcumenol provides a theoretical basis for further research and clinical applications.
In silico tool is the flourishing pathway for Researchers and budding chemists to strain the analytical data in a snapshot. Traditionally, drug research has heavily relied on labor-intensive experiments, often limited by time, cost, and ethical constraints. In silico tools have paved the way for more efficient and cost-effective drug development processes. By employing advanced computational algorithms, these tools can screen large libraries of compounds, identifying potential toxicities and prioritizing safer drug candidates for further investigation. Integrating in silico tools into the drug research pipeline has significantly accelerated the drug discovery process, facilitating early-stage decision-making and reducing the reliance on resource-intensive experimentation. Moreover, these tools can potentially minimize the need for animal testing, promoting the principles of the 3Rs (reduction, refinement, and replacement) in animal research. This paper highlights the immense potential of in silico tools in revolutionizing drug research. By leveraging computational models to predict drug metabolism, pharmacokinetics, and toxicity. Researchers can make informed decisions and prioritize the most promising drug candidates for further investigation. The synchronicity of In silico tools in this article on trending topics is insightful and will play an increasingly integral role in expediting drug development.
C-reactive protein (CRP) is an acute-phase protein which is synthesized by the liver in response to the secretion of several inflammatory cytokines including interleukin 6 (IL-6), IL-1 and tumor necrosis factor (TNF). CRP was the first acute-phase protein to be described and adopted in clinical laboratories as an exquisitely sensitive systemic marker of inflammation and tissue damage. The measurement of CRP is widely used for the diagnosis and monitoring of inflammatory conditions, including sepsis, trauma, and malignancies. In the last decades, impressive advances in analytical methods (from qualitative to high-sensitivity assays), automation and availability of results in a short time, not only translated in an increasing demand for the right management of systemic inflammatory diseases, but also in evaluating subclinical inflammatory processes underlying atherothrombotic events. CRP measurement is one of the most requested laboratory tests for both the wide range of clinical conditions in which it may assure a valuable information and some analytical advantages due to the evidence that it is a "robust biomarker". Even recently, the measurement of CRP received new interest, particularly as a biomarker of severity of Coronavirus disease 2019 (COVID-19), and it deserves further concern for improving demand appropriateness and result interpretation.
Cytokine dynamics in patients with coronavirus disease 2019 (COVID-19) have been studied in blood but seldomly in respiratory specimens. We studied different cell markers and cytokines in fresh nasopharyngeal swab specimens for the diagnosis and for stratifying the severity of COVID-19. This was a retrospective case-control study comparing Myeloperoxidase (MPO), Adenosine deaminase (ADA), C-C motif chemokine ligand 22 (CCL22), Tumour necrosis factor alpha (TNFα) and Interleukin-6 (IL-6) mRNA expression in 490 (327 patients and 163 control) nasopharyngeal specimens from 317 (154 COVID-19 and 163 control) hospitalized patients. Of the 154 COVID-19 cases, 46 died. Both total and normalized MPO, ADA, CCL22, TNFα, and IL-6 mRNA expression levels were significantly higher in the nasopharyngeal specimens of infected patients when compared with controls, with ADA showing better performance (OR 5.703, 95% CI 3.424 – 9.500, p < 0.001). Receiver operating characteristics (ROC) curve showed that the cut-off value of normalized ADA mRNA level at 2.37 x 10-3 had a sensitivity of 81.8% and specificity of 83.4%. While patients with severe COVID-19 had more respiratory symptoms, and elevated lactate dehydrogenase, multivariate analysis showed that severe COVID-19 patients had lower CCL22 mRNA (OR 0.211, 95% CI 0.060 – 0.746, p = 0.016) in nasopharyngeal specimens, while lymphocyte count, C-reactive protein, and viral load in nasopharyngeal specimens did not correlate with disease severity. In summary, ADA appears to be a better biomarker to differentiate between infected and uninfected patients, while CCL22 has the potential in stratifying the severity of COVID-19.
The risk for COVID-19-associated mortality increases with age, disability, and underlying medical conditions (1). Early in the emergence of the Omicron variant of SARS-CoV-2, the virus that causes COVID-19, mortality among hospitalized COVID-19 patients was lower than that during previous pandemic peaks (2-5), and some health authorities reported that a substantial proportion of COVID-19 hospitalizations were not primarily for COVID-19-related illness,* which might account for the lower mortality among hospitalized patients. Using a large hospital administrative database, CDC assessed in-hospital mortality risk overall and by demographic and clinical characteristics during the Delta (July-October 2021), early Omicron (January-March 2022), and later Omicron (April-June 2022) variant periods† among patients hospitalized primarily for COVID-19. Model-estimated adjusted mortality risk differences (aMRDs) (measures of absolute risk) and adjusted mortality risk ratios (aMRRs) (measures of relative risk) for in-hospital death were calculated comparing the early and later Omicron periods with the Delta period. Crude mortality risk (cMR) (deaths per 100 patients hospitalized primarily for COVID-19) was lower during the early Omicron (13.1) and later Omicron (4.9) periods than during the Delta (15.1) period (p<0.001). Adjusted mortality risk was lower during the Omicron periods than during the Delta period for patients aged ≥18 years, males and females, all racial and ethnic groups, persons with and without disabilities, and those with one or more underlying medical conditions, as indicated by significant aMRDs and aMRRs (p<0.05). During the later Omicron period, 81.9% of in-hospital deaths occurred among adults aged ≥65 years and 73.4% occurred among persons with three or more underlying medical conditions. Vaccination, early treatment, and appropriate nonpharmaceutical interventions remain important public health priorities for preventing COVID-19 deaths, especially among persons most at risk.
The recent surge of COVID-19 hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of 100s of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and non-survivors. With increasing length of hospitalization, the survivors’ samples showed a trend towards normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of ten proteins and five metabolites we could predict patient survival with 92% accuracy (AUC 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.
The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2), is usually associated with a wide variety of clinical presentations from asymptomatic to severe cases. The use of saliva as a diagnostic and monitoring fluid has gained importance since it can be used to investigate the immune response and to direct quantification of antibodies against COVID-19. Additionally, the use of proteomics in saliva has allowed to increase our understanding of the underlying pathophysiology of diseases, bringing new perspectives on diagnostics, monitoring, and treatment. In this work, we compared the salivary proteome of 10 patients with COVID-19, (five patients with mild and five patients with severe COVID-19) and ten control healthy patients. Through the application of proteomics, we have identified 30 proteins whose abundance levels differed between the COVID-19 groups and the control group. Two of these proteins (TGM3 and carbonic anhydrase-CA6) were validated by the measurement of gGT and TEA respectively, in 98 additional saliva samples separated into two groups: (1) COVID-19 group, integrated by 66 patients who tested positive for COVID-19 (2) control group, composed of 32 healthy individuals who did not show any sign of disease for at least four weeks and were negative for COVID-19 in RT-PCR. In the proteomic study there were observed upregulations in CAZA1, ACTN4, and ANXA4, which are proteins related to the protective response against the virus disturbance, and the upregulation of TGM3, that is correlated to the oxidative damage in pulmonary tissue. We also showed the downregulation in cystatins and CA6 that can be involved in the sensory response to stimulus and possibly related to the presence of anosmia and dysgeusia during the COVID-19. Additionally, the presence of FGB in patients with severe COVID-19 but not in mild COVID-19 patients could indicate a higher viral aggregation and activation in these cases. In conclusion, the salivary proteome in patients with COVID-19 showed changes in proteins related to the protective response to viral infection, and the altered sensory taste perception that occur during the disease. Moreover, gGT and TEA could be potential biomarkers of respiratory complications that can occurs during COVID 19 although further larger studies should be made to corroborate this.
Mass spectrometry (MS) based diagnostic detection of 2019 novel coronavirus infectious disease (COVID-19) has been postulated to be a useful alternative to classical PCR based diagnostics. These MS based approaches have the potential to be both rapid and sensitive and can be done on-site without requiring a dedicated laboratory or depending on constrained supply chains (i.e., reagents and consumables). Matrix-assisted laser desorption ionization (MALDI)-time-of-flight (TOF) MS has a long and established history of microorganism detection and systemic disease assessment. Previously, we have shown that automated machine learning (ML) enhanced MALDI-TOF-MS screening of nasal swabs can be both sensitive and specific for COVID-19 detection. The underlying molecules responsible for this detection are generally unknown nor are they required for this automated ML platform to detect COVID-19. However, the identification of these molecules is important for understanding both the mechanism of detection and potentially the biology of the underlying infection. Here, we used nanoscale liquid chromatography tandem MS to identify endogenous peptides found in nasal swab saline transport media to identify peptides in the same the mass over charge (m/z) values observed by the MALDI-TOF-MS method. With our peptidomics workflow, we demonstrate that we can identify endogenous peptides and endogenous protease cut sites. Further, we show that SARS-CoV-2 viral peptides were not readily detected and are highly unlikely to be responsible for the accuracy of MALDI based SARS-CoV-2 diagnostics. Further analysis with more samples will be needed to validate our findings, but the methodology proves to be promising.
As of December 2021, SARS-CoV-2 had caused over 250 million infections and 5 million deaths worldwide. Furthermore, despite the development of highly effective vaccines, novel variants of SARS-CoV-2 continue to sustain the pandemic, and the search for effective therapies for COVID-19 remains as urgent as ever. Though the primary manifestation of COVID-19 is pneumonia, the disease can affect multiple organs, including the kidneys, with acute kidney injury (AKI) being among the most common extrapulmonary manifestations of severe COVID-19. In this article, we start by reflecting on the epidemiology of kidney disease in COVID-19, which overwhelmingly demonstrates that AKI is common in COVID-19 and is strongly associated with poor outcomes. We also present emerging data showing that COVID-19 may result in long-term renal impairment and delve into the ongoing debate about whether AKI in COVID-19 is mediated by direct viral injury. Next, we focus on the molecular pathogenesis of SARS-CoV-2 infection by both reviewing previously published data and presenting some novel data on the mechanisms of cellular viral entry. Finally, we relate these molecular mechanisms to a series of therapies currently under investigation and propose additional novel therapeutic targets for COVID-19.
Severe COVID-19 is associated with a systemic hyperinflammatory response leading to acute respiratory distress syndrome (ARDS), multi-organ failure, and death. Galectin-3 is a ß-galactoside binding lectin known to drive neutrophil infiltration and the release of pro-inflammatory cytokines contributing to airway inflammation. Thus, we aimed to investigate the potential of galectin-3 as a biomarker of severe COVID-19 outcomes. We prospectively included 156 patients with RT-PCR confirmed COVID-19. A severe outcome was defined as the requirement of invasive mechanical ventilation (IMV) and/or in-hospital death. A non-severe outcome was defined as discharge without IMV requirement. We used receiver operating characteristic (ROC) and multivariable logistic regression analysis to determine the prognostic ability of serum galectin-3 for a severe outcome. Galectin-3 levels discriminated well between severe and non-severe outcomes and correlated with markers of COVID-19 severity, (CRP, NLR, D-dimer, and neutrophil count). Using a forward-stepwise logistic regression analysis we identified galectin-3 [odds ratio (OR) 3.68 (95% CI 1.47–9.20), p < 0.01] to be an independent predictor of severe outcome. Furthermore, galectin-3 in combination with CRP, albumin and CT pulmonary affection > 50%, had significantly improved ability to predict severe outcomes [AUC 0.85 (95% CI 0.79–0.91, p < 0.0001)]. Based on the evidence presented here, we recommend clinicians measure galectin-3 levels upon admission to facilitate allocation of appropriate resources in a timely manner to COVID-19 patients at highest risk of severe outcome.
Introduction
Coronavirus disease of 2019 (COVID-19) has resulted in millions of cases worldwide. As the pandemic has progressed, the understanding of this disease has evolved.
Objective
This first in a two-part series on COVID-19 updates provides a focused overview of the presentation and evaluation of COVID-19 for emergency clinicians.
Discussion
COVID-19, caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), has resulted in significant morbidity and mortality worldwide. Several variants exist, including a variant of concern known as Delta (B.1.617.2 lineage) and the Omicron variant (B.1.1.529 lineage). The Delta variant is associated with higher infectivity and poor patient outcomes, and the Omicron variant has resulted in a significant increase in infections. While over 80% of patients experience mild symptoms, a significant proportion can be critically ill, including those who are older and those with comorbidities. Upper respiratory symptoms, fever, and changes in taste/smell remain the most common presenting symptoms. Extrapulmonary complications are numerous and may be severe, including the cardiovascular, neurologic, gastrointestinal, and dermatologic systems. Emergency department evaluation includes focused testing for COVID-19 and assessment of end-organ injury. Imaging may include chest radiography, computed tomography, or ultrasound. Several risk scores may assist in prognostication, including the 4C (Coronavirus Clinical Characterisation Consortium) score, quick COVID Severity Index (qCSI), NEWS2, and the PRIEST score, but these should only supplement and not replace clinical judgment.
Conclusion
This review provides a focused update of the presentation and evaluation of COVID-19 for emergency clinicians.
Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.
The novel SARS-CoV-2 Omicron variant (B.1.1.529), first found in early November 2021, has sparked considerable global concern and it has >50 mutations, many of which are known to affect transmissibility or cause immune escape. ............
Coronavirus disease 2019 (COVID-19) has brought about a great threat to global public health. Recently, a new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant B.1.1.529 has been reported in South Africa and induced a rapid increase in COVID-19 cases. On November 24, 2021, B.1.1.529 named Omicron was designated as a variant under monitoring (VUM) by World Health Organization (WHO). Two days later, the Omicron variant was classified as a variant of concern (VOC). This variant harbors a high number of mutations, including 15 mutations in the receptor-binding domain (RBD) of spike. The Omicron variant also shares several mutations with the previous VOC Alpha, Beta, and Gamma variants, which immediately raised global concerns about viral transmissibility, pathogenicity, and immune evasion. Here we described the discovery and characteristics of the Omicron variant, compared the mutations of the spike in the five VOCs, and further raised possible strategies to prevent and overcome the prevalence of the Omicron variant.
Numerous reverse transcription polymerase chain reaction (RT-PCR) tests have emerged over the past year as the gold standard for detecting millions of cases of SARS-CoV-2 reported daily worldwide. However, problems with critical shortages of key reagents such as PCR primers and RNA extraction kits and unpredictable test reliability related to high viral replication cycles have triggered the need for alternative methodologies to PCR to detect specific COVID-19 proteins. Several authors have developed methods based on liquid chromatography with tandem mass spectrometry (LC–MS/MS) to confirm the potential of the technique to detect two major proteins, the spike and the nucleoprotein, of COVID-19. In the present work, an S-Trap mini spin column digestion protocol was used for sample preparation prodromal to LC–MS/MS analysis in multiple reactions monitoring ion mode (MRM) to obtain a comprehensive method capable of detecting different viral proteins. The developed method was applied to n. 81 oro/nasopharyngeal swabs submitted in parallel to quantitative reverse transcription PCR (RT-qPCR) assays to detect RdRP, the S and N genes specific for COVID-19, and the E gene for all Sarbecoviruses, including SARS-CoV-2 (with cycle negativity threshold set to 40). A total of 23 peptides representative of the six specific viral proteins were detected in the monitoring of 128 transitions found to have good ionic currents extracted in clinical samples that reacted differently to the PCR assay. The best instrumental response came from the FLPFQFGR sequence of spike [558−566] peptide used to test the analytical performance of the method that has good sensitivity with a low false-negative rate. Transition monitoring using a targeted MS approach has the great potential to detect the fragmentation reactions of any peptide molecularly defined by a specific amino acid sequence, offering the extensibility of the approach to any viral sequence including derived variants and thus providing insights into the development of new types of clinical diagnostics.
Knowledge of the metabolic stability of a new drug substance eliminated by biotransformation is essential for envisaging the pharmacokinetic parameters required for deciding drug dosing and frequency. Strategies aimed at modifying lead compounds may improve metabolic stability, thereby reducing the drug dosing frequency. Replacement of selective hydrogens with deuterium can effectively enhance the drug’s metabolic stability by increasing the biological half-life. Further, cyclization, change in ring size, and chirality can substantially improve the metabolic stability of drugs. The microsomal t1/2 approach for measuring drug in vitro intrinsic clearance by automated LC-MS/MS offers sensitive high-throughput screens with reliable data. The obtained in vitro intrinsic clearance from metabolic stability data helps predict the drug’s in vivo total clearance using different scaling factors and hepatic clearance models. This review summarises all the recent approaches and technological advancements in metabolic stability studies for narrowing down the potential lead compounds in drug discovery. Further, we summarised the potential pitfalls and assumptions made during the in vivo intrinsic clearance estimation from in vitro intrinsic clearance.
The need for precision medicine approaches to monitor health and disease makes it important to develop sensitive and accurate assays for proteome profiles in blood. Here, we describe an approach for plasma profiling based on proximity extension assay combined with next generation sequencing. First, we analyze the variability of plasma profiles between and within healthy individuals in a longitudinal wellness study, including the influence of genetic variations on plasma levels. Second, we follow patients newly diagnosed with type 2 diabetes before and during therapeutic intervention using plasma proteome profiling. The studies show that healthy individuals have a unique and stable proteome profile and indicate that a panel of proteins could potentially be used for early diagnosis of diabetes, including stratification of patients with regards to response to metformin treatment. Although validation in larger cohorts is needed, the analysis demonstrates the usefulness of comprehensive plasma profiling for precision medicine efforts. The proximity extension assay (PEA) is a popular tool to measure plasma protein levels. Here, the authors extend the proteome coverage of PEA by combining it with next-generation sequencing, enabling the analysis of nearly 1500 proteins from minute amounts of plasma.
Among COVID-19 hospitalized patients, high incidence of alterations in inflammatory and coagulation biomarkers correlates with a poor prognosis. Comorbidities such as chronic degenerative diseases are frequently associated with complications in COVID-19 patients. The aim of this study was to evaluate inflammatory and procoagulant biomarkers in COVID-19 patients from a public hospital in Mexico. Blood was sampled within the first 48 h after admission in 119 confirmed COVID-19 patients that were classified in 3 groups according to oxygen demand, evolution and the severity of the disease as follows: 1) Non severe: nasal cannula or oxygen mask; 2) Severe: high flow nasal cannula and 3) Death: mechanical ventilation eventually leading to fatal outcome. Blood samples from 20 healthy donors were included as a Control Group. Analysis of inflammatory and coagulation biomarkers including D-dimer, interleukin 6, interleukin 8, PAI-1, P-selectin and VWF was performed in plasma. Routine laboratory and clinical biomarkers were also included and compared among groups. Concentrations of D-dimer (14.5 ± 13.8 µg/ml) and PAI-1 (1223 ± 889.6 ng/ml) were significantly elevated in severe COVID-19 patients (P < 0.0001). A significant difference was found in interleukin-6, PAI-1 and P-selectin in non-severe and healthy donors when compared to Severe COVID-19 and deceased patients (P < 0.001). VWF levels were also significantly different between severe patients (153.5 ± 24.3 UI/dl) and non-severe ones (133.9 ± 20.2 UI/dl) (P < 0.0001). WBC and glucose levels were also significantly elevated in patients with Severe COVID-19. Plasma concentrations of all prothrombotic biomarkers were significantly higher in patients with a fatal outcome.
The ongoing pandemic of coronavirus disease 2019 (COVID-19) poses several challenges to clinicians. Timely diagnosis and hospitalization, risk stratification, effective utilization of intensive care services, selection of appropriate therapies, monitoring and timely discharge are essential to save the maximum number of lives. Clinical assessment is indispensable, but laboratory markers, or biomarkers, can provide additional, objective information which can significantly impact these components of patient care. COVID-19 is not a localized respiratory infection but a multisystem disease caused by a diffuse systemic process involving a complex interplay of the immunological, inflammatory and coagulative cascades. The understanding of what the virus does to the body and how the body reacts to it has uncovered a gamut of potential biomarkers. This review discusses the different classes of biomarkers – immunological, inflammatory, coagulation, hematological, cardiac, biochemical and miscellaneous – in terms of their pathophysiological basis followed by the current evidence. Differences between children and adults are highlighted. The role of biomarkers in the diagnosis and management of Multisystem Inflammatory Syndrome in Children (MIS-C) is reviewed. The correlation of biomarkers with clinical and radiological features and the viral load, temporal evolution and the effect of treatment remain to be studied in detail. Which biomarker needs to be evaluated when and in whom, and how best this information can contribute to patient care are questions which currently lack convincing answers. With the evidence currently available broad guidelines on the rational use of available biomarkers are presented. Integrating clinical and laboratory data, monitoring trends rather than a single value, correlating with the natural course of the disease and tailoring guidelines to the individual patient and healthcare setting are essential.
Multiple Biomarkers have recently been shown to be elevated in COVID-19, a respiratory infection with multi-organ dysfunction; however, information regarding the prognostic value of cardiac biomarkers as it relates to disease severity and cardiac injury are inconsistent. The goal of this meta-analysis was to summarize the evidence regarding the prognostic relevance of cardiac biomarkers from data available in published reports. PubMed, Embase and Web of Science were searched from inception through April 2020 for studies comparing median values of cardiac biomarkers in critically ill versus non-critically ill COVID-19 patients, or patients who died versus those who survived. The weighted mean differences (WMD) and 95% confidence interval (CI) between the groups were calculated for each study and combined using a random effects meta-analysis model. The odds ratio (OR) for mortality based on cardiac injury was combined from studies reporting it. Troponin levels were significantly higher in COVID-19 patients who died or were critically ill versus those who were alive or not critically ill (WMD 0.57, 95% CI 0.43–0.70, p < 0.001). Additionally, BNP levels were also significantly higher in patients who died or were critically ill (WMD 0.45, 95% CI − 0.21–0.69, p < 0.001). Cardiac injury was independently associated with significantly increased odds of mortality (OR 6.641, 95% CI 1.26–35.1, p = 0.03). A significant difference in levels of D-dimer was seen in those who died or were critically ill. CK levels were only significantly higher in those who died versus those who were alive (WMD 0.79, 95% CI 0.25–1.33, p = 0.004). Cardiac biomarkers add prognostic value to the determination of the severity of COVID-19 and can predict mortality.
Hyperinflammation contributes to lung injury and subsequent acute respiratory distress syndrome (ARDS) with high mortality in patients with severe coronavirus disease 2019 (COVID-19). To understand the underlying mechanisms involved in lung pathology, we investigated the role of the lung-specific immune response. We profiled immune cells in bronchoalveolar lavage fluid and blood collected from COVID-19 patients with severe disease and bacterial pneumonia patients not associated with viral infection. By tracking T cell clones across tissues, we identified clonally expanded tissue-resident memory-like Th17 cells (Trm17 cells) in the lungs even after viral clearance. These Trm17 cells were characterized by a potentially pathogenic cytokine expression profile of IL17A and CSF2 (GM-CSF). Interactome analysis suggests that Trm17 cells can interact with lung macrophages and cytotoxic CD8+ T cells, which have been associated with disease severity and lung damage. High IL-17A and GM-CSF protein levels in the serum of COVID-19 patients were associated with a more severe clinical course. Collectively, our study suggests that pulmonary Trm17 cells are one potential orchestrator of the hyperinflammation in severe COVID-19.
Immune and inflammatory responses to SARS-CoV-2 contribute to disease severity of COVID-19. However, the utility of specific immune-based biomarkers to predict clinical outcome remains elusive. Here, we analyzed levels of 66 soluble biomarkers in 175 Italian patients with COVID-19 ranging from mild/moderate to critical severity, and assessed type-I IFN-, type-II IFN-, and NF-κB-dependent whole blood transcriptional signatures. A broad inflammatory signature was observed, implicating activation of various immune and non-hematopoietic cell subsets. Discordance between IFN-α2a protein and IFNA2 transcript levels in blood suggests that type-I IFNs during COVID-19 may be primarily produced by tissue-resident cells. Multivariable analysis of patients' first samples revealed 12 biomarkers (CCL2, IL-15, sST2, NGAL, sTNFRSF1A, ferritin, IL-6, S100A9, MMP-9, IL-2, sVEGFR1, IL-10) that when increased were independently associated with mortality. Multivariate analyses of longitudinal biomarker trajectories identified 8 of the aforementioned biomarkers (IL-15, IL-2, NGAL, CCL2, MMP-9, sTNFRSF1A, sST2, IL-10) and two additional biomarkers (lactoferrin, CXCL9) that were significantly associated with mortality when increased, while IL-1α was associated with mortality when decreased. Among these, sST2, sTNFRSF1A, IL-10, and IL-15 were consistently higher throughout the hospitalization in patients who died versus those who recovered, suggesting that these biomarkers may provide an early warning of eventual disease outcome.
Major wildfires that started in the summer of 2020 along the west coast of the U.S. have made PM 2.5 concentrations in cities in this region rank among the highest in the world. Regions of Washington were impacted by active wildfires in the state, and by aged wood smoke transported from fires in Oregon and California. This study aims to assess the population health impact of increased PM 2.5 concentrations attributable to the wildfire. Average daily PM 2.5 concentrations for each county before and during the 2020 Washington wildfire episode were obtained from the Washington Department of Ecology. Utilizing previously established associations of short-term mortality for PM 2.5 , we estimated excess mortality for Washington attributable to the increased PM 2.5 levels. On average, PM 2.5 concentrations increased 91.7 μg/m ³ during the wildfire episode. Each week of wildfire smoke exposures was estimated to result in 87.6 (95% CI: 70.9, 103.1) cases of increased all-cause mortality, 19.1 (95% CI: 10.0, 28.2) increased cardiovascular disease deaths, and 9.4 (95% CI: 5.1, 13.5) increased respiratory disease deaths. Because wildfire smoke episodes are likely to continue impacting the Pacific Northwest in future years, continued preparedness and mitigations to reduce exposures to wildfire smoke are necessary to avoid this excess health burden.
Background:
The severe acute respiratory syndrome (SARS) coronavirus-2 is a novel coronavirus belonging to the family Coronaviridae and is now known to be responsible for the outbreak of a series of recent acute atypical respiratory infections originating in Wuhan, China. The disease caused by this virus, termed coronavirus disease 19 or simply COVID-19, has rapidly spread throughout the world at an alarming pace and has been declared a pandemic by the WHO on March 11, 2020. In this review, an update on the pathophysiology, clinical presentation and the most recent management strategies for COVID-19 has been described.
Materials and methods:
A search was conducted for literature and various articles/case reports from 1997 to 2020 in PUBMED/MEDLINE for the keywords coronavirus, SARS, Middle East respiratory syndrome and mRNA virus.
Results and conclusions:
COVID-19 has now spread globally with increasing morbidity and mortality among all populations. In the absence of a proper and effective antibody test, the diagnosis is presently based on a reverse-transcription PCR of nasopharyngeal and oropharyngeal swab samples. The clinical spectrum of the disease presents in the form of a mild, moderate or severe illness. Most patients are either asymptomatic carriers who despite being without symptoms have the potential to be infectious to others coming in close contact, or have a mild influenza-like illness which cannot be differentiated from a simple upper respiratory tract infection. Moderate and severe cases require hospitalisation as well as intensive therapy which includes non-invasive as well as invasive ventilation, along with antipyretics, antivirals, antibiotics and steroids. Complicated cases may require treatment by immunomodulatory drugs and plasma exchange therapy. The search for an effective vaccine for COVID-19 is presently in full swing, with pharmaceutical corporations having started human trials in many countries.
The outbreak of Coronavirus disease of 2019 (COVID-19) caused by the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), has posed a serious health threat. The increasing number of COVID-19 cases around the world is overwhelming hospitals and pushing the global death toll to over 746,000, which has pushed the sprint to find new treatment options. In this article, we reviewed the SARS-CoV-2 pathophysiology, transmission, and potential treatment strategies.
Introduction:
COVID-19 caused by the SARS-CoV-2 continues to spread rapidly across the world. In our study, we aim to investigate the relationship between the liver enzymes on admission (AST, ALT, ALP, GGT) and severity of COVID-19. We evaluated course of disease, hospital stay, liver damage and mortality.
Materials and methods:
Our study included 614 patients who were hospitalized with the diagnosis of COVID-19 between 03.16.20-05.12.20. Patients with liver disease, hematological and solid organ malignancy with liver metastases were excluded, resulting in 554 patients who met our inclusion criteria. We retrospectively evaluated liver transaminase levels, AST/ALT ratio, cholestatic enzyme levels and R ratio during hospital admission and these were compared in terms of morbidity, mortality and clinical course.
Results:
Mean age of 554 subjects were 66.21±15.45 years, 328 (59.2%) were men. The mean values of liver enzymes on admission were AST(36.2±33.6 U/L), ALT(34.01±49.34 U/L), ALP(78.8±46.86 U/L), GGT(46.25±60.05 U/L). Mortality rate and need for intensive care unit were statistically significant in subjects that had high ALT-AST levels during their admission to the hospital(p=0.001). According to the ROC analysis AST/ALT ratio was a good marker of mortality risk (AUC=0.713:p=0.001) and expected probability of intensive care unit admission (AUC=0.636:p=0.001). R ratio, which was used to evaluate prognosis, showed a poor prognosis rate of 26.5% in the cholestatic injury group, 36.1% in the mixed pattern group and 30% in the hepato-cellular injury group(p 0.001).
Conclusions:
ALT-AST elevation and AST/ALT ratio>1 was associated with more severe course and increased mortality in COVID-19.
The emergence of coronavirus disease 2019 (COVID-19) in December 2019 has resulted in over 20 million cases and 741,808 deaths globally, affecting more than 200 countries. COVID-19 was declared a pandemic on 11 March 2020 by the World Health Organization. The disease is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). There is limited information on COVID-19, and treatment has so far focused on supportive care and use of repurposed drugs. COVID-19 can be transmitted via person-to-person contact through droplet spread. Some of the recommended precautionary measures to reduce the rate of disease spread include social dis-tancing, good hygiene practices, and avoidance of crowded areas. These measures are effective Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). because the droplets are heavy and can only travel approximately 1 meter in the air, settling quickly on fixed surfaces. Promising strategies to combat SARS-CoV-2 include discovery of therapeutic targets/drugs and vaccines. In this review, we summarize the epidemiology, pathophysi-ology, and diagnosis of COVID-19. We also address the mechanisms of action of approved repurposed drugs for therapeutic management of the disease.
Due to the unprecedented public health crisis caused by COVID-19, our first contribution to the newly launching journal, Advances in Biomarker Sciences and Technology, has abruptly diverted to focus on the current pandemic. As the number of new COVID-19 cases and deaths continue to rise steadily around the world, the common goal of healthcare providers, scientists, and government officials worldwide has been to identify the best way to detect the novel coronavirus, named SARS-CoV-2, and to treat the viral infection – COVID-19. Accurate detection, timely diagnosis, effective treatment, and future prevention are the vital keys to management of COVID-19 and can help curb the viral spread. Traditionally, biomarkers play a pivotal role in the early detection of disease etiology, diagnosis, treatment and prognosis. To assist myriad ongoing investigations and innovations, we developed this current article that overviews known and emerging biomarkers for SARS-CoV-2 detection, COVID-19 diagnostics, treatment and prognosis, and ongoing work to identify and develop more biomarkers for new drugs and vaccines. Moreover, biomarkers of socio-psychological stress, the high-technology quest for new virtual drug screening, and digital applications are described.
Detection of SARS-CoV-2 using RT–PCR and other advanced methods can achieve high accuracy. However, their application is limited in countries that lack sufficient resources to handle large-scale testing during the COVID-19 pandemic. Here, we describe a method to detect SARS-CoV-2 in nasal swabs using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and machine learning analysis. This approach uses equipment and expertise commonly found in clinical laboratories in developing countries. We obtained mass spectra from a total of 362 samples (211 SARS-CoV-2-positive and 151 negative by RT–PCR) without prior sample preparation from three different laboratories. We tested two feature selection methods and six machine learning approaches to identify the top performing analysis approaches and determine the accuracy of SARS-CoV-2 detection. The support vector machine model provided the highest accuracy (93.9%), with 7% false positives and 5% false negatives. Our results suggest that MALDI-MS and machine learning analysis can be used to reliably detect SARS-CoV-2 in nasal swab samples. SARS-CoV-2 is reliably detected in nasal swab samples using mass spectrometry and machine learning analysis.
Ferritin is an iron-binding molecule, which comprises 24 subunits, heavy (FeH) and light (FeL) subunits, suggested to have a pathogenic role by the ‘hyperferritinemic syndrome’. In this work, we tested (1) FeH and FeL in bone marrow (BM) and sera in patients with macrophage activation syndrome (MAS); (2) pro-inflammatory effects of ferritin, FeL, and FeH on macrophages; (3) ability of FeH-stimulated macrophages to stimulate the proliferation of peripheral blood mononuclear cells (PBMCs); (4) production of mature IL-1β and IL-12p70 in extracellular compartments of FeH-stimulated macrophages. Immunofluorescence analysis and liquid chromatography mass spectrometry (LC–MS/MS) based proteomics were performed to identify FeL and FeH in BM and sera, respectively, in the same patients. Macrophages were stimulated with ferritin, FeH, and FeL to assess pro-inflammatory effects by RT-PCR and western blot. The proliferation of co-cultured PBMCs with FeH-stimulated macrophages was tested. Immunofluorescence showed an increased FeH expression in BMs, whereas LC–MS/MS identified that FeL was mainly represented in sera. FeH induced a significant increase of gene expressions of IL-1β, IL-6, IL-12, and TNF-α, more marked with FeH, which also stimulated NLRP3. FeH-stimulated macrophages enhanced the proliferation of PBMCs. The ELISA assays showed that mature form of IL-1β and IL-12p70 were increased, in extracellular compartments of FeH-stimulated macrophages. Our results showed FeH in BM biopsies of MAS patients, whereas, LC–MS/MS identified FeL in the sera. FeH showed pro-inflammatory effects on macrophages, stimulated NLRP3, and increased PBMCs proliferation.
The COVID-19 outbreak is a great threat to public health worldwide. Lung injury is
the main outcome of COVID-19 infection; however, damage can occur in other organs
including the liver. Currently, limited data are available that link underlying liver injury with
the severe SARS-CoV-2 infection. This review summarizes the available data on liver
test abnormalities in COVID-19 patients; critically evaluates the possible causes of liver
injury and provides recommendations for clinicians. In laboratory tests, serum levels of
liver test markers notably transaminase, gamma-glutamyl transferase and total bilirubin
were significantly higher in severe patients with COVID-19 infection. The use of certain
drugs especially lopinavir and ritonavir showed an association with the progression of liver
damage in severe cases. Available data suggest that liver injury in COVID-19 patients may
result from direct effect by the virus, immune-mediated inflammation or drug-induced
toxicity. Some studies demonstrated that COVID-19 patients with pre-existing liver
disease are at higher risk for hospitalizations and mortality. Therefore, the impact of
pre-existing liver disease on treatment and clinical outcomes of COVID-19 should be
determined. Large-scale clinical studies are needed to identify the causes of liver injury
in patients with COVID-19 infection.
Importance
The coronavirus disease 2019 (COVID-19) pandemic, due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19.
Observations
SARS-CoV-2 is spread primarily via respiratory droplets during close face-to-face contact. Infection can be spread by asymptomatic, presymptomatic, and symptomatic carriers. The average time from exposure to symptom onset is 5 days, and 97.5% of people who develop symptoms do so within 11.5 days. The most common symptoms are fever, dry cough, and shortness of breath. Radiographic and laboratory abnormalities, such as lymphopenia and elevated lactate dehydrogenase, are common, but nonspecific. Diagnosis is made by detection of SARS-CoV-2 via reverse transcription polymerase chain reaction testing, although false-negative test results may occur in up to 20% to 67% of patients; however, this is dependent on the quality and timing of testing. Manifestations of COVID-19 include asymptomatic carriers and fulminant disease characterized by sepsis and acute respiratory failure. Approximately 5% of patients with COVID-19, and 20% of those hospitalized, experience severe symptoms necessitating intensive care. More than 75% of patients hospitalized with COVID-19 require supplemental oxygen. Treatment for individuals with COVID-19 includes best practices for supportive management of acute hypoxic respiratory failure. Emerging data indicate that dexamethasone therapy reduces 28-day mortality in patients requiring supplemental oxygen compared with usual care (21.6% vs 24.6%; age-adjusted rate ratio, 0.83 [95% CI, 0.74-0.92]) and that remdesivir improves time to recovery (hospital discharge or no supplemental oxygen requirement) from 15 to 11 days. In a randomized trial of 103 patients with COVID-19, convalescent plasma did not shorten time to recovery. Ongoing trials are testing antiviral therapies, immune modulators, and anticoagulants. The case-fatality rate for COVID-19 varies markedly by age, ranging from 0.3 deaths per 1000 cases among patients aged 5 to 17 years to 304.9 deaths per 1000 cases among patients aged 85 years or older in the US. Among patients hospitalized in the intensive care unit, the case fatality is up to 40%. At least 120 SARS-CoV-2 vaccines are under development. Until an effective vaccine is available, the primary methods to reduce spread are face masks, social distancing, and contact tracing. Monoclonal antibodies and hyperimmune globulin may provide additional preventive strategies.
Conclusions and Relevance
As of July 1, 2020, more than 10 million people worldwide had been infected with SARS-CoV-2. Many aspects of transmission, infection, and treatment remain unclear. Advances in prevention and effective management of COVID-19 will require basic and clinical investigation and public health and clinical interventions.
Although COVID-19 is most well known for causing substantial respiratory pathology, it can also result in several extrapulmonary manifestations. These conditions include thrombotic complications, myocardial dysfunction and arrhythmia, acute coronary syndromes, acute kidney injury, gastrointestinal symptoms, hepatocellular injury, hyperglycemia and ketosis, neurologic illnesses, ocular symptoms, and dermatologic complications. Given that ACE2, the entry receptor for the causative coronavirus SARS-CoV-2, is expressed in multiple extrapulmonary tissues, direct viral tissue damage is a plausible mechanism of injury. In addition, endothelial damage and thromboinflammation, dysregulation of immune responses, and maladaptation of ACE2-related pathways might all contribute to these extrapulmonary manifestations of COVID-19. Here we review the extrapulmonary organ-specific pathophysiology, presentations and management considerations for patients with COVID-19 to aid clinicians and scientists in recognizing and monitoring the spectrum of manifestations, and in developing research priorities and therapeutic strategies for all organ systems involved.
Background:
Over 5,488,000 cases of coronavirus disease-19 (COVID-19) have been reported since December 2019. We aim to explore risk factors associated with mortality in COVID-19 patients and assess the use of D-dimer as a biomarker for disease severity and clinical outcome.
Methods:
We retrospectively analyzed the clinical, laboratory, and radiological characteristics of 248 consecutive cases of COVID-19 in Renmin Hospital of Wuhan University, Wuhan, China from January 28 to March 08, 2020. Univariable and multivariable logistic regression methods were used to explore risk factors associated with in-hospital mortality. Correlations of D-dimer upon admission with disease severity and in-hospital mortality were analyzed. Receiver operating characteristic curve was used to determine the optimal cutoff level for D-dimer that discriminated those survivors versus non-survivors during hospitalization.
Results:
Multivariable regression that showed D-dimer > 2.0 mg/L at admission was the only variable associated with increased odds of mortality [OR 10.17 (95% CI 1.10-94.38), P = 0.041]. D-dimer elevation (≥ 0.50 mg/L) was seen in 74.6% (185/248) of the patients. Pulmonary embolism and deep vein thrombosis were ruled out in patients with high probability of thrombosis. D-dimer levels significantly increased with increasing severity of COVID-19 as determined by clinical staging (Kendall's tau-b = 0.374, P = 0.000) and chest CT staging (Kendall's tau-b = 0.378, P = 0.000). In-hospital mortality rate was 6.9%. Median D-dimer level in non-survivors (n = 17) was significantly higher than in survivors (n = 231) [6.21 (3.79-16.01) mg/L versus 1.02 (0.47-2.66) mg/L, P = 0.000]. D-dimer level of > 2.14 mg/L predicted in-hospital mortality with a sensitivity of 88.2% and specificity of 71.3% (AUC 0.85; 95% CI = 0.77-0.92).
Conclusions:
D-dimer is commonly elevated in patients with COVID-19. D-dimer levels correlate with disease severity and are a reliable prognostic marker for in-hospital mortality in patients admitted for COVID-19.
There have been over 7 million cases and almost 413,372 deaths globally due to the novel coronavirus (2019‐nCoV) associated disease COVID‐19, as of June 11, 2020. Phylogenetic analysis suggests that there is a common source for these infections. The overall sequence similarities between the spike protein of 2019‐nCoV and that of SARS‐CoV are known to be around 76‐78% and 73‐76% for whole protein and receptor‐binding domain (RBD), respectively. Thus, they have the potential to serve as drug and/ or vaccine candidate. However, the individual response against 2019‐nCoV differs due to genetic variations in the human population. Understanding the variations in Angiotensin‐converting enzyme 2 (ACE2) and human leukocyte antigen (HLA) that may affect the severity of 2019‐nCoV infection could help in identifying individuals at higher risk from the COVID‐19. A number of potential drugs/vaccines as well as antibody/cytokine‐based therapeutics are running in various developmental stages of preclinical/clinical trials against SARS‐CoV, MERS‐CoV and 2019‐nCoV with substantial cross‐reactivity, which may be used against COVID‐19. For diagnosis, reverse transcription polymerase chain reaction (RT‐PCR) is the gold standard test for initial diagnosis of COVID‐19. Kit based on serological tests are also recommended for investigating the spread of COVID‐19 but it is challenging due to antibodies cross‐reactivity. This review comprehensively summarizes the recent reports available regarding the host‐pathogen interaction, morphological and genomic structure of the virus, and the diagnostic techniques as well as available and potential therapeutics against COVID‐19.
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Abstract Background Since December 2019, the outbreak of COVID-19 caused a large number of hospital admissions in China. Many patients with COVID-19 have symptoms of acute respiratory distress syndrome, even are in danger of death. This is the first study to evaluate dynamic changes of D-Dimer and Neutrophil-Lymphocyte Count Ratio (NLR) as a prognostic utility in patients with COVID-19 for clinical use. Methods In a retrospective study, we collected data from 349 hospitalized patients who diagnosed as the infection of the COVID-19 in Wuhan Pulmonary Hospital. We used ROC curves and Cox regression analysis to explore critical value (optimal cut-off point associated with Youden index) and prognostic role of dynamic changes of D-Dimer and NLR. Results Three hundred forty-nine participants were enrolled in this study and the mortality rate of the patients with laboratory diagnosed COVID-19 was 14.9%. The initial and peak value of D-Dimer and NLR in deceased patients were higher statistically compared with survivors (P
The novel coronavirus SARS-CoV-2 is the seventh known species of coronavirus, infectious to human beings. The pandemic COVID-19 spread all over the world with an unprecedented spreading rate after its first appearance in Wuhan, China. As a novel viral disease there in no antiviral treatment or vaccine for the COVID-19. At present, the early detection and the quarantine of infected patients are the ways to stop the spreading of the disease. This review will discuss about the current invitro diagnostic methods used worldwide for the early and accurate diagnosis of COVID-19. Currently the nucleic acid based polymerase chain reaction is used as the reliable diagnostic platform and antigen/antibody detection immunoassays are playing the role of screening tests for early detection and prognosis in COVID-19 treatment.
Background:
The World Health Organization has declared coronavirus disease 2019 (COVID-19) a public health emergency of global concern. Updated analysis of cases might help identify the risk factors of illness severity.
Results:
The median age was 63 years, and 44.9% were severe cases. Severe patients had higher APACHE II (8.5 vs. 4.0) and SOFA (2 vs. 1) scores on admission. Among all univariable parameters, lymphocytes, CRP, and LDH were significantly independent risk factors of COVID-19 severity. LDH was positively related both with APACHE II and SOFA scores, as well as P/F ratio and CT scores. LDH (AUC = 0.878) also had a maximum specificity (96.9%), with the cutoff value of 344.5. In addition, LDH was positively correlated with CRP, AST, BNP and cTnI, while negatively correlated with lymphocytes and its subsets.
Conclusions:
This study showed that LDH could be identified as a powerful predictive factor for early recognition of lung injury and severe COVID-19 cases.
Methods:
We extracted data regarding 107 patients with confirmed COVID-19 from Renmin Hospital of Wuhan University. The degree of severity of COVID-19 patients (severe vs. non-severe) was defined at the time of admission according to American Thoracic Society guidelines for community acquired pneumonia.
Objectives
Circulating calprotectin (cCLP) has been shown to be a promising prognostic marker for COVID-19 severity. We aimed to investigate the prognostic value of serial measurements of cCLP in COVID-19 patients admitted to an intensive care unit (ICU).
Methods
From November 2020 to May 2021, patients with COVID-19, admitted at the ICU of the OLV Hospital, Aalst, Belgium, were prospectively included. For sixty-six (66) patients, blood samples were collected at admission and subsequently every 48 h during ICU stay. On every sample (total n=301), a cCLP (EliA™ Calprotectin 2, Phadia 200, Thermo Fisher Scientific; serum/plasma protocol (for Research Use Only, -RUO-) and C-reactive protein (CRP; cobas c501/c503, Roche Diagnostics) analysis were performed. Linear mixed models were used to associate biomarkers levels with mortality, need for mechanical ventilation, length of stay at ICU (LOS-ICU) and medication use (antibiotics, corticosteroids, antiviral and immune suppressant/modulatory drugs).
Results
Longitudinally higher levels of all biomarkers were associated with LOS-ICU and with the need for mechanical ventilation. Medication use and LOS-ICU were not associated with variations in cCLP and CRP levels. cCLP levels increased significantly during ICU hospitalization in the deceased group (n=21/66) but decreased in the non-deceased group (n=45/66). In contrast, CRP levels decreased non-significantly in both patient groups, although significantly longitudinally higher CRP levels were obtained in the deceased subgroup.
Conclusions
Serial measurements of cCLP provides prognostic information which can be useful to guide clinical management of COVID-19 patients in ICU setting.
Background and aim:
SARS-CoV-2 infection spawns from an asymptomatic condition to a fatal disease. Age, comorbidities, and several blood biomarkers are associated with infection outcome. We searched for biomarkers by untargeted and targeted proteomic analysis of saliva, a source of viral particles and host proteins.
Methods:
Saliva samples from 19 asymptomatic and 16 symptomatic SARS-CoV-2 infected subjects, and 20 controls were analyzed by LC-MS/MS for untargeted peptidomic (flow through of 10 kDa filter) and proteomic (trypsin digestion of filter retained proteins) profiling.
Results:
Peptides from 53 salivary proteins were identified. ADF was detected only in controls, while IL1RA only in infected subjects. PRPs, DSC2, FABP5, his-1, IL1RA, PRH1, STATH, SMR3B, ANXA1, MUC7, ACTN4, IGKV1-33 and TGM3 were significantly different between asymptomatic and symptomatic subjects. Retained proteins were 117, being 11 highly different between asymptomatic and symptomatic (fold change ≥2 or ≤-2). After validation by LC-MS/MS-SRM (selected reaction monitoring analysis), the most significant discriminant proteins at PCA were IL1RA, CYSTB, S100A8, S100A9, CA6, and FABP5.
Conclusions:
The differentially abundant proteins involved in innate immunity (S100 proteins), taste (CA6 and cystatins), and viral binding to the host (FABP5), appear to be of interest for use as potential biomarkers and drugs targets.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the ongoing coronavirus disease 2019 (COVID-19) pandemic. Here we report a novel strategy for the rapid detection of SARS-CoV-2 based on an enrichment approach exploiting the affinity between the virus and cellulose sulfate ester functional groups, hot acid hydrolysis, and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS). Virus samples were enriched using cellulose sulfate ester microcolumns. Virus peptides were prepared using the hot acid aspartate-selective hydrolysis and characterized by MALDI-TOF MS. Collected spectra were processed with a peptide fingerprint algorithm, and searching parameters were optimized for the detection of SARS-CoV-2. These peptides provide high sequence coverage for nucleocapsid (N protein) and allow confident identification of SARS-CoV-2. Peptide markers contributing to the detection were rigorously identified using bottom-up proteomics. The approach demonstrated in this study holds the potential for developing a rapid assay for COVID-19 diagnosis and detecting virus variants from a variety of sources, such as sewage and nasal swabs.
Assessment of drug candidate's potential to inhibit cytochrome P450 (CYP) enzymes remains crucial in pharmaceutical drug discovery and development. Both direct and time-dependent inhibition of drug metabolizing CYP enzymes by the concomitant administered drug is the leading cause of drug–drug interactions (DDIs), resulting in the increased toxicity of the victim drug. In this context, pharmaceutical companies have grown increasingly diligent in limiting CYP inhibition liabilities of drug candidates in the early stages and examining risk assessments throughout the drug development process. This review discusses different strategies and decision-making processes for assessing the drug–drug interaction risks by enzyme inhibition and lays particular emphasis on in vitro study designs and interpretation of CYP inhibition data in a stage-appropriate context.
COVID-19 is a highly contagious respiratory disease that can be infected through human exhaled breath. Human breath analysis is an attractive strategy for rapid diagnosis of COVID-19 in a non-invasive way by monitoring breath biomarkers. Mass spectrometry (MS)-based approaches offer a promising analytical platform for human breath analysis due to their high speed, specificity, sensitivity, reproducibility, and broad coverage, as well as its versatile coupling methods with different chromatographic separation, and thus can lead to a better understanding of the clinical and biochemical processes of COVID-19. Herein, we try to review the developments and applications of MS-based approaches for multidimensional analysis of COVID-19 breath samples, including metabolites, proteins, microorganisms, and elements. New features of breath sampling and analysis are highlighted. Prospects and challenges on MS-based breath analysis related to COVID-19 diagnosis and study are discussed.
The heterogeneous disease course of COVID-19 is unpredictable, ranging from mild self-limiting symptoms to cytokine storms, acute respiratory distress syndrome (ARDS), multi-organ failure and death. Identification of high-risk cases will enable appropriate intervention and escalation. This study investigates the routine laboratory tests and cytokines implicated in COVID-19 for their potential application as biomarkers of disease severity, respiratory failure and need of higher-level care.
From analysis of 203 samples, CRP, IL-6, IL-10 and LDH were most strongly correlated with the WHO ordinal scale of illness severity, the fraction of inspired oxygen delivery, radiological evidence of ARDS and level of respiratory support (p ≤ 0.001). IL-6 levels of ≥3.27 pg/ml provide a sensitivity of 0.87 and specificity of 0.64 for a requirement of ventilation, and a CRP of ≥37 mg/l of 0.91 and 0.66.
Reliable stratification of high-risk cases has significant implications on patient triage, resource management and potentially the initiation of novel therapies in severe patients.
Background
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged late in 2019 causing COVID-19 (coronavirus disease-2019) may adversely affect the cardiovascular system. Publications from Asia, Europe and North America have identified cardiac troponin as an important prognostic indicator for patients hospitalized with COVID-19. We recognized from publications within the first 6 months of the pandemic that there has been much uncertainty on the reporting, interpretation, and pathophysiology of an increased cardiac troponin concentration in this setting.
Content
The purpose of this mini-review is: a) to review the pathophysiology of SARS-CoV-2 and the cardiovascular system, b) to overview the strengths and weaknesses of selected studies evaluating cardiac troponin in patients with COVID-19, and c) recommend testing strategies in the acute period, in the convalescence period and in long-term care for patients who have become ill with COVID-19.
Summary
This review provides important educational information and identifies gaps in understanding the role of cardiac troponin and COVID-19. Future, properly designed studies will hopefully provide the much-needed evidence on the path forward in testing cardiac troponin in patients with COVID-19.
Coronaviruses may activate dysregulated host immune responses. As exploratory studies have suggested that interleukin-6 (IL-6) levels are elevated in cases of complicated Covid-19, we undertook a systematic review and meta-analysis to assess the evidence in this field. We systematically searched MEDLINE and EMBASE for studies investigating the immunological response in Covid-19; additional grey literature searches were undertaken. Study selection and data abstraction was undertaken independently by two authors. Meta-analysis was undertaken using random effects models to compute ratios of means with 95% confidence intervals (95%CIs). Eight published studies and two preprints (n = 1798) were eligible for inclusion. Meta-analysis of mean IL-6 concentrations demonstrated 2.9-fold higher levels in patients with complicated Covid-19 compared with patients with noncomplicated disease (six studies; n = 1302; 95%CI, 1.17-7.19; I2 = 100%). Consistent results were found in sensitivity analyses exclusively restricted to studies comparing patients requiring ICU admission vs no ICU admission (two studies; n = 540; ratio of means = 3.24; 95%CI, 2.54-4.14; P < .001; I2 = 87%). Nine of ten studies were assessed to have at least moderate risk of bias. In patients with Covid-19, IL-6 levels are significantly elevated and associated with adverse clinical outcomes. Inhibition of IL-6 may be a novel target for therapeutics for the management of dysregulated host responses in patients with Covid-19 and high-quality studies of intervention in this field are urgently required.
The global epidemiology of coronavirus disease 2019 (COVID-19) suggests a wide spectrum of clinical severity, ranging from asymptomatic to fatal. Although the clinical and laboratory characteristics of COVID-19 patients have been well characterized, the pathophysiological mechanisms underlying disease severity and progression remain unclear. This review highlights key mechanisms that have been proposed to contribute to COVID-19 progression from viral entry to multisystem organ failure, as well as the central role of the immune response in successful viral clearance or progression to death.
The recent corona virus disease (COVID-19) outbreak has claimed the lives of many around the world and highlighted an urgent need for experimental strategies to prevent, treat and eradicate the virus. COVID-19, an infectious disease caused by a novel corona virus and no approved specific treatment is available yet. A vast number of promising antiviral treatments involving nanotechnology are currently under investigation to aid in the development of COVID-19 drug delivery. The prospective treatment options integrating the ever-expanding field of nanotechnology have been compiled, with the objective to show that these can be potentially developed for COVID-19 treatment. This review summarized the current state of knowledge, research priorities regarding the pandemic and post COVID-19. We also focus on the possible nanotechnology approaches that have proven to be successful against other viruses and the research agenda to combat COVID-19.
The emergence of novel coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 coronavirus, has necessitated the urgent development of new diagnostic and therapeutic strategies. Rapid research and development, on an international scale, has already generated assays for detecting SARS-CoV-2 RNA and host immunoglobulins. However, the complexities of COVID-19 are such that a fuller definition of patient status, trajectory, sequelae and responses to therapy is now required. There is accumulating evidence – from studies of both COVID-19 and the related disease SARS – that protein biomarkers could help to provide this definition. Proteins associated with blood coagulation (D-dimer), cell damage (lactate dehydrogenase) and the inflammatory response (e.g. C-reactive protein) have already been identified as possible predictors of COVID-19 severity or mortality. Proteomics technologies, with their ability to detect many proteins per analysis, have begun to extend these early findings. In order to be effective, proteomics strategies must include not only methods for comprehensive data acquisition (e.g. using mass spectrometry) but also informatics approaches via which to derive actionable information from large data-sets. Here we review applications of proteomics to COVID-19 and SARS, and outline how pipelines involving technologies such as artificial intelligence could be of value for research on these diseases.