Global trends and research status in clonal hematopoiesis: a bibliometric analysis of the last 10 years

Global trends and research status in clonal hematopoiesis: a bibliometric analysis of the last 10 years | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Global trends and research status in clonal hematopoiesis: a bibliometric analysis of the last 10 years QingQing Luo, Li Yu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5703090/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Objective: Clonal hematopoiesis (CH) refers to the clonal expansion of hematopoietic stem cells caused by somatic mutations. CH is commonly observed in elderly individuals and is closely associated with myeloid malignancies as well as various non-malignant diseases. This study aims to explore the research trends and hotspots of CH using bibliometric analysis. Methods: Relevant studies were retrieved from the Web of Science Core Collection database based on predefined inclusion criteria. Bibliometric analysis and visualization were conducted using VOSviewer, CiteSpace, and R software. Results: A total of 851 studies were included. From 2014 to 2024, the annual number of publications showed a consistent upward trend. The United States was identified as the leading country in this field, contributing 53.7% of the total publications. Harvard Medical School and Benjamin L Ebert were recognized as the most influential institution and author, respectively. Blood was the most prolific journal, with the highest citation and H-index. Research on CH-related gene mutations and their association with the risk of acute myeloid leukemia is currently the most extensively studied area, while cardiovascular diseases and inflammation have emerged as recent research hotspots. Conclusion: This study is the first to systematically analyze research related to CH using bibliometric methods. Our analysis reveals the overall landscape of CH research and identifies the most influential contributors in the field, including countries, institutions, authors, and journals. Moreover, we identify emerging research hotspots and key areas, highlighting potential avenues for exploration and innovation within the field of CH. Clonal hematopoiesis Bibliometric Research trend Research hotspots Visualized Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction As individuals age, somatic mutations gradually accumulate in their tissues. While most of these mutations have minimal or no functional impact, some can confer a selective growth advantage to certain cells. In the hematopoietic system, this can result in a large fraction of circulating blood cells being derived from a single mutated hematopoietic stem cells (HSCs), a phenomenon known as Clonal Hematopoiesis (CH). Since the major breakthrough in 2014, CH has become a central topic of interest in both scientific and clinical research [ 1 , 2 ]. CH is primarily driven by a limited set of gene mutations involving epigenetic regulation (DNMT3A, TET2, and ASXL1), signaling pathways (JAK2), RNA splicing (SF3B1 and SRSF2), and DNA damage response (TP53 and PPM1D). Additionally, mosaic chromosomal alterations (mCAs) are also an important mechanism of CH, including amplifications, deletions, and copy-neutral loss of heterozygosity (CNLOH), among others [ 3 ]. CH becomes more prevalent with age due to the accumulation of mutations at the population level. In healthy individuals under 40, CH is detected in less than 1% of cases, but its prevalence skyrockets to 20% in individuals over 90 years old [ 4 ]. Additionally, external factors such as smoking, obesity, infections, and exposure to cancer treatments can further accelerate the progression of CH [ 5 ]. Although CH itself is not synonymous with malignancy, many of the commonly CH genes are driver mutations for myeloid tumor and are considered the “first hit” in hematologic malignant transformation [ 1 ]. The presence of CH is associated with a 30 ~ 40% increase in overall mortality, which cannot be fully explained by the increased risk of hematologic malignancies. Instead, the primary contributor to this elevated mortality appears to be an increased incidence of cardiovascular diseases (CVD) [ 6 ]. Moreover, emerging research has linked CH to a range of age-associated conditions, including type 2 diabetes (T2D), chronic obstructive pulmonary disease (COPD), chronic liver disease, gout, rheumatoid arthritis, and tumors [ 7 – 11 ]. This linkage may be driven by the production of mutated immune effector cells by altered HSCs, resulting in elevated levels of pro-inflammatory factors [ 12 ]. Despite significant progress in CH research in recent years, most existing studies have focused on genetic mutations, clinical phenotypes, and underlying mechanisms. However, a comprehensive analysis of the current state of research, key areas of focus, and global development trends remains notably absent. Bibliometric analysis, as a methodology combining qualitative and quantitative approaches, offers valuable insights into research trends, emerging hotspots, and academic impact by examining the contributions of countries, institutions, authors, and journals [ 13 , 14 ]. This study employs bibliometric methods to review the research outputs on CH over the past decade. By mapping the research landscape in this field, we aim to provide new perspectives and directions for future investigations into CH. 2. Materials and methods Data acquisition The articles in this study were indexed from the Web of Science Core Collection (WoSCC) database, which contains more than 10,000 journals and is one of the most commonly used and authoritative databases for bibliometric analysis [15]. The search strategy was presented as follows: TS = (“clonal hematopoiesis”) OR (“clonal haematopoiesis”). The publication period was limited to between 2014 and 2024, and the publication type was limited to original articles written in English. Two researchers retrieved and screened the raw data, removing publications unrelated to CH in the title and abstract by screening, and resolved any discrepancies through discussion. A flowchart describing how publications were selected is presented in Figure 1 . Data extraction The retrieved literature was stored in plain text file formats for further analysis. The following data were extracted from the selected publications: title, authors, institutions, countries, journals (including the 2024 journal impact factor [IF]), publication year, citation counts, and H-index. Bibliometric analysis This study employed VOSviewer (version 1.6.20), CiteSpace (version 6.1.6), and R (version 4.3.2) software to generate visualizations. CiteSpace is a powerful tool for identifying and visualizing emerging trends and hotspots in specific research fields. It achieves this through the analysis of citation bursts, co-citation networks, and the temporal evolution of high-frequency keywords [16]. VOSviewer is a bibliometric software tool designed for constructing and visualizing bibliometric networks. In this study, VOSviewer was employed to analyze collaboration networks among countries, institutions, journals, and authors, as well as to identify co-citation relationships and generate keyword overlay visualizations. In these visualizations, each node represents a specific parameter, with node size reflecting the parameter's importance. Different clusters are distinguished by nodes and lines of varying colors, while the thickness of the connecting lines indicates the strength of the relationship between nodes [17]. Total Link Strength (TLS) refers to the sum of the connection strengths between a specific node and all other nodes within the network. It is used to assess the overall influence or centrality of that node within the bibliometric analysis. H-index is a robust metric that evaluates the productivity and impact of authors, countries, institutions, and journals. In this study, we report the H-index of the corresponding author specifically within the field of CH. Finally, we used citation data from the selected papers to detect pairs of articles that were cited by the same references. The co-citation strength between two papers was calculated based on how often they were cited together in the same article. This was done using bibliometric software tools to automate the extraction and analysis of the co-citation relationships. 3. Result Growth trend of publications A total of 851 publications meeting the inclusion criteria were retrieved from the WoSCC database. The annual distribution of publications in the field of CH is presented in Figure 2A , which reveals a consistent upward trend over the years. When I calibrated the annual total publications, this trend persisted ( supplementary Figure 1 ). The number of publications reached its peak in 2024, with 182 articles published, accounting for 21.4% of the total output. As shown in Figure 2B , the cumulative number of publications from 2014 to 2024 has steadily increased, further underscoring the growing academic interest in the field of CH. Between 2017 and 2021, both the citation count ( Figure 2C ) and H-index ( Figure 2D ) were relatively high, with annual citations consistently exceeding 5,000 and the H-index surpassing 25, indicating significant scholarly impact. Analysis of country/region and institution attributes of the publications We analyzed the publication count, total citations, and H-index of the top ten productive countries. As shown in Figure 3 and Table 1 , the United States of America (USA) leads with 457 publications, accounting for 53.7% of the total output, followed by Germany and England, each with 117 and 88 publications. Moreover, the USA not only dominates in publication output but also excels in academic influence, boasting a total of 33,939 citations and an H-index of 346. As shown in Figure 4A , the visualization of the international collaboration network among 55 participating countries highlights the USA as the central hub, with the strongest collaboration network (TLS = 439) and the closest ties to China, Germany, the United Kingdom, and Canada. Figure 4B presents the complex collaboration network among institutions, comprising 1591 distinct entities. Harvard Medical School has the most extensive collaboration network with a TLS of 362. Focusing on the top ten productive institutions ( Table 2 ), all of these institutions are based in the USA. Harvard Medical School ranks first with 99 publications, accounting for 11.6% of the total output. It is followed by Dana-Farber Cancer Institute with 72 publications (8.5%) and Massachusetts General Hospital with 65 publications (7.6%). Additionally, Harvard Medical School stands out with a remarkable citation impact of 9,115 citations and the highest H-index of 129. Analysis of authors of publications Table 3 highlights the top 10 authors with the highest publication output. Benjamin L Ebert ranks first, with 53 publications, accounting for 6.2% of the total, followed by Pradeep Natarajan with 49 publications, and Alexander G Bick with 45. Benjamin L Ebert also demonstrates exceptional citation impact, amassing 3,337 citations and achieving an H-index of 33, underscoring the substantial influence in the field. To visualize the complex collaboration network among these authors, Figure 4C presents a network map. In this intricate network, Benjamin L Ebert emerges as the most central node, with the highest number of collaborations (TLS = 101). A three-field plot was created to visually represent the top 20 authors with the highest publication output, along with their affiliated institutions, countries, journals, and keywords. Notably, most of these prominent authors are affiliated with Harvard University in the USA. The publications are primarily featured in The New England Journal of Medicine, Blood, and Nature, with keywords predominantly focusing on “clonal hematopoiesis”, “inflammation”, “aging”, “atherosclerosis” and “clonal hematopoiesis of indeterminate potential (CHIP)” ( Figure 5 ). Analysis of source journals and co-cited journals Among the 251 papers published in the top ten journals ( Table 4 ), accounting for 29.5% of the total publication output, Blood, Blood Advances, and Leukemia are the most prominent journals in this field, with 53, 51, and 30 publications, respectively. Blood leads significantly in both citation count (5,306) and H-index (35), far outperforming Blood Advances (1,174 citations and an H-index of 20) and Leukemia (1,195 citations and an H-index of 19). IF is a key metric for assessing a journal’s value and the significance of its publications. Nature holds the highest IF at 50.5, followed by Blood at 21.0 and Cell Stem Cell at 19.8. Figure 4D illustrates the cocitation network among journals. The top three cocited journals are: Blood (4,258 cocitations), The New England Journal of Medicine (2,553 cocitations), and Nature (2,103 cocitations). Analysis of highly cited studies The top 10 most cited studies are listed in Table 5 . Among these, three originate from Brigham and Women’s Hospital in the USA, and two from the Memorial Sloan Kettering Cancer Center. The study by Siddhartha Jaiswal published in 2014 in The New England Journal of Medicine (IF = 96.2), titled “Age-related clonal hematopoiesis associated with adverse outcomes” has been cited 3,282 times, making it the most cited paper in this field [2]. In terms of research topics, four studies found that CH is common in the elderly and associated with increased risk of blood cancer [1-3, 18, 19]. Two studies analyzed the relationship between CH and anticancer treatments. Kelly L Bolton [20] and Catherine C Coombs et al. [21] contend that cancer therapy shapes the fitness landscape of CH, ultimately leading to adverse clinical outcomes. Furthermore, two studies examined the association between CH and CVD. Siddhartha Jaiswal [22] found that patients with DNMT3A and TET2 mutations have a significantly increased risk of CVD, possibly due to mutated hematopoietic cells driving inflammation by activating the NLRP3 inflammasome [23]. Another study discussed the distinction between CH and Myelodysplastic Syndromes (MDS) [24]. The citation density distribution is shown in Figure 6 . Analysis of co-cited references Table 6 lists the top 10 most cocited references and provides a visualization of cocited publications in Figure 7A . The studies by Siddhartha Jaiswal et al. [2] on age-related CH and its adverse outcomes, and by Giulio Genovese et al. [1] on CH and its risk of blood cancer inferred from blood DNA sequence were cited the most, 530 and 412 times respectively. Among the top 10 cocited papers, three were published in The New England Journal of Medicine (IF = 96.2), two in Blood (IF = 21.0), and one in Nature (IF = 50.5). To further analyze the dynamic changes in citation patterns, we used CiteSpace to identify the top 15 references with the strongest citation bursts. As shown in Figure 7B , the most significant citation burst was observed for the 2014 paper by Siddhartha Jaiswal et al. [2], followed by the 2014 study by Giulio Genovese et al. [1] published in The New England Journal of Medicine, and the 2014 paper by Mingchao Xie et al. [25] in Nature Medicine. These findings underscore the significant impact and relevance of these publications in the field. Keyword analysis of research hotspots Keyword co-occurrence analysis is a commonly used method to identify trending research topics. The top 10 most frequently used keywords are “clonal hematopoiesis”, “risk”, “mutations”, “acute myeloid leukemia” (AML), “dnmt3a”, “leukemia”, “tet2”, “inflammation”, “stem cells”, and “age”. Clustering keywords helps delineate the distribution of research themes ( Figure 8A ). The largest red cluster contains keywords related to the mutation spectrum of CH, its prevalence, and its association with clinical outcomes, including “landscape”, “prevalence”, “outcomes”, and “prognosis”. The green cluster focuses on the relationship between CH and CVD, with keywords like “atherosclerosis”, “heart failure”, “inflammation”, “dnmt3a”, and “tet2”. The blue cluster primarily investigates the mechanisms of CH in hematopoietic stem cells, with keywords like “dna methylation”, “hematopoietic stem cell”, and “self-renewal”. As shown in Figure 8B , keywords such as “acute myeloid leukemia”, “genes”, “hematopoietic stem cells” and “evolution” represent key topics from earlier studies. In contrast, current research hotspots are characterized by keywords like “heart failure”, “inflammation”, “atherosclerosis” and “clonal hematopoiesis of indeterminate potential” (CHIP). The keyword evolution depicted in Figure 8C reveals the changing research interests over time. In 2014, the focus was primarily on CH-related genes and their association with myeloid malignancies, including “acute myeloid leukemia”, “myelodysplastic syndromes”, “mutations”, “tet2”, and “dnmt3a”. From 2014 to 2020, interest in the relationship between CH and cardiovascular diseases surged, with keywords such as “atherosclerosis”, “heart failure”, and “inflammation” emerging prominently. In addition, studies on tp53 and jak2 mutants are increasing. After 2020, attention shifted toward the clinical significance and mechanisms of CH. The burst intensity of keywords as shown in Figure 8D , offers valuable insights into the dynamism and emerging trends of research frontiers. Among the top 15 keywords with the highest burst intensity, “acute myeloid leukemia” stands out with the strongest recent burst, underscoring its significant implications. Additionally, the sustained bursts of “dynamics” and “landscape” in 2024 emphasize their continued relevance as critical and enduring research topics. Discussion To the best of our knowledge, this is the first comprehensive bibliometric analysis of publications related to CH. Our findings reveal a consistent upward trend in the annual number of publications in this field. Notably, 2024 stands out as a pivotal year, with the highest number of publications. The period from 2017 to 2021 exhibited significant academic impact, as reflected by high citation counts and H-index. The observed decline in citation counts and H-index over the past three years may be attributed to the proximity of the data collection period. The analysis encompassed the most influential countries, institutions, authors, and journals within the field. The results indicate that the USA dominates this area of research, as evidenced by its extensive international collaborations, the highest number of publications, the most citations, and the highest H-index. All of the top ten research institutions are based in the USA, with Harvard Medical School recognized as the most impactful institution in this field. Benjamin L Ebert has established a central role in the study of CH through his long-standing focus on its molecular mechanisms and implications in disease. However, many of studies are the result of collaborative efforts within research teams, which may not be fully reflected in the bibliometric analysis. Blood, Blood Advances, and Leukemia are considered the leading journals in this domain, with Blood ranking first in terms of publication count, citations, and H-index, underscoring the strong connection between CH and hematological diseases. Additionally, Blood, The New England Journal of Medicine, and Nature rank as the top three cocited journals, reflecting the breadth and significance of CH research in these publications. In addition, we examined the top 10 most cited publications, widely regarded as the most impactful and significant contributions to the field. In 2014, Siddhartha Jaiswal [2] and Giulio Genovese [1] performed DNA exome sequencing on a large cohort and found that somatic mutations associated with CH increase with age, correlating with higher risks of hematologic cancers, all-cause mortality, and CVD, laying the foundation for subsequent CH research. Andrew L Young further confirmed that CH-related mutations are widespread in healthy adults [19]. David P Steensma [24] explored the nature and prevalence of CHIP and differentiated it from myelodysplastic syndromes (MDS). Florian Zink [18] developed a method to identify individuals with CH based on the accumulation of somatic mutations in the dominant HSC clone. Alexander G. Bick [3] observed that germline genetic variation shapes HSCs function leading to CHIP through mechanisms that are both specific to CH and shared mechanisms leading to somatic mutations across tissues. CH is also associated with an increased risk of atherosclerotic cardiovascular disease, potentially through mechanisms involving TET2-deficient macrophages and NLRP3 inflammasome-mediated IL-1β secretion [22, 23]. Kelly L. Bolton [20] and Catherine C. Coombs' study [21] found that cancer treatments shape the landscape of CH. Cancer therapies such as radiotherapy, platinum-based drugs, and topoisomerase II inhibitors preferentially select for mutations in DNA damage response genes (e.g., TP53, PPM1D, CHEK2), ultimately leading to poor prognosis. Keyword analysis revealed that the most frequently appearing terms included “CH”, “mutation”, and “risk”, indicating that CH-related genetic mutations and their association with disease risk are the most widely studied areas in this field. CH involves mutations in 74 driver genes, the majority of which overlap with those implicated in AML. Mutations in TET2, DNMT3A, and ASXL1 are the most prevalent, collectively representing over 75% of cases. Meanwhile, mutations in PPM1D, JAK2, SF3B1, SRSF2, and TP53 account for an additional 15% [3, 26]. Recent studies analyzing whole-blood exome data from 200,618 individuals in the UK Biobank have identified 17 novel genes whose mutations are comparable in impact to classic CH drivers [27]. In addition, the disease most closely associated with CH has been hematologic malignancies (HR: 12.9; 95% CI: 5.8-28.7). Approximately 42% of hematologic cancers already harbor CH mutations in DNA sampled more than six months before diagnosis [1]. Although the relative risk of myeloid malignancies is increased, the absolute risk remains low, with the malignant transformation rate of CH estimated at 0.5~1% annually. The risk of progression to myeloid malignancies depends on specific molecular and hematologic features. DNMT3A mutation has the lowest progression risk, whereas TP53, IDH1, IDH2, or RUNX1 mutation carries the highest risk of evolving into myeloid malignancies [28]. In the overlay and timeline map from the bibliometric analysis, keywords related to myeloid tumor appeared earlier, while CVD and inflammation have emerged as recent research hotspots. In nested case-control analyses from two prospective cohorts, individuals with CH were found to have a 1.9-fold increased risk of coronary heart disease compared to non-carriers [22]. Soichi Sano et al. [29] demonstrated that TET2-mediated CH accelerates heart failure progression via activation of the IL-1β/NLRP3 inflammasome pathway. This finding suggests a novel therapeutic direction for heart failure, aiming to mitigate its progression by inhibiting NLRP3 inflammasome activation. Moreover, NLRP3 inflammasome activation and increased IL-1β secretion driven by TET2 mutations have also been implicated in heightened susceptibility to atherosclerosis and atrial fibrillation [23, 30]. Isidoro Cobo et al. [31] revealed that loss of function in DNMT3A or TET2 impairs mitochondrial DNA integrity and activates cGAS signaling, leading to a type I interferon response, which elevates the risk of CVD. Using CRISPR technology to introduce DNMT3A mutations into murine HSCs, researchers observed exacerbated cardiac dysfunction and fibrosis following heart failure, driven by the upregulation of inflammatory mediators such as CXCL1, CXCL2, IL-6, and CCL5 [32]. Furthermore, heart failure patients harboring DNMT3A mediated CH exhibit a highly inflammatory transcriptomic profile in circulating monocytes and T cells, potentially contributing to the worsening of chronic heart failure [33]. DNMT3A or TET2 mutations have been significantly associated with poorer prognoses in CVD patients, likely due to elevated levels of inflammatory cytokines [34]. The bibliometric analysis in this study primarily highlights the association between CH and its mediation of myeloid malignancies and cardiovascular diseases. However, recent studies suggest that CH is closely linked to various age-related diseases. Waihay J Wong et al. [8] found that CH patients are more likely to develop liver inflammation and fibrosis (OR = 1.74), driven by elevated inflammatory cytokines in TET2-deficient macrophages. CH is also associated with a higher incidence of gout (OR = 1.69, 95% CI: 1.09-2.61), likely due to increased IL-1β levels [9]. CH carriers face a 1.6- to 2.2-fold higher risk of moderate-to-severe and severe COPD, respectively [35], and a 23% increased risk of T2D. Among CH mutations, TET2 (HR = 1.48) and ASXL1 (HR = 1.76) confer the greatest risk, while DNMT3A mutations are not statistically significant (HR = 1.15) [36]. DNMT3A-mediated CH promotes IL-20 expression via the Irf3-NF-κB pathway, driving osteoclast differentiation and ultimately leading to osteoporosis [37]. CH is also linked to the development of solid tumors. Ruiyi Tian et al. [38] reported that CH increases lung cancer risk (cases: 12.5% vs. controls: 8.7%; OR = 1.36, 95% CI: 1.06-1.74). Yongliang Zhang et al. [39] analyzed over 10,000 Chinese pan-cancer patients and found that 14% of plasma cell-free DNA samples harbored CH mutations, with detectability increasing with age. However, these studies have not been fully reflected in the bibliometric analysis, likely due to the relatively limited number and their more recent publication dates. Bibliometric analysis provides a novel and objective perspective on the development of hotspots and trends in CH research. In our analysis, we primarily focused on research related to CHIP, as studies involving CHIP genes have dominated the field of CH. This focus is reflected in the majority of our top hits from the bibliometric analysis. However, other subtypes of CH, such as mCAs, are lacking in our analysis, which reflects the current bias in the field. Moreover, this study has certain limitations in its methodology. The data were extracted exclusively from the WoSCC database, which may have led to the omission of relevant information from other sources. Additionally, this study included only English-language publications, which may overlook research from non-English-speaking countries or regions, thus limiting a comprehensive understanding of global research trends. Due to the novelty of the research topic and strict selection criteria, the number of included studies is relatively small, which may limit the robustness of the conclusions and the ability to capture the full scope of the field. In conclusion, the past decade has seen significant growth in research exploring the role of CH in various diseases, prompting us to select a comprehensive range of relevant publications from 2014 to 2024 for our study. By utilizing various statistical software programs, we performed a detailed bibliometric analysis to obtain a comprehensive overview of the advancements in understanding CH and its implications. Our analysis examined publication characteristics, identifying the most influential nations, institutions, authors, and journals, while also highlighting key research hotspots, emerging trends, and potential directions for future research. This has strengthened the understanding of CH and its related diseases. Declarations Financial support: This research was funded by the National Natural Science Foundation of China (82260043), the Natural Science Foundation of Jiangxi Province (20232ACB206016, 20204BCJ22030) and the Major Discipline Academic and Technical Leaders Training Program of Jiangxi Province (20225BCJ22001). Author Contributions: QingQing Luo and Li Yu designed the study, QingQing Luo collected the data, performed the analysis, and wrote the initial draft. 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Nat Med. 2014;20(12):1472-8. doi: 10.1038/nm.3733. PubMed PMID: 25326804. Khoury JD, Solary E, Abla O, Akkari Y, Alaggio R, Apperley JF, et al. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms. Leukemia. 2022;36(7):1703-19. doi: 10.1038/s41375-022-01613-1. PubMed PMID: 35732831. Bernstein N, Spencer Chapman M, Nyamondo K, Chen Z, Williams N, Mitchell E, et al. Analysis of somatic mutations in whole blood from 200,618 individuals identifies pervasive positive selection and novel drivers of clonal hematopoiesis. Nat Genet. 2024;56(6):1147-55. doi: 10.1038/s41588-024-01755-1. PubMed PMID: 38744975. Weeks LD, Ebert BL. Causes and consequences of clonal hematopoiesis. Blood. 2023;142(26):2235-46. doi: 10.1182/blood.2023022222. PubMed PMID: 37931207. Sano S, Oshima K, Wang Y, MacLauchlan S, Katanasaka Y, Sano M, et al. Tet2-Mediated Clonal Hematopoiesis Accelerates Heart Failure Through a Mechanism Involving the IL-1β/NLRP3 Inflammasome. J Am Coll Cardiol. 2018;71(8):875-86. doi: 10.1016/j.jacc.2017.12.037. PubMed PMID: 29471939. Lin AE, Bapat AC, Xiao L, Niroula A, Ye J, Wong WJ, et al. Clonal Hematopoiesis of Indeterminate Potential With Loss of Tet2 Enhances Risk for Atrial Fibrillation Through Nlrp3 Inflammasome Activation. Circulation. 2024;149(18):1419-34. doi: 10.1161/CIRCULATIONAHA.123.065597. PubMed PMID: 38357791. Cobo I, Tanaka TN, Chandra Mangalhara K, Lana A, Yeang C, Han C, et al. DNA methyltransferase 3 alpha and TET methylcytosine dioxygenase 2 restrain mitochondrial DNA-mediated interferon signaling in macrophages. Immunity. 2022;55(8). doi: 10.1016/j.immuni.2022.06.022. PubMed PMID: 35931086. Sano S, Oshima K, Wang Y, Katanasaka Y, Sano M, Walsh K. CRISPR-Mediated Gene Editing to Assess the Roles of Tet2 and Dnmt3a in Clonal Hematopoiesis and Cardiovascular Disease. Circ Res. 2018;123(3):335-41. doi: 10.1161/CIRCRESAHA.118.313225. PubMed PMID: 29728415. Abplanalp WT, Cremer S, John D, Hoffmann J, Schuhmacher B, Merten M, et al. Clonal Hematopoiesis-Driver DNMT3A Mutations Alter Immune Cells in Heart Failure. Circ Res. 2021;128(2):216-28. doi: 10.1161/CIRCRESAHA.120.317104. PubMed PMID: 33155517. Wang S, Hu S, Luo X, Bao X, Li J, Liu M, et al. Prevalence and prognostic significance of DNMT3A- and TET2- clonal haematopoiesis-driver mutations in patients presenting with ST-segment elevation myocardial infarction. EBioMedicine. 2022;78:103964. doi: 10.1016/j.ebiom.2022.103964. PubMed PMID: 35339897. Miller PG, Qiao D, Rojas-Quintero J, Honigberg MC, Sperling AS, Gibson CJ, et al. Association of clonal hematopoiesis with chronic obstructive pulmonary disease. Blood. 2022;139(3):357-68. doi: 10.1182/blood.2021013531. PubMed PMID: 34855941. Tobias DK, Manning AK, Wessel J, Raghavan S, Westerman KE, Bick AG, et al. Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk. Diabetes Care. 2023;46(11):1978-85. doi: 10.2337/dc23-0805. PubMed PMID: 37756531. Kim PG, Niroula A, Shkolnik V, McConkey M, Lin AE, Słabicki M, et al. Dnmt3a-mutated clonal hematopoiesis promotes osteoporosis. J Exp Med. 2021;218(12). doi: 10.1084/jem.20211872. PubMed PMID: 34698806. Tian R, Wiley B, Liu J, Zong X, Truong B, Zhao S, et al. Clonal Hematopoiesis and Risk of Incident Lung Cancer. J Clin Oncol. 2023;41(7):1423-33. doi: 10.1200/JCO.22.00857. PubMed PMID: 36480766. Zhang Y, Yao Y, Xu Y, Li L, Gong Y, Zhang K, et al. Pan-cancer circulating tumor DNA detection in over 10,000 Chinese patients. Nat Commun. 2021;12(1):11. doi: 10.1038/s41467-020-20162-8. PubMed PMID: 33397889. Tables Table 1. The top 10 most productive countries regarding clonal hematopoiesis research from 2014 to 2024 Rank Country Counts Percentage Total Citation H-Index 1 USA 457 53.7 33939 346 2 Germany 117 13.7 5473 93 3 England 88 10.3 12015 83 4 Canada 69 8.1 3306 55 5 Japan 64 7.5 3119 64 6 France 61 7.2 1830 39 7 Italy 59 6.9 3882 45 8 Sweden 58 6.8 12026 40 9 China 56 6.6 1432 40 10 Spain 49 5.8 6749 38 Table 2. The top 10 most productive institution regarding clonal hematopoiesis research from 2014 to 2024 Rank Institution Country Counts Percentage Total Citation H-Index 1 Harvard Medical School USA 99 11.6 9115 129 2 Dana Farber Cancer Institute USA 72 8.5 10618 57 3 Massachusetts General Hospital USA 65 7.6 11656 61 4 Memorial Sloan Kettering Cancer Center USA 65 7.6 8608 80 5 Brigham And Women's Hospital USA 56 6.6 12072 68 6 Vanderbilt University USA 44 5.2 2005 42 7 Washington University USA 40 4.7 2936 43 8 Stanford University USA 39 4.6 2428 43 9 University of texas system USA 33 3.9 1900 43 10 Broad Institute of MIT and Harvard USA 32 3.8 1709 49 Table 3. The top 10 productive authors regarding clonal hematopoiesis research from 2014 to 2024 Rank Names Counts Percentage Total Citation H-Index 1 Benjamin L Ebert 53 6.2 3337 33 2 Pradeep Natarajan 49 5.8 1452 29 3 Alexander G Bick 45 5.3 1140 24 4 Ross L Levine 29 3.4 1685 19 5 Abhishek Niroula 28 3.3 768 19 6 Md Mesbah Uddin 26 3.1 653 16 7 Christopher J Gibson 24 2.8 397 17 8 Michael C Honigberg 23 2.7 531 11 9 Siddhartha Jaiswal 17 2.0 1947 22 10 Peter Libby 17 2.0 2627 13 Table 4. The top 10 most productive journals regarding clonal hematopoiesis research from 2014 to 2024 Rank Journals Counts Percentage Total Citation H-Index IF (2024) 1 Blood 53 6.2 5306 35 21.0 2 Blood Advances 51 6.0 1174 20 7.4 3 Leukemia 30 3.5 1195 19 12.8 4 Nature Communications 27 3.2 1900 19 14.7 5 Experimental Hematology 20 2.4 661 8 2.5 6 Haematologica 16 1.9 359 9 8.2 7 JCO Precision Oncology 16 1.9 337 9 5.3 8 Cell Stem Cell 13 1.5 1594 13 19.8 9 Hematology-American Society of Hematology Education Program 13 1.5 278 9 2.9 10 Nature 12 1.4 1413 11 50.5 Table 5. The top 10 most cited publications regarding clonal hematopoiesis research from 2014 to 2024 Rank Title Year Institution Author Journal Citation 1 Age-related clonal hematopoiesis associated with adverse outcomes 2014 Brigham and Women's Hospital Siddhartha Jaiswal The New England journal of medicine 3282 2 Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence 2014 Harvard Medical School Giulio Genovese The New England journal of medicine 2471 3 Clonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease 2017 Brigham and Women’s Hospital Siddhartha Jaiswal The New England journal of medicine 1710 4 Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes 2015 Brigham and Women's Hospital David P Steensma Blood 1440 5 Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice 2017 Boston University School of Medicine José J Fuster Science 1001 6 Therapy-Related Clonal Hematopoiesis in Patients with Non-hematologic Cancers Is Common and Associated with Adverse Clinical Outcomes 2017 Memorial Sloan Kettering Cancer Center Catherine C Coombs Cell Stem Cell 569 7 Clonal hematopoiesis, with and without candidate driver mutations, is common in the elderly 2017 deCODE genetics/AMGEN Florian Zink Blood 545 8 Clonal haematopoiesis harbouring AML-associated mutations is ubiquitous in healthy adults 2016 Washington University School of Medicine Andrew L Young Nature communications 502 9 Cancer therapy shapes the fitness landscape of clonal hematopoiesis 2020 Memorial Sloan Kettering Cancer Center Kelly L Bolton Nature genetics 414 10 Inherited causes of clonal haematopoiesis in 97,691 whole genomes 2020 Massachusetts General Hospital Alexander G Bick Nature 366 Table 6. Top 10 co-cited references. Rank Title Year Institution Author Journal CO-Citation 1 Age-Related Clonal Hematopoiesis Associated with Adverse Outcomes 2014 Brigham and Women's Hospital Siddhartha Jaiswal The New England journal of medicine 530 2 Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence 2014 Harvard Medical School Giulio Genovese The New England journal of medicine 412 3 Clonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease 2017 Brigham and Women's Hospital Siddhartha Jaiswal The New England journal of medicine 325 4 Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes 2015 Brigham and Women's Hospital David P Steensma Blood 268 5 Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice 2017 Boston University School of Medicine José J Fuster Science 197 6 Therapy-Related Clonal Hematopoiesis in Patients with Non-hematologic Cancers Is Common and Associated with Adverse Clinical Outcomes 2017 Memorial Sloan Kettering Cancer Center Catherine C Coombs Cell stem cell 166 7 Clonal hematopoiesis, with and without candidate driver mutations, is common in the elderly 2017 deCODE genetics/AMGEN Florian Zink Blood 142 8 Cancer therapy shapes the fitness landscape of clonal hematopoiesis 2020 Memorial Sloan Kettering Cancer Center Kelly L Bolton Nature genetics 128 9 Inherited causes of clonal haematopoiesis in 97,691 whole genomes 2020 Massachusetts General Hospital Alexander G Bick Nature 112 10 Genetic Interleukin 6 Signaling Deficiency Attenuates Cardiovascular Risk in Clonal Hematopoiesis 2020 Massachusetts General Hospital Alexander G Bick Circulation 88 Additional Declarations No competing interests reported. Supplementary Files S1.png Supplementary Figure 1. Adjusted number of published publications. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 08 Apr, 2025 Editor assigned by journal 08 Apr, 2025 Reviews received at journal 28 Mar, 2025 Reviewers agreed at journal 27 Mar, 2025 Reviewers agreed at journal 27 Mar, 2025 Reviews received at journal 26 Mar, 2025 Reviewers agreed at journal 25 Mar, 2025 Reviewers invited by journal 25 Mar, 2025 Submission checks completed at journal 24 Mar, 2025 First submitted to journal 27 Feb, 2025 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. 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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-5703090","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":447396260,"identity":"f71287dd-ef8b-4fa4-88c1-465c8a9dba0f","order_by":0,"name":"QingQing Luo","email":"","orcid":"","institution":"Second Affiliated Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"QingQing","middleName":"","lastName":"Luo","suffix":""},{"id":447396261,"identity":"aa1857ac-8a68-4dbb-adad-829852dc36f2","order_by":1,"name":"Li Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYFCCBIYPDAY2PPzMzAcgAgcIa2GcwVCRJifZzpZAipYzh40NzvMYEKfFnD35YDNvG3Niw2Gebw9+tjHI8d1IYPxcgEeLZc+zRKAWtsTGZt7thr1tDMaSNxKYpWfg0WJwI8f8MW8bT2IzM+82acY2hsQNNxLYmHnwasn/CLRFIrGNmecZSEs9EVpyGJt5zhgY8zDzsIG0JBgQ1HLmmWHjnIoEOQlmNjPJnnMShjPPPGyWxqvlePLDhjcG/3nszx9+JvGjzEae73jywc/4tIAAE5ICCSBmbCCgAajkB0Elo2AUjIJRMKIBAOYMTFuKUmbDAAAAAElFTkSuQmCC","orcid":"","institution":"Second Affiliated Hospital of Nanchang University","correspondingAuthor":true,"prefix":"","firstName":"Li","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2024-12-24 03:23:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5703090/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5703090/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81535514,"identity":"11f2c9a8-2f77-45b4-9e9e-195c8a5372b0","added_by":"auto","created_at":"2025-04-28 10:09:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":398393,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the literature screening process.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/43e067555822f2125b9dacdd.png"},{"id":81536059,"identity":"06c6789f-296a-452c-b84f-9e3fc0cb328c","added_by":"auto","created_at":"2025-04-28 10:17:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":607524,"visible":true,"origin":"","legend":"\u003cp\u003eThe characteristics of the included studies. A: The global annual number of publications; B: The global annual number of cumulative publications; C: The global annual number of citations of the publications; D: The global annual H-index values of the publications.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/9a1cfb73e1ad040bef017187.png"},{"id":81536053,"identity":"b0372c18-640a-4036-84e5-f9dc558d4325","added_by":"auto","created_at":"2025-04-28 10:17:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1096868,"visible":true,"origin":"","legend":"\u003cp\u003eThe country attributes of the publications.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/13f158fb6a9e0b80207cf071.png"},{"id":81536055,"identity":"03bc97b8-675c-4acc-b47c-9a35f5e32327","added_by":"auto","created_at":"2025-04-28 10:17:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4185763,"visible":true,"origin":"","legend":"\u003cp\u003eThe coauthorship network map of countries A, institutions B, and authors C. D: The cocitation network map of journals.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/cd923e46d43b283032681237.png"},{"id":81535521,"identity":"7900cec1-1c90-4f28-a50e-8e4e3a01c20b","added_by":"auto","created_at":"2025-04-28 10:09:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1469925,"visible":true,"origin":"","legend":"\u003cp\u003eThe three-field plot. A: The top 20 authors with the highest number of publications and related institutions, countries. B: The associated journals and keywords.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/f958262626152d8901c1a870.png"},{"id":81535525,"identity":"63e2a1ba-ba8c-4aef-b09b-5290f149844c","added_by":"auto","created_at":"2025-04-28 10:09:08","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":881190,"visible":true,"origin":"","legend":"\u003cp\u003eThe citation density map of publications. The shading of colors represents the level of citations for each publication.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/f143c7feb68f96694796a1db.png"},{"id":81535523,"identity":"a55dde7f-aac6-4861-8859-28b71743ee62","added_by":"auto","created_at":"2025-04-28 10:09:08","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":726668,"visible":true,"origin":"","legend":"\u003cp\u003eA: The visualization of the top 10 cocited publications. B The top 15 references with the strongest citation bursts.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/510368daade8c2efd62d8624.png"},{"id":81535519,"identity":"dedf6ccd-0612-43a6-922f-dc065b6f3960","added_by":"auto","created_at":"2025-04-28 10:09:08","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1878129,"visible":true,"origin":"","legend":"\u003cp\u003eThe network A, overlay B, and timeline C map of keyword co-occurrence. D The top 15 keywords with the strongest citation bursts.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/3624f33326fda20db5b5437a.png"},{"id":81537549,"identity":"1a890006-0f56-41c8-93ae-c2136501e992","added_by":"auto","created_at":"2025-04-28 10:33:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12344497,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/27209a02-1f03-43d1-b65b-0ead16129ee6.pdf"},{"id":81536052,"identity":"8d31334d-0783-4a02-a9ce-bfbdaf6a115e","added_by":"auto","created_at":"2025-04-28 10:17:08","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":37167,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1.\u003c/strong\u003e Adjusted number of published publications.\u003c/p\u003e","description":"","filename":"S1.png","url":"https://assets-eu.researchsquare.com/files/rs-5703090/v1/6dcb61bc9d08f162236fe771.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global trends and research status in clonal hematopoiesis: a bibliometric analysis of the last 10 years","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAs individuals age, somatic mutations gradually accumulate in their tissues. While most of these mutations have minimal or no functional impact, some can confer a selective growth advantage to certain cells. In the hematopoietic system, this can result in a large fraction of circulating blood cells being derived from a single mutated hematopoietic stem cells (HSCs), a phenomenon known as Clonal Hematopoiesis (CH). Since the major breakthrough in 2014, CH has become a central topic of interest in both scientific and clinical research [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. CH is primarily driven by a limited set of gene mutations involving epigenetic regulation (DNMT3A, TET2, and ASXL1), signaling pathways (JAK2), RNA splicing (SF3B1 and SRSF2), and DNA damage response (TP53 and PPM1D). Additionally, mosaic chromosomal alterations (mCAs) are also an important mechanism of CH, including amplifications, deletions, and copy-neutral loss of heterozygosity (CNLOH), among others [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. CH becomes more prevalent with age due to the accumulation of mutations at the population level. In healthy individuals under 40, CH is detected in less than 1% of cases, but its prevalence skyrockets to 20% in individuals over 90 years old [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additionally, external factors such as smoking, obesity, infections, and exposure to cancer treatments can further accelerate the progression of CH [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough CH itself is not synonymous with malignancy, many of the commonly CH genes are driver mutations for myeloid tumor and are considered the \u0026ldquo;first hit\u0026rdquo; in hematologic malignant transformation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The presence of CH is associated with a 30\u0026thinsp;~\u0026thinsp;40% increase in overall mortality, which cannot be fully explained by the increased risk of hematologic malignancies. Instead, the primary contributor to this elevated mortality appears to be an increased incidence of cardiovascular diseases (CVD) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Moreover, emerging research has linked CH to a range of age-associated conditions, including type 2 diabetes (T2D), chronic obstructive pulmonary disease (COPD), chronic liver disease, gout, rheumatoid arthritis, and tumors [\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This linkage may be driven by the production of mutated immune effector cells by altered HSCs, resulting in elevated levels of pro-inflammatory factors [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Despite significant progress in CH research in recent years, most existing studies have focused on genetic mutations, clinical phenotypes, and underlying mechanisms. However, a comprehensive analysis of the current state of research, key areas of focus, and global development trends remains notably absent.\u003c/p\u003e \u003cp\u003eBibliometric analysis, as a methodology combining qualitative and quantitative approaches, offers valuable insights into research trends, emerging hotspots, and academic impact by examining the contributions of countries, institutions, authors, and journals [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This study employs bibliometric methods to review the research outputs on CH over the past decade. By mapping the research landscape in this field, we aim to provide new perspectives and directions for future investigations into CH.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eData acquisition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe articles in this study were indexed from the Web of Science Core Collection (WoSCC) database, which contains more than 10,000 journals and is one of the most commonly used and authoritative databases for bibliometric analysis [15]. The search strategy was presented as follows: TS = (“clonal hematopoiesis”) OR (“clonal haematopoiesis”). The publication period was limited to between 2014 and 2024, and the publication type was limited to original articles written in English. Two researchers retrieved and screened the raw data, removing publications unrelated to CH in the title and abstract by screening, and resolved any discrepancies through discussion. A flowchart describing how publications were selected is presented in \u003cstrong\u003eFigure 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe retrieved literature was stored in plain text file formats for further analysis. The following data were extracted from the selected publications: title, authors, institutions, countries, journals (including the 2024 journal impact factor [IF]), publication year, citation counts, and H-index.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBibliometric analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed VOSviewer (version 1.6.20), CiteSpace (version 6.1.6), and R (version 4.3.2) software to generate visualizations. CiteSpace is a powerful tool for identifying and visualizing emerging trends and hotspots in specific research fields. It achieves this through the analysis of citation bursts, co-citation networks, and the temporal evolution of high-frequency keywords [16]. VOSviewer is a bibliometric software tool designed for constructing and visualizing bibliometric networks. In this study, VOSviewer was employed to analyze collaboration networks among countries, institutions, journals, and authors, as well as to identify co-citation relationships and generate keyword overlay visualizations. In these visualizations, each node represents a specific parameter, with node size reflecting the parameter's importance. Different clusters are distinguished by nodes and lines of varying colors, while the thickness of the connecting lines indicates the strength of the relationship between nodes [17].\u003c/p\u003e\n\u003cp\u003eTotal Link Strength (TLS) refers to the sum of the connection strengths between a specific node and all other nodes within the network. It is used to assess the overall influence or centrality of that node within the bibliometric analysis. H-index is a robust metric that evaluates the productivity and impact of authors, countries, institutions, and journals. In this study, we report the H-index of the corresponding author specifically within the field of CH. Finally, we used citation data from the selected papers to detect pairs of articles that were cited by the same references. The co-citation strength between two papers was calculated based on how often they were cited together in the same article. This was done using bibliometric software tools to automate the extraction and analysis of the co-citation relationships.\u003c/p\u003e"},{"header":"3. Result","content":"\u003cp\u003e\u003cstrong\u003eGrowth trend of publications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 851 publications meeting the inclusion criteria were retrieved from the WoSCC database. The annual distribution of publications in the field of CH is presented in \u003cstrong\u003eFigure 2A\u003c/strong\u003e, which reveals a consistent upward trend over the years. When I calibrated the annual total publications, this trend persisted (\u003cstrong\u003esupplementary Figure 1\u003c/strong\u003e). The number of publications reached its peak in 2024, with 182 articles published, accounting for 21.4% of the total output. As shown in \u003cstrong\u003eFigure 2B\u003c/strong\u003e, the cumulative number of publications from 2014 to 2024 has steadily increased, further underscoring the growing academic interest in the field of CH. Between 2017 and 2021, both the citation count (\u003cstrong\u003eFigure 2C\u003c/strong\u003e) and H-index (\u003cstrong\u003eFigure 2D\u003c/strong\u003e) were relatively high, with annual citations consistently exceeding 5,000 and the H-index surpassing 25, indicating significant scholarly impact.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of country/region and institution attributes of the publications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analyzed the publication count, total citations, and H-index of the top ten productive countries. As shown in \u003cstrong\u003eFigure 3\u003c/strong\u003e and \u003cstrong\u003eTable 1\u003c/strong\u003e, the United States of America (USA) leads with 457 publications, accounting for 53.7% of the total output, followed by Germany and England, each with 117 and 88 publications. Moreover, the USA not only dominates in publication output but also excels in academic influence, boasting a total of 33,939 citations and an H-index of 346. As shown in \u003cstrong\u003eFigure 4A\u003c/strong\u003e, the visualization of the international collaboration network among 55 participating countries highlights the USA as the central hub, with the strongest collaboration network (TLS = 439) and the closest ties to China, Germany, the United Kingdom, and Canada.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 4B\u003c/strong\u003e presents the complex collaboration network among institutions, comprising 1591 distinct entities. Harvard Medical School has the most extensive collaboration network with a TLS of 362. Focusing on the top ten productive institutions (\u003cstrong\u003eTable 2\u003c/strong\u003e), all of these institutions are based in the USA. Harvard Medical School ranks first with 99 publications, accounting for 11.6% of the total output. It is followed by Dana-Farber Cancer Institute with 72 publications (8.5%) and Massachusetts General Hospital with 65 publications (7.6%). Additionally, Harvard Medical School stands out with a remarkable citation impact of 9,115 citations and the highest H-index of 129.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of authors of publications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e highlights the top 10 authors with the highest publication output. Benjamin L Ebert ranks first, with 53 publications, accounting for 6.2% of the total, followed by Pradeep Natarajan with 49 publications, and Alexander G Bick with 45. Benjamin L Ebert also demonstrates exceptional citation impact, amassing 3,337 citations and achieving an H-index of 33, underscoring the substantial influence in the field. To visualize the complex collaboration network among these authors, \u003cstrong\u003eFigure 4C\u003c/strong\u003e presents a network map. In this intricate network, Benjamin L Ebert emerges as the most central node, with the highest number of collaborations (TLS = 101).\u003c/p\u003e\n\u003cp\u003eA three-field plot was created to visually represent the top 20 authors with the highest publication output, along with their affiliated institutions, countries, journals, and keywords. Notably, most of these prominent authors are affiliated with Harvard University in the USA. The publications are primarily featured in The New England Journal of Medicine, Blood, and Nature, with keywords predominantly focusing on \u0026ldquo;clonal hematopoiesis\u0026rdquo;, \u0026ldquo;inflammation\u0026rdquo;, \u0026ldquo;aging\u0026rdquo;, \u0026ldquo;atherosclerosis\u0026rdquo; and \u0026ldquo;clonal hematopoiesis of indeterminate potential (CHIP)\u0026rdquo; (\u003cstrong\u003eFigure 5\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of source journals and co-cited journals\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 251 papers published in the top ten journals (\u003cstrong\u003eTable 4\u003c/strong\u003e), accounting for 29.5% of the total publication output, Blood, Blood Advances, and Leukemia are the most prominent journals in this field, with 53, 51, and 30 publications, respectively. Blood leads significantly in both citation count (5,306) and H-index (35), far outperforming Blood Advances (1,174 citations and an H-index of 20) and Leukemia (1,195 citations and an H-index of 19). IF is a key metric for assessing a journal\u0026rsquo;s value and the significance of its publications. Nature holds the highest IF at 50.5, followed by Blood at 21.0 and Cell Stem Cell at 19.8. \u003cstrong\u003eFigure 4D\u003c/strong\u003e illustrates the cocitation network among journals. The top three cocited journals are: Blood (4,258 cocitations), The New England Journal of Medicine (2,553 cocitations), and Nature (2,103 cocitations).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of highly cited studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe top 10 most cited studies are listed in \u003cstrong\u003eTable 5\u003c/strong\u003e. Among these, three originate from Brigham and Women\u0026rsquo;s Hospital in the USA, and two from the Memorial Sloan Kettering Cancer Center. The study by Siddhartha Jaiswal published in 2014 in The New England Journal of Medicine (IF = 96.2), titled \u0026ldquo;Age-related clonal hematopoiesis associated with adverse outcomes\u0026rdquo; has been cited 3,282 times, making it the most cited paper in this field [2]. In terms of research topics, four studies found that CH is common in the elderly and associated with increased risk of blood cancer [1-3, 18, 19]. Two studies analyzed the relationship between CH and anticancer treatments. Kelly L Bolton [20] and Catherine C Coombs et al. [21] contend that cancer therapy shapes the fitness landscape of CH, ultimately leading to adverse clinical outcomes. Furthermore, two studies examined the association between CH and CVD. Siddhartha Jaiswal [22] found that patients with DNMT3A and TET2 mutations have a significantly increased risk of CVD, possibly due to mutated hematopoietic cells driving inflammation by activating the NLRP3 inflammasome [23]. Another study discussed the distinction between CH and Myelodysplastic Syndromes (MDS) [24]. The citation density distribution is shown in\u003cstrong\u003e\u0026nbsp;Figure 6\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of co-cited references\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e lists the top 10 most cocited references and provides a visualization of cocited publications in \u003cstrong\u003eFigure 7A\u003c/strong\u003e. The studies by Siddhartha Jaiswal et al. [2] on age-related CH and its adverse outcomes, and by Giulio Genovese et al. [1] on CH and its risk of blood cancer inferred from blood DNA sequence were cited the most, 530 and 412 times respectively. Among the top 10 cocited papers, three were published in The New England Journal of Medicine (IF = 96.2), two in Blood (IF = 21.0), and one in Nature (IF = 50.5). To further analyze the dynamic changes in citation patterns, we used CiteSpace to identify the top 15 references with the strongest citation bursts. As shown in \u003cstrong\u003eFigure 7B\u003c/strong\u003e, the most significant citation burst was observed for the 2014 paper by Siddhartha Jaiswal et al. [2], followed by the 2014 study by Giulio Genovese et al. [1] published in The New England Journal of Medicine, and the 2014 paper by Mingchao Xie et al. [25] in Nature Medicine. These findings underscore the significant impact and relevance of these publications in the field.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKeyword analysis of research hotspots\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKeyword co-occurrence analysis is a commonly used method to identify trending research topics. The top 10 most frequently used keywords are \u0026ldquo;clonal hematopoiesis\u0026rdquo;, \u0026ldquo;risk\u0026rdquo;, \u0026ldquo;mutations\u0026rdquo;, \u0026ldquo;acute myeloid leukemia\u0026rdquo; (AML), \u0026ldquo;dnmt3a\u0026rdquo;, \u0026ldquo;leukemia\u0026rdquo;, \u0026ldquo;tet2\u0026rdquo;, \u0026ldquo;inflammation\u0026rdquo;, \u0026ldquo;stem cells\u0026rdquo;, and \u0026ldquo;age\u0026rdquo;. Clustering keywords helps delineate the distribution of research themes (\u003cstrong\u003eFigure 8A\u003c/strong\u003e). The largest red cluster contains keywords related to the mutation spectrum of CH, its prevalence, and its association with clinical outcomes, including \u0026ldquo;landscape\u0026rdquo;, \u0026ldquo;prevalence\u0026rdquo;, \u0026ldquo;outcomes\u0026rdquo;, and \u0026ldquo;prognosis\u0026rdquo;. The green cluster focuses on the relationship between CH and CVD, with keywords like \u0026ldquo;atherosclerosis\u0026rdquo;, \u0026ldquo;heart failure\u0026rdquo;, \u0026ldquo;inflammation\u0026rdquo;, \u0026ldquo;dnmt3a\u0026rdquo;, and \u0026ldquo;tet2\u0026rdquo;. The blue cluster primarily investigates the mechanisms of CH in hematopoietic stem cells, with keywords like \u0026ldquo;dna methylation\u0026rdquo;, \u0026ldquo;hematopoietic stem cell\u0026rdquo;, and \u0026ldquo;self-renewal\u0026rdquo;. As shown in \u003cstrong\u003eFigure 8B\u003c/strong\u003e, keywords such as \u0026ldquo;acute myeloid leukemia\u0026rdquo;, \u0026ldquo;genes\u0026rdquo;, \u0026ldquo;hematopoietic stem cells\u0026rdquo; and \u0026ldquo;evolution\u0026rdquo; represent key topics from earlier studies. In contrast, current research hotspots are characterized by keywords like \u0026ldquo;heart failure\u0026rdquo;, \u0026ldquo;inflammation\u0026rdquo;, \u0026ldquo;atherosclerosis\u0026rdquo; and \u0026ldquo;clonal hematopoiesis of indeterminate potential\u0026rdquo; (CHIP).\u003c/p\u003e\n\u003cp\u003eThe keyword evolution depicted in \u003cstrong\u003eFigure 8C\u003c/strong\u003e reveals the changing research interests over time. In 2014, the focus was primarily on CH-related genes and their association with myeloid malignancies, including \u0026ldquo;acute myeloid leukemia\u0026rdquo;, \u0026ldquo;myelodysplastic syndromes\u0026rdquo;, \u0026ldquo;mutations\u0026rdquo;, \u0026ldquo;tet2\u0026rdquo;, and \u0026ldquo;dnmt3a\u0026rdquo;. From 2014 to 2020, interest in the relationship between CH and cardiovascular diseases surged, with keywords such as \u0026ldquo;atherosclerosis\u0026rdquo;, \u0026ldquo;heart failure\u0026rdquo;, and \u0026ldquo;inflammation\u0026rdquo; emerging prominently. In addition, studies on tp53 and jak2 mutants are increasing. After 2020, attention shifted toward the clinical significance and mechanisms of CH. The burst intensity of keywords as shown in \u003cstrong\u003eFigure 8D\u003c/strong\u003e, offers valuable insights into the dynamism and emerging trends of research frontiers. Among the top 15 keywords with the highest burst intensity, \u0026ldquo;acute myeloid leukemia\u0026rdquo; stands out with the strongest recent burst, underscoring its significant implications. Additionally, the sustained bursts of \u0026ldquo;dynamics\u0026rdquo; and \u0026ldquo;landscape\u0026rdquo; in 2024 emphasize their continued relevance as critical and enduring research topics.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this is the first comprehensive bibliometric analysis of publications related to CH. Our findings reveal a consistent upward trend in the annual number of publications in this field. Notably, 2024 stands out as a pivotal year, with the highest number of publications. The period from 2017 to 2021 exhibited significant academic impact, as reflected by high citation counts and H-index. The observed decline in citation counts and H-index over the past three years may be attributed to the proximity of the data collection period.\u003c/p\u003e\n\u003cp\u003eThe analysis encompassed the most influential countries, institutions, authors, and journals within the field. The results indicate that the USA dominates this area of research, as evidenced by its extensive international collaborations, the highest number of publications, the most citations, and the highest H-index. All of the top ten research institutions are based in the USA, with Harvard Medical School recognized as the most impactful institution in this field. Benjamin L Ebert has established a central role in the study of CH through his long-standing focus on its molecular mechanisms and implications in disease. However, many of studies are the result of collaborative efforts within research teams, which may not be fully reflected in the bibliometric analysis. Blood, Blood Advances, and Leukemia are considered the leading journals in this domain, with Blood ranking first in terms of publication count, citations, and H-index, underscoring the strong connection between CH and hematological diseases. Additionally, Blood, The New England Journal of Medicine, and Nature rank as the top three cocited journals, reflecting the breadth and significance of CH research in these publications.\u003c/p\u003e\n\u003cp\u003eIn addition, we examined the top 10 most cited publications, widely regarded as the most impactful and significant contributions to the field.\u0026nbsp;In 2014, Siddhartha Jaiswal [2] and Giulio Genovese [1] performed DNA exome sequencing on a large cohort and found that somatic mutations associated with CH increase with age, correlating with higher risks of hematologic cancers, all-cause mortality, and CVD, laying the foundation for subsequent CH research. Andrew L Young further confirmed that CH-related mutations are widespread in healthy adults [19]. David P Steensma [24] explored the nature and prevalence of CHIP and differentiated it from myelodysplastic syndromes (MDS). Florian Zink [18] developed a method to identify individuals with CH based on the accumulation of somatic mutations in the dominant HSC clone. Alexander G. Bick [3] observed that germline genetic variation shapes HSCs function leading to CHIP through mechanisms that are both specific to CH and shared mechanisms leading to somatic mutations across tissues. CH is also associated with an increased risk of atherosclerotic cardiovascular disease, potentially through mechanisms involving TET2-deficient macrophages and NLRP3 inflammasome-mediated IL-1\u0026beta; secretion [22, 23]. Kelly L. Bolton [20] and Catherine C. Coombs\u0026apos; study [21] found that cancer treatments shape the landscape of CH. Cancer therapies such as radiotherapy, platinum-based drugs, and topoisomerase II inhibitors preferentially select for mutations in DNA damage response genes (e.g., TP53, PPM1D, CHEK2), ultimately leading to poor prognosis.\u003c/p\u003e\n\u003cp\u003eKeyword analysis revealed that the most frequently appearing terms included \u0026ldquo;CH\u0026rdquo;, \u0026ldquo;mutation\u0026rdquo;, and \u0026ldquo;risk\u0026rdquo;, indicating that CH-related genetic mutations and their association with disease risk are the most widely studied areas in this field. CH involves mutations in 74 driver genes, the majority of which overlap with those implicated in AML. Mutations in TET2, DNMT3A, and ASXL1 are the most prevalent, collectively representing over 75% of cases. Meanwhile, mutations in PPM1D, JAK2, SF3B1, SRSF2, and TP53 account for an additional 15% [3, 26]. Recent studies analyzing whole-blood exome data from 200,618 individuals in the UK Biobank have identified 17 novel genes whose mutations are comparable in impact to classic CH drivers [27]. In addition, the disease most closely associated with CH has been hematologic malignancies (HR: 12.9; 95% CI: 5.8-28.7). Approximately 42% of hematologic cancers already harbor CH mutations in DNA sampled more than six months before diagnosis [1]. Although the relative risk of myeloid malignancies is increased, the absolute risk remains low, with the malignant transformation rate of CH estimated at 0.5~1% annually. The risk of progression to myeloid malignancies depends on specific molecular and hematologic features. DNMT3A mutation has the lowest progression risk, whereas TP53, IDH1, IDH2, or RUNX1 mutation carries the highest risk of evolving into myeloid malignancies [28].\u003c/p\u003e\n\u003cp\u003eIn the overlay and timeline map from the bibliometric analysis, keywords related to myeloid tumor appeared earlier, while CVD and inflammation have emerged as recent research hotspots. In nested case-control analyses from two prospective cohorts, individuals with CH were found to have a 1.9-fold increased risk of coronary heart disease compared to non-carriers [22]. Soichi Sano et al. [29] demonstrated that TET2-mediated CH accelerates heart failure progression via activation of the IL-1\u0026beta;/NLRP3 inflammasome pathway. This finding suggests a novel therapeutic direction for heart failure, aiming to mitigate its progression by inhibiting NLRP3 inflammasome activation. Moreover, NLRP3 inflammasome activation and increased IL-1\u0026beta; secretion driven by TET2 mutations have also been implicated in heightened susceptibility to atherosclerosis and atrial fibrillation [23, 30]. Isidoro Cobo et al.\u0026nbsp;[31]\u0026nbsp;revealed that loss of function in DNMT3A or TET2 impairs mitochondrial DNA integrity and activates cGAS signaling, leading to a type I interferon response, which elevates the risk of CVD. Using CRISPR technology to introduce DNMT3A mutations into murine HSCs, researchers observed exacerbated cardiac dysfunction and fibrosis following heart failure, driven by the upregulation of inflammatory mediators such as CXCL1, CXCL2, IL-6, and CCL5\u0026nbsp;[32]. Furthermore, heart failure patients harboring DNMT3A mediated CH exhibit a highly inflammatory transcriptomic profile in circulating monocytes and T cells, potentially contributing to the worsening of chronic heart failure\u0026nbsp;[33]. DNMT3A or TET2 mutations have been significantly associated with poorer prognoses in CVD patients, likely due to elevated levels of inflammatory cytokines\u0026nbsp;[34].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe bibliometric analysis in this study primarily highlights the association between CH and its mediation of myeloid malignancies and cardiovascular diseases. However, recent studies suggest that CH is closely linked to various age-related diseases. Waihay J Wong et al. [8] found that CH patients are more likely to develop liver inflammation and fibrosis (OR = 1.74), driven by elevated inflammatory cytokines in TET2-deficient macrophages. CH is also associated with a higher incidence of gout (OR = 1.69, 95% CI: 1.09-2.61), likely due to increased IL-1\u0026beta; levels [9]. CH carriers face a 1.6- to 2.2-fold higher risk of moderate-to-severe and severe COPD, respectively [35], and a 23% increased risk of T2D. Among CH mutations, TET2 (HR = 1.48) and ASXL1 (HR = 1.76) confer the greatest risk, while DNMT3A mutations are not statistically significant (HR = 1.15) [36]. DNMT3A-mediated CH promotes IL-20 expression via the Irf3-NF-\u0026kappa;B pathway, driving osteoclast differentiation and ultimately leading to osteoporosis [37]. CH is also linked to the development of solid tumors. Ruiyi Tian et al. [38] reported that CH increases lung cancer risk (cases: 12.5% vs. controls: 8.7%; OR = 1.36, 95% CI: 1.06-1.74). Yongliang Zhang et al. [39] analyzed over 10,000 Chinese pan-cancer patients and found that 14% of plasma cell-free DNA samples harbored CH mutations, with detectability increasing with age. However, these studies have not been fully reflected in the bibliometric analysis, likely due to the relatively limited number and their more recent publication dates. Bibliometric analysis provides a novel and objective perspective on the development of hotspots and trends in CH research. In our analysis, we primarily focused on research related to CHIP, as studies involving CHIP genes have dominated the field of CH. This focus is reflected in the majority of our top hits from the bibliometric analysis. However, other subtypes of CH, such as mCAs, are lacking in our analysis, which reflects the current bias in the field. Moreover, this study has certain limitations in its methodology. The data were extracted exclusively from the WoSCC database, which may have led to the omission of relevant information from other sources. Additionally, this study included only English-language publications, which may overlook research from non-English-speaking countries or regions, thus limiting a comprehensive understanding of global research trends. Due to the novelty of the research topic and strict selection criteria, the number of included studies is relatively small, which may limit the robustness of the conclusions and the ability to capture the full scope of the field.\u003c/p\u003e\n\u003cp\u003eIn conclusion, the past decade has seen significant growth in research exploring the role of CH in various diseases, prompting us to select a comprehensive range of relevant publications from 2014 to 2024 for our study. By utilizing various statistical software programs, we performed a detailed bibliometric analysis to obtain a comprehensive overview of the advancements in understanding CH and its implications. Our analysis examined publication characteristics, identifying the most influential nations, institutions, authors, and journals, while also highlighting key research hotspots, emerging trends, and potential directions for future research. This has strengthened the understanding of CH and its related diseases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFinancial support:\u0026nbsp;\u003c/strong\u003eThis research was funded by the National Natural Science Foundation of China (82260043), the Natural Science Foundation of Jiangxi Province (20232ACB206016, 20204BCJ22030) and the Major Discipline Academic and Technical Leaders Training Program of Jiangxi Province (20225BCJ22001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eQingQing Luo and Li Yu designed the study, QingQing Luo collected the data, performed the analysis, and wrote the initial draft. All authors reviewed and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval statement:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent statement:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eAll data are contained within the manuscript and its additional files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGenovese G, K\u0026auml;hler AK, Handsaker RE, Lindberg J, Rose SA, Bakhoum SF, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med. 2014;371(26):2477-87. doi: 10.1056/NEJMoa1409405. PubMed PMID: 25426838.\u003c/li\u003e\n\u003cli\u003eJaiswal S, Fontanillas P, Flannick J, Manning A, Grauman PV, Mar BG, et al. Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med. 2014;371(26):2488-98. doi: 10.1056/NEJMoa1408617. PubMed PMID: 25426837.\u003c/li\u003e\n\u003cli\u003eBick AG, Weinstock JS, Nandakumar SK, Fulco CP, Bao EL, Zekavat SM, et al. Inherited causes of clonal haematopoiesis in 97,691 whole genomes. Nature. 2020;586(7831):763-8. doi: 10.1038/s41586-020-2819-2. PubMed PMID: 33057201.\u003c/li\u003e\n\u003cli\u003eVlasschaert C, Mack T, Heimlich JB, Niroula A, Uddin MM, Weinstock J, et al. A practical approach to curate clonal hematopoiesis of indeterminate potential in human genetic data sets. Blood. 2023;141(18):2214-23. doi: 10.1182/blood.2022018825. PubMed PMID: 36652671.\u003c/li\u003e\n\u003cli\u003eDunn WG, McLoughlin MA, Vassiliou GS. Clonal hematopoiesis and hematological malignancy. J Clin Invest. 2024;134(19). doi: 10.1172/JCI180065. PubMed PMID: 39352393.\u003c/li\u003e\n\u003cli\u003eOren O, Small AM, Libby P. Clonal hematopoiesis and atherosclerosis. J Clin Invest. 2024;134(19). doi: 10.1172/JCI180066. PubMed PMID: 39352379.\u003c/li\u003e\n\u003cli\u003eJaiswal S. Clonal hematopoiesis and nonhematologic disorders. Blood. 2020;136(14):1606-14. doi: 10.1182/blood.2019000989. PubMed PMID: 32736379.\u003c/li\u003e\n\u003cli\u003eWong WJ, Emdin C, Bick AG, Zekavat SM, Niroula A, Pirruccello JP, et al. Clonal haematopoiesis and risk of chronic liver disease. Nature. 2023;616(7958):747-54. doi: 10.1038/s41586-023-05857-4. PubMed PMID: 37046084.\u003c/li\u003e\n\u003cli\u003eAgrawal M, Niroula A, Cunin P, McConkey M, Shkolnik V, Kim PG, et al. TET2-mutant clonal hematopoiesis and risk of gout. Blood. 2022;140(10):1094-103. doi: 10.1182/blood.2022015384. PubMed PMID: 35714308.\u003c/li\u003e\n\u003cli\u003eSavola P, Lundgren S, Ker\u0026auml;nen MAI, Almusa H, Ellonen P, Leirisalo-Repo M, et al. Clonal hematopoiesis in patients with rheumatoid arthritis. Blood Cancer J. 2018;8(8):69. doi: 10.1038/s41408-018-0107-2. PubMed PMID: 30061683.\u003c/li\u003e\n\u003cli\u003eLiu X, Sato N, Shimosato Y, Wang T-W, Denda T, Chang Y-H, et al. CHIP-associated mutant ASXL1 in blood cells promotes solid tumor progression. Cancer Sci. 2022;113(4):1182-94. doi: 10.1111/cas.15294. PubMed PMID: 35133065.\u003c/li\u003e\n\u003cli\u003eAvagyan S, Henninger JE, Mannherz WP, Mistry M, Yoon J, Yang S, et al. Resistance to inflammation underlies enhanced fitness in clonal hematopoiesis. Science. 2021;374(6568):768-72. doi: 10.1126/science.aba9304. PubMed PMID: 34735227.\u003c/li\u003e\n\u003cli\u003eNinkov A, Frank JR, Maggio LA. Bibliometrics: Methods for studying academic publishing. Perspect Med Educ. 2022;11(3):173-6. doi: 10.1007/s40037-021-00695-4. PubMed PMID: 34914027.\u003c/li\u003e\n\u003cli\u003eZhang J, Song L, Xu L, Fan Y, Wang T, Tian W, et al. Knowledge Domain and Emerging Trends in Ferroptosis Research: A Bibliometric and Knowledge-Map Analysis. Front Oncol. 2021;11:686726. doi: 10.3389/fonc.2021.686726. PubMed PMID: 34150654.\u003c/li\u003e\n\u003cli\u003eJiang S, Liu Y, Zheng H, Zhang L, Zhao H, Sang X, et al. Evolutionary patterns and research frontiers in neoadjuvant immunotherapy: a bibliometric analysis. Int J Surg. 2023;109(9):2774-83. doi: 10.1097/JS9.0000000000000492. PubMed PMID: 37216225.\u003c/li\u003e\n\u003cli\u003eYuan X, Lai Y. Bibliometric and visualized analysis of elite controllers based on CiteSpace: landscapes, hotspots, and frontiers. Front Cell Infect Microbiol. 2023;13:1147265. doi: 10.3389/fcimb.2023.1147265. PubMed PMID: 37124043.\u003c/li\u003e\n\u003cli\u003evan Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010;84(2):523-38. PubMed PMID: 20585380.\u003c/li\u003e\n\u003cli\u003eZink F, Stacey SN, Norddahl GL, Frigge ML, Magnusson OT, Jonsdottir I, et al. Clonal hematopoiesis, with and without candidate driver mutations, is common in the elderly. Blood. 2017;130(6):742-52. doi: 10.1182/blood-2017-02-769869. PubMed PMID: 28483762.\u003c/li\u003e\n\u003cli\u003eYoung AL, Challen GA, Birmann BM, Druley TE. Clonal haematopoiesis harbouring AML-associated mutations is ubiquitous in healthy adults. Nat Commun. 2016;7:12484. doi: 10.1038/ncomms12484. PubMed PMID: 27546487.\u003c/li\u003e\n\u003cli\u003eBolton KL, Ptashkin RN, Gao T, Braunstein L, Devlin SM, Kelly D, et al. Cancer therapy shapes the fitness landscape of clonal hematopoiesis. Nat Genet. 2020;52(11):1219-26. doi: 10.1038/s41588-020-00710-0. PubMed PMID: 33106634.\u003c/li\u003e\n\u003cli\u003eCoombs CC, Zehir A, Devlin SM, Kishtagari A, Syed A, Jonsson P, et al. Therapy-Related Clonal Hematopoiesis in Patients with Non-hematologic Cancers Is Common and Associated with Adverse Clinical Outcomes. Cell Stem Cell. 2017;21(3). doi: 10.1016/j.stem.2017.07.010. PubMed PMID: 28803919.\u003c/li\u003e\n\u003cli\u003eJaiswal S, Natarajan P, Silver AJ, Gibson CJ, Bick AG, Shvartz E, et al. Clonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease. N Engl J Med. 2017;377(2):111-21. doi: 10.1056/NEJMoa1701719. PubMed PMID: 28636844.\u003c/li\u003e\n\u003cli\u003eFuster JJ, MacLauchlan S, Zuriaga MA, Polackal MN, Ostriker AC, Chakraborty R, et al. Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice. Science. 2017;355(6327):842-7. doi: 10.1126/science.aag1381. PubMed PMID: 28104796.\u003c/li\u003e\n\u003cli\u003eSteensma DP, Bejar R, Jaiswal S, Lindsley RC, Sekeres MA, Hasserjian RP, et al. Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood. 2015;126(1). doi: 10.1182/blood-2015-03-631747. PubMed PMID: 25931582.\u003c/li\u003e\n\u003cli\u003eXie M, Lu C, Wang J, McLellan MD, Johnson KJ, Wendl MC, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med. 2014;20(12):1472-8. doi: 10.1038/nm.3733. PubMed PMID: 25326804.\u003c/li\u003e\n\u003cli\u003eKhoury JD, Solary E, Abla O, Akkari Y, Alaggio R, Apperley JF, et al. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms. Leukemia. 2022;36(7):1703-19. doi: 10.1038/s41375-022-01613-1. PubMed PMID: 35732831.\u003c/li\u003e\n\u003cli\u003eBernstein N, Spencer Chapman M, Nyamondo K, Chen Z, Williams N, Mitchell E, et al. Analysis of somatic mutations in whole blood from 200,618 individuals identifies pervasive positive selection and novel drivers of clonal hematopoiesis. Nat Genet. 2024;56(6):1147-55. doi: 10.1038/s41588-024-01755-1. PubMed PMID: 38744975.\u003c/li\u003e\n\u003cli\u003eWeeks LD, Ebert BL. Causes and consequences of clonal hematopoiesis. Blood. 2023;142(26):2235-46. doi: 10.1182/blood.2023022222. PubMed PMID: 37931207.\u003c/li\u003e\n\u003cli\u003eSano S, Oshima K, Wang Y, MacLauchlan S, Katanasaka Y, Sano M, et al. Tet2-Mediated Clonal Hematopoiesis Accelerates Heart Failure Through a Mechanism Involving the IL-1\u0026beta;/NLRP3 Inflammasome. J Am Coll Cardiol. 2018;71(8):875-86. doi: 10.1016/j.jacc.2017.12.037. PubMed PMID: 29471939.\u003c/li\u003e\n\u003cli\u003eLin AE, Bapat AC, Xiao L, Niroula A, Ye J, Wong WJ, et al. Clonal Hematopoiesis of Indeterminate Potential With Loss of Tet2 Enhances Risk for Atrial Fibrillation Through Nlrp3 Inflammasome Activation. Circulation. 2024;149(18):1419-34. doi: 10.1161/CIRCULATIONAHA.123.065597. PubMed PMID: 38357791.\u003c/li\u003e\n\u003cli\u003eCobo I, Tanaka TN, Chandra Mangalhara K, Lana A, Yeang C, Han C, et al. DNA methyltransferase 3 alpha and TET methylcytosine dioxygenase 2 restrain mitochondrial DNA-mediated interferon signaling in macrophages. Immunity. 2022;55(8). doi: 10.1016/j.immuni.2022.06.022. PubMed PMID: 35931086.\u003c/li\u003e\n\u003cli\u003eSano S, Oshima K, Wang Y, Katanasaka Y, Sano M, Walsh K. CRISPR-Mediated Gene Editing to Assess the Roles of Tet2 and Dnmt3a in Clonal Hematopoiesis and Cardiovascular Disease. Circ Res. 2018;123(3):335-41. doi: 10.1161/CIRCRESAHA.118.313225. PubMed PMID: 29728415.\u003c/li\u003e\n\u003cli\u003eAbplanalp WT, Cremer S, John D, Hoffmann J, Schuhmacher B, Merten M, et al. Clonal Hematopoiesis-Driver DNMT3A Mutations Alter Immune Cells in Heart Failure. Circ Res. 2021;128(2):216-28. doi: 10.1161/CIRCRESAHA.120.317104. PubMed PMID: 33155517.\u003c/li\u003e\n\u003cli\u003eWang S, Hu S, Luo X, Bao X, Li J, Liu M, et al. Prevalence and prognostic significance of DNMT3A- and TET2- clonal haematopoiesis-driver mutations in patients presenting with ST-segment elevation myocardial infarction. EBioMedicine. 2022;78:103964. doi: 10.1016/j.ebiom.2022.103964. PubMed PMID: 35339897.\u003c/li\u003e\n\u003cli\u003eMiller PG, Qiao D, Rojas-Quintero J, Honigberg MC, Sperling AS, Gibson CJ, et al. Association of clonal hematopoiesis with chronic obstructive pulmonary disease. Blood. 2022;139(3):357-68. doi: 10.1182/blood.2021013531. PubMed PMID: 34855941.\u003c/li\u003e\n\u003cli\u003eTobias DK, Manning AK, Wessel J, Raghavan S, Westerman KE, Bick AG, et al. Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk. Diabetes Care. 2023;46(11):1978-85. doi: 10.2337/dc23-0805. PubMed PMID: 37756531.\u003c/li\u003e\n\u003cli\u003eKim PG, Niroula A, Shkolnik V, McConkey M, Lin AE, Słabicki M, et al. Dnmt3a-mutated clonal hematopoiesis promotes osteoporosis. J Exp Med. 2021;218(12). doi: 10.1084/jem.20211872. PubMed PMID: 34698806.\u003c/li\u003e\n\u003cli\u003eTian R, Wiley B, Liu J, Zong X, Truong B, Zhao S, et al. Clonal Hematopoiesis and Risk of Incident Lung Cancer. J Clin Oncol. 2023;41(7):1423-33. doi: 10.1200/JCO.22.00857. PubMed PMID: 36480766.\u003c/li\u003e\n\u003cli\u003eZhang Y, Yao Y, Xu Y, Li L, Gong Y, Zhang K, et al. Pan-cancer circulating tumor DNA detection in over 10,000 Chinese patients. Nat Commun. 2021;12(1):11. doi: 10.1038/s41467-020-20162-8. PubMed PMID: 33397889.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe top 10 most productive countries regarding\u0026nbsp;clonal hematopoiesis research from 2014 to 2024\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCounts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Citation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH-Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e53.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e33939\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e346\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eGermany\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e5473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eEngland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e12015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eCanada\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e3306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eJapan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e3119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eFrance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e1830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eItaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e3882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eSweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e12026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e1432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e6749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe top 10 most productive institution regarding\u0026nbsp;clonal hematopoiesis research from 2014 to 2024\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstitution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCounts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Citation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH-Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eHarvard Medical School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eDana Farber Cancer Institute\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e10618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eMassachusetts General Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e11656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eMemorial Sloan Kettering Cancer Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eBrigham And Women\u0026apos;s Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e12072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eVanderbilt University\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eWashington University\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eStanford University\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eUniversity of texas system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eBroad Institute of MIT and Harvard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe top 10 productive authors regarding\u0026nbsp;clonal hematopoiesis research from 2014 to 2024\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNames\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCounts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Citation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH-Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eBenjamin L Ebert\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e3337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003ePradeep Natarajan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e1452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eAlexander G Bick\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e1140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eRoss L Levine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e1685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eAbhishek Niroula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMd Mesbah Uddin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eChristopher J Gibson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMichael C Honigberg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eSiddhartha Jaiswal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e1947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003ePeter Libby\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e2627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe top 10 most productive journals regarding\u0026nbsp;clonal hematopoiesis research from 2014 to 2024\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"109%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJournals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCounts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Citation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH-Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIF (2024)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eBlood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e5306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e21.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eBlood Advances\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eLeukemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eNature Communications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eExperimental Hematology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eHaematologica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eJCO Precision Oncology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eCell Stem Cell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eHematology-American Society of Hematology Education Program\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 220px;\"\u003e\n \u003cp\u003eNature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e50.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eThe top 10 most cited publications regarding clonal hematopoiesis research from 2014 to 2024\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"718\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTitle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstitution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJournal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCitation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eAge-related clonal hematopoiesis associated with adverse outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBrigham and Women\u0026apos;s Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eSiddhartha Jaiswal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eThe New England journal of medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eClonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eHarvard Medical School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eGiulio Genovese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eThe New England journal of medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2471\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eClonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBrigham and Women\u0026rsquo;s Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eSiddhartha Jaiswal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eThe New England journal of medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eClonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBrigham and Women\u0026apos;s Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eDavid P Steensma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eBlood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1440\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eClonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBoston University School of Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eJos\u0026eacute;\u0026nbsp;J Fuster\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eScience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eTherapy-Related Clonal Hematopoiesis in Patients with Non-hematologic Cancers Is Common and Associated with Adverse Clinical Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eMemorial Sloan Kettering Cancer Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eCatherine C Coombs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;Cell Stem Cell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e569\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eClonal hematopoiesis, with and without candidate driver mutations, is common in the elderly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003edeCODE genetics/AMGEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eFlorian Zink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eBlood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eClonal haematopoiesis harbouring AML-associated mutations is ubiquitous in healthy adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eWashington University School of Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eAndrew L Young\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNature communications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e502\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eCancer therapy shapes the fitness landscape of clonal hematopoiesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;Memorial Sloan Kettering Cancer Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eKelly L Bolton\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNature genetics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003eInherited causes of clonal haematopoiesis in 97,691 whole genomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eMassachusetts General Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eAlexander G Bick\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e366\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 6.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTop 10 co-cited references.\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"718\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTitle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstitution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJournal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCO-Citation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eAge-Related Clonal Hematopoiesis Associated with Adverse Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBrigham and Women\u0026apos;s Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eSiddhartha Jaiswal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eThe New England journal of medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e530\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eClonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eHarvard Medical School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eGiulio Genovese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eThe New England journal of medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e412\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eClonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBrigham and Women\u0026apos;s Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eSiddhartha Jaiswal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eThe New England journal of medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eClonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBrigham and Women\u0026apos;s Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eDavid P Steensma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eBlood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e268\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eClonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBoston University School of Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eJos\u0026eacute;\u0026nbsp;J Fuster\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eScience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eTherapy-Related Clonal Hematopoiesis in Patients with Non-hematologic Cancers Is Common and Associated with Adverse Clinical Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eMemorial Sloan Kettering Cancer Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eCatherine C Coombs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eCell stem cell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eClonal hematopoiesis, with and without candidate driver mutations, is common in the elderly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003edeCODE genetics/AMGEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eFlorian Zink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eBlood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eCancer therapy shapes the fitness landscape of clonal hematopoiesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eMemorial Sloan Kettering Cancer Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eKelly L Bolton\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eNature genetics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eInherited causes of clonal haematopoiesis in 97,691 whole genomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eMassachusetts General Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eAlexander G Bick\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eNature\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eGenetic Interleukin 6 Signaling Deficiency Attenuates Cardiovascular Risk in Clonal Hematopoiesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eMassachusetts General Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eAlexander G Bick\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;Circulation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\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":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Clonal hematopoiesis, Bibliometric, Research trend, Research hotspots, Visualized","lastPublishedDoi":"10.21203/rs.3.rs-5703090/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5703090/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eClonal hematopoiesis (CH) refers to the clonal expansion of hematopoietic stem cells caused by somatic mutations. CH is commonly observed in elderly individuals and is closely associated with myeloid malignancies as well as various non-malignant diseases. This study aims to explore the research trends and hotspots of CH using bibliometric analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eRelevant studies were retrieved from the Web of Science Core Collection database based on predefined inclusion criteria. Bibliometric analysis and visualization were conducted using VOSviewer, CiteSpace, and R software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 851 studies were included. From 2014 to 2024, the annual number of publications showed a consistent upward trend. The United States was identified as the leading country in this field, contributing 53.7% of the total publications. Harvard Medical School and Benjamin L Ebert were recognized as the most influential institution and author, respectively. Blood was the most prolific journal, with the highest citation and H-index. Research on CH-related gene mutations and their association with the risk of acute myeloid leukemia is currently the most extensively studied area, while cardiovascular diseases and inflammation have emerged as recent research hotspots.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This study is the first to systematically analyze research related to CH using bibliometric methods. Our analysis reveals the overall landscape of CH research and identifies the most influential contributors in the field, including countries, institutions, authors, and journals. Moreover, we identify emerging research hotspots and key areas, highlighting potential avenues for exploration and innovation within the field of CH.\u003c/p\u003e","manuscriptTitle":"Global trends and research status in clonal hematopoiesis: a bibliometric analysis of the last 10 years","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 10:09:03","doi":"10.21203/rs.3.rs-5703090/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-04-08T11:16:20+00:00","index":"hide","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-08T09:47:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-28T17:27:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"163910258838576022975355200461221726774","date":"2025-03-27T15:25:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"183663886944566694127715260447523311489","date":"2025-03-27T13:37:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-26T09:17:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6724878097406657006026180900136629065","date":"2025-03-25T08:37:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-25T05:55:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-24T12:16:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2025-02-27T14:21:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"370cf8d2-8bb2-42a0-972b-4e9d3f7053fc","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T10:09:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-28 10:09:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5703090","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5703090","identity":"rs-5703090","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}