FGF–FGFR Signaling in Parkinson’s Disease: Mechanistic Links to Ferroptosis and Neuroprotection

Parkinson's disease (PD) is characterized by progressive degeneration of the nigrostriatal dopaminergic system and α-synuclein (α-syn) pathology, with disease progression driven by convergent mechanisms including neuroinflammation, mitochondrial injury, oxidative stress, and regulated cell-death programs such as ferroptosis. Fibroblast growth factors (FGFs) and fibroblast growth factor receptors (FGFRs) constitute a key signaling system in the central nervous system, influencing not only neuronal survival and glial states but also intersecting with networks governing redox homeostasis and iron metabolism. Accumulating evidence indicates that, beyond classical neurotrophic actions, FGF-FGFR signaling can modulate mitochondrial quality control, glial inflammatory activation, and lipid peroxidation-related processes, thereby reshaping cellular susceptibility to ferroptotic injury. This review summarizes current advances in understanding FGF signaling networks in Parkinson's disease, synthesizes their potential mechanistic links to the interplay among neuroinflammation, mitochondrial dysfunction, and redox imbalance as well as to ferroptosis regulation, and discusses the experimental basis and translational challenges of targeting the FGF pathway as a disease-modifying therapeutic strategy.

Authors

Institutions

Publication Details

Journal
Brain Sciences
Published
2026-01-29
DOI
https://doi.org/10.3390/brainsci16020151
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

FGF–FGFR Signaling in Parkinson’s Disease: Mechanistic Links to Ferroptosis and Neuroprotection

Dewei Mao, Ran Li, Hao Wang, Min Yan et al.
Brain Sciences
Ferroptosis and cancer prognosis
article

FGF–FGFR Signaling in Parkinson’s Disease: Mechanistic Links to Ferroptosis and Neuroprotection

Dewei Mao, Ran Li, Hao Wang, Min Yan, Xuewen Tian, Xiao Wen
article en

Abstract

Parkinson's disease (PD) is characterized by progressive degeneration of the nigrostriatal dopaminergic system and α-synuclein (α-syn) pathology, with disease progression driven by convergent mechanisms including neuroinflammation, mitochondrial injury, oxidative stress, and regulated cell-death programs such as ferroptosis. Fibroblast growth factors (FGFs) and fibroblast growth factor receptors (FGFRs) constitute a key signaling system in the central nervous system, influencing not only neuronal survival and glial states but also intersecting with networks governing redox homeostasis and iron metabolism. Accumulating evidence indicates that, beyond classical neurotrophic actions, FGF-FGFR signaling can modulate mitochondrial quality control, glial inflammatory activation, and lipid peroxidation-related processes, thereby reshaping cellular susceptibility to ferroptotic injury. This review summarizes current advances in understanding FGF signaling networks in Parkinson's disease, synthesizes their potential mechanistic links to the interplay among neuroinflammation, mitochondrial dysfunction, and redox imbalance as well as to ferroptosis regulation, and discusses the experimental basis and translational challenges of targeting the FGF pathway as a disease-modifying therapeutic strategy.

Brain SciencesVol. 16(2)
Shandong Sport University (CN), Chinese University of Hong Kong, Shenzhen (CN)
National Science and Technology Major Project
Good health and well-being
Openalex Percentile: Top 75%
Ferroptosis and cancer prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.