Identificação de genes diferencialmente expressos em pacientes com sepse e a correlação com o perfil inflamatório: análise in silico de potenciais biomarcadores

Abstract

Introduction: Sepsis is a global public health problem and represents the leading cause of morbidity and mortality worldwide in non-cardiac intensive care units. The incidence and mortality of the sepsis are still high, and has a great economic and social impact. Despite all the dedication to a more thorough investigation in order to diagnose and precocious and accurate prognosis in recent decades, this approach remains a considerable and growing challenge to health care. In this context of the development of quick, accessible and suitable diagnostic tools to improve sepsis identification, prevention and treatment, the use of differentially expressed genes (GDE) as potential biomarkers in the diagnosis and prognosis of sepsis. Therefore, the objective of this research was to study the expression profile of genes and their correlation with intracellular pathways modulated by cytokines and growth factors associated with sepsis progression and severity. Methods & Results: After survey of publicly available databases in NCBI Geo DataSet, three array expression data sets were later selected, which met the inclusion criteria of this study the GSE12624 (control with n = 36 and complicated by sepsis with n = 34), GSE131761 (a control group with n = 15 samples, a septic shock group with n = 81 samples.) and GSE69063 (patients with sepsis n = 19 samples and control n = 11 samples). The GDE were chosen that had a p -value <0.05 and whose expression had a fold change less than -1.1 or larger than +1.1. The genes were analyzed according to the Enrichr road enrichment program to verify that the gene expression of individuals is consistent with the studied disease. Soon after a network of interactions was built between the genes through the String program. Ontology analysis of the main intracellular pathways had significantly increased expression. Through the VENN diagram, five differentially expressed genes present in the three studies ARG1, RPSKA5, HAPGD, DAAM2 and PCOLCE2 were identified in the three studies. These five genes were analyzed in the string. A network of interactions was built between genes through this program. The analysis of the genes evaluated regarding the sensitivity and specificity based on the signal intensity of each sample through the SPSS 20.0 statistical tool. Conclusion: ARG1, HAPGD, DAAM2 and PCOLCE2 genes are involved in several sepsis -related intracellular pathways and have had good specificity and sensitivity. These results contribute to understanding the role of these genes in the sepsis and will help build a signature profile for early diagnosis and precise prognostic disease.