Circulating miRNAs in sepsis—A network under attack: An in-silico prediction of the potential existence of miRNA sponges in sepsis

Abstract

Biomarkers based on the molecular mechanism of sepsis are important for timely diagnosis and treatment. A large panel of small non-coding microRNAs was reported to modulate the immune response in sepsis but have not been tested in clinical practice. Large-scale identification of microRNA networks in sepsis might reveal a new biological mechanism that can be also targeted by gene therapy. Therefore, the main objective of this study is to perform a comparison of the miRNA network between septic patients and healthy controls. We used the previously measured levels of expression of 16 different circulating human and viral microRNAs in plasma from 99 septic patients and 53 healthy controls. We used three different computational methods to find correlations between the expressions of microRNAs and to build microRNA networks for the two categories, septic patients and healthy controls. We found that the microRNA network of the septic patients is significantly less connected when compared to miRNA network of the healthy controls (21 edges vs 52 edges, P < 0.0001). We hypothesize that several microRNAs (miR-16, miR-29a, miR-146, miR-155, and miR-182) are being sponged in sepsis explaining the loss of connection in the septic patient miRNA network. This was specific for sepsis, as it did not occur in other conditions characterized by an increased inflammatory response such as in post-surgery patients. Using several target prediction instruments, we predicted potential common sponges for the miRNA network in sepsis from several signaling pathways. Understanding the dynamics of miRNA network in sepsis is useful to explain the molecular pathophysiology of sepsis and for designing therapeutic strategies that target essential components of the immune response pathways.

Exosomal lncRNAs as new players in cell-to-cell communication

“…The same phenomenon has been observed in the case of microRNAs (63) and circulating proteins (64). One possible solution to overcome this issue of low specificity is to analyze more than one circulating molecule and build networks with direct and indirect interactions between the molecules (65,66). Another solution is to integrate the membrane proteins of exosomes in the diagnostic algorithm.…”

miR-543 regulates the epigenetic landscape of myelofibrosis by targeting TET1 and TET2

“…As a second approach for identifying the functionally most relevant miRNAs among the 23 found to be differentially expressed by microarray, we built an expression network for these miRNAs (37). This represents a high-level correlation between the miRNA expression in a given group of patients and is composed of nodes (the miRNAs) and of edges (high correlations between the expression of 2 miRNAs) (38,39). The miRNA network of nonresponders is far more connected compared with responders ( Figure 1C): it contains 104 edges, being a well-connected network with 14 nodes with over 10 edges each (nodes with high node connectivity, 0.4783-0.6087).…”

LncRNA KCNQ1OT1 attenuates sepsis-induced myocardial injury via regulating miR-192-5p/XIAP axis

“…11 Reports have denoted that miRNAs participate in the progression of sepsis. 12,13 Researches have suggested that miR-192-5p was diminished in some tumors such as lung cancer, bladder carcinoma, and so on. 14,15 Instead, miR-192-5p function in the pathophysiological process of sepsis needs further exploration.…”