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Record W4414350995 · doi:10.3389/fnagi.2025.1620172

Association of brain-derived neurotrophic factor in blood and cerebrospinal fluid with Parkinson’s disease and non-motor symptoms of Parkinson’s disease: a systematic review and meta-analysis of 6655 participants

2025· review· en· W4414350995 on OpenAlexaboutno aff
Zhenzhen Zhao, Jiahui Sun, Youhong Liu, Miao Liu, D. Tong

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2025
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
Fundersnot available
KeywordsBiomarkerBrain-derived neurotrophic factorDiseaseCerebrospinal fluidNeurotrophic factorsCognition

Abstract

fetched live from OpenAlex

Background Brain-derived neurotrophic factor (BDNF) is essential for regulating neuronal proliferation and survival in neurodegenerative diseases, including Parkinson’s disease (PD). However, Studies on BDNF levels in peripheral blood and cerebrospinal fluid (CSF) have inconsistent results. Therefore, this study aimed to examine BDNF levels in patients with PD and to explore their correlation with non-motor symptoms. Methods Four databases (PubMed, Embase, Cochrane Library, and CNKI) were searched for eligible studies. The quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated using Stata version 14.0, applying either a fixed-effect or a random-effects model based on heterogeneity. Furthermore, subgroup analysis, meta-regression, and sensitivity analysis were employed to identify and analyze sources of heterogeneity. Publication bias was assessed using funnel plots and Egger’s test. Results A comprehensive systematic review and meta-analysis was conducted, encompassing 48 articles. A total of 38 studies, covering 2,589 patients with PD and 2,422 healthy controls, were analyzed, revealing significantly lower peripheral blood BDNF levels in PD patients compared to healthy controls (SMD = −1.037; 95% CI [−1.412, −0.662]; P < 0.001), with substantial heterogeneity (I2 = 97.0%; P < 0.001). This result may be more applicable to serum samples and the Asian population according to subgroup analysis. PD patients with depression showed no significant difference in serum BDNF levels compared to those without depression (SMD = −0.511; 95% CI [−1.692, 0.671]; P = 0.397). A significant association was found between decreased serum BDNF concentrations and cognitive impairment in PD (SMD = −1.035; 95% CI [−1.340, −0.730]; P < 0.001). Moreover, negative correlations were observed between lower serum BDNF levels and autonomic dysfunction, rapid eye movement sleep behavior disorder (RBD), and restless legs syndrome (RLS), respectively. However, CSF BDNF levels showed no statistically significant difference between PD patients and controls (SMD = −0.398; 95% CI [−2.499, 1.703]; P = 0.711). Conclusion Reduced expression of BDNF is associated with both PD and its non-motor symptoms. Further research is needed to explore the potential of BDNF as a biomarker for non-motor symptoms of PD, particularly for cognitive impairment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.024
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0190.038
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.303
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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