Past,Present,and Future of Liver-Brain Axis in Alzheimer’s Disease: A Bibliometric Review

Abstract

Background:

No effective drugs currently exist to cure Alzheimer’s disease (AD) due to its complexity and the lack of understanding of the involved molecular signaling and pathways. The relationship between liver health and AD is now widely recognized. Still, molecular links and shared pathways between the liver and brain remain unclear, making the liver-brain axis in AD therapies a new area for exploration. However, bibliometric studies on this topic are lacking.

Objective:

This study aims to review the liver-brain axis in AD and identify future research hotspots and trends through bibliometric analysis.

Methods:

Articles and reviews related to AD and liver and its related diseases were searched in the Web of Science Core Collection (WoSCC) database up to 2024. Data were processed and visually analyzed using VOSviewer, CiteSpace, and Pajek.

Results:

We collected 1,777 articles on AD and liver and its related diseases from 2,517 institutions across 80 countries. Keyword cluster analysis identified 11 clusters, with ‘insulin resistance,’ ‘amyloid-beta,’ ‘apolipoprotein-E,’ ‘oxidative stress,’ and ‘inflammation’ appearing most frequently, and exhibiting strong total link strength. These results indicate that these topics have been the primary focus of research on the liver-brain axis in AD.

Conclusions:

This study is the first to comprehensively analyze the liver-brain axis in AD using bibliometric methods. The research results identify recent research frontiers and hotspots, aiding scholars in gaining a deeper understanding of the correlation between AD and the liver.

Keywords

Alzheimer’s disease bibliometric analysis liver liver-brain axis review

INTRODUCTION

Alzheimer’s disease (AD) is one of the most common and complex irreversible neurological disorders, first documented by the German physician Alois Alzheimer in 1907. 1 It is primarily characterized by the formation of amyloid-β (Aβ) deposits in senile plaques and intracellular neurofibrillary tangles formed by hyperphosphorylation of tau protein. AD now affects one in ten adults over the age of 65, with its prevalence increasing with age. 2 However, there is still no effective cure for AD.

Previous research on the pathogenesis of AD has focused on the central nervous system. Aβ is recognized as a key protein that promotes AD pathogenesis, with an imbalance in the production and clearance of Aβ playing a crucial role in AD development. 3 Despite strategies to remove Aβ from the brain being a major focus of AD therapy, they have achieved limited clinical success. 4 Consequently, more scientists are now concentrating on developing strategies based on peripheral Aβ clearance.5,6, 5,6 Most Aβ in the brain can be eliminated via transport to the periphery.7,8, 7,8 Currently, pathways such as the blood-brain barrier (BBB) and perivascular lymphatic drainage are proposed to mediate the peripheral outflow of Aβ.6,9, 6,9 Aβ that is not eliminated through phagocytosis or proteolytic degradation in the central nervous system can be transported to the bloodstream via the BBB, interstitium, and cerebrospinal fluid. In the blood, some Aβ molecules undergo degradation by phagocytes or Aβ-degrading enzymes, while others are transported by lipoproteins, red blood cells, and albumin to peripheral organs or tissues, where they are degraded by liver cells or macrophages, or eliminated from the body through liver excretion. 10 Specifically, LRP-1 expressed in hepatocytes binds to Aβ and mediates its uptake from the circulation. Beyond the role of the liver in clearing circulating Aβ, evidence linking the liver to AD includes lipid and bile acid metabolism, as well as inflammatory communication between the two organs that may occur through pro-inflammatory factors.11 –13 In advanced age, the BBB becomes more permeable, allowing for closer contact between the periphery and the brain. At this point, the liver, due to its detoxification function, may become saturated, increasing inflammation and oxidative stress, which in turn exacerbates neuroinflammation and oxidative stress in the nervous system.

A study suggests that hepatic dysfunction might potentially contribute to AD by acting as a reservoir of pro-inflammatory cytokines during chronic inflammation resulting from various forms of injury, such as viral infection, drug-induced damage, and metabolic disorders. 11 The expression of LRP-1 is drastically reduced in conditions of alcohol abuse, obesity, or diabetes, which may subsequently affect the clearance of Aβ.7,14, 7,14 Additionally, hepatic DHA biosynthesis is linked to AD. Diet-derived α-linolenic acid (ALA, C18:3 omega-3) is absorbed by the intestine and delivered to the liver, where it serves as a precursor for DHA. Peroxisomal dysfunction impairs the conversion of tetracosahexaenoic acid (C24:6 omega-3) into DHA in the livers of subjects with AD. This systemic deficiency in DHA may reduce the flux of this neuroprotective fatty acid to the brain, leading to cognitive impairment. 15 If liver health continues to deteriorate in the absence of any pathogenic or external factors, it is most likely due to unhealthy foods and lifestyle choices. Its role in the liver-brain axis of AD is now beginning to attract considerable attention. Western diet-induced metabolic disorders that cause non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) raise blood cholesterol levels, particularly 27-hydroxycholesterol, a form that flows freely through the BBB. This accumulation of cholesterol in the brain facilitates the production of Aβ in lipid rafts, leading to a vicious cycle of AD progression. 16 Adding junk food to our daily diet can lead to vitamin and mineral depletion, hormonal abnormalities, and DNA oxidation. These eating habits can eventually lead to insulin resistance, which can also lead to metabolic dysfunction. 17 However, the ketogenic intervention has shown a notable positive impact on cognitive function in patients with AD or mild cognitive impairment,18 –20 suggesting that ketone bodies could provide effective energy generation for those at risk of neurodegenerative disorders. 21 Exercise intervention has also been found to reduce the progression of AD22,23, 22,23 and enhance liver metabolic function.24,25, 24,25

These studies have demonstrated the importance of the liver in maintaining normal neurological function.26,27, 26,27 The hypothesis of the liver-brain axis of neurodegeneration was first proposed in 2009. 28 This hypothesis posits that progressive hepatic steatosis elicits inflammation and activation of pro-inflammatory cytokines, leading to insulin resistance and triggering a cascade of lipolysis and lipid imbalance, which increases ceramide production and accumulation. The cytotoxicity of ceramides contributes to the development of insulin resistance, while their lipophilic nature facilitates their passage across the BBB, resulting in central nervous system insulin resistance and neurodegeneration. Recent studies have found that individuals with AD exhibit markedly elevated liver dysfunction compared to healthy individuals,29,30, 29,30 and liver diseases such as NAFLD are inextricably linked to AD. 31 In 2023, Professor Zhu’s team revealed the mechanism of action of the liver-brain axis in AD, finding that the liver plays a crucial role in normal brain function and may contribute to the pathogenesis of AD. The liver, responsible for regulating metabolism and supporting the immune system, maybe a key organ in the development and prognosis of AD. Therefore, we conducted a bibliometric analysis of the liver-brain axis in AD to review the role of the liver in AD and identify future research hotspots and trends.

Bibliometric analysis is a method used to evaluate and examine research papers in a specific field of study during a defined period, employing both qualitative and quantitative approaches. 32 This technique focuses on the analysis of nations, organizations, publications, authors, and keywords associated with the research of a particular issue. Furthermore, it performs performance evaluations of authors, institutions, and countries, providing readers with an impartial perspective on the patterns and limitations in the field.33,34, 33,34 This study was undertaken to identify evolutionary patterns and emerging areas of concern in AD and liver and its related diseases, to guide future research and informed scientific decision-making.

MATERIALS AND METHODS

Data sources and search strategies

The study utilized the Web of Science as its selected data source, and to ensure the completeness and accuracy of the retrieved data, the “citation index” was specifically set to SCI-EXPANDED. The Web of Science is widely recognized as the premier database for bibliometric analysis and has been endorsed by most scholars as a top-tier digital literary resource database. We performed a literature search using the Web of Science Core Collection (WoSCC) database. Figure 1 details the retrieval procedure, and all retrieved records were downloaded in ‘plain text’ format. We restricted the literature category to ‘article or review,’ the language to ‘English,’ and included free terms related to Alzheimer’s disease and liver disease (Supplementary Material). First, we searched for terms related to Alzheimer’s disease (#1) and liver disease (#2 to #8), then combined the liver disease terms (#2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8) to form #9. Finally, we combined #1 and #9 to obtain the result: 2,333 articles and 1,057 reviews. We examined the titles, abstracts, and full texts of the papers to exclude those not relevant to our subject matter, resulting in 1,777 articles for analysis. We used VOSviewer, CiteSpace, and Pajek for visualization analysis. Data extraction and analysis focused on ‘Countries, Institutions, and Journals,’ ‘Cited and Co-cited Authors,’ ‘Cited and Co-cited References,’ and ‘Keywords.’

Fig. 1

Diagram of literature retrieval processes.

Statistical analysis

For visual analysis in this study, the following software tools were utilized: VOSViewer (version 1.6.19), CiteSpace (version 6.2.R3), Pajek, and Scimago Graphica.

CiteSpace, a Java-based software program for scientometrics and data visualization, has been used to depict the distribution, trends, and connections of scientific knowledge. 35 This tool generates author, literary, and other visual networks, calculates betweenness centrality, detects bursts, and identifies shifts in current research hotspots and emerging trends. 36 In this study, it was applied to analyze cited articles and keywords. VOSViewer is a free computer application capable of creating and displaying visual bibliometric charts using online data. It systematically comprehends the development and structure of scientific research. 37 Pajek is an advanced tool designed for analyzing intricate nonlinear networks, providing extensive capabilities for examining complex networks. Our study used it to enhance the VOSViewer’s ability to create visually appealing and easily understandable visualizations. Scimago Graphica, a novel approach to data exploration and visual communication, was used to produce a visualization of the published country map.

RESULTS

Annual publications and trends

The number of published works over each span indicates the focus of study in that field. According to Fig. 2A, there has been an overall increase in the number of yearly publications. The data indicates an increasing academic focus on researching AD and the liver and its related diseases in recent years.

Fig. 2

Panel A shows the number of articles published varied by year, and panel B shows the visualization of authors related to Alzheimer’s disease and the liver and its diseases. Panel C shows the Visual Analysis of the most cited references, nodes are sized according to the number of citations. Panel D shows the Visual Analysis of the cluster of cited references.

Analysis of authors and co-cited authors

Emphasizing the significant contributions made by prominent scholars, particularly those who have authored multiple frequently referenced articles in specific domains, can assist academics in their progress and provide further guidance. 38 A total of 9987 authors contributed to the literature on AD and the liver and its related diseases. Supplementary Table 1 shows the top 20 most productive authors in this field, highlighting their contributions. We used VOSviewer to generate a density image of the core author collaboration network (Fig. 2B). To enhance clarity, the network was designed to showcase the collaboration of 256 authors who each contributed to at least 3 articles. The size of each node corresponds to the number of studies authored by the individual, with larger nodes indicating a greater number of published articles. The degree of collaboration between the two authors is reflected in the proximity of their nodes. Network visualization demonstrates that each cluster provides information about the research field’s representative scientists and core strengths. Author collaborations can be used to identify research cliques, while author analysis can reveal the variations and agreements among researchers on certain study themes. The analysis identified three author groups, with the fusion component of each group exhibiting low significance, indicating a scarcity of connections between the teams.

Analysis of cited and co-cited references

A co-citation connection occurs when two or more articles are referenced simultaneously in one or more subsequent publications. 39 Co-citation analysis involves extracting co-citation relationships from a dataset to measure the relationship between two pieces of literature and reflect the structure and dynamics of the knowledge domain. 40 CiteSpace can visualize these co-occurrences. The co-citation network analysis by CiteSpace (Fig. 2C) shows some of the co-citations, first authors, and years of publication for the references in the 1,777 articles. Each circle in the visualization symbolizes a cited reference, and the size of the circle corresponds to the frequency of citations. The connection between the two circles signifies that both citations are mentioned in the same paper within the articles gathered in this research. Line thickness is positively related to co-citation frequency. The nodes are colored differently to signify different years, while purple rings indicate centrality. Nodes with high centrality are regarded as significant points in the literature. The article authored by Nho K. has the highest number of citations in the WoSCC database. Supplementary Table 2 lists the top 20 most highly cited articles according to CiteSpace. The article titled ‘Association of Altered Liver Enzymes with Alzheimer Disease Diagnosis, Cognition, Neuroimaging Measures, and Cerebrospinal Fluid Biomarkers,’ published in JAMA Network Open (IF = 13.8) in 2019, has accumulated 42 citations (Nho K,2019), making it the most cited. The paper titled ‘Liver Dysfunction as a Novel Player in Alzheimer’s Progression: Looking Outside the brain’ by Estrada LD, published in Frontiers in Aging Neuroscience (IF = 4.498), is the second most frequently referenced article. 11

A hierarchical clustering network is established when two publications share several identical references and exhibit a consistent nature. By analyzing co-citations and clustering, we can summarize the research themes in a particular field and explore hotspots and research directions. 41 Figure 2D shows the cluster analysis performed using CiteSpace. The varied colors within the cluster correspond to distinct years, while the size of the cluster indicates the magnitude of citations. The nodes on the map represent the cited references, we identified 13 clusters (Supplementary Table 3): #0 whole brain, #2 high-density lipoprotein, #3 liver cirrhosis, #4 beta-amyloid accumulation, #5 altered cholesterol metabolism, #6 mean age, #7 NDS-treated HFD mice, #8 countering neurodegenerative disorder, #9 seladin-1 gene promoter, #10 RXR Agonist, #11 bile acid, #12 liver function, #15 brain. Among all clusters, “ whole brain “ (cluster #0) contained the most articles, with 29 articles. The most cited article in this cluster is “ Formation and function of apolipoprotein e-containing lipoproteins in the nervous system “, which discusses the role of APOE in the brain, particularly AD. 42

The profile value (S) indicates the average contour value of the cluster. Typically, if S > 0.5, the clustering is considered accurate, and if S > 0.7, it is deemed highly persuasive. In our paper, each cluster had a weighted mean silhouette value of 0.949 or higher, indicating that the quality of the clusters was acceptable.

Analysis of keywords

Keywords are standardized terms selected from the title and text to accurately depict the subject of the paper. 43 They are used to precisely identify research frontiers and hot spots, making them an effective tool for bibliometric analysis. In addition to search phrases, the keywords derived from the titles and abstracts of 1,777 papers were examined using VOSviewer. A total of 9,208 keywords were retrieved, of which 151 keywords appeared more than twenty times, we specifically chose the top 151 keywords that had a minimum of 20 occurrences to create a co-occurrence network (Fig. 3A). As shown in Fig. 3A and Supplementary Table 4, the phrase “Alzheimer’s disease” had the highest number of co-occurrences, totaling 912, followed by “oxidative stress,” “brain,” “mouse model,” “insulin-resistance,” “inflammation,” and “amyloid-beta.”

Fig. 3

Panel A shows the visualization of keywords on Alzheimer’s disease and the liver and its diseases, panel B shows the Visual Analysis of the cluster of keywords, and panel C shows the keyword timeline graph in Alzheimer’s disease and the liver and its diseases. Panel D shows the keyword time zone map for Alzheimer’s disease and the liver and its diseases.

In CiteSpace, we found that these keywords are grouped into 18 clusters (Fig. 3B) based on the similarity of their co-occurrence patterns. These clusters include #0 subchronic toxicity, #1 neuroinflammatory modulator, #2 anthocyanin-rich mulberry, #3 neuroprotective effect, #4 apoe level, #5 obesity hepatic steatosis neuroinflammation, #6 other amino acid, #7 cardiovascular diseases, #8 incident dementia, #9 target-directed ligand, #10 lipoxins resolvins protectins maresin, #11 cholesterol metabolism, #12 potential NMDA ligand, #13 risk factor, #14 incident dementia cognition, #15 Wilson’s disease, #16 oxidative damage, and #17 AD mice. Nodes with the same color within a cluster suggest a strong relationship in terms of co-occurrence. The size of the nodes and the breadth of the linkages vary depending on the level and intensity of co-occurrence. Betweenness centrality measures the importance of nodes in a network, where larger nodes and higher total connection strength indicate a greater volume of information transmitted.

After conducting a comprehensive investigation into these clusters, we observed that each cluster focuses on specific study content. The major citing article of cluster #9 is “Associations between liver function and cerebrospinal fluid biomarkers of Alzheimer’s disease pathology in non-demented adults: The CABLE study”. This article proposes a connection between abnormal liver function and the development of AD, both clinically and pathologically, suggesting that amyloid and tau pathology may link liver function to cognitive decline. 44 The major citing article of cluster #13 is “Alcohol as a Modifiable Risk Factor for Alzheimer’s Disease-Evidence from Experimental Studies”. This article describes how alcohol-mediated liver injury may significantly affect brain Aβ levels by altering peripheral and central Aβ homeostasis. 45

The primary function of the terms “time zone map” and “the timeline diagram” are to facilitate the rapid understanding of the progression of a particular field and enable the prediction of its future trajectory, especially for beginners. The timeline visualization of keyword clustering is illustrated in Fig. 3C, while the time zone visualization is shown in Fig. 3D. The nodes in these diagrams represent the terms, and connections among nodes indicate co-occurrence relationships. The various colors indicate different years, and the size of the nodes corresponds to frequency, with larger nodes representing greater frequencies. Purple rings signify centrality, indicating nodes of significant importance in the literature. Red circles represent burst keywords, such as liver x receptor, cholesterol homeostasis, brain insulin resistance, andamyloid-beta.

Analysis of countries/regions and analysis of institutions

A total of 2,517 institutions from 80 distinct countries/regions contributed papers on AD and liver and its related diseases. We ranked 20 high-productivity countries/regions and institutions as shown in Supplementary Table 5. The United States leads in productivity with 528 articles, followed by China (411 articles), Germany (130 articles), Italy (108 articles), and Japan (107 articles). The USA and China are major contributors in this field, as evidenced by their citation counts of 30,825 and 12,635, which surpass those of other countries including Germany (6,750), Italy (6,116), and the United Kingdom (6,069). Figure 4A and 4B depict the collaboration relationships among the top-ranked countries using VOSviewer and Scimago Graphica. The minimal inclusion requirement was set at 5 papers per nation; a total of 48 countries met this criterion. In the visualization, each country is represented as a circle, with the circle’s size directly correlating to the country’s level of participation in terms of co-authorship. Lines symbolize the connections between nations, and the width of the line signifies the intensity of cooperation between the two countries. Significant collaboration and exchanges are observed, especially among the United States, China, and Japan. Among the 80 countries engaged in international collaborations, the United States leads with 358 collaborations, followed by Germany with 181collaborations.

Fig. 4

Panel A shows the visualization of countries related to Alzheimer’s disease and the liver and its diseases. The size of the nodes corresponds to the number of publications, the lines represent collaboration, and the line thickness represents the intensity of connections. Panel B shows the extent of international cooperation between nations with Alzheimer’s disease and the liver and its diseases. Panel C shows the visualization of institutions related to Alzheimer’s disease and the liver and its diseases. The size of the nodes corresponds to the number of publications, the lines represent collaboration, and the line thickness represents the intensity of connections. Panel D shows the visualization of journals related to Alzheimer’s disease and the liver and its diseases. The size of the nodes corresponds to the number of publications, the lines represent collaboration, and the line thickness represents the intensity of connections.

These published articles originate from 2,517 institutions worldwide. The top 20 high-productivity institutions in AD and liver and its related diseases research are presented in Supplementary Table 5, with most of them located in China. The Chinese Academy of Sciences has the highest number of published articles, with 28, followed by Harvard Medical School (20 articles) and Karolinska Institute (20 articles). In the collaboration network shown in Fig. 4C, the minimum inclusion threshold was set at 6 documents per country; a total of 133 institutions met this threshold. The most influential institutions are the Chinese Academy of Sciences and Karolinska Institute, each with 26 total links. Despite active cooperation between certain countries and institutions, most nations and research institutes are dispersed and lack continuous and widespread collaboration.

Analysis of journals

To identify the most productive and significant journals, we utilize VOSviewer software to analyze the published articles about AD and liver and its related diseases (Fig. 4D). The results indicated that a total of 1,777 articles were published across 720 academic journals. Supplementary Table 6 shows the top 20 most productive journals in this field. Among them, Journal of Alzheimer’s Disease, with an impact factor of 4.1, released 61 relevant papers, contributing to 3.43% of all publications, followed by International Journal of Molecular Sciences with 27 articles (1.99%), PLoS One with 33 articles (1.85%), Nutrients with 25 articles (1.40%), and Frontiers in Aging Neuroscience with 23 articles (1.29%). The analysis of journal co-citations reveals the contribution of each journal to this field. The co-citation network of journals visualized using VOSviewer visualization (Fig. 4D), shows that the three most significant publications with the most co-citations are the International Journal of Molecular Sciences, the Journal of Alzheimer’s Disease, and the Journal of Neuroscience.

Figure 5 shows the Journal double maps. These maps display the citation connections between journals and the co-cited journals, along with the primary fields in which they are concentrated. The left side represents the group of journals that give citations, while the right side represents the group of cited journals. The orange path corresponds to the primary citation pathway, illustrating the scientific studies produced in the field of Molecular/Biology/Genetics that were predominantly referenced by the literature in Molecular/Biology/Immunology. The green path represents another primary citation pathway, encompassing research in Molecular/Biology/Genetics that was predominantly cited by literature in Medicine/Medical/Clinical.

Fig. 5

The journal double maps Alzheimer’s disease and the liver and its diseases.

DISCUSSION

General overview

To the best of our knowledge, this is the first global investigation of trends in the liver-brain axis in AD using bibliometric analysis. Based on publishing output trends, the number of papers focusing on AD and liver and its related diseases has been increasing rapidly. Our study shows that the United States and China have made significant contributions to this field. Universities are the most common research institutions, with nearly half of the top 20 located in China. However, there remains a disparity in the impact of publications between China and the United States, suggesting that the overall quality of publications in China is lower compared to the United States. Thus, China must increase the output of high-level research. Journal publication analysis reveals significant enthusiasm for the field in journals such as the Journal of Alzheimer’s Disease, International Journal of Molecular Sciences, PLoS One, and Nutrients. According to a visual analysis of authors in the field, Suzanne M. de la Monte has the highest quantity of publications on this topic, and has greater influence. In 2009, she published an article titled “The liver-brain axis of alcohol-mediated neurodegeneration: role of toxic lipids”, detailing how alcohol abuse crosses the BBB through toxic lipids, creating a neurodegenerative liver-brain axis that leads to progressive white matter degradation and cognitive dysfunction. 28 Gary E. Landreth, whose work over the past 20 years has focused on the major genetic risk factors for AD, has shown that targeting the LXR and PPAR pathways may be an effective treatment for AD.46,47, 46,47 The efforts of these authors have made an outstanding contribution and offer hope for forthcoming medical therapy.

Based on an analysis of cited and co-cited references, we found that “Association of Altered Liver Enzymes with Alzheimer Disease Diagnosis, Cognition, Neuroimaging Measures, and Cerebrospinal Fluid Biomarkers “is the most cited frequently. This study is the first to demonstrate a correlation between peripheral measures of liver function and a brain biomarker attributed to AD. It shows that liver function biomarkers (total bilirubin, albumin, alkaline phosphatase, alanine aminotransferase, and aspartate aminotransferase) can accurately predict neurodegeneration. These findings will help healthcare providers evaluate patients with abnormal liver function to detect early Alzheimer’s symptoms 12 and provide a new avenue for scientists to develop early diagnosis and prevention strategies for AD. Based on keyword analysis, “insulin-resistance” “amyloid-beta” “apolipoprotein-e” “oxidative stress” “inflammation", and “cholesterol” appear frequently and have strong total link strength. This suggests that these topics have been the focus of research on the liver and liver disease in AD, indicating a growing link between the liver and AD.

The liver-brain axis in AD

There is growing interest in whether targeting the liver-brain axis could be a potential therapeutic approach for treating AD. Many scholars have devoted themselves to this research. In 2020, Margaret et al. provided evidence that the liver is the origin of brain Aβ deposits and is involved in peripheral clearance of circulating Aβ from the blood. 48 Schindler et al. demonstrated a positive correlation between systemic levels of Aβ in the blood and both the amyloid accumulation in the brain and cognitive deterioration in AD. 26 However because the peripheral and brain sources of Aβ are indistinguishable, they did not test whether peripherally produced Aβ could cause the disease. In 2021, researchers from Curtin University, Australia genetically engineered mice to restrict the expression of these genes to hepatocytes (hepatocyte-specific human amyloid strain) to differentiate between Aβ synthesized by the liver and Aβ produced in the brain and elsewhere. Their results showed that Aβ produced by the liver can enter the brain and cause neurodegeneration. 49

We then describe the mechanisms by which the liver-brain axis influences AD (Fig. 6). LRP-1 is an endocytotic and signal transduction receptor expressed in various tissues, including cell surfaces, and its soluble form in plasma.50,51, 50,51 It is essential for clearing Aβ from the brain and throughout the body. In 2022, Huang et al. suggested that hepatic dysfunction may elevate the risk of AD through multiple pathophysiologic mechanisms. 52 Under pathological conditions, a decrease in LRP-1 hinders the clearance of Aβ in the liver,53,54, 53,54 and the liver’s capacity to produce fibroblast growth factor 21 55 may be impaired. This results in a decreased replenishment of fibroblast growth factor 21 in the brain, diminishing its protective effects on the astroglia-neuron-lactic acid shuttle system and other brain tissue. 56 Liver growth factor, a liver albumin-bilirubin complex,57,58, 57,58 reduces Aβ content, phosphorylated tau/tau ratio, and the number of Aβ plaques larger than 25μm in diameter, while also regulating protein ubiquitination and HSP70 protein levels. 59 In 2023, Wu et al. found that liver-soluble epoxide hydrolase targets the liver-brain axis to regulate plasma 14,15-EET 60 levels, which can rapidly cross the BBB and regulate brain antibody metabolism. 61 This pathway, initiated through the liver, suggests that 14,15-EET may be a critical connection to the liver-brain axis in maintaining brain Aβ homeostasis. 62 Overall, impaired hepatic peripheral Aβ clearance and abnormalities in hepatic physiological processes may contribute to AD neurodegeneration.

Fig. 6

The mechanisms by which the liver-brain axis in Alzheimer’s disease. In liver dysfunction, the reduction of LRP-1 impedes the clearance of Aβ from the liver, and the liver’s ability to synthesize FGF21 may also be impaired, affecting the astroglia-neuron-lactic acid shuttle system via the PP2A/MAPKs/HIF-1a pathway and leading to tau protein phosphorylation. LGF administration resulted in the phosphorylation of tau protein and the number of Aβ plaques larger than 25μm in diameter. And ketogenic interventions can improve cognition. Hepatic sEH regulation can bidirectionally regulate plasma levels of 14, 15-epoxide dicartrienoic acid (-EET), and 14,15-EET can rapidly cross the blood-brain barrier and regulate brain Aβ metabolism through multiple pathways.

Furthermore, research has established a connection between AD and certain liver conditions. Infection with the Hepatitis C virus (HCV) is a major cause of serious liver diseases such as chronic hepatitis, cirrhosis, and hepatocellular carcinoma. 63 According to a cohort study, HCV may increase the risk of developing AD. 64 APOE is a key participant in Aβ homeostasis and plays an essential function in the maturation of HCV particles. 65 HCV may cause neuroinflammation by penetrating the BBB. 66 A recent report indicated that a higher ratio of aspartate aminotransferase to alanine aminotransferase, a predictor of cirrhosis in patients with chronic HCV infection, was associated with a diagnosis of AD. 12 NAFLD is identified when more than 5% of hepatocytes are steatotic, without other causes for fat accumulation in the liver. 67 It is the leading cause of liver disease worldwide. 68 The clinical syndrome of NAFLD ranges from bland steatosis to steatohepatitis, which can progress to fibrosis and cirrhosis. 69 In NAFLD, the accumulation of lipids in hepatocytes and infiltration of inflammatory immune cells results in hepatocyte injury and stimulates the sustained secretion of pro-inflammatory cytokines and chemokines into the systemic circulation, leading to low-grade systemic inflammation. This inflammation increases cytokines and upregulates pro-atherogenic transcription factors, which recruit monocytes and other immune cells to cross the BBB and infiltrate the brain, inducing neuroinflammation and disrupting brain function. 70 Recent research has started to consider NAFLD when assessing dementia, and hepatocytes are now being explored as potential biomarkers for AD. 71 There is also an increasing amount of research on AD and liver and its related diseases, with evidence suggesting that staging of liver disease severity and assessing secretory liver factors may be useful in diagnosing neurodegenerative diseases.

The above research indicates that the liver-brain axis may significantly impact the initiation or progression of AD. Further clinical investigations should prioritize determining whether the liver-brain axis plays a pivotal role in initiating AD or merely expedites its progression. Additionally, research should explore whether targeting the liver-brain axis can be an effective treatment for AD.

Limitation

This study is the first attempt to describe the liver-brain axis in AD. It provides a rapid overview of the study subjects, research hotspots, and trends in the areas of the liver-brain axis in AD through bibliometric analysis based on literature. However, our study has its limitations. Firstly, the data are exclusively from the WoSCC database, potentially omitting relevant studies from other databases. Secondly, most articles are published in English, which may introduce selection bias regarding publicationlanguage.

Conclusion

The liver-brain axis in AD has become an emerging area of research; however, current studies are limited, and many questions remain unanswered. For example, although research has shown a connection between liver pathology alterations and AD, there is still a limited understanding of the specific roles that various types and severities of liver pathology play in the evolution of AD. A deeper understanding of the liver-brain axis in AD might open new avenues for the early detection and treatment of AD. If treatment strategies and interventions targeting the liver-brain axis can be effectively implemented in clinical settings, they may significantly benefit individuals with AD and reduce the related societal and economic burden.

AUTHOR CONTRIBUTIONS

XinLian Liu (Conceptualization; Writing – review & editing); Jianishaya Yeerlan (Conceptualization; Data curation; Visualization; Writing – original draft); Zhirong Liu (Conceptualization; Formal analysis; Writing – review & editing); Qin Wang (Methodology); Yang Bai (Investigation); YiRui Yan (Formal analysis); LuKe Xu (Software); Cui Jia (Project administration); LuShun Zhang (Funding acquisition).

Footnotes

ACKNOWLEDGMENTS

The authors have no acknowledgments to report.

FUNDING

This work was supported by the National Natural Science Foundation of China (No.81401161), the Open Project of Development and Regeneration Key Laboratory of Sichuan Province (23LHPDZYB07); Sichuan Provincial College Student Innovation and Entrepreneurship Training Program Project (S202313705089, S202413705092, S202413705087).

CONFLICT OF INTEREST

There are no conflicts of interest that the authors are required to disclose.

DATA AVAILABILITY

The data supporting the findings of this study are available within the article and its supplementary material.

The supplementary material is available in the electronic version of this article: .

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