Evidence map›Paper›PMID 37475029›Full record

ArticleJournal of neuroinflammation2023

Cerebrospinal fluid GFAP is a predictive biomarker for conversion to dementia and Alzheimer's disease-associated biomarkers alterations among de novo Parkinson's disease patients: a prospective cohort study.

Tingting Liu, Hongzhou Zuo, Di Ma, Dan Song, Yuying Zhao, Oumei Cheng

Open access · goldAbstract read
In one paragraph

Article in Journal of neuroinflammation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
10.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
  2. What's in a name? reframing advanced Parkinson's disease as a multidimensional state.Journal of neural transmission (Vienna, Austria : 1996) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Tingting Liu *Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Hongzhou Zuo *Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Di Ma *Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Dan SongDepartment of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Yuying ZhaoDepartment of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Oumei ChengDepartment of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China. chengoumei01@aliyun.com.
Chongqing Medical University · CNThe Affiliated Yongchuan Hospital of Chongqing Medical University · CN

Funding

National Natural Science Foundation of China 81100981National Natural Science Foundation of China 81471334National Natural Science Foundation of China 81871002
6 · The paper itself

Abstract

backgroundDementia is a prevalent non-motor manifestation among individuals with advanced Parkinson's disease (PD). Glial fibrillary acidic protein (GFAP) is an inflammatory marker derived from astrocytes. Research has demonstrated the potential of plasma GFAP to forecast the progression to dementia in PD patients with mild cognitive impairment (PD-MCI). However, the predictive role of cerebrospinal fluid (CSF) GFAP on future cognitive transformation and alterations in Alzheimer's disease (AD)-associated CSF biomarkers in newly diagnosed PD patients has not been investigated.

methods210 de novo PD patients from the Parkinson's Progression Markers Initiative were recruited. Cognitive progression in PD participants was evaluated using Cox regression. Cross-sectional and longitudinal associations between baseline CSF GFAP and cognitive function and AD-related CSF biomarkers were evaluated using multiple linear regression and generalized linear mixed model.

resultsAt baseline, the mean age of PD participants was 60.85 ± 9.78 years, including 142 patients with normal cognition (PD-NC) and 68 PD-MCI patients. The average follow-up time was 6.42 ± 1.69 years. A positive correlation was observed between baseline CSF GFAP and age (β = 0.918, p < 0.001). There was no statistically significant difference in baseline CSF GFAP levels between PD-NC and PD-MCI groups. Higher baseline CSF GFAP predicted greater global cognitive decline over time in early PD patients (Montreal Cognitive Assessment, β = - 0.013, p = 0.014). Furthermore, Cox regression showed that high baseline CSF GFAP levels were associated with a high risk of developing dementia over an 8-year period in the PD-NC group (adjusted HR = 3.070, 95% CI 1.119-8.418, p = 0.029). In addition, the baseline CSF GFAP was positively correlated with the longitudinal changes of not only CSF α-synuclein (β = 0.313, p < 0.001), but also CSF biomarkers associated with AD, namely, amyloid-β 42 (β = 0.147, p = 0.034), total tau (β = 0.337, p < 0.001) and phosphorylated tau (β = 0.408, p < 0.001).

conclusionsCSF GFAP may be a valuable prognostic tool that can predict the severity and progression of cognitive deterioration, accompanied with longitudinal changes in AD-associated pathological markers in early PD.

Indexed as

Alzheimer DiseaseCognitive DysfunctionParkinson DiseaseAgedAmyloid beta-PeptidesBiomarkersCross-Sectional StudiesGlial Fibrillary Acidic ProteinHumansMiddle AgedPeptide FragmentsProspective Studiestau ProteinsAmyloid beta-PeptidesBiomarkersGlial Fibrillary Acidic ProteinPeptide Fragmentstau ProteinsCerebrospinal fluidCognition declineGlial fibrillary acidic proteinParkinson’s diseaseParkinson’s Progression Markers Initiative

Identifiers

PMID37475029
PMCPMC10357612
OpenAlexW4384923774

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.