A Bibliometric Analysis of Exosomes Associated with Rheumatic Diseases in the 21st Century

Abstract

Purpose

Numerous studies have suggested that exosomes are associated with rheumatic diseases, but no bibliometric analysis has been performed. This study presents the first comprehensive bibliometric analysis aiming to evaluate the current research hotspots and to anticipate future trends.

Methods

An electronic search was conducted in the Web of Science Core Collection (WOSCC) using exosome and rheumatic disease-specific terminology to identify eligible studies published from January 1, 2000 to October 19, 2024. Only English-language articles and review articles were selected for bibliometric analysis. Data analysis and visualization were conducted using CiteSpace 6.2.R3, VOSviewer 1.6.18, and the Bibliometrix R package.

Results

A total of 1,251 publications with 49,374 citations were extracted from the WOSCC database. Both publication and citation frequency increased steadily. 255 different countries or regions, 4,413 institutions and 7,213 authors contributed to the field. China and the USA are the leading countries and Shanghai Jiao Tong University has a significant influence. Théry C is the most frequently co-cited researcher. Most papers are published in Frontiers in Immunology, while Stem Cell Research & Therapy has the highest citations. Research is primarily concentrated in cell biology, immunology, and experimental medicine. Exosm, mesenchymal stem cells (MSCs), autoimmunity, regeneration, and others are major areas of research in this field. Research hotspots primarily focus on the diagnostic potential and therapeutic applications of exosomes in osteoarthritis and rheumatoid arthritis. Exosomes derived from MSCs and their cargo, such as microRNAs (miRNAs), have the potential to serve as biomarkers and therapeutic vehicles in these diseases.

Conclusion

This study firstly quantifies and identifies the current status and research frontiers of exosomes in RDs by using bibliometric analysis, which may provide valuable insights for researchers to navigate trends and emerging applications into the field.

Video Abstract

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Introduction

Exosomes are endocytic membrane-derived vehicles that ranging from 30 to 120 nm in size, identified as key mediators in intercellular communication.¹ Released by a variety of cell types, these vehicles are consistently found in bodily fluids such as breast milk, urine, plasma, and saliva.² Exosomes carry a diverse cargo, including proteins, lipids, DNA, and various RNA species.³ Originating in endosomes, their biogenesis involves interactions with other intracellular vesicles and organelles, shaping their final content.⁴ Each exosome reflects the characteristics and functions of its parent cell. The unique biological properties of exosomes enable them to protect internal biomolecules from deterioration and evade immune clearance, allowing for the delivery of more effective cargo with potential therapeutic targeting effects.⁵ Moreover, exosomes can penetrate various biological barriers, including the blood-brain barrier, while their associated toxic side effects are minimized.^6,7

Rheumatic diseases (RDs) encompass a range of disorders primarily targeting the musculoskeletal system, directly affect bones, joints, muscles, connective tissues, and periarticular soft tissue.⁸ The primary pathobiological characteristic of many RDs is the development of an excessively self-reactive, antigen-driven immune response, which contributes to the complex inflammatory processes and tissue damage.⁹ Due to the chronic nature of these disorders and the frequent adverse effects of conventional treatments, patients often seek complementary and alternative therapies, hoping for “less toxic” remedies.¹⁰ Exosomes have been extensively studied for their role in RDs, particularly in relation to autoimmune and inflammatory conditions such as rheumatoid arthritis (RA), osteoarthritis (OA), and systemic lupus erythematosus (SLE). Exosomes derived from mesenchymal stem cells (MSCs), synovial fluid (SF), or immune cells carry proteins, lipids, and nucleic acids capable of modulating immune responses and tissue repair. Long non-coding RNAs (lncRNAs) in exosomes have been implicated in the pathogenesis of RA through the nuclear factor kappa B (NF-κB) and Wnt signaling pathways, with the resulting imbalance in Th17/Treg cell production contributing to synovial cell damage.¹¹ Exosome-derived miRNAs, such as miR-451a and miR-25-3p, are promising candidates for early diagnosis of RA.¹² Additionally, exosomal miR-26b-5p regulates the polarisation of macrophages and the hypertrophy of chondrocytes in OA.¹³ Exosomes also help determine the cellular origin of disease onset. In the synovial fluid of patients with inflammatory arthritis, the most common exosomes are derived from platelets, T cells and B cells.¹⁴ Exosomes from various sources demonstrate potential diagnostic and therapeutic effects in RDs. MSCs-derived exosomes have been shown to modulate immune responses and exhibit immune suppressive effects. Exosomal miR-16 and miR-21 secreted by bone marrow mesenchymal stem cells (BMSCs), as well as miR-146a-5p from umbilical cord mesenchymal stem cell (UC-MSCs) exosomes, promote the transition of macrophages to an anti-inflammatory M2 macrophage phenotype, thereby inhibiting the inflammatory response.¹⁵ Exosomes are recognized as emerging leaders in regenerative medicine.¹⁶ The integration of exosomes with biomaterials, such as hydrogels, has emerged as a novel therapeutic strategy. This approach not only lubricates joints but also serves as a drug delivery system, enabling sustained release of therapeutic agents.^17,18 Additionally, engineered exosomes modified with specific bioactive molecules can regulate corresponding target proteins, thereby enhancing anti-inflammatory and immunomodulatory effects.¹⁹ For example, engineered exosomes overexpressing miR-140 target calpain 1, modulate mitophagy, and ameliorate OA progression via intra-articular delivery.²⁰ In conclusion, exosomes can influence RDs through various pathways.

Bibliometrics is a field of quantitative analysis applied to scholarly literature, capable of mapping intellectual structures, identifying research trends, and assessing scholarly impact. Its core value lies in providing a systematic method to measure and evaluate the vast output of scientific research, offering insights on the evolution of research and the interconnections between various research domains. However, recent studies suggested that exosomes hold significant potential in the treatment of RDs, and bibliometric analysis on exosomes in RDs have not yet emerged. This study aims to address this gap by performing a bibliometric analysis of exosomes associated with RDs in the 21st century. Our objective is to evaluate the current state of research to gain a better understanding of the research dynamics in this field. Additionally, we seek to predict future thematic development and research priorities by examining research trends and hotspots. This analysis will also emphasize the impact of exosomes on the diagnosis and treatment of OA and RA, underscoring the importance of continued research in this field.

Methods

Search Strategy and Data Collection

The literature source for this analysis is the Web of Science Core Collection (WOSCC), which is recognized for its comprehensive and standardized coverage of international scientific literature. The search strategy utilized the following search string: (TS=(“rheumatic disease” OR “rheumatology” OR “rheumatism” OR “rheumatoid arthritis” OR “psoriatic arthritis” OR “osteoarthritis” OR “gout” OR “pseudogout” OR “arthritis” OR “Takayasu arteritis” OR “ankylosing spondylitis” OR “spondyloarthropathy” OR vasculitis OR “granulomatosis with polyangiitis” OR “Wegener granulomatosis” OR “microscopic polyangiitis” OR “Behçet” OR “systemic lupus erythematosus” OR “Sjogren’s syndrome” OR “systemic sclerosis” OR “scleroderma” OR “connective tissue disease” OR “autoimmune disease” OR “myositis” OR “polymyositis” OR “dermatomyositis” OR “idiopathic inflammatory myositis” OR “antiphospholipid syndrome” OR “fibromyalgia” OR “Still’s disease” OR “polymyalgia rheumatica”)) AND TS=(“exosomes” OR “exosome” OR “exosomal”). The time frame was restricted to the 21st century (January 1, 2000 to October 19, 2024). Only articles and review articles published in English were considered to maintain the academic rigor and linguistic consistency of the analysis. Duplicates were removed using CiteSpace. All highly cited papers indexed by the WOSCC were extracted into a table format. The data were downloaded and verified independently by two researchers (YYZ and SWW) to assure the accuracy of the study. Any discrepancies were addressed through the third-party (XYA). The flow chart depicted in Figure 1 illustrates the data extraction and analysis process.

Figure 1.

The flow chart for data extraction and analysis process.

Data Analysis and Visualization

We use CiteSpace 6.2. R3, VOSviewer 1.6.18, and Bibliometrix R packages to conduct data analysis and visualization of the countries or regions, institutions, authors, journals, keywords, and references involved in this field. CiteSpace is renowned for its ability to visualize citation networks, knowledge structures, research fronts, and trends in scientific domains.²¹ Node size indicates relative proportion and line thickness shows connection strength.²² It provides a range of metrics to assess the significance of nodes within a network. Temporal metrics like citation burst indicate periods of abrupt change in the frequency of an entity, highlighting emerging terms.²³ Structural metrics such as centrality, modularity, and silhouette score are used. Nodes with high centrality (≥ 0.1) generally connect different clusters and are quantitatively considered pivotal in network analysis. The modularity and silhouette metrics, namely the Q value and the S value, are important for assessment. Generally, the Q value ranges from 0 to 1, and the S value ranges from −1 to 1. Low Q value indicates fuzzy clusters, while high Q value indicates clear cluster structure. The Q value greater than 0.3 indicates the identified community structure is significant. The S value exceeding 0.7 considered high credibility and exceeding 0.5 considered reasonable. If the S value approaches 1, the cluster is perfectly separated from others. If the S value approaching 0 suggests ambiguous cluster boundaries, and approaching −1 suggests invalid partitioning.²⁴ VOSviewer is a software tool designed for creating and visualizing bibliometric networks. Node size indicates item frequency, line thickness represents the strength of association, and colors distinguish thematic clusters.²⁵ Bibliometrix is an R package designed for comprehensive science mapping analysis, providing a suite of tools for quantitative research in bibliometrics and scientometrics. This package supports three key phases of analysis: data importing and conversion to R format, bibliometric analysis of a publication dataset, and building and plotting matrices for co-citation, coupling, collaboration, and co-occurrence analysis.²⁶

Results

Analysis of Publication Outputs and Growth Trend Predictions

Annual publications can reflect research progress and trends in the field. From 2000 to 2024, a total of 1,251 publications were extracted from WOSCC database, including 780 articles and 471 reviews. As of October 19, 2024, these articles received 49,374 citations, equating to an average of 39.47 citations per article. As shown in Figure 2, the overall publication trend has increased since the 21st century. In 2020, the number of papers grew rapidly, reaching 100 for the first time. Since then, there has been an exponential increase in the number of papers each year. Moreover, as demonstrated in Supplementary Figure 1, the dominance of research articles within this growth continues and even increases. Additionally, citation frequency has increased significantly. The fitting equation for publications was y =0.8623e°.^2157x, and the simulation curve clearly indicates a relatively strong coefficient of determination (R² = 0.8987), which suggests that the number of annual articles is expected to steadily increase.

Figure 2.

The annual publication, annual citation frequency, and the growth trend prediction.

Analysis the Network of Cooperation Across Countries or Regions and Institutions

A total of 255 different countries or regions were extracted from our database. The top 10 countries with the highest number of publications and citations are reported in Table 1. China was the most productive country (n = 699, 55.88%), followed by the USA (n = 205, 16.39%), Italy (n = 67, 5.36%). Meanwhile, China has established a leading position in terms of citation frequency and H-index, indicating its significant contribution to the development of this field and its extremely high degree of influence. Figure 3A illustrates the collaborative network between countries or regions. Supplementary Table 1 shows the top three countries or regions with high centrality are the USA (0.45), Germany (0.22), and China (0.22). The burst intensity revealed that the USA had the biggest strength, and the longest citation burst (2000 to 2018, strength 23.66) (Supplementary Figure 2). These analysis highlight that the global research focus is primarily on the function of exosomes and potential therapeutic applications in RDs (like cartilage repair and regeneration).^27,30

Table 1.

The Top 10 Countries or Regions of the Number of Publications and Frequency of Citations

Rank	Country or Region	Article Counts	Year	H-Index	Total Citations	Average Citations
1	China	699	2010	68	19,666	28.13
2	USA	205	2000	58	13,219	64.48
3	Italy	67	2001	26	3446	51.43
4	South Korea	57	2015	20	1931	33.88
5	Iran	47	2017	20	1245	26.49
6	Japan	42	2010	19	1259	29.98
7	Germany	38	2002	21	1569	41.29
8	England	33	2010	17	874	26.48
9	Spain	33	2004	18	1312	39.76
10	France	30	2001	18	3635	121.17

Note: Year means the first publication year recorded for the countries or regions.

Figure 3.

The network map of cooperation between countries or regions (A) and institutions (B).

Notes: Data for the “Taiwan” region is included within “People’s Republic of China”.

An analysis of 4,413 institutions shows that the primary research institutions in this field are primarily based in China. The visual analysis reveals that Shanghai Jiao Tong University holds significant influence in the field, which published 43 articles with 2,694 citations, with an average of 62.65 citations per article and an H-index of 19. Furthermore, although the Pennsylvania Commonwealth System of Higher Education published only 20 articles, with an average citation of 160.45, far surpassing the other institutions (Table 2). At the same time, Supplementary Table 1 indicates that it is also the institution with the highest centrality. Figure 3B demonstrated that network collaboration between institutions. Radboud University Nijmegen showed the strongest citation burst (2001 to 2007, strength 7.9) (Supplementary Figure 2).

Table 2.

The Top 10 Institutions of the Number of Publications and Frequency of Co-Citations

Rank	Institution	Article Counts	Year	H-Index	Total Citations	Average Citations	Country
1	Shanghai Jiao Tong University	42	2017	19	2694	62.65	China
2	Central South University	34	2013	18	1100	32.35	China
3	Sichuan University	31	2020	13	701	22.61	China
4	Sun Yat Sen University	28	2018	15	1244	42.90	China
5	Southern Medical University - China	26	2019	10	412	15.85	China
6	Fudan University	23	2020	9	342	14.87	China
7	Chinese Academy of Medical Sciences - Peking Union Medical College	23	2018	11	357	14.88	China
8	Anhui Medical University	22	2018	10	627	28.50	China
9	Peking University	21	2018	9	294	14.00	China
10	Nanjing Medical University	21	2010	14	839	39.95	China

Note: Year means the first publication year recorded for the institutions.

Analysis the Network of Authors and Co-Citation Authors

Analyzing authors’ contributions provides a straightforward means of identifying academic pioneers in the field. Using VOSviewer, we visualize an extensive analysis of 7,213 authors as shown in Figure 4. To enhance the clarity of the visualization, Figure 4A demonstrated a collaborative network analysis on a subset of 85 authors, each having at least 11 publications, ultimately forming 18 clusters. Cluster #1 (red) is the largest, comprising 11 items. Cluster #2 (green) forms a collaborative network centered around professors Liang Yujie, Duan Li, and Xu Xiao from Shenzhen University, who are also the top three contributors in terms of publication count. Their research emphasizes the role of exosomes as effective carriers for delivering miRNA into chondrocytes in osteoarthritis treatment.^31,35 Cluster #3 (blue) primarily consists of researchers hailing from IRCCS Institute Orthopedic Galeazzi, with De Girolamo, Laura as the central figure, and their primary research focus on adipose-derived mesenchymal stem cells (ASCs)-extracellular vehicles (EVs).^36,38 Cluster #4 (yellow) is centered on Toh Wei Seong from the National University of Singapore, who proposed MSCs exosomes could mediate M2-like macrophage polarization in the immunoregulatory mechanism.³⁹ Notably, Table 3 highlights Toh Wei Seong ranks 4th in publication count and is the only author in the top 10 by publication output who also ranks within the top 10 for citation frequency. It is evident that active cooperation occurs within the same cluster, whereas cross-cluster collaboration is not discernible. Figure 4B demonstrates that Théry C is the most frequent co-citations author, with work indicating that exosomes possess a unique molecular composition and potent immunostimulatory properties,²⁹ followed by Zhang S, Tao S, and Cosenza S. The authors were primarily grouped into 4 clusters in the co-citation network, namely Théry C, Raposo G, Kim Sh, etc. from cluster #1 (red); Zhang Sp, Tao Sc, Cosenza S, Mao Gp, Toh Ws, etc. from cluster #2 (blue); Zhang Y, Kalluri R, etc. from cluster #3 (green); Lai Rc, etc. from cluster #4 (yellow). Cluster #1 (red) and cluster #2 (blue) focus on clinical research involving mesenchymal stem cells-derived exosomes for the prevention and treatment of inflammatory arthritis.^40,43

Figure 4.

The visualization map of authors’ co-authorship (A) and co-citation (B).

Table 3.

The Top 10 Authors of the Number of Publications and Frequency of Co-Citations

Rank	Author	Article Counts	Citations	Total Link Strength	Rank	Author	Co-Citations	Total Link Strength
1	Liang, Yujie	13	714	53	1	Théry, C	400	7478
2	Duan, Li	11	688	50	2	Zhang, Sp	310	7204
3	Xu, Xiao	11	710	50	3	Tao, Sc	306	7838
4	Toh, Wei Seong	10	1482	30	4	Cosenza, S	298	7061
5	Xia, Jiang	9	645	31	5	Zhang, Y	262	5685
6	De Girolamo, Laura	8	168	31	6	Mao, Gp	225	6595
7	Gupta, Ashim	8	143	11	7	Kalluri, R	191	3531
8	Jorgensen, Christian	8	1148	15	8	Raposo, G	191	3632
9	Noel, Daniele	8	1148	15	9	Toh, Ws	188	3798
10	Pruijn, Gjm	8	405	12	10	Kim, Sh	187	3305

Analysis of Journals, Co-Citation Journals, and Research Categories

To assess the impact and academic status of journals in this field, we performed a visual analysis of the journals. As shown in Table 4 and Figure 5A, the journal with the highest number of publications is Frontiers in Immunology (n = 63, 5.04%), followed by International Journal of Molecular Sciences (n = 54, 4.32%) and Stem Cell Research & Therapy (n = 30, 2.40%). Among the top 10 productive journals, there were 7 journals ranked in Q1 according to Journal Citation Reports (JCR), 5 of which had an impact factor (IF) higher than 5. The journal with the highest citation is Stem Cell Research & Therapy (n = 2248), followed by Journal of Immunology (n = 1691), and International Journal of Molecular Sciences (n = 1684). Notably, the top three most productive journals also rank highly in terms of citation frequency, underscoring their significant academic influence, which may be attributed to their broad academic coverage. Additionally, we conducted an analysis of the top 20 research categories in this field, as depicted in Figure 5B. The primary research areas are focused on cell biology, immunology, experimental medicine research, biochemistry, and molecular biology. To explore the thematic distribution and citation trajectories of academic journals, we used a dual-map overlay of journals to highlight the extensive communication across interdisciplinary fields. This visual representation illustrates the citation connections between two distinct sections: the left side denotes the citing journals, while the right side denotes the cited journals. Figure 5C shows that journals within the realms of Molecular/ Biology/ Genetics are frequently cited by journals from Molecular/ Biology/ Immunology and Medicine/ Medical/ Clinical, illustrating the translation of basic research into clinical research.

Table 4.

The Top 10 Journals and Co-Cited Journal

Rank	Journal	Article Counts	H-Index	JCR (2025)	IF (2025)	Co-Cited Journal	Co-Citations	JCR (2025)	IF (2025)
1	Frontiers in Immunology	63	23	Q1	5.9	Stem Cell Research & Therapy	2248	Q1	7.3
2	International Journal of Molecular Sciences	54	16	Q1	4.9	Journal of Immunology	1691	Q2	3.4
3	Stem Cell Research & Therapy	30	19	Q1	7.3	International Journal of Molecular Sciences	1684	Q1	4.9
4	Journal of Nanobiotechnology	29	14	Q1	12.6	Frontiers in Immunology	1617	Q1	5.9
5	Frontiers in Bioengineering and Biotechnology	26	13	Q1	4.8	Scientific Reports	1536	Q1	3.9
6	Arthritis Research & Therapy	21	13	Q1	4.6	Osteoarthritis and Cartilage	1501	Q1	9.0
7	Cells	21	14	Q2	5.2	Plos One	1489	Q2	2.6
8	International Immunopharmacology	19	7	Q2	4.7	Journal of Extracellular Vesicles	1440	Q1	14.5
9	Frontiers in Cell and Developmental Biology	18	11	Q2	4.3	Biomaterials	1359	Q1	12.9
10	Autoimmunity Reviews	14	11	Q1	8.3	Arthritis Research & Therapy	1295	Q1	4.6

Figure 5.

The analysis of journals, co-citation journals, and research categories. (A) Core Source Journals Identified by Bradford’s Law. (B) Nightingale rose chart of the top 20 research categories. (C) A dual-map overlay of the journals.

Analysis of Co-Occurrence Keywords

A meticulous analysis of keywords was conducted to vividly identify the active research areas, the emerging trends, the development of new knowledge domains, and the relationships between different topics in this field. Figure 6A reveals a total of 372 nodes and 706 edges. The top three most prominent keywords are extracellular vesicles (n = 390), exosm (n = 316), and mesenchymal stem cells (n = 310), probably due to our search strategy. Exosomes are a subset of extracellular vesicles, but in many cases, the terms “exosomes” and “extracellular vesicles” are used interchangeably.⁴⁴ Exosomes derived from MSCs have garnered widespread attention due to their potential in tissue repair and regenerative medicine. The work of Zhang S is particularly representative. They discovered that exosomes from MSCs can promote cartilage regeneration through multiple mechanisms, including enhancing proliferation, reducing apoptosis, modulating immune responsiveness, and restoring matrix homeostasis.^30,43,45 Rheumatoid arthritis (n = 215) and osteoarthritis (n = 161) are the most extensively studied diseases. The keyword “expression” exhibits the highest centrality score of 0.54 within this network. Its high-cited articles indicate that exosomes from various sources, carrying specific molecular expressions such as miRNAs and proteins, have therapeutic potential in modulating pathological states and improving disease symptoms.^46,48 Supplementary Table 2, indicate that the keyword analysis also encompasses various laboratory indicators, including the pathological mechanisms of disease (such as inflammation),⁴⁹ construction of experimental models (such as collagen-induced arthritis models),^50,51 detection methods (such as in vitro or vivo experiments),⁵² and indicators to assess therapeutic efficacy (such as vascular endothelial growth factor).⁴⁶ “Regeneration” is a key word widely used in clinical treatment. MSCs have been recognized as a rational therapeutic strategy in regenerative medicine. However, compared with MSCs, exosomes derived from MSCs offer a more stable and controllable therapeutic entity. This innovative research direction has opened new avenues for the development of regenerative medicine.⁵³

Figure 6.

The analysis of co-occurrence keywords. (A) The network visualization map of keywords. (B) The timeline view of keywords cluster.

Keywords were classified into 13 clusters as shown in Figure 6B, including cluster #0 human pm scl, cluster #1 cancer, cluster #2 fas ligand, cluster #3 regenerative medicine, cluster #4 systemic sclerosis, cluster #5 chondrocytes, cluster #6 extracellular vesicles, cluster #7 expression, cluster #8 rheumatoid arthritis, cluster #9 dendritic cells, cluster #10 mesenchymal stromal cells, cluster #11 mesenchymal stem cell, cluster #12 microparticle. The keyword cluster timeline boasted a modularity Q value of 0.7796 and a mean silhouette S value of 0.9033, which signifies a well-structured and interconnected field.²⁴ The timeline reveals a dynamic and evolving research field, with a clear progression from basic science to translational and therapeutic research. It highlights the multidisciplinary nature in this field, encompassing immunology, cell biology, and regenerative medicine, with a growing emphasis on the role of exosomes in disease pathogenesis and potential therapeutic applications. Supplementary Figure 3 showed the keyword citation burst analysis from 2000 to 2024. The keyword “dendritic cells” shows the strongest citation burst (2006 to 2018; strength 18.03). The keyword with the longest duration is “autoantibody” and “autoimmune disease” for lasting 14 years.

Therefore, we have made a systematic summary of the expression of exosomes in RDs, presented in Table 5 and Table 6, showing that exosomes are significantly expressed in specific RDs, particularly OA and RA. Current research is mainly conducted in animal models and other basic studies. The functions of exosomes vary depending on their source and the cargo they carry, with most exosomes originating from MSCs and expanding their functions beyond their inherent roles. Exosomes can carry a variety of cargoes, the most important of which are miRNAs, which regulate the expression of various protein-coding genes. The expression of exosomes in RDs involves multiple biological mechanisms and pathways, providing a basis for the development of new therapeutic strategies and potentially improving the treatment outcomes of RDs. These findings not only reveal the current research focus but also may provide significant insights into predicting the future development trends of the field.

Table 5.

The in-Depth Impact of Exosomes Sourced From Various Types on OA

Exosome Source	Exosome Cargo	Model	Biological Effects	Study
MSCs	MiR-92a-3p	Mouse	Regulate cartilage development and homeostasis by inhibiting Wnt5a expression	[48]
	LncRNA-KLF3-AS1	Mouse	Induce chondrocyte proliferation and inhibit chondrocyte apoptosis via miR-206/GIT1 axis	[47]
	LncRNA-KLF3-AS1	Rat	Promote cartilage repair and chondrocyte proliferation	[54]
	N.D.	Mouse	Protect chondrocytes from apoptosis and inhibit macrophage activation	[55]
	N.D.	Mouse	Regulate the level of chondrocyte glutamine metabolism	[56]
	N.D.	Mouse	Rescue cartilage injury through the reduction of ferroptosis in macrophages via GOT1/CCR2/Nrf2/HO-1 signaling pathway	[57]
	N.D.	Rat	Attenuate inflammation and restore matrix homeostasis	[43]
	N.D.	Rabbit	Inhibit mitochondrial dysfunction-induced apoptosis of chondrocytes	[58]
BMSCs	MiR-206	Mouse	Promote osteoblast proliferation and differentiation by reducing ELF3	[59]
	MiR-136-5p	Mouse	Promote chondrocyte migration and inhibit chondrocyte degeneration by targeting ELF3	[60]
	MiR-125a-5p	Mouse	Induce chondrocyte migration and inhibit cartilage degeneration by downregulating E2F2	[61]
	MiR-9-5p	Rat	Alleviate inflammation and protect cartilage by inhibiting syndecan-1	[62]
	MiR-127-3p	Rat	Relieve chondrocyte damage by inhibiting cadherin 11-mediated Wnt/beta-catenin pathway	[63]
	MiR-361-5p	Rat	Alleviate chondrocyte damage by targeting DDX20 and inactivating the NF-κB pathway	[64]
	MiR-326	Rat	Inhibit pyroptosis of chondrocytes and cartilage by targeting HDAC3 and STAT1//NF-κB p65	[65]
	CircYAP1, miRNA-21	Rat	Mitigate OA symptoms and pathology progression through circYAP1/ miRNA-21/ TLR7 axis	[66]
	CircRNA_0001236	Mouse	Alleviate cartilage degradation and enhance cartilage repair through miR-3677-3p/Sox9 axis	[67]
	LncRNA MEG-3	Rat	Reduce the senescence and apoptosis of chondrocytes	[68]
	LncRNA SNHG7	Human chondrocytes	Inhibit inflammation and ferroptosis through miR-485-5p/FSP1 Axis	[69]
	LncRNA LYRM4-AS1	Chondrocytes	Regulate the lncRNA LYRM4-AS1-GRPR-miR-6515-5p to alleviate inflammation	[70]
	TGF-131	Mouse	Inhibit abnormal angiogenesis in subchondral bone	[71]
	Runx2	Rabbit	Promote the proliferation, migration, and phenotypic maintenance of articular chondrocytes	[72]
	N.D.	Mouse	Abrogate the aberrant nerve invasion in subchondral bone	[73]
	N.D.	Rat	Promote cartilage repair and ECM synthesis, and relieve pain	[74]
	N.D.	Rat	Promote the phenotypic transformation of synovial macrophages from M1 to M2	[75]
	N.D.	Rat	Inhibit chondrocyte apoptosis and the expression of MMPs, and regulate dynamin-related protein 1-mediated mitophagy	[76]
	N.D.	Rat	Attenuate chondrocyte ferroptosis by disrupting the METTL3-m6A-ACSL4 axis	[77]
	N.D.	Chondrocytes	Protect chondrocytes by inhibiting cell apoptosis and inflammatory response	[78]
UC-MSCs	MiRNAs	Rat	Promote chondrocyte proliferation and migration, inhibit chondrocyte apoptosis and regulate the polarization of macrophages	[79]
	MiR-100-5p	Human chondrocytes	Inhibit ROS production and cell apoptosis through the miR-100-5p/NADPH oxidase 4 axis	[80]
	MiRNAs	Human chondrocytes	Anti-inflammation by reversing COL2A1 and MMP13	[81]
	N.D.	Mouse	Anti-inflammation by reducing pro-inflammatory cytokines and increasing Arg-1 expression in macrophages and synovial fibroblasts	[82]
	N.D.	Rat	Promote cartilage regeneration by downregulating synovial fluid cytokines, MMP13 and ADAMTS-5, and upregulating COL2	[83]
WJMSCs	MiRNAs	Rabbit	Enhance the reparative effect of the acellular cartilage ECM scaffold by regulating the microenvironment of the articular cavity	[84]
SMSCs	MiR-155-5p	Mouse	Enhance proliferation and migration, attenuate apoptosis, and modulate ECM secretion in chondrocytes	[85]
	MiR-485-3p	Mouse	Relieve cartilage degradation by targeting neuropilin-1 and succedent inactivation of the PI3K/Akt pathway	[86]
	MiR-320c	Rat and human chondrocytes	Suppresse ECM degradation and chondrocyte apoptosis to enhance chondrogenesis by targeting ADAM19	[87,88]
	MiR-140-5p, Wnt5a, Wnt5b	Rat	Enhance the proliferation and migration without damaging ECM secretion	[41]
	MiR-129-5p	Human chondrocytes	Inhibite HMGB1 release	[89]
	MiR-212-5p	Human chondrocytes	Suppress chondrocyte degeneration and inflammation by targeting ELF3	[90]
	MATN3	Mouse	Prevent ECM degradation and autophagy defects by delivering MATN3/IL-17A	[52]
	BMP-7	Mouse	Attenuate inflammation and cartilage injury by synovial macrophages M2 polarization	[91]
ESC-MSCs	N.D.	Mouse	Balance synthesis and degradation of cartilage ECM	[92]
IPFP-MSCs	MiR-100-5p	Mouse	Protect articular cartilage and ameliorate gait abnormalities by inhibiting the mTOR-autophagy pathway	[49]
ADSCs	MiR-93-5p	Mouse	Inhibit inflammation and alleviate the progression of OA by targeting miR-93-5p/ADAMTS9 signal axis	[93]
	miR-338-3p	Mouse	Inhibit Runx2 expression	[94]
	miR-486-5p	Rat	Alleviate endoplasmic reticulum stress induced chondrocyte apoptosis	[95]
	MiR-376c-3p	Rat	Mitigate chondrocyte degradation and synovial fibrosis through repress the Wnt-beta-catenin pathway by targeting Wnt3 or Wnt9a	[96]
	MiR-429	Rat	Ameliorate chondral injury via promote autophagy and chondrocyte proliferation by targeting FEZ2	[97]
	MiR-145, MiR-221	Chondrocytes	Promote chondrogenesis and suppress inflammation	[98]
USCs	MiR-140-5p	Rat	Enhance proliferation and migration, inhibit apoptosis and increase ECM secretion by downregulating VEGFA	[99]
	N.D.	Rat	Inhibit chondrocyte apoptosis and inflammation and promote chondrocyte proliferation, increase the structural integrity and smoothness of the cartilage surfaces	[100]
DPSCs	MiR-140-5p	Rat	Inhibit chondrocyte apoptosis by regulating the expression levels of apoptosis-related proteins	[101]
	N.D.	Mouse	Repress osteoclast activation by inhibiting TRPV4 activation	[102]
SHEDs	MiR-100-5p	Human chondrocytes	Suppress inflammation by repressing mTOR expression	[103]
	N.D.	Human chondrocytes	Suppress inflammation through the NF-κB pathway	[104]
CSPCs	N.D.	Rat	Promote cartilage repair by modulating immune responses, inhibiting inflammation, and improving the intracellular environment	[105]
SSCs	N.D.	Rat and rabbit	Promote meniscal healing in the avascular region through inflammation modulation, promotion of cell migration, and secretion of ECM components	[106]
SF	MiR-182	Rat and human chondrocytes	Participate in the dual variation of the OA microenvironment	[107]
	MiR-182-5p	Human chondrocytes	Downregulate TNFAIP8 and promote autophagy via the ATG/LC3 pathway	[108]
FLSs	MiR-146a	Rat	Modulate cartilage degradation and macrophage polarization through modulate the TLR 4/TRAF6/NF-κB pathway	[109]
	MiR-126-3p	Rat	Constrain chondrocyte inflammation and cartilage degeneration	[110]
	MiR-214-3p	Rat	Ameliorate chondrocyte inflammation and degeneration of cartilage tissues	[111]
	MiR-19b-3p	Rat and human chondrocytes	Enhance cartilage ferroptosis and damage by sponging SLC7A11	[112]
M2 macrophages	MiR-26b-5p	Mouse	Regulate macrophage polarization and chondrocyte hypertrophy by targeting TLR3 and COL10A1	[13]
	N.D.	Rat	Protect KOA by inhibiting the PI3K/AKT/mTOR Pathway	[113]
M1 macrophages	MiR-363	Human chondrocytes	Mediate the destructive effect of M1 macrophages on chondrocytes by repressing G3BP2	[114]
Vascular endothelial cells	N.D.	Mouse	Induce apoptosis via decrease the ability of chondrocytes to resist oxidative stress by inhibiting autophagy and p21 expression	[115]
Chondrocytes	MiR-95-5p	Human chondrocytes	Regulate cartilage development and homoeostasis via histone deacetylase 2/8[	[116]
	N.D.	Mouse	Restore mitochondrial dysfunction and polarize macrophage response toward an M2 phenotype	[117]
	N.D.	Rat	Accelerate cartilage calcification	[118]
Osteocytes	DLX2	Mouse	Mediate cartilage repair and inactivate the Wnt pathway	[119]
Osteoclasts	MiRNAs	Mouse	Decrease the resistance of cartilage to matrix degeneration, angiogenesis and sensory innervation	[120]
	MiR-212-3p	Mouse and human chondrocytes	Suppress the anabolism and accelerate the catabolism of chondrocytes by targeting TGF-beta 1/Smad2 signaling	[121]
Placenta	N.D.	Rat and human chondrocytes	Alleviate symptoms, suppress the expression of inflammatory and catabolic genes	[122]
Platelet	N.D.	Mouse	Promote chondrocyte proliferation and migration and attenuate cartilage degeneration to improve the microarchitecture of subchondral bone	[123]
PRP	N.D.	Rabbit	Protect articular cartilage and inhibit apoptosis via Wnt/β-catenin signaling pathway	[124]

Abbreviations: MSCs, Mesenchymal stem cells; BMSCs, Bone marrow MSCs; UC-MSCs, Umbilical cord MSCs; WJMSCs, Umbilical cord Wharton’s jelly MSCs; SMSCs, Synovial MSCs; ESC-MSCs, Embryonic stem cell-induced MSCs; IPFP-MSCs, Infrapatellar fat pad MSCs; ADSCs, Adipose -derived MSCs; USCs, Urine-derived stem cells; DPSCs, Dental pulp stem cells; SHEDs, Stem cells from human exfoliated deciduous teeth; CSPCs, Primary chondrogenic stem cells; SSCs, Skeletal stem cells; SF, Synovial fluid; FLSs, Fibroblast-like synoviocytes; PRP, Platelet-rich plasma; GIT1, G-protein-coupled receptor kinase interacting protein-1; GOT1, Glutamic-oxaloacetic transaminase 1; CCR2, C-C motif chemokine receptor 2; Nrf2, Nuclear factor erythroid 2-related factor 2; HO-1, Heme oxygenase 1; Elf3, E74-like factor 3; E2F2, E2F transcription factor 2; DDX20, Asp-Glu-Ala-Asp-box polypeptide 20; HDAC3, Histone deacetylase 3; STAT1, Signal transducer and activator of transcription 1; YAP1, Yes-associated protein 1; TLR, Toll-like receptor; Sox9, Sex-determining region Y-box 9; SNHG7, Small nucleolar RNA host gene 7; FSP1, Ferroptosis suppressor protein 1; GRPR, Gastrin-releasing peptide receptor; TGF, Transforming growth factor; ECM, Extracellular matrix; METTL3, Methyltransferase like 3; M6A, N6-methyladenosine; ACSL4, Acyl-CoA synthetase long chain family member 4; ROS, Reactive oxygen species; COL2, Collagen type II; MMP, Matrix metalloproteinase; ADAMTS, A Disintegrin and metalloproteinase with Thrombospondin motifs; PI3K, Phosphatidylinositol 3-kinase; Akt, Protein kinase B; HMGB1, High mobility group protein-1; MATN3, Matrilin-3; BMP, Bone morphogenetic protein; FEZ2, Fasciculation and elongation protein zeta 2; VEGF, Vascular endothelial growth factor; TRPV4, Transient receptor potential vanilloid 4; TNFAIP, Tumor necrosis factor alpha-induced protein; ATG, Autophagy-related gene; LC3, Microtubule-associated protein 1A/1B-light chain 3; TRAF6, Tumor necrosis factor receptor-associated factor 6; SLC7A11, Solute carrier family 7 member 11; G3BP2, G3BP stress granule assembly factor 2; TGF-beta 1, Transforming Growth Factor-beta 1; Smad2, Mothers against decapentaplegic homolog 2.

Table 6.

The in-Depth Impact of Exosomes Sourced From Various Types on RA

Exosome Source	Exosome Cargo	Model	Biological Effects	Study
MSCs	MiR-150-5p	Mouse	Inhibit synoviocyte hyperplasia and angiogenesis via MMP14 and VEGF	[46]
	CircFBXW7	Rat	Attenuate cell proliferation, migration and inflammation by targeting miR-216a-3p/HDAC4	[125]
	LncRNA HAND2-AS1	Human chondrocytes	Suppress the activation of RA-FLSs via miR-143-3p/TNFAIP3/NF-κB pathway	[126]
]BMSCs	MiR-205-5p	Mouse	Regulate MDM2 in FLSs	[127]
	MiR-23-5p	Mouse	Relieve inflammatory response	[128]
	MiR-223	Rat	Regulate the activation of inflammasomes via downregulation of NLRP3 expression in macrophages	[129]
	LncRNA TUG1	Mouse	Ameliorate RA damage via BLIMP1-mediated Th17/Treg balance	[130]
	Proteins	Rat	Alleviate RA symptoms through shuttling proteins related to cell adhesion and tissue repair ability	[131]
	FGL1	Rat	Suppress the inflammations, specific rheumatoid and immunological markers, meditate the NF-κB pathway to inhibit cell apoptosis	[132]
UC-MSCs	MiR-150-5p	Mouse	Alleviate bone erosion and regulate bone immunity via the aryl hydrocarbon receptor	[133]
	MiR-140-3p	Rat	Attenuate joint injury by silencing serum- and glucocorticoid-inducible kinase 1	[134]
	MiR-451a	Rat	Inhibit RA SFs proliferation, migration and invasion by inhibiting ATF2	[135]
	N.D.	Mouse	Regulate the balance between Th1/Th17 and Treg cells	[136]
SMSCs	CircEDIL3	Mouse	Ameliorate arthritis severity by targeting circEDIL3/miR-485-3p/PIAS3/STAT3/ VEGF functional module	[137]
GMSCs	N.D.	Mouse	Reduce incidences and bone erosion of arthritis by suppressing the immune response	[138]
FLSs	MiR-486-5p	Mouse	Induce osteoblast differentiation by activating the BMP/Smad signaling pathway and repressing Tob1	[139]
	MiR-106b	Mouse	Suppresses chondrocyte proliferation and migration by downregulating PDK4	[140]
	MiR-124-3p	Rat	Promote macrophage migration via PTX3 and PSMB5	[141]
	CircFTO	Mouse	Deteriorate RA by enhancing m6A modification of Sox9 in chondrocytes	[142]
	LncRNA HOTTIP	Mouse	Increase inflammation by targeting the miR-1908-5p/ STAT3 axis	[143]
	lncRNA TRAFD1-4:1	Human chondrocytes	Suppress chondrocyte proliferation and migration by degrading cartilage extracellular matrix	[11]
Macrophages	MiR-103a	Mouse	Promote inflammation and angiogenesis via the downregulation of HNF4 and activation of JAK/STAT3 signaling pathway	[144]
PBMCs	LncRNA NEAT1	Mouse	Promote FLS proliferation and inflammation via the miR-23a/MDM2/SIRT6 axis	[145]

Abbreviations: GMSCs, Gingival MSCs; PBMSCs, Peripheral blood mononuclear cells; HDAC4, Histone deacetylase 4; MDM2, Murine double minute 2; NLRP3, NLR family pyrin domain-containing 3; BLIMP1, B lymphocyte-induced maturation protein 1; FGL1, Fibrinogen-like protein 1; ATF2, Activating transcription factor 2; PIAS3, Protein inhibitor of activated STAT3; PDK4, Pyruvate dehydrogenase kinase 4; PTX3, Pentraxin 3; PSMB5, Proteasome 20S subunit beta 5; TRAF1, Tumor necrosis factor-associated factor 1; HNF4A, Hepatocyte nuclear factor 4 alpha; JAK, Janus kinase; NEAT1, Nuclear paraspeckle assembly transcript 1; SIRT6, Sirtuin 6.

Analysis of Co-Citation References

A co-citation analysis was conducted to elucidate the structural relationships among citations and to provide insights into the development trends and interdisciplinary connections within the field.¹⁵⁰ Table 7, extracted from the WoSCC database, presents a quantitative summary of the most influential research in the field. The number of citations range from 1,652 to 514, with most influential works originating from the USA. Figure 7A showed the most highly cited article is “Regulation of immune responses by extracellular vehicles” by Robbins, PD, published in 2014 in Nature Reviews Immunology (n = 1652). It provides an in-depth examination of the intricate mechanisms through which extracellular vesicles regulate immune responses. It underscores their potential as therapeutic targets or diagnostic markers in immunological disorders.⁵⁰ The second-ranked article is “Membrane vesicles, current state-of-the-art: emerging role of extracellular vesicles” by György, B (n = 1622), which emphasize the burgeoning role of extracellular vesicles in mechanisms of intercellular communication and immune regulation.¹⁴⁶ The main content of highly co-cited references emphasizes the powerful immunomodulatory functions of exosomes. In addition, exosomes also serve as potential biomarkers and therapeutic vehicles, with clinical applications in treating and preventing various inflammatory diseases. The article “Exosome: from internal vesicle of the multivesicular body to intercellular signaling device” by Denzer K has the highest centrality score of 0.32, as shown in Supplementary Table 3. The second ranking is the article “Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells” by Valadi H (0.31). They reveal the physiological functions and characteristics of exosomes. For instance, follicular dendritic cells can bind to B-lymphocyte-derived exosomes on their cell surface.¹⁵¹ Exosomes contain mRNAs and microRNAs. These RNAs can be delivered to other cells and translated into proteins within the recipient cells, facilitating the transfer of information between cells.¹⁵² These articles are distributed across various journals, reflecting their relevance to immunology, oncology, rheumatology, regenerative medicine, and other disciplines.

Table 7.

The Top 10 Most Cited References

Rank	Article Title	First Author	Source	Time Cited	Country	Year
1	Regulation of immune responses by extracellular vesicles50	Robbins, PD	Nature Reviews Immunology	1652	USA	2014
2	Membrane vesicles, current state-of-the-art: emerging role of extracellular vesicles146	György, B	Cellular and Molecular Life Sciences	1622	Hungary	2011
3	Proteomic analysis of dendritic cell-derived exosomes: a secreted subcellular compartment distinct from apoptotic vesicles29	Théry, C	Journal of Immunology	1237	France	2001
4	Treatment of brain inflammatory diseases by delivering exosome encapsulated anti-inflammatory drugs from the nasal region to the brain147	Zhuang, XY	Molecular Therapy	1067	USA	2011
5	Immunoregulatory mechanisms of mesenchymal stem and stromal cells in inflammatory diseases27	Shi, YF	Nature Reviews Nephrology	742	China	2018
6	MSC exosomes mediate cartilage repair by enhancing proliferation, attenuating apoptosis and modulating immune reactivity30	Zhang, SP	Biomaterials	607	Singapore	2018
7	Exosomes from human saliva as a source of microRNA biomarkers148	Michael, A	Oral Diseases	552	USA	2010
8	Origins, structures, and functions of circulating DNA in oncology149	Thierry, AR	Cancer and Metastasis Reviews	548	France	2016
9	Emerging role of extracellular vesicles in inflammatory diseases51	Buzas, EI	Nature Reviews Rheumatology	536	Hungary	2014
10	Exosomes derived from miR-140-5p-overexpressing human synovial mesenchymal stem cells enhance cartilage tissue regeneration and prevent osteoarthritis of the knee in a rat model41	Tao, SC	Theranostics	514	China	2017

Figure 7.

The analysis of co-citation references. (A) The network visualization map of co-citation references. (B) The cluster visualization map of co-citation references.

The network shown in Figure 7 is pruned at a level that ensures the most significant connections, highlighting several key nodes and clusters that represent the central concepts and research foci within this domain, the modularity Q value of 0.7877 and a mean silhouette S value of 0.9095. Figure 7B identified 13 clusters, based on their content, these clusters were divided into two research directions. The first major research area encompasses RDs, represented by cluster #0 osteoarthritis, cluster #7 rheumatoid arthritis, and cluster #14 complications. Cluster #0, the largest cluster, focuses on the role of exosomes in promoting cartilage tissue regeneration and preventing osteoarthritis. The second principal research direction delves into the function and applications of exosomes in RDs. These clusters can be systematically categorized into three overarching groups: Molecular and cellular biology: cluster #2 reference genes, cluster #3 microparticles, cluster #9 microparticle, cluster #8 exocrine dysfunction, cluster #10 apoptotic bodies, and cluster #11 endosome; Immunology-related: cluster #1 autoimmunity, cluster #4 autoantibodies, cluster #12 toll-like receptor 4; Therapeutic applications: cluster #5 regeneration. The results of co-citation reference cluster align with the keyword analysis, revealing that research in this field is primarily concentrated on specific RDs. Research on exosomes spans multiple domains including genetics, cell biology, and molecular biology. In addition, the role of exosomes in immune responses and applications in regenerative medicine also shows great potential.

Discussion

In the 21st century (from 2000 to 2024), a total of 1251 publications and 49,374 citations related to RDs and exosomes were extracted from WOSCC database. The trend of annual publications and citations is expected to steadily increase. Notably, there was a rapid surge in the number of publications in 2020, which can be attributed to the widespread COVID-19 pandemic. This global health crisis has intensified the focus on autoimmune health,¹⁵³ as patients with rheumatic diseases are more susceptible to contracting COVID-19 compared to the general population.¹⁵⁴ The increased dominance of research articles throughout the pandemic years is also notable It suggests that research in this area, potentially involving bioinformatics or experimental modeling, demonstrated resilience in the face of laboratory restrictions. However, additional factors, such as governmental healthcare policies, must also be considered in this context. Research on this topic spans 255 countries or regions and 4,413 institutions. China and the USA are leading contributors, with Chinese institutions such as Shanghai Jiao Tong University and Central South University dominating the number of publications. Based on the analysis of the authors and co-cited authors, Liang, Yujie is the most productive author, with the top three authors with the highest number of publications. Théry C stands out as the most frequently cited researcher. We have identified Frontiers in Immunology, International Journal of Molecular Sciences, Stem Cell Research & Therapy, and Journal of Immunology as the core journals in this field. The dual-map overlay of journals suggests that clinical medical research requires a foundation in experimental studies in molecular biology, biotechnology, and genetics. Combining insights from the WOSCC database, the main research directions in this field focus on cell biology and immunology.

Through a detailed analysis of keywords and co-cited reference, the research focus and future development trends in the field during the 21st century can be discerned. As research progresses, the mysteries of exosomes are gradually being unveiled. Particularly, reference cluster analysis (such as cluster #3, cluster #8, cluster #9, and cluster #10) and co-citation reference centrality analysis both indicate that the composition, physiological characteristics, and applications of exosomes are the current focus of this field. Our research reveals that Théry C. is the most frequently cited author. As a leading figure in exosome research, she has revealed that exosomes play a crucial role in altering gene expression and intracellular signaling pathways in the recipient cells by transporting RNA, lipids, and proteins. Exosomes are captured by neighboring recipient cells through the interaction of vesicular ligands with cellular receptors, thereby participating in the transmission of biological signals and the regulation of various biological processes.^155,157 Each exosome is an extension of the characteristics and functions of its original cell. Exosomes function as vehicles for antigen presentation in immune responses, regulating the activation and signaling of immune cells.¹⁵²

Keyword analysis revealed that “mesenchymal stem cells” exhibited a higher frequency of occurrence, and the top two keywords by centrality score were “expression” and “cell-derived exosomes”, collectively indicating that research into MSC-derived exosomes is a current hotspot. Together with the results of the co-citation reference analysis (such as cluster #0 and cluster #7), recent studies demonstrate that in order to address the severe threat posed by RDs such as OA and RA, researchers are turning their attention to the potential of exosomes in disease diagnosis and treatment. Given the high prevalence and severe clinical outcomes of these diseases, inflammation and immune dysregulation are well-established pathogenic mechanisms. Exosomes can mediate disease progression and serve as therapeutic targets by participating in various pathological processes. As indicated by the dual-map overlay results, the knowledge trajectory in this field demonstrates a transition from basic research towards clinical research. Therefore, researchers have focused their attention on these diseases. Additionally, the availability of experimental models, accessibility of clinical samples, and substantial government funding are also key factors that have driven the research in this area.

The pathogenesis of OA is complex, with many pathological manifestations including synovial inflammation, ligament degeneration, subchondral bone remodeling, cartilage damage, and changes in the neuromuscular structures around the joints. The main factor leading to OA is a high level of inflammation. Inflammation plays a pivotal role in driving cartilage progression and bone destruction.¹⁵⁸ T lymphocytes and macrophages are the primary inflammatory cells involved in the pathogenesis of OA. Inflammatory fibroblast-like synoviocytes derived exosomes (FLS-exos) aggravate inflammation and M1 polarization in macrophage. Increased levels of the inflammatory response promote immune cell infiltration, proliferation, and angiogenesis, leading to further joint damage.¹⁵⁹ Synovial fluid-derived exosomes (SF-exos) contribute to the onset and progression of OA by promoting the activation of pro-inflammatory M1 macrophages and inducing the production of IL-1β along with other inflammatory cytokines. It also upregulated the levels of matrix metalloproteinase (MMP), leading to the degradation of the chondrocyte extracellular matrix (ECM).¹⁶⁰ Exosomes can modulate OA through their encapsulated cargo, such as miRNA and lncRNA. They may also serve as promising biomarkers, such as hsa_circ_0104873, which significantly increased in the SF of OA patients.¹⁶¹

RA is characterized by synovial hyperplasia, immune cell infiltration, and autoantibody production. The immune pathogenesis of RA is related to an imbalance between memory Th17 and memory regulatory T cells. As antigen-presenting carriers, exosomes in the SF of RA patients contain citrullinated proteins that are recognized by anti-citrullinated peptide antibodies, a hallmark of RA. This recognition initiates an inflammatory response characterized by the proliferation of Th1 and Th17 cells, ultimately leading to joint damage.¹⁶² During the active phase of RA, plasma exosomes increase the release of pro-inflammatory cytokines such as IL-1, TNF, and IL-17.¹⁶³ Exosomes contribute to joint destruction and inflammatory processes: various nucleic acid components carried by exosomes, such as high levels of miR-221-3p and circFTO in FLS-exos, can damage bone and cartilage.^142,164 The lncRNA in exosomes can activate the NF-κB and Wnt signaling pathways, leading to Th17/Treg centered inflammation and resulting in synovial cells damage.¹⁶⁵ On the other hand, exosomes derived from inflammatory FLS can induce macrophages M1 polarization, generating a pro-inflammatory response.¹⁶⁶ Additionally, studies have shown that exosomes from RA patients carrying the co-inhibitory receptor PD-1 and related miRNAs can induce T cell exhaustion, leading to the progression of RA into a chronic disease.¹⁶⁷ Furthermore, circulating exosomal miRNA and serum exosomal lncRNA may be valuable biomarkers for RA.^168,170

Exosomes are double-edged swords in biological processes. While implicated in the pathogenesis of RDs, they also hold significant therapeutic potential. Exosomes from diverse sources, carrying various cargos, exhibit distinct therapeutic effects on RDs. MSCs have been widely used as immunosuppressants and are emerging as a research hotspot in regenerative medicine. Studies have demonstrated that MSC-Exos possess anti-apoptotic, anti-inflammatory, and regenerative effects in RDs.¹⁷¹ MSC-exos can rescue cartilage injury and regulate macrophage polarization by reducing ferroptosis, a form of iron-dependent cell death implicated in OA.^57,141 Exosomes can promote cartilage regeneration and mitigate cartilage degradation. Synovial MSCs derived exosomes (SMSC-exos) regulate bone regeneration and significantly promote cartilage repair through the Wnt5a/Wnt5b/YAP pathway.⁴¹ BMSC-Exos inherit the anti-inflammatory property of BMSCs, inhibiting macrophage activation reducing IL-1β levels and alleviating chondrocyte apoptosis.⁵⁵ Furthermore, Platelet-rich plasma derived exosomes (PRP-exos) can activate the Wnt/β-catenin signaling pathway, reduce pro-inflammatory factor IL-1β levels, and alleviate joint t inflammation.¹²⁴ FLS from RA patients exhibit an aggressive phenotype that causes damage to cartilage and bone.¹⁷² Components such as Fibrinogen-like protein 1 (FGL1) and miR-143-3p contained in MSC-exos can inhibit RA-FLS activation by reducing the activity of the NF-κB pathway.^126,132 Additionally, SMSC-exos inhibit signal transducer and activator of transcription 1 (STAT3) activity and downregulate vascular endothelial growth factor (VEGF) complex expression, resulting in reduced angiogenesis.¹³⁷ BMSC-exos have also been shown to exert anti-inflammatory effects by dose-dependently inhibiting T lymphocyte proliferation and reducing the CD4+ and CD8+ T cell ratio.¹⁷³ It also ameliorates inflammation by preventing the release of NLRP3 (NLR family pyrin domain-containing 3) in RA rats.¹²⁹ UMSC-exos have demonstrated the ability to reduce the Th1/Th17 to Treg cell ratio.¹³⁶

However, despite the potential applications of exosomes in RDs, several challenges that need to be addressed. Standardization and validation of products are major challenges. Current isolation techniques, such as ultracentrifugation, and the purity of exosomes produced by different methods, may affect the quality and efficacy of exosomes.¹⁷⁴ Exosomes can modulate the activity of recipient cells and therefore have potential immunogenicity and tumorigenicity. However, compared to MSCs, exosomes, as cell-free vesicles, significantly reduce immunogenicity.¹⁷⁵ Moreover, Heterogeneity in exosome yield and cargo composition between different batches and cell sources further complicates their clinical application. The keyword analysis timeline shows that the popularity of regenerative medicine research has increased significantly in recent years. Regenerative medicine is poised to emerge as the next frontier in this field, with the potential to lead to significant breakthroughs in the treatment of RDs. One promising therapeutic strategy is the bioengineering of exosomes, which exhibit enhanced targeting, retention and stability.¹⁷⁶ For example, engineered exosomes surface-modified with a chondrocyte-affinity peptide (CAP) and loaded with nuclear factor E2-related factor 2 (Nrf2) facilitated targeted delivery to cartilaginous endplate cells by inhibiting dynamin-related protein 1 (Drp1)-mediated mitochondrial fission.¹⁷⁷ Another innovative approach indicates that engineered exosomes loaded with triptolide can inhibit RA fibroblast proliferation and demonstrate lesion-targeting specificity, enhancing therapeutic efficacy.¹⁷⁸ In addition, pH-responsive engineered exosome can reprogram chondrocytes to sustainably produce endogenous hyaluronic acid (HA), enhancing cartilage regeneration.¹⁷⁹ To further optimize delivery efficiency, encapsulating exosomes into biomaterials like hydrogels enhances bioavailability and enables spatiotemporally controlled release, promoting cartilage protection and regeneration.^180,181 Superoxide dismutase 3 (SOD3)-rich exosome-loaded hydrogel microspheres reduce reactive oxygen species (ROS) and enhance ECM synthesis in OA.¹⁸² Moreover, magnetic polysaccharide hydrogel microcarriers co-deliver stem cell exosomes and diclofenac sodium to repair cartilage and alleviate OA symptoms.¹⁸³

Bibliometrics analysis is a valuable tool for assessing academic impact and identifying trends, but it also has its limitations. Firstly, bibliometric indicators represent only one aspect of research evaluation and do not provide a comprehensive overview of research results. Secondly, bibliometrics methods may not always accurately capture emerging and interdisciplinary fields, as the body of literature is constantly evolving, and it often takes time for progress to be reflected in the data. Thirdly, relying solely on the WOSCC database for data collection may limit the interpretation of the results. However, most databases, such as PubMed, do not always provide complete references and citations for articles. Fourthly, the presence of homonymous authors could introduce errors in the author analysis, affecting the accuracy of the results. Finally, the language of the included literature is limited to English and the article types are restricted to articles and review articles, potentially excluding important articles. However, this limitation is inherent in the software used for the analysis.

Conclusion

In conclusion, this bibliometric analysis provides a comprehensive landscape of exosomes in RDs in the 21st century. The steady upward trend in publications and citations reflects the growing interest in the field. China and the USA emerge as prominent contributors. Théry C is the most frequently co-cited author and has a significant impact. Core journals like Frontiers in Immunology, International Journal of Molecular Sciences, and Stem Cell Research & Therapy suggest that the primary research foci are rooted in cell biology, immunology, and experimental medicine. This study highlights the dual role of exosomes in disease pathogenesis and treatment. The burgeoning interest in exosomes as key players in the progression of OA and RA, with the potential to serve as biomarkers and therapeutic vehicles, such as modulating immune dysregulation, cartilage degradation, and inflammatory responses. It also bridges basic science with clinical applications, providing a basis for regenerative medicine applications, such as engineering exosomes. Therefore, our analysis may foster the development of the field and help scholars to navigate the intellectual architecture of research frontiers of exosomes in RDs. Compared with other diseases, the research on the pathogenesis and therapeutic strategies of exosomes in RDs is relatively limited. Further studies are still required to elucidate the exact mechanisms of exosomes in RDs, which will provide novel insights for disease diagnosis and treatment.

Funding Statement

This work was supported by Capital’s Funds for Health Improvement and Research (Grant number: 2024-1-4065); Elite Medical Professionals Project of China-Japan Friendship Hospital (Grant number: ZRJY2024-GG08); Rheumatology Branch of China Association of Chinese Medicine Youth Pei Ying Project (Grant number: 202327-007).

Ethics Approval and Informed Consent

The manuscript does not contain clinical studies or patient data. The data were obtained directly from the database without any additional human or experimental animal involvement, so there was no need for ethical approval.

Author Contributions

Jing Luo and Qingwen Tao contributed equally and shared corresponding authorship. All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

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.