Serum microRNA signatures identified by Solexa sequencing predict sepsis patients' mortality: a prospective observational study.
BACKGROUND
Sepsis is the leading cause of death in Intensive Care Units. Novel sepsis biomarkers and targets for treatment are needed to improve mortality from sepsis. MicroRNAs (miRNAs) have recently been used as finger prints for sepsis, and our goal in this prospective study was to investigate if serum miRNAs identified in genome-wide scans could predict sepsis mortality.


RESULTS
We enrolled 214 sepsis patients (117 survivors and 97 non-survivors based on 28-day mortality). Solexa sequencing followed by quantitative reverse transcriptase polymerase chain reaction assays was used to test for differences in the levels of miRNAs between survivors and non-survivors. miR-223, miR-15a, miR-16, miR-122, miR-193*, and miR-483-5p were significantly differentially expressed. Receiver operating characteristic curves were generated and the areas under the curve (AUC) for these six miRNAs for predicting sepsis mortality ranged from 0.610 (95%CI: 0.523-0.697) to 0.790 (95%CI: 0.719-0.861). Logistic regression analysis showed that sepsis stage, Sequential Organ Failure Assessment scores, Acute Physiology and Chronic Health Evaluation II scores, miR-15a, miR-16, miR-193b*, and miR-483-5p were associated with death from sepsis. An analysis was done using these seven variables combined. The AUC for these combined variables' predictive probability was 0.953 (95% CI: 0.923-0.983), which was much higher than the AUCs for Acute Physiology and Chronic Health Evaluation II scores (0.782; 95% CI: 0.712-0.851), Sequential Organ Failure Assessment scores (0.752; 95% CI: 0.672-0.832), and procalcitonin levels (0.689; 95% CI: 0.611-0.784). With a cut-off point of 0.550, the predictive value of the seven variables had a sensitivity of 88.5% and a specificity of 90.4%. Additionally, miR-193b* had the highest odds ratio for sepsis mortality of 9.23 (95% CI: 1.20-71.16).


CONCLUSIONS
Six serum miRNA's were identified as prognostic predictors for sepsis patients.


BACKGROUND
ClinicalTrials.gov NCT01207531.
Department of Respiratory Medicine, Hainan Branch of Chinese PLA General Hospital, Sanya, Hainan Province, China.
Huijuan
H
Wang
Pengjun
P
Zhang
Weijun
W
Chen
Dan
D
Feng
Yanhong
Y
Jia
Lixin
L
Xie
D000328:Adult; D000368:Aged; D019540:Area Under Curve; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D035683:MicroRNAs / Q000235:genetics; D008875:Middle Aged; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D018805:Sepsis / Q000235:genetics / Q000401:mortality*
D035683:MicroRNAs