Back

μ-Opioid Endomorphins and DDP-IV Inhibitor SitagliptinEnhance Amyloid-Beta Clearance and Memory in anAlzheimer's Cell Model

Yung, M.

2025-07-31 neuroscience
10.1101/2025.07.24.666703 bioRxiv
Show abstract

Alzheimers Disease is a neurodegenerative disorder caused by A{beta}42 aggregation. Endomorphins 1 and 2 (EM1, EM2), two novel -opioid agonists, have been implicated in protecting against A{beta}42 toxicity, though it is unclear how the endomorphins achieve their effects. Phase one of the study found that EM1 and EM2 activation protected A{beta}42-treated cells. This protection, mediated by -opioid receptor (MOR) activation, also reduced rotenone-induced oxidative stress, both in a dose-dependent manner. Pretreatment with naloxone, a -opioid antagonist, reversed these effects, confirming MOR involvement in EM1 and EM2s actions. In phase two, molecular docking techniques suggested that sitagliptin can prevent intracellular EM1 degradation. In vitro assays demonstrated that sitagliptin enhanced intracellular EM1s beneficial effects in promoting cell survival and reducing cell apoptotic activity, A{beta}42 aggregation, and hydrogen peroxide free radical concentrations. This suggests intracellular EM1 can mitigate the toxic effects of A{beta}42 aggregation. However, sitagliptin did not enhance EM1s effects on BDNF expression or neurite outgrowth, suggesting that MOR activation, rather than intracellular EM1, primarily drives mechanisms associated with memory improvement. Collectively, our findings suggest that both intracellular EM1 and EM1-mediated MOR activation offer potential therapeutic avenues for mitigating memory impairment in Alzheimers and potentially COVID-19. Furthermore, this research underscores the critical role of the MOR in broader memory mechanisms.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.