Identification of a predictive multiplex biomarker of delayed cerebral ischemia and early metabolic deregulation after aneurysmal subarachnoid haemorrhage based on metabolomics and lipidomics

Abstract

Abstract BACKGROUND. Delayed cerebral ischaemia (DCI) following aneurysmal subarachnoid haemorrhage (aSAH) is a major cause of complications and death. Here we set out to identify high-performance predictive biomarkers of DCI and its underlying metabolic disruptions using metabolomics and lipidomics approaches. METHODS. This single-centre retrospective observational study enrolled 61 consecutive patients with severe aSAH requiring external ventricular drainage between 2013 and 2016, among them 22 experienced a DCI. Blood and cerebrospinal fluid (CSF) were sampled within the first 24 h after admission. We carried out LC-MS/MS-based plasma and CSF metabolomic and lipidomic profiling together with total fatty acids analysis. RESULTS. We identified a panel of 20 metabolites that together showed high predictive performance for DCI (area under the receiver operating characteristic curve: 0.968). This panel of metabolites included lactate, cotinine, salicylate, 6 phosphatidylcholines, and 4 sphingomyelins. Early biological disruptions that might explain the subsequent DCI found systemic hypoxia driven mainly by higher blood lactate, arginine and proline metabolism likely associated to vascular NO, dysregulation of the citric acid cycle in the brain, defective systemic energy metabolism and disrupted ceramide/sphingolipid metabolism. We also unexpectedly found a potential influence of gut microbiota on the onset of DCI. CONCLUSION. We identified a predictive metabolomic/lipidomic signature of further DCI in aSAH patients at admission to a NeuroCritical Care Unit. This signature is associated with significant systemic and cerebral biological dysregulations and reveal a potential link between DCI and gut microbiota. We conclude that targeting early peripheral hypoxia could help in preventing DCI. Clinical trial registration Clinicaltrials.gov identifier: NCT02397759