초록 열기/닫기 버튼
Objectives: Except the known risk factors for stroke, few studies have identified novel metabolic markers that could effectively detect stroke at an early stage. In this study, we explored the dose-response relationship between serum metabolites and the incidence of stroke. Methods: We studied 213 adults in the Korean Cancer Prevention Study-II (KCPS-II) biobank and estimated dose-response relationship between serum metabolites and stroke (42 cases and 171 controls). Three serum metabolites (Acetylcholine, HexadecylAcetylGlycerol, and 1-acetyl-2-formyl-sn-glycero-3-phosphocholine) were used in this study. The analysis included (1) exploratory nonlinear analysis, (2) estimation of flexion points and slopes at below and above the points. In the model to estimate risk of incidence of stroke, we controlled for conventional risk factors such as age, sex, systolic blood pressure, type 2 diabetes, triglyceride, and smoking status. Results: The relationship between incidence of stroke and log-transformed 1-acetyl-2-formyl-sn-glycero-3-phosphocholine was non-linear with flexion point around intensity score of 8.8, whereas other metabolites, log-transformed Acetylcholine and HexadecylAcetylGlycerol, showed negative linear patterns. Conclusions: The study suggests that metabolic markers are associated with incidence of stroke, particularly, at or above the flexion point. The study result may contribute to developing a novel system for precise stroke prediction.
