# Stem-cell-derived extracellular vesicles in neurodegeneration and neuroaging: therapeutic potential and challenges

**Authors:** Mohit Kumar, Sudipta Ray, Susmita Sil

PMC · DOI: 10.20517/evcna.2025.65 · Extracellular Vesicles and Circulating Nucleic Acids · 2025-09-30

## TL;DR

Stem-cell-derived extracellular vesicles may help treat brain aging and neurodegeneration by reducing inflammation and supporting brain function.

## Contribution

This paper reviews how stem-cell-derived extracellular vesicles can combat neurodegeneration and aging through multiple biological mechanisms.

## Key findings

- Stem-cell-derived EVs can reduce neuroinflammation and senescence in the brain.
- EVs from stem cells improve cognitive function and promote neuronal survival via neuroprotective miRNAs.
- These EVs can cross the blood-brain barrier and offer targeted therapeutic delivery.

## Abstract

Neuroaging is a complex biological process in which the brain undergoes progressive functional decline marked by synaptic loss, neuroinflammation, and cognitive decline. At the molecular and cellular level, aging is driven by multiple interconnected hallmarks, including genomic instability, telomere attrition, epigenetic alterations, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication. Among these, cellular senescence, a state of irreversible cell cycle arrest, has emerged as a critical contributor to brain aging. Senescent cells accumulate with age, driven by the p53-p21 and p16-pRb pathways, and secrete pro-inflammatory factors via senescence-associated secretory phenotype (SASP), thereby exacerbating neurodegeneration, vascular dysfunction, and cognitive decline. Extracellular vesicles (EVs) are natural nanocarriers of proteins, lipids, and nucleic acids, and have emerged as key mediators of intercellular communication and therapeutics for aging and age-related conditions. EVs derived from various cell types, such as mesenchymal stem cells (MSCs), neural stem cells (NSCs), and induced pluripotent stem cells (iPSCs), can modulate senescence-related pathways, reduce inflammation, and promote tissue repair. Preclinical studies demonstrate that stem-cell-derived EVs can improve cognitive performance, enhance neurogenesis, reduce senescence phenotype, improve neuronal survival through neuroprotective miRNAs (miR-181a-2-3p), suppress neuroinflammation via inhibition of NLRP3 inflammasome, and support synaptic plasticity. Stem cell EVs possess natural biocompatibility, the ability to cross the blood-brain barrier (BBB), and targeted delivery mechanisms, making them promising candidates for anti-aging interventions. This review elaborates on the multifaceted role of stem cell EVs in mitigating brain aging, senescence, and age-associated chronic disease phenotype.

## Linked entities

- **Genes:** TP53 (tumor protein p53) [NCBI Gene 7157], CDKN1A (cyclin dependent kinase inhibitor 1A) [NCBI Gene 1026], CDKN2A (cyclin dependent kinase inhibitor 2A) [NCBI Gene 1029], RB1 (RB transcriptional corepressor 1) [NCBI Gene 5925], NLRP3 (NLR family pyrin domain containing 3) [NCBI Gene 114548]

## Full-text entities

- **Genes:** RB1 (RB transcriptional corepressor 1) [NCBI Gene 5925] {aka OSRC, PPP1R130, RB, p105-Rb, p110-RB1, pRb}, CDKN2A (cyclin dependent kinase inhibitor 2A) [NCBI Gene 1029] {aka ARF, CAI2, CDK4I, CDKN2, CMM2, INK4}, NLRP3 (NLR family pyrin domain containing 3) [NCBI Gene 114548] {aka AGTAVPRL, AII, AVP, C1orf7, CIAS1, CLR1.1}, TP53 (tumor protein p53) [NCBI Gene 7157] {aka BCC7, BMFS5, LFS1, P53, TRP53}, H3P16 (H3 histone pseudogene 16) [NCBI Gene 644914] {aka H3.6, H3F3AP6, p21}
- **Diseases:** vascular dysfunction (MESH:D002561), neuroinflammation (MESH:D000090862), mitochondrial dysfunction (MESH:D028361), cognitive decline (MESH:D003072), neurodegeneration (MESH:D019636), inflammation (MESH:D007249)
- **Chemicals:** lipids (MESH:D008055)

## Full text

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## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12540269/full.md

## References

144 references — full list in the complete paper: https://tomesphere.com/paper/PMC12540269/full.md

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Source: https://tomesphere.com/paper/PMC12540269