Serum Protein Profiling Reveals a Specific Upregulation of the Immunomodulatory Protein Progranulin in Coronavirus Disease 2019

Unagi: Deep Generative Model for Deciphering Cellular Dynamics and In-Silico Drug Discovery in Complex Diseases

Human diseases are characterized by intricate cellular dynamics. Single-cell sequencing provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in-silico drug interventions. Here, we introduce UNAGI, a deep generative neural network tailored to analyze time-series single-cell transcriptomic data. This tool captures the complex cellular dynamics underlying disease progression, enhancing drug perturbation modeling and discovery. When applied to a dataset from patients with Idiopathic Pulmonary Fibrosis (IPF), UNAGI learns disease-informed cell embeddings that sharpen our understanding of disease progression, leading to the identification of potential therapeutic drug candidates. Validation via proteomics reveals the accuracy of UNAGI's cellular dynamics analyses, and the use of the Fibrotic Cocktail treated human Precision-cut Lung Slices confirms UNAGI's predictions that Nifedipine, an antihypertensive drug, may have antifibrotic effects on human tissues. UNAGI's versatility extends to other diseases, including a COVID dataset, demonstrating adaptability and confirming its broader applicability in decoding complex cellular dynamics beyond IPF, amplifying its utility in the quest for therapeutic solutions across diverse pathological landscapes.

Human mRNA in saliva can correctly identify individuals harboring acute infection

The COVID-19 pandemic demonstrated the poor ability of body temperature to reliably identify SARS-CoV-2-infected individuals, an observation that has been made before in the context of other infectious diseases. While acute infection does not always cause fever, it does reliably drive host transcriptional responses as the body responds at the site of infection. These transcriptional changes can occur both in cells that are directly harboring replicating pathogens and in cells elsewhere that receive a molecular signal that infection is occurring. Here, we identify a core set of approximately 70 human genes that are together upregulated in cultured human cells infected by a broad array of viral, bacterial, and fungal pathogens. We have named these "core response" genes. In theory, transcripts from these genes could serve as biomarkers of infection in the human body, in a way that is agnostic to the specific pathogen causing infection. As such, we perform human studies to show that these infection-induced human transcripts can be measured in the saliva of people harboring different types of infections. The number of these transcripts in saliva can correctly classify infection status (whether a person harbors an infection) 91% of the time. Furthermore, in the case of SARS-CoV-2 specifically, the number of core response transcripts in saliva correctly identifies infectious individuals even when enrollees, themselves, are asymptomatic and do not know they are infected.IMPORTANCEThere are a variety of clinical and laboratory criteria available to clinicians in controlled healthcare settings to help them identify whether an infectious disease is present. However, in situations such as a new epidemic caused by an unknown infectious agent, in health screening contexts performed within communities and outside of healthcare facilities or in battlefield or potential biowarfare situations, this gets more difficult. Pathogen-agnostic methods for rapid screening and triage of large numbers of people for infection status are needed, in particular methods that might work on an easily accessible biospecimen like saliva. Here, we identify a small, core set of approximately 70 human genes whose transcripts serve as saliva-based biomarkers of infection in the human body, in a way that is agnostic to the specific pathogen causing infection.

Integrative single-cell transcriptome analysis provides new insights into post-COVID-19 pulmonary fibrosis and potential therapeutic targets

The global COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 virus has resulted in a significant number of patients experiencing persistent symptoms, including post-COVID pulmonary fibrosis (PCPF). This study aimed to identify novel therapeutic targets for PCPF using single-cell RNA-sequencing data from lung tissues of COVID-19 patients, idiopathic pulmonary fibrosis (IPF) patients, and a rat transforming growth factor beta-1-induced fibrosis model treated with antifibrotic drugs. Patients with COVID-19 had lower alveolar macrophage counts than healthy controls, whereas patients with COVID-19 and IPF presented with elevated monocyte-derived macrophage counts. A comparative transcriptome analysis showed that macrophages play a crucial role in IPF and COVID-19 development and progression, and fibrosis- and inflammation-associated genes were upregulated in both conditions. Functional enrichment analysis revealed the upregulation of inflammation and proteolysis and the downregulation of ribosome biogenesis. Cholesterol efflux and glycolysis were augmented in both macrophage types. The study suggests that antifibrotic drugs may reverse critical lung fibrosis mediators in COVID-19. The results help clarify the molecular mechanisms underlying pulmonary fibrosis in patients with severe COVID-19 and IPF and highlight the potential efficacy of antifibrotic drugs in COVID-19 therapy. Collectively, all these findings may have significant implications for the development of new treatment strategies for PCPF.

Organokines in COVID-19: A Systematic Review

Coronavirus disease 2019 (COVID-19) is a viral infection caused by SARS-CoV-2 that induces a generalized inflammatory state. Organokines (adipokines, osteokines, myokines, hepatokines, and cardiokines) can produce beneficial or harmful effects in this condition. This study aimed to systematically review the role of organokines on COVID-19. PubMed, Embase, Google Scholar, and Cochrane databases were searched, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and 37 studies were selected, comprising more than 2700 individuals infected with the virus. Among COVID-19 patients, organokines have been associated with endothelial dysfunction and multiple organ failure due to augmented cytokines and increased SARS-CoV-2 viremia. Changes in the pattern of organokines secretion can directly or indirectly contribute to aggravating the infection, promoting immune response alterations, and predicting the disease progression. These molecules have the potential to be used as adjuvant biomarkers to predict the severity of the illness and severe outcomes.

High Serum Progranulin Levels in COVID-19 Patients: A Pilot Study

In this study, we aimed to determine whether the progranulin level in serum predicts the course and severity of the disease in COVID-19 (+) patients and whether it can be used as a biomarker in these patients. Therefore, we sampled 61 people infected with COVID-19, and the cases were divided into the following groups: asymptomatic, noncomplicated, moderate, and severe. Concentrations of progranulin, TNF-α, IL-6 from in serum obtained from all participants were measured using commercially available ELISA kits, as well as WBC, PLT, NE, LY, ALT, AST, Hb, PCT, and CRP were examined with clinical analyzer. All measurements obtained for the patient samples were compared with those of 20 healthy individuals. The serum progranulin concentration was statistically higher in the COVID-19 (+) patient group than in the control group of healthy individuals [112.6 ± 54.8, 0.0 (0.0-54.2 pg/ml, respectively p = 0.000)]. ROC analysis was performed to evaluate the progranulin potential as a biomarker for COVID-19 (+) patients. A larger AUC (0.931 ± 0.08) value and a more significant p-value for progranulin than for CRP (p = 0.000) was detected. As a result, we believe that progranulin reaches high levels in the COVID-19 disease and may be a determinant in diagnosis and prognosis, and may be a better biomarker than CRP.

Current and novel biomarkers of thrombotic risk in COVID-19: a Consensus Statement from the International COVID-19 Thrombosis Biomarkers Colloquium

Coronavirus disease 2019 (COVID-19) predisposes patients to thrombotic and thromboembolic events, owing to excessive inflammation, endothelial cell activation and injury, platelet activation and hypercoagulability. Patients with COVID-19 have a prothrombotic or thrombophilic state, with elevations in the levels of several biomarkers of thrombosis, which are associated with disease severity and prognosis. Although some biomarkers of COVID-19-associated coagulopathy, including high levels of fibrinogen and D-dimer, were recognized early during the pandemic, many new biomarkers of thrombotic risk in COVID-19 have emerged. In this Consensus Statement, we delineate the thrombotic signature of COVID-19 and present the latest biomarkers and platforms to assess the risk of thrombosis in these patients, including markers of platelet activation, platelet aggregation, endothelial cell activation or injury, coagulation and fibrinolysis as well as biomarkers of the newly recognized post-vaccine thrombosis with thrombocytopenia syndrome. We then make consensus recommendations for the clinical use of these biomarkers to inform prognosis, assess disease acuity, and predict thrombotic risk and in-hospital mortality. A thorough understanding of these biomarkers might aid risk stratification and prognostication, guide interventions and provide a platform for future research.

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.

Elevated Serum Levels of Progranulin and Soluble Vascular Cell Adhesion Molecule-1 in Patients with COVID-19

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with the angiocentric inflammation and angiogenesis, yet the molecules involved in this process remain to be determined.

Methods

We did a cross-sectional study of a cohort of patients with COVID-19 in Zunyi, China between February 1 and March 30, 2020. Serum concentrations of PGRN were determined by enzyme-linked immunosorbent assay in patients with COVID-19 at hospital admission and at discharge. In parallel, the serum levels of soluble adhesion molecules, vascular cell adhesion molecule-1 (sVCAM-1), intercellular adhesion molecule-1 (sICAM-1), P-selectin (sP-selectin), and E-selectin (sE-selectin) were assayed by a human adhesion molecule multiplex kit. The association between serum PGRN levels and other laboratory test results was analyzed by Spearman correlation analysis.

Results

At baseline, the median serum PGRN levels in patients with COVID-19 were 94.8 ng/mL [interquartile range (IQR): 66.6–119.6 ng/mL], which was significantly elevated compared with those in healthy controls (46.3 ng/mL, IQR: 41.8–55.6 ng/mL). Moreover, the median serum sVCAM-1 levels were significantly higher in COVID-19 patients (1396.0 ng/mL, IQR: 1019.1–1774.8 ng/mL) than those in healthy controls (612.4 ng/mL, IQR: 466.4–689.3 ng/mL). However, the levels of sICAM-1, sP-selectin, and sE-selectin were not significantly elevated in patients with COVID-19 when compared to healthy controls. Further analysis showed that serum PGRN levels were significantly positively associated with sVCAM-1 (r= 0.675, P= 0.008) and inversely with sICAM-1 (r= −0.609, P= 0.021) and aspartate aminotransferase levels (r= −0.560, P= 0.037) in patients with COVID-19 at hospital admission. In COVID-19 patients, serum PGRN and sVCAM-1 levels fell significantly after successful treatment.

Conclusion

The present study demonstrates elevated serum PGRN and sVCAM-1 levels in patients with COVID-19, which may provide clues as to the mechanisms underlying the pathogenesis of COVID-19. Further studies are warranted to evaluate the potential of PGRN and sVCAM-1 as biomarkers and investigate their role in the pathogenesis of COVID-19.

Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology

The COVID-19 pandemic caused by SARS-CoV-2 challenges the understanding of factors affecting disease progression and severity. The identification of prognostic biomarkers and physiological processes associated with disease symptoms is relevant for the development of new diagnostic and therapeutic interventions to contribute to the control of this pandemic. To address this challenge, in this study, we used a quantitative proteomics together with multiple data analysis algorithms to characterize serum protein profiles in five cohorts from healthy to SARS-CoV-2-infected recovered (hospital discharge), nonsevere (hospitalized), and severe [at the intensive care unit (ICU)] cases with increasing systemic inflammation in comparison with healthy individuals sampled prior to the COVID-19 pandemic. The results showed significantly dysregulated proteins and associated biological processes and disorders associated to COVID-19. These results corroborated previous findings in COVID-19 studies and highlighted how the representation of dysregulated serum proteins and associated BPs increases with COVID-19 disease symptomatology from asymptomatic to severe cases. The analysis was then focused on novel disease processes and biomarkers that were correlated with disease symptomatology. To contribute to translational medicine, results corroborated the predictive value of selected immune-related biomarkers for disease recovery [Selenoprotein P (SELENOP) and Serum paraoxonase/arylesterase 1 (PON1)], severity [Carboxypeptidase B2 (CBP2)], and symptomatology [Pregnancy zone protein (PZP)] using protein-specific ELISA tests. Our results contributed to the characterization of SARS-CoV-2–host molecular interactions with potential contributions to the monitoring and control of this pandemic by using immune-related biomarkers associated with disease symptomatology.

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.

A single transcript for the prognosis of disease severity in COVID-19 patients

With many countries strapped for medical resources due to the COVID-19 pandemic, it is highly desirable to allocate the precious resources to those who need them the most. Several markers have been found to be associated with the disease severity in COVID-19 patients. However, the established markers only display modest prognostic power individually and better markers are urgently needed. The aim of this study is to investigate the potential of S100A12, a prominent marker gene for bacterial infection, in the prognosis of disease severity in COVID-19 patients. To ensure the robustness of the association, a total of 1695 samples from 14 independent transcriptome datasets on sepsis, influenza infection and COVID-19 infection were examined. First, it was demonstrated that S100A12 was a marker for sepsis and severity of sepsis. Then, S100A12 was found to be a marker for severe influenza infection, and there was an upward trend of S100A12 expression as the severity level of influenza infection increased. As for COVID-19 infection, it was found that S100A12 expression was elevated in patients with severe and critical COVID-19 infection. More importantly, S100A12 expression at hospital admission was robustly correlated with future quantitative indexes of disease severity and outcome in COVID-19 patients, superior to established prognostic markers including CRP, PCT, d-dimer, ferritin, LDH and fibrinogen. Thus, S100A12 is a valuable novel prognostic marker for COVID-19 severity and deserves more attention.

Cytokine adsorption in patients with severe COVID-19 pneumonia requiring extracorporeal membrane oxygenation (CYCOV): a single centre, open-label, randomised, controlled trial

Background

We sought to clarify the benefit of cytokine adsorption in patients with COVID-19 supported with venovenous extracorporeal membrane oxygenation (ECMO).

Methods

We did a single-centre, open-label, randomised, controlled trial to investigate cytokine adsorption in adult patients with severe COVID-19 pneumonia requiring ECMO. Patients with COVID-19 selected for ECMO at the Freiburg University Medical Center (Freiburg, Germany) were randomly assigned (1:1) to receive cytokine adsorption using the CytoSorb device or not. Randomisation was computer-generated, allocation was concealed by opaque, sequentially numbered sealed envelopes. The CytoSorb device was incorporated into the ECMO circuit before connection to the patient circuit, replaced every 24 h, and removed after 72 h. The primary endpoint was serum interleukin-6 (IL-6) concentration 72 h after initiation of ECMO analysed by intention to treat. Secondary endpoints included 30-day survival. The trial is registered with ClinicalTrials.gov (NCT04324528) and the German Clinical Trials Register (DRKS00021300) and is closed.

Findings

From March 29, 2020, to Dec 29, 2020, of 34 patients assessed for eligibility, 17 (50%) were treated with cytokine adsorption and 17 (50%) without. Median IL-6 decreased from 357·0 pg/mL to 98·6 pg/mL in patients randomly assigned to cytokine adsorption and from 289·0 pg/mL to 112·0 pg/mL in the control group after 72 h. One patient in each group died before 72 h. Adjusted mean log IL-6 concentrations after 72 h were 0·30 higher in the cytokine adsorption group (95% CI −0·70 to 1·30, p=0·54). Survival after 30 days was three (18%) of 17 with cytokine adsorption and 13 (76%) of 17 without cytokine adsorption (p=0·0016).

Interpretation

Early initiation of cytokine adsorption in patients with severe COVID-19 and venovenous ECMO did not reduce serum IL-6 and had a negative effect on survival. Cytokine adsorption should not be used during the first days of ECMO support in COVID-19.

Funding

None.

ICODE: the international COVID-19 thrombosis biomarkers colloquium-novel soluble biomarkers: circulating cell-free nucleic acids and other molecules

This article summarizes the evidence derived from clinical (observational) studies describing novel soluble biomarkers in COVID-19. Our goal was to stimulate further research (preclinical as well as clinical studies) and therefore we discuss potential prognostic value, but also technical details, such as sample preparation. A table provides an overview of the described biomarkers measured in plasma, serum or other (namely bronchoalveolar) fluids.