Impaired liver function is one of the complications of acute cholecystitis, and improper treatment can lead to acute liver failure and even death. Therefore, timely evaluation of liver function provides a reliable basis for clinical diagnosis and treatment. However, no biomarkers have been identified to predict liver injury in patients with cholecystitis.
Deep sequencing was used to analyze microRNA expression profiles in plasma exosomes from cholecystitis patients. Sequencing results were confirmed by quantitative real-time PCR (RT-qPCR).
The findings demonstrated that biomarker panels consisting of multiple exosome-derived miRNAs improved the sensitivity of cholecystitis prediction. Further analysis revealed that hsa-miR-4440 and hsa-miR-6808-5p could specifically suggest the risk of early liver injury in patients with cholecystitis, with AUROCs of 0.895(95% CI: 0.764 to 1.025) and 0.804(95% CI: 0.6495 to 0.9589) respectively. Additionally, our GWAS analysis based on the results published by the FinnGen Biobank found that ALT was limitedly associated with cholecystitis, demonstrating the importance of our research into novel predictive biomarkers of early liver injury.
Biomarker panels composed of multiple exosome-derived miRNAs could accurately predict cholecystitis. Furthermore, hsa-miR-4440 and hsa-miR-6808-5p could serve as early predictors of liver injury in patients with cholecystitis, thereby aiding in the selection of clinical treatment modalities.