Evidence map›Paper›PMID 40884749›Full record

ArticleNeurodegenerative disease management2025

Serum Neurofilament light chain predicts autonomic symptoms in early Parkinson's disease.

Linyi Li, Yaqiong Yang, En'an Zhang, Heyu Chen, Zhenxiang Zhao

Abstract read
In one paragraph

Article in Neurodegenerative disease management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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. Review
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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

5 authors.

Linyi LiDepartment of Neurology, Central China Fuwai Hospital of Zhengzhou University, Fuwai Central China Cardiovascular Hospital & Heart Centre of Henan Provincial People's Hospital, Central China Fuwai Hospital, Zhengzhou, China.
Yaqiong YangDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China.
En'an ZhangDepartment of Pediatrics, Kaifeng Children's Hospital, Kaifeng, Henan, China.
Heyu ChenSchool of Biological Science, University of Aberdeen, Aberdeen, UK.
Zhenxiang ZhaoDepartment of Neurology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAutonomic dysfunction is a common non-motor symptom of Parkinson's disease (PD). However, reliable biomarkers for predicting autonomic symptoms in PD remain unidentified. Neurofilament light chain (NfL), a biomarker of neuronal impairment, is closely correlated with disease progression in PD.

objectiveThis study examines the relationship between serum NfL levels and autonomic impairment in patients with early-stage PD.

methodsA total of 312 patients with PD were included in the Parkinson's Progression Markers Initiative (PPMI) database. Autonomic symptoms were assessed using the Scale for Outcomes in Parkinson's Disease for Autonomic Symptoms (SCOPA-AUT). Kaplan-Meier survival analysis and linear mixed-effects models were used to evaluate associations between serum NfL and autonomic symptoms.

resultsHigher baseline serum NfL levels were significantly associated with increased SCOPA-AUT scores and greater autonomic symptoms over time. Patients with the highest tertile of baseline serum NfL levels had an increased risk of developing OH over the five-year follow-up period (

conclusionsElevated baseline serum NfL levels may be a valuable biomarker for predicting autonomic symptoms in early-stage Parkinson's disease, which might be a new target in disease monitoring and early intervention.

Indexed as

Autonomic Nervous System DiseasesNeurofilament ProteinsParkinson DiseaseAgedBiomarkersDisease ProgressionFemaleHumansMaleMiddle AgedBiomarkersneurofilament protein LNeurofilament Proteinsautonomic symptomsbiomarkerneurofilament light chainParkinson’s diseaseserum

Identifiers

PMID40884749
PMCPMC12952744

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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.