Serum levels of microRNA have been proposed as biomarkers in various inflammatory diseases. However, up to now, their clinical relevance in critical illness and sepsis is unclear.
Single-center clinical study.
Fourteen-bed medical ICU of the University Hospital Aachen, university laboratory research unit.
Subjects and Patients:
Experimental sepsis model in C57Bl/6 mice; 223 critically ill patients in comparison with 76 healthy volunteers.
We used the model of cecal pole ligation and puncture for induction of polymicrobial sepsis in mice and measured alterations in serum levels of six different microRNAs with a known function in inflammatory diseases upon induction of septic disease. These results from mice were translated into a large and well-characterized cohort of critically ill patients admitted to the medical ICU.
Measurements and Main Results:
Serum miR-133a was then measured in 223 critically ill patients (138 with sepsis and 85 without sepsis) and 76 controls and associated with disease severity, organ failure, and prognosis. Significant alterations of miR-133a, miR-150, miR-155, and miR-193b* were found in mice after cecal pole ligation and puncture–induced sepsis. Among all regulated microRNAs, miR-133a displayed the most prominent and concordant up-regulation in sepsis, and this microRNA was therefore chosen for further investigation in the human. Here, significantly elevated miR-133a levels were found in critically ill patients at ICU admission, when compared with healthy controls, especially in patients with sepsis. Correlation analyses revealed significant correlations of miR-133a with disease severity, classical markers of inflammation and bacterial infection, and organ failure. Strikingly, high miR-133a levels were predictive for an unfavorable prognosis and represented a strong independent predictor for both ICU and long-term mortality in critically ill patients.
miR-133a serum levels were significantly elevated in critical illness and sepsis. High miR-133a levels were associated with the severity of disease and predicted an unfavorable outcome of critically ill patients.