George N. Dalekos
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Research Interests
George N. Dalekos has a total of 48 co-authors. Here are the top co-authors by number of shared publications:
- Nikolaos K. Gatselis
Department of Medicine & Research Laboratory of Internal Medicine, General University Hospital of Larissa, European Reference Network on Hepatological Diseases, Larissa, Greece
4 shared publications - Vasiliki Lygoura
Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, Full Member of the European Reference Network on Hepatological Diseases (ERN RARE-LIVER), General University Hospital of Larissa, 41110 Larissa, Greece
3 shared publications - Christos Hadjichristodoulou
Laboratory of Hygiene and Epidemiology, Faculty of Medicine, University of Thessaly
2 shared publications - Elli Botsfari
Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece
2 shared publications - Evangelia Asvestopoulou
Department of Immunology & Histocompatibility, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece
2 shared publications - Evangelos Bakaros
Department of Immunology & Histocompatibility, School of Medicine, University of Thessaly, 41222 Larissa, Greece
2 shared publications
Latest Publications
- Open Access
Innate Immune Gene Polymorphisms and COVID-19 Prognosis
COVID-19 is characterized by a heterogeneous clinical presentation and prognosis. Risk factors contributing to the development of severe disease include old age and the presence of comorbidities. However, the genetic background of the host has also been recognized as an important determinant of disease prognosis. Considering the pivotal role of innate immunity in the control of SARS-CoV-2 infection, we analyzed the possible contribution of several innate immune gene polymorphisms (including TLR2-rs5743708, TLR4-rs4986790, TLR4-rs4986791, CD14-rs2569190, CARD8-rs1834481, IL18-rs2043211, and CD40-rs1883832) in disease severity and prognosis. A total of 249 individuals were enrolled and further divided into five (5) groups, according to the clinical progression scale provided by the World Health Organization (WHO) (asymptomatic, mild, moderate, severe, and critical). We identified that elderly patients with obesity and/or diabetes mellitus were more susceptible to developing pneumonia and respiratory distress syndrome after SARS-CoV-2 infection, while the IL18-rs1834481 polymorphism was an independent risk factor for developing pneumonia. Moreover, individuals carrying either the TLR2-rs5743708 or the TLR4-rs4986791 polymorphisms exhibited a 3.6- and 2.5-fold increased probability for developing pneumonia and a more severe disease, respectively. Our data support the notion that the host’s genetic background can significantly affect COVID-19 clinical phenotype, also suggesting that the IL18-rs1834481, TLR2-rs5743708, and TLR4-rs4986791 polymorphisms may be used as molecular predictors of COVID-19 clinical phenotype.
Open AccessInnate Immune Gene Polymorphisms and COVID-19 Prognosis
COVID-19 is characterized by a heterogeneous clinical presentation and prognosis. Risk factors contributing to the development of severe disease include old age and the presence of comorbidities. However, the genetic background of the host has also been recognized as an important determinant of disease prognosis. Considering the pivotal role of innate immunity in the control of SARS-CoV-2 infection, we analyzed the possible contribution of several innate immune gene polymorphisms (including TLR2-rs5743708, TLR4-rs4986790, TLR4-rs4986791, CD14-rs2569190, CARD8-rs1834481, IL18-rs2043211, and CD40-rs1883832) in disease severity and prognosis. A total of 249 individuals were enrolled and further divided into five (5) groups, according to the clinical progression scale provided by the World Health Organization (WHO) (asymptomatic, mild, moderate, severe, and critical). We identified that elderly patients with obesity and/or diabetes mellitus were more susceptible to developing pneumonia and respiratory distress syndrome after SARS-CoV-2 infection, while the IL18-rs1834481 polymorphism was an independent risk factor for developing pneumonia. Moreover, individuals carrying either the TLR2-rs5743708 or the TLR4-rs4986791 polymorphisms exhibited a 3.6- and 2.5-fold increased probability for developing pneumonia and a more severe disease, respectively. Our data support the notion that the host’s genetic background can significantly affect COVID-19 clinical phenotype, also suggesting that the IL18-rs1834481, TLR2-rs5743708, and TLR4-rs4986791 polymorphisms may be used as molecular predictors of COVID-19 clinical phenotype.
- Open Access
- 8 August 2023
- Published by MDPI AG in Preprints.org
Innate Immune Gene Polymorphisms and COVID‐19 Prognosis
COVID-19 is characterized by a heterogeneous clinical presentation and prognosis. Risk factors contributing to the development of severe disease include old age and the presence of comorbidities. However, the genetic background of the host has also been recognized as an important determinant of disease prognosis. Considering the pivotal role of innate immunity in the control of SARS-CoV-2 infection, we analyzed the possible contribution of several innate immune gene polymorphisms (including TLR2-rs5743708, TLR4-rs4986790, TLR4-rs4986791, CD14-rs2569190, CARD8-rs1834481, IL18-rs2043211 and CD40-rs1883832) in disease severity and prognosis. A total of 249 individuals were enrolled and further divided into five (5) groups, according to the clinical progression scale provided by the World Health Organization (WHO) (asymptomatic, mild, moderate, severe and critical). We identified that elderly patients with obesity and/or diabetes mellitus were more susceptible to developing pneumonia and respiratory distress syndrome after SARS-CoV-2 infection, while the IL18-rs1834481 polymorphism was an independent risk factor for developing pneumonia. Moreover, individuals carrying either the TLR2-rs5743708 or the TLR4-rs4986791 polymorphisms exhibited a 3.6- and 2.5-fold increased probability for developing pneumonia and a more severe disease, respectively. Our data supports the notion that the host’s genetic background can significantly affect COVID-19 clinical phenotype, also suggesting that the IL18-rs1834481, TLR2-rs5743708 and TLR4-rs4986791 polymorphisms may be used as molecular predictors of COVID-19 clinical phenotype.
- 8 August 2023
- Published by MDPI AG in Preprints.org
Open AccessInnate Immune Gene Polymorphisms and COVID‐19 Prognosis
COVID-19 is characterized by a heterogeneous clinical presentation and prognosis. Risk factors contributing to the development of severe disease include old age and the presence of comorbidities. However, the genetic background of the host has also been recognized as an important determinant of disease prognosis. Considering the pivotal role of innate immunity in the control of SARS-CoV-2 infection, we analyzed the possible contribution of several innate immune gene polymorphisms (including TLR2-rs5743708, TLR4-rs4986790, TLR4-rs4986791, CD14-rs2569190, CARD8-rs1834481, IL18-rs2043211 and CD40-rs1883832) in disease severity and prognosis. A total of 249 individuals were enrolled and further divided into five (5) groups, according to the clinical progression scale provided by the World Health Organization (WHO) (asymptomatic, mild, moderate, severe and critical). We identified that elderly patients with obesity and/or diabetes mellitus were more susceptible to developing pneumonia and respiratory distress syndrome after SARS-CoV-2 infection, while the IL18-rs1834481 polymorphism was an independent risk factor for developing pneumonia. Moreover, individuals carrying either the TLR2-rs5743708 or the TLR4-rs4986791 polymorphisms exhibited a 3.6- and 2.5-fold increased probability for developing pneumonia and a more severe disease, respectively. Our data supports the notion that the host’s genetic background can significantly affect COVID-19 clinical phenotype, also suggesting that the IL18-rs1834481, TLR2-rs5743708 and TLR4-rs4986791 polymorphisms may be used as molecular predictors of COVID-19 clinical phenotype.
- Open Access
Soluble IL-2R Levels at Baseline Predict the Development of Severe Respiratory Failure and Mortality in COVID-19 Patients
Risk stratification of coronavirus disease-19 (COVID-19) patients by simple markers is critical to guide treatment. We studied the predictive value of soluble interleukin-2 receptor (sIL-2R) for the early identification of patients at risk of developing severe clinical outcomes. sIL-2R levels were measured in 197 patients (60.9% males; median age 61 years; moderate disease, n = 65; severe, n = 132, intubated and/or died, n = 42). All patients received combined immunotherapies (anakinra ± corticosteroids ± intravenous immunoglobulin ± tocilizumab) according to our local treatment algorithm. The endpoint was the composite event of intubation due to severe respiratory failure (SRF) or mortality. Median (interquartile range) sIL-2R levels were significantly higher in patients with severe disease, compared with those with moderate disease (6 (6.2) vs. 5.2 (3.4) ng/mL, p = 0.017). sIL-2R was the strongest laboratory predictive factor for intubation/death (hazard ratio 1.749, 95%CI 1.041–2.939, p = 0.035) after adjustment for other known risk factors. Youden’s index revealed optimal sIL-2R cut-off for predicting intubation/death at 9 ng/mL (sensitivity: 67%; specificity: 86%; positive and negative predictive value: 57% and 91%, respectively). Delta sIL-2R between the day of event or discharge minus admission date was higher in patients that intubated/died than in those who did not experience an event (2.91 (10.42) vs. 0.44 (2.88) ng/mL; p = 0.08)). sIL-2R on admission and its dynamic changes during follow-up may reflect disease severity and predict the development of SRF and mortality.
Open AccessSoluble IL-2R Levels at Baseline Predict the Development of Severe Respiratory Failure and Mortality in COVID-19 Patients
Risk stratification of coronavirus disease-19 (COVID-19) patients by simple markers is critical to guide treatment. We studied the predictive value of soluble interleukin-2 receptor (sIL-2R) for the early identification of patients at risk of developing severe clinical outcomes. sIL-2R levels were measured in 197 patients (60.9% males; median age 61 years; moderate disease, n = 65; severe, n = 132, intubated and/or died, n = 42). All patients received combined immunotherapies (anakinra ± corticosteroids ± intravenous immunoglobulin ± tocilizumab) according to our local treatment algorithm. The endpoint was the composite event of intubation due to severe respiratory failure (SRF) or mortality. Median (interquartile range) sIL-2R levels were significantly higher in patients with severe disease, compared with those with moderate disease (6 (6.2) vs. 5.2 (3.4) ng/mL, p = 0.017). sIL-2R was the strongest laboratory predictive factor for intubation/death (hazard ratio 1.749, 95%CI 1.041–2.939, p = 0.035) after adjustment for other known risk factors. Youden’s index revealed optimal sIL-2R cut-off for predicting intubation/death at 9 ng/mL (sensitivity: 67%; specificity: 86%; positive and negative predictive value: 57% and 91%, respectively). Delta sIL-2R between the day of event or discharge minus admission date was higher in patients that intubated/died than in those who did not experience an event (2.91 (10.42) vs. 0.44 (2.88) ng/mL; p = 0.08)). sIL-2R on admission and its dynamic changes during follow-up may reflect disease severity and predict the development of SRF and mortality.
- Open Access
- 13 January 2022
- Published by MDPI AG in Microorganisms
- Vol. 10 (1) , 159
Plethora of Resistance Genes in Carbapenem-Resistant Gram-Negative Bacteria in Greece: No End to a Continuous Genetic Evolution
Carbapenem-resistant Gram-negative bacteria are a public health threat that requires urgent action. The fact that these pathogens commonly also harbor resistance mechanisms for several other antimicrobial classes further reduces patient treatment options. The present study aimed to provide information regarding the multidrug resistance genetic background of carbapenem-resistant Gram-negative bacteria in Central Greece. Strains from a tertiary care hospital, collected during routine practice, were characterized using a DNA microarray-based assay. Various different resistance determinants for carbapenems, other beta-lactams, aminoglycosides, quinolones, trimethoprim, sulfonamides and macrolides were detected among isolates of the same sequence type. Eighteen different multidrug resistance genomic profiles were identified among the twenty-four K. pneumoniae ST258, seven different profiles among the eight K. pneumoniae ST11, four profiles among the six A. baumannii ST409 and two among the three K. oxytoca. This report describes the multidrug resistance genomic background of carbapenem-resistant Gram-negative bacteria from a tertiary care hospital in Central Greece, providing evidence of their continuous genetic evolution.
- 13 January 2022
- Published by MDPI AG in Microorganisms
- Vol. 10 (1) , 159
Open AccessPlethora of Resistance Genes in Carbapenem-Resistant Gram-Negative Bacteria in Greece: No End to a Continuous Genetic Evolution
Carbapenem-resistant Gram-negative bacteria are a public health threat that requires urgent action. The fact that these pathogens commonly also harbor resistance mechanisms for several other antimicrobial classes further reduces patient treatment options. The present study aimed to provide information regarding the multidrug resistance genetic background of carbapenem-resistant Gram-negative bacteria in Central Greece. Strains from a tertiary care hospital, collected during routine practice, were characterized using a DNA microarray-based assay. Various different resistance determinants for carbapenems, other beta-lactams, aminoglycosides, quinolones, trimethoprim, sulfonamides and macrolides were detected among isolates of the same sequence type. Eighteen different multidrug resistance genomic profiles were identified among the twenty-four K. pneumoniae ST258, seven different profiles among the eight K. pneumoniae ST11, four profiles among the six A. baumannii ST409 and two among the three K. oxytoca. This report describes the multidrug resistance genomic background of carbapenem-resistant Gram-negative bacteria from a tertiary care hospital in Central Greece, providing evidence of their continuous genetic evolution.