Dataset Information

Association of Interleukin-17F Polymorphism and Mortality Predictors with the Risk of COVID-19.

ABSTRACT:

Background

Th-17 cells, a proinflammatory subset of CD4 T lymphocytes, have been suggested as a possible cause of coronavirus disease-19 (COVID-19)-related immunological injuries. The aim of this study was to investigate the relationship between IL-17F (rs763780) polymorphism and the susceptibility to and outcomes of COVID-19 infection and to determine the clinical and laboratory predictors of COVID-19 death.

Methods

This case-control study included 132 COVID-19 patients and 135 healthy age- and sex-matched controls. The participants were tested for IL-17F rs763780 polymorphism via TaqMan-based genotyping and for the expression of IL-17 by enzyme-linked immunosorbent assay. This study also investigated the predictors for COVID-19 mortality.

Results

A non-statistically significant association was observed between IL-17F alleles and genotypes with COVID-19 (P=0.309, P=0.138, respectively). Moreover, no significant difference in the IL-17F genotypes was observed between non-survivors and survivors (P=0.482). In the multivariate analysis, the participants with the following characteristics had 17.7-, 11.2-, 8-, and 17.9-fold higher odds of exhibiting in-hospital mortality, respectively: (1) hypertension, (2) age of >57 years, (3) WBC count of >12.6 × 10³/mm³, and (4) D-dimer of >0.9 ng/ml. The ROC curve analysis showed that IL-17 at a cutoff point of >46 pg/ml was a perfect discriminator of COVID-19 patients from control subjects (AUC = 1.0).

Conclusion

The findings indicate that the IL-17F H161R variant does not influence the risk of COVID-19. However, the IL-17 level is a perfect discriminator of COVID-19 infection. Hypertension, age of >57 years, white blood cell count of >12.6 × 10³/mm³, and D-dimer of >0.9 ng/ml are the independent predictors for death among COVID-19 patients.

SUBMITTER: El-Desoky MM

PROVIDER: S-EPMC9633175 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Association of Interleukin-17F Polymorphism and Mortality Predictors with the Risk of COVID-19.

El-Desoky Manal M MM Tharwat Samar S Mostafa Nora N Hewidy Asem A AA Elmorsey Rehab A RA Abdelhafez Mona S MS El-Ashry Amira H AH Elhendawi Mona M MM Fathy Aya Ahmed AA Hisham Fatma Azzahraa FA

International journal of clinical practice 20221027

<h4>Background</h4>Th-17 cells, a proinflammatory subset of CD4 T lymphocytes, have been suggested as a possible cause of coronavirus disease-19 (COVID-19)-related immunological injuries. The aim of this study was to investigate the relationship between IL-17F (rs763780) polymorphism and the susceptibility to and outcomes of COVID-19 infection and to determine the clinical and laboratory predictors of COVID-19 death.<h4>Methods</h4>This case-control study included 132 COVID-19 patients and 135 h ...[more]

PMID: 36349054

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Project description:IntroductionPatients with end-stage kidney disease face a higher risk of severe outcomes from SARS-CoV-2 infection. Moreover, it is not well known to what extent potentially modifiable risk factors contribute to mortality risk. In this historical cohort study, we investigated the incidence and risk factors for 30-day mortality among hemodialysis patients with SARS-CoV-2 infection treated in the European Fresenius Medical Care NephroCare network using conventional and machine learning techniques.MethodsWe included adult hemodialysis patients with the first documented SARS-CoV-2 infection between February 1, 2020, and March 31, 2021, registered in the clinical database. The index date for the analysis was the first SARS-CoV-2 suspicion date. Patients were followed for up to 30 days until April 30, 2021. Demographics, comorbidities, and various modifiable risk factors, expressed as continuous parameters and as key performance indicators (KPIs), were considered to tap multiple dimensions including hemodynamic control, nutritional state, and mineral metabolism in the 6 months before the index date. We used logistic regression (LR) and XGBoost models to assess risk factors for 30-day mortality.ResultsWe included 9,211 patients (age 65.4 ± 13.7 years, dialysis vintage 4.2 ± 3.7 years) eligible for the study. The 30-day mortality rate was 20.8%. In LR models, several potentially modifiable factors were associated with higher mortality: body mass index (BMI) 30-40 kg/m2 (OR: 1.28, CI: 1.10-1.50), single-pool Kt/V (OR off-target vs on-target: 1.19, CI: 1.02-1.38), overhydration (OR: 1.15, CI: 1.01-1.32), and both low (<2.5 mg/dl) and high (≥5.5 mg/dl) serum phosphate levels (OR: 1.52, CI: 1.07-2.16 and OR: 1.17, CI: 1.01-1.35). On-line hemodiafiltration was protective in the model using KPIs (OR: 0.86, CI: 0.76-0.97). SHapley Additive exPlanations analysis in XGBoost models shows a high influence on prediction for several modifiable factors as well, including inflammatory parameters, high BMI, and fluid overload. In both LR and XGBoost models, age, gender, and comorbidities were strongly associated with mortality.ConclusionBoth conventional and machine learning techniques showed that KPIs and modifiable risk factors in different dimensions ascertained 6 months before the COVID-19 suspicion date were associated with 30-day COVID-19-related mortality. Our results suggest that adequate dialysis and achieving KPI targets remain of major importance during the COVID-19 pandemic as well.

Dataset Information

Association of Interleukin-17F Polymorphism and Mortality Predictors with the Risk of COVID-19.

Background

Methods

Results

Conclusion

Publications

Association of Interleukin-17F Polymorphism and Mortality Predictors with the Risk of COVID-19.

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