Different Profiles of Antibodies and Cytokines Were Found Between Severe and Moderate COVID-19 Patients

Intrinsic Factors Behind the Long-COVID: V. Immunometabolic Disorders

The complex link between COVID-19 and immunometabolic diseases demonstrates the important interaction between metabolic dysfunction and immunological response during viral infections. Severe COVID-19, defined by a hyperinflammatory state, is greatly impacted by underlying chronic illnesses aggravating the cytokine storm caused by increased levels of Pro-inflammatory cytokines. Metabolic reprogramming, including increased glycolysis and altered mitochondrial function, promotes viral replication and stimulates inflammatory cytokine production, contributing to illness severity. Mitochondrial metabolism abnormalities, strongly linked to various systemic illnesses, worsen metabolic dysfunction during and after the pandemic, increasing cardiovascular consequences. Long COVID-19, defined by chronic inflammation and immune dysregulation, poses continuous problems, highlighting the need for comprehensive therapy solutions that address both immunological and metabolic aspects. Understanding these relationships shows promise for effectively managing COVID-19 and its long-term repercussions, which is the focus of this review paper.

PET Foils Functionalized with Reactive Copolymers as Adaptable Microvolume ELISA Spot Array Platforms for Multiplex Serological Analysis of SARS-CoV-2 Infections

Microvolume ELISA platforms have become vital in diagnostics for their high-throughput capabilities and minimal sample requirements. High-quality substrates with advanced surface properties are essential for these applications. They enable both efficient biomolecule immobilization and antifouling properties, which are critical for assay sensitivity and specificity. This study presents PET-based microvolume ELISA spot arrays coated with amine- and DBCO-reactive copolymers MCP-2 and Copoly Azide. The platforms were designed for the sensitive and specific detection of specific antibodies such as COVID-19 biomarkers. Supporting robust attachment of the SARS-CoV-2 nucleoprotein (NP), these arrays outperform traditional approaches. It was demonstrated that covalent attachment methods proved more efficient than passive adsorption, together with the reduction of non-specific binding. Analytical performance was verified with classical ELISA and real-time Surface Plasmon Resonance (SPR) analysis. It enables sensitive detection of IgG and IgA antibodies, including IgG subclasses, in human serum. Clinically, the platform achieved 100.0% sensitivity and 92.9% specificity for anti-NP antibody detection in COVID-19-positive and negative samples. Additionally, DNA-directed immobilization extended the platform's utility to multiplex serological measurements. These findings underscore the potential of PET-based microvolume ELISA arrays as scalable, high-throughput diagnostic tools suitable for detecting multiple biomarkers in a single assay and easily integrated into microfluidic devices.

Symptom clusters and symptom networks of symptom experiences in patients with SARS-CoV-2 infection

Context

Symptom clusters and symptom networks can potentially enhance the precision in managing symptoms. However, limited research has been conducted on the symptom network experienced by patients infected with Severe Acute Respiratory Syndrome Coronavirus 2.

Objectives

To identify the composition of symptom clusters in SARS-CoV-2 infected patients, establish a symptom network to explore the centrality indices, and investigate independent risk factors influencing the occurrence of symptom clusters.

Methods

Between February 2022 and June 2023, a total of 418 patients diagnosed with SARS-CoV-2 infection were recruited in the Second Affiliated Hospital of Chongqing Medical University. A symptom questionnaire was utilized to assess three dimensions encompassing a comprehensive range of 40 symptoms. Principal component analysis was employed to identify distinct symptom clusters, while network analysis elucidated the interconnections among these symptoms. Univariate analysis and multiple linear regression analysis were conducted to investigate the factors influencing the manifestation of these symptom clusters.

Results

Eight symptom clusters were identified, namely the nasopharyngeal-related symptom cluster, the circulatory-related symptom cluster, the neural-related symptom cluster, the physical-related symptom cluster, the digestive-related symptom cluster, the respiratory-related symptom cluster, the fever-related symptom cluster, and the sensory-related symptom cluster. The three centrality indices with the highest values were chest tightness (rs = 7.84, rc = 0.013, rb = 6.99), muscle aches (rs = 7.32, rc = 0.013, rb = 2.72), and smell abnormality (rs = 6.56, rc = 0.011, rb = 4.58). Variables including age, gender, income, education, hyperlipidemia, chronic bronchitis, and tumor were associated with the occurrence of these eight symptom clusters.

Conclusion

The findings of this study highlight the necessity to explore symptom clusters and symptom networks in order to enhance the effectiveness of symptom management in patients with SARS-CoV-2 infection. Particularly crucial is the evaluation of centrality indices as an integral component of caring for such patients. Early detection of high-risk individuals within each symptom cluster can provide a scientific foundation for developing interventions that will optimize patient prognosis.

Differential decline of SARS-CoV-2-specific antibody levels, innate and adaptive immune cells, and shift of Th1/inflammatory to Th2 serum cytokine levels long after first COVID-19

BACKGROUND

SARS-CoV-2 has triggered a pandemic and contributes to long-lasting morbidity. Several studies have investigated immediate cellular and humoral immune responses during acute infection. However, little is known about long-term effects of COVID-19 on the immune system.

METHODS

We performed a longitudinal investigation of cellular and humoral immune parameters in 106 non-vaccinated subjects ten weeks (10 w) and ten months (10 m) after their first SARS-CoV-2 infection. Peripheral blood immune cells were analyzed by multiparametric flow cytometry, serum cytokines were examined by multiplex technology. Antibodies specific for the Spike protein (S), the receptor-binding domain (RBD) and the nucleocapsid protein (NC) were determined. All parameters measured 10 w and 10 m after infection were compared with those of a matched, noninfected control group (n = 98).

RESULTS

Whole blood flow cytometric analyses revealed that 10 m after COVID-19, convalescent patients compared to controls had reduced absolute granulocyte, monocyte, and lymphocyte counts, involving T, B, and NK cells, in particular CD3+CD45RA+CD62L+CD31+ recent thymic emigrant T cells and non-class-switched CD19+IgD+CD27+ memory B cells. Cellular changes were associated with a reversal from Th1- to Th2-dominated serum cytokine patterns. Strong declines of NC- and S-specific antibody levels were associated with younger age (by 10.3 years, p < .01) and fewer CD3-CD56+ NK and CD19+CD27+ B memory cells. Changes of T-cell subsets at 10 m such as normalization of effector and Treg numbers, decline of RTE, and increase of central memory T cell numbers were independent of antibody decline pattern.

CONCLUSIONS

COVID-19 causes long-term reduction of innate and adaptive immune cells which is associated with a Th2 serum cytokine profile. This may provide an immunological mechanism for long-term sequelae after COVID-19.

Proprotein Convertase Subtilisin/Kexin Type 9 Induction in COVID-19 Is Poorly Associated with Disease Severity and Cholesterol Levels

SARS-CoV-2 infection was shown to induce proprotein convertase subtilisin/kexin type 9 (PCSK9) plasma levels in sepsis. Here, we investigate the association between serum PCSK9 levels and disease severity. PCSK9 was measured in serum of 55 controls, 40 patients with moderate and 60 patients with severe COVID-19 disease. Serum PCSK9 was elevated in moderate COVID-19 compared to controls and further increased in severe cases. PCSK9 levels were not associated with C-reactive protein, bacterial superinfections, interventions, or survival in patients with severe COVID-19. PCSK9 regulates circulating cholesterol levels, and 15 cholesteryl ester (CE) species and free cholesterol (FC) were quantified by direct flow injection analysis using a high-resolution hybrid quadrupole-Orbitrap mass spectrometer. Most CE species with shorter fatty acid chains were decreased in severe compared to moderate COVID-19, and none of the CE species were correlated with PCSK9 in patients with severe COVID-19. Levels of all CE species negatively correlated with C-reactive protein in severe COVID-19 patients. Notably, FC was induced in severe compared to moderate COVID-19. The FC/CE ratio correlated positively with inflammatory markers and was associated with non-survival. The current study suggests that the imbalance between CE and FC levels is associated with disease severity and mortality in patients with COVID-19.

High Serum S100A12 as a Diagnostic and Prognostic Biomarker for Severity, Multidrug-Resistant Bacteria Superinfection and Herpes Simplex Virus Reactivation in COVID-19

Neutrophils are critical immune cells in severe coronavirus disease 2019 (COVID-19). S100 calcium-binding protein A12 (S100A12) is highly expressed in neutrophils during acute inflammation. The aim of this study was to evaluate serum S100A12 levels as a diagnostic and prognostic tool in COVID-19. Serum samples of patients with moderate and severe COVID-19 were collected during 2020 to 2024. Enzyme-linked immunosorbent assay was used to measure serum S100A12 levels in 63 patients with moderate COVID-19, 60 patients with severe disease and 33 healthy controls. Serum S100A12 levels were elevated in moderate COVID-19 compared to controls and were even higher in severe cases. In moderate disease, serum S100A12 levels positively correlated with immune cell counts. While C-reactive protein and procalcitonin are established inflammation markers, they did not correlate with serum S100A12 levels in either patient cohort. Patients with severe COVID-19 and vancomycin-resistant enterococcus (VRE) infection had increased S100A12 levels. Elevated S100A12 levels were also observed in patients with herpes simplex reactivation. Fungal superinfections did not alter S100A12 levels. These data show that serum S100A12 increases in moderate and severe COVID-19 and is further elevated by VRE bloodstream infection and herpes simplex reactivation. Therefore, S100A12 may serve as a novel biomarker for severe COVID-19 and an early diagnostic indicator for bacterial and viral infections.

Developing Deep LSTMs With Later Temporal Attention for Predicting COVID-19 Severity, Clinical Outcome, and Antibody Level by Screening Serological Indicators Over Time

OBJECTIVE

The clinical course of COVID-19, as well as the immunological reaction, is notable for its extreme variability. Identifying the main associated factors might help understand the disease progression and physiological status of COVID-19 patients. The dynamic changes of the antibody against Spike protein are crucial for understanding the immune response. This work explores a temporal attention (TA) mechanism of deep learning to predict COVID-19 disease severity, clinical outcomes, and Spike antibody levels by screening serological indicators over time.

METHODS

We use feature selection techniques to filter feature subsets that are highly correlated with the target. The specific deep Long Short-Term Memory (LSTM) models are employed to capture the dynamic changes of disease severity, clinical outcome, and Spike antibody level. We also propose deep LSTMs with a TA mechanism to emphasize the later blood test records because later records often attract more attention from doctors.

RESULTS

Risk factors highly correlated with COVID-19 are revealed. LSTM achieves the highest classification accuracy for disease severity prediction. Temporal Attention Long Short-Term Memory (TA-LSTM) achieves the best performance for clinical outcome prediction. For Spike antibody level prediction, LSTM achieves the best permanence.

CONCLUSION

The experimental results demonstrate the effectiveness of the proposed models. The proposed models can provide a computer-aided medical diagnostics system by simply using time series of serological indicators.

IFN-γ decreases PD-1 in T lymphocytes from convalescent COVID-19 patients via the AKT/GSK3β signaling pathway

Post-COVID-19 syndrome may be associated with the abnormal immune status. Compared with the unexposed age-matched elder group, PD-1 in the CD8+ T cells from recovered COVID-19 patients was significantly lower. IFN-γ in the plasma of COVID-19 convalescent patients was increased, which inhibited PD-1 expression in CD8+ T cells from COVID-19 convalescent patients. scRNA-seq bioinformatics analysis revealed that AKT/GSK3β may regulate the INF-γ/PD-1 axis in CD8+ T cells from COVID-19 convalescent patients. In parallel, an IFN-γ neutralizing antibody reduced AKT and increased GSK3β in PBMCs. An AKT agonist (SC79) significantly decreased p-GSK3β. Moreover, AKT decreased PD-1 on CD8+ T cells, and GSK3β increased PD-1 on CD8+ T cells according to flow cytometry analysis. Collectively, we demonstrated that recovered COVID-19 patients may develop long COVID. Increased IFN-γ in the plasma of recovered Wuhan COVID-19 patients contributed to PD-1 downregulation on CD8+ T cells by regulating the AKT/GSK3β signaling pathway.

Development of a free cytokine immunoassay to maintain binding and dissociation equilibrium in vitro

Using competitive ELISA to detect free cytokines is limited as it can only reflect relative trends rather than accurately determine the real state and quantity of cytokines due to the dynamic equilibrium between dissociation and binding. This imprecise quantification adversely affects the usage of clinical medication and the validity assessment. In this study, we have developed a novel cytokine immunoassay that utilizes Rosetta molecular docking prediction technique, we screened two specific antibody pairs binding IL-1β and Durg respectively and then established the Total IL-1β and Total Drug ELISA assay. Protein A column could separate bound IL-1β and free IL-1β, and the bound IL-1β occupied for about 90% of the total. This innovative approach ensures the maintenance of equilibrium between the free cytokines and complex. We have developed a free cytokine content detection method that combines ELISA and solid phase extraction, which can detect the true concentration of free cytokines without destroying the free-binding dynamic equilibrium. It can be used to verify the accuracy of clinical PK/PD and other data, evaluate the applicability of detection methods, and guide clinical drug use and drug efficacy evaluation.

SARS-CoV-2 Antibody Responses in Pediatric Patients: A Bibliometric Analysis

The characteristics, dynamics and mechanisms/determinants of the immune response to SARS-CoV-2 infection are not fully understood. We performed a bibliometric review of studies that have assessed SARS-CoV-2 antibody responses in the pediatric population using Web of Science online databases, VOSviewer and Bibliometrix tools. The analysis was conducted on 84 publications, from 310 institutions located in 29 countries and published in 57 journals. The results showed the collaboration of scientists and organizations, international research interactions and summarized the findings on (i) the measured titers of antibodies (total antibody and/or individual antibody classes IgG, IgM, IgA) against different antigens (C-terminal region of N (N CT), full-length N protein (N FL), RBD, RBD Alpha, RBD Beta, RBD Gamma, RBD Delta, spike (S), S1, S2) in the case of different clinical forms of the disease; and (ii) the correlations between SARS-CoV-2 antibodies and cytokines, chemokines, neutrophils, C-reactive protein, ferritin, and the erythrocyte sedimentation rate. The presented study offers insights regarding research directions to be explored in the studied field and may provide a starting point for future research.

Seroprevalence of IgG and Subclasses against the Nucleocapsid of SARS-CoV-2 in Health Workers

BACKGROUND

The nucleocapsid protein of SARS-CoV-2 participates in viral replication, transcription, and assembly. Antibodies against this protein have been proposed for the epidemiological analysis of the seroprevalence of COVID-19 associated with natural infection by SARS-CoV-2. Health workers were one of the most exposed populations, and some had an asymptomatic form of the disease, so detecting IgG antibodies and subclasses against the N protein can help to reclassify their epidemiological status and obtain information about the effector mechanisms associated with viral elimination.

METHODS

In this study, we analyzed 253 serum samples collected in 2021 and derived from health workers, and evaluated the presence of total IgG and subclasses against the N protein of SARS-CoV-2 by indirect ELISA.

RESULTS

From the analyzed samples, 42.69% were positive to anti-N IgG antibodies. A correlation between COVID-19 asymptomatic infection and IgG antibodies was observed (p = 0.006). The detected subclasses were: IgG1 (82.4%), IgG2 (75.9%), IgG3 (42.6%), and IgG4 (72.6%).

CONCLUSIONS

This work provides evidence about the high seroprevalence of total IgG and subclasses of anti-N and their relations with the asymptomatic infection of SARS-CoV-2 and related symptoms.

Characterisation of the pro-inflammatory cytokine signature in severe COVID-19

Clinical outcomes from infection with SARS-CoV-2, the cause of the COVID-19 pandemic, are remarkably variable ranging from asymptomatic infection to severe pneumonia and death. One of the key drivers of this variability is differing trajectories in the immune response to SARS-CoV-2 infection. Many studies have noted markedly elevated cytokine levels in severe COVID-19, although results vary by cohort, cytokine studied and sensitivity of assay used. We assessed the immune response in acute COVID-19 by measuring 20 inflammatory markers in 118 unvaccinated patients with acute COVID-19 (median age: 70, IQR: 58-79 years; 48.3% female) recruited during the first year of the pandemic and 44 SARS-CoV-2 naïve healthy controls. Acute COVID-19 was associated with marked elevations in nearly all pro-inflammatory markers, whilst eleven markers (namely IL-1β, IL-2, IL-6, IL-10, IL-18, IL-23, IL-33, TNF-α, IP-10, G-CSF and YKL-40) were associated with disease severity. We observed significant correlations between nearly all markers elevated in those infected with SARS-CoV-2 consistent with widespread immune dysregulation. Principal component analysis highlighted a pro-inflammatory cytokine signature (with strongest contributions from IL-1β, IL-2, IL-6, IL-10, IL-33, G-CSF, TNF-α and IP-10) which was independently associated with severe COVID-19 (aOR: 1.40, 1.11-1.76, p=0.005), invasive mechanical ventilation (aOR: 1.61, 1.19-2.20, p=0.001) and mortality (aOR 1.57, 1.06-2.32, p = 0.02). Our findings demonstrate elevated cytokines and widespread immune dysregulation in severe COVID-19, adding further evidence for the role of a pro-inflammatory cytokine signature in severe and critical COVID-19.

Cytokine levels associated with favorable clinical outcome in the CAPSID randomized trial of convalescent plasma in patients with severe COVID-19

Objectives

To determine the profile of cytokines in patients with severe COVID-19 who were enrolled in a trial of COVID-19 convalescent plasma (CCP).

Methods

Patients were randomized to receive standard treatment and 3 CCP units or standard treatment alone (CAPSID trial, ClinicalTrials.gov NCT04433910). The primary outcome was a dichotomous composite outcome (survival and no longer severe COVID-19 on day 21). Time to clinical improvement was a key secondary endpoint. The concentrations of 27 cytokines were measured (baseline, day 7). We analyzed the change and the correlation between serum cytokine levels over time in different subgroups and the prediction of outcome in receiver operating characteristics (ROC) analyses and in multivariate models.

Results

The majority of cytokines showed significant changes from baseline to day 7. Some were strongly correlated amongst each other (at baseline the cluster IL-1ß, IL-2, IL-6, IL-8, G-CSF, MIP-1α, the cluster PDGF-BB, RANTES or the cluster IL-4, IL-17, Eotaxin, bFGF, TNF-α). The correlation matrix substantially changed from baseline to day 7. The heatmaps of the absolute values of the correlation matrix indicated an association of CCP treatment and clinical outcome with the cytokine pattern. Low levels of IP-10, IFN-γ, MCP-1 and IL-1ß on day 0 were predictive of treatment success in a ROC analysis. In multivariate models, low levels of IL-1ß, IFN-γ and MCP-1 on day 0 were significantly associated with both treatment success and shorter time to clinical improvement. Low levels of IP-10, IL-1RA, IL-6, MCP-1 and IFN-γ on day 7 and high levels of IL-9, PDGF and RANTES on day 7 were predictive of treatment success in ROC analyses. Low levels of IP-10, MCP-1 and high levels of RANTES, on day 7 were associated with both treatment success and shorter time to clinical improvement in multivariate models.

Conclusion

This analysis demonstrates a considerable dynamic of cytokines over time, which is influenced by both treatment and clinical course of COVID-19. Levels of IL-1ß and MCP-1 at baseline and MCP-1, IP-10 and RANTES on day 7 were associated with a favorable outcome across several endpoints. These cytokines should be included in future trials for further evaluation as predictive factors.

Peritoneal M2 macrophage-derived extracellular vesicles as natural multitarget nanotherapeutics to attenuate cytokine storms after severe infections

Cytokine storms are a primary cause of multiple organ damage and death after severe infections, such as SARS-CoV-2. However, current single cytokine-targeted strategies display limited therapeutic efficacy. Here, we report that peritoneal M2 macrophage-derived extracellular vesicles (M2-EVs) are multitarget nanotherapeutics that can be used to resolve cytokine storms. In detail, primary peritoneal M2 macrophages exhibited superior anti-inflammatory potential than immobilized cell lines. Systemically administered M2-EVs entered major organs and were taken up by phagocytes (e.g., macrophages). M2-EV treatment effectively reduced excessive cytokine (e.g., TNF-α and IL-6) release in vitro and in vivo, thereby attenuating oxidative stress and multiple organ (lung, liver, spleen and kidney) damage in endotoxin-induced cytokine storms. Moreover, M2-EVs simultaneously inhibited multiple key proinflammatory pathways (e.g., NF-κB, JAK-STAT and p38 MAPK) by regulating complex miRNA-gene and gene-gene networks, and this effect was collectively mediated by many functional cargos (miRNAs and proteins) in EVs. In addition to the direct anti-inflammatory role, human peritoneal M2-EVs expressed angiotensin-converting enzyme 2 (ACE2), a receptor of SARS-CoV-2 spike protein, and thus could serve as nanodecoys to prevent SARS-CoV-2 pseudovirus infection in vitro. As cell-derived nanomaterials, the therapeutic index of M2-EVs can be further improved by genetic/chemical modification or loading with specific drugs. This study highlights that peritoneal M2-EVs are promising multifunctional nanotherapeutics to attenuate infectious disease-related cytokine storms.

High Expression of HERV-K (HML-2) Might Stimulate Interferon in COVID-19 Patients

Background. Interferon is a marker of host antiviral immunity, which is disordered in COVID-19 patients. ERV can affect the secretion of interferon through the cGAS-STING pathway. In this study, we explored whether IFN-I and HERV-K (HML-2) were activated in COVID-19 patients and whether there was an interaction between them. Methods. We collected blood samples from COVID-19 patients and healthy controls. We first detected the expression of HERV-K (HML-2) gag, env, and pol genes and IFN-I-related genes between patients and healthy people by qPCR, synchronously detected VERO cells infected with SARS-CoV-2. Then, the chromosome distributions of highly expressed HERV-K (HML-2) gag, env, and pol genes were mapped by the next-generation sequencing results, and GO analysis was performed on the related genes. Results. We found that the HERV-K (HML-2) gag, env, and pol genes were highly expressed in COVID-19 patients and VERO cells infected with SARS-CoV-2. The interferon-related genes IFNB1, ISG15, and IFIT1 were also activated in COVID-19 patients, and GO analysis showed that HERV-K (HML-2) can regulate the secretion of interferon. Conclusions. The high expression of HERV-K (HML-2) might activate the increase of interferon in COVID-19 patients, proving that HERV-K does not only play a negative role in the human body.

Association of tumor necrosis factor alpha ‐308 single nucleotide polymorphism with SARS CoV‐2 infection in an Iraqi Kurdish population

Uncovering risk factors playing roles in the severity of Coronavirus disease 2019 (Covid‐19) are important for understanding pathoimmunology of the disease caused by severe acute respiratory syndrome Coronavirus 2 (SARS CoV‐2). Genetic variations in innate immune genes have been found to be associated with Covid‐19 infections. A single‐nucleotide polymorphism (SNP) in a promoter region of tumor necrosis factor alpha (TNF‐α) gene, TNF‐α −308G>A, increases expression of TNF‐α protein against infectious diseases leading to immune dysregulations and organ damage. This study aims to discover associations between TNF‐α −308G>A SNP and Covid‐19 infection. Polymerase chain reaction‐restriction fragment length polymorphism (PCR‐RFLP) was used for genotyping a general Kurdish population and Covid‐19 patients. The homozygous mutant (AA) genotype was found to be rare in the current studied population. Interestingly, the heterozygous (GA) genotype was significantly (p value = 0.0342) higher in the Covid‐19 patients than the general population. This suggests that TNF‐α −308G>A SNP might be associated with Covid‐19 infections. Further studies with larger sample sizes focusing on different ethnic populations are recommended.