Literature DB >> 31868681

Integrated Plasma and Neuroimaging Biomarkers Associated with Motor and Cognition Severity in Parkinson's Disease.

Chih-Hao Chen1,2, Bo-Ching Lee3, Chin-Hsien Lin1.   

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.

Entities:  

Keywords:  Parkinson’s disease; biomarker; cognitive decline; dementia; neurofilament light zzm321990chain; α-synuclein

Mesh:

Substances:

Year:  2020        PMID: 31868681     DOI: 10.3233/JPD-191766

Source DB:  PubMed          Journal:  J Parkinsons Dis        ISSN: 1877-7171            Impact factor:   5.568


  2 in total

Review 1.  The Key Role of Magnetic Resonance Imaging in the Detection of Neurodegenerative Diseases-Associated Biomarkers: A Review.

Authors:  Ke-Ru Li; An-Guo Wu; Yong Tang; Xiao-Peng He; Chong-Lin Yu; Jian-Ming Wu; Guang-Qiang Hu; Lu Yu
Journal:  Mol Neurobiol       Date:  2022-07-12       Impact factor: 5.682

2.  Prediction of Cognitive Degeneration in Parkinson's Disease Patients Using a Machine Learning Method.

Authors:  Pei-Hao Chen; Ting-Yi Hou; Fang-Yu Cheng; Jin-Siang Shaw
Journal:  Brain Sci       Date:  2022-08-07
  2 in total

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