The Predictive Value of Serum ACE2 and TMPRSS2 Concentrations in Patients with COVID-19-A Prospective Pilot Study.

One of the major challenges for healthcare systems during the Coronavirus-2019 (COVID-19) pandemic was the inability to successfully predict which patients would require mechanical ventilation (MV). Angiotensin-Converting Enzyme 2 (ACE2) and TransMembrane Protease Serine S1 member 2 (TMPRSS2) are enzymes that play crucial roles in SARS-CoV-2 entry into human host cells. However, their predictive value as biomarkers for risk stratification for respiratory deterioration requiring MV has not yet been evaluated. We aimed to evaluate whether serum ACE2 and TMPRSS2 levels are associated with adverse outcomes in COVID-19, and specifically the need for MV. COVID-19 patients admitted to an Israeli tertiary medical center between March--November 2020, were included. Serum samples were obtained shortly after admission (day 0) and again following one week of admission (day 7). ACE2 and TMPRSS2 concentrations were measured with ELISA. Of 72 patients included, 30 (41.6%) ultimately required MV. Serum ACE2 concentrations >7.8 ng/mL at admission were significantly associated with the need for MV (p = 0.036), inotropic support, and renal replacement therapy. In multivariate logistic regression analysis, elevated ACE2 at admission was associated with the need for MV (OR = 7.49; p = 0.014). To conclude, elevated serum ACE2 concentration early in COVID-19 illness correlates with respiratory failure necessitating mechanical ventilation. We suggest that measuring serum ACE2 at admission may be useful for predicting the risk of severe disease.

Characterization of the significant decline in humoral immune response six months post-SARS-CoV-2 mRNA vaccination: A systematic review.

Accumulating evidence shows a progressive decline in the efficacy of coronavirus disease 2019 (COVID-19) (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) messenger RNA (mRNA) vaccines such as Pfizer-BioNTech (mRNA BNT161b2) and Moderna (mRNA-1273) in preventing breakthrough infections due to diminishing humoral immunity over time. Thus, this review characterizes the kinetics of anti-SARS-CoV-2 antibodies after the second dose of a primary cycle of COVID-19 mRNA vaccination. A systematic search of the literature was performed and a total of 18 articles (N = 15 980 participants) were identified and reviewed. The percent difference of means of reported antibody titers was then calculated to determine the decline in humoral response after the peak levels postvaccination. Findings revealed that the peak humoral response was reached at 21-28 days after the second dose, after which serum levels progressively diminished at 4-6-month postvaccination. Additionally, results showed that regardless of age, sex, serostatus, and presence of comorbidities, longitudinal data reporting antibody measurement exhibited a decline of both anti-receptor binding domain immunoglobulin G (IgG) and anti-spike IgG, ranging from 94% to 95% at 90-180 days and 55%-85% at 140-160 days, respectively, after the peak antibody response. This suggests that the rate of antibody decline may be independent of patient-related factors and peak antibody titers but mainly a function of time and antibody class/molecular target. Hence, this study highlights the necessity of more efficient vaccination strategies to provide booster administration in attenuating the effects of waning immunity, especially in the appearance of new variants of concerns.

Clinical Predictors of SARS-CoV-2 Testing Pressure on Clinical Laboratories: A Multinational Study Analyzing Google Trends and Over 100 Million Diagnostic Tests.

OBJECTIVE: Evidence has shown that Google searches for clinical symptom keywords correlates with the number of new weekly patients with COVID-19. This multinational study assessed whether demand for SARS-CoV-2 tests could also be predicted by Google searches for key COVID-19 symptoms. METHODS: The weekly number of SARS-CoV-2 tests performed in Italy and the United States was retrieved from official sources. A concomitant electronic search was performed in Google Trends, using terms for key COVID-19 symptoms. RESULTS: The model that provided the highest coefficient of determination for the United States (R2 = 82.8%) included a combination of searching for cough (with a time lag of 2 weeks), fever (with a time lag of 2 weeks), and headache (with a time lag of 3 weeks; the time lag refers to the amount of time between when a search was conducted and when a test was administered). In Italy, headache provided the model with the highest adjusted R2 (86.8%), with time lags of both 1 and 2 weeks. CONCLUSION: Weekly monitoring of Google Trends scores for nonspecific COVID-19 symptoms is a reliable approach for anticipating SARS-CoV-2 testing demands ~2 weeks in the future.

The anti-inflammatory cytokine response characterized by elevated interleukin-10 is a stronger predictor of severe disease and poor outcomes than the pro-inflammatory cytokine response in coronavirus disease 2019 (COVID-19).

OBJECTIVES: Severe coronavirus disease 2019 (COVID-19) is associated with a dysregulated immune state. While research has focused on the hyperinflammation, little research has been performed on the compensatory anti-inflammatory response. The aim of this study was to evaluate the anti-inflammatory cytokine response to COVID-19, by assessing interleukin-10 (IL-10) and IL-10/lymphocyte count ratio and their association with outcomes. METHODS: Adult patients presenting to the emergency department (ED) with laboratory-confirmed COVID-19 were recruited. The primary endpoint was maximum COVID-19 severity within 30 days of index ED visit. RESULTS: A total of 52 COVID-19 patients were enrolled. IL-10 and IL-10/lymphocyte count were significantly higher in patients with severe disease (p<0.05), as well as in those who developed severe acute kidney injury (AKI) and new positive bacterial cultures (all p≤0.01). In multivariable analysis, a one-unit increase in IL-10 and IL-10/lymphocyte count were associated with 42% (p=0.031) and 32% (p=0.013) increased odds, respectively, of severe COVID-19. When standardized to a one-unit standard deviations scale, an increase in the IL-10 was a stronger predictor of maximum 30-day severity and severe AKI than increases in IL-6 or IL-8. CONCLUSIONS: The hyperinflammatory response to COVID-19 is accompanied by a simultaneous anti-inflammatory response, which is associated with poor outcomes and may increase the risk of new positive bacterial cultures. IL-10 and IL-10/lymphocyte count at ED presentation were independent predictors of COVID-19 severity. Moreover, elevated IL-10 was more strongly associated with outcomes than pro-inflammatory IL-6 or IL-8. The anti-inflammatory response in COVID-19 requires further investigation to enable more precise immunomodulatory therapy against SARS-CoV-2.