ReviewAnimal models and experimental medicine2026
The liver-brain axis: A multidimensional regulatory network implicated in Alzheimer's disease pathogenesis and clinical implications.
Review in Animal models and experimental medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β (Aβ) deposition. The liver-brain axis underscores the central role of the liver in modulating cognitive function through multidimensional regulatory mechanisms. As a core metabolic and detoxification organ, the liver also helps maintain cerebral homeostasis via pathways including the urea cycle, antioxidant systems, ketone body metabolism, and bile acid regulation. Dysfunction of these processes may lead to ammonia accumulation, exacerbated oxidative stress, and Aβ clearance, thereby accelerating the pathological progression of AD. Liver-derived factors such as apolipoprotein E (APOE), C-reactive protein (CRP), fibroblast growth factor 21 (FGF21), and insulin-like growth factor 1 (IGF-1) significantly increase the risk of AD through dual mechanisms-inhibiting Aβ clearance and activating neuroinflammation, thereby directly affecting cognitive function via modulation of inflammation, metabolism, and blood-brain barrier (BBB) integrity. Neural interfaces formed by the hypothalamic-pituitary-target gland axis and the vagus nerve enable communication from the liver to the brain, with emerging evidence also supporting a reverse influence from the brain to the liver. Emerging technologies such as molecular tracing and nanocarriers provide new tools for deciphering dynamic interactions within the liver-brain axis. Liver-targeted metabolic interventions show potential for reversing cognitive impairment. Unlike previous reviews that mainly focused on single pathways, this review conceptualizes the liver-brain axis as a multidimensional regulatory network in AD. By clearly linking network nodes to potential therapeutic interventions, it provides us with a novel framework that not only describes the various mechanisms but also focuses on identifying actionable targets for disease prevention and treatment.
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