Serum Protein Profiling Reveals a Landscape of Inflammation and Immune Signaling in Early-stage COVID-19 Infection

Extraction of naturally occurring peptides versus the tryptic digestion of proteins from fetal versus adult bovine serum for LC-ESI-MS/MS

The naturally occurring peptides and digested proteins of fetal versus adult bovine serum were compared by LC-ESI-MS/MS after correction against noise from blank injections and random MS/MS spectra as statistical controls. Serum peptides were extracted by differential precipitation with mixtures of acetonitrile and water. Serum proteins were separated by partition chromatography over quaternary amine resin followed by tryptic digestion. The rigorous X!TANDEM goodness of fit algorithm that has a low error rate as demonstrated by low FDR q-values (q ≤ 0.01) showed qualitative and quantitative agreement with the SEQUEST cross correlation algorithm on 12,052 protein gene symbols. Tryptic digestion provided a quantitative identification of the serum proteins where observation frequency reflected known high abundance. In contrast, the naturally occurring peptides reflected the cleavage of common serum proteins such as C4A, C3, FGB, HPX, A2M but also proteins in lower concentration such as F13A1, IK, collagens and protocadherins. Proteins associated with cellular growth and development such as actins (ACT), ribosomal proteins like Ribosomal protein S6 (RPS6), synthetic enzymes and extracellular matrix factors were enriched in fetal calf serum. In contrast to the large literature from cord blood, IgG light chains were absent from fetal serum as observed by LC-ESI-MS/MS and confirmed by ELISA.

The impact and inflammatory characteristics of SARS-CoV-2 infection during ovarian stimulation on the outcomes of assisted reproductive treatment

Introduction

Despite the global prevalence of coronavirus disease 2019 (COVID-19), limited research has been conducted on the effects of SARS-CoV-2 infection on human reproduction. The aims of this study were to investigate the impact of SARS-CoV-2 infection during controlled ovarian stimulation (COS) on the outcomes of assisted reproductive treatment (ART) and the cytokine status of patients.

Methods

This retrospective cohort study included 202 couples who received ART treatment, 101 couples infected with SARS-CoV-2 during COS and 101 matched uninfected couples. The parameters of ovarian stimulation and pregnancy outcomes were compared between the two groups. The All-Human Inflammation Array Q3 kit was utilized to measure cytokine levels in both blood and follicular fluid.

Results

No difference was found in the number of good-quality embryos (3.3 ± 3.1 vs. 3.0 ± 2.2, P = 0.553) between the infected and uninfected groups. Among couples who received fresh embryo transfers, no difference was observed in clinical pregnancy rate (53.3% vs. 51.5%, P = 0.907). The rates of fertilization, implantation, miscarriage, ectopic pregnancy and live birth were also comparable between the two groups. After adjustments were made for confounders, regression models indicated that the quality of embryos (B = 0.16, P = 0.605) and clinical pregnancy rate (P = 0.206) remained unaffected by SARS-CoV-2 infection. The serum levels of MCP-1, TIMP-1, I-309, TNF-RI and TNF-RII were increased, while that of eotaxin-2 was decreased in COVID-19 patients. No significant difference was found in the levels of cytokines in follicular fluid between the two groups.

Conclusion

Asymptomatic or mild COVID-19 during COS had no adverse effects on ART outcomes. Although mild inflammation was present in the serum, it was not detected in the follicular fluid of these patients. The subsequent immune response needs further investigation.

CoVProt: Toward a Mass Spectrometry Data Portal for COVID-19 Proteomics Research and Development

The coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc globally. Beyond the pandemic, the long-term effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in multiple organ systems are yet to be deciphered. This calls for continued systems science research. Moreover, the host response to SARS-CoV-2 varies person-to-person and gives rise to different degrees of morbidity and mortality. Mass spectrometry (MS) has been a proven asset in studies of the SARS-CoV-2 from an omics systems science lens. To strengthen the proteomics research dedicated to COVID-19, we introduce here a web-based portal, CoVProt. The portal is work in progress and aims for a comprehensive curation of MS-based proteomics data of COVID-19 clinical samples for deep proteomic investigations, data visualization, and easy data accessibility for life sciences innovations and planetary health research community. Currently, CoVProt contains information on 2725 different proteins and 37,125 different peptides from six data sets covering a total of 202 clinical samples. Moreover, all pertinent data sets extracted from the literature have been reanalyzed using a common analysis pipeline developed by combining multiple tools. Going forward, we anticipate that the CoVProt portal will also provide access to the clinical parameters of the patients. The CoVProt (v1.0) portal addresses an existing significant gap to study COVID-19 host proteomics, which, to the best of our knowledge, is the first effort in this direction. We believe that CoVProt is poised to make contributions as a community resource for proteomic applications and aims to broadly support clinical studies to facilitate the discovery of COVID-19 biomarkers and therapeutics with translational potential.

Comprehensive proteomics and meta-analysis of COVID-19 host response

COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community.

Immune and cytokine alterations and RNA-sequencing analysis in gestational tissues from pregnant women after recovery from COVID-19

BACKGROUND

COVID-19 is a global pandemic. Understanding the immune responses in pregnant women recovering from COVID-19 may suggest new therapeutic approaches.

METHODS

We performed a cross-sectional study between March 1, 2020, and September 1, 2020. Participants were assigned into the convalescent COVID-19 group if they had a previous COVID-19 infection during pregnancy or the healthy control group. RNA-Seq was performed on human umbilical cord mesenchymal stem cells (hUMSCs) and human amniotic mesenchymal stem cells (hAMSCs). Immunohistochemical staining, cytokine testing, lymphocyte subset analysis, RNA-Seq, and functional analyses were performed on the placental and umbilical cord blood (UCB) and compared between the two groups.

RESULTS

A total of 40 pregnant women were enrolled, with 13 in the convalescent group and 27 in the control group. There were 1024, 46, and 32 differentially expressed genes (DEGs) identified in the placental tissue, hUMSCs, and hAMSCs between the convalescent and control groups, respectively. Enrichment analysis showed those DEGs were associated with immune homeostasis, antiviral activity, cell proliferation, and tissue repair. Levels of IL-6, TNF-α, total lymphocyte counts, B lymphocytes, Tregs percentages, and IFN-γ expressing CD4+ and CD8+ T cells were statistically different between two groups (p ≤ 0.05). ACE2 and TMPRSS2 expressed on the placenta were not different between the two groups (p > 0.05).

CONCLUSION

Multiple changes in immune responses occurred in the placental tissue, hUMSCs, and hAMSCs after maternal recovery from COVID-19, which might imply their protective roles against COVID-19 infection.

Proteomics Identifies Circulating TIMP-1 as a Prognostic Biomarker for Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, although disease stratification using in-depth plasma proteomics has not been performed to date. By measuring more than 1000 proteins in the plasma of 147 DLBCL patients using data-independent acquisition mass spectrometry and antibody array, DLBCL patients were classified into four proteomic subtypes (PS-I-IV). Patients with the PS-IV subtype and worst prognosis had increased levels of proteins involved in inflammation, including a high expression of metalloproteinase inhibitor-1 (TIMP-1) that was associated with poor survival across two validation cohorts (n = 180). Notably, the combination of TIMP-1 with the international prognostic index (IPI) identified 64.00% to 88.24% of relapsed and 65.00% to 80.49% of deceased patients in the discovery and two validation cohorts, which represents a 24.00% to 41.67% and 20.00% to 31.70% improvement compared to the IPI score alone, respectively. Taken together, we demonstrate that DLBCL heterogeneity is reflected in the plasma proteome and that TIMP-1, together with the IPI, could improve the prognostic stratification of patients.

Detection of Mutant Peptides of SARS-CoV-2 Variants by LC/MS in the DDA Approach Using an In-House Database

Equipped with a dramatically high mutation rate, which happens to be a signature of RNA viruses, SARS-CoV-2 trampled across the globe infecting individuals of all ages and ethnicities. As the variants of concern (VOC) loomed large, definitive detection of SARS-CoV-2 strains became a matter of utmost importance in epidemiological and clinical research. Besides, unveiling the disease pathogenesis at the molecular level and deciphering the therapeutic targets became key priorities since the emergence of the pandemic. Mass spectrometry has been largely used in this regard. A critical part of mass spectrometric analyses is the proteome database required for the identification of peptides. Presently, the mutational information on proteins available on SARS-CoV-2 databases cannot be used to analyze data extracted from mass spectrometers. Hence, we developed the novel Mutant Peptide Database (MPD) for the mass spectrometry (MS)-based identification of mutated peptides, which contains information from 11 proteins of SARS-CoV-2 from a total of 21,549 SARS-CoV-2 variants across different regions of India. The database was validated using clinical samples, and its applicability was also demonstrated with the mutated peptides extracted from the literature. We believe that MPD will support broad-spectrum MS-based studies like viral detection, disease pathogenesis, and therapeutics with respect to SARS-CoV-2 and its variants.

In-depth serum proteomics reveals the trajectory of hallmarks of cancer in hepatitis B virus-related liver diseases

Hepatocellular carcinoma (HCC) is a prevalent cancer in China, with chronic hepatitis B (CHB) and liver cirrhosis (LC) being high-risk factors for developing HCC. Here, we determined the serum proteomes (762 proteins) of 125 healthy controls and Hepatitis B virus-infected CHB, LC, and HCC patients and constructed the first cancerous trajectory of liver diseases. The results not only reveal that the majority of altered biological processes were involved in the hallmarks of cancer (inflammation, metastasis, metabolism, vasculature, coagulation), but also identify potential therapeutic targets in cancerous pathways (i.e., IL17 signaling pathway). Notably, the biomarker panels for detecting HCC in CHB and LC high-risk populations were further developed using machine learning in two cohorts comprised of 200 samples (discovery cohort=125, validation cohort=75). The protein signatures significantly improved the area under the receiver operating characteristic curve (AUC) of HCC (CHB discovery and validation cohort = 0.953 and 0.891, respectively; LC discovery and validation cohort = 0.966 and 0.818, respectively) compared to using the traditional biomarker, alpha-fetoprotein (AFP), alone. Finally, selected biomarkers were validated with parallel reaction monitoring (PRM) mass spectrometry in an additional cohort (n=120). Altogether, our results provide fundamental insights into the continuous changes of cancer biology processes in liver diseases and identify candidate protein targets for early detection and intervention.

Increase of mast cells in COVID-19 pneumonia may contribute to pulmonary fibrosis and thrombosis

AIMS

Lung tissue from COVID-19 patients shares similar histomorphological features with chronic lung allograft disease, also suggesting activation of autoimmune-related pathways in COVID-19. To more clearly understand the underlying spectrum of pathophysiology in COVID-19 pneumonia, we analysed mRNA expression of autoimmune-related genes in post-mortem lung tissue from COVID-19 patients.

METHODS AND RESULTS

Formalin-fixed, paraffin-embedded lung tissue samples of 18 COVID-19 patients and eight influenza patients were used for targeted gene expression profiling using NanoString technology. Multiplex immunofluorescence for tryptase and chymase was applied for validation. Genes related to mast cells were significantly increased in COVID-19. This finding was strengthened by multiplex immunofluorescence also showing a significant increase of tryptase- and chymase-positive cells in COVID-19. Furthermore, receptors for advanced glycation end-products (RAGE) and pro-platelet basic protein (PPBP) were up-regulated in COVID-19 compared to influenza. Genes associated with Type I interferon signalling showed a significant correlation to detected SARS-CoV2 pathway-related genes. The comparison of lung tissue samples from both groups based on the presence of histomorphological features indicative of acute respiratory distress syndrome did not result in finding any specific gene or pathways.

CONCLUSION

Two separate means of measuring show a significant increase of mast cells in SARS-CoV-2-infected lung tissue compared to influenza. Additionally, several genes involved in fibrosis and thrombosis, among which are RAGE and PPBP, are up-regulated in COVID-19. As mast cells are able to induce thrombosis and fibrosis, they may play an important role in the pathogenesis of COVID-19.

Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS

BACKGROUND

Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis.

METHODS

We performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). To this end, we used two different approaches, first we compared the molecular omics profiles between ARDS groups, and second, we correlated clinical manifestations within each group with the omics profiles.

RESULTS

The comparison of the two ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis.

CONCLUSION

In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes.

Circulating Peptidome Is Strongly Altered in COVID-19 Patients

Whilst the impact of coronavirus disease 2019 (COVID-19) on the host proteome, metabolome, and lipidome has been largely investigated in different bio-fluids, to date, the circulating peptidome remains unexplored. Thus, the present study aimed to apply an untargeted peptidomic approach to provide insight into alterations of circulating peptides in the development and severity of SARS-CoV-2 infection. The circulating peptidome from COVID-19 severe and mildly symptomatic patients and negative controls was characterized using LC-MS/MS analysis for identification and quantification purposes. Database search and statistical analysis allowed a complete characterization of the plasma peptidome and the detection of the most significant modulated peptides that were impacted by the infection. Our results highlighted not only that peptide abundance inversely correlates with disease severity, but also the involvement of biomolecules belonging to inflammatory, immune-response, and coagulation proteins/processes. Moreover, our data suggested a possible involvement of changes in protein degradation patterns. In the present research, for the first time, the untargeted peptidomic approach enabled the identification of circulating peptides potentially playing a crucial role in the progression of COVID-19.

Noninvasive nasopharyngeal proteomics of COVID-19 patient identify abnormalities related to complement and coagulation cascade and mucosal immune system

Serum or plasma have been the primary focus of proteomics studies for COVID-19 to identity biomarkers and potential drug targets. The nasal mucosal environment which consists of lipids, mucosal immune cells, and nasal proteome, has been largely neglected but later revealed to have critical role combating SARS-CoV-2 infection. We present a bottom-up proteomics investigation of the host response to SARS-CoV-2 infection in the nasopharyngeal environment, featuring a noninvasive approach using proteins in nasopharyngeal swabs collected from groups of 76 SARS-CoV-2 positive and 76 negative patients. Results showed that 31 significantly down-regulated and 6 up-regulated proteins were identified (p < 0.05, log₂ FC > 1.3) in SARS-CoV-2 positive patient samples as compared to the negatives; these proteins carry potential value as markers for the early detection of COVID-19, disease monitoring, as well as be drug targets. The down-regulation of coagulation factor 5 indicates a thrombotic abnormality in COVID-19 patients and the decreased IgG4 suggests an abnormal immune response at the point of entry in human nasopharyngeal environment, which is in consistent with KEGG and GO pathway analysis. Our study also demonstrated that mass spectrometry proteomics analysis of nasopharyngeal swabs can be used as a powerful early approach to evaluate host response to SARS-CoV-2 viral infection.

Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS

BACKGROUND

Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions.

METHODS AND FINDINGS

In this study, we compared COVID-19 ARDS (n = 43) and bacterial sepsis-induced (non-COVID-19) ARDS (n = 24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within- ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation.

CONCLUSION

We present a first comprehensive molecular characterization of differences between two ARDS etiologies-COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.

Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS

Background

Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions.

Methods and Findings

In this study, we compared COVID-19 ARDS (n=43) and bacterial sepsis-induced (non-COVID-19) ARDS (n=24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within-ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation.

Conclusion

We present a first comprehensive molecular characterization of differences between two ARDS etiologies - COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.

Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS

Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis. In this study, we performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). The comparison of these ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis. In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes.

Rise of the SARS-CoV-2 Variants: can proteomics be the silver bullet?

INTRODUCTION

The challenges posed by emergent strains of SARS-CoV-2 need to be tackled by contemporary scientific approaches, with proteomics playing a significant role.

AREAS COVERED

In this review, we provide a brief synthesis of the impact of proteomics technologies in elucidating disease pathogenesis and classifiers for the prognosis of COVID-19 and propose proteomics methodologies that could play a crucial role in understanding emerging variants and their altered disease pathology. From aiding the design of novel drug candidates to facilitating the identification of T cell vaccine targets, we have discussed the impact of proteomics methods in COVID-19 research. Techniques varied as mass spectrometry, single-cell proteomics, multiplexed ELISA arrays, high-density proteome arrays, surface plasmon resonance, immunopeptidomics, and in silico docking studies that have helped augment the fight against existing diseases were useful in preparing us to tackle SARS-CoV-2 variants. We also propose an action plan for a pipeline to combat emerging pandemics using proteomics technology by adopting uniform standard operating procedures and unified data analysis paradigms.

EXPERT OPINION

The knowledge about the use of diverse proteomics approaches for COVID-19 investigation will provide a framework for future basic research, better infectious disease prevention strategies, improved diagnostics, and targeted therapeutics.

COVIDomics: The Proteomic and Metabolomic Signatures of COVID-19

Omics-based technologies have been largely adopted during this unprecedented global COVID-19 pandemic, allowing the scientific community to perform research on a large scale to understand the pathobiology of the SARS-CoV-2 infection and its replication into human cells. The application of omics techniques has been addressed to every level of application, from the detection of mutations, methods of diagnosis or monitoring, drug target discovery, and vaccine generation, to the basic definition of the pathophysiological processes and the biochemical mechanisms behind the infection and spread of SARS-CoV-2. Thus, the term COVIDomics wants to include those efforts provided by omics-scale investigations with application to the current COVID-19 research. This review summarizes the diverse pieces of knowledge acquired with the application of COVIDomics techniques, with the main focus on proteomics and metabolomics studies, in order to capture a common signature in terms of proteins, metabolites, and pathways dysregulated in COVID-19 disease. Exploring the multiomics perspective and the concurrent data integration may provide new suitable therapeutic solutions to combat the COVID-19 pandemic.

Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications

COVID-19 complications still present a huge burden on healthcare systems and warrant predictive risk models to triage patients and inform early intervention. Here, we profile 893 plasma proteins from 50 severe and 50 mild-moderate COVID-19 patients, and 50 healthy controls, and show that 375 proteins are differentially expressed in the plasma of severe COVID-19 patients. These differentially expressed plasma proteins are implicated in the pathogenesis of COVID-19 and present targets for candidate drugs to prevent or treat severe complications. Based on the plasma proteomics and clinical lab tests, we also report a 12-plasma protein signature and a model of seven routine clinical tests that validate in an independent cohort as early risk predictors of COVID-19 severity and patient survival. The risk predictors and candidate drugs described in our study can be used and developed for personalized management of SARS-CoV-2 infected patients.

Prognostic markers for patients with COVID-19 are of critical importance in determining the course of SARS-CoV-2 infection and patient handling. Here the authors determine and apply a prognostic proteomic panel for risk and drug prediction in the management of SARS-CoV-2 infected patients.

Looking at COVID-19 from a Systems Biology Perspective

The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characteristic of the network medicine, to approach the study of the pathobiology. Proteomics and interactomics especially allow to generate datasets that, reduced and represented in the forms of networks, can be analyzed with the tools of systems biology to unveil specific pathways central to virus-human host interaction. Moreover, artificial intelligence tools can be implemented for the identification of druggable targets and drug repurposing. In this review article, we provide an overview of the results obtained so far, from a systems biology perspective, in the understanding of COVID-19 pathobiology and virus-host interactions, and in the development of disease classifiers and tools for drug repurposing.

Antibody-Based Affinity Capture Combined with LC-MS Analysis for Identification of COVID-19 Disease Serum Biomarkers

Blood serum or plasma proteins are potentially useful in COVID-19 research as biomarkers for risk prediction, diagnosis, stratification, and treatment monitoring. However, serum protein-based biomarker identification and validation is complicated due to the wide concentration range of these proteins, which spans more than ten orders of magnitude. Here we present a combined affinity purification-liquid chromatography mass spectrometry approach which allows identification and quantitation of the most abundant serum proteins along with the nonspecifically bound and interaction proteins. This led to the reproducible identification of more than 100 proteins that were not specifically targeted by the affinity column. Many of these have already been implicated in COVID-19 disease.

Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19

Background: The COVID-19 pandemic poses an imminent threat to humanity, especially for those who have comorbidities. Evidence of COVID-19 and COPD comorbidities is accumulating. However, data revealing the molecular mechanism of COVID-19 and COPD comorbid diseases is limited. Methods: We got COVID-19/COPD -related genes from different databases by restricted screening conditions (top500), respectively, and then supplemented with COVID-19/COPD-associated genes (FDR<0.05, |LogFC|≥1) from clinical sample data sets. By taking the intersection, 42 co-morbid host factors for COVID-19 and COPD were finally obtained. On the basis of shared host factors, we conducted a series of bioinformatics analysis, including protein-protein interaction analysis, gene ontology and pathway enrichment analysis, transcription factor-gene interaction network analysis, gene-microRNA co-regulatory network analysis, tissue-specific enrichment analysis and candidate drug prediction. Results: We revealed the comorbidity mechanism of COVID-19 and COPD from the perspective of host factor interaction, obtained the top ten gene and 3 modules with different biological functions. Furthermore, we have obtained the signaling pathways and concluded that dexamethasone, estradiol, progesterone, and nitric oxide shows effective interventions. Conclusion: This study revealed host factor interaction networks for COVID-19 and COPD, which could confirm the potential drugs for treating the comorbidity, ultimately, enhancing the management of the respiratory disease.

Next generation plasma proteome profiling of COVID-19 patients with mild to moderate symptoms

Background

COVID-19 has caused millions of deaths globally, yet the cellular mechanisms underlying the various effects of the disease remain poorly understood. Recently, a new analytical platform for comprehensive analysis of plasma protein profiles using proximity extension assays combined with next generation sequencing has been developed, which allows for multiple proteins to be analyzed simultaneously without sacrifice on accuracy or sensitivity.

Methods

We analyzed the plasma protein profiles of COVID-19 patients (n = 50) with mild and moderate symptoms by comparing the protein levels in newly diagnosed patients with the protein levels in the same individuals after 14 days.

Findings

The study has identified more than 200 proteins that are significantly elevated during infection and many of these are related to cytokine response and other immune-related functions. In addition, several other proteins are shown to be elevated, including SCARB2, a host cell receptor protein involved in virus entry. A comparison with the plasma protein response in patients with severe symptoms shows a highly similar pattern, but with some interesting differences.

Interpretation

The study presented here demonstrates the usefulness of “next generation plasma protein profiling” to identify molecular signatures of importance for disease progression and to allow monitoring of disease during recovery from the infection. The results will facilitate further studies to understand the molecular mechanism of the immune-related response of the SARS-CoV-2 virus.

Funding

This work was financially supported by Knut and Alice Wallenberg Foundation.

Generation and Export of Red Blood Cell ATP in Health and Disease

Metabolic homeostasis in animals depends critically on evolved mechanisms by which red blood cell (RBC) hemoglobin (Hb) senses oxygen (O₂) need and responds accordingly. The entwined regulation of ATP production and antioxidant systems within the RBC also exploits Hb-based O₂-sensitivity to respond to various physiologic and pathophysiologic stresses. O₂ offloading, for example, promotes glycolysis in order to generate both 2,3-DPG (a negative allosteric effector of Hb O₂ binding) and ATP. Alternatively, generation of the nicotinamide adenine dinucleotide phosphate (NADPH) critical for reducing systems is favored under the oxidizing conditions of O₂ abundance. Dynamic control of ATP not only ensures the functional activity of ion pumps and cellular flexibility, but also contributes to the availability of vasoregulatory ATP that can be exported when necessary, for example in hypoxia or upon RBC deformation in microvessels. RBC ATP export in response to hypoxia or deformation dilates blood vessels in order to promote efficient O₂ delivery. The ability of RBCs to adapt to the metabolic environment via differential control of these metabolites is impaired in the face of enzymopathies [pyruvate kinase deficiency; glucose-6-phosphate dehydrogenase (G6PD) deficiency], blood banking, diabetes mellitus, COVID-19 or sepsis, and sickle cell disease. The emerging availability of therapies capable of augmenting RBC ATP, including newly established uses of allosteric effectors and metabolite-specific additive solutions for RBC transfusates, raises the prospect of clinical interventions to optimize or correct RBC function via these metabolite delivery mechanisms.

Immune response pattern across the asymptomatic, symptomatic and convalescent periods of COVID-19

We present an integrated analysis of urine and serum proteomics and clinical measurements in asymptomatic, mild/moderate, severe and convalescent cases of COVID-19. We identify the pattern of immune response during COVID-19 infection. The immune response is activated in asymptomatic infection, but is dysregulated in mild and severe COVID-19 patients. Our data suggest that the turning point depends on the function of myeloid cells and neutrophils. In addition, immune defects persist into the recovery stage, until 12 months after diagnosis. Moreover, disorders of cholesterol metabolism span the entire progression of the disease, starting from asymptomatic infection and lasting to recovery. Our data suggest that prolonged dysregulation of the immune response and cholesterol metabolism might be the pivotal causative agent of other potential sequelae. Our study provides a comprehensive understanding of COVID-19 immunopathogenesis, which is instructive for the development of early intervention strategies to ameliorate complex disease sequelae.

Advances and Utility of the Human Plasma Proteome

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

Mass Spectrometry-based Proteomics and Glycoproteomics in COVID-19 Biomarkers Identification: A Mini-review

The first corona-pandemic, coronavirus disease 2019 (COVID-19) caused a huge health crisis and incalculable damage worldwide. Knowledge of how to cure the disease is urgently needed. Emerging immune escaping mutants of the virus suggested that it may be potentially persistent in human society as a regular health threat as the flu virus. Therefore, it is imperative to identify appropriate biomarkers to indicate pathological and physiological states, and more importantly, clinic outcomes. Proteins are the performers of life functions, and their abundance and modification status can directly reflect the immune status. Protein glycosylation serves a great impact in modulating protein function. The use of both unmodified and glycosylated proteins as biomarkers has also been proved feasible in the studies of SARS, Zika virus, influenza, etc. In recent years, mass spectrometry-based glycoproteomics, as well as proteomics approaches, advanced significantly due to the evolution of mass spectrometry. We focus on the current development of the mass spectrometry-based strategy for COVID-19 biomarkers' investigation. Potential application of glycoproteomics approaches and challenges in biomarkers identification are also discussed.

Application of omics technology to combat the COVID-19 pandemic

As of August 27, 2021, the ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to over 220 countries, areas, and territories. Thus far, 214,468,601 confirmed cases, including 4,470,969 deaths, have been reported to the World Health Organization. To combat the COVID-19 pandemic, multiomics-based strategies, including genomics, transcriptomics, proteomics, and metabolomics, have been used to study the diagnosis methods, pathogenesis, prognosis, and potential drug targets of COVID-19. In order to help researchers and clinicians to keep up with the knowledge of COVID-19, we summarized the most recent progresses reported in omics-based research papers. This review discusses omics-based approaches for studying COVID-19, summarizing newly emerged SARS-CoV-2 variants as well as potential diagnostic methods, risk factors, and pathological features of COVID-19. This review can help researchers and clinicians gain insight into COVID-19 features, providing direction for future drug development and guidance for clinical treatment, so that patients can receive appropriate treatment as soon as possible to reduce the risk of disease progression.

Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19

The worldwide pandemic of coronavirus disease 2019 (COVID-19) presents us with a serious public health crisis. To combat the virus and slow its spread, wider testing is essential. There is a need for more sensitive, specific, and convenient detection methods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Advanced detection can greatly improve the ability and accuracy of the clinical diagnosis of COVID-19, which is conducive to the early suitable treatment and supports precise prophylaxis. In this article, we combine and present the latest laboratory diagnostic technologies and methods for SARS-CoV-2 to identify the technical characteristics, considerations, biosafety requirements, common problems with testing and interpretation of results, and coping strategies of commonly used testing methods. We highlight the gaps in current diagnostic capacity and propose potential solutions to provide cutting-edge technical support to achieve a more precise diagnosis, treatment, and prevention of COVID-19 and to overcome the difficulties with the normalization of epidemic prevention and control.

Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome - A multi-omics big data study

Coronavirus disease 2019 (COVID-19) is a viral pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that led to more than 800,00 deaths and continues to be a major threat worldwide. The scientific community has been studying the risk factors associated with SARS-CoV-2 infection and pathogenesis. Recent studies highlight the possible contribution of atmospheric air pollution, specifically particulate matter (PM) exposure as a co-factor in COVID-19 severity. Hence, meaningful translation of suitable omics datasets of SARS-CoV-2 infection and PM exposure is warranted to understand the possible involvement of airborne exposome on COVID-19 outcome. Publicly available transcriptomic data (microarray and RNA-Seq) related to COVID-19 lung biopsy, SARS-CoV-2 infection in epithelial cells and PM exposure (lung tissue, epithelial and endothelial cells) were obtained in addition with proteome and interactome datasets. System-wide pathway/network analysis was done through appropriate software tools and data resources. The primary findings are; 1. There is no robust difference in the expression of SARS-CoV-2 entry factors upon particulate exposure, 2. The upstream pathways associated with upregulated genes during SARS-CoV-2 infection considerably overlap with that of PM exposure, 3. Similar pathways were differentially expressed during SARS-CoV-2 infection and PM exposure, 4. SARS-CoV-2 interacting host factors were predicted to be associated with the molecular impact of PM exposure and 5. Differentially expressed pathways during PM exposure may increase COVID-19 severity. Based on the observed molecular mechanisms (direct and indirect effects) the current study suggests that airborne PM exposure has to be considered as an additional co-factor in the outcome of COVID-19.

Proteomic Analysis Identifies Prolonged Disturbances in Pathways Related to Cholesterol Metabolism and Myocardium Function in the COVID-19 Recovery Stage

The COVID-19 pandemic has become a worldwide health crisis. So far, most studies have focused on the epidemiology and pathogenesis of this infectious disease. Little attention has been given to the disease sequelae in patients recovering from COVID-19, and nothing is known about the mechanisms underlying these sequelae. Herein, we profiled the serum proteome of a cohort of COVID-19 patients in the disease onset and recovery stages. Based on the close integration of our proteomic analysis with clinical data, we propose that COVID-19 is associated with prolonged disorders in cholesterol metabolism and myocardium, even in the recovery stage. We identify potential biomarkers for these disorders. Moreover, severely affected patients presented more serious disturbances in these pathways. Our findings potentially support clinical decision-making to improve the prognosis and treatment of patients.

Discovery of plasma biomarkers with data-independent acquisition mass spectrometry and antibody microarray for diagnosis and risk stratification of pulmonary embolism

BACKGROUND

Pulmonary embolism (PE) is a leading cause of cardiovascular mortality worldwide. Rapid and accurate diagnosis and risk stratification are crucial for timely treatment options, especially in high-risk PE.

OBJECTIVES

The study aims to profile the comprehensive changes of plasma proteomes in PE patients and identify the potential biomarkers for both diagnosis and risk stratification.

PATIENTS/METHODS

Based on the data-independent acquisition mass spectrometry and antibody array proteomic technology, we screened the plasma samples (13 and 32 proteomes, respectively) in two independent studies consisting of high-risk PE patients, non-high-risk PE patients, and healthy controls. Some significantly differentially expressed proteins were quantified by ELISA in a new study group with 50 PE patients and 26 healthy controls.

RESULTS

We identified 207 and 70 differentially expressed proteins in PE and high-risk PE. These proteins were involved in multiple thrombosis-associated biological processes including blood coagulation, inflammation, injury, repair, and chemokine-mediated cellular response. It was verified that five proteins including SAA1, S100A8, TNC, GSN, and HRG had significant change in PE and/or in high-risk PE. The receiver operating characteristic curve analysis based on binary logistic regression showed that the area under the curve (AUC) of SAA1, S100A8, and TNC in PE diagnosis were 0.882, 0.788, and 0.795, and AUC of S100A8 and TNC in high-risk PE diagnosis were 0.773 and 0.720.

CONCLUSION

As predictors of inflammation or injury repair, SAA1, S100A8, and TNC are potential plasma biomarkers for the diagnosis and risk stratification of PE.

Quantitative proteomics of hamster lung tissues infected with SARS-CoV-2 reveal host factors having implication in the disease pathogenesis and severity

Syrian golden hamsters (Mesocricetus auratus) infected by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) manifests lung pathology. In this study, efforts were made to check the infectivity of a local SARS‐CoV‐2 isolate in a self‐limiting and non‐lethal hamster model and evaluate the differential expression of lung proteins during acute infection and convalescence. The findings of this study confirm the infectivity of this isolate in vivo. Analysis of clinical parameters and tissue samples show the pathophysiological manifestation of SARS‐CoV‐2 infection similar to that reported earlier in COVID‐19 patients and hamsters infected with other isolates. However, diffuse alveolar damage (DAD), a common histopathological feature of human COVID‐19 was only occasionally noticed. The lung‐associated pathological changes were very prominent on the 4th day post‐infection (dpi), mostly resolved by 14 dpi. Here, we carried out the quantitative proteomic analysis of the lung tissues from SARS‐CoV‐2‐infected hamsters on day 4 and day 14 post‐infection. This resulted in the identification of 1585 proteins of which 68 proteins were significantly altered between both the infected groups. Pathway analysis revealed complement and coagulation cascade, platelet activation, ferroptosis, and focal adhesion as the top enriched pathways. In addition, we also identified altered expression of two pulmonary surfactant‐associated proteins (Sftpd and Sftpb), known for their protective role in lung function. Together, these findings will aid in understanding the mechanism(s) involved in SARS‐CoV‐2 pathogenesis and progression of the disease.

Proteomics-Based Insights Into the SARS-CoV-2-Mediated COVID-19 Pandemic: A Review of the First Year of Research

In late 2019, a virus subsequently named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China and led to a worldwide pandemic of the disease termed coronavirus disease 2019. The global health threat posed by this pandemic led to an extremely rapid and robust mobilization of the scientific and medical communities as evidenced by the publication of more than 10,000 peer-reviewed articles and thousands of preprints in the first year of the pandemic alone. With the publication of the initial genome sequence of SARS-CoV-2, the proteomics community immediately joined this effort publishing, to date, more than 100 peer-reviewed proteomics studies and submitting many more preprints to preprint servers. In this review, we focus on peer-reviewed articles published on the proteome, glycoproteome, and glycome of SARS-CoV-2. At a basic level, proteomic studies provide valuable information on quantitative aspects of viral infection course; information on the identities, sites, and microheterogeneity of post-translational modifications; and, information on protein-protein interactions. At a biological systems level, these studies elucidate host cell and tissue responses, characterize antibodies and other immune system factors in infection, suggest biomarkers that may be useful for diagnosis and disease-course monitoring, and help in the development or repurposing of potential therapeutics. Here, we summarize results from selected early studies to provide a perspective on the current rapidly evolving literature.

Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics

The COVID-19 pandemic constitutes an ongoing worldwide threat to human society and has caused massive impacts on global public health, the economy and the political landscape. The key to gaining control of the disease lies in understanding the genetics of SARS-CoV-2 and the disease spectrum that follows infection. This study leverages traditional and intelligent bibliometric methods to conduct a multi-dimensional analysis on 5,632 COVID-19 genetic research papers, revealing that 1) the key players include research institutions from the United States, China, Britain and Canada; 2) research topics predominantly focus on virus infection mechanisms, virus testing, gene expression related to the immune reactions and patient clinical manifestation; 3) studies originated from the comparison of SARS-CoV-2 to previous human coronaviruses, following which research directions diverge into the analysis of virus molecular structure and genetics, the human immune response, vaccine development and gene expression related to immune responses; and 4) genes that are frequently highlighted include ACE2, IL6, TMPRSS2, and TNF. Emerging genes to the COVID-19 consist of FURIN, CXCL10, OAS1, OAS2, OAS3, and ISG15. This study demonstrates that our suite of novel bibliometric tools could help biomedical researchers follow this rapidly growing field and provide substantial evidence for policymakers’ decision-making on science policy and public health administration.

Mumbai mayhem of COVID-19 pandemic reveals important factors that influence susceptibility to infection

BACKGROUND

COVID-19 severity is disproportionately high in the elderly and people with comorbidities. However, other factors that predispose individuals to increased chances of infection are unclear.

METHODS

Data from 18,600 people screened for COVID-19 in Mumbai during the outbreak's initial phase, March 7 to June 30, 2020, were used to assess risk factors associated with COVID-19 using the odds ratio analysis.

FINDINGS

Males aged ≥60 years having both diabetes and hypertension were at the highest risk of COVID-19 infection (M vs. F OR=2.5, 95% CI=1.34-4.67, p = 0.0049). People having both diabetes and hypertension in ≥20 years (OR=4.11, 95% CI=3.26-5.20, p <0.0001), diabetes and hypertension independently in 20-39 (OR=4.13, 95% CI=2.22-7.70, p <0.0001, OR=4.32, 95% CI=2.10-8.88, p = 0.0001) and ≥60 years (OR=2.69, 95% CI=1.87-3.87, p <0.0001, OR=2.03, 95% CI=1.46-2.82, p <0.0001), chronic renal disease in 20-39 years (OR=5.38, 95% CI=1.91-15.09, p = 0.0007) age groups had significantly higher risk of COVID-19 infection than those without comorbidity. Quarantined people had significantly lower positive odds (OR=0.59, 95% CI=0.53-0.66, p <0.001) than non-quarantined people.

INTERPRETATION

Our research indicates that the risk of getting COVID-19 disease is not equal. When considering sex, age, and comorbidity together, we found that males aged ≥60 years and having both diabetes and hypertension had a significantly high risk of COVID-19 infection. Therefore, remedial measures such as vaccination programs should be prioritized for at-risk individuals.

FUNDING

SERB, India: SB/S1/COVID-2/2020 and Seed grant RD/0520-IRCCHC0-006 from IRCC, IIT Bombay.

Nanotechnology to the Rescue: Treatment Perspective for the Immune Dysregulation Observed in COVID-19

The study of the use of nanotechnology for drug delivery has been extensive. Nanomedical approaches for therapeutics; drug delivery in particular is superior to conventional methods in that it allows for controlled targeted delivery and release, higher stability, extended circulation time, minimal side-effects, and improved pharmacokinetic clearance (of the drug) form the body, to name a few. The magnitude of COVID-19, the current ongoing pandemic has been severe; it has caused widespread the loss of human life. In individuals with severe COVID-19, immune dysregulation and a rampant state of hyperinflammation is observed. This kind of an immunopathological response is detrimental and results in rapid disease progression, development of secondary infections, sepsis and can be fatal. Several studies have pin-pointed the reason for this immune dysregulation; deviations in the signaling pathways involved in the mediation and control of immune responses. In severe COVID-19 patients, many signaling cascades including JAK/STAT, NF-κB, MAPK/ERK, TGF beta, VEGF, and Notch signaling were found to be either upregulated or inactivated. Targeting these aberrant signaling pathways in conjunction with antiviral therapy will effectuate mitigation of the hyperinflammation, hypercytokinemia, and promote faster recovery. The science of the use of nanocarriers as delivery agents to modulate these signaling pathways is not new; it has already been explored for other inflammatory diseases and in particular, cancer therapy. Numerous studies have evaluated the efficacy and potential of nanomedical approaches to modulate these signaling pathways and have been met with positive results. A treatment regime, that includes nanotherapeutics and antiviral therapies will prove effective and holds great promise for the successful treatment of COVID-19. In this article, we review different nanomedical approaches already studied for targeting aberrant signaling pathways, the host immune response to SARS-CoV-2, immunopathology and the dysregulated signaling pathways observed in severe COVID-19 and the current treatment methods in use for targeting signaling cascades in COVID-19. We then conclude by suggesting that the use of nanomedical drug delivery systems for targeting signaling pathways can be extended to effectively target the aberrant signaling pathways in COVID-19 for best treatment results.

Prognostic bioindicators in severe COVID-19 patients

Background

Severe acute respiratory syndrome caused by novel coronavirus 2 (SARS-CoV-2) emerged in Wuhan (China) in December 2019. Here we evaluated a panel of biomarkers to phenotype patients and to define the role of immuno-inflammatory mediators as biomarkers of severity.

Materials and methods

Serum samples were obtained from 24 COVID-19 patients on admission to hospital, before any treatment or infusion of intravenous steroids or invasive ventilation. KL-6 IL-6 and C-peptide were measured by chemiluminescent enzyme immunoassay. IL-6 assay was validated for accuracy and precision. The validity of variables used to distinguish severe from mild-to-moderate patients was assessed by areas under curves (AUC) of the receiver operating characteristic (ROC) and logistic regression was performed to combine parameters of the two groups.

Results

In the severe group, IL-6, CRP and KL-6 concentrations were significantly higher than in mild-to-moderate patients. KL-6, IL-6 and CRP concentrations were directly correlated with each other. ROC curve analysis of the logistic regression model including IL-6, KL-6 and CRP showed the best performance with an AUC of 0.95.

Conclusions

Besides corroborating previous reports of over-expression of IL-6 in severe COVID-19 patients requiring mechanical ventilation, analytical determination of other mediators showed that IL-6 concentrations were correlated with those of KL-6 and CRP. The combination of these three prognostic bioindicators made it possible to distinguish severe COVID-19 patients with poor prognosis from mild-to-moderate patients.

Progress in understanding COVID-19: insights from the omics approach

Sequencing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome is a crucial task for controlling the ongoing coronavirus disease (COVID-19) pandemic. However, elucidating the pathological mechanisms of SARS-CoV-2 in humans has been challenging. A comprehensive analysis of the molecular characteristics of SARS-CoV-2 and molecular changes in COVID-19 patients may have practical significance in developing assays for the detection of SARS-CoV-2 and formulating clinical treatment strategies against COVID-19. The omics approach for studying biochemical mechanisms can be used to elucidate the molecular characteristics and pathophysiology of SARS-CoV-2. The omics-scale research on COVID-19 has been carried out rapidly, bringing hope for developing a robust diagnostic assay, discovering reliable biomarkers to assess disease progression, and developing therapeutic drugs and vaccines. In this review, we summarize, from an omics perspective, the strategies for the detection of SARS-CoV-2 antigens and antibodies against the virus, the metabolomic and proteomic changes in COVID-19 patients, and the progress of research on anti-SARS-CoV-2 drugs with their potential clinical applications.

In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over forty million patients worldwide. Although most coronavirus disease 2019 (COVID-19) patients have a good prognosis, some develop severe illness. Markers that define disease severity or predict clinical outcome need to be urgently developed as the mortality rate in critical cases is approximately 61.5%. In the present study, we performed in-depth proteome profiling of undepleted plasma from eight COVID-19 patients. Quantitative proteomic analysis using the BoxCar method revealed that 91 out of 1222 quantified proteins were differentially expressed depending on the severity of COVID-19. Importantly, we found 76 proteins, previously not reported, which could be novel prognostic biomarker candidates. Our plasma proteome signatures captured the host response to SARS-CoV-2 infection, thereby highlighting the role of neutrophil activation, complement activation, platelet function, and T cell suppression as well as proinflammatory factors upstream and downstream of interleukin-6, interleukin-1B, and tumor necrosis factor. Consequently, this study supports the development of blood biomarkers and potential therapeutic targets to aid clinical decision-making and subsequently improve prognosis of COVID-19.

Longitudinal proteomic profiling reveals increased early inflammation and sustained apoptosis proteins in severe COVID-19

SARS-CoV-2 infection has a risk to develop into life-threatening COVID-19 disease. Whereas age, hypertension, and chronic inflammatory conditions are risk factors, underlying host factors and markers for disease severity, e.g. requiring intensive care unit (ICU) treatment, remain poorly defined. To this end, we longitudinally profiled blood inflammation markers, antibodies, and 101 plasma proteins of hospitalized COVID-19 patients who did or did not require ICU admission. While essentially all patients displayed SARS-CoV-2-specific antibodies and virus-neutralization capacity within 12-15 days, a rapid, mostly transient upregulation of selective inflammatory markers including IL-6, CXCL10, CXCL11, IFNγ, IL-10, and monocyte-attracting CCL2, CCL7 and CCL8, was particularly evident in ICU patients. In addition, there was consistent and sustained upregulation of apoptosis-associated proteins CASP8, TNFSF14, HGF, and TGFB1, with HGF discriminating between ICU and non-ICU cohorts. Thus, COVID-19 is associated with a selective inflammatory milieu within which the apoptotic pathway is a cardinal feature with potential to aid risk-based patient stratification.