RT info:eu-repo/semantics/doctoralThesis
T1 Biomarcadores moleculares en la predicción de gravedad en pacientes hospitalizados por COVID-19
A1 Gorgojo Galindo, Óscar
A2 Universidad de Valladolid. Escuela de Doctorado
K1 Biomarcadores moleculares
K1 COVID-19
K1 Biomarker
K1 Biomarcador
K1 Cytokine storm
K1 Tormenta de citoquinas
K1 microRNA
K1 microARN
K1 32 Ciencias Médicas
AB INTRODUCTION: In December 2019, SARS-CoV-2 emerged in China, whose particular characteristics derived in the COVID-19 pandemic, resulting in a major problem for health systems in most countries. Severe cases of COVID-19 are characterized by a hyperproduction of cytokines, caused by an ineffective interferon-mediated response, accompanied by lymphocytopenia and uncoordination between the innate and adaptive response. Evasion of the innate response through virus nonstructural proteins and miRNA, generated by both the virus itself and the host during infection, leads to severe respiratory disease that reduces the chances of survival in the most severe cases.HYPOTHESIS AND OBJECTIVES: In this context, it is hypothesized to describe molecular biomarkers related to the immune response that are important in the prognosis of COVID-19 patients. The main objective is to characterize the cytokine and miRNA profile as possible determinants in the alteration of the immune response in COVID-19 patients.METHODOLOGY: Observational study of patients with positive results of COVID-19 admitted to the Hospital Clínico Universitario de Valladolid (Spain). Patients with other active infections or terminal chronic diseases were not enrolled in the study. From the patient's plasma, on the one hand, the cytokine profile on the first, third and sixth day of admission was characterised using Luminex technology and, on the other hand, the miRNAs from extracellular vesicles were sequenced. Data were analysed using both the statistical package IBM SPSS Statistics Software (SPSS) version 28 and the statistical package R version 4.2.3.RESULTS: Article 1. HGF was the only cytokine that formed part of the multivariate model associated with the risk of intubation or death on the day of admission (OR = 7.38, 95% CI (1.28-42.4), p = 0.025), together with blood group A/B/AB, glycemia, D-dimer, procalcitonin and ferritin. The model was validated by the AUROC method showing an area under the curve of 0.94 with a sensitivity of 91.7% and a specificity of 95% and, on the other hand, by the bootstrapping method. Article 2. Principal component analysis included three groups of cytokines associated with mortality in patients hospitalized for COVID-19. The combination of HGF, MCP-1, IL-18, eotaxin and SCF was significantly elevated in deceased patients, showing an increasing trend, while IL-1α and VEGFA remained constant. Finally, the combination of BDNF, IL-12 and IL-15 was associated with surviving patients. Article 3. Patients with severe COVID-19 showed differential expression of 50 miRNAs derived from extracellular vesicles associated with signaling pathways involved in the inflammatory response and cell adhesion. Specifically, 15 miRNAs were associated with severe cases compared to the control group. Finally, the miRNAs miR-1469 and miR-6124 were significant predictors of mortality with an AUC of 0.94.CONCLUSIONS: (i) HFG constitutes an important biomarker in predicting mortality and severity taking into account glycemia, D-dimer, procalcitonin, ferritin and blood type (ii) COVID-19 patients who remitted show elevated levels of BDNF, IL-12 and IL-15 related to an effective response by T lymphocytes and NK cells, (iii) the cytokines HGF, MCP-1, IL-18, eotaxin and SCF show an increasing trend in COVID-19 patients who died during their admission, while IL-1α and VEGFA remain constant in the first six days of admission, (iv) the miRNAs miR-1469 and miR-6124 are differentially expressed in severe cases and are capable of predicting mortality with high accuracy in patients hospitalized for COVID-19.
YR 2025
FD 2025
LK https://uvadoc.uva.es/handle/10324/79733
UL https://uvadoc.uva.es/handle/10324/79733
LA spa
NO Escuela de Doctorado
DS UVaDOC
RD 18-nov-2025