Fibronectin as a Marker of Disease Severity in Critically Ill COVID-19 Patients

Proteomic Evolution from Acute to Post-COVID-19 Conditions

Many COVID-19 survivors have post-COVID-19 conditions, and females are at a higher risk. We sought to determine (1) how protein levels change from acute to post-COVID-19 conditions, (2) whether females have a plasma protein signature different from that of males, and (3) which biological pathways are associated with COVID-19 when compared to restrictive lung disease. We measured protein levels in 74 patients on the day of admission and at 3 and 6 months after diagnosis. We determined protein concentrations by multiple reaction monitoring (MRM) using a panel of 269 heavy-labeled peptides. The predicted forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLCO) were measured by routine pulmonary function testing. Proteins associated with six key lipid-related pathways increased from admission to 3 and 6 months; conversely, proteins related to innate immune responses and vasoconstriction-related proteins decreased. Multiple biological functions were regulated differentially between females and males. Concentrations of eight proteins were associated with FVC, %, and they together had c-statistics of 0.751 (CI:0.732-0.779); similarly, concentrations of five proteins had c-statistics of 0.707 (CI:0.676-0.737) for DLCO, %. Lipid biology may drive evolution from acute to post-COVID-19 conditions, while activation of innate immunity and vascular regulation pathways decreased over that period. (ProteomeXchange identifiers: PXD041762, PXD029437).

COVID-19 induces more pronounced extracellular matrix deposition than other causes of ARDS

BACKGROUND

Lung fibrosis is a major concern in severe COVID-19 patients undergoing mechanical ventilation (MV). Lung fibrosis frequency in post-COVID syndrome is highly variable and even if the risk is proportionally small, many patients could be affected. However, there is still no data on lung extracellular matrix (ECM) composition in severe COVID-19 and whether it is different from other aetiologies of ARDS.

METHODS

We have quantified different ECM elements and TGF-β expression in lung tissue of 28 fatal COVID-19 cases and compared to 27 patients that died of other causes of ARDS, divided according to MV duration (up to six days or seven days or more). In COVID-19 cases, ECM elements were correlated with lung transcriptomics and cytokines profile.

RESULTS

We observed that COVID-19 cases presented significant increased deposition of collagen, fibronectin, versican, and TGF-β, and decreased decorin density when compared to non-COVID-19 cases of similar MV duration. TGF-β was precociously increased in COVID-19 patients with MV duration up to six days. Lung collagen was higher in women with COVID-19, with a transition of upregulated genes related to fibrillogenesis to collagen production and ECM disassembly along the MV course.

CONCLUSIONS

Fatal COVID-19 is associated with an early TGF-β expression lung environment after the MV onset, followed by a disordered ECM assembly. This uncontrolled process resulted in a prominent collagen deposition when compared to other causes of ARDS. Our data provides pathological substrates to better understand the high prevalence of pulmonary abnormalities in patients surviving COVID-19.

Long COVID and the Neuroendocrinology of Microbial Translocation Outside the GI Tract: Some Treatment Strategies

Similar to previous pandemics, COVID-19 has been succeeded by well-documented post-infectious sequelae, including chronic fatigue, cough, shortness of breath, myalgia, and concentration difficulties, which may last 5 to 12 weeks or longer after the acute phase of illness. Both the psychological stress of SARS-CoV-2 infection and being diagnosed with COVID-19 can upregulate cortisol, a stress hormone that disrupts the efferocytosis effectors, macrophages, and natural killer cells, leading to the excessive accumulation of senescent cells and disruption of biological barriers. This has been well-established in cancer patients who often experience unrelenting fatigue as well as gut and blood–brain barrier dysfunction upon treatment with senescence-inducing radiation or chemotherapy. In our previous research from 2020 and 2021, we linked COVID-19 to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) via angiotensin II upregulation, premature endothelial senescence, intestinal barrier dysfunction, and microbial translocation from the gastrointestinal tract into the systemic circulation. In 2021 and 2022, these hypotheses were validated and SARS-CoV-2-induced cellular senescence as well as microbial translocation were documented in both acute SARS-CoV-2 infection, long COVID, and ME/CFS, connecting intestinal barrier dysfunction to disabling fatigue and specific infectious events. The purpose of this narrative review is to summarize what is currently known about host immune responses to translocated gut microbes and how these responses relate to fatiguing illnesses, including long COVID. To accomplish this goal, we examine the role of intestinal and blood–brain barriers in long COVID and other illnesses typified by chronic fatigue, with a special emphasis on commensal microbes functioning as viral reservoirs. Furthermore, we discuss the role of SARS-CoV-2/Mycoplasma coinfection in dysfunctional efferocytosis, emphasizing some potential novel treatment strategies, including the use of senotherapeutic drugs, HMGB1 inhibitors, Toll-like receptor 4 (TLR4) blockers, and membrane lipid replacement.

Serum Proteome Signatures of Anti-SARS-CoV-2 Vaccinated Healthcare Workers in Greece Associated with Their Prior Infection Status

Over the course of the pandemic, proteomics, being in the frontline of anti-COVID-19 research, has massively contributed to the investigation of molecular pathogenic properties of the virus. However, data on the proteome on anti-SARS-CoV-2 vaccinated individuals remain scarce. This study aimed to identify the serum proteome characteristics of anti-SARS-CoV-2 vaccinated individuals who had previously contracted the virus and comparatively assess them against those of virus-naïve vaccine recipients. Blood samples of n = 252 individuals, out of whom n = 35 had been previously infected, were collected in the "G. Gennimatas" General Hospital of Thessaloniki, from 4 January 2021 to 31 August 2021. All participants received the BNT162b2 mRNA COVID-19 vaccine (Pfizer/BioNTech). A label-free quantitative proteomics LC-MS/MS approach was undertaken, and the identified proteins were analyzed using the GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes) databases as well as processed by bioinformatics tools. Titers of total RBD-specific IgGs against SARS-CoV-2 were also determined using the SARS-CoV-2 IgG II Quant assay. A total of 47 proteins were significantly differentially expressed, the majority of which were down-regulated in sera of previously infected patients compared to virus-naïve controls. Several pathways were affected supporting the crucial role of the humoral immune response in the protection against SARS-CoV-2 infection provided by COVID-19 vaccination. Overall, our comprehensive proteome profiling analysis contributes novel knowledge of the mechanisms of immune response induced by anti-SARS-CoV-2 vaccination and identified protein signatures reflecting the immune status of vaccine recipients.

Exploring SARS-CoV2 host-pathogen interactions and associated fungal infections cross-talk: Screening of targets and understanding pathogenesis

The COVID-19 associated opportunistic fungal infections have posed major challenges in recent times. Global scientific efforts have identified several SARS-CoV2 host-pathogen interactions in a very short time span. However, information about the molecular basis of COVID-19 associated opportunistic fungal infections is not readily available. Previous studies have identified a number of host targets involved in these opportunistic fungal infections showing association with COVID-19 patients. We screened host targets involved in COVID-19-associated opportunistic fungal infections, in addition to host-pathogen interaction data of SARS-CoV2 from well-known and widely used biological databases. Venn diagram was prepared to screen common host targets involved in studied COVID-19-associated fungal infections. Moreover, an interaction network of studied disease targets was prepared with STRING to identify important targets on the basis of network biological parameters. The host-pathogen interaction (HPI) map of SARS-CoV2 was also prepared and screened to identify interactions of the virus with targets involved in studied fungal infections. Pathway enrichment analysis of host targets involved in studied opportunistic fungal infections and the subset of those involved in SARS-CoV2 HPI were performed separately. This data-based analysis screened six common targets involved in all studied fungal infections, among which CARD9 and CYP51A1 were involved in host-pathogen interactions with SARS-CoV2. Moreover, several signaling pathways such as integrin signaling were screened, which were associated with disease targets involved in SARS-CoV2 HPI. The results of this study indicate several host targets deserving detailed investigation to develop strategies for the management of SARS-CoV2-associated fungal infections.

Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis

Fibronectin (FN) plays an essential role in the host’s response to infection. In previous studies, a significant decrease in the FN level was observed in sepsis; however, it has not been clearly elucidated how this parameter affects the patient’s survival. To better understand the relationship between FN and survival, we utilized innovative approaches from the field of explainable machine learning, including local explanations (Break Down, Shapley Additive Values, Ceteris Paribus), to understand the contribution of FN to predicting individual patient survival. The methodology provides new opportunities to personalize informative predictions for patients. The results showed that the most important indicators for predicting survival in sepsis were INR, FN, age, and the APACHE II score. ROC curve analysis showed that the model’s successful classification rate was 0.92, its sensitivity was 0.92, its positive predictive value was 0.76, and its accuracy was 0.79. To illustrate these possibilities, we have developed and shared a web-based risk calculator for exploring individual patient risk. The web application can be continuously updated with new data in order to further improve the model.