SCIENTIFIC HUB

Follow the evidence.

SCIENTIFIC LITERATURE · MED

Lessons from inducible pluripotent stem cell models on neuronal senescence in aging and neurodegeneration.

Nat Aging · 2024-03-01

DOI: 10.1038/s43587-024-00586-3PMID: 38429379

Open accessresearch-article; Review; Journal ArticleOriginal source ↗

Research overview

The text below is the source article’s original abstract under a verified reuse license. cc by

Age remains the central risk factor for many neurodegenerative diseases including Parkinson's disease, Alzheimer's disease and amyotrophic lateral sclerosis. Although the mechanisms of aging are complex, the age-related accumulation of senescent cells in neurodegeneration is well documented and their clearance can alleviate disease-related features in preclinical models. Senescence-like characteristics are observed in both neuronal and glial lineages, but their relative contribution to aging and neurodegeneration remains unclear. Human pluripotent stem cell-derived neurons provide an experimental model system to induce neuronal senescence. However, the extensive heterogeneity in the profile of senescent neurons and the methods to assess senescence remain major challenges. Here, we review the evidence of cellular senescence in neuronal aging and disease, discuss human pluripotent stem cell-based model systems used to investigate neuronal senescence and propose a panel of cellular and molecular hallmarks to characterize senescent neurons. Understanding the role of neuronal senescence may yield novel therapeutic opportunities in neurodegenerative disease.

Scientific assessment

01

Research question

Assess the question within the original study’s scope.

02

Methods & sample

Check the source article for study design and sample details.

03

Key findings

An editorially approved findings summary is not yet published for this record.

04

Limitations

Generalizability, bias and clinical meaning require separate assessment.

Methods, samples and clinical conclusions are not inferred from bibliographic metadata.