Evidence map›Paper›PMID 39920821›Full record

ArticleAlzheimer's research & therapy2025

β-synuclein in cerebrospinal fluid as a potential biomarker for distinguishing human prion diseases from Alzheimer's and Parkinson's disease.

Bing Xu, Kang Xiao, Xiaoxi Jia, Rundong Cao, Donglin Liang, Ruhan A, Weiwei Zhang, Chunjie Li, Liping Gao, Cao Chen and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Alzheimer's research & therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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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

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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

2 citing papers in PubMed.

  1. Article
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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

12 authors.

Bing Xu *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Kang Xiao *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaoxi JiaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Rundong CaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Donglin LiangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Ruhan ANational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Weiwei ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Chunjie LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Liping GaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Cao ChenNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Qi ShiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. shiqi@ivdc.chinacdc.cn.
Xiaoping DongNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. dongxp238@sina.com.

Funding

SKLID Development Grants from the National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, China CDC 2021SKLID504, 2019SKLID401, 2019SKLID603, and 2021SKLID503
6 · The paper itself

Abstract

backgroundβ-synuclein (β-syn), mainly expressed in central nerve system, is one of the biomarkers in cerebrospinal fluid (CSF) and blood for synaptic damage, which has been reported to be elevated in CSF and blood of the patients of prion diseases (PrDs).

methodsWe analyzed 314 CSF samples from patients in China National Surveillance for CJD. The diagnostic groups of the 223 patients with PrDs included sporadic Creutzfeldt-Jacob disease (sCJD), genetic CJD (gCJD), fatal familial insomnia (FFI) and Gerstmann-Straussler-Scheinker (GSS). 91 patients with non-PrDs comprised Alzheimer's disease (AD), Parkinson's disease (PD), viral encephalitis (VE) or autoimmune encephalitis (AE) were enrolled in the control groups. The CSF β-syn levels were measured by a commercial microfluidic ELISA. The Mann-Whitney U test and Kruskal-Wallis H test were employed to analyze two or more sets of continuous variables. Multiple linear regression was also performed to evaluate the factors for CSF β-syn levels. Receiver operating characteristics (ROC) curves and area under the curve (AUC) values were used to assess the diagnostic performance of β-syn.

resultsThe median of β-syn levels (2074 pg/ml; IQR: 691 to 4332) of all PrDs was significantly higher than that of non-PrDs group (504 pg/ml; IQR: 126 to 3374). The CSF β-syn values in the cohorts of sCJD, T188K-gCJD, E200K-gCJD and P102L-GSS were remarkably higher than that of the group of AD + PD, but similar as that of the group of VE + AE. The elevated CSF β-syn in sCJD and gCJD cases was statistically associated with CSF 14-3-3 positive and appearance of mutism. ROC curve analysis identified satisfied performance for distinguishing from AD + PD, with high AUC values in sCJD (0.7640), T188K-gCJD (0.8489), E200K-gCJD (0.8548), P102L-GSS (0.7689) and D178N-FFI (0.7210), respectively.

conclusionOur data here indicate that CSF β-syn is a potential biomarker for distinguishing PrDs (gCJD, sCJD and GSS) from AD and PD, but is much less efficient from VE and AE. These findings have critical implications for early diagnosis and monitoring of synaptic integrity in prion diseases.

Indexed as

Alzheimer Diseasebeta-SynucleinParkinson DiseasePrion DiseasesAdultAgedAged, 80 and overBiomarkersDiagnosis, DifferentialFemaleHumansMaleMiddle AgedROC Curvebeta-SynucleinBiomarkersCerebrospinal fluidHuman prion diseasesβ-synuclein

Identifiers

PMID39920821
PMCPMC11806663

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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.