Research overview
The text below is the source article’s original abstract under a verified reuse license. cc by
Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease, multiple sclerosis, and amyotrophic lateral sclerosis share converging mechanisms of neuronal dysfunction, including protein aggregation, oxidative stress, and chronic neuroinflammation. Glial cells, once considered passive supporters, are now recognized as central drivers of these processes, offering both pathogenic triggers and therapeutic opportunities. Yet, despite compelling preclinical evidence, the translation of glial-targeted therapies into clinical success has been limited. This review provides a critical synthesis of current knowledge by examining therapeutic strategies through the lens of their translational challenges and failures. This narrative review highlights how interspecies variability of glial phenotypes, shifting neuroprotective versus neurotoxic states, limited biomarker stratification, and delivery barriers have constrained trials, such as anti-triggering receptor expressed on myeloid cells 2 (anti-TREM2) antibodies in AD and glial cell line-derived neurotrophic factor (GDNF) in PD. By analyzing these obstacles across major neurodegenerative disorders, this review argue that the next stage of glial medicine requires precision approaches that integrate stage-specific phenotyping, biomarker-guided patient selection, and innovative delivery platforms. Understanding not only what has been tried but why translation has stalled is essential to chart a roadmap for effective, disease-modifying glial therapies in the aging brain.
Scientific assessment
Research question
Assess the question within the original study’s scope.
Methods & sample
Check the source article for study design and sample details.
Key findings
An editorially approved findings summary is not yet published for this record.
Limitations
Generalizability, bias and clinical meaning require separate assessment.
Methods, samples and clinical conclusions are not inferred from bibliographic metadata.