Affiliations: [a] Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| [b] Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| [c] Department of Medical Imaging, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
Correspondence:
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Correspondence to: Dr. Chin-Hsien Lin, No.7 Chuang-Shan South Road, Department of Neurology, National Taiwan
University Hospital, Taipei 100, Taiwan. Tel.: +886 2 23123456/Ext. 65335; Fax: +886 2 23418395;
E-mail: [email protected].
Abstract: Background/Objective:Easily accessible biomarkers are crucial for disease-modifying clinical trials in patients with Parkinson’s disease (PD). We investigated integrated plasma and neuroimaging biomarkers correlating with motor and cognitive severity in PD patients. Methods:This cross-sectional study enrolled 170 participants (12 controls and 158 PD patients). Plasma α-synuclein and neurofilament light chain (NfL) level, and global and regional cortical thickness (CTh) on brain MRI were analyzed to predict advanced motor stage (Hoehn & Yahr stage ≥3), and PD dementia (PDD, MMSE score <26). Results:Plasma α-synuclein and NfL levels were higher in PD patients than controls (both P < 0.0001 for α-synuclein and NfL). Plasma NfL levels were significantly elevated in patients with advanced motor stage (P = 0.008) or PDD; α-synuclein was elevated in the advanced motor stage group. Global CTh was thinner in patients with PDD than controls (2.33±0.19 mm vs 2.43±0.14 mm, P = 0.06). Among PD patients, higher α-synuclein was associated with thinner limbic CTh, whereas higher NfL was associated with thinner temporal CTh and insular CTh. The accuracy of predicting advanced motor stage using age and sex alone (area under the curve [AUC] 0.63) was significantly improved by the addition of plasma α-synuclein and NfL, and temporal and insula CTh (full model, AUC 0.77, P = 0.004). The accuracy of predicting PDD using age and sex alone (AUC 0.82) increased by incorporating plasma α-synuclein and NfL, and temporal and insula CTh as full model (AUC 0.87, P = 0.047). Conclusions:Integrated plasma and neuroimaging biomarkers reflect both motor and cognitive aspects of PD severity.
