The age again in the eye of the COVID-19 storm: evidence-based decision making

Killer-cell immunoglobulin-like receptor polymorphism is associated with COVID-19 outcome: Results of a pilot observational study

The pathogenesis of COVID-19 warrants unravelling. Genetic polymorphism analysis may help answer the variability in disease outcome. To determine the role of KIR and HLA polymorphisms in susceptibility, progression, and severity of SARS-CoV-2 infection, 458 patients and 667 controls enrolled in this retrospective observational study from April to December 2020. Mild/moderate and severe/death study groups were established. HLA-A, -B, -C, and KIR genotyping were performed using the Lifecodes® HLA-SSO and KIR-SSO kits on the Luminex® 200™ xMAP fluoroanalyser. A probability score using multivariate binary logistic regression analysis was calculated to estimate the likelihood of severe COVID-19. ROC analysis was used to calculate the best cut-off point for predicting a worse clinical outcome with high sensitivity and specificity. A p ≤ 0.05 was considered statistically significant. KIR AA genotype protected positively against severity/death from COVID-19. Furthermore, KIR3DL1, KIR2DL3 and KIR2DS4 genes protected patients from severe forms of COVID-19. KIR Bx genotype, as well as KIR2DL2, KIR2DS2, KIR2DS3 and KIR3DS1 were identified as biomarkers of severe COVID-19. Our logistic regression model, which included clinical and KIR/HLA variables, categorised our cohort of patients as high/low risk for severe COVID-19 disease with high sensitivity and specificity (Se = 94.29%, 95% CI [80.84-99.30]; Sp = 84.55%, 95% CI [79.26-88.94]; OR = 47.58, 95%CI [11.73-193.12], p < 0.0001). These results illustrate an association between KIR/HLA ligand polymorphism and different COVID-19 outcomes and remarks the possibility of use them as a surrogate biomarkers to detect severe patients in possible future infectious outbreaks.

Risk of severe COVID-19 in unvaccinated patients during the period from wild-type to Omicron variant: real-world evidence from Japan

BACKGROUND

Many studies have reported that the Omicron variant is less pathogenic than the Delta variant and the wild-type. Epidemiological evidence regarding the risk of severe COVID-19 from the wild-type to the Omicron variant has been lacking.

METHODS

Study participants were COVID-19 patients aged 18 and older without previous COVID-19 infection who were notified to the Nara Prefecture Chuwa Public Health Center from January 2020 to March 2023, during the periods from the wild-type to the Omicron variant. The outcome variable was severe COVID-19 (i.e., ICU admission or COVID-19-related death). The explanatory variable was SARS-CoV-2 variant type or the number of COVID-19 vaccinations. Covariates included gender, age, risk factors for aggravation, and the number of general hospital beds per population. The generalized estimating equations of negative binomial regression models were used to estimate the adjusted incidence proportion (AIP) with 95% confidence interval (CI) for severe COVID-19.

RESULTS

Among 77,044 patients included in the analysis, 14,556 (18.9%) were unvaccinated and 520 (0.7%) developed severe COVID-19. Among unvaccinated patients, the risk of severe COVID-19 increased in the Alpha/Delta variants and decreased in the Omicron variant compared to the wild-type (AIP [95% CI] was 1.55 [1.06-2.27] in Alpha/Delta and 0.25 [0.15-0.40] in Omicron), but differed by age. Especially in patients aged ≥80, there was no significant difference in the risk of severe COVID-19 between the wild-type and the Omicron variant (AIP [95% CI] = 0.59 [0.27-1.29]). Regarding the preventive effect of vaccines, among all study participants, the number of vaccinations was significantly associated with the prevention of severe COVID-19, regardless of variant type. After stratified analyses by age, patients aged ≥80 remained a significant association for all variant types. On the other hand, the number of vaccinations had no association in Omicron BA.5 of patients aged 18-64.

CONCLUSIONS

Patients aged ≥80 had less reduction in risk of severe COVID-19 during the Omicron variant period, and a greater preventive effect of vaccines against severe COVID-19, compared to younger people. Our findings suggest that booster vaccination is effective and necessary for older people, especially aged ≥80.

HCG18, LEF1AS1 and lncCEACAM21 as biomarkers of disease severity in the peripheral blood mononuclear cells of COVID-19 patients

BACKGROUND

Even after 3 years from SARS-CoV-2 identification, COVID-19 is still a persistent and dangerous global infectious disease. Significant improvements in our understanding of the disease pathophysiology have now been achieved. Nonetheless, reliable and accurate biomarkers for the early stratification of COVID-19 severity are still lacking. Long noncoding RNAs (LncRNAs) are ncRNAs longer than 200 nucleotides, regulating the transcription and translation of protein-coding genes and they can be found in the peripheral blood, thus holding a promising biomarker potential. Specifically, peripheral blood mononuclear cells (PBMCs) have emerged as a source of indirect biomarkers mirroring the conditions of tissues: they include monocytes, B and T lymphocytes, and natural killer T cells (NKT), being highly informative for immune-related events.

METHODS

We profiled by RNA-Sequencing a panel of 2906 lncRNAs to investigate their modulation in PBMCs of a pilot group of COVID-19 patients, followed by qPCR validation in 111 hospitalized COVID-19 patients.

RESULTS

The levels of four lncRNAs were found to be decreased in association with COVID-19 mortality and disease severity: HLA Complex Group 18-242 and -244 (HCG18-242 and HCG18-244), Lymphoid Enhancer Binding Factor 1-antisense 1 (LEF1-AS1) and lncCEACAM21 (i.e. ENST00000601116.5, a lncRNA in the CEACAM21 locus). Interestingly, these deregulations were confirmed in an independent patient group of hospitalized patients and by the re-analysis of publicly available single-cell transcriptome datasets. The identified lncRNAs were expressed in all of the PBMC cell types and inversely correlated with the neutrophil/lymphocyte ratio (NLR), an inflammatory marker. In vitro, the expression of LEF1-AS1 and lncCEACAM21 was decreased upon THP-1 monocytes exposure to a relevant stimulus, hypoxia.

CONCLUSION

The identified COVID-19-lncRNAs are proposed as potential innovative biomarkers of COVID-19 severity and mortality.

Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach: An outcome prediction alternative

COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV-2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV-2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV-2 infection.

Association between inflammatory cytokines and anti-SARS-CoV-2 antibodies in hospitalized patients with COVID-19

BACKGROUND

COVID-19 patients may experience "cytokine storm" when human immune system produces excessive cytokines/chemokines. However, it remains unclear whether early responses of inflammatory cytokines would lead to high or low titers of anti-SARS-CoV-2 antibodies.

METHODS

This retrospective study enrolled a cohort of 272 hospitalized patients with laboratory-confirmed SARS-CoV-2. Laboratory assessments of serum cytokines (IL-2R, IL-6, IL-8, IL-10, TNF-α), anti-SARS-CoV-2 IgG/IgM antibodies, and peripheral blood biomarkers were conducted during hospitalization.

RESULTS

At hospital admission, 36.4% patients were severely ill, 51.5% patients were ≥ 65 years, and 60.3% patients had comorbidities. Higher levels of IL-2R and IL-6 were observed in older patients (≥65 years). Significant differences of IL-2R (week 2 to week ≥5 from symptom onset), IL-6 (week 1 to week ≥5), IL-8 (week 2 to week ≥5), and IL-10 (week 1 to week 3) were observed between moderately-ill and severely ill patients. Anti-SARS-CoV-2 IgG titers were significantly higher in severely ill patients than in moderately ill patients, but such difference was not observed for IgM. High titers of early-stage IL-6, IL-8, and TNF-α (≤2 weeks after symptom onset) were positively correlated with high titers of late-stage IgG (≥5 weeks after symptom onset). Deaths were mostly observed in severely ill older patients (45.9%). Survival analyses revealed risk factors of patient age, baseline COVID-19 severity, and baseline IL-6 that affected survival time, especially in severely ill older patients.

CONCLUSION

Early responses of elevated cytokines such as IL-6 reflect the active immune responses, leading to high titers of IgG antibodies against COVID-19.

Persistence of SARS-CoV-2 total immunoglobulins in a series of convalescent plasma and blood donors

Background

The vast majority of COVID-19 cases both symptomatic and asymptomatic develop immunity after COVID-19 contagion. Whether lasting differences exist between infection and vaccination boosted immunity is yet to be known. The aim of this study was to determine how long total anti-SARS-CoV2 antibodies due to past infection persist in peripheral blood and whether sex, age or haematological features can influence their lasting.

Material and methods

A series of 2421 donations either of SARS-CoV-2 convalescent plasma or whole blood from 1107 repeat donors from January 2020 to March 2021 was analysed. An automated chemiluminescence immunoassay for total antibodies recognizing the nucleocapsid protein of SARS-CoV-2 in human serum and plasma was performed. Sex, age, blood group, blood cell counts and percentages and immunoglobulin concentrations were extracted from electronic recordings. Blood donation is allowed after a minimum of one-month post symptom’s relapse. Donors were 69.7% males and their average age was 46. The 250 donors who had later donations after a positive one underwent further analysis. Both qualitative (positivity) and quantitative (rise or decline of optical density regarding consecutive donations) outcomes were evaluated.

Results and discussion

In 97.6% of donors with follow-up, anti-SARS-CoV-2 protein N total antibodies remained positive at the end of a follow-up period of 12.4 weeks median time (1–46, SD = 9.65) after the first positive determination. The blood group was not related to antibody waning. Lower lymphocyte counts and higher neutrophils would help predict future waning or decay of antibodies. Most recovered donors maintain their total anti-SARS-CoV-2 N protein antibodies for at least 16 weeks (at least one month must have been awaited from infection resolution to blood donation). The 10 individuals that could be followed up longer than 40 weeks (approximately 44 weeks after symptom’s relapse) were all still positive.

Innate and Adaptive Immune Assessment at Admission to Predict Clinical Outcome in COVID-19 Patients

During the COVID-19 pandemic, many studies have been carried out to evaluate different immune system components to search for prognostic biomarkers of the disease. A broad multiparametric antibody panel of cellular and humoral components of the innate and the adaptative immune response in patients with active SARS-CoV-2 infection has been evaluated in this study. A total of 155 patients were studied at admission into our center and were categorized according to the requirement of oxygen therapy as mild or severe (the latter being those with the requirement). The patients with severe disease were older and had high ferritin, D-dimer, C-reactive protein, troponin, interleukin-6 (IL-6) levels, and neutrophilia with lymphopenia at admission. Moreover, the patients with mild symptoms had significantly increased circulating non-classical monocytes, innate lymphoid cells, and regulatory NK cells. In contrast, severe patients had a low frequency of Th1 and regulatory T cells with increased activated and exhausted CD8 phenotype (CD8⁺CD38⁺HLADR⁺ and CD8⁺CD27^-CD28^-, respectively). The predictive model included age, ferritin, D-dimer, lymph counts, C4, CD8⁺CD27^-CD28^-, and non-classical monocytes in the logistic regression analysis. The model predicted severity with an area under the curve of 78%. Both innate and adaptive immune parameters could be considered potential predictive biomarkers of the prognosis of COVID-19 disease.