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It has been suggested that alcohol consumption protects against Parkinson's disease (PD). Here we assessed postmortem tissue samples from the brains and livers of 100 subjects with ages at death ranging from 51 to 93. Twenty percent of these subjects were demented. We used standardized assessment strategies to assess both the brain and liver pathologies (LP). Our cohort included subjects with none, mild, moderate, and severe LP caused by alcohol consumption. We noted a significant negative correlation of categorical data between liver steatosis and α-synuclein (αS) in the brain and a significant negative correlation between the extent of liver steatosis and fibrosis and the extent of αS in the brain. There was a significant negative association between the observation of Alzheimer’s type II astrocytes and αS pathology in the brain. No association was noted between LP and hyperphosphorylated τ (HPτ). No significant correlation could be seen between the extent of LP and the extent of HPτ, amyloid β protein (Aβ) or transactive DNA binding protein 43 (TDP43) in the brain. There were significant correlations observed between the extent of HPτ, Aβ, αS, and TDP43 in the brain and between liver steatosis, inflammation, and fibrosis. Subjects with severe LP displayed a higher frequency of Alzheimer’s type II astrocytes compared to those with no, or mild, LP. The assessed protein alterations were not more prevalent or severe in subjects with Alzheimer’s type II astrocytes in the brain. In all cases, dementia was attributed to a combination of altered proteins, i.e., mixed dementia and dementia was observed in 30% of those with mild LP when compared with 13% of those with severe LP. In summary, our results are in line with the outcome obtained by the two recent meta-analyses suggesting that subjects with a history of alcohol consumption seldom develop an α-synucleinopathy.
It has been suggested that alcohol consumption protects against Parkinson's disease (PD). Here we assessed postmortem tissue samples from the brains and livers of 100 subjects with ages at death ranging from 51 to 93. Twenty percent of these subjects were demented. We used standardized assessment strategies to assess both the brain and liver pathologies (LP). Our cohort included subjects with none, mild, moderate, and severe LP caused by alcohol consumption. We noted a significant negative correlation of categorical data between liver steatosis and α-synuclein (αS) in the brain and a significant negative correlation between the extent of liver steatosis and fibrosis and the extent of αS in the brain. There was a significant negative association between the observation of Alzheimer’s type II astrocytes and αS pathology in the brain. No association was noted between LP and hyperphosphorylated τ (HPτ). No significant correlation could be seen between the extent of LP and the extent of HPτ, amyloid β protein (Aβ) or transactive DNA binding protein 43 (TDP43) in the brain. There were significant correlations observed between the extent of HPτ, Aβ, αS, and TDP43 in the brain and between liver steatosis, inflammation, and fibrosis. Subjects with severe LP displayed a higher frequency of Alzheimer’s type II astrocytes compared to those with no, or mild, LP. The assessed protein alterations were not more prevalent or severe in subjects with Alzheimer’s type II astrocytes in the brain. In all cases, dementia was attributed to a combination of altered proteins, i.e., mixed dementia and dementia was observed in 30% of those with mild LP when compared with 13% of those with severe LP. In summary, our results are in line with the outcome obtained by the two recent meta-analyses suggesting that subjects with a history of alcohol consumption seldom develop an α-synucleinopathy.
NAFLD has some potential risk factors for developing Alzheimer's disease. This study attempted to establish the potential connections between NAFLD-associated Alzheimer's disease (AD) by analyzing shared genes and pathways using bioinformatics tools. Initially, prepared gene lists related to AD and NAFLD were collected from the GeneCard database, and genes with GeneCard relevance score ≥ 20 were extracted to make a new gene list. The Venn diagram identified common genes (417) between the two diseases from the new gene list. The common genes were used for further analysis of the PPI network, which was constructed using the STRING database with a minimum required interaction score ≥ 0.9 to obtain network relationships. The networks had shown 397 nodes, 1210 edges, an average node degree of 54.7, and an expected number of edges at 397. The top 25 hub genes were calculated by Cytoscape (vs3.10.2) using the bottleneck, degree, and closeness method using CytoHubba. The merged network of the top 25 hub genes from the previously mentioned three methods was contracted to identify the connection between NAFLD and AD. Our study revealed that important pathways were PI3K-Akt and AGE-RAGE in diabetic complications, NAFLD-related systemic inflammation to neuroinflammation, and LRP-1-induced amyloid and tau hyperphosphorylation. This suggests an interrelation between the two major diseases, ushering in the need for new possibilities utilizing this crosstalk.
Multiple organs and tissues coordinate to respond to dietary and environmental challenges. It is interorgan crosstalk that contributes to systemic metabolic homeostasis. The liver and brain, as key metabolic organs, have their unique dialogue to transmit metabolic messages. The interconnected pathogenesis of liver and brain is implicated in numerous metabolic and neurodegenerative disorders. Recent insights have positioned the liver not only as a central metabolic hub but also as an endocrine organ, capable of secreting hepatokines that transmit metabolic signals throughout the body via the bloodstream. Metabolites from the liver or gut microbiota also facilitate a complex dialogue between liver and brain. In parallel to humoral factors, the neural pathways, particularly the hypothalamic nuclei and autonomic nervous system, are pivotal in modulating the bilateral metabolic interplay between the cerebral and hepatic compartments. The term “liver–brain axis” vividly portrays this interaction. At the end of this review, we summarize cutting-edge technical advancements that have enabled the observation and manipulation of these signals, including genetic engineering, molecular tracing, and delivery technologies. These innovations are paving the way for a deeper understanding of the liver–brain axis and its role in metabolic homeostasis.
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