Introduction: Stem cell-based regenerative medicine has provided an excellent opportunity to investigate therapeutic strategies and innovative treatments for Alzheimer’s disease (AD). However, there is an absence of visual overviews to assess the published literature systematically. Methods: In this review, the bibliometric approach was used to estimate the searched data on stem cell research in AD from 2004 to 2022, and we also utilized CiteSpace and VOSviewer software to evaluate the contributions and co-occurrence relationships of different countries/regions, institutes, journals, and authors as well as to discover research hot spots and encouraging future trends in this field. Results: From 2004 to 2022, a total of 3,428 publications were retrieved. The number of publications and citations on stem cell research in AD has increased dramatically in the last nearly 20 years, especially since 2016. North America and Asia were the top 2 highest output regions. The leading country in terms of publications and access to collaborative networks was the USA. Centrality analysis revealed that the UCL (0.05) was at the core of the network. The Journal of Alzheimer’s Disease (n = 102, 2.98%) was the most productive academic journal. The analyses of keyword burst detection indicated that exosomes, risk factors, and drug delivery only had burst recently. Citations and co-citation achievements clarified that cluster #0 induced pluripotent stem cells, #2 mesenchymal stem cells, #3 microglia, and #6 adult hippocampal neurogenesis persisted to recent time. Conclusion: This bibliometric analysis provides a comprehensive guide for clinicians and scholars working in this field. These analysis and results hope to provide useful information and references for future understanding of the challenges behind translating underlying stem cell biology into novel clinical therapeutic potential in AD.

© 2023 S. Karger AG, Basel

Introduction

The most frequent cause of dementia, Alzheimer’s disease (AD), is a progressive debilitating neurodegenerative disorder that causes great suffering for both patients and their families [1, 2]. Clinically, the course of AD leads to memory loss, impaired judgment, confusion, a loss of language and logical thinking, dementia in the later stages, and ultimately death [3]. Additionally, by 2050, the prevalence of AD is predicted to double in Europe and treble worldwide [1]. In this situation, the public health community is concentrating efforts on the prevention and treatment of this epidemic disorder.

Growing evidence suggests that the development of AD is a complex syndrome that arises from multiple factors with various molecular targets, but the detailed pathogenesis of AD is still unclear so far [4–6]. Over decades of research, many hypotheses on the etiology of AD have been developed [7], including amyloid cascade (amyloid burden), tau hyperphosphorylation (hyperphosphorylated tau proteins), cholinergic hypothesis (cholinergic deficit), mitochondrial dysfunction (decline in base line and rate of mitochondrial function), oxidative stress (chronic oxidative exposure), and neuroinflammation (chronic inflammatory insult) (shown in Fig. 1). On the basis of these assumptions, several efforts have been made to design some efficient treatments [7–11]. In general, there is a lack of an acceptable and effective therapy as well as a logical chronological order of the events in AD. Due to this unmet medical need as well as AD’s effects on society, the healthcare system, individuals, and researchers have been challenged to better understand AD and develop more efficient management strategies.

Fig. 1.

Hypotheses on the etiology of Alzheimer’s disease (AD). This figure overviews possible hypotheses on the etiology of AD, including amyloid cascade, tau hyperphosphorylation, cholinergic disruption, oxidative stress, mitochondrial dysfunction, and neuroinflammation.

Since the pioneering study paved the way for stem cell implantation as a therapy for damaged brain by Rosenberg [12], the application of alternate cell tissue sources and the development of new stem cell technologies in recent years have pointed to intriguing new research possibilities in this field [13–16]. Stem cell-based therapy may be a better approach than traditional therapies, as it can replace injured or lost neuronal cells, secrete neurotrophic factors, reduce amyloid beta (Aß) levels, increase synaptic connections, and improve the microenvironment in the brain fundamentally [17–19]. The possible mechanisms of action are shown in Figure 2. Over the last few decades, scientists have never stopped exploring the stem cell therapy in AD, thus the immense amount of recent research as well as the large number of review articles having reported in this field. However, the US Food and Drug Administration (FDA)-approved clinical trials have a lot of unrealized potential. Additionally, there is an absence of visual overviews to assess the published literature systematically that can assist researchers in obtaining research trends in this field.

Fig. 2.

Possible mechanism of action of stem cells in treatment of Alzheimer’s disease (AD). This figure overviews possible mechanisms of stem cells in the treatment of AD, including promotion of activation of endogenous cells, decrease of amyloid and tau cascade, anti-inflammatory response, replacement of injured or lost neuronal cells, secretion of neurotrophic factors, increase in the connection and recovery of sphingolipid metabolism, and recovery of mitochondrial dysfunction.

Bibliometrics can use mathematical and statistical methods to analyze a large number of documents in a particular research field, which can provide a broad, quantitative, and qualitative overview of a particular topic with a deep background, has grown to be a crucial part of study review [20, 21]. It can aid researchers in understanding the trajectory of a certain field of study, as well as assessing the contributions of journals, institutions, and nations in that field. It can serve as a foundation for the creation of clinical recommendations, particularly in the medical profession [22–26]. To the best of our knowledge, there is no bibliometric study and visualization map on stem cell research in AD. To address this gap, the present study is the first comprehensive scientometric study, aiming to determine and study the characteristics of articles about the global performance and development of stem cell research in AD. By utilizing a visualization tool, you may sum up the most recent developments in this topic, understand its research hot spots, and provide specific references for potential future study directions. Furthermore, urgent collaboration between several academic fields is required to create accurate in vivo neurogenesis detection methods.

MethodsData Collection and Search Strategy

The data of this study were derived from the Science Citation Index Expanded (SCI-Expanded) database of the Web of Science Core Collection (WoSCC), a US institute of scientific information. To have relevant research articles in the WoSCC database, the selection of publications was done prudently and performed on a single day, March 26, 2022, to avoid biases introduced by daily database updating. We used an advanced search strategy of topic search, and the query was “Alzheimer’s disease” (all fields) or “Alzheimer dementia” (all fields) or “Alzheimer dementias” (all fields) or “Alzheimer type dementia” (all fields) or “Alzheimer syndrome” (all fields) AND “Stem cell” (all fields) or “Stem cells” (all fields) AND LANGUAGE (English) AND DOCUMENTTYPES (articles and reviews). A total of 3,593 records from 2004 to 2022 were identified from WoSCC, and those of the following types were excluded: EDITORIAL MATERIAL, MEETING ABSTRACT, CORRECTION, LETTER, NEWS ITEM, RETRACTION. Two authors (Yi Zhu and Lan-Fang Qin) independently searched the WoSCC database for relevant literature and downloaded the relevant information (title, keyword, author information, abstract, publishing journal, reference, etc.) in TXT format. Any divergences were settled by consultation or by seeking the external specialists to reach consensus. Ultimately, a total of 3,428 unique articles were included, imported into bibliometrics, and transferred into CiteSpace and VOSviewer software for bibliometric analysis. The retrieval strategy used in this study is shown in Figure 3.

Fig. 3.

The retrieval strategy used in this study.

Analysis Tool

The exported data were then imported into CiteSpace 5.8.R3, 64-bit (Drexel University, Philadelphia, USA) [27, 28] and VOSviewer 1.6.16 (Leiden University, Leiden, Netherlands) [29, 30]. The bibliometric online analysis platform (http://bibliometric.com/) was then used to identify co-cited articles, keywords, countries, institutions, journals, authors, and network characteristics of keyword bursts and to visually present the results. It contained all the documents indexed by SCI-EXPANDED since 1950. Before performing the co-word analysis and document co-citation analysis, we employed CiteSpace’s “eliminating duplicates function.” As a result, the final dataset had two duplicates. Using Microsoft Excel (version 16.46), a simple descriptive analysis was carried out (such as the number of publications per year, publications with the most citations, etc.). To determine the distribution of countries and regions, academic journals and co-cited academic journals, authors and co-cited authors, keyword bursts and their trends, and co-cited references, CiteSpace or VOSviewer were used. Detailed procedures of the enrollment and analysis are illustrated in Figure 4.

Fig. 4.

Flow diagram of the included publications and methods of bibliometric analysis.

ResultsAnalysis of the Publication Characteristics and Citation Trends

In this study, Figure 5a shows an upward trend and the related literature on stem cell research in AD might be roughly divided into three stages, being an important bellwether to evaluate the current situation, development trend, and prospects of this fields. The period of 2004–2008 was the initial stage of research, when the WoSCC first included an article that was published in Journal of Medicinal Chemistry in 2004 by Coowar et al. [31]. In the 7 years from 2009 to 2015, which represented the second developmental stage, the annual number of articles in this field increased steadily and was relatively small with the maximum being 217, indicating that the development of this field was relatively slow and had a lack of creative breakthroughs in this stage. However, from 2016 to 2021, the publications on stem cell research in AD entered a third stage of rapid development. The total number of publications was 2,402, and the average was approximately 400.3 per year. The annual number of academic articles increased significantly, more than twice that of the second stage. Most likely, between 2009 and 2021, the number of times these studies were cited climbed steadily (shown in Fig. 5a), denoting that stem cell research in AD had received a great deal of attention. This might be attributed to stem cell differentiation technology which began to make breakthroughs in 2016. The model fitting curve indicated a significant correlation between the publications per year and year (R2 = 0.9847). This model predicted that the number of papers in 2022 would be nearly 600 (shown in Fig. 5b). At the same time, the model fitting curve (R2 = 0.9778) estimated the sum of annual citations in 2022 will be nearly 40,000 (shown in Fig. 5c). Geographic distribution maps based on the total publications of different countries are shown in Figure 5d. The top 10 countries/regions were primarily distributed across North America, Asia, Europe, and Australia. North America and Asia were the top 2 highest output regions. For nearly the past 20 years, the countries with the most publications were the USA (1,386), China (686), and England (371). Trends in the annual number of publications in the top 10 countries/regions are also shown in Figure 5e.

Fig. 5.

Distribution of publications and citations from different years. The number of published articles per year and summed total citations of annual publications related to stem cell research in AD from 2004 to 2022. a The number of publications and citations during different years. b The polynomial curve fitting of publications growth. c The polynomial curve fitting of citations growth. d Geographic distribution maps based on the total publications of different countries. e The top 10 countries/regions on stem cell research in AD.

Analysis of Authors and Co-Cited Authors

The impactful authors were appraised by the number of publications in this study. 18,342 researchers were involved in stem cell research in AD. Among these, Wang Y. was the most productive author with 46 articles, followed by Na D.L. (45 articles), Zhang Y. (43 articles), Kim H.J. (35 articles), and Zhao J. (33 articles) (shown in Fig. 6a). In this study, we also evaluated the author contributions by two parameters: the citation count for evaluating the influence of scientists and their papers, and the h-index for determining the quality of a scientist. According to citations in this field, Selkon D.J. ranked first (436 citations), followed by Takahashi K. (375 citations), Hardy J. (314 citations), Braak H. (269 citations), and Zhang Y. (259 citations) (shown in Fig. 6b). In the same light, the h-index of authors, Bennett D.A. ranked first (25), followed by Lipton S.A. (24), Wang Y. (17), Maiese K. (17), and Blurtonjones M. (17) (shown in Fig. 6c). The ability to identify research groups and possible collaborators with the highest impact through the use of a visual map of co-authored publications can also aid in the development of collaborative ties amongst scholars. In this study, VOSviewer was used to visualize authors who had at least five publications and at least 300 citations overall. The results are displayed in Figure 6d. Each node on the graph represented a different author. The size of the circle reflected the number of articles the researcher had produced. The lines linking the circles showed the writers’ collaboration; the thicker the line, the tighter the authors’ cooperation. Figure 6d shows there was a close co-occurrence relationship between authors and co-cited authors, with more prolific authors often co-occurring more with other authors.

Fig. 6.

Author contributions to stem cell research in AD from 2004 to 2022. a Number of publications from different authors. b Total citations in the research filed from different authors. c The h-index of publications from different authors. d Network map of co-authorship between authors with more than five publications.

Analysis of Affiliations Countries/Regions and Institutions

In this study, Figure 7a shows that the top 10 institutions provided a total of 1,408 articles, or 41.07 percent of all the papers. The USA was the leading contributor to stem cell research in AD, publishing nearly 30 percent of all studies. Institutions with =20 publications were used to construct a network map, which showing institutions involved in this field (shown in Fig. 7b). The network map also reflected the state of research activities and communication among these institutions in different countries/regions. The visualization map showed that collaboration between institutions was more extensive than that between countries; for instance, the UCL and Univ Cambridge (England) had close cooperation with Univ Calif Irvine and Harvard Med Sch (USA). The graph of research networks, however, showed that Chinese Acad Sci (China) had a lower density, indicating largely independent research teams and highlighting the need for additional engagement with other institutions in different countries and areas (shown in Fig. 7b). Higher centrality in a collaborative network corresponded to more intense cooperation. The prominence of network nodes was measured by the centrality index. Centrality analysis revealed that the UCL (0.05) was at the core of the network, followed by Univ Cambridge (0.03), Johns Hopkins Univ (0.03), Columbia Univ (0.03), Univ Calif San Francisco (0.03), and Chinese Acad Sci (0.03) (Table 1).

Fig. 7.

Analysis of institutions involved in stem cell research in AD. a The top 10 institutions involved in stem cell research in AD. b A network map shows institutions involved in stem cell research in AD. The color and thickness in the inner circle of the node indicated the occurrence frequency of different time periods.

Table 1.

Ranking of top 10 institutions for collaboration in this research

RankInstitutionsArticles countsCountryCentrality1UCL88England0.052Chinese Acad Sci82China0.033Univ Calif Irvine80USA0.024Univ Calif San Diego79USA0.025Harvard Med Sch78USA0.016Univ Cambridge73England0.037Johns Hopkins Univ71USA0.038Shanghai Jiao Tong Univ67China0.019Columbia Univ66USA0.0310Univ Calif San Francisco61USA0.03Analysis of Journals and Co-Cited Academic Journals

In this study, all publications came from 10,723 different journals, with the Journal of Alzheimer’s Disease (n = 102, 2.98%, IF 2021 = 4.160) publishing the greatest number of articles/reviews, followed by Stem Cell Research (n = 86, 2.51%, IF 2021 = 2.020). Among the top 10 journals (Table 2), 40% (4/10) were from the USA, followed by 20% (2/10) from the Netherlands and Switzerland. Simultaneously, among journals with more than 40 articles, the Journal of Neuroscience (n = 49, 1.43%, IF 2021 = 6.167) had the highest impact factor, followed by the International Journal of Molecular Sciences (n = 83, 2.42%, IF 2021 = 5.923). 232 publications had more than 200 citations, according to the citation network map (shown in Fig. 8a). It was evident that papers in this area were frequently published in a few high-impact journals, indicating that the research in this area at this time was still rather active and cutting-edge. The CiteSpace program was also used to generate the co-occurrence network of subject categories. Figure 8b shows that the positive citation linkages between various journals, which demonstrating co-citations and annotating cited journals based on citation frequency. The dual-map overlay of journals in Figure 8c showed the journals’ topics distribution. On the map, the citing journals were on the left, and the cited journals were on the right. The fields that the journals covered were indicated by the labels. The colored lines showed the citation paths from left to right. As Figure 8c also shows that there was a distinct orange citation path, which suggesting that studies from Molecular/Biology/Immunology journals were frequently cited in studies from the Molecular/Biology/Genetics journals.

Table 2.

The top 10 productive journals that published articles on stem cell research in AD

RankJournal titleCountryOutput [%]IF (2021)Quartile in category (2021)1Journal of Alzheimer’s DiseaseNetherlands102 [2.98]4.160Q22Stem Cell ResearchNetherlands86 [2.51]2.020Q33PLOS ONEUSA85 [2.48]3.240Q24International Journal of Molecular SciencesUSA83 [2.42]5.923Q25Scientific ReportsEngland74 [2.16]4.996Q16Molecular NeurobiologyUSA61 [1.78]5.590Q17Neural Regeneration ResearchChina50 [1.46]5.135Q28Frontiers in Aging NeuroscienceSwitzerland49 [1.43]5.750Q29Journal of NeuroscienceUSA49 [1.43]6.167Q110Frontiers in Cellular NeuroscienceSwitzerland43 [1.25]5.505Q2Fig. 8.

Analysis of journals involved in stem cell research in AD. a A network map shows academic journals publishing research on stem cell research in AD. b CiteSpace visualization map shows the co-occurrence network of subject categories. c The dual-map overlay of journals involved in stem cell research in AD. The dual map shows the relationships between publications and citations, with dots representing citing journals on the left and cited journals on the right.

Analysis of Keyword Co-Occurrence Related to Research Hot Spots

In this study, research hot spots and frontiers of stem cell research in AD could be identified by analyzing the results of keyword co-occurrence in all 3,428 publications. The overlay visualization map was created using the VOSviewer to evaluate a total of 12,531 keywords that were recognized as occurring more than 25 times with the full counting approach (shown in Fig. 9a). A line linking two keywords served as a sign in the keyword visualization map. Each link’s thickness represented the degree of co-occurrence between two terms. The number of occurrences was represented by the size of the bubble. The colors displayed in the network visualization map indicated the different clusters produced by the keywords, and the high-frequency keywords were Alzheimer’s disease (1167), Mouse model (425), Expression (383), Brain (382), Oxidative stress (336), Stem-cells (332), Neurodegeneration (323), Neural stem-cells (318), Neurogenesis (314), and Amyloid-beta (305). CiteSpace was also used to capture keywords with strong citation bursts. The top 25 keywords with the strongest citation bursts were presented in Figure 9b. The time interval was shown by a blue line, and the burst period was shown by a red reflecting line, which also showed the beginning and ending years as well as the burst time period. In order to concentrate on terms that indicated the trends of stem cell research in AD, keywords with little to no research significance were removed. As Figure 9b showed that, between 2004 and 2022, neural stem cell had the highest burst strength (14.45), followed by subventricular zone (11.39), adult hippocampal neurogenesis (10.96), transgenic mice (10.76), and central nervous system (10.20). However, keywords associated with Alzheimer’s disease, such as subventricular zone, transgenic mice, dentate gyrus, beta catenin, and neural stem cell, began to burst during the early stages. Following that, keywords like neurotrophic factor, nerve growth factor, insulin resistance and marrow stromal cell began to explode, indicating that the study focus had shifted to finding solutions to these perplexing issues. Also worth noting, keywords such as exosomes, risk factor, and drug delivery only had burst recently.

Fig. 9.

Keywords co-occurrence analysis of global research on stem cells in AD from 2004 to 2022. a The overlay visualization map of keywords. The nodes coded with purple and blue color represented the keywords that appeared relatively earlier upon time course before or around 2016, whereas keywords that appeared around 2017 were coded with green color and those frequently used around or after 2018 appeared in yellow. b Keywords with the strongest citation bursts in stem cell research in AD.

Analysis of Co-Cited References and Burst References

In this study, CiteSpace was used to construct the network of co-cited references, resulting in a broad perspective of stem cell research in AD. The Modularity Q (0.7192) and Mean Silhouette (0.91) values were both greater than 0.5. Figure 10a displays the visual network of the citation analysis of publications on stem cell research in AD. A cited article was represented by each node. The links between the nodes represented the number of times the same article was cited. A thick purple ring denoted high centrality, and the node width correlated with the total number of co-cited articles. The red ring denoted the blast of citations in the network. These references which showing in the network map were cited more than 70 times, with the top two receiving more than 100 citations each. For readability purposes, the information in Figure 10a is illustrated in Table 3 below, and the top 10 citation analysis of publications on stem cell research in AD are exhibited. The top 10 most co-cited original articles related to stem cell research in AD are also given in Table 4. The majority of the top 10 included references was published in or after 2016. Only one of these references was co-cited less than 2,000 times.

Fig. 10.

Co-cited references map involved in stem cell research in AD. a CiteSpace visualization map shows the co-occurrence network of co-cited references. The diameter of each node is proportional to the total co-citation counts of the associated article. The thick purple circles in the nodes indicated high centrality. b CiteSpace visualization map shows the cluster of co-cited references. c The top 25 references with the strongest citation bursts from 2004 to 2022.

Table 3.

The top 10 citation analysis of publications on stem cell research in AD

RankReferencesTitleSourceYearCountryCitations1Israel et al. [32]Probing sporadic and familial Alzheimer’s disease using induced pluripotent stem cellsNature2012England1162Kondo et al. [33]Modeling Alzheimer’s disease with iPSCs reveals stress phenotypes associated with intracellular Aß and differential drug responsivenessCell Stem Cell2013USA1013Selkoe and Hardy [34]The amyloid hypothesis of Alzheimer's disease at 25 yearsEMBO Mol Med2016England884Choi et al. [35]A three-dimensional human neural cell culture model of Alzheimer’s diseaseNature2014England815Raja et al. [36]Self-organizing 3D human neural tissue derived from induced pluripotent stem cells recapitulate Alzheimer’s disease phenotypesPLOS ONE2016USA716Keren-Shaul et al. [37]A unique microglia type associated with restricting development of Alzheimer’s diseaseCell2017USA767Muratore et al. [38]The familial Alzheimer’s disease APPV717I mutation alters APP processing and Tau expression in iPSC-derived neuronsHum Mol Genet2014England758De Strooper B and Karran [39]The cellular phase of Alzheimer’s diseaseCell2016USA759Abud et al. [40]iPSC-derived human microglia-like cells to study neurological diseasesNeuron2017USA7310Heneka et al. [41]Neuroinflammation in Alzheimer’s diseaseLancet Neurol2015England72Table 4.

The top 10 co-citation analysis of cited reference on stem cell research in AD

RankReferencesTitleSourceYearCountryCo-citations1Vos et al. [42]Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the global burden of disease study 2015Lancet2016England3,7182Klionsky et al. [43]Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)Autophagy2016USA3,5273Wang et al. [44]Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the global burden of disease study 2015Lancet2016England2,9934Vos et al. [45]Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the global burden of disease study 2016Lancet2017England2,7285Afshin et al. [46]Health effects of overweight and obesity in 195 countries over 25 yearsN Engl J Med2017USA2,7236Liddelow et al. [47]Neurotoxic reactive astrocytes are induced by activated microgliaNature2017England2,5267Naghavi et al. [48]Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the global burden of disease study 2016Lancet2017England2,4188Glass et al. [49]Mechanisms underlying inflammation in neurodegenerationCell2010USA2,1449Forouzanfar et al. [50]Global, regional, and national comparative risk assessment of 79 behavioral, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015Lancet2016England2,06410Hnisz et al. [51]Super-enhancers in the control of cell identity and diseaseCell2013USA1,828

In this study, the co-citation network could also be divided into clusters using CiteSpace, which would then show closely associated references in one cluster and loosely related references in another. Co-citation relevance was examined in 181,294 cited references from 3,428 articles/reviews, and a cluster network graph was produced. Each cluster was identified by words taken from the titles of the citing publications found within the cluster. The top 16 clusters are shown in Figure 10b, including #0 induced pluripotent stem cells (iPSCs), #1 neurogenesis, #2 mesenchymal stem cells (MSCs), #3 microglia, #4 reprogramming, #5 bone marrow-derived microglia, #6 adult hippocampal neurogenesis, #7 insulin, #8 s-nitrosylation, and #9 neural stem cells. Additionally, CiteSpace was used to evaluate the references that had a lot of recent citations. Figure 10c illustrates the top 25 references with the strongest citation bursts from 2004 to 2022. Among the top 25 references with the strongest citation bursts, “Moreno-Jimenez E.P., 2019, NAT MED, V25, P554, DOI 10.10388/S41591-019-0375-9” (2020–2022, strength 22.32), Lin Y.T., 2018, NEURON, V98, P11141, DOI 10.1016/j.neuron.2018.06.008” (2019–2022, strength 14.49), and “Liddelow S.A., 2017, NATURE, V541, P481, DOI 10.1038/nature21029” (2019–2020, strength 13.16) were the recent emergence of high-citation references.

In this study, CiteSpace was also used to create a co-word timeline view. Notably, as illustrated in Figure 11, cluster #1 neurogenesis and #5 bone marrow-derived microglia were mainly included in the early time, and cluster #0 iPSCs, #2 MSCs, #3 microglia and #6 adult hippocampal neurogenesis persisted to recent time, indicating these methods and technologies for AD treatments now. Purple or red rings surrounded certain nodes in the temporal cluster map, signifying high ratings for “betweenness centrality.” The top 10 papers with higher “betweenness centrality” are shown in Table 5, suggesting some emerging trends in this field. Meanwhile, according to the statistical curve of the published article number (shown in Fig. 5a), there was an obvious fluctuation trend in 2009 and 2016. Therefore, combined with the analysis of the above two pieces of information, this study divided the development of stem cell research into three stages.

Fig. 11.

The timeline view of co-cited clusters with cluster labels. This view clearly presents the differences in the appearance time point and time span of clusters.

Table 5.

Cited papers with the highest “betweenness centrality” among the top 10 clusters

RankReferencesTitleSourceYearCentralityCluster #1Shi et al. [52]Human cerebral cortex development from pluripotent stem cells to functional excitatory synapsesNat Neurosci20120.24#02Shi et al. [53]A human stem cell model of early Alzheimer’s disease pathology in Down syndromeSci Transl Med20120.14#13Ballatore et al. [54]Tau-mediated neurodegeneration in Alzheimer’s disease and related disordersNat Rev Neurosci20070.13#64Qian et al. [55]Brain-region-specific organoids using mini-bioreactors for Modeling ZIKV exposureCell20160.13#45Haass and Selkoe [56]Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer’s amyloid beta-peptideNat Rev Mol Cell Biol20070.11#16Duncan and Valenzuela [57]Alzheimer’s disease, dementia, and stem cell therapyStem Cell Res Ther20170.10#0, #97Ashe and Zahs [58]Probing the biology of Alzheimer’s disease in miceNeuron20100.09#48Huang and Mucke [59]Alzheimer mechanisms and therapeutic strategiesCell20120.09#19Sposito et al. [60]Developmental regulation of tau splicing is disrupted in stem cell-derived neurons from frontotemporal dementia patients with the 10 + 16 splice-site mutation in MAPTHum Mol Genet20150.09#410Armijo et al. [61]Increased susceptibility to Aß toxicity in neuronal cultures derived from familial Alzheimer’s disease (PSEN1-A246E) induced pluripotent stem cellsNeurosci Lett20170.09#0, #4Discussion

In AD, the hypothesis of circuit reconstruction in the damaged brain via direct cell replacement has been pursued extensively so far. In this context, stem cells represent a useful option since they repair injured neuronal tissue and provide a conducive environment [17, 62]. Interestingly, current breakthroughs in preclinical research and clinical trials of stem cells in AD have ignited hope for the treatment of this refractory disease [63]. However, there are no reviews to assess the published literature systematically in this field. This paper is, to our knowledge, the first attempt to reveal the knowledge maps of global scientific publications related to stem cell research in AD from 2004 to 2022 by employing a scientometric analysis. Review of these researches nearly the past 20 years highlights current status and hot spots, paying more attention to development trends and exciting frontiers.

General Information on Stem Cell Research in AD

According to statistics from the annual number of publications and citations (shown in Fig. 5a–c), stem cell research in AD has been a surge of interest. The majority of investigations during the initial stage, which spans from 2004 to 2008, used genetically modified animals to imitate the human AD pathophysiology. Since a new method developed by Takahashi and Yamanaka in 2007, iPSCs have revolutionized neurological diseases modeling on account of eliminating ethical concerns and resolving the issue of immune rejection in stem cell transplantation [64, 65]. At the same time, the iPSC approach presents exceptional prospects for patient-specific medication screening and patient-specific patient studies [66–68]. It also reflects in the second stage, from 2009 onward, where the annual number of publications increases steadily and reaches 217 papers for the first time in 2015. In the third stage, which runs from 2016 to 2021, the combination of iPSC-based and 3D bioprinting technologies produces more dependable and realistic cell cultures because of resolving the low efficiency of reprogramming [36, 69, 70] and ultimately accelerates the development of this field.

The USA, China, England, Germany, and South Korea are the top five productive countries in terms of country distribution. North America and Asia have produced the most articles among the top 10 nations (shown in Fig. 5d, e), indicating that these two continents may be potential areas for stem cell research in AD. Based on the data coming from individual publications, Wang Y. (China), Na D.L. (South Korea), Zhang Y. (China), Kim H.J. (South Korea), and Zhao J. (China) have the highest number of individual publications and all make significant contributions to the progression of stem cell research in AD (shown in Fig. 6a). In addition, studies by Selkoe D.J. (USA), Takahashi K. (Japan), Hardy J. (England), Braak H. (Germany), and Zhang Y. (China) have the highest average number of citations, indicating that these authors publ