Type 1 diabetes (T1D) is an autoimmune disease characterized by an ongoing destructive process due to aberrant antibodies and autoreactive T cell responses to self-antigens of pancreatic islet beta cells (β-cells), ultimately leading to absolute insulin deficiency (DiMeglio et al., 2018). Recently, an increasing number of studies have helped us understand how gut microbial dysbiosis disrupts immune homeostasis as a consequence of abnormal innate and adaptive immune responses to alterations in the gut microbiota and its metabolites, thereby engaging β-cell autoimmunity (Hu et al., 2015, 2017; Brown et al., 2019; Siljander et al., 2019).

Alterations in gut microbiota composition and intestinal permeability increase prior to T1D diagnosis, as shown by multiple large and well-characterized human T1D cohort studies (Davis-Richardson et al., 2014; Kemppainen et al., 2015; Kostic et al., 2015; Maffeis et al., 2016; Vatanen et al., 2016; Stewart et al., 2018; Vatanen et al., 2018; Harbison et al., 2019). Gut microbiota dysbiosis has also been observed in T1D patients (Brown et al., 2011; Mejía-León et al., 2014; Alkanani et al., 2015; Kostic et al., 2015; Stewart et al., 2018; Vatanen et al., 2018; Harbison et al., 2019; Huang et al., 2020a,b). Evidence from non-obese diabetic (NOD) mice, a widely used animal model of T1D, further confirmed that gut microbiota is involved in the progression of islet autoimmunity and T1D onset (Wen et al., 2008; Brown et al., 2016; Pearson et al., 2016; Huang et al., 2020a; Fuhri Snethlage et al., 2021; Huang et al., 2021; Girdhar et al., 2022; Jia et al., 2022; Marietta et al., 2022).

One of the critical T1D management strategies is to improve glycemic control and reduce complications in patients with T1D. More recently, research has focused on studying the association between gut microbiota and glycemic control and diabetic complications. The results showed that gut microbiota alteration is related to glycemic control, diabetic kidney disease, and macrovascular complications (Winther et al., 2020; van Heck et al., 2022; Shilo et al., 2022a). Based on these findings, therapeutic strategies targeting the gut microbiota were administrated in rodent and human studies to investigate their roles in preventing or reversing T1D progression, making remarkable advances (Mariño et al., 2017; Hänninen et al., 2018; Huang et al., 2020a; de Groot et al., 2021; Zou et al., 2021; Bell et al., 2022; He et al., 2022; Martens et al., 2022). Yet, despite these advances, further validation is required, and many challenges still need to be addressed.

Bibliometrics is a widely employed method to map studies within a specific research field by statistical and quantitative analysis of the academic impact and characteristics of publications. The aim is to complement empirical findings and to highlight frontier research and development trends toward guiding future directions in a rapidly evolving field such as gut microbiota. Global research trends in gut microbiota (Baudoin et al., 2019; Yuan et al., 2021; Zyoud et al., 2022a) and their roles in different diseases, including cancer (Zhang et al., 2020; Yang et al., 2022; Zyoud et al., 2022b), neuropsychiatric (Zyoud et al., 2019; Zhu et al., 2020; Cabanillas-Lazo et al., 2022; Wang H. et al., 2022; Zhao et al., 2022) and gastrointestinal disorders (Zyoud et al., 2021), among others, have been extensively explored and illustrated by bibliometric analysis.

Although previous research has studied the role of gut microbiota in T1D pathogenesis, diagnosis, prognostication, and treatment, to date no quantitative description of gut microbiota and T1D has been reported. In this article, we reviewed the role of gut microbiota in the field of T1D, identified related articles, and analyzed their characteristics. Our present study included research involving both animal models and human beings, allowing researchers to better understand how gut microbiota works in T1D.

The present study is the first bibliometric research about gut microbiota and T1D and includes a total of 324 articles retrieved from SCIE of WoSCC for bibliometric and visualization analysis. Since 2008, the number of publications per year has increased, and the average annual citations of articles also peaked in 2008. Based on the fit of the curve and actual data of 2022, we project that the number of publications per year will remain at relatively constant level for a period.

Four publications in 2008 were included in our analysis, and subsequent analysis of the historical citation network suggested that a study conducted by Li Wen and her colleagues is the most cited original article and a milestone in the field of research on gut microbiota and T1D. In that study, Li Wen et al. found that Myd88 deficiency protects NOD mice from T1D, whereas Myd88^−/− NOD mice under germ-free conditions did develop T1D (Wen et al., 2008). Their study revealed for the first time that the interplay between the host innate immune system and gut microbiota is at the root of T1D pathogenesis, thus laying a solid foundation for future research.

European countries and the United States are the leading contributors to this field. Research success in those countries may be linked to their well-characterized cohort studies, the most representatives of which are The Environmental Determinants of Diabetes in the Young (TEDDY), the Pathogenesis of Type 1 Diabetes-Testing the Hygiene Hypothesis (DIABIMMUNE), and All Babies in Southeast Sweden (ABIS) studies. To identify environmental factors related to the onset of T1D, the TEDDY study recruited newborns with high-risk human leukocyte antigen (HLA) alleles from the general population and first-degree relatives (FDRs) of T1D patients, who were prospectively analyzed and followed up at different clinical centers, including centers in Colorado, Washington State, Georgia, Florida in the United States, centers in Finland, Germany and Sweden. DIABIMMUNE is another important multinational longitudinal study for testing the hygiene hypothesis in T1D, which recruited newborns with high-risk HLA haplotypes from Finland, Estonia, and Russian Karelia. In addition, ABIS from Sweden is a prospective birth cohort aimed at examining the role of gut microbiota in the etiology of T1D. Diet intervention studies, such as the Primary dietary intervention study to reduce the risk of islet autoimmunity in children at increased risk for type 1 diabetes (BABYDIET), the Finnish Diabetes Prediction and Prevention Project (DIPP), and the Trial to Reduce IDDM in the Genetically at Risk (TRIGR) also directly or indirectly addressed the association between gut microbiota and islet β-cell autoimmunity.

Moreover, we relied on animal models to explore how gut microbiota regulate T1D pathogenesis (Tlaskalová-Hogenová et al., 2011; Pearson et al., 2016). Evidence has shown that NOD mice develop spontaneous β-cell autoimmunity mimicking T1D and the development of this animal model under specific pathogen free and germ free condition enables research on gut microbiota to move forward from bedside to bench. Although the current main researchers and research institutions are located in the United States and European countries, the keywords “Asian” and “Africa” have appeared recently, indicating that research on T1D and gut microbiota is starting to gain widespread attention in these two regions. To compensate for research disadvantages in Asian and Africa in relevant animal studies, such as the later start, the lack of depth of research, the relatively small size of human studies, and most studies are cross-sectional. Therefore, actions to improve research conditions and techniques, in addition to setting up large well-characterized cohorts in Asian and Africa is needed.

In the present study, we analyzed publications on gut microbiota and T1D and listed the most influential research, researchers, and institutions. This information may be helpful for those who want to learn from the outstanding studies and seek collaboration opportunities. Another key feature of our study consisted of highlighting the hotspots and change trends of research on T1D and gut microbiota. The high-frequency keywords and clustering analysis indicated the current hotspots and main research directions. Our analysis of animal studies and human research conducted in the past two decades suggested that gut microbiota is closely related to the onset of islet β-cell autoimmunity in T1D from seven perspectives. Several environmental triggers, especially gut microbiota, contribute to islet β-cell autoimmunity based on human research (Cluster 1 and Cluster 2), and the most prevalent stage has advanced from children to early pregnancy although the exact reasons for this shift must be further investigated. Subsequently, the causative link between gut microbiota and T1D has gradually been proved in animal models. From Cluster 3 to Cluster 6, the hot topics explored by researchers are associated with the mechanism underlying the effect of gut microbiota on T1D, including alterations in the gut microbiota and its metabolites, which can cause changes in intestinal permeability, mimic molecules in β-cell islets, and induce oxidative stress, inflammation abnormal innate and adaptive immune responses.

Among the top of the 50 most frequently used author keywords and keywords plus, 16 s RNA sequencing and detecting short chain fatty acids stand out as major methods for exploring alterations in the gut microbiome composition and its metabolites. The terms “metagenomics” and “metabolomics” have been more frequently used in recent research, and the advent of multi-omics profiling technologies has enabled us to identify the gut microbiome composition at species level, to explore the functional potential of the gut microbiome, and to investigate mycobiomes and virome in to the context of T1D (Vehik et al., 2019; Auchtung et al., 2022). These new research technologies are more comprehensive and accurate tools for testing and verifying alterations in the gut microbiota and its effect on T1D.

The keywords cloud has showed that T cells play a key role in T1D progression regulated by gut microbiota, as confirmed by many studies and this research continues. Moreover, other components of the immune system, most recently neutrophils, have also gained considerable research attention. Some of the important goals of these studies are translational applications of gut microbiota toward improving therapeutic strategies for T1D (Cluster 7). Recently, an increasing number of studies have suggested that gut microbiota is involved in the glycemic control and complications of T1D. Therefore, gut microbiota-targeted therapeutic strategies are promising new approaches not only in preventing or halting disease progression but also in improving the clinical outcome of T1D patients. The present gut microbiota-targeted therapeutic strategy in T1D, which consists of diet, probiotics, prebiotics, fecal transplant, among other measures, has made only an initial progress. However, gut microbiota-targeted therapeutic strategies have already brought venture, benefits, challenges, and opportunities for the prevention and cure of T1D.

Machine learning, a newly emerged keyword in the field of gut microbiota in T1D, has promoted the development of research on integrating gut microbiota to predict disease progress and therapeutic response. Current research has revealed that gut microbiota may be able to predict the diabetes risk. Simultaneously, whether in individuals without diabetes or patients with type 2 diabetes (T2D) or T1D, gut microbiota can predict the individual postprandial glucose response (Zeevi et al., 2015; Mendes-Soares et al., 2019; Shilo et al., 2022b). In addition, integrating clinical and gut microbiome characteristics can predict the short-and long-term glucose status and β-cell function of T2D patients (Aasmets et al., 2021). In the field of T1D, the microbial risk score and the genetic risk score model predicted well the impact of interactions between host genetics and gut microbiome on disease progression (Wang C. et al., 2022). We believe that machine learning is a potential research direction in the field of gut microbiota and T1D, which enables the integration of medical information and gut microbiota data to identify predictive microbiota biomarkers and to develop customized therapy toward reshaping the gut microbiota of T1D patients.

In the present study, we extracted the publications of original research articles on gut microbiota and T1D published in SCIE of WoSCC and conducted bibliometric and visualization analysis. The development and deep research on gut microbiota in NOD mice would bringing T1D to a new translational level in the field of gut microbiota. And the application of multi-omics and machine learning approaches will be a necessary future step for better understanding the gut microbiota in T1D and develop customized therapy toward reshaping the gut microbiota of T1D patients. Based on these, the warming of gut microbiota-targeted therapeutic strategies that would help develop optimal strategies for “precision” gut microbiota modulation in T1D, and progress is being made toward this goal, but there is still a lot to do.

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

KG, JL, and JH performed the literature search and drafted the manuscript. JH provided ideas and suggestions. KG, JL, XL, JH, and ZZ discussed and revised the manuscript. All authors contributed to the article and approved the submitted version.

This work was funded by the National Natural Science Foundation of China (grant nos. 82100899 awarded to JH and 81820108007 awarded to ZZ), the Natural Science Foundation of the Hunan province of China (grant no. 2021JJ40833 awarded to JH) and the Pilot and Feasibility grant of the Yale Diabetes Research Center (grant no. DK 045735 awarded to JH).

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.

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