LC-MS-based urine metabolomics analysis of chronic subdural hematoma for biomarker discovery.

Abstract

Chronic subdural hematoma (CSDH) is one of the most common neurosurgical diseases with atypical manifestations. The aim of this study was to utilize urine metabolomics to explore potential biomarkers for the diagnosis and prognosis of CSDH. Seventy-seven healthy controls and ninety-two patients with CSDH were enrolled in our study. In total, 261 urine samples divided into the discovery group and validation group were analyzed by LC-MS. The statistical analysis and functional annotation were applied to discover potential biomarker panels and altered metabolic pathways. A total of 53 differential metabolites were identified in this study. And the urinary metabolic profiles showed apparent separation between patients and controls. Further functional annotation showed that the differential metabolites were associated with lipid metabolism, fatty acid metabolism, amino acid metabolism, biotin metabolism, steroid hormone biosynthesis, and pentose and glucuronate interconversions. Moreover, one panel of Capryloylglycine, cis-5-Octenoic acid, Ethisterone, and 5,6-DiHETE showed good predictive performance in the diagnosis of CSDH, with an AUC of 0.89 in discovery group and an AUC of 0.822 in validation group. Another five metabolites (Trilobinol, 3'-Hydroxyropivacaine, Ethisterone, Arginyl-Proline, 5-alpha-Dihydrotestosterone glucuronide) showed the levels of them returned to a healthy state after surgery, showing good possibility to monitor the recovery of CSDH patients. The findings of the study revealed urine metabolomic differences between CSDH and controls. The potentially diagnostic and prognostic biomarker panels of urine metabolites were established, and functional analysis demonstrated deeper metabolic disorders of CSDH, which might conduce to improve early diagnose of CSDH clinically.