Diabetes mellitus is increasing worldwide and is expected to affect approximately 642 million people by 2040 (Ogurtsova et al., 2017). Diabetes-associated cognitive dysfunction (DACD) is a complication caused by chronic hyperglycemia and microvascular diseases, which can lead to transient or permanent cognitive dysfunction (Kodl and Seaquist, 2008). Demographic trends for DACD very closely resemble those seen in diabetes mellitus (Biessels and Despa, 2018). Data from the large USA Veterans Registry showed that the prevalence of cognitive dysfunction in diabetes was 13.1% among those 65–74 years old and 24.2% among those 74 years and older (Biessels and Whitmer, 2020).

Type 1 diabetes mellitus (T1DM) can reduce cognitive abilities such as intelligence, processing speed, and mental flexibility (Kodl and Seaquist, 2008). While type 2 diabetes mellitus (T2DM) can specifically affect memory, processing speed, and executive function, which eventually results in cognitive dysfunction (McCrimmon et al., 2012). According to the severity, DACD can be classified into three approximate stages: asymptomatic preclinical stage, mild cognitive impairment (MCI), and dementia (Koekkoek et al., 2015). DACD has been found to significantly reduce an individual’s quality of life (Biessels and Despa, 2018), and increase their mortality (Biessels et al., 2020). Thus, DACD has received extensive attention from the medical community.

With further research, the number of studies on DACD is gradually increasing in recent years. Exploring the mechanism of DACD provides some clues, such as insulin resistance (IR), structural changes in brain tissue, altered cerebral blood flow, abnormal metabolism of brain cells, and impaired insulin signaling pathways (Stranahan et al., 2008; Geijselaers et al., 2015; Biessels and Despa, 2018). Additionally, daily care guideline on DACD has provided some advice on treatment and diagnosis methods (Koekkoek et al., 2015). However, there are still gaps in understanding the underlying mechanisms of DACD and improving therapeutic strategies (Biessels and Despa, 2018).

Bibliometric analysis is a powerful technique that can be applied to assess any particular research topic, predict emerging patterns, and reveal the research frontiers in a scientific field (Deng et al., 2022). Traditional literature reviews and systematic reviews cannot provide multiple perspectives in such an intuitive way as this approach (Yang et al., 2022). This method has been applied to analyze the hotspots of diabetes and its complications, assisting in the development of further research on disease prevention and treatment (Dehghanbanadaki et al., 2022; Zhang et al., 2022). Despite the extensive research conducted in the field of DACD in recent decades, there has been a lack of quantitative bibliometric analysis to assess the specific progress made in this area. Therefore, this study performed the co-authorship analysis of countries, institutions, authors, assessed the journal performances, and explored the emerging trends in the field of DACD using bibliometric analysis.

This study is the first bibliometric analysis of global research on DACD. It can present the general trends in the field to researchers systematically and visually. We searched a total of 4,378 DACD-related articles and reviews published over the past 23 years. Although the number of publications has fluctuated over the decades, there has been an overall trend of growth in recent years. Our data revealed a burst of research activity after 2017. Biessels and Reagan (2015) pointed out that hippocampal insulin resistance maybe a potential mechanism of cognitive dysfunction in T2DM. Furthermore, Chatterjee’s finding further supported the role of diabetes in the etiology of dementia (Chatterjee et al., 2016). These findings provided new insights into DACD and have garnered the interest of researchers in the field, resulting in a surge of published papers.

The number of publications is considered to be a significant indicator to appraise the strength of national research. By this bibliometric analysis, the USA was the country with the largest number of publications, followed by China. This indicates that they have produced more in-depth studies in this field. The promotion of research in a certain field can be attributed to two important factors: governmental expenditure on healthcare and inter regional cooperation (Li et al., 2022). The USA spends $10,202 per capita on healthcare, outpacing most countries (Martin et al., 2022). Then, the USA has been a major contributor to DACD research, as can be seen from the fact that the majority of collaborations in this field are concentrated in it. The reasons for this include the presence of leading research institutions and funding opportunities. Thus, the USA has had a significant impact on the field over the past few decades.

Identifying core authors in the field can help researchers find potential collaborators. Our results on the analysis of authors showed that Biessels, GJ was the most productive and the most co-cited author, indicating that he is a key researcher in this field. His team have been focusing on mechanisms (atherosclerosis, microvascular disease, glucose toxicity, insulin resistance, inflammation, etc.) and treatments of DACD, as well as providing guidelines for the daily care of patients with DACD (Kamal et al., 2000; Brands et al., 2005; Koekkoek et al., 2015; Biessels and Despa, 2018). Furthermore, they identified and described the progress of cognitive dysfunction and its various stages, while also utilized MRI to determine the underlying structural changes in the brain (Manschot et al., 2006; van den Berg et al., 2006; Biessels and Reijmer, 2014; Brundel et al., 2014). Nine of the top 10 core authors came from developed countries, and only one from developing country China, American and European countries take the lead in this field, while research from China in this field has gained increasing attention in recent years. Studies by leading authors in the developed countries mainly focus on the link with the inflammatory, metabolic, vascular, hormonal factors between DACD, contributing to the early knowledge base relating to DACD. The study by Wang Shaohua, the only author from China, focused on prevention and treatment strategies for DACD, has explored the association between serum uric acid levels (Huang et al., 2019), lipoprotein-associated phospholipase A2 (Cai et al., 2017), serum IGF-1/IGFBP-3 molar ratio decreased (Huang et al., 2015) and cognitive functions in T2DM patients. Overall, the study on DACD showed close collaboration among the authors. Besides, most of the scholars engaged in DACD research were from different countries, and the cooperation was mostly confined to the research team. Therefore, the a fore-mentioned team members will produce more insightful articles, strengthening collaboration with these elite groups and across nations, leading to more notable advancements in DACD.

Identification of core journals can provide researchers with a wealth of reliable reference information and help them to screen the most suitable target journals (Zhuang et al., 2014). Diabetes Care may be the potential core journal in this field as the highest IF, TGCS, and co-citations. The journal Diabetes Care aims to improve the quality of patient care by catering to the needs of all healthcare professionals involved in the treatment of diabetes. Researchers in this field can prioritize this journal when they are searching for relevant references or submitting manuscripts.

The analysis of co-cited references provides insight into the core themes and key findings of current research (Wang et al., 2021). Most of the top 10 co-cited references concentrated on the pathophysiological mechanisms, treatment, and daily management of DACD. According to citation analysis, the most frequently co-cited reference is the publication by Biessels GJ in Nature Reviews Endocrinology in 2018 (Biessels and Despa, 2018). This article reviewed previous research in three areas: risk factors, brain imaging, and neuropathology. Several key clues to the underlying mechanisms of DACD and the future research focus were provided. Identifying the risk factors that affect the brain and contribute to the development of DACD through the observation of experimental models is a way to provide targeted treatment and prevention strategies for people with DACD. Hence, it had the highest cited and represented a high-level recognition of his research by other scholars. Another article with 112 citations was published in 2018 by Arnold SE. The team conducted a thorough review of experimental data and key observations on insulin signaling in the brain, emphasizing its effects on both neurons and glia. They proposed that both T2DM and Alzheimer’s disease (AD) are linked to cerebral insulin resistance and brain dysfunction (Arnold et al., 2018).

The combination of keyword cluster analysis and co-cited reference cluster can find hot topics (Xu et al., 2022b). Our results showed that signaling pathways were a hot spot and frontier area in this field. Recent popular pathways include the insulin–insulin receptor substrate (IRS) –Akt pathway, the phosphoinositide 3-kinase (PI3K) –Akt pathway, and the mitogen-activated extracellular signal-regulated kinase (MEK) –extracellular signal-regulated kinase (ERK) pathway (Arnold et al., 2018). Faulty activation of these signal pathways cascades results in impaired microvascular and mitochondrial function, and enhanced advanced glycation end products (AGE) and inflammation levels, which exacerbate oxidative stress (Biessels and Reagan, 2015; Grillo et al., 2015; Riederer et al., 2017; Arnold et al., 2018). These processesare usually associated with neurotoxicity, neurodegeneration, and cognitive deficits (Riederer et al., 2017). Moreover, brain insulin resistance has been verified to be an important pathway related to neurodegeneration and dysfunction in AD (Biessels and Reagan, 2015). Insulin receptors are widespread distribution in the brain, so the impairment of the insulin signaling pathway would influence development and function of major cell types of the brain (such as neurons, astrocytes, microglia, etc.) (Biessels and Reagan, 2015; Arnold et al., 2018). Neuron insulin resistance-induced deficits in synaptic plasticity, receptor regulation, or synaptic transmission, contributed to impaired regulation of metabolism or cognition dysfunction (Biessels and Reagan, 2015; Arnold et al., 2018). Similarly, astrocytic mitochondrial dysfunction, insulin resistance, and metabolic dysfunction may be also involved in the DACD pathology processes (Shen et al., 2023). In addition, a recent single-cell study found that activation of microglia in the hippocampus of db/db mouse promotes the expression of inflammatory factors and increase oxidative stress damage, which provides a novel strategy for screening DACD diagnostic biomarkers or potential therapeutic targets (Ma et al., 2022). Although studies above have provided some clues in this field, the pathogenesis of DACD is still not well understood. Future studies using single-cell sequencing analysis might be a trend to identify promising diagnostic biomarkers or potential therapeutic targets for DACD.

In recent years, more and more literature has focused on the impact of anti-diabetes drugs on DACD, which is becoming a new trend in the study of DACD treatment strategies. Earlier studies have demonstrated that insulin (Claxton et al., 2014), insulin sensitizer metformin (Koenig et al., 2017), dipeptidyl peptidase 4 (DPP4) inhibitors vildagliptin (Pipatpiboon et al., 2013), and peroxisome proliferator-activated receptor-γ (PPARγ) agonists rosiglitazone (Pathan et al., 2008) can improve cognitive dysfunction. Studies in rodent models show that insulin could improve cognitive performance by activating insulin receptor signaling in the hippocampus (Biessels and Reagan, 2015). Interestingly, compared to direct injection of insulin, intranasal insulin could directly supply insulin to brain target and penetrate the blood–brain barrier, thereby result in enhancing cognitive performance in mice (Chen et al., 2021). In adults with mild cognitive impairment, daily treatment with long-acting intranasal insulin could also mitigate cognition dysfunction (Claxton et al., 2014). Similarly, metformin, an insulin response enhancer, can improve cognitive dysfunction (Lin et al., 2018; Samaras et al., 2020) by modulating Akt/ glycogen synthase kinase 3 (GSK3) or cAMP response element binding (CREB) / brain-derived neurotrophic factor (BDNF) signaling pathway (Keshavarzi et al., 2019), and inhibiting cyclin-dependent kinase 5 (CDK5) hyper-activation and CDK5-dependent tau hyperactivation (Wang et al., 2020). Additionally, vildagliptin is a DPP4 inhibitor, which can enhance insulin sensitivity and prevent mitochondrial damage in the brain inhigh-fat diet-fed (HFD) rats (Pintana et al., 2013; Pipatpiboon et al., 2013). In elderly patients with type 2 diabetes, DPP4 inhibitor decreases the risk of cognitive dysfunction compared to sulfonylureas (Kim et al., 2019). In addition, the PPARγ agonists rosiglitazone reverses cognitive dysfunction by improving the peripheral insulin resistance in rats with high-fat diet (Pathan et al., 2008). The cognitive enhancement potential of anti-diabetic drugs has been evaluated in a number of preclinical and clinical studies (Chen et al., 2021). Nevertheless, these results are still needed to be verified by multi-center and large-sample clinical trials. In summary, from a pharmacotherapy perspective, identifying landmark anti-diabetes drugs that might improve the life quality and long-term outcomes of DACD patients are emerging trends in this field.

With the help of bibliometric analysis, this study systematically displays the research on DACD and captures the hotspots and emerging trends in this field. However, this study still has some shortcomings. Firstly, the study was limited to the Web of Science Core Collection database for literature screening, which may exclude a few relevant literature. This is due to current limitations in scientometric software, making combining multiple databases for analysis difficult. In the future, we will select more databases available for bibliometric analysis. Secondly, we only focused on the period from 2000 to 2022, thus we can not fully display the landscape of research on DACD. Therefore, we will try to select longer period for performing analysis to provide comprehensive information for this research field. Finally, only several tools such as VOSviewer, CiteSpace, Histcite, and R bibliometric package were used in this study, which may not fully interpret these data, we will try to perform the artificial neural networks in the following research using other tools.

Bibliometric analysis shows that research on DACD is developing rapidly and has broad prospects. The most prolific country, institution, journal, and author are the USA, the University of Washington, Diabetes Care, and Biessels GJ, respectively. The reference with the most co-cited is written by Biessels, GJ in 2018. The research focuses are the underlying mechanism of DACD and the effect of anti-diabetes drugs on DACD. In addition, exploring new drugs targeting signal pathways for DACD is the emerging trend. In summary, this study systematically analyzes the literature on DACD, shows the landscape of research in the past decades, and provides direction for future research.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

SH and QL designed the study plan and drafted the manuscript and retouched it. JZ and CW screened the literature. SH and XL performed the software analysis. ZW and DW revised the final version of manuscript and approved it. All authors contributed to the article and approved the submitted version.

This study was supported by Hainan Provincial Natural Science Foundation of China (grant no. 2019RC365) and Guangzhou Key Laboratory of Neuropathic Pain Mechanism at Spinal Cord Level (202102100005).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.