Astrocytes in Alzheimer's Disease: Scientometric Analysis of 40 Years of Research

introduction: 1.Introduction Alzheimer's disease (AD) is a common neurodegenerative disorder affecting millions worldwide, particularly older adults1. It is characterized by progressive cognitive decline, memory loss, and impaired reasoning and communication. The pathology of AD involves amyloid-β (Aβ) plaques, neurofibrillary tangles, and neuroinflammation. Despite advancements in understanding these markers, the exact mechanisms of AD remain partially understood, driving ongoing research into its contributors and modulators2. Astrocytes, a prevalent type of glial cell in the central nervous system CNS, play a key role in maintaining CNS homeostasis and are increasingly recognized as crucial players in AD pathogenesis3. Their roles in AD include Aβ clearance4, synaptic regulation5, neuroinflammation modulation6, and blood-brain barrier(BBB) maintenance7. Astrocytes interact with neurons and microglia, influencing neuroinflammation and synaptic dysfunction—both significant factors in AD progression8-11. Depending on their phenotypic states and external stimuli, astrocytes can either protect against or contribute to neurodegeneration, highlighting their dual role in AD pathology. Understanding this dual nature could open therapeutic opportunities aimed at enhancing astrocytic protective functions while reducing their detrimental effects. Despite progress in understanding astrocytes' role in AD, there have been limited comprehensive bibliometric assessments of the research landscape12. Systematic mapping is an emerging technique that evolves from systematic reviews, aiming to categorize research within a broad subject area. Bibliometrics involves a quantitative assessment of the scientific knowledge structure based on citation data, essentially serving as a performance evaluation. The integration of bibliometrics and systematic mapping occurs through scientometric analysis, which seeks to chart scientific knowledge by examining performance metrics, influence, and research trends over time. To date, no scientometric analysis has focused specifically on astrocytes in AD. This study aims to fill that gap by applying bibliometric methods to analyze and visualize relevant literature, summarize the field's evolution, explore current research hotspots, and identify future research directions. Our primary objective is to evaluate the evolution of astrocyte research in AD over the past four decades, using co-citation network analysis to highlight pivotal studies and emerging trends. We also aim to map the research landscape by quantifying contributions from countries, institutions, authors, and journals. Ultimately, this analysis seeks to identify current gaps and opportunities, providing valuable insights for future research and policy development in AD. materials and methods: 2.Methods 2.1. Database and Search strategy The Web of Science Core Collection (WoSCC), a widely used dataset in bibliometrics13, was retrieved for this study. Figure 1 provides a detailed explanation of the data retrieval and exclusion criteria. Initially, searches were conducted using terms related to astrocytes based on MeSH in the title(TI) (29,068 results), abstract(AB) (63,953 results), and author keywords(AK) (22,964 results), which were then combined to yield 76,213 results. Astrocytes-related terms= (Astrocyte* OR Astroglia* OR Cell, Astroglia* OR Astroglial*).A similar search for AD-related terms based on MeSH was performed in the TI (101,515 results), AB(169,750 results), and AK (91,512 results). AD-related terms=((Alzheimer Disease* OR Alzheimer Syndrome OR ATD OR Alzheimer Type Dementia OR Dementia, Alzheimer-Type OR Alzheimer's Diseases OR Alzheimer Diseases OR Alzheimers Diseases OR Alzheimer Dementia OR Alzheimer Demen* OR Dementia, Alzheimer OR Dementia, Senile OR Senile Dementia OR Dementia, Alzheimer Type OR Alzheimer Type Dementia OR Senile Dementia, Alzheimer Type OR Alzheimer Type Senile Dementia OR Primary Senile Degenerative Dementia OR Alzheimer Sclerosis OR Sclerosis, Alzheimer OR Dementia, Primary Senile Degenerative OR Dementia, Presenile OR Presenile Dementia OR Acute Confusional Senile Dementia OR Senile Dementia, Acute Confusional OR Alzheimer Disease, Early Onset OR Early Onset Alzheimer Disease OR Presenile Alzheimer Dementia OR Alzheimer Disease, Late Onset OR Late Onset Alzheimer Disease OR Alzheimer's Disease, Focal Onset OR Focal Onset Alzheimer's Disease OR Familial Alzheimer Disease OR Alzheimer Disease, Familial OR Familial Alzheimer Diseases)).These Alzheimer-related results were merged and producd 213,924 records. Finally, the two combined datasets were intersected, resulting in 6,292 relevant records. Data were collected on September 21, 2024. Exclusions were applied to remove Proceeding Papers, Corrections, Early Access articles, News Items, Book Chapters, Retractions, Reprints, Biographical Items, Book Reviews, Meeting Abstracts, Editorial Materials, and Letters. Only articles and reviews in English were retained. Ultimately, a total of 5,384 studies were included for further analysis (Figure 1). 2.2. Data processing The data covered the period from 1 January 1984 to 21 September 2024, with the data segmented into one-year time slices for detailed analysis. All records from the WoSCC were exported as "full records and cited references" in plain text format and Tab format14.Initial data was conducted using Microsoft Excel 2021 (version 16.48) and Online Analysis Platform of Literature Metrology (OALM) (http://bibliometric.com/). Python 3.13 was utilized to analyze annual publication trends, total publications per year, and the fitted trend curve (Figure 1). CiteSpace (6.2.4R, 64-bit Advanced Edition) was employed to generate knowledge maps and cluster analysis of institutions, documents, references and keywords. Additionally, VOSviewer (1.6.20) applied full counting to produce visual representations for authors, journals and collaborative network analysis15. The bibliometrix R package was used to perform historiographic analysis by tracking trends in journals and authors, as well as calculating key metrics such as the g-index16, h-index17, number of citations (NC), and number of publications (NP)18. results: 3.Results 3.1. The Number of Publications and General Characteristics Figure 2A displays the annual count of publications and corresponding citations from 1984 to 2024. The number of publications has increased steadily over the years, reaching over 489 by 2022. The number of citations, on the other hand, surged significantly starting in the early 2000s, peaking at nearly 40,000 in 2022 and 2023. Notably, these documents exhibit an impressive annual growth rate of 15.6%, indicating a robust increase in scholarly outputs. The significant decline in the volume of documents in 2024 may be due to the fact that the data only included records up to September 21, 2024. As of the retrieval date, 5,834 papers sourced from 798 different sources were published over the last 40 years. Among them, articles account for the majority. There were 4,689 articles, accounting for 80.38%, and 1,145 reviews, accounting for 19.62% of the papers (Figure 2B, Table S1). Additionally, figure 2C shows the cumulative number of publications over the study period, depicting an exponential growth trend that is consistent with the general rise in scientific productivity. To further understand this growth, Price's Law was applied to fit an exponential growth model (Figure 2D), yielding a high correlation coefficient (R² = 0.8316), which confirms the exponential nature of publication trends in this field. 3.2. Analysis of Cooperation between Countries Our analysis of WoSCC data reveals that, over the past 40 years, 5,834 publications originated from 76 countries, highlighting the collaborative nature of research worldwide. The country collaboration map (Figures 3A, 3B) illustrates strong international partnerships, particularly between the U.S., Europe, and Asia. The United States leads in academic output, contributing 1,640 articles (28.1%) from 1984 to 2024—far exceeding other nations like Japan and China, which produced 802 (13.7%) and 337 (5.8%) articles, respectively (Figure 3F). Figure 3B emphasizes the strategic importance of certain countries in the research network, reflecting the network visualizations in Figure 3A. Figure 3C presents the article production trends for China, Germany, Italy, Japan, and the U.S., which are the top five countries with the highest number of publications. The U.S. shows steady growth and maintains its leading position, while China has experienced significant growth, particularly from the early 2000s, positioning itself as a major player in academic publishing. Japan also shows growth after 2000 but still lags behind China's output. The analysis of the most cited countries further emphasizes impact, with the U.S. leading in both the number of publications and citations (157,217), followed by China (22,229) and the United Kingdom (21,099) (Figure 3D). There is also a notable trend toward increased multiple-country collaborations, indicating a shift toward more globalized research efforts (Figures 3A, 3B, 3F). Figure 3E shows the annual publication count for each country, further reaffirming the leading position of the U.S. Figure 3F distinguishes between single-country publications (SCP) and multiple-country publications (MCP). The U.S. dominates in both SCP and MCP, showcasing its strength in both independent research and international collaborations. China follows closely, particularly in S