Genetic Predisposition to SARS-CoV-2 Infection: Cytokine Polymorphism and Disease Transmission within Households

We addressed the question of the influence of the molecular polymorphism of cytokines from different T helper subsets on the susceptibility to SARS-CoV-2 infection. From a cohort of 527 samples (collected from 26 May 2020 to 31 March 2022), we focused on individuals living in the same household (n = 58) with the SARS-CoV-2-infected person. We divided them into households with all individuals SARS-CoV-2 PCR positive (n = 29, households, 61 individuals), households with mixed PCR pattern (n = 24, 62) and negative households (n = 5, 15), respectively. TGF-β1 and IL-6 were the only cytokines tested with a significant difference between the cohorts. We observed a shift toward Th2 and the regulatory Th17 and Treg subset regulation for households with all members infected compared to those without infection. These data indicate that the genetically determined balance between the cytokines acting on different T helper cell subsets may play a pivotal role in transmission of and susceptibility to SARS-CoV-2 infection. Contacts infected by their index persons were more likely to highly express TGF-β1, indicating a reduced inflammatory response. Those not infected after contact had a polymorphism leading to a higher IL-6 expression. IL-6 acts in innate immunity, allergy and on the T helper cell differentiation, explaining the reduced susceptibility to SARS-CoV-2.

Individual Immune Response to SARS-CoV-2 Infection-The Role of Seasonal Coronaviruses and Human Leukocyte Antigen

During the coronavirus pandemic, evidence is growing that the severity, susceptibility and host immune response to SARS-CoV-2 infection can be highly variable. Several influencing factors have been discussed. Here, we investigated the humoral immune response against SARS-CoV-2 spike, S1, S2, the RBD, nucleocapsid moieties and S1 of seasonal coronaviruses: hCoV-229E, hCoV-HKU1, hCoV-NL63 and hCoV-OC43, as well as MERS-CoV and SARS-CoV, in a cohort of 512 individuals. A bead-based multiplex assay allowed simultaneous testing for all the above antigens and the identification of different antibody patterns. Then, we correlated these patterns with 11 HLA loci. Regarding the seasonal coronaviruses, we found a moderate negative correlation between antibody levels against hCoV-229E, hCoV-HKU1 and hCoV-NL63 and the SARS-CoV-2 antigens. This could be an indication of the original immunological imprinting. High and low antibody response patterns were distinguishable, demonstrating the individuality of the humoral response towards the virus. An immunogenetical factor associated with a high antibody response (formation of ≥4 different antibodies) was the presence of HLA A*26:01, C*02:02 and DPB1*04:01 alleles, whereas the HLA alleles DRB3*01:01, DPB1*03:01 and DB1*10:01 were enriched in low responders. A better understanding of this variable immune response could enable more individualized protective measures.

Abstract P598: Increased Risk of Acute Stroke in Patients With Severe Course of Covid-19: A Multicenter Study and Meta-Analysis

Introduction: Recent studies linked coronavirus disease 2019 (COVID-19) to thromboembolic complications likely mediated by increased blood coagulability and inflammatory endothelial impairment.

Objective: We aimed to assess the risk of acute stroke in patients with COVID-19 related to clinical severity of the disease.

Methods: We conducted an observational multicenter cohort study in four participating hospitals in Saxony, Germany to characterize consecutive patients with laboratory-confirmed COVID-19 who experienced acute stroke during hospitalization. Furthermore, we performed a systematic review using PubMed/MEDLINE, EMBASE, Cochrane Library and bibliographies of identified articles following PRISMA guidelines including data from observational studies of acute stroke in COVID-19 patients. Data was extracted by two independent reviewers and pooled with multicenter data to calculate risk ratios (RR) and 95% confidence intervals (95%CIs) for acute stroke related to COVID-19 severity using random effects model. Between-study heterogeneity was assessed using Cochran’s Q and I 2 -statistics. PROSPERO identifier : CRD42020187194.

Results: Of 165 patients hospitalized for COVID-19 (49.1% males, median age 67 [57-79], 72.1% severe or critical) included in the multicenter study, overall stroke rate was 4.2% (95%CI: 1.9-8.7). Systematic literature search identified two observational studies involving 576 patients that were eligible for meta-analysis. Among 741 pooled COVID-19 patients overall stroke rate was 2.9% (95%CI: 1.9-4.5). Risk of acute stroke was increased for patients with severe compared to non-severe COVID-19 (RR 4.12, 95%CI 1.7-10.25; p=0.002) with no evidence of heterogeneity (I 2 =0%, p=0.82).

Conclusions: Synthesized analysis of data from our multicenter study and previously published cohorts demonstrate that severity of COVID-19 is associated with an increased risk of acute stroke, underscoring the necessity of neurological monitoring in patients infected with SARS-CoV-2.

Association of history of cerebrovascular disease with severity of COVID-19

OBJECTIVE

To determine whether a history of cerebrovascular disease (CVD) increases risk of severe coronavirus disease 2019 (COVID-19).

METHODS

In a retrospective multicenter study, we retrieved individual data from in-patients treated March 1 to April 15, 2020 from COVID-19 registries of three hospitals in Saxony, Germany. We also performed a systematic review and meta-analysis following PRISMA recommendations using PubMed, EMBASE, Cochrane Library databases and bibliographies of identified papers (last search on April 11, 2020) and pooled data with those deriving from our multicenter study. Of 3762 records identified, 11 eligible observational studies of laboratory-confirmed COVID-19 patients were included in quantitative data synthesis. Risk ratios (RR) of severe COVID-19 according to history of CVD were pooled using DerSimonian and Laird random effects model. Between-study heterogeneity was assessed using Cochran's Q and I2-statistics. Severity of COVID-19 according to definitions applied in included studies was the main outcome. Sensitivity analyses were conducted for clusters of studies with equal definitions of severity.

RESULTS

Pooled analysis included data from 1906 laboratory-confirmed COVID-19 patients (43.9% females, median age ranging from 39 to 76 years). Patients with previous CVD had higher risk of severe COVID-19 than those without [RR 2.07, 95% confidence interval (CI) 1.52-2.81; p < 0.0001]. This association was also observed in clusters of studies that defined severe manifestation of the disease by clinical parameters (RR 1.44, 95% CI 1.22-1.71; p < 0.0001), necessity of intensive care (RR 2.79, 95% CI 1.83-4.24; p < 0.0001) and in-hospital death (RR 2.18, 95% CI 1.75-2.7; p < 0.0001).

CONCLUSION

A history of CVD might constitute an important risk factor of unfavorable clinical course of COVID-19  suggesting a need of tailored infection prevention and clinical management strategies for this population at risk.

Increased risk of acute stroke among patients with severe COVID-19: a multicenter study and meta-analysis

BACKGROUND AND PURPOSE

Recent observations linked coronavirus disease 2019 (COVID-19) to thromboembolic complications possibly mediated by increased blood coagulability and inflammatory endothelial impairment. We aimed to define the risk of acute stroke in patients with severe and non-severe COVID-19.

METHODS

We performed an observational, multicenter cohort study in four participating hospitals in Saxony, Germany to characterize consecutive patients with laboratory-confirmed COVID-19 who experienced acute stroke during hospitalization. Furthermore, we conducted a systematic review using PubMed/MEDLINE, Embase, Cochrane Library and bibliographies of identified papers following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines including data from observational studies of acute stroke in COVID-19 patients. Data were extracted by two independent reviewers and pooled with multicenter data to calculate risk ratios (RRs) and 95% confidence intervals (95% CIs) for acute stroke related to COVID-19 severity using a random-effects model. Between-study heterogeneity was assessed using Cochran's Q and I2 statistics. International Prospective Register of Systematic Reviews registration number: CRD42020187194.

RESULTS

Of 165 patients hospitalized for COVID-19 (49.1% males, median age = 67 years [57-79 years], 72.1% severe or critical) included in the multicenter study, overall stroke rate was 4.2% (95% CI: 1.9-8.7). Systematic literature search identified two observational studies involving 576 patients that were eligible for meta-analysis. Amongst 741 pooled COVID-19 patients, overall stroke rate was 2.9% (95% CI: 1.9-4.5). Risk of acute stroke was increased for patients with severe compared to non-severe COVID-19 (RR = 4.18, 95% CI: 1.7-10.25; P = 0.002) with no evidence of heterogeneity (I2  = 0%, P = 0.82).

CONCLUSIONS

Synthesized analysis of data from our multicenter study and previously published cohorts indicates that severity of COVID-19 is associated with an increased risk of acute stroke.

Departmental consumption of antibiotic drugs and subsequent resistance: a quantitative link

OBJECTIVE

To look for a quantitative model linking departmental consumption of antibiotic drugs to the subsequent isolation of resistant hospital-acquired coliform pathogens.

MATERIALS AND METHODS

Included in the study were all patients with hospital-acquired bloodstream infections caused by a coliform pathogen, detected in six departments of internal medicine of one university hospital during the period 1991-1996, who had not been hospitalized in the month before the infection (n = 394). Departmental consumption of antibiotics in the year before the infection [expressed as defined daily dosages (DDD)/100 patient days], antibiotic treatment given to the individual patient before the infection, the day of hospital stay on which the infection occurred, and the department and the calendar year were all included in a logistic model to predict the isolation of a resistant pathogen. We looked at five drugs: gentamicin, amikacin, cefuroxime, ceftazidime and ciprofloxacin.

RESULTS

Five logistic models were fitted for the resistance to each of the antibiotic drugs. The multivariable-adjusted odds ratios for a pathogen resistant to the specific antibiotic were 1.03 [95% confidence interval (CI) 0.70-1.50] for gentamicin, 1.80 (95% CI 1.00-3.24) for amikacin, 1.12 (95% CI 1.02-1.23) for cefuroxime, 1.45 (95% CI 1.19-1.76) for ceftazidime and 1.06 (95% CI 0.57-1.97) for ciprofloxacin, per 1 DDD/100 patient days.

CONCLUSIONS

The departmental consumption of cephalosporin drugs and amikacin in six autonomous departments of medicine in the same hospital was associated with a measurable and statistically significant increase in the probability of infection caused by a resistant pathogen.