期刊
SCIENTIFIC REPORTS
卷 12, 期 1, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41598-022-13849-z
关键词
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资金
- British Heart Foundation [RG/13/6/29947, CH/12/1/29419]
- Bristol National Institute for Health Research Cardiovascular Biomedical Research Units
This study found that measuring changes in urinary levels of extracellular vesicles (EVs) and microRNAs (miRs) can predict the onset of acute kidney injury (AKI) in cardiac surgery patients. Pre-operative levels of podocalyxin-positive EVs, urinary particle concentrations, and miR-125a-5p have moderate predictive value for AKI. These findings suggest that urinary EVs and miRs may serve as potential biomarkers for AKI prediction in cardiac surgery patients.
We hypothesised that measuring changes in urinary levels of EV and miR will predict the onset of acute kidney injury in cardiac surgery patients. The study was performed in the cohort of the REVAKI-2 trial. Urine samples were collected before and 24 h after the procedure from 94 cardiac surgery patients. Urinary particle concentrations and size distribution were assessed using NanoSight. EV derivation and levels were measured using flow cytometry. Samples from 10 selected patients were sequenced, and verification was performed with advanced TaqMan assays in samples from all patients. Urinary particle concentrations significantly increased in patients with AKI after surgery, with the percentage of EV positive for CD105 and beta 1-integrin also increasing. Pre-surgery podocalyxin-positive EV were significantly lower in patients with AKI. Their levels correlated with the severity of the injury. Pre-operative miR-125a-5p was expressed at lower levels in urine from patients with AKI when adjusted for urinary creatinine. Levels of miR-10a-5p were lower after surgery in AKI patients and its levels correlated with the severity of the injury. Pre-operative levels of podocalyxin EVs, urinary particle concentrations and miR-125a-5p had moderate AKI predictive value and, in a logistic model together with ICU lactate levels, offered good (AUC = 82%) AKI prediction.
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