Plasma glial fibrillary acidic protein as a biomarker of disease progression in Parkinson’s disease: a prospective cohort study

Abstract

BackgroundReactive astrogliosis has been demonstrated to have a role in Parkinson’s disease (PD); however, astrocyte-specific plasma glial fibrillary acidic protein (GFAP)’s correlation with PD progression remains unknown. We aimed to determine whether plasma GFAP can monitor and predict PD progression.MethodsA total of 184 patients with PD and 95 healthy controls (HCs) were included in this prospective cohort study and followed-up for 5 years. Plasma GFAP, amyloid-beta (Aβ), p-tau181, and neurofilament light chain (NfL) were measured at baseline and at 1- and 2-year follow-ups. Motor and non-motor symptoms, activities of daily living, global cognitive function, executive function, and disease stage were evaluated using the Unified Parkinson’s Disease Rating Scale (UPDRS) part III, UPDRS-I, UPDRS-II, Montreal Cognitive Assessment (MoCA), Frontal Assessment Battery (FAB), and Hoehn and Yahr (H&Y) scales at each visit, respectively.ResultsPlasma GFAP levels were higher in patients with PD (mean [SD]: 69.80 [36.18], pg/mL) compared to HCs (mean [SD]: 57.89 [23.54], pg/mL). Higher levels of GFAP were observed in female and older PD patients. The adjusted linear mixed-effects models showed that plasma GFAP levels were significantly associated with UPDRS-I scores (β: 0.006, 95% CI [0.001–0.011], p = 0.027). Higher baseline plasma GFAP correlated with faster increase in UPDRS-I (β: 0.237, 95% CI [0.055–0.419], p = 0.011) and UPDRS-III (β: 0.676, 95% CI [0.023–1.330], p = 0.043) scores and H&Y stage (β: 0.098, 95% CI [0.047–0.149], p < 0.001) and faster decrease in MoCA (β: − 0.501, 95% CI [− 0.768 to − 0.234], p < 0.001) and FAB scores (β: − 0.358, 95% CI [− 0.587 to − 0.129], p = 0.002). Higher baseline plasma GFAP predicted a more rapid progression to postural instability (hazard ratio: 1.009, 95% CI [1.001–1.017], p = 0.033).ConclusionsPlasma GFAP might be a potential biomarker for monitoring and predicting disease progression in PD.