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. 2026 Sep 26;21:945–954. doi: 10.1016/j.ibneur.2026.09.018

Research landscape of neurodegenerative diseases and brain energy metabolism: A multi-database integrative analysis

Chengxi Weng a,g,1, Xiaomai Huang b,1, Haochen Huang c,d,1, Fang Ke e,f, Lijuan Zhang a, Fengping Xu g, Xiaoli Lin g,⁎
PMCID: PMC13657352  PMID: 42866711

Abstract

Objective

Neurodegenerative diseases are characterized by the progressive degeneration or death of neurons and their myelin sheaths. Increasing evidence suggests that impaired brain energy metabolism is a fundamental mechanism underlying the pathogenesis of these disorders. Therefore, a comprehensive understanding of research trends in this field is essential.

Methods

A bibliometric analysis was conducted using merged and deduplicated data retrieved from the Web of Science Core Collection(WoSCC) and Scopus databases. Publications from 2004 to 2024 related to neurodegenerative diseases and brain energy metabolism were systematically analyzed. Key parameters included publication trends, and contributions from countries, institutions, journals, authors, references, and keywords.

Results

A total of 3639 publications were identified, showing an overall increasing trend over the past two decades. These studies involved contributions from 54 countries or regions and were published across 459 academic journals. The United States and Italy were the leading contributors in this field. Keyword analysis revealed an evolution in research focus, with “microglia,” “inflammation,” and “cognitive decline” emerging as prominent and rapidly developing topics in recent years.

Conclusion

This study provides a comprehensive overview of global research trends in brain energy metabolism in neurodegenerative diseases over the past 20 years. It highlights emerging hotspots and suggests potential future research directions, offering valuable insights for advancing this field.

Keywords: Neurodegenerative diseases, Brain energy metabolism, CiteSpace, VOSviewer, Bibliometric analysis

1. Introduction

Neurodegenerative diseases represent a heterogeneous group of disorders characterized by the progressive and selective loss of neurons, leading to impairments in sensory, motor, and memory functions (Kahroba et al., 2021, Zhou et al., 2020). Alzheimer's disease(AD), Parkinson's disease(PD), Huntington's disease(HD), amyotrophic lateral sclerosis(ALS), and multiple sclerosis(MS) are among the most prominent examples of these conditions (Yaribeygi et al., 2018). According to the World Health Organization's 2022 research blueprint, the prevalence of neurodegenerative diseases in individuals aged 60 and above varies by region: Southeast Asia reports a prevalence of 2.9%, Europe has a prevalence of 6.5%, while other regions show prevalence rates ranging from 3.1% to 5.7% (Zhang et al., 2024). AD, the most prevalent neurodegenerative disorder globally, currently affects an estimated 57 million individuals, with projections indicating a substantial increase to approximately 78 million by 2030 (Nichols and Vos, 2021, Knopman et al., 2021). Over the past few decades, most clinically approved drugs, such as memantine and donepezil, have primarily been used to alleviate symptoms in patients (Adlimoghaddam et al., 2018). However, their limitations differ according to their pharmacological mechanisms. Donepezil, an acetylcholinesterase inhibitor, is mainly associated with cholinergic adverse effects, including gastrointestinal symptoms, insomnia, bradycardia, and syncope, while its benefits in cognitive and functional outcomes are generally modest. In contrast, memantine, an N-methyl-D-aspartate receptor antagonist, is generally well tolerated but may cause dizziness, confusion, and hallucinations, with relatively small and sometimes inconsistent clinical benefits across different outcomes. Therefore, while both drugs provide symptomatic relief, neither has demonstrated a definitive disease-modifying effect or the ability to cure AD (Zhang et al., 2024).

The pathogenesis of neurodegenerative diseases remains unclear. Currently, the prevailing view in the scientific community is that these diseases are associated with multiple interconnected pathological mechanisms, including abnormal protein aggregation, neuroinflammation, oxidative stress, and gut microbiome dysbiosis. Rather than acting independently, these processes may interact through complex molecular pathways. For example, abnormal protein aggregation can activate inflammatory responses and increase oxidative stress, while neuroinflammation and oxidative stress may further impair protein clearance and promote protein misfolding. In addition, gut microbiome dysbiosis may influence neurodegeneration by modulating immune responses, inflammation, and oxidative stress through the gut–brain axis (Amartumur et al., 2024, Chen et al., 2016). Since the 20th century, increasing evidence has pointed to abnormal brain energy metabolism as a core mechanism underlying most neurodegenerative diseases (Jing et al., 2024, Yin et al., 2016). There are regional differences in brain energy production and consumption rates across various types of neurodegenerative diseases. For example, in AD, cortical metabolism is typically reduced in the temporal-parietal cortex, frontal cortex, and posterior cingulate cortex (Ardanaz et al., 2022, Jensen et al., 2020, Meyer et al., 2019). Studies have also shown that patients with HD primarily exhibit a reduction in metabolic rates in the striatal and thalamocortical regions (Pagano et al., 2016).

The relationship between neurodegenerative diseases and brain energy metabolism is a relatively new and rapidly evolving field. In recent years, an increasing number of studies and publications have highlighted its growing prominence. However, to date, no comprehensive analysis has been conducted on the key authors, institutions, research advancements, and emerging trends in this field. To address this gap and leverage our expertise, we performed a bibliometric analysis aimed at systematically synthesizing the existing body of research. This work not only provides a clear framework for newcomers to the field to understand both classical issues and recent developments, but also offers fresh perspectives on potential future research directions. Such insights are particularly crucial for long-standing researchers who have dedicated significant efforts to advancing knowledge in this domain. Bibliometrics, a discipline that employs statistical and mathematical techniques to quantitatively and qualitatively analyze the volume and distribution of literature, has become extensively utilized within the realm of medical research (Kokol et al., 2021). Instruments such as CiteSpace, VOSviewer, and the "bibliometrix" software package are extensively leveraged for the analysis of large-scale unstructured data (Chen, 2006, Van Eck and Waltman, 2010, Derviş, 2019). To our knowledge, there has been no bibliometric analysis specifically addressing the relationship between neurodegenerative diseases and brain energy metabolism to date. Therefore, to address this gap, the present study aims to systematically examine the current landscape and future research directions in the fields of neurodegenerative diseases and brain energy metabolism through bibliometric methods.

2. Methods and materials

2.1. Data searching and literature screening

To explore the research landscape of PD in relation to brain energy metabolism, we conducted a systematic literature search in two major databases: the Web of Science Core Collection(WoSCC) and Scopus. The search strategies were carefully tailored for each database, and the detailed search terms are provided in Supplementary Tables 1,2. This study retrieved articles that were published from January 1, 2004, to December 31, 2024. All the search and download tasks were accomplished within one day to prevent potential bias resulting from the daily database updates. The inclusion criteria for this study are that the articles should be published between 2004 and 2024, the language should be English, and the document types should be articles or reviews. Other languages or document types will be excluded from the analysis. To ensure data integrity and avoid duplicate counting, duplicate records were identified and removed through a combination of the automated deduplication function in CiteSpace and manual verification. To facilitate a comprehensive bibliometric analysis, the indicators extracted from the merged WoSCC and Scopus dataset included annual publication output, document types, countries/regions, institutions, authors, journals, keywords, as well as the citation content and citation counts of each publication and the corresponding cited references. The processes of literature retrieval, deduplication, and preliminary data curation were conducted independently by three authors contributed equally, with any discrepancies resolved through discussion and consensus. All relevant references were exported in TXT format as "Full Records and Citations". Furthermore, the study was conducted in accordance with the principles outlined in the Declaration of Helsinki (Goodyear et al., 2007). No experimental content requiring ethical review was involved in this research. This study was conducted in accordance with two seminal bibliometric reporting frameworks: the BIBLIO guidelines proposed by Montazeri et al. and the bibliometric research methodology established by Donthu et al. (2021); Montazeri et al., (2023). Furthermore, our literature selection process rigorously adhered to the PRISMA-S for systematic evidence synthesis (Rethlefsen et al., 2021).

2.2. Data analysis

To visualize the outcomes of our bibliometric analysis, we employed a suite of analytical tools including CiteSpace(V6.1 R6), VOSviewer(V1.6.20), bibliometric packages within R(V4.2.1), Pajek 1.0.0.0, and Microsoft Excel 2021. CiteSpace, developed by Chaomei Chen, is one of the most widely used bibliometric analysis tools. This software reveals the development trends within a specific field of knowledge over a defined period, identifying key publications, authors, and emerging topics. It assists researchers in mapping the knowledge structure and evolution of a particular research domain (Chen, 2006, Chen, 2014).In CiteSpace (version 6.1.R6), the following parameter settings were applied: the time slicing was set from 2004 to 2024, with one slice per year, and the top 50 most cited items were selected for each time slice. The node types were set sequentially to "References" and "Keywords." The Pathfinder algorithm was applied to enhance the clarity of the visualized networks. VOSviewer is a Java-based bibliometric analysis software developed by Nees Jan van Eck and colleagues. It is primarily used for analyzing bibliometric networks. By constructing collaboration networks of authors, countries, or institutions, it helps researchers understand the competitive or collaborative relationships within the academic research process (Van Eck and Waltman, 2010). In VOSviewer (version 1.6.20), networks were constructed for country collaboration, institutional collaboration, journal co-citation, and keyword co-occurrence. The threshold values were set as follows: a minimum of 15 publications for countries and 15 for institutions in the collaboration networks; a minimum of 500 citations for journal co-citation, and 50 occurrences for keyword co-occurrence networks. And Microsoft Office Excel 2021 was utilized for the quantitative analysis of publication counts and total citation frequencies. Additionally,the R package "bibliometrix"(Version 4.2.1) was utilized to analyze thematic evolution and to create keyword cloud diagrams (Derviş, 2019).

3. Result

3.1. Publication outputs and cited trends

The literature retrieval process is summarized in Fig. 1. Initially, 3311 records were identified from the Web of Science Core Collection (WoSCC) and 3594 records from Scopus. After excluding ineligible publication types, including book chapters, corrections, editorial materials, and meeting abstracts, 3247 and 3512 records remained in WoSCC and Scopus, respectively. Following the removal of non-English publications, 3242 records from WoSCC and 3501 records from Scopus were retained for further analysis. The two datasets were subsequently merged and deduplicated using CiteSpace, resulting in a final dataset of 3639 unique publications, which formed the basis for all subsequent bibliometric and visualization analyses(Fig. 1).

Fig. 1.

Fig. 1

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Flowchart of selected publications for this study.

The annual citation count refers to the total number of citations received by the publications included in the dataset during a given year. Fig. 2 illustrates the annual publication counts and corresponding citation frequencies over the past two decades. Despite minor annual fluctuations in the number of publications from 2004 to 2024, an overall upward trend is evident. Notably, a significant increase occurred in 2020, with the peak reached in 2021, totaling 321 articles. Citation counts also show a continuous upward trend, with a particularly rapid increase after 2020, reaching a peak of 21,976 citations by 2024, with an average of 79 citations per article. This trend suggests that while the number of publications has slightly decreased in recent years, academic influence remains high. Overall, these data reveal that over the past two decades, research on neurodegenerative diseases and their association with brain energy metabolism has garnered significant academic attention and appears to be entering a period of accelerated progress. Based on current research trends and academic interest, it is anticipated that the focus on this field and research activity will continue to rise in the future.

Fig. 2.

Fig. 2

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Trends of annual publications and citations.

3.2. Country / regional distribution

As shown in Fig. 3 A, researchers from 54 different countries or regions have contributed to this research field. The countries with the highest research output are primarily the United States and Italy. The United States is at the forefront with 1265 publications, achieving a citation count of 93,948, followed by China and Italy and the United States holds the top position with an H-index of 262(Supplementary Table 3). Fig. 3B depicts the global collaboration network in the field of neurodegenerative diseases and brain energy metabolism, created using VOSviewer software. This network includes only countries or regions that have published at least 10 relevant papers, with 44 countries meeting this criterion. The collaboration links are particularly strong among the United States, China, and Italy, highlighting their significant influence and leadership in this research area. Fig. 3 C provides a more intuitive visualization of the cooperation relationships, with the United States possessing the most extensive collaboration network. These findings further emphasize the role of international collaboration in advancing research on neurodegenerative diseases and brain energy metabolism.

Fig. 3.

Fig. 3

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(A) Visualization of global distribution of publications. (B) Collaboration mapping with a minimum number of documents of country of > 10 publications based on collaboration among countries. (C) Network mapping of cooperation relationships among the main countries.

3.3. Institutions

By December 2024, research articles related to neurodegenerative diseases and brain energy metabolism had been published by over 1000 institutions. Leading the field is the University of Kentucky in the United States, with 63 publications and 5155 total citations, boasting a centrality of 0.03, which indicates its significant academic influence and collaboration network. It is followed by Johns Hopkins University and Harvard Medical School, with 60 and 51 publications, and 5031 and 2687 citations, respectively(Supplementary Table 4). Fig. 4 A presents a collaboration network diagram illustrating the relationships between various research institutions. The nodes in the figure represent academic institutions, and these nodes are grouped into several clusters, each represented by a different color, reflecting different collaboration groups. Inserm, the University of Kentucky, and the University of Coimbra occupy central positions within their respective clusters.

Fig. 4.

Fig. 4

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(A) Visualization of the network among institutions. (B) Visualization of the network among journals. (C) Network visualization showing the co-cited relationship between journals. (D) The dual-map overlay of journals.

3.4. Journals

A total of 459 journals have published articles on brain energy metabolism in neurodegenerative diseases. Supplementary Table 5 lists the top 10 journals ranked by publication count and citation frequency. The Journal of AD leads with 129 related publications and a total of 7708 citations. In Fig. 4B, The Journal of AD is shown to have published a total of 131 articles in this field, emerging as the leading journal, and the figure also presents an intuitive collaboration network among journals. Cited journals refer to those whose articles are frequently referenced by other researchers in their own studies. Citation count is a key indicator of the influence of journal articles. The Proceedings of the National Academy of Sciences of the United States of America ranks first with 8580 citations, highlighting its authority and impact in the field(Fig. 4 C). As shown in Fig. 4D, the dual journal overlay map not only reveals the thematic distribution of academic journals but also illustrates the citation relationships between different journals. The journals on the left represent citing journals, while those on the right represent cited journals. The orange path indicates that research published in biological and genetic journals is frequently cited by studies in molecular, biological, and immunological journals.

3.5. Authors and Co-authors

As of 2024, a total of 17,955 authors have participated in this research, with their publication output distribution conforming to Lotka's and Bradford’s law, as illustrated in Fig. 5C-D. Supplementary Table 6 presents the top 10 authors with the highest publication output and citation counts. The author with the highest number of publications is Mark P. Mattson from the United States, who has published a total of 27 articles, with an average citation count of 184.74. Co-cited authors are those whose research is simultaneously mentioned and cited in one or more academic publications. In this research field, the top three most cited scholars are Da Butterfield, S. Hoyer, and M.P. Mattson, whose work has been widely recognized. The research conducted by these scholars has exerted a profound influence on the field of neurodegenerative diseases and brain energy metabolism. Fig. 5 A illustrates the author collaboration network, which is divided into three clusters represented by distinct colors. Within these clusters, Dario Arnaldi, Daniela Peran, and Marco Paganini each occupy a central position. In the co-citation analysis conducted using VOSviewer, 106 authors were selected, each with at least 100 citations. In the generated network (Fig. 5B), Da Butterfield, M.P. Mattson, and L. Pellerin have the highest number of connections.

Fig. 5.

Fig. 5

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(A) Network visualization showing the relationship between authors. (B) Network visualization showing co-citation relationships between authors with at least 100 co-citations by authors. (C) The result of Lotka’ law. (D) Core journals determined according to Bradford’ s law.

3.6. Co- cited references and references burst

Supplementary Table 7 presents the top 10 most-cited references since 2004. The article titled "Brain energy metabolism: focus on astrocyte-neuron metabolic cooperation," published in Cell Metabolism in 2011 by Mireille Bélanger and colleagues, has garnered the highest citation count in this field, with 194 citations. In these pioneering studies, terms such as “AD” and “energy metabolism” are frequently encountered. Among the top ten most influential articles, six investigations focus on AD, while two studies examine energy metabolism. Citation burst analysis was conducted using CiteSpace software, which identified 20 references exhibiting citation bursts (Figure S1), with the most recent burst occurring in 2020 and still ongoing. The article published by DA Butterfield and colleagues in 2019 has demonstrated the highest burst value, with an intensity of 23.18. These works provide important perspectives on the current state of research in neurodegenerative diseases and offer valuable guidance for the future development of this field.

3.7. Keyword

Keywords succinctly summarize the research focus of an article, and their analysis helps us grasp the key topics, trends, and anticipated directions of emerging fields. Fig. 6 A presents a word cloud showing the top three keywords: energy metabolism, oxidative stress, and AD. In Fig. 6B, a total of 117 high-frequency terms were identified through co-occurrence analysis using VOSviewer. Through cluster analysis, five distinct clusters were formed: the red cluster includes keywords such as energy metabolism and oxidative stress, primarily related to molecular mechanisms of diseases; the yellow and green clusters encompass keywords such as neurodegeneration and AD, linked to clinical research; the purple cluster focuses on energy metabolism, cellular and molecular biology, and neuroscience; the blue cluster mainly addresses cellular functions, cell death, and stress responses, including keywords like metabolism and dysfunction. Fig. 6 C illustrates the temporal evolution of the keywords. Early keywords are represented by purple nodes, while recent hot topics are shown by yellow nodes. Initially, terms like HD, in vivo, and rat brain were core keywords. The increasing attention directed toward terms such as microglia, cognitive decline, and inflammation in contemporary research underscores their potential to become focal points of future investigative endeavors. Fig. 6D displays the CiteSpace timeline visualization, showing the evolution of keywords and the shift in research hotspots from 2004 to 2024. Since 2021, research on microglia, inflammation, and cognitive decline—one of the primary clinical manifestations of neurodegenerative diseases—has seen significant growth, suggesting these keywords reflect current hotspots in the field.

Fig. 6.

Fig. 6

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(A) Word cloud map of keywords. (B) Web Visualization Map of Keywords. (C) Keyword overlay visualization. (D) Visual timeline of keywords from 2004 to 2024.

Fig. 7 highlights the top 20 keywords with the strongest citation bursts from 2000 to 2024. The keyword with the highest burst intensity is transgenic mice, with an intensity of 30.11, peaking from 2006 to 2015. Microglia, cognitive decline, and inflammation are the most recent and highly discussed keywords, signaling a growing focus on the mechanisms underlying neurodegenerative diseases. This trend is expected to continue until 2025 and may persist further into the future.

Fig. 7.

Fig. 7

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CiteSpace visualization map of the top 20 keywords with the strongest citation bursts.

4. Discussion

This study primarily utilizes integrated data from the WoSCC and Scopus databases and employs software tools such as VOSviewer (v1.6.20) and CiteSpace (v6.1 R6) to conduct a comprehensive analysis of the developments in the field of brain energy metabolism in neurodegenerative diseases.

We focused on analyzing publications related to neurodegenerative diseases and brain energy metabolism from January 1, 2004, to December 31, 2024. The results revealed contributions from 54 countries, 1000 institutions, and 17,955 researchers in this field. From 2004–2024, publications related to neurodegenerative diseases and brain energy metabolism exhibited a general upward trend, with fluctuations in specific years. Notably, although the number of publications declined in 2019 and 2023, citation counts continued to rise. This suggests that, during this period, certain highly influential academic works gained widespread recognition and acclaim.Our analysis suggests that the notable surge in citations may be attributed to two influential works: Gerald A. Dienel's seminal study, titled "Brain Glucose Metabolism: Integration of Energetics with Function," published in Physiological Reviews in 2019, and the review article by Fangda Leng et al., titled "Neuroinflammation and Microglial Activation in Alzheimer Disease: Where Do We Go from Here?" published in Nature Reviews Neurology in 2020. These impactful studies likely contributed to the sustained increase in citations during this period (Leng and Edison, 2021, Dienel, 2019). Studies have demonstrated that neuroinflammation—particularly the dynamic activation of microglia—has been identified as one of the core drivers in the progression of AD, rather than a mere secondary response. Consistently, genetic studies, fluid and imaging biomarkers, as well as single-cell transcriptomic data indicate that microglia sense amyloid-beta (Aβ) and tau via recognition receptors, thereby initiating phagocytic inflammatory responses and secreting inflammatory factors. Conversely, these inflammatory factors further influence Aβ deposition and tau propagation. These three components form an interactive cycle, which renders therapeutic strategies focused solely on clearing protein aggregates ineffective (Leng and Edison, 2021). These observations provide a biological rationale for combining anti-inflammatory and anti-protein aggregation strategies. Of note, this combinatorial concept is mainly supported by pre-clinical mechanistic findings; definitive clinical evidence confirming synergistic therapeutic effects in human patients remains absent. Large-scale prospective clinical trials are warranted to further validate this hypothesis. Concurrently, targeting their pro-inflammatory properties, efforts will be made to develop inhibitors against specific pathways such as NF-κB and NLRP3, or to regulate microglial phenotypes through agents like interferons and PPARγ agonists, thereby enhancing their anti-inflammatory and phagocytic functions for the clearance of pathological substances. Concurrently, targeting their pro-inflammatory properties, efforts will be made to develop inhibitors against specific pathways such as NF-κB and NLRP3, or to regulate microglial phenotypes through agents like interferons and PPARγ agonists, thereby enhancing their anti-inflammatory and phagocytic functions for the clearance of pathological substances.

Co-occurrence and collaboration-network analyses of 54 countries and 1000 institutions reveal a highly skewed global distribution of research in this field. The United States dominates in citations, h-index, and overall contribution. The United States, Germany, and Italy rank among the top in both the number of publications and total citations, a position largely attributed to their active involvement in several multinational collaborative initiatives targeting neurodegenerative diseases. Notable examples include the BRAIN Initiative, led by the United States in partnership with several European countries, and the DZNE project, supported by the Alzheimer’s Association. These large-scale programs offer valuable reference points for early-career researchers seeking to understand the global research landscape.For instance, in 2024, Mariano I. Gabitto and colleagues leveraged spatial transcriptomic data and reference atlases generated by the BRAIN Initiative to analyze cells from the middle temporal gyrus of 84 AD patients. Their findings revealed a biphasic pathological trajectory: in early stages, gradual accumulation of pathology was associated with the emergence of inflammatory microglia, reactive astrocytes, and the loss of somatostatin-expressing inhibitory neurons; whereas in later stages, a sharp escalation in pathology was observed, marked by the depletion of excitatory neurons and vasoactive intestinal peptide (VIP)-positive inhibitory neuron subtypes (Gabitto et al., 2024). Additionally, The European Union's "Neurodegenerative Diseases Joint Programme" (JPND) is one of the largest global research initiatives focused on neurodegenerative diseases. The first phase of this programme was officially launched in 2012. As of now, the initiative has expanded to over 30 countries, including France, Germany, and Canada, and has established multiple large-scale cohort databases focused on neurodegenerative diseases, such as EPAD and ADNI-EU. These cohorts are accessible to registered researchers through online applications and offer free access to clinical data, thereby lowering the barrier to data acquisition. Moreover, these cohorts rank among the largest and most comprehensive worldwide in terms of participant numbers and disease coverage. They help to fundamentally address issues such as enrollment bias and limited statistical power that often arise from regionally restricted clinical studies (Zaib et al., 2023, Matilla-Dueñas et al., 2017). In contrast, while emerging countries such as China have exhibited a rapid increase in publication output and maintain a high level of domestic and international co-authorship, their involvement in major international collaborative programs remains comparatively limited. Moreover, research from China tends to focus more on applied aspects, whereas investigations into fundamental mechanisms are still in a phase of active development. For example, Jin Hongjun and colleagues demonstrated that electroacupuncture could enhance cognitive and memory performance in AD mouse models and reduce Aβ deposition (Pan et al., 2025). These trends suggest that greater participation in international research consortia may provide Chinese scholars and institutions with expanded opportunities to elevate the impact and originality of their scientific contributions.

Renowned journals provide the latest research advancements and developments in their respective fields, helping readers stay informed about cutting-edge scientific progress. Among them, the Journal of AD ranked first with 129 articles, followed by the International Journal of Molecular Sciences, PLoS One, and Molecular Neurobiology. Results from journal co-citation analysis indicate that authoritative journals such as Nature and Cell frequently appear in citation analyses, suggesting that this field has garnered considerable attention and recognition within the academic community. Notably, three out of the top ten highly cited papers originate from these premier journals. In 2006, Michael T. Lin and M. Flint Beal described a distinct molecular cascade within the substantia nigra of patients with sporadic PD in their review: inhibition of mitochondrial complex I triggers bioenergetic failure, which subsequently induces oxidative stress and ultimately leads to neuronal death (Lin and Beal, 2006). A body of subsequent studies has demonstrated that this cascade is initiated prior to the onset of clinical symptoms, making it a critical target for early-stage intervention. For instance, in PD, researchers using conditional knockout mice with deletion of the Ndufs2 gene encoding an essential complex I subunit specifically in dopaminergic neurons (ndufs2 mice) have demonstrated that isolated complex-I dysfunction alone is sufficient to trigger progressive parkinsonian-like phenotypes (Vos, 2022). Furthermore, in AD, assessments of mitochondrial function using the novel PET radiotracer [18 F]BCPP-EF have revealed that reduced complex-I activity within the medial temporal lobe is significantly associated with tau deposition and clinical manifestations (Terada et al., 2021). ME MacDonald and colleagues were the first to clone and identify a novel gene, IT15 (later renamed huntingtin), located at 4p16.3. In the normal population, this gene contains a polymorphic (CAG)n trinucleotide repeat sequence (11–34 repeats). However, in the disease-associated chromosomes of all 75 HD families studied, this repeat sequence undergoes abnormal expansion (≥42 repeats), with the length of expansion showing a negative correlation with the age of onset. Since HD is an autosomal dominant genetic disorder caused by the expansion of unstable CAG repeat sequences, a PCR-based molecular diagnostic method can be established based on this characteristic. This method, which directly measures the length of repeat sequences, is capable of replacing traditional linkage analysis. It is applicable to asymptomatic screening, prenatal diagnosis, and genetic counseling, with the advantages of simplicity and rapidity (MacDonald et al., 1993).

Mark P. Mattson, from the Johns Hopkins University School of Medicine, is the most prolific author in the field with 27 publications. His articles have been cited 4988 times, yielding an average citation count of 184.74 per paper. Additionally, M. Flint Beal from Cornell University ranks third with 24 publications, yet his articles have an impressive citation total of 7318, giving him the highest citation count in the field, with an average of 304.92 citations per paper. Professor Mark P. Mattson and his team have consistently focused on understanding brain aging and the pathogenesis of diseases such as AD, PD, and HD. Their research primarily concentrates on the role of glutamate in neuronal development and injury, and how pharmacological interventions can modulate these processes to protect neurons (Balusu et al., 2023, Kostandy, 2012). Glutamate plays a crucial role not only in synaptic transmission but also in neuronal plasticity and disease. It interacts with nerve growth factor (NGF) to jointly regulate the plasticity of both developing and adult neurons, neurogenesis, synaptic growth, synaptogenesis, and cell survival. For example, glutamate can stimulate the production of brain-derived neurotrophic factor (BDNF), which, in turn, modulates glutamate receptor subunits and Ca2 + homeostasis, thereby influencing synaptic signaling (Mattson, 2008). In addition, Professor Mattson's research also encompasses antibody-based therapies, which involve using antibodies to eliminate harmful proteins, such as β-amyloid and tau, from the brain. This therapeutic approach has shown promising results in clinical trials, offering new hope for the treatment of AD (Mata et al., 2014). Professor M. Flint Beal, who passed away in 2021, was a renowned neurologist and translational neuroscientist. He dedicated much of his career to studying AD, PD, HD and ALS, with a particular focus on the impact of aging on the susceptibility of specific brain regions. By analyzing key factors such as oxidative stress and mitochondrial dysfunction, he sought to uncover the core pathological mechanisms underlying these diseases (Mata et al., 2014). Initially, Professor M. Flint Beal proposed that defects in mitochondrial complex I could impair oxidative phosphorylation in the electron transport chain, thereby increasing excitotoxicity. Additionally, mitochondrial dysfunction may contribute to neurodegenerative diseases through various mechanisms, including the generation of free radicals, impaired calcium buffering capacity, and mitochondrial permeability transition (Beal, 1998). Recently, Professor M. In 2022, Flint Beal's team uncovered the significant role of succinylation in AD, particularly its aberrant modification of mitochondrial proteins, amyloid precursor protein (APP), and tau, a microtubule-associated protein. These findings offer new insights into the pathogenesis of AD and suggest potential therapeutic targets (Yang et al., 2022).

Through co-occurrence analysis of keywords and a detailed examination of the top 20 most cited emerging keywords, three prominent research trends have emerged. These trends are associated with the keywords "microglia," "inflammation," and "cognitive decline," which are highlighted as focal points in Fig. 6 C. Microglia are the resident macrophages of the central nervous system, implicated in neurodegenerative diseases and brain inflammatory disorders (Colonna and Butovsky, 2017). Microglia play a dual role in diseases such as AD and stroke, where their activated state may either exacerbate toxicity or provide neuroprotection (Kwon and Koh, 2020). When microglia are activated, they release pro-inflammatory cytokines that lead to neuronal damage (Muzio et al., 2021). Energy metabolism is a central regulatory factor for microglial function, with dynamic changes in metabolic patterns directly influencing their immunological activity and neuroprotective or neurotoxic effects (Muzio et al., 2021). Under resting conditions, microglia predominantly rely on oxidative phosphorylation for ATP generation, characterized by robust mitochondrial function and high energy efficiency (Bielanin and Sun, 2023). Upon exposure to pro-inflammatory stimuli such as Aβ, microglia undergo metabolic reprogramming, characterized by enhanced glycolysis and concomitant suppression of oxidative phosphorylation. This metabolic shift is marked by decreased mitochondrial respiratory chain activity and reduced ATP production (Gimeno-Bayón et al., 2014). In 2025, Professor Chen Hongwei's team pioneered the design of BV2 microglia membrane-camouflaged multienzyme biomimetic gallic acid-selenium nanoparticles (BM@GA-Se nanosomes). This breakthrough therapeutic strategy targeted PD by suppressing microglial pyroptosis via selective blockade of the HSP90/NLRP3/Caspase-1 signaling axis (Wang et al., 2025). Nevertheless, BV2 membranes exhibit limitations in personalized immunomodulatory properties. Future directions may involve deriving patient-specific "autologous membrane-nanovesicles" through peripheral blood mononuclear cell (PBMC)-induced iPSC-microglia membrane engineering, potentially enabling PD course modification. While these findings substantially advance our understanding of metabolic regulation in microglia during neurodegeneration, critical knowledge gaps persist. Current microglial subpopulation classifications predominantly rely on murine models and non-spatially resolved data, lacking dynamic metabolic profiling of human disease-progression tissues. Integrative single-cell analyses—synthesizing spatial transcriptomics, metabolomics, and proteomics—applied to postmortem human specimens could precisely delineate disease-specific phenotypes. Furthermore, the metabolic-inflammatory crosstalk among microglia, astrocytes, and neurons remains elusive, particularly under metabolic dysregulation states (e.g.,diabetes, obesity). Direct evidence is urgently needed to clarify whether microglial metabolic reprogramming exacerbates neuroinflammation and neuronal injury in these contexts. Inflammation, through the activation of NF-κB and glial cell responses, leads to Purkinje cell damage, which in turn contributes to the development of ataxia and autism spectrum disorders.This suggests that inflammation may influence specific neurons through distinct signaling pathways, leading to diverse disease manifestations (Revuelta et al., 2020). Furthermore, Aβ deposition and tau protein abnormalities can also activate microglia, leading to enhanced glycolysis and exacerbating inflammation and oxidative stress. Inflammation impairs the generation of new neurons in the hippocampus of adult rats, whereas the drug minocycline, which inhibits microglial activation, can restore neurogenesis. This suggests that excessive microglial activation may suppress neurogenesis through inflammation, leading to cognitive decline (Gemma et al., 2010, Sato, 2015, Ekdahl et al., 2003). Emerging evidence reveals that amyloid-β42 oligomer stimulation disrupts homeostatic microglial metabolism and immune function via the pro-inflammatory factor TREM1. Notably, TREM1 deficiency mitigates neuritic dystrophy, attenuates disease-associated microglial transcriptional signatures, and prevents hippocampal memory decline (Wilson et al., 2024). Nevertheless, cognitive impairment in neurodegenerative diseases remains incurable, posing a significant therapeutic challenge. The blood-brain barrier (BBB), intricate brain microenvironment, and dynamic heterogeneity of neuroinflammatory responses critically limit treatment efficacy—current approaches such as cholinesterase inhibitors offer only transient symptomatic relief without altering disease progression. Future research must prioritize elucidating the causal mechanisms linking neuroinflammation, neuronal metabolism, and synaptic plasticity to identify druggable targets. A deeper mechanistic understanding of TREM1- and NF-κB-mediated signaling cascades, alongside microglial metabolic reprogramming, is imperative to delineate their precise roles in neuronal injury. Concurrently, the development of BBB-penetrant delivery platforms (e.g., nanovectors, cell-mediated transport) and multimodal biomarker monitoring systems could enable earlier, more precise interventions, enhancing both the timeliness and specificity of cognitive disorder therapeutics.

5. Limitation

Although this study provides valuable insights into global research trends in neurodegenerative diseases and brain energy metabolism, several limitations should be acknowledged. First, variations in institutional access to the WoSCC and Scopus may lead to minor discrepancies in the retrieved records; however, such differences are unlikely to substantially affect the overall trends or conclusions. Moreover, some recently published high-quality and high-impact studies may have been underrepresented due to limited citation counts or their recent publication dates, and therefore may not yet be identified as emerging hotspots. Furthermore, this study included both original articles and review papers. As review articles generally accumulate citations more rapidly than original research articles, certain citation-based indicators may have been influenced to some extent. However, the inclusion of both document types enabled a more comprehensive representation of the knowledge base and developmental trajectory of this research field. Finally, the results of co-occurrence, clustering, and citation burst analyses are inherently influenced by the selected algorithms and threshold settings, which introduces a degree of methodological and interpretative subjectivity (Huang et al., 2025).

6. Conclusion

This bibliometric analysis examines the literature on neurodegenerative diseases and brain energy metabolism over the past two decades. Despite certain limitations, it provides a comprehensive exploration of the key topics and emerging trends in the field. Through citation analysis and collaborative networks, it highlights the importance of international cooperation, particularly from developing countries such as China. These insights offer researchers a valuable overview of the historical development and current focal points within the field.

CRediT authorship contribution statement

Chengxi Weng: Writing – original draft, Data curation, Conceptualization. Xiaomai Huang: Writing – original draft, Software. Haochen Huang: Supervision, Software, Project administration. Fang Ke: Software, Methodology, Investigation. Lijuan Zhang: Writing – review & editing, Supervision, Project administration. Fengping Xu: Writing – review & editing, Methodology, Conceptualization. Xiaoli Lin: Writing – review & editing, Writing – original draft, Supervision, Software, Methodology, Conceptualization.

Funding

This work was supported by Fujian Provincial Natural Science Foundation of China (Grant number: 2025J011663)

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Footnotes

Appendix A

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ibneur.2026.09.018.

Appendix A. Supplementary material

Supplementary material

mmc1.docx (305.2KB, docx)

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