Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19

Clinical presentations and diagnostic approaches of pediatric necrotizing tracheobronchitis with influenza A virus and Staphylococcus aureus co-infections

In March 2023, our pediatric intensive care unit (PICU) retrospectively examined six cases of pediatric necrotizing tracheobronchitis (NTB), focusing on co-infections with influenza A virus (IAV) and Staphylococcus aureus (S. aureus). This study aimed to elucidate NTB's clinical characteristics, diagnostics, and therapeutic approaches. Diagnostics included symptom assessment, microbiological testing that confirmed all patients were positive for IAV H1N1 with a predominant S. aureus co-infection, and bronchoscopy. The patients predominantly exhibited fever, cough, and dyspnea. Laboratory analysis revealed decreased lymphocyte counts and elevated infection markers like C-reactive protein and procalcitonin. Chest computed tomography (CT) scans detected tracheobronchial obstructions in half of the cases, while bronchoscopy showed severe mucosal congestion, edema, necrosis, and purulent-hemorrhagic exudates. Treatments encompassed comprehensive strategies like oxygen therapy, intubation, bronchoscopic interventions, thoracentesis, oseltamivir, and a regimen of antibiotics. Our findings suggested potential correlations between clinical markers, notably lymphocyte count and procalcitonin, and clinical interventions such as the number of rescues and intensive care unit (ICU) duration. This research highlights the importance of early detection and the role of bronchoscopy and specific markers in assessing NTB, advocating for continued research in larger cohorts to better understand its clinical trajectory and refine treatment approaches for this challenging pediatric disease.

Severe COVID-19 infection: An institutional review and literature overview

BACKGROUND

Our study aimed to describe the group of severe COVID-19 patients at an institutional level, and determine factors associated with different outcomes.

METHODS

A retrospective chart review of patients admitted with severe acute hypoxic respiratory failure due to COVID-19 infection. Based on outcomes, we categorized 3 groups of severe COVID-19: (1) Favorable outcome: progressive care unit admission and discharge (2) Intermediate outcome: ICU care (3) Poor outcome: in-hospital mortality.

RESULTS

Eighty-nine patients met our inclusion criteria; 42.7% were female. The average age was 59.7 (standard deviation (SD):13.7). Most of the population were Caucasian (95.5%) and non-Hispanic (91.0%). Age, sex, race, and ethnicity were similar between outcome groups. Medicare and Medicaid patients accounted for 62.9%. The average BMI was 33.5 (SD:8.2). Moderate comorbidity was observed, with an average Charlson Comorbidity index (CCI) of 3.8 (SD:2.6). There were no differences in the average CCI between groups(p = 0.291). Many patients (67.4%) had hypertension, diabetes (42.7%) and chronic lung disease (32.6%). A statistical difference was found when chronic lung disease was evaluated; p = 0.002. The prevalence of chronic lung disease was 19.6%, 27.8%, and 40% in the favorable, intermediate, and poor outcome groups, respectively. Smoking history was associated with poor outcomes (p = 0.04). Only 7.9% were fully vaccinated. Almost half (46.1%) were intubated and mechanically ventilated. Patients spent an average of 12.1 days ventilated (SD:8.5), with an average of 6.0 days from admission to ventilation (SD:5.1). The intermediate group had a shorter average interval from admission to ventilator (77.2 hours, SD:67.6), than the poor group (212.8 hours, SD:126.8); (p = 0.001). The presence of bacterial pneumonia was greatest in the intermediate group (72.2%), compared to the favorable group (17.4%), and the poor group (56%); this was significant (p<0.0001). In-hospital mortality was seen in 28.1%.

CONCLUSION

Most patients were male, obese, had moderate-level comorbidity, a history of tobacco abuse, and government-funded insurance. Nearly 50% required mechanical ventilation, and about 28% died during hospitalization. Bacterial pneumonia was most prevalent in intubated groups. Patients who were intubated with a good outcome were intubated earlier during their hospital course, with an average difference of 135.6 hours. A history of cigarette smoking and chronic lung disease were associated with poor outcomes.

SARS-CoV-2-associated lymphopenia: possible mechanisms and the role of CD147

T lymphocytes play a primary role in the adaptive antiviral immunity. Both lymphocytosis and lymphopenia were found to be associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While lymphocytosis indicates an active anti-viral response, lymphopenia is a sign of poor prognosis. T-cells, in essence, rarely express ACE2 receptors, making the cause of cell depletion enigmatic. Moreover, emerging strains posed an immunological challenge, potentially alarming for the next pandemic. Herein, we review how possible indirect and direct key mechanisms could contribute to SARS-CoV-2-associated-lymphopenia. The fundamental mechanism is the inflammatory cytokine storm elicited by viral infection, which alters the host cell metabolism into a more acidic state. This "hyperlactic acidemia" together with the cytokine storm suppresses T-cell proliferation and triggers intrinsic/extrinsic apoptosis. SARS-CoV-2 infection also results in a shift from steady-state hematopoiesis to stress hematopoiesis. Even with low ACE2 expression, the presence of cholesterol-rich lipid rafts on activated T-cells may enhance viral entry and syncytia formation. Finally, direct viral infection of lymphocytes may indicate the participation of other receptors or auxiliary proteins on T-cells, that can work alone or in concert with other mechanisms. Therefore, we address the role of CD147-a novel route-for SARS-CoV-2 and its new variants. CD147 is not only expressed on T-cells, but it also interacts with other co-partners to orchestrate various biological processes. Given these features, CD147 is an appealing candidate for viral pathogenicity. Understanding the molecular and cellular mechanisms behind SARS-CoV-2-associated-lymphopenia will aid in the discovery of potential therapeutic targets to improve the resilience of our immune system against this rapidly evolving virus.

Evaluation and Mechanistic Investigation of Human Milk Oligosaccharide against SARS-CoV-2

Four human milk oligosaccharides (HMOs), 3'-sialyllactose (3'-SL), 6'-sialyllactose (6'-SL), 2'-fucosyllactose (2'-FL), and 3-fucosyllactose (3-FL), were assessed for their possible antiviral activity against the SARS-CoV-2 spike receptor binding domain (RBD) in vitro. Among them, only 2'-FL/3-FL exhibited obvious antibinding activity against direct binding and trans-binding in competitive immunocytochemistry and enzyme-linked immunosorbent assays. The antiviral effects of 2'-FL/3-FL were further confirmed by pseudoviral assays with three SARS-Cov-2 mutants, with a stronger inhibition effect of 2'-FL than 3-FL. Then, 2'-FL/3-FL were studied with molecular docking and microscale thermophoresis analysis, showing that the binding sites of 2'-FL on RBD were involved in receptor binding, in addition to a tighter bond between them, thus enabling 2'-FL to be more effective than 3-FL. Moreover, the immunomodulation effect of 2'-FL was preliminary evaluated and confirmed in a human alveolus chip. These results would open up possible applications of 2'-FL for the prevention of SARS-CoV-2 infections by competitive binding inhibition.

How immune breakthroughs could slow disease progression and improve prognosis in COVID-19 patients: a retrospective study

Background

Previous infections and vaccinations have produced preexisting immunity, which differs from primary infection in the organism immune response and may lead to different disease severities and prognoses when reinfected.

Objectives

The purpose of this retrospective cohort study was to investigate the impact of immune breakthroughs on disease progression and prognosis in patients with COVID-19.

Methods

A retrospective cohort study was conducted on 1513 COVID-19 patients in Chengdu Public Health Clinical Medical Center from January 2020 to November 2022. All patients were divided into the no immunity group (primary infection and unvaccinated, n=1102) and the immune breakthrough group (previous infection or vaccination, n=411). The immune breakthrough group was further divided into the natural immunity subgroup (n=73), the acquired immunity subgroup (n=322) and the mixed immunity subgroup (n=16). The differences in clinical and outcome data and T lymphocyte subsets and antibody levels between two groups or between three subgroups were compared by ANOVA, t test and chi-square test, and the relationship between T lymphocyte subsets and antibody levels and the disease progression and prognosis of COVID-19 patients was assessed by univariate analysis and logistic regression analysis.

Results

The total critical rate and the total mortality rate were 2.11% and 0.53%, respectively. The immune breakthrough rate was 27.16%. In the no immunity group, the critical rate and the mortality rate were all higher, and the coronavirus negative conversion time was longer than those in the immune breakthrough group. The differences in the critical rate and the coronavirus negative conversion time between the two groups were all statistically significant (3.72% vs. 0.24%, 14.17 vs. 11.90 days, all p<0.001). In addition, in the no immunity group, although lymphocyte counts and T subsets at admission were higher, all of them decreased consistently and significantly and were significantly lower than those in the immune breakthrough group at the same time from the first week to the fourth week after admission (all p<0.01). The total antibody levels and specific Immunoglobulin G (IgG) levels increased gradually and were always significantly lower than those in the immune breakthrough group at the same time from admission to the fourth week after admission (all p<0.001). Moreover, in the natural immunity subgroup, lymphocyte counts and T subsets at admission were the highest, and total antibody levels and specific IgG levels at admission were the lowest. Then, all of them decreased significantly and were the lowest among the three subgroups at the same time from admission to one month after admission (total antibody: from 546.07 to 158.89, IgG: from 6.00 to 3.95) (all p<0.001). Those in the mixed immunity subgroup were followed by those in the acquired immunity subgroup. While lymphocyte counts and T subsets in these two subgroups and total antibody levels (from 830.84 to 1008.21) and specific IgG levels (from 6.23 to 7.51) in the acquired immunity subgroup increased gradually, total antibody levels (from 1100.82 to 908.58) and specific IgG levels (from 7.14 to 6.58) in the mixed immunity subgroup decreased gradually. Furthermore, T lymphocyte subsets and antibody levels were negatively related to disease severity, prognosis and coronavirus negative conversion time. The total antibody, specific IgM and IgG levels showed good utility for predicting critical COVID-19 patients and dead COVID-19 patients.

Conclusion

Among patients with COVID-19 patients, immune breakthroughs resulting from previous infection or vaccination, could decelerate disease progression and enhance prognosis by expediting host cellular and humoral immunity to accelerate virus clearance, especially in individuals who have been vaccinated and previously infected.

Clinical trial registry

Chinese Clinical Trial Register ChiCTR2000034563.

Pattern-recognition receptors (PRRs) in SARS-CoV-2

Pattern recognition receptors (PRRs) are specific sensors that directly recognize various molecules derived from viral or bacterial pathogens, senescent cells, damaged cells, and apoptotic cells. These sensors act as a bridge between nonspecific and specific immunity in humans. PRRs in human innate immunity were classified into six types: toll-like receptors (TLR), C-type lectin receptors (CLRs), nucleotide-binding and oligomerization domain (NOD)-like receptors (NLRs), absent in melanoma 2 (AIM2)-like receptors (ALRs), retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs), and cyclic GMP-AMP (cGAMP) synthase (cGAS). Numerous types of PRRs are responsible for recognizing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which is immensely effective in prompting interferon responses. Detection of SARS-CoV-2 infection by PRRs causes the initiation of an intracellular signaling cascade and subsequently the activation of various transcription factors that stimulate the production of cytokines, chemokines, and other immune-related factors. Therefore, it seems that PRRs are a promising potential therapeutic approach for combating SARS-CoV-2 infection and other microbial infections. In this review, we have introduced the current knowledge of various PRRs and related signaling pathways in response to SARS-CoV-2.

Redistribution and Activation of CD16brightCD56dim NK Cell Subset to Fight against Omicron Subvariant BA.2 after COVID-19 Vaccination

With the alarming surge in COVID-19 cases globally, vaccination must be prioritised to achieve herd immunity. Immune dysfunction is detected in the majority of patients with COVID-19; however, it remains unclear whether the immune responses elicited by COVID-19 vaccination function against the Omicron subvariant BA.2. Of the 508 enrolled patients infected with Omicron BA.2, 102 were unvaccinated controls, and 406 were vaccinated. Despite the presence of clinical symptoms in both groups, vaccination led to a significant decline in nausea or vomiting, abdominal pain, headache, pulmonary infection, and overall clinical symptoms and a moderate rise in body temperature. The individuals infected with Omicron BA.2 were also characterised by a mild increase in both serum pro- and anti-inflammatory cytokine levels after vaccination. There were no significant differences or trend changes between T- and B-lymphocyte subsets; however, a significant expansion of NK lymphocytes in COVID-19-vaccinated patients was observed. Moreover, the most effective CD16brightCD56dim subsets of NK cells showed increased functional capacities, as evidenced by a significantly greater IFN-γ secretion and a stronger cytotoxic potential in the patients infected with Omicron BA.2 after vaccination. Collectively, these results suggest that COVID-19 vaccination interventions promote the redistribution and activation of CD16brightCD56dim NK cell subsets against viral infections and that they could facilitate the clinical management of patients infected with Omicron BA.2.

CD4+ T-Cell Depression is Linked to the Severity of COVID-19 and Predicts Mortality

Objective

Most patients with coronavirus disease (COVID-19) have abnormalities of lymphocyte subsets. This study aimed to determine the distribution of lymphocytes in patients with various severity levels of COVID-19 and to describe the relationship between the CD4+ T helper and prognosis.

Materials and Methods

Adult (>18 years old) patients with COVID-19 who followed up in a tertiary hospital were included in the study prospectively. Demographic and clinical characteristics of the patients were obtained from the hospital records. Peripheral flow cytometry was studied in patients with different severity of COVID-19 and different prognoses. Next, we analyzed the characteristics and predictive values of lymphocyte subsets in COVID-19 patients.

Results

Totally 86 patients were included in the study, of which 21 (24.4%) had asymptomatic, 23 (26.7%) had mild/moderate, and 42 (48.8%) had severe/critical COVID-19. Severe/critical patients had lower lymphocyte levels and older age than asymptomatic patients (p<0.001 and p<0.001, respectively). We determined that decreased CD4+ T cell ratio (p<0.001) and CD4+ /CD8+ ratio (p<0.001) were indicative of the severity of the disease. CD4+ T cell ratio on admission (odds ratio [OR]=0.858; p=0.033), day seven CD4+ T cell ratio (OR=0.840; p=0.029), and C-reactive protein (CRP) levels (OR=1.014; p=0.043) were prognostic factors for mortality. According to receiver operating characteristics (ROC) curve analysis, the area under the curve was greater than 0.9 for decreased CD4 + T cell ratio on admission and the seventh day.

Conclusion

A low CD4+ T helper ratio predicts a poor prognosis. In combination with CRP, it can be used in clinical follow-up.

Adaptive immune dysfunction in patients with COVID-19 and impaired kidney function during the omicron surge

BACKGROUND

Little is known about the characteristics of lymphocyte subsets and the association with patient outcomes in COVID-19 with and without impaired kidney function.

METHODS

Lymphocyte subsets were compared in COVID-19 patients with or without kidney dysfunction. The primary outcome was a composite of all-cause mortality or intensive care unit admission. Secondary outcomes included duration of viral shedding, length of hospital stay, and acute kidney injury.

RESULTS

Lymphocyte subset cell counts demonstrated the lowest in patients with severe/critical COVID-19 and kidney dysfunction. Among all lymphocyte subset parameters, Th cell count was the most significant indicator for outcomes. ROC of the combined model of Th cell count and eGFR presented better predictive value than that of the other parameters. Th cell count <394.5 cells/μl and eGFR <87.5 ml/min/1·73m² were independently associated with poor outcomes. The propensity score matching analysis revealed consistent results.

CONCLUSIONS

Reduced Th cell count and eGFR may be applied as promising predictive indicators for identifying COVID-19 patients with high risk and poor outcomes.

The Risk Factors and Outcomes for Radiological Abnormalities in Early Convalescence of COVID-19 Patients Caused by the SARS-CoV-2 Omicron Variant: A Retrospective, Multicenter Follow-up Study

BACKGROUND

The emergence of the severe acute respiratory syndrome coronavirus 2 omicron variant has been triggering the new wave of coronavirus disease 2019 (COVID-19) globally. However, the risk factors and outcomes for radiological abnormalities in the early convalescent stage (1 month after diagnosis) of omicron infected patients are still unknown.

METHODS

Patients were retrospectively enrolled if they were admitted to the hospital due to COVID-19. The chest computed tomography (CT) images and clinical data obtained at baseline (at the time of the first CT image that showed abnormalities after diagnosis) and 1 month after diagnosis were longitudinally analyzed. Uni-/multi-variable logistic regression tests were performed to explore independent risk factors for radiological abnormalities at baseline and residual pulmonary abnormalities after 1 month.

RESULTS

We assessed 316 COVID-19 patients, including 47% with radiological abnormalities at baseline and 23% with residual pulmonary abnormalities at 1-month follow-up. In a multivariate regression analysis, age ≥ 50 years, body mass index ≥ 23.87, days after vaccination ≥ 81 days, lymphocyte count ≤ 1.21 × 10^-9/L, interleukin-6 (IL-6) ≥ 10.05 pg/mL and IgG ≤ 14.140 S/CO were independent risk factors for CT abnormalities at baseline. The age ≥ 47 years, presence of interlobular septal thickening and IL-6 ≥ 5.85 pg/mL were the independent risk factors for residual pulmonary abnormalities at 1-month follow-up. For residual abnormalities group, the patients with less consolidations and more parenchymal bands at baseline could progress on CT score after 1 month. There were no significant changes in the number of involved lung lobes and total CT score during the early convalescent stage.

CONCLUSION

The higher IL-6 level was a common independent risk factor for CT abnormalities at baseline and residual pulmonary abnormalities at 1-month follow-up. There were no obvious radiographic changes during the early convalescent stage in patients with residual pulmonary abnormalities.

Remdesivir improves biomarkers associated with disease severity in COVID-19 patients treated in an outpatient setting

BACKGROUND

Remdesivir (RDV) is an intravenous antiviral with activity against SARS-CoV-2 for treatment of hospitalized COVID-19 patients with moderate-to-severe disease. Biomarkers associated with clinical outcomes have been identified for COVID-19, but few evaluated in context of antiviral treatment. Here, we assessed baseline (day 1, prior to first RDV dose) biomarkers and the impact of RDV treatment on longitudinal biomarker readouts.

METHODS

Recently, RDV was evaluated in high-risk, non-hospitalized patients with confirmed SARS-CoV-2 infection and was highly effective at preventing disease progression. The randomized, double-blind, placebo-controlled Phase 3 study included 562 participants who received at least 1 dose of study drug, of which 312 consented for longitudinal biomarker assessments at baseline, day 3, and day 14. We assessed sixteen baseline biomarkers and the impact of RDV treatment on longitudinal biomarker readouts.

RESULTS

Six well-known, inflammation-associated biomarkers are elevated at baseline in participants meeting the primary endpoint of hospitalization or death by day 28. Moreover, in comparison to placebo, biomarkers in RDV-treated participants show accelerated improvement, including reduction of soluble angiopoietin-2, D-dimer, and neutrophil-to-lymphocyte ratio, as well as an increase in lymphocyte counts.

CONCLUSIONS

Overall, the findings in this study suggest that RDV treatment may accelerate the improvement of multiple biomarkers of COVID-19 severity, which are associated with better clinical outcomes during infection. These findings have implications for better understanding the activity of antiviral treatments in COVID-19.

Kinetics of Immune Subsets in COVID-19 Patients Treated with Corticosteroids

RATIONALE

Changes in anti-SARS-CoV-2 defense immune subsets in patients treated with dexamethasone (DXM) for severe COVID-19 and their relation to disease outcomes are poorly understood.

METHODS

Blood-lymphocyte subsets of 110 hospitalized COVID-19 patients were prospectively examined. A first sample was taken at enrollment and a second one 7-10 days later. Total B-, T-lymphocytes, CD4+, CD8+, T-regulatory (Treg), Natural-Killer (NK) and NK T-cells were counted using flow cytometry.

RESULTS

At enrollment, patients with respiratory failure, characterized by DXM failure (intubation/death) or DXM success (hospital discharge) exhibited significantly fewer CD3+, CD4+ and CD8+ cells and B-lymphocytes compared to the control group (no respiratory failure/no DXM). At the time of treatment completion, the DXM-failure group exhibited significantly fewer CD3+, CD4+ and CD8+ cells, memory CD4+ and CD8+ T-lymphocytes, compared to the control and the DXM-success groups and fewer activated CD4+ T-lymphocytes, Tregs and NK cells compared to the control group. At the time of treatment completion, the number of all investigated lymphocyte subsets increased in the DXM-success group and was similar to those of the control group. NK cells significantly decreased over time in the DXM-failure group.

CONCLUSION

The lymphocyte kinetics differ between DXM-treated and control COVID-19 patients and are associated with clinical outcomes.

Validation of the T-Lymphocyte Subset Index (TLSI) as a Score to Predict Mortality in Unvaccinated Hospitalized COVID-19 Patients

Lymphopenia has been consistently reported as associated with severe coronavirus disease 2019 (COVID-19). Several studies have described a profound decline in all T-cell subtypes in hospitalized patients with severe and critical COVID-19. The aim of this study was to assess the role of T-lymphocyte subset absolute counts measured at ward admission in predicting 30-day mortality in COVID-19 hospitalized patients, validating a new prognostic score, the T-Lymphocyte Subset Index (TLSI, range 0−2), based on the number of T-cell subset (CD4+ and CD8+) absolute counts that are below prespecified cutoffs. These cutoff values derive from a previously published work of our research group at Policlinico Tor Vergata, Rome, Italy: CD3+CD4+ < 369 cells/μL, CD3+CD8+ < 194 cells/μL. In the present single-center retrospective study, T-cell subsets were assessed on admission to the infectious diseases ward. Statistical analysis was performed using JASP (Version 0.16.2. JASP Team, 2022, Amsterdam, The Netherlands) and Prism8 (version 8.2.1. GraphPad Software, San Diego, CA, USA). Clinical and laboratory parameters of 296 adult patients hospitalized because of COVID-19 were analyzed. The overall mortality rate was 22.3% (66/296). Survivors (S) had a statistically significant lower TLSI score compared to non-survivors (NS) (p < 0.001). Patients with increasing TLSI scores had proportionally higher rates of 30-day mortality (p < 0.0001). In the multivariable logistic analysis, the TLSI was an independent predictor of in-hospital 30-day mortality (OR: 1.893, p = 0.003). Survival analysis showed that patients with a TLSI > 0 had an increased risk of death compared to patients with a TLSI = 0 (hazard ratio: 2.83, p < 0.0001). The TLSI was confirmed as an early and independent predictor of COVID-19 in-hospital 30-day mortality.