Evidence map›Paper›PMID 41026459›Full record

ArticleActa neurologica Belgica2025

Elucidate biomarkers and the molecular pathways associated with genetic variants that contribute to the etiology of Parkinson's disease.

Hai Duc Nguyen

Abstract read
In one paragraph

Article in Acta neurologica Belgica, 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

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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

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

1 author.

Hai Duc NguyenDepartment of Microbiology, Tulane National Primate Research Center, Louisiana, 70433, USA. dnguyen14@tulane.edu.ORCID http://orcid.org/0000-0001-8419-7784

Funding

Tulane NPRC SPF Sheltered Outdoor Enclosure ExpansionP51OD011104 · OD · TULANE UNIVERSITY OF LOUISIANA · PI L Lee HAMM · 2012 to 2026
$142.4M
NIH HHS P51 OD011104
6 · The paper itself

Abstract

Genetic variants can affect signaling pathways that are important in the pathophysiology of Parkinson's disease (PD). Comprehending their relationship is crucial for the development of diagnostic instruments and preventative drugs for PD. We thoroughly analyzed data from 68 genome-wide association studies to uncover significant genetic variations and clarify the molecular pathways underlying the etiology of Parkinson's disease (PD) resulting from genetic variants. Six common biomarkers linked to PD were found in all 68 investigations: SNCA, TMEM175, BST1, RIT2, LRRK2, and MCCC1. SNCA (↑rs5019538 and ↑rs356182), LRRK2 (↑rs34637584 and ↑rs76904798), and SH3GL2 (↑rs10756907 and ↓rs13294100) were the main biomarkers associated with PD. The clinical traits of PD, such as age at onset, cognitive progression, motor progression, composite progression, tremor dominant, and postural instability gait difficulty, have been found to be underpinned by additional biomarkers, including APOE, NTRK2, SLCO1B3, SLC28A3, AQP10, SNCAIP, ANO2, CADM1, PTPRD, GPR32, GPR321, SQOR, SULT1C2, GABRG2, CYP4Z1, CDH13, and FANCF. Significant evidence was found linking genetic variants linked to an increased risk of PD to reduced dopamine production, receptor recycling, oxidoreductase activity, and increased amyloid-beta accumulation. Considerable evidence links genetic variations with a lower risk of PD due to improved synaptic vesicle signaling, neuron projection development, controlled histone methylation, and excitatory postsynaptic potential. Additionally, we found MYT1L and hsa-miR-20a-5p, which are essential for understanding the genetic variations linked to PD. These findings provide a solid underpinning for future therapeutic approaches aimed at PD, with a focus on the genetic variants and processes connected to the illness.

Indexed as

Genetic Predisposition to DiseaseGenetic VariationParkinson DiseaseSignal TransductionBiomarkersGenome-Wide Association StudyHumansBiomarkersBiomarkersGWASMolecular mechanismsParkinson’s disease

Identifiers

PMID41026459
PMCPMC12644238

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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.