Literature DB >> 35879562

Plasma biomarkers inclusive of α-synuclein/amyloid-beta40 ratio strongly correlate with Mini-Mental State Examination score in Parkinson's disease and predict cognitive impairment.

Daniel Kam Yin Chan1,2,3, Jack Chen4, Ren Fen Chen5, Jayesh Parikh6, Ying Hua Xu4,7,6, Peter A Silburn8, George D Mellick9.   

Abstract

Plasma biomarkers for Parkinson's disease (PD) diagnosis that carry predictive value for cognitive impairment are valuable. We explored the relationship of Mini-Mental State Examination (MMSE) score with plasma biomarkers in PD patients and compared results to vascular dementia (VaD) and normal controls. The predictive accuracy of an individual biomarker on cognitive impairment was evaluated using area under the receiver operating characteristic curve (AUROC), and multivariate logistic regression was applied to evaluate predictive accuracy of biomarkers on cognitive impairment; 178 subjects (41 PD, 31 VaD and 106 normal controls) were included. In multiple linear regression analysis of PD patients, α-synuclein, anti-α-synuclein, α-synuclein/Aβ40 and anti-α-synuclein/Aβ40 were highly predictive of MMSE score in both full model and parsimonious model (R2 = 0.838 and 0.835, respectively) compared to non-significant results in VaD group (R2 = 0.149) and in normal controls (R2 = 0.056). Α-synuclein and anti-α-synuclein/Aβ40 were positively associated with MMSE score, and anti-α-synuclein, α-synuclein/Aβ40 were negatively associated with the MMSE score among PD patients (all Ps < 0.005). In the AUROC analysis, anti-α-synuclein (AUROC = 0.788) and anti-α-synuclein/Aβ40 (AUROC = 0.749) were significant individual predictors of cognitive impairment. In multivariate logistic regression, full model of combined biomarkers showed high accuracy in predicting cognitive impairment (AUROC = 0.890; 95%CI 0.796-0.984) for PD versus controls, as was parsimonious model (AUROC = 0.866; 95%CI 0.764-0.968). In conclusion, simple combination of biomarkers inclusive of α-synuclein/Aβ40 strongly correlates with MMSE score in PD patients versus controls and is highly predictive of cognitive impairment.
© 2022. The Author(s).

Entities:  

Keywords:  Amyloid-beta40; Biomarkers; Cognitive impairment; Mini-Mental State Examination score; Parkinson’s disease; α-synuclein

Year:  2022        PMID: 35879562     DOI: 10.1007/s00415-022-11287-5

Source DB:  PubMed          Journal:  J Neurol        ISSN: 0340-5354            Impact factor:   6.682


  19 in total

1.  Plasma levels of beta-amyloid (1-42) in Alzheimer's disease and mild cognitive impairment.

Authors:  Marzia Pesaresi; Carlo Lovati; Pierluigi Bertora; Enrico Mailland; Daniela Galimberti; Elio Scarpini; Pierluigi Quadri; Gianluigi Forloni; Claudio Mariani
Journal:  Neurobiol Aging       Date:  2006-04-25       Impact factor: 4.673

2.  Association of genetic polymorphisms of claudin-1 with small vessel vascular dementia.

Authors:  Vivek Srinivasan; Nady Braidy; Ying Hua Xu; Peter Xie; Kiran Kancherla; Sashiruben Chandramohan; Eunice Kar Wing Chan; Daniel Ky Chan
Journal:  Clin Exp Pharmacol Physiol       Date:  2017-06       Impact factor: 2.557

3.  Pipeline to gene discovery - Analysing familial Parkinsonism in the Queensland Parkinson's Project.

Authors:  Steven R Bentley; Stephanie Bortnick; Ilaria Guella; Javed Y Fowdar; Peter A Silburn; Stephen A Wood; Matthew J Farrer; George D Mellick
Journal:  Parkinsonism Relat Disord       Date:  2018-01-03       Impact factor: 4.891

Review 4.  Neuropathological alterations in Alzheimer disease.

Authors:  Alberto Serrano-Pozo; Matthew P Frosch; Eliezer Masliah; Bradley T Hyman
Journal:  Cold Spring Harb Perspect Med       Date:  2011-09       Impact factor: 6.915

5.  Strong Predictive Algorithm of Pathogenesis-Based Biomarkers Improves Parkinson's Disease Diagnosis.

Authors:  Daniel Kam Yin Chan; Nady Braidy; Ren Fen Chen; Ying Hua Xu; Steven Bentley; Michal Lubomski; Ryan L Davis; Jack Chen; Carolyn M Sue; George D Mellick
Journal:  Mol Neurobiol       Date:  2022-01-07       Impact factor: 5.590

6.  Neuropathologic substrates of Parkinson disease dementia.

Authors:  David J Irwin; Matthew T White; Jon B Toledo; Sharon X Xie; John L Robinson; Vivianna Van Deerlin; Virginia M-Y Lee; James B Leverenz; Thomas J Montine; John E Duda; Howard I Hurtig; John Q Trojanowski
Journal:  Ann Neurol       Date:  2012-10-04       Impact factor: 10.422

Review 7.  Diagnostic procedures for Parkinson's disease dementia: recommendations from the movement disorder society task force.

Authors:  Bruno Dubois; David Burn; Christopher Goetz; Dag Aarsland; Richard G Brown; Gerald A Broe; Dennis Dickson; Charles Duyckaerts; Jefferey Cummings; Serge Gauthier; Amos Korczyn; Andrew Lees; Richard Levy; Irene Litvan; Yoshikuni Mizuno; Ian G McKeith; C Warren Olanow; Werner Poewe; Cristina Sampaio; Eduardo Tolosa; Murat Emre
Journal:  Mov Disord       Date:  2007-12       Impact factor: 10.338

Review 8.  Parkinson's disease.

Authors:  Bastiaan R Bloem; Michael S Okun; Christine Klein
Journal:  Lancet       Date:  2021-04-10       Impact factor: 79.321

9.  Screening for impaired cognitive domains in a large Parkinson's disease population and its application to the diagnostic procedure for Parkinson's disease dementia.

Authors:  Kouichi Ohta; Kazushi Takahashi; Jun Gotoh; Keiji Yamaguchi; Morinobu Seki; Yoshihiro Nihei; Satoko Iwasawa; Norihiro Suzuki
Journal:  Dement Geriatr Cogn Dis Extra       Date:  2014-05-23

10.  Plasma Levels of α-Synuclein, Aβ-40 and T-tau as Biomarkers to Predict Cognitive Impairment in Parkinson's Disease.

Authors:  Nai-Ching Chen; Hsiu-Ling Chen; Shau-Hsuan Li; Yen-Hsiang Chang; Meng-Hsiang Chen; Nai-Wen Tsai; Chiun-Chieh Yu; Shieh-Yueh Yang; Cheng-Hsien Lu; Wei-Che Lin
Journal:  Front Aging Neurosci       Date:  2020-04-28       Impact factor: 5.750

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