Research in the genetics of pheochromocytoma and paraganglioma: A bibliometric analysis from 2002 to 2022

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We used bibliometric methods to investigate the historical changes and trend in PPGL research. There was a total of 1,263 articles published in English from 2002 to 2022 included in our study. The number of annual publications and citations in this field has been increasing in the past 20 years. Furthermore, most of the publications originated from the European countries and the United States. The co-occurrence analysis showed close cooperation between different countries, institutions, or authors. The dual-map discipline analysis revealed that majority articles focused on four disciplines: #2 (Medicine, Medical, Clinical), #4 (Molecular, Biology, Immunology), #5 (Health, Nursing, Medicine), and #8 (Molecular, Biology, Genetics). The hotspot analysis revealed the keywords that have been landmark for PPGL genetics research in different time periods, and there was continued interest in gene mutations, especially on SDHX family genes. In conclusion, this study displays the current status of research and future trends in the genetics of PPGL. In the future, more in-depth research should concentrate on crucial mutation genes and their specific mechanisms to assist in molecular target therapy. It is hoped that this study may help to provide directions for future research on genes and PPGL. pheochromocytoma paraganglioma PPGL genetics bibliometric analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1 Introduction Pheochromocytoma (PPC) and paraganglioma (PGL), collectively known as PPGL, are rare neuroendocrine tumors. Pheochromocytoma originates from the adrenal medulla, while paraganglioma originates from the paraganglia outside the adrenal medulla. It synthesizes and secretes large amounts of catecholamine that lead to a systemic cardiometabolic disorder. PPGLs are heritable tumors, with about 35–40% of patients with PPGL having a germline predisposition[ 1 ]. Given the strong genetic predisposition, patients are required to undergo genetic testing and counseling. Numerous studies have explored the familial inheritance and the molecular pathogenesis of PPGL. In previous studies, NF1 was first identified as the cause of the genetic syndrome of PPGL (neurofibromatosis type 1), followed by RET and VHL[ 2 – 4 ]. The number of susceptibility loci has gradually increased to more than 20 in previous studies[ 5 – 10 ]. The field of PPGL genetics is rapidly evovling. Improved understanding of the genetics and genomic patterns of PPGL have advanced the early detection, diagnosis, monitoring, and treatment of these tumors and the development of potential therapeutic targets. Therefore, there is a need to conduct research on the genetics of PPGL to promote the development of precision medicine. Bibliometric research is a summary of hot spots and trends in a certain research field or area and is conducted through visual pictures and charts. Bibliometric analysis provides clues for future relevant research[ 11 ]. A recent bibliometric analysis evaluated the top 200 most cited articles in the PPGL field from 1985 to 2020[ 12 ]. An increased number of studies have explored gene research in PPGL. However, no bibliometric analysis has been conducted on the genetics of PPGL. Therefore, this study aimed to conduct a comprehensive bibliometric analysis from 2002 to 2022 to explore the historical changes and future research trends in the genetics of PPGL. 2 Materials And Methods 2.1 Data collection and retrieval strategy The following search strategy: TS = ("paraganglioma*" OR "phaeochromocytoma*"OR "chromaffinoma" OR "chromaffin tumor" OR" Carotid Body Tumor" OR "Glomus Jugulare Tumor" OR "Glomus Tympanicum Tumor") and TS = ("genetic*" OR "epigenetic*" OR "genome*") was used to search for articles within the Web of science core collection (WOSCC) online database. The literature types were limited to “article or review”. The time span was set from 2002 to 2022, and the search was limited to articles published in English. All relevant records, including full records and cited references were independently screened by two authors (Lei Li and Lihua Guan). Data were converted to text format for subsequent analysis. The search yielded 1,263 articles. The literature search and data collection were completed within one day on February 4th, 2023. 2.2 Data analysis Bibliometrix was used to draw a landscape of international cooperation networks and intensity in the RStudio environment (version 1.2.5033). CiteSpace (version 6.1 R4) was used to analyze interdisciplinary relationships and construct a dual-map overlay. The references/keywords with citation bursts were used to assess changes in the research hotspots. The co-citation analysis of authors was used to show the research trends and influence of relevant authors. In addition, the timeline of keywords was conduct to emphasize the cluster analysis of keywords and the time trend[ 13 , 14 ]. VOS viewer (version 1.6.18) was used to generate a visualization network of co-citation relationship of journals or documents in the genetics of PPGL. Besides, the structure and clustering of the keywords co-occurrence network drew by VOS viewer was evaluated by the Modularity Q and Mean Silhouette, respectively. The Modularity Q between 0.4–0.8 indicates the more significant the clustering result, while the closer of the Mean Silhouette is to 1 represents the higher homogeneity within the cluster[ 15 ]. Furthermore, h-index (high citations index), proposed by Jorge J. Hirsch in 2005[ 16 ] is a quantitative evaluation method of academic achievements and shows that h articles have been cited at least h times. 3 Results 3.1 Trends in annual publications Our search yielded 1,263 publications, including 941 reviews and 322 articles. Figure 1 shows the trend in annual publication and citation frequency of the genetics of pheochromocytoma and paraganglioma (PPGL) research. The results revealed an overall increasing trend in the number of publications and the frequency of citations in the past twenty years. Annual publications increased from 18 articles (2002) to 98 articles (2022), while citation frequency increased from 13 times (2002) to 4,584 times (2022), peaking at 115 articles in 2020 and 5,366 times in 2021, respectively. Furthermore, there was a rapid growth in the number of annual publications from 2016 to 2020, with the grow rate of 18.3%. 3.2 Contributions of Countries/Regions and Institutions The publications originated from 65 countries/regions, with majority publications being from the European countries and the United States. Table 1 shows the top 10 most productive countries based on the number of publications. The United States was the most productive country (with 501 publications), followed by France(n = 177) and Germany(n = 164). However, in regard to the average citation frequency, USA is much lower than France and Germany, with the highest average citation frequency of 76.54 in France. Furthermore, although Sweden contributed 61 publications (rank 10th) in the past 20 years, it had the fourth highest average citation frequency (58.34 times), indicating that Sweden published many high-quality articles in this field along the time. Additionally, there was a close academic cooperation between countries and regions as shown in Fig. 2 . There was a total of 1,573 institutions contributing to this field over the past two decades. Figure 3 shows organizations with more than 10 publications. The collaboration network of institutions was centered on NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD), with the highest publications of 105 publications and considerably higher than other institutions. The average publication year of NIHCD was in 2016, which revealed that NICHD generated a burst of publications and consistently focused on this field in the recent 5 years. Moreover, though the number of publications by Hopital Universitaire European Georges-Pompidou (65 publications) and the Université Paris Cité (57 publications) were lower than NICHD, their average citation frequencies were much higher than NIHCD (detailed in Supplementary Table S1 ) . Moreover, the tight collaboration among different institutions across the world can be seen in the Fig. 3 . Table 1 The top 10 countries based on the number of original articles Rank Country/region Number of publications (%) Average citation frequency 1 USA 501(39.67) 51.93 2 France 177(14.01) 76.54 3 Germany 164(12.99) 66.18 4 England 138(10.93) 57.18 5 Italy 136(10.77) 52.59 6 Netherlands 124(9.82) 63.40 7 Spain 111(8.79) 42.58 8 China 83(6.57) 8.07 9 Australia 75(5.94) 47.78 10 Sweden 61(4.83) 58.34 3.3 Analysis of the most influential journals The top 10 most productive journals were shown in Table 2 , publishing a total of 345 publications and accounting for 27.3% of all publications. The Journal of Clinical Endocrinology & Metabolism had the highest publications (n = 81) and the highest h-index of 37, indicating that the journal played a leading role in this field. Additionally, among the top 10 journals, four journals were published in USA and three of them were in England, revealing that USA and England attached great importance to the genetics of PPGL indirectly. Figure 4 displayed the network diagram of co-citation analysis of top 20 most cited journals, which demonstrated a mutual reference relationship centered on the Journal of Clinical Endocrinology & Metabolism and close relationships among these journals. The dual-map overlay of the discipline distribution of publications in the past 20 years is shown in Fig. 5 . The dual-map overlay analysis revealed the distribution of disciplines in the genetics of PPGL, indicating the basis of discipline orientation and interaction between disciplines. Publications in genetics of PPGL were mainly affiliated with 14 disciplines. However, they were concentrated in four disciplines: #2 (Medicine, Medical, Clinical), #4 (Molecular, Biology, Immunology), #5 (Health, Nursing, Medicine), and #8 (Molecular, Biology, Genetics), indicating that these disciplines were the key areas of research in PPGL. In addition, the articles published on discipline #2 and #4 cite articles from discipline #8, suggesting that molecular biology has provided a foundation for research in this field. Similarly, articles in discipline #5 offered inspiration for articles in discipline #2. Table 2 The top 10 journals based on the number of the original articles Rank Journal Category Zones Country/region Number of publications (%) H-index 1 Journal of Clinical Endocrinology & Metabolism Q1 USA 81(6.4) 37 2 Endocrine-related cancer Q1 England 53(4.2) 28 3 Clinical Endocrinology Q3 England 39(3.1) 18 4 cancers Q1 Switzerland 33(2.6) 9 5 Endocrine pathology Q2 USA 28(2.2) 15 6 Hormone and Metabolic Research Q3 Germany 27(2.1) 13 7 European journal of Endocrinology Q1 England 24(1.9) 16 8 Frontiers in Endocrinology Q1 USA 24(1.9) 8 9 Familial Cancer Q3 Netherlands 18(1.4) 9 10 Head and neck-journal for the Sciences and the Head and neck Q1 USA 18(1.4) 8 3.4 Analysis of co-cited references and reference burst detection The co-citation network of documents shown in Fig. 6 , shows the connection and relevance of articles through the common cited relationship. Figure 7 provides a landscape of major milestones in the genetics of PPGL along the time. References with strong values in the strength label indicates significant milestones in this area. This co-citation network in Fig. 6 contains 86 references and forms 4 clusters displayed in different colors, among which green cluster contained more highly cited articles. In addition, in this cluster, the article by Baysal BE in 2000 was the most frequently cited. Moreover, two articles written by Neumann HPH in 2002 and 2004 became hot topics of research in this field for about five years after publication respectively. Red cluster centered on Lender JWN (2014), which formed a burst during 2015–2019 with the strongest strength value of 49.76. The article by Burnichon N (2010) in blue cluster also had a considerable influence in the genetics of PPGL, which generated a strong citation burst from 2011 to 2015 and had the second highest citation strength value (49.25). The yellow cluster centered on Amar L was the smallest but maintained a strong correlation with documents in other clusters. 3.5 Analysis of research hotspots The top 40 most frequently occurring keywords visualized in Fig. 8 , which showed the most concerned topic in this field. The timeline map of keywords was showed in Fig. 9 , suggesting the development and changes of the research hotspots. The hotspot timeline cluster network included 726 nodes, with the modularity Q and mean silhouette values of were 0.5134 and 0.8091, respectively, suggesting that the cluster network was significant and robust, and the keywords within each cluster had a high degree of homogeneity. Moreover, keywords clusters were arranged by the descending size of the cluster vertically, meaning that the smallest number of the cluster represented the largest cluster. The topmost cluster (cluster #0, Succinate dehydrogenase) consisted of 136 nodes and the 10 most frequently occurring words from Fig. 8 were included (Table 3 ). Additionally, the cluster #0 ranged from 2002 to 2022 and included the most burst terms. The 10 most common keywords based on the co-occurrence cluster (excluding keywords used in the retrieval) are shown in Table 3 . The top three keywords were germline mutations (centrality = 0.07, firstly appeared in 2002), mutation (centrality = 0.04, firstly appeared in 2002), and succinate-dehydrogenase (centrality = 0.03, firstly appeared in 2004), which were closely related to the pathogenesis of PPGL. Figure 10 shows the top 20 most frequently occurring keywords with the strongest citation bursts ranked based on the starting time of burst, indicating the emerging trends. The keyword, hereditary paraganglioma, was the first to generate a citation burst and lasted for the longest time, from 2002 to 2012, indicating continuous interest on hereditary paraganglioma. Additionally, research on genes and gene mutations has increased, giving rise to nine citation bursts in the last 20 years, including ret protooncogene (2002–2006), complex Ⅱ gene (2006–2011), sdhd gene (2005–2011), molecular genetics (2012–2016), max mutation (2013–2019), germline mutation (2013–2015), hif2a mutation (2014–2017), sdh mutation (2014–2016), and somatic mutation (2015–2019), demonstrating the status of the exploration of genes and their molecular mechanisms in the PPGL research field. Table 3 The 10 most frequently occurring keywords (derived from the list in Fig. 8 , excluding the keywords used in the literature search) Label Occurrences Centrality Year of first occurrence Germline mutations 259 0.07 2002 Mutation 247 0.04 2002 Succinate-dehydrogenase 224 0.03 2004 Malignant pheochromocytoma 152 0.05 2005 Diagnosis 149 0.02 2003 Gene 135 0.06 2003 Tumor 133 0.03 2005 Management 107 0.03 2002 Head 107 0.03 2004 Gene mutation 104 0.03 2005 4 Discussion This bibliometric analysis concentrated on the genetics of PPGLs from 2002 to 2022, depicting the historical changes and development of this field in the past 20 years. In our study, there is a general increasing trend in the annual number of publications and citation frequency, suggesting increased interest in the genetics of PPGL. Furthermore, most publications originated from the European countries and the United States, among which the most productive country was the United States. But the citation frequency of USA only ranked fifth, followed by some European countries, suggesting that these European countries had more in-depth research in this field. As for institutions, the NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD) contributed to the highest number of publications and mainly published in recent 5 years, indicating that it had great potential to make huge contributions in this field. In 2014, NICHD published an article by Lenders JW et al.[ 17 ], which provided the first clinical guidelines for the diagnosis and treatment of pheochromocytoma and paraganglioma, including biochemical testing, imaging tests and genetic testing. In recent years, the update of diagnostic guidelines to include genetic testing in various types of PPGL further proved the importance of genetics in disease detection[ 18 , 19 ]. Co-citation analysis shows documents on similar research topics or authors with similar research directions. The top 20 co-citation network of journals showed the close relationship among journals. The journals’ co-citation cluster was centered on the Journal of Clinical Endocrinology & Metabolism founded in the USA. In addition, this journal had the highest number of publications and h-index, indicating that the journal has authoritative reference value in this field. Furthermore, the document co-citation analysis network primarily formed four clusters. In green cluster, the most cited article was published by Baysal BE in 2000[ 20 ], which focused on genetic analysis of familial paragangliomas and genetic testing for screening individuals with a genetic risk of the disease. The article laid a foundation for subsequent in-depth exploration of the impact of genetic alterations on pathogenesis of PPGL. Additionally, in this cluster, two articles published by Neumann HPH in 2002[ 21 ] and 2004[ 22 ] also had a considerable influence on this field, which described the relationship between gene mutations and pheochromocytoma and paraganglioma respectively, which became a hot topic of interest and resulted in strong citation bursts in 2002–2007 and 2005–2009. Also, these two publications demonstrated the importance of genetic testing in PPGL. Moreover, Astuti D[ 23 ] published an article about germline SDHD mutation in 2001. This is the first time to report SDHD mutation in familial phaeochromocytoma, but not in sporadic pheochromocytoma, which illustrates the crucial role of SDHD mutations in genetic pathogenesis and became an important milestone in the study of SDHx family mutations. In another cluster, a study conducted by Burnichon N[ 24 ] in 2009 investigated gene mutations in succinate dehydrogenase subunits (SDHx) associated with paraganglioma, using the QMPSF and MLPA methods. Furthermore, the PPGL diagnostic guidelines issued by Lenders JW et al. in 2014[ 17 ] formed another important landmark in the PPGL field, as shown by the strongest burst citation value. The top keywords and burst terms reflected the research hotspots and predicted new research frontiers. The top 3 most frequently occurring keywords were associated with mutation (germline mutations, mutation and succinate dehydrogenase) and the gene mutation happened in succinate dehydrogenase related genes are usual and widely investigated. Furthermore, the largest keyword cluster (cluster #0) was also included succinate dehydrogenase, with the highest burst strength. As shown on the keywords co-occurrence time-view map, PPGL-related genetics research consistently focused on succinate dehydrogenase, from sdhd gene (2005–2011), succinate dehydrogenase (2012–2015) to sdh mutation (2014–2016). Succinate dehydrogenase comprises four subunits (SDHA, SDHB, SDHC, and SDHD). Additionally, succinate dehydrogenase plays a crucial role in oxidizing succinic acid to fumarate in the Krebs cycle and electron transfer in the mitochondrial respiratory chain. Impaired succinate dehydrogenase activity is linked to reprogramming of cellular metabolic pathways, and accumulation of oncometabolites in the cytoplasm responsible for genome-wide hypermethylation and pseudohypoxic “signature” contributing to PPGL tumourigenesis[ 25 ]. The SDHx gene family (sdhd, sdhc, sdhb, sdha and sdhaf2) encodes the subunits of succinate dehydrogenase enzyme complex. Mutations (germline mutations or somatic LOH) in these genes results in a protein with loss of enzyme activity. The penetrance of sdha and sdhd gene mutation carriers was first proposed in 2006[ 26 ]. Subsequently, there was a gradual increase in research on other members of the SDHx family in PPGL[ 27 ]. Germline mutations in SDHx account for a hereditary background in approximately 20% of PPGL tumors[ 28 , 29 ]. This bibliometric analysis revealed increased interest in metabolic reprogramming in the etiology of PPGLs, representing a major milestone in the genetics of PPGLs. With regard to cluster #1(metastatic pheochromocytoma), most of the keywords focused on the diagnosis and management of metastatic pheochromocytoma. Metastasis occurs in 35% of the PPGL patients. Gene mutations, especially sdhb mutation, are associated with increased metastasis rate[ 27 ]. Tumors with sdhb mutations are highly aggressive and are characterized by activation of the epithelial-mesenchymal transition pathway. Due to the heterogeneity and low incidence rate of PPGL, no effective targeted therapies have been developed. Symptomatic patients are managed by surgery, radiotherapy, or chemotherapy, which only achieves partial relief[ 30 , 31 ]. Ascorbic acid has been exploited as a potential therapeutic agent as it targets the redox pathway in SDHB-deficient PPGL[ 32 ]. This bibliometric analysis shows the current status and trends of genetic research in PPGL from 2002–2022. However, there are some limitations in our study. Firstly, we only analyzed publications retrieved from the WoSCC database in the past 20 years, thus it is unable to fully understand the historical development of this field. Secondly, we only included articles published in English. If non-English articles were also included, the results would be slightly different. Thirdly, this analysis only focused on genetics in PPGL. Therefore, future analysis concentrating on other or more aspects of the disease may assist in acquiring the overall picture of research changes of this field and understanding the cause of PPGL more comprehensively. 5 Conclusion To sum up, the current study presents a clear picture of the historical development and future research trends in the genetics of PPGL from 2002 to 2022 by bibliometric methods. Over the past two decades, there has been a general upward trend in gene-related research in PPGL, suggesting the important role of genetic factors in the pathogenesis, prediction and treatment of PPGL. In the future, it is worthwhile to continue in-depth research on crucial mutant genes and their specific mechanisms of pathogenesis in order to develop drugs or therapeutic methods that specifically target the mutations to effectively treat PPGL. Furthermore, it is hoped that our study will contribute to directions of future research on PPGL. Declarations Funding This work was supported by Capital’s Funds for Health Improvement and Research(CFH-2020-1-4014) and Beijing Key Clinical Specialty for Laboratory Medicine - Excellent Project (No. ZK201000). Competing Interests The authors have no relevant financial or non-financial interests to disclose. Availability of data and materials The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors Authors’ contributions Conceptualization: Ling Qiu; Methodology: Lei Li and Yiwen Lu; Formal analysis and investigation: Lei Li, Jian Zhong; Writing - original draft preparation: Lihua Guan; Writing - review and editing: Lihua Guan and Lei Li; Funding acquisition:Ling Qiu; Supervision: Yutong Zou Ethics approval Not applicable Consent to participate Not applicable Consent for publication Not applicable References Fishbein L. Pheochromocytoma/Paraganglioma: Is This a Genetic Disorder? Curr Cardiol Rep. 2019;21(9):104. Cawthon RM, Weiss R, Xu GF, Viskochil D, Culver M, Stevens J, et al. A major segment of the neurofibromatosis type 1 gene: cDNA sequence, genomic structure, and point mutations. Cell. 1990;62(1):193-201. Ikeda I, Ishizaka Y, Tahira T, Suzuki T, Onda M, Sugimura T, et al. Specific expression of the ret proto-oncogene in human neuroblastoma cell lines. Oncogene. 1990;5(9):1291-6. 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Supplementary Files SupplementaryMaterial.doc Cite Share Download PDF Status: Published Journal Publication published 27 Apr, 2023 Read the published version in Clinical and Experimental Medicine → Version 1 posted Editorial decision: Major revision 28 Feb, 2023 Reviews received at journal 28 Feb, 2023 Reviewers agreed at journal 24 Feb, 2023 Reviewers invited by journal 22 Feb, 2023 Editor assigned by journal 22 Feb, 2023 Submission checks completed at journal 22 Feb, 2023 First submitted to journal 16 Feb, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2597108","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":177999726,"identity":"b5424b40-1050-414d-b7f9-a421facd8ce3","order_by":0,"name":"Lei Li","email":"","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Science","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Li","suffix":""},{"id":177999728,"identity":"41afd1a7-98cd-4bd9-b7c8-4ffdfcb3ddcc","order_by":1,"name":"Lihua Guan","email":"","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Science","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lihua","middleName":"","lastName":"Guan","suffix":""},{"id":177999729,"identity":"1f2ef107-ea57-472b-98d2-9190dff79c91","order_by":2,"name":"Yiwen Lu","email":"","orcid":"","institution":"Guangxi Medical University, The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yiwen","middleName":"","lastName":"Lu","suffix":""},{"id":177999731,"identity":"e3b052d6-5d7f-4e1e-8fbc-dfed1b86f6f5","order_by":3,"name":"Yueming Tang","email":"","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Science","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yueming","middleName":"","lastName":"Tang","suffix":""},{"id":177999733,"identity":"9bfcea62-2e42-4991-a804-87724f7bb5c3","order_by":4,"name":"Yutong Zou","email":"","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Science","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yutong","middleName":"","lastName":"Zou","suffix":""},{"id":177999735,"identity":"ccbbafd4-9f21-4aa9-ac0e-0522d92aee62","order_by":5,"name":"Jian Zhong","email":"","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Science","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Zhong","suffix":""},{"id":177999738,"identity":"b9867875-f5f1-47c9-b06d-3009ab7bbf81","order_by":6,"name":"Ling Qiu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYBACA2YwyZDA2N7Y+PADaVp6DjcbSxClBUonMEiktwnwEKWFnffwizcFh/OYZz5sY5BgsJPTbSDoML40yzkGh4sZZye2PShgSDY2O0BQC4+ZMY/B4cTG2YntBhIMBxK3Ea9l5sE2CR4itRg/BmuZwUi8FjPGOQbpxYw9icBANiDCL/b9Z4w/vPljnWfYfvzhww8VdnIEtQABmwQoOgwbwJYSVg4CzB9AWuSJUzwKRsEoGAUjEQAALyM/tw5+UIQAAAAASUVORK5CYII=","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Science","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Qiu","suffix":""}],"badges":[],"createdAt":"2023-02-17 03:59:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2597108/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2597108/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10238-023-01049-6","type":"published","date":"2023-04-27T20:36:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":33364498,"identity":"e3720049-e24c-4407-9542-c9d83c068bd8","added_by":"auto","created_at":"2023-02-23 18:58:19","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":98600,"visible":true,"origin":"","legend":"\u003cp\u003eTrend in annual publications and citations from 2002 to 2022\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/136f41ee69125e0df2d544f9.jpg"},{"id":33364499,"identity":"4ae4cfc6-ab81-49a8-a76d-f0b90c8f048d","added_by":"auto","created_at":"2023-02-23 18:58:19","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":178568,"visible":true,"origin":"","legend":"\u003cp\u003eThe collaboration network of countries/regions. The number of publications is shown by intensity of the blue color; the thickness of the red line shows the strength of collaboration\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/d91193c70bb1ef0cb58f7606.jpg"},{"id":33364506,"identity":"dac17c9c-966f-4a6d-9bd8-ded303c680f6","added_by":"auto","created_at":"2023-02-23 18:58:20","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":718395,"visible":true,"origin":"","legend":"\u003cp\u003eThe collaboration network of institutions. The size of nodes represents the number of publications. The size of the links indicates the cooperation intensity; the time of contributions is presented by the brightness of the color\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/19b6c278d67608a636871787.jpg"},{"id":33364770,"identity":"49ba39e3-5db5-4ad7-b1c4-acadd59fe97f","added_by":"auto","created_at":"2023-02-23 19:06:20","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":333083,"visible":true,"origin":"","legend":"\u003cp\u003eThe network of top 20 co-citation journals. The size of nodes represents the number of citations; the size of the links indicates the cooperation intensity\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/07af6aac66d37ec2ccd7de8f.jpg"},{"id":33364503,"identity":"7e56ac3b-132f-4450-b9be-8c86b22330ab","added_by":"auto","created_at":"2023-02-23 18:58:20","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1859810,"visible":true,"origin":"","legend":"\u003cp\u003eA dual-map overlay of discipline distribution of publications. 1-14 represent different subject areas; the left part shows the distributions of citing journals; the right part shows cited journals; the lines show relationships between the citing and cited journals; the horizontal axis of the ellipse shows the number of authors while the vertical axis shows the number of published articles\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/208dea78479326b10ca526c2.jpg"},{"id":33364767,"identity":"fd667ddb-4726-408f-ab99-b5d60fac775f","added_by":"auto","created_at":"2023-02-23 19:06:20","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":610573,"visible":true,"origin":"","legend":"\u003cp\u003eThe network of co-citation document. Each Node is named after first author and publication year and the size refers to citation frequency. The link represents the beginning of the connections. This network only shows references with more than 10 citations\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/fe738247f4191daa367ff32e.jpg"},{"id":33364769,"identity":"787b774b-ba9a-419f-b28c-f2c26b1cfdd4","added_by":"auto","created_at":"2023-02-23 19:06:20","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":234493,"visible":true,"origin":"","legend":"\u003cp\u003eThe top 20 references with citation burst. The red bar represents the burst duration. The burst strength represents the scientific value of the article in PPGL genetic research\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/a9087a3ecdb86e00f80230d4.jpg"},{"id":33364501,"identity":"d654a937-1d64-458e-b5ff-451e807ccd31","added_by":"auto","created_at":"2023-02-23 18:58:20","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":343091,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurrence network of the 40 most frequently occurring keywords. The size of the nodes indicates the frequency of occurrence\u003c/p\u003e","description":"","filename":"Figure8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/6e09b55b7b1122e1f40af173.jpg"},{"id":33364508,"identity":"885f7d59-b41f-462f-a445-dc37d2b5954f","added_by":"auto","created_at":"2023-02-23 18:58:20","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":2446019,"visible":true,"origin":"","legend":"\u003cp\u003eTimeline map of the keywords co-occurrence. #0~#14 represents keyword tags of each cluster; the position of nodes refers to the time when the keyword firstly occurred and the size of nodes represents the occurring frequency. Red rings represent keywords with citation burst\u003c/p\u003e","description":"","filename":"Figure9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/92581428268ea15780f4a450.jpg"},{"id":33364766,"identity":"58aa34f4-ef03-4821-b7f6-1dd531193fc2","added_by":"auto","created_at":"2023-02-23 19:06:20","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":112152,"visible":true,"origin":"","legend":"\u003cp\u003eTop 20 keywords with the strongest citation bursts\u003c/p\u003e","description":"","filename":"Figure10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/3312e266d400c4901ca4f7dd.jpg"},{"id":44726903,"identity":"dbd198c0-f6fc-47df-8825-dadf775c6e31","added_by":"auto","created_at":"2023-10-16 20:50:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1460322,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/6df7dd56-4b33-45b0-9d1d-212ccf396bc6.pdf"},{"id":33365179,"identity":"50d620c1-405f-401b-b51a-fea654e91bdd","added_by":"auto","created_at":"2023-02-23 19:14:20","extension":"doc","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":44032,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.doc","url":"https://assets-eu.researchsquare.com/files/rs-2597108/v1/873b54d6d08422cfb0ddda8a.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eResearch in the genetics of pheochromocytoma and paraganglioma: A bibliometric analysis from 2002 to 2022\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003ePheochromocytoma (PPC) and paraganglioma (PGL), collectively known as PPGL, are rare neuroendocrine tumors. Pheochromocytoma originates from the adrenal medulla, while paraganglioma originates from the paraganglia outside the adrenal medulla. It synthesizes and secretes large amounts of catecholamine that lead to a systemic cardiometabolic disorder. PPGLs are heritable tumors, with about 35\u0026ndash;40% of patients with PPGL having a germline predisposition[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Given the strong genetic predisposition, patients are required to undergo genetic testing and counseling. Numerous studies have explored the familial inheritance and the molecular pathogenesis of PPGL. In previous studies, NF1 was first identified as the cause of the genetic syndrome of PPGL (neurofibromatosis type 1), followed by RET and VHL[\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The number of susceptibility loci has gradually increased to more than 20 in previous studies[\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The field of PPGL genetics is rapidly evovling. Improved understanding of the genetics and genomic patterns of PPGL have advanced the early detection, diagnosis, monitoring, and treatment of these tumors and the development of potential therapeutic targets. Therefore, there is a need to conduct research on the genetics of PPGL to promote the development of precision medicine.\u003c/p\u003e \u003cp\u003eBibliometric research is a summary of hot spots and trends in a certain research field or area and is conducted through visual pictures and charts. Bibliometric analysis provides clues for future relevant research[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A recent bibliometric analysis evaluated the top 200 most cited articles in the PPGL field from 1985 to 2020[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. An increased number of studies have explored gene research in PPGL. However, no bibliometric analysis has been conducted on the genetics of PPGL.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to conduct a comprehensive bibliometric analysis from 2002 to 2022 to explore the historical changes and future research trends in the genetics of PPGL.\u003c/p\u003e"},{"header":"2 Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003e2.1 Data collection and retrieval strategy\u003c/h2\u003e\n\u003cp\u003eThe following search strategy: TS = (\"paraganglioma*\" OR \"phaeochromocytoma*\"OR \"chromaffinoma\" OR \"chromaffin tumor\" OR\" Carotid Body Tumor\" OR \"Glomus Jugulare Tumor\" OR \"Glomus Tympanicum Tumor\") and TS = (\"genetic*\" OR \"epigenetic*\" OR \"genome*\") was used to search for articles within the Web of science core collection (WOSCC) online database. The literature types were limited to \u0026ldquo;article or review\u0026rdquo;. The time span was set from 2002 to 2022, and the search was limited to articles published in English. All relevant records, including full records and cited references were independently screened by two authors (Lei Li and Lihua Guan). Data were converted to text format for subsequent analysis. The search yielded 1,263 articles. The literature search and data collection were completed within one day on February 4th, 2023.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003e2.2 Data analysis\u003c/h2\u003e\n\u003cp\u003eBibliometrix was used to draw a landscape of international cooperation networks and intensity in the RStudio environment (version 1.2.5033). CiteSpace (version 6.1 R4) was used to analyze interdisciplinary relationships and construct a dual-map overlay. The references/keywords with citation bursts were used to assess changes in the research hotspots. The co-citation analysis of authors was used to show the research trends and influence of relevant authors. In addition, the timeline of keywords was conduct to emphasize the cluster analysis of keywords and the time trend[\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]. VOS viewer (version 1.6.18) was used to generate a visualization network of co-citation relationship of journals or documents in the genetics of PPGL. Besides, the structure and clustering of the keywords co-occurrence network drew by VOS viewer was evaluated by the Modularity Q and Mean Silhouette, respectively. The Modularity Q between 0.4\u0026ndash;0.8 indicates the more significant the clustering result, while the closer of the Mean Silhouette is to 1 represents the higher homogeneity within the cluster[\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, h-index (high citations index), proposed by Jorge J. Hirsch in 2005[\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e] is a quantitative evaluation method of academic achievements and shows that h articles have been cited at least h times.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Trends in annual publications\u003c/h2\u003e\n\u003cp\u003eOur search yielded 1,263 publications, including 941 reviews and 322 articles. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the trend in annual publication and citation frequency of the genetics of pheochromocytoma and paraganglioma (PPGL) research. The results revealed an overall increasing trend in the number of publications and the frequency of citations in the past twenty years. Annual publications increased from 18 articles (2002) to 98 articles (2022), while citation frequency increased from 13 times (2002) to 4,584 times (2022), peaking at 115 articles in 2020 and 5,366 times in 2021, respectively. Furthermore, there was a rapid growth in the number of annual publications from 2016 to 2020, with the grow rate of 18.3%.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Contributions of Countries/Regions and Institutions\u003c/h2\u003e\n\u003cp\u003eThe publications originated from 65 countries/regions, with majority publications being from the European countries and the United States. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the top 10 most productive countries based on the number of publications. The United States was the most productive country (with 501 publications), followed by France(n\u0026thinsp;=\u0026thinsp;177) and Germany(n\u0026thinsp;=\u0026thinsp;164). However, in regard to the average citation frequency, USA is much lower than France and Germany, with the highest average citation frequency of 76.54 in France. Furthermore, although Sweden contributed 61 publications (rank 10th) in the past 20 years, it had the fourth highest average citation frequency (58.34 times), indicating that Sweden published many high-quality articles in this field along the time. Additionally, there was a close academic cooperation between countries and regions as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eThere was a total of 1,573 institutions contributing to this field over the past two decades. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows organizations with more than 10 publications. The collaboration network of institutions was centered on NIH Eunice Kennedy Shriver National Institute of Child Health \u0026amp; Human Development (NICHD), with the highest publications of 105 publications and considerably higher than other institutions. The average publication year of NIHCD was in 2016, which revealed that NICHD generated a burst of publications and consistently focused on this field in the recent 5 years. Moreover, though the number of publications by Hopital Universitaire European Georges-Pompidou (65 publications) and the Universit\u0026eacute; Paris Cit\u0026eacute; (57 publications) were lower than NICHD, their average citation frequencies were much higher than NIHCD \u003cstrong\u003e(detailed in Supplementary Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/strong\u003e. Moreover, the tight collaboration among different institutions across the world can be seen in the Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe top 10 countries based on the number of original articles\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRank\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCountry/region\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNumber of publications (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAverage citation frequency\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUSA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e501(39.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e51.93\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFrance\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e177(14.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e76.54\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGermany\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e164(12.99)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e66.18\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEngland\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e138(10.93)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e57.18\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eItaly\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e136(10.77)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e52.59\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNetherlands\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e124(9.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e63.40\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSpain\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e111(8.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e42.58\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChina\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e83(6.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAustralia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e75(5.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e47.78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSweden\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e61(4.83)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e58.34\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3 Analysis of the most influential journals\u003c/h2\u003e\n\u003cp\u003eThe top 10 most productive journals were shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, publishing a total of 345 publications and accounting for 27.3% of all publications. The Journal of Clinical Endocrinology \u0026amp; Metabolism had the highest publications (n\u0026thinsp;=\u0026thinsp;81) and the highest h-index of 37, indicating that the journal played a leading role in this field. Additionally, among the top 10 journals, four journals were published in USA and three of them were in England, revealing that USA and England attached great importance to the genetics of PPGL indirectly. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e displayed the network diagram of co-citation analysis of top 20 most cited journals, which demonstrated a mutual reference relationship centered on the Journal of Clinical Endocrinology \u0026amp; Metabolism and close relationships among these journals.\u003c/p\u003e\n\u003cp\u003eThe dual-map overlay of the discipline distribution of publications in the past 20 years is shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. The dual-map overlay analysis revealed the distribution of disciplines in the genetics of PPGL, indicating the basis of discipline orientation and interaction between disciplines. Publications in genetics of PPGL were mainly affiliated with 14 disciplines. However, they were concentrated in four disciplines: #2 (Medicine, Medical, Clinical), #4 (Molecular, Biology, Immunology), #5 (Health, Nursing, Medicine), and #8 (Molecular, Biology, Genetics), indicating that these disciplines were the key areas of research in PPGL. In addition, the articles published on discipline #2 and #4 cite articles from discipline #8, suggesting that molecular biology has provided a foundation for research in this field. Similarly, articles in discipline #5 offered inspiration for articles in discipline #2.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe top 10 journals based on the number of the original articles\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRank\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eJournal\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCategory Zones\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCountry/region\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNumber of publications (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eH-index\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJournal of Clinical Endocrinology \u0026amp; Metabolism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUSA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e81(6.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndocrine-related cancer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEngland\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e53(4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eClinical Endocrinology\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEngland\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e39(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ecancers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSwitzerland\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33(2.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndocrine pathology\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUSA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e28(2.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHormone and Metabolic Research\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGermany\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27(2.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEuropean journal of Endocrinology\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEngland\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24(1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFrontiers in Endocrinology\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUSA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24(1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFamilial Cancer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNetherlands\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18(1.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHead and neck-journal for the Sciences and the Head and neck\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQ1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUSA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18(1.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4 Analysis of co-cited references and reference burst detection\u003c/h2\u003e\n\u003cp\u003eThe co-citation network of documents shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, shows the connection and relevance of articles through the common cited relationship. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e provides a landscape of major milestones in the genetics of PPGL along the time. References with strong values in the strength label indicates significant milestones in this area. This co-citation network in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e contains 86 references and forms 4 clusters displayed in different colors, among which green cluster contained more highly cited articles. In addition, in this cluster, the article by Baysal BE in 2000 was the most frequently cited. Moreover, two articles written by Neumann HPH in 2002 and 2004 became hot topics of research in this field for about five years after publication respectively. Red cluster centered on Lender JWN (2014), which formed a burst during 2015\u0026ndash;2019 with the strongest strength value of 49.76. The article by Burnichon N (2010) in blue cluster also had a considerable influence in the genetics of PPGL, which generated a strong citation burst from 2011 to 2015 and had the second highest citation strength value (49.25). The yellow cluster centered on Amar L was the smallest but maintained a strong correlation with documents in other clusters.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.5 Analysis of research hotspots\u003c/h2\u003e\n\u003cp\u003eThe top 40 most frequently occurring keywords visualized in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, which showed the most concerned topic in this field. The timeline map of keywords was showed in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e, suggesting the development and changes of the research hotspots. The hotspot timeline cluster network included 726 nodes, with the modularity Q and mean silhouette values of were 0.5134 and 0.8091, respectively, suggesting that the cluster network was significant and robust, and the keywords within each cluster had a high degree of homogeneity. Moreover, keywords clusters were arranged by the descending size of the cluster vertically, meaning that the smallest number of the cluster represented the largest cluster. The topmost cluster (cluster #0, Succinate dehydrogenase) consisted of 136 nodes and the 10 most frequently occurring words from Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e were included (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Additionally, the cluster #0 ranged from 2002 to 2022 and included the most burst terms. The 10 most common keywords based on the co-occurrence cluster (excluding keywords used in the retrieval) are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. The top three keywords were germline mutations (centrality\u0026thinsp;=\u0026thinsp;0.07, firstly appeared in 2002), mutation (centrality\u0026thinsp;=\u0026thinsp;0.04, firstly appeared in 2002), and succinate-dehydrogenase (centrality\u0026thinsp;=\u0026thinsp;0.03, firstly appeared in 2004), which were closely related to the pathogenesis of PPGL. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e shows the top 20 most frequently occurring keywords with the strongest citation bursts ranked based on the starting time of burst, indicating the emerging trends. The keyword, hereditary paraganglioma, was the first to generate a citation burst and lasted for the longest time, from 2002 to 2012, indicating continuous interest on hereditary paraganglioma. Additionally, research on genes and gene mutations has increased, giving rise to nine citation bursts in the last 20 years, including ret protooncogene (2002\u0026ndash;2006), complex Ⅱ gene (2006\u0026ndash;2011), sdhd gene (2005\u0026ndash;2011), molecular genetics (2012\u0026ndash;2016), max mutation (2013\u0026ndash;2019), germline mutation (2013\u0026ndash;2015), hif2a mutation (2014\u0026ndash;2017), sdh mutation (2014\u0026ndash;2016), and somatic mutation (2015\u0026ndash;2019), demonstrating the status of the exploration of genes and their molecular mechanisms in the PPGL research field.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe 10 most frequently occurring keywords (derived from the list in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, excluding the keywords used in the literature search)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eLabel\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOccurrences\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCentrality\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eYear of first occurrence\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGermline mutations\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e259\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMutation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e247\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSuccinate-dehydrogenase\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e224\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMalignant pheochromocytoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e152\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiagnosis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e149\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2003\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGene\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e135\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2003\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTumor\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e133\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eManagement\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHead\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGene mutation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e104\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":" \u003cp\u003eThis bibliometric analysis concentrated on the genetics of PPGLs from 2002 to 2022, depicting the historical changes and development of this field in the past 20 years.\u003c/p\u003e \u003cp\u003eIn our study, there is a general increasing trend in the annual number of publications and citation frequency, suggesting increased interest in the genetics of PPGL. Furthermore, most publications originated from the European countries and the United States, among which the most productive country was the United States. But the citation frequency of USA only ranked fifth, followed by some European countries, suggesting that these European countries had more in-depth research in this field. As for institutions, the NIH Eunice Kennedy Shriver National Institute of Child Health \u0026amp; Human Development (NICHD) contributed to the highest number of publications and mainly published in recent 5 years, indicating that it had great potential to make huge contributions in this field. In 2014, NICHD published an article by Lenders JW et al.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which provided the first clinical guidelines for the diagnosis and treatment of pheochromocytoma and paraganglioma, including biochemical testing, imaging tests and genetic testing. In recent years, the update of diagnostic guidelines to include genetic testing in various types of PPGL further proved the importance of genetics in disease detection[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCo-citation analysis shows documents on similar research topics or authors with similar research directions. The top 20 co-citation network of journals showed the close relationship among journals. The journals\u0026rsquo; co-citation cluster was centered on the Journal of Clinical Endocrinology \u0026amp; Metabolism founded in the USA. In addition, this journal had the highest number of publications and h-index, indicating that the journal has authoritative reference value in this field. Furthermore, the document co-citation analysis network primarily formed four clusters. In green cluster, the most cited article was published by Baysal BE in 2000[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], which focused on genetic analysis of familial paragangliomas and genetic testing for screening individuals with a genetic risk of the disease. The article laid a foundation for subsequent in-depth exploration of the impact of genetic alterations on pathogenesis of PPGL. Additionally, in this cluster, two articles published by Neumann HPH in 2002[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and 2004[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] also had a considerable influence on this field, which described the relationship between gene mutations and pheochromocytoma and paraganglioma respectively, which became a hot topic of interest and resulted in strong citation bursts in 2002\u0026ndash;2007 and 2005\u0026ndash;2009. Also, these two publications demonstrated the importance of genetic testing in PPGL. Moreover, Astuti D[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] published an article about germline SDHD mutation in 2001. This is the first time to report SDHD mutation in familial phaeochromocytoma, but not in sporadic pheochromocytoma, which illustrates the crucial role of SDHD mutations in genetic pathogenesis and became an important milestone in the study of SDHx family mutations. In another cluster, a study conducted by Burnichon N[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] in 2009 investigated gene mutations in succinate dehydrogenase subunits (SDHx) associated with paraganglioma, using the QMPSF and MLPA methods. Furthermore, the PPGL diagnostic guidelines issued by Lenders JW et al. in 2014[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] formed another important landmark in the PPGL field, as shown by the strongest burst citation value.\u003c/p\u003e \u003cp\u003eThe top keywords and burst terms reflected the research hotspots and predicted new research frontiers. The top 3 most frequently occurring keywords were associated with mutation (germline mutations, mutation and succinate dehydrogenase) and the gene mutation happened in succinate dehydrogenase related genes are usual and widely investigated. Furthermore, the largest keyword cluster (cluster #0) was also included succinate dehydrogenase, with the highest burst strength. As shown on the keywords co-occurrence time-view map, PPGL-related genetics research consistently focused on succinate dehydrogenase, from sdhd gene (2005\u0026ndash;2011), succinate dehydrogenase (2012\u0026ndash;2015) to sdh mutation (2014\u0026ndash;2016). Succinate dehydrogenase comprises four subunits (SDHA, SDHB, SDHC, and SDHD). Additionally, succinate dehydrogenase plays a crucial role in oxidizing succinic acid to fumarate in the Krebs cycle and electron transfer in the mitochondrial respiratory chain. Impaired succinate dehydrogenase activity is linked to reprogramming of cellular metabolic pathways, and accumulation of oncometabolites in the cytoplasm responsible for genome-wide hypermethylation and pseudohypoxic \u0026ldquo;signature\u0026rdquo; contributing to PPGL tumourigenesis[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The SDHx gene family (sdhd, sdhc, sdhb, sdha and sdhaf2) encodes the subunits of succinate dehydrogenase enzyme complex. Mutations (germline mutations or somatic LOH) in these genes results in a protein with loss of enzyme activity. The penetrance of sdha and sdhd gene mutation carriers was first proposed in 2006[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Subsequently, there was a gradual increase in research on other members of the SDHx family in PPGL[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Germline mutations in SDHx account for a hereditary background in approximately 20% of PPGL tumors[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This bibliometric analysis revealed increased interest in metabolic reprogramming in the etiology of PPGLs, representing a major milestone in the genetics of PPGLs.\u003c/p\u003e \u003cp\u003eWith regard to cluster #1(metastatic pheochromocytoma), most of the keywords focused on the diagnosis and management of metastatic pheochromocytoma. Metastasis occurs in 35% of the PPGL patients. Gene mutations, especially sdhb mutation, are associated with increased metastasis rate[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Tumors with sdhb mutations are highly aggressive and are characterized by activation of the epithelial-mesenchymal transition pathway. Due to the heterogeneity and low incidence rate of PPGL, no effective targeted therapies have been developed. Symptomatic patients are managed by surgery, radiotherapy, or chemotherapy, which only achieves partial relief[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Ascorbic acid has been exploited as a potential therapeutic agent as it targets the redox pathway in SDHB-deficient PPGL[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis bibliometric analysis shows the current status and trends of genetic research in PPGL from 2002\u0026ndash;2022. However, there are some limitations in our study. Firstly, we only analyzed publications retrieved from the WoSCC database in the past 20 years, thus it is unable to fully understand the historical development of this field. Secondly, we only included articles published in English. If non-English articles were also included, the results would be slightly different. Thirdly, this analysis only focused on genetics in PPGL. Therefore, future analysis concentrating on other or more aspects of the disease may assist in acquiring the overall picture of research changes of this field and understanding the cause of PPGL more comprehensively.\u003c/p\u003e"},{"header":"5 Conclusion","content":" \u003cp\u003eTo sum up, the current study presents a clear picture of the historical development and future research trends in the genetics of PPGL from 2002 to 2022 by bibliometric methods. Over the past two decades, there has been a general upward trend in gene-related research in PPGL, suggesting the important role of genetic factors in the pathogenesis, prediction and treatment of PPGL. In the future, it is worthwhile to continue in-depth research on crucial mutant genes and their specific mechanisms of pathogenesis in order to develop drugs or therapeutic methods that specifically target the mutations to effectively treat PPGL. Furthermore, it is hoped that our study will contribute to directions of future research on PPGL.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis work was supported by Capital\u0026rsquo;s Funds for Health Improvement and Research(CFH-2020-1-4014) and Beijing Key Clinical Specialty for Laboratory Medicine - Excellent Project (No. ZK201000).\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eConceptualization: Ling Qiu; Methodology: Lei Li and Yiwen Lu; Formal analysis and investigation: Lei Li, Jian Zhong; Writing - original draft preparation: Lihua Guan; Writing - review and editing: Lihua Guan and Lei Li; Funding acquisition:Ling Qiu; Supervision: Yutong Zou\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFishbein L. Pheochromocytoma/Paraganglioma: Is This a Genetic Disorder? Curr Cardiol Rep. 2019;21(9):104.\u003c/li\u003e\n\u003cli\u003eCawthon RM, Weiss R, Xu GF, Viskochil D, Culver M, Stevens J, et al. A major segment of the neurofibromatosis type 1 gene: cDNA sequence, genomic structure, and point mutations. Cell. 1990;62(1):193-201.\u003c/li\u003e\n\u003cli\u003eIkeda I, Ishizaka Y, Tahira T, Suzuki T, Onda M, Sugimura T, et al. Specific expression of the ret proto-oncogene in human neuroblastoma cell lines. Oncogene. 1990;5(9):1291-6.\u003c/li\u003e\n\u003cli\u003eTahira T, Ishizaka Y, Itoh F, Sugimura T, Nagao M. Characterization of ret proto-oncogene mRNAs encoding two isoforms of the protein product in a human neuroblastoma cell line. Oncogene. 1990;5(1):97-102.\u003c/li\u003e\n\u003cli\u003eFavier J, Amar L, Gimenez-Roqueplo AP. Paraganglioma and phaeochromocytoma: from genetics to personalized medicine. 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J Med Genet. 2018;55(6):384-94.\u003c/li\u003e\n\u003cli\u003eZelinka T, Musil Z, Duskova J, Burton D, Merino MJ, Milosevic D, et al. Metastatic pheochromocytoma: does the size and age matter? Eur J Clin Invest. 2011;41(10):1121-8.\u003c/li\u003e\n\u003cli\u003eJasim S, Jimenez C. Metastatic pheochromocytoma and paraganglioma: Management of endocrine manifestations, surgery and ablative procedures, and systemic therapies. Best Pract Res Clin Endocrinol Metab. 2020;34(2):101354.\u003c/li\u003e\n\u003cli\u003eLiu Y, Pang Y, Zhu B, Uher O, Caisova V, Huynh TT, et al. Therapeutic Targeting of SDHB-Mutated Pheochromocytoma/Paraganglioma with Pharmacologic Ascorbic Acid. Clin Cancer Res. 2020;26(14):3868-80.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"clinical-and-experimental-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"clem","sideBox":"Learn more about [Clinical and Experimental Medicine](https://www.springer.com/journal/10238)","snPcode":"10238","submissionUrl":"https://submission.nature.com/new-submission/10238/3","title":"Clinical and Experimental Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"pheochromocytoma, paraganglioma, PPGL, genetics, bibliometric analysis","lastPublishedDoi":"10.21203/rs.3.rs-2597108/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2597108/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOver the past two decades, there has been a significant growth in articles focusing on the genetics of pheochromocytoma and paraganglioma (PPGL). We used bibliometric methods to investigate the historical changes and trend in PPGL research. There was a total of 1,263 articles published in English from 2002 to 2022 included in our study. The number of annual publications and citations in this field has been increasing in the past 20 years. Furthermore, most of the publications originated from the European countries and the United States. The co-occurrence analysis showed close cooperation between different countries, institutions, or authors. The dual-map discipline analysis revealed that majority articles focused on four disciplines: #2 (Medicine, Medical, Clinical), #4 (Molecular, Biology, Immunology), #5 (Health, Nursing, Medicine), and #8 (Molecular, Biology, Genetics). The hotspot analysis revealed the keywords that have been landmark for PPGL genetics research in different time periods, and there was continued interest in gene mutations, especially on SDHX family genes. In conclusion, this study displays the current status of research and future trends in the genetics of PPGL. In the future, more in-depth research should concentrate on crucial mutation genes and their specific mechanisms to assist in molecular target therapy. It is hoped that this study may help to provide directions for future research on genes and PPGL.\u003c/p\u003e","manuscriptTitle":"Research in the genetics of pheochromocytoma and paraganglioma: A bibliometric analysis from 2002 to 2022","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-02-23 18:58:14","doi":"10.21203/rs.3.rs-2597108/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-02-28T13:19:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-02-28T13:13:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187d1462-23e0-49a4-9f07-6538562496dc","date":"2023-02-24T12:34:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-02-22T13:08:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-02-22T07:52:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-02-22T07:52:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Clinical and Experimental Medicine","date":"2023-02-17T03:56:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"clinical-and-experimental-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"clem","sideBox":"Learn more about [Clinical and Experimental Medicine](https://www.springer.com/journal/10238)","snPcode":"10238","submissionUrl":"https://submission.nature.com/new-submission/10238/3","title":"Clinical and Experimental Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"468210ae-500a-4cb4-815b-a8e2d9b429eb","owner":[],"postedDate":"February 23rd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T20:42:28+00:00","versionOfRecord":{"articleIdentity":"rs-2597108","link":"https://doi.org/10.1007/s10238-023-01049-6","journal":{"identity":"clinical-and-experimental-medicine","isVorOnly":false,"title":"Clinical and Experimental Medicine"},"publishedOn":"2023-04-27 20:36:32","publishedOnDateReadable":"April 27th, 2023"},"versionCreatedAt":"2023-02-23 18:58:14","video":"","vorDoi":"10.1007/s10238-023-01049-6","vorDoiUrl":"https://doi.org/10.1007/s10238-023-01049-6","workflowStages":[]},"version":"v1","identity":"rs-2597108","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2597108","identity":"rs-2597108","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}