Moyamoya disease (MMD) is a rare cerebrovascular disease in humans. Although early revascularization can improve symptoms, it cannot reverse the progression of the disease. The current diagnosis still relies on traditional a Digital Subtraction Angiography (DSA) examination, which is invasive and expensive, leading to delayed diagnosis and affecting treatment timing and patient prognosis. The ability to diagnose MMD early and develop personalized treatment plans can significantly improve the prognosis of patients. Here, we have introduced the research on MMD biomarkers. By integrating proteomics and metabolomics data, we have successfully identified over 1700 features from more than 60 serum samples collected at the onset of symptoms in MMD patients. We use multiple computational strategies to interpret complex information in serum, providing a comprehensive perspective for early diagnosis of MMD. Diagnostic ability of our biomarker is significantly better than previous studies, especially when used in combination. In the study of molecular mechanisms, we found that the ferroptosis pathway was significant disruption in MMD patients, which was also confirmed by transcriptomics data. Finally, we validated the metabolites and proteins associated with ferroptosis pathways, as well as the biomarkers screened by machine learning, using another independent MMD cohort. Our research provides important clues for the diagnosis of MMD, and this assay can identify MMD early, thereby promoting stronger monitoring and intervention.