Objective To determine whether CSF biomarkers can be used as a predictor of freezing of gait (FOG) in Parkinson disease (PD) and to investigate the predictive value of clinical, dopamine transporter (DAT) imaging, and CSF parameters both separately and in combination.
Methods This study using the PPMI data included 393 patients with newly diagnosed PD without FOG at baseline. We evaluated CSF for β-amyloid 1-42 (Aβ42), α-synuclein, total tau, phosphorylated tau181, and the calculated ratio of Aβ42 to total tau at baseline. Demographic and clinical data and DAT imaging results were also investigated. Cox proportional-hazards regression analyses were performed to identify the factors predictive of FOG. From these results, we constructed a predictive model for the development of FOG.
Results During a median follow-up of 4.0 years, only Aβ42 among the CSF biomarkers was associated with the development of FOG (hazard ratio 0.997, 95% confidence interval [CI] 0.996–0.999, p = 0.009). Postural instability gait difficulty (PIGD) score, caudate DAT uptake, and, to a lesser extent, male sex, Movement Disorders Society Unified Parkinson's Disease Rating Scale motor score, and Montreal Cognitive Assessment score were also predictive of FOG. The combined model integrating the PIGD score, caudate DAT uptake, and CSF Aβ42 achieved a better discriminative ability (area under the curve 0.755, 95% CI 0.700–0.810) than any factor alone.
Conclusion We found CSF Aβ42 to be a predictor of FOG in patients with early PD. Furthermore, the development of FOG within 4 years after diagnosis of PD can be predicted with acceptable accuracy with our risk model.