Identifying Immunological and Clinical Predictors of COVID-19 Severity and Sequelae by Mathematical Modeling

Memory SARS-CoV-2 T-cell response in convalescent COVID-19 patients with undetectable specific IgG antibodies: a comparative study

Background

During the COVID-19 pandemic, a variable percentage of patients with SARS-CoV-2 infection failed to elicit humoral response. This study investigates whether patients with undetectable SARS-CoV-2 IgG are able to generate SARS-CoV-2 memory T cells with proliferative capacity upon stimulation.

Methods

This cross-sectional study was conducted with convalescent COVID-19 patients, diagnosed with a positive real-time PCR (RT-PCR) from nasal and pharyngeal swab specimens. COVID-19 patients were enrolled ≥3 months after the last PCR positive. Proliferative T-cell response after whole blood stimulation was assessed using the FASCIA assay.

Results

A total of 119 participants (86 PCR-confirmed COVID-19 patients and 33 healthy controls) were randomly filtered from an initial cohort. Of these 86 patients, 59 had detectable (seropositive) and 27 had undetectable (seronegative) SARS-CoV-2 IgG. Seropositive patients were subclassified as asymptomatic/mild or severe according to the oxygen supplementation requirement. SARS-CoV-2 CD3+ and CD4+ T cells showed significantly lower proliferative response in seronegative than in seropositive patients. The ROC curve analysis indicated that ≥ 5 CD4+ blasts/μL of blood defined a "positive SARS-CoV-2 T cell response". According to this cut-off, 93.2% of seropositive patients had a positive T-cell response compared to 50% of seronegative patients and 20% of negative controls (chi-square; p < 0.001).

Conclusions

This proliferative assay is useful not only to discriminate convalescent patients from negative controls, but also to distinguish seropositive patients from those with undetectable SARS-CoV-2 IgG antibodies. Memory T cells in seronegative patients are able to respond to SARSCoV-2 peptides, although at a lower magnitude than seropositive patients.

Liver Injury Associated with COVID-19 Infection: Pathogenesis, Histopathology, Prognosis, and Treatment

Liver injury occurs frequently as a consequence of SARS-CoV-2 infection. Direct infection of the liver leads to hepatic impairment with elevated transaminases. In addition, severe COVID-19 is characterized by cytokine release syndrome, which may initiate or exacerbate liver injury. In patients with cirrhosis, SARS-CoV-2 infection is associated with acute-on-chronic liver failure. The Middle East and North Africa (MENA) region is one of the world's regions characterized by a high prevalence of chronic liver diseases. Both parenchymal and vascular types of injury contribute to liver failure in COVID-19, with a myriad of pro-inflammatory cytokines playing a major role in perpetuating liver injury. Additionally, hypoxia and coagulopathy complicate such a condition. This review discusses the risk factors, and the underlying causes of impaired liver functions in COVID-19, with a focus on key players in the pathogenesis of liver injury. It also highlights the histopathological changes encountered in postmortem liver tissues as well as potential predictors and prognostic factors of such injury, in addition to the management strategies to ameliorate liver damage.

Liver injury associated with the severity of COVID-19: A meta-analysis

Background

The current 2019 novel coronavirus disease (COVID-19) pandemic is a major threat to global health. It is currently uncertain whether and how liver injury affects the severity of COVID-19. Therefore, we conducted a meta-analysis to determine the association between liver injury and the severity of COVID-19.

Methods

A systematic search of the PubMed, Embase, and Cochrane Library databases from inception to August 12, 2022, was performed to analyse the reported liver chemistry data for patients diagnosed with COVID-19. The pooled odds ratio (OR), weighted mean difference (WMD) and 95% confidence interval (95% CI) were assessed using a random-effects model. Furthermore, publication bias and sensitivity were analyzed.

Results

Forty-six studies with 28,663 patients were included. The pooled WMDs of alanine aminotransferase (WMD = 12.87 U/L, 95% CI: 10.52-15.23, I ² = 99.2%), aspartate aminotransferase (WMD = 13.98 U/L, 95% CI: 12.13-15.83, I ² = 98.2%), gamma-glutamyl transpeptidase (WMD = 20.67 U/L, 95% CI: 14.24-27.10, I ² = 98.8%), total bilirubin (WMD = 2.98 μmol/L, 95% CI: 1.98-3.99, I ² = 99.4%), and prothrombin time (WMD = 0.84 s, 95% CI: 0.46-1.23, I ² = 99.4%) were significantly higher and that of albumin was lower (WMD = -4.52 g/L, 95% CI: -6.28 to -2.75, I ² = 99.9%) in severe cases. Moreover, the pooled OR of mortality was higher in patients with liver injury (OR = 2.72, 95% CI: 1.18-6.27, I ² = 71.6%).

Conclusions

Hepatocellular injury, liver metabolic, and synthetic function abnormality were observed in severe COVID-19. From a clinical perspective, liver injury has potential as a prognostic biomarker for screening severely affected patients at early disease stages.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, Identifier: CRD42022325206.

Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases

The liver is a key organ involved in a wide range of functions, whose damage can lead to chronic liver disease (CLD). CLD accounts for more than two million deaths worldwide, becoming a social and economic burden for most countries. Among the different factors that can cause CLD, alcohol abuse, viruses, drug treatments, and unhealthy dietary patterns top the list. These conditions prompt and perpetuate an inflammatory environment and oxidative stress imbalance that favor the development of hepatic fibrogenesis. High stages of fibrosis can eventually lead to cirrhosis or hepatocellular carcinoma (HCC). Despite the advances achieved in this field, new approaches are needed for the prevention, diagnosis, treatment, and prognosis of CLD. In this context, the scientific com-munity is using machine learning (ML) algorithms to integrate and process vast amounts of data with unprecedented performance. ML techniques allow the integration of anthropometric, genetic, clinical, biochemical, dietary, lifestyle and omics data, giving new insights to tackle CLD and bringing personalized medicine a step closer. This review summarizes the investigations where ML techniques have been applied to study new approaches that could be used in inflammatory-related, hepatitis viruses-induced, and coronavirus disease 2019-induced liver damage and enlighten the factors involved in CLD development.

CXCL10 Chemokine: A Critical Player in RNA and DNA Viral Infections

Chemokines constitute a group of small, secreted proteins that regulate leukocyte migration and contribute to their activation. Chemokines are crucial inflammatory mediators that play a key role in managing viral infections, during which the profile of chemokine expression helps shape the immune response and regulate viral clearance, improving clinical outcome. In particular, the chemokine ligand CXCL10 and its receptor CXCR3 were explored in a plethora of RNA and DNA viral infections. In this review, we highlight the expression profile and role of the CXCL10/CXCR3 axis in the host defense against a variety of RNA and DNA viral infections. We also discuss the interactions among viruses and host cells that trigger CXCL10 expression, as well as the signaling cascades induced in CXCR3 positive cells.

IL-6, IL-10, sFas, granulysin and indicators of intestinal permeability as early biomarkers for a fatal outcome in COVID-19

The clinical presentation of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ranges between mild respiratory symptoms and a severe disease that shares many of the features of sepsis. Sepsis is a deregulated response to infection that causes life-threatening organ failure. During sepsis, the intestinal epithelial cells are affected, causing an increase in intestinal permeability and allowing microbial translocation from the intestine to the circulation, which exacerbates the inflammatory response. Here we studied patients with moderate, severe and critical COVID-19 by measuring a panel of molecules representative of the innate and adaptive immune responses to SARS-CoV-2, which also reflect the presence of systemic inflammation and the state of the intestinal barrier. We found that non-surviving COVID-19 patients had higher levels of low-affinity anti-RBD IgA antibodies than surviving patients, which may be a response to increased microbial translocation. We identified sFas and granulysin, in addition to IL-6 and IL-10, as possible early biomarkers with high sensitivity (>73 %) and specificity (>51 %) to discriminate between surviving and non-surviving COVID-19 patients. Finally, we found that the microbial metabolite d-lactate and the tight junction regulator zonulin were increased in the serum of patients with severe COVID-19 and in COVID-19 patients with secondary infections, suggesting that increased intestinal permeability may be a source of secondary infections in these patients. COVID-19 patients with secondary infections had higher disease severity and mortality than patients without these infections, indicating that intestinal permeability markers could provide complementary information to the serum cytokines for the early identification of COVID-19 patients with a high risk of a fatal outcome.