Urolithin A reduces amyloid-beta load and improves cognitive deficits uncorrelated with plaque burden in a mouse model of Alzheimer's disease.
Josué Ballesteros-ÁlvarezWynnie NguyenRenuka SivapathamAnand RaneJulie K AndersenPublished in: GeroScience (2022)
In the present study, we investigated the effects of urolithin A (UA), a metabolite generated from ellagic acid via its metabolism by gut bacteria, as an autophagy activator with potential neuroprotective activity. WT and 3xTg-AD mice were administered long-term intermittent dietary supplementation with UA. UA was found to prevent deficits in spatial memory, cued fear response, and exploratory behavior in this model. It also decreased the Aβ plaque burden in areas of the hippocampus where these protein deposits are prominent in the model. Interestingly, correlation analyses demonstrate that Aβ plaque burden positively correlates with enhanced spatial memory in 3xTg-AD mice on a control diet but not in those supplemented with UA. In contrast, Aβ42 abundance in cortical and hippocampal homogenates negatively correlate with spatial memory in UA-fed mice. Our data suggest that plaque formation may be a protective mechanism against neurodegeneration and cognitive decline and that targeting the generation of proteotoxic Aβ species might be a more successful approach in halting disease progression. UA was also found to extend lifespan in normal aging mice. Mechanistically, we demonstrate that UA is able to induce autophagy and to increase Aβ clearance in neuronal cell lines. In summary, our studies reveal UA, likely via its actions as a autophagy inducer, is capable of removing Aβ from neurons and its dietary administration prevents the onset of cognitive deficits associated with pathological Aβ deposition in the 3xTg-AD mouse model as well as extending lifespan in normal aging mice.
Keyphrases
- cognitive decline
- mouse model
- high fat diet induced
- cell death
- coronary artery disease
- signaling pathway
- oxidative stress
- endoplasmic reticulum stress
- magnetic resonance
- type diabetes
- traumatic brain injury
- mild cognitive impairment
- spinal cord injury
- gene expression
- metabolic syndrome
- machine learning
- cancer therapy
- genome wide
- high intensity
- small molecule
- weight loss
- climate change
- artificial intelligence
- binding protein
- high resolution
- nuclear factor
- skeletal muscle
- deep learning
- human health
- toll like receptor