Metabolic alterations of peripheral blood immune cells and heterogeneity of neutrophil in intracranial aneurysms patients

Background: Intracranial aneurysms (IAs) represent a severe cerebrovascular disease that can potentially lead to subarachnoid haemorrhage. Previous studies have demonstrated the involvement of peripheral immune cells in the formation and progression of IAs. Nevertheless, the impact of metabolic alterations in peripheral immune cells and changes in neutrophil heterogeneity on the occurrence and progression of IAs remains uncertain. Methods: Single-cell Cytometry by Time-of-Flight (CyTOF) technology was employed to profile the single-cell atlas of peripheral blood mononuclear cells (PBMCs) and polymorphonuclear cells (PMNs) in 72 patients with IAs. In a matched cohort, metabolic shifts in PBMC subsets of IA patients were investigated by contrasting the expression levels of key metabolic enzymes with their respective counterparts in the healthy control group. Simultaneously, compositional differences in peripheral blood PMNs subsets between the two groups were analysed to explore the impact of altered heterogeneity in neutrophils on the initiation and progression of IAs. Furthermore, integrating immune features based on CyTOF analysis and clinical characteristics, we constructed an aneurysm occurrence model and an aneurysm growth model using the random forest method in conjunction with LASSO regression. Results: Different subsets exhibited distinct metabolic characteristics. Overall, PBMCs from patients elevated CD98 expression and increased proliferation. Conversely, CD36 was up-regulated in T cells, B cells and monocytes from the controls but down-regulated in NK and NKT cells. The comparison also revealed differences in the metabolism and function of specific subsets between the two groups. In terms of PMNs, the neutrophil landscape within patients group revealed a pronounced shift towards heightened complexity. Various neutrophil subsets from the IA group generally exhibited lower expression levels of anti-inflammatory functional molecules (IL-4 and IL-10). By integrating clinical and immune features, the constructed aneurysm occurrence model could precisely identify patients with IAs with high prediction accuracy (AUC = 0.987). Furthermore, the aneurysm growth model also exhibited superiority over ELAPSS scores in predicting aneurysm growth (lower prediction errors and out-of-bag errors). Conclusion: These findings enhanced our understanding of peripheral immune cell participation in aneurysm formation and growth from the perspectives of immune metabolism and neutrophil heterogeneity. Moreover, the predictive model based on CyTOF features holds the potential to aid in diagnosing and monitoring the progression of human IAs.