The project aims to identify differentially expressed proteins that could be of biomarker value for patients with reversible cerebral vasoconstriction syndrome (RCVS). An RCVS-CSF spectral library resource was established from DDA/DIA analysis of cerebrospinal fluids of 21 RCVS patients and 20 sex-age-matched controls. Personalized RCVS-CSF proteomic profiles from patients and controls revealed alterations in the complement system, adhesion molecule, and extracellular matrix which might contribute to the disruption of the blood-brain barrier. The differentially expressed proteins within the patient cohorts, nominated potential biomarker candidates, and the protein signature suggested by machine learning techniques may provide insights into the unknown molecular understanding of the devastating disease.