Global trends and emerging research hotspots in Alport syndrome: a comprehensive bibliometric analysis (1961–2024)

Introduction

Alport syndrome is an inherited kidney disorder caused by pathogenic variants in type IV collagen genes (COL4A3, COL4A4, and COL4A5), leading to glomerular basement membrane abnormalities and progressive kidney disease (1). Typical manifestations include persistent hematuria, proteinuria, and declining renal function, often accompanied by sensorineural hearing loss and ocular abnormalities (2). X-linked inheritance is the most common form, with autosomal recessive and autosomal dominant forms also reported (1,3). Given its multisystem involvement and variable clinical course, early diagnosis and coordinated care across nephrology, audiology, and ophthalmology are important for long-term outcomes (4-7).

Recent advances, including next-generation sequencing (NGS) for diagnosis and increasing therapeutic research spanning renoprotective strategies and mutation-targeted approaches (8,9), have expanded the Alport syndrome literature (10-12). However, the rapid growth and diversification of publications make it difficult to obtain a structured, quantitative view of how the field is evolving across countries, institutions, collaboration communities, and thematic foci (5).

Bibliometric analysis applies quantitative methods to publication metadata, including authorship, citations, and keyword co-occurrence, to map research structure and identify influential contributors, collaboration patterns, and topics receiving increasing attention over time (13,14). Unlike narrative reviews, bibliometrics is particularly suited to answering “field-level” questions—where evidence is produced, how collaboration networks are organized, and how research themes shift—without making causal claims about biological mechanisms or treatment efficacy.

To date, a comprehensive bibliometric assessment of Alport syndrome research remains limited (15). Therefore, we conducted a bibliometric and visualization analysis to characterize publication trends, collaboration networks, and thematic patterns in Alport syndrome research, and to describe topics showing increased prominence during the study period. We present this article in accordance with the BIBLIO reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0334/rc).

Methods

Search strategies and data collection

A comprehensive bibliometric analysis was conducted utilizing the Web of Science Core Collection (WoSCC), a robust database providing access to high-quality scholarly literature across various disciplines. The search strategy employed the following formula: TS = (“Alport*” NEAR/1 (“Syndrome” OR “Disease” OR “Nephritis”)). This query retrieves records where “Alport” appears within one word of “syndrome”, “disease”, or “nephritis”, thereby improving precision and reducing false positives. All bibliographic data retrieval was completed on January 15, 2025, to minimize discrepancies from database updates. Only English-language records were included to ensure consistency in data extraction and analysis.

Included document types were original research articles; non-article types such as reviews, editorials, letters, conference abstracts, and book chapters were excluded (Figure 1). Duplicate records resulting from overlap between WoSCC indices (e.g., SCI-E, ESCI) were identified and removed prior to analysis. Exported data included full records and cited references in both plain text and WoSCC export formats, capturing journal names, publication years, titles, countries/regions, institutions, authors, keywords, references, and citation counts.

Figure 1 Flowchart of the literature screening process.

Statistical analysis

Three bibliometric tools were used to leverage their complementary strengths. VOSviewer (version 1.6.20) generated high-quality network and density maps, suitable for visually identifying clusters of institutions, authors, and topics (16). CiteSpace (version 6.3.R1) was employed for temporal and evolutionary analyses, detecting citation bursts and emerging research topics over time (17). Bibliometrix (R package, version 4.3.3) was used for detailed quantitative analyses, including collaboration networks, keyword co-occurrence, and cluster detection, providing flexible statistical and visualization options within R (18). Using these tools in combination enabled a comprehensive assessment of both structural relationships and dynamic research trends. For network analyses (e.g., co-authorship, institutional collaboration, and co-citation), thresholds were set to improve interpretability: authors or institutions with a minimum of 8 publications, or journals with at least 4 co-citation links, were included in the respective networks. Network visualizations were constructed using bibliographic coupling and co-occurrence analysis, with research themes clustered via VOSviewer’s built-in algorithm. Temporal evolution was assessed by computing the average publication year of keywords. Emerging trends were identified by detecting keywords with significant citation bursts in recent years. CiteSpace was configured with time slicing at one-year intervals, selection of the top 50 most cited items per slice, and pathfinder network scaling for pruning. Citation burst strength, as calculated by CiteSpace, quantifies the intensity and duration of a sudden increase in citations for a keyword or reference; mathematically, this is based on Kleinberg’s burst detection algorithm, which models frequency changes over time.

Impact metrics including h-index, g-index, and m-index were calculated primarily using bibliometrix (19,20). Full counting was used by default, but fractional counting was applied in VOSviewer for selected analyses to account for co-authorship contributions. CiteSpace analyses used full counting. Self-citations were not excluded from citation metrics. Journal significance was evaluated using Journal Citation Reports (JCR) quartile rankings and Impact Factors (IF) as of the 2023 report (21).

Results

Publication and citation trends analysis

The literature search and screening process, depicted in Figure 1, resulted in the inclusion of 1,637 Alport syndrome-related publications spanning from 1961 to 2024, with an observed annual growth rate of 1.09%. Authorship was distributed across 8,448 individuals, of whom 66 authored single-author papers, with a mean of 7.62 co-authors per document. Notably, international collaboration was substantial, as 23.8% of the publications featured authors from multiple countries. Collectively, these articles cited 24,591 references and used 2,060 unique keywords, reflecting the broad scope of research topics. The average citation count per document was 33.4, indicating a strong citation performance within the field.

The evolution of publication output can be divided into three distinct phases (Figure 2). During the Steady Initiation Phase (1961–1990), research output was limited, with fewer than 10 publications annually and a cumulative total of just 126 by 1990. This was followed by an Explosive Growth Phase beginning in 1991, where the average annual output exceeded 30 publications and cumulative publications more than tripled to 414 by 2002. Since 2003, the Sustained Growth Phase has seen annual publications consistently surpass 40, peaking at 75 in 2020 and reaching 67 in 2024. This trajectory highlights the increasing global interest in Alport syndrome.

Figure 2 Annual publication trends from 1961 to 2024, based on data from the Web of Science Core Collection (WoSCC). The figure depicts the number of publications per year and highlights three distinct phases: initiation (1961–1990), growth (1991–2002), and sustained expansion (2003–2024).

Analysis of countries

Country-level analysis (Table S1 and Figure 3A) reveals that the United States is the leading contributor, accounting for 420 articles (25.7%), followed by China (170; 10.4%) and Japan (162; 9.9%). International collaboration rates vary, with the United States displaying a moderate multi-country publication (MCP) ratio of 0.245, while Finland (MCP = 0.529) and Sweden (MCP = 0.600) demonstrate stronger collaborative engagement. In terms of citation impact, the United States leads with 20,221 citations (average 48.1 per document), followed by Germany (3,930 citations; 39.7 average), while Finland stands out with the highest average citations per document (152.7), reflecting the high impact of its contributions despite lower overall output. The international collaboration network map (Figure 3B) shows the United States at the center of a dense web of global partnerships, particularly with China, Japan, and European countries. Germany (total link strength = 270) and the United Kingdom (total link strength = 237) also emerge as key nodes in international collaboration.

Figure 3 Analysis of countries and institutions involved in Alport syndrome research. (A) Geographic distribution of publications by corresponding authors’ countries. (B) International collaboration network map. Node color = research cluster (community); node size = number of collaborative publications; edge thickness = collaboration strength. Only countries with ≥3 international collaborations are shown. (C) Top ten institutions ranked by total article count. (D) Institutional collaboration network. Node color = research cluster; node size = number of collaborations; edge thickness = collaboration strength. Only institutions with ≥7 international collaborations are labeled.

Analysis of institutions

Institutional analysis further supports this view of thematic and collaborative specialization. Harvard University is the most productive institution, with 168 articles, followed by Université Paris Cité (n=155) and Assistance Publique-Hôpitaux de Paris (n=145) (Figure 3C). Based on publication output (NP), the University of Minnesota ranked first (72 publications), followed by Shigei Medical Research Institute (n=58), Kobe University and Washington University (52 each), and Okayama University (n=50). When impact was assessed using average citations per article (AC), University of Helsinki (AC = 170.15) and Karolinska Institute (AC = 127.42) stood out, despite more modest publication counts, suggesting high citation efficiency (Table S2).

Among the 102 institutions engaged in at least seven international collaborations, the University of Minnesota reported the highest number of international links (n=114), closely followed by Harvard (n=111) and Shigei Medical Research Institute (n=106). Cluster analysis of the institutional collaboration network (Figure 3D) revealed several distinct collaboration communities. Cluster 1 (red) was centered on the University of Minnesota and Harvard University; Cluster 2 (green) included major European institutions (e.g., Université Paris Cité and Assistance Publique-Hôpitaux de Paris); and Cluster 3 (blue) was represented by key Japanese institutions (e.g., Shigei Medical Research Institute and Okayama/Osaka-related nodes). Overall, these patterns indicate stable, clustered partnership structures across regions. In addition to academic and hospital-based institutions, we also identified a small number of industry-affiliated organizations (e.g., Axcelead Drug Discovery Partners and Pfizer-related units) and industry-academia collaborative addresses (e.g., Pfizer/GENYO-related entities) among the retrieved records. However, most industry institutions appeared only once in our dataset and therefore did not meet the minimum occurrence/visualization threshold used for the institutional collaboration network; consequently, they were not prominently displayed.

Analysis of authors

Analysis of author productivity and collaboration further illustrates the multidisciplinary and international nature of Alport syndrome research. Tryggvason K is the most cited author (h-index = 30, 5,750 citations), followed by Sado Y (h-index = 27, 2,834 citations, 46 publications) and Antignac C (h-index = 26, 3,383 citations, 31 publications) (Table S3). Authors such as Gross Oliver and Sado Y lead in total publications, while Tryggvason K demonstrates the highest citation impact per article. The co-authorship network (Figure 4) reveals three main collaborative groups, led by Nozu Kandai, Antignac C, and Tryggvason K, respectively. Notably, Nozu Kandai is the most internationally connected author (total link strength = 244), followed by Iijima Kazumoto (total link strength = 235) and Nakanishi Koichi (total link strength = 186).

Figure 4 Author collaboration network map. Node size is proportional to the number of publications; node color indicates research cluster (as identified by clustering algorithm); edge thickness reflects strength of collaboration. Only authors with ≥8 international collaborations are shown.

Analysis of journals

In journal analysis, Kidney International emerges as the leading publication venue, with 104 articles and 4,655 citations, and boasts the highest IF (14.8, JCR Q1 2023) (Table S4). Pediatric Nephrology (86 articles, IF: 2.6, Q2) and Nephrology Dialysis Transplantation (77 articles, IF: 4.8, Q1) are also prominent. Importantly, the Journal of the American Society of Nephrology (JASN) stands out for its citation efficiency, with 3,006 citations across 63 articles (47.7 citations per article), surpassing even Kidney International (44.8 citations per article) and Nephrology Dialysis Transplantation (39.1 citations per article). Journal network analysis (Figure 5A,5B) confirms Kidney International and JASN as central hubs for both publication and co-citation, with 74 journals demonstrating notable coupling relationships.

Figure 5 Analysis of journals in Alport syndrome research. (A) Co-occurrence network of journals. Node size = number of publications; node color = journal cluster; edge thickness = co-occurrence strength. (B) Coupling network of journals. Node size = number of citations; node color = cluster; edge thickness = coupling strength.

Analysis of keyword occurrences bursts

The keyword analysis revealed “identification” (330 occurrences, total link strength = 1,608) as the most frequent term, followed by “IV collagen” (290 occurrences, total link strength = 1,370), “mutations” (284 occurrences, total link strength = 1,232), “natural history” (160 occurrences, total link strength = 854), and “gene” (175 occurrences, total link strength = 683), reflecting key research focuses in the field (Table S5). The co-occurrence analysis revealed three thematic clusters (Figure 6A): Cluster 1 (Red) focused on genetic mechanisms, featuring “identification”, “IV collagen”, and “mutations”; Cluster 2 (Green) centered on clinical correlations, including “genotype-phenotype”, “natural history”, and “renal failure”; Cluster 3 (Blue) emphasized pathophysiology through “mouse model”, “expression”, and “fibrosis”.

Figure 6 Keyword analysis depicting research trends and emerging themes. (A) Keyword co-occurrence network. Node size = frequency of keyword; node color = thematic cluster (e.g., genetic mechanisms, clinical features, pathophysiology). (B) Overlay visualization of keyword evolution. Node size = frequency. (C) Timeline analysis illustrates the progression of research keywords from early investigations to recent focuses. (D) Citation burst analysis of keywords. Bar lengths represent burst duration and strength. Clustered colors group keywords by theme. A note within the figure highlights three major research phases: foundational genetics (early), clinical correlations (intermediate), and precision medicine/therapeutics (recent).

The overlay visualization (Figure 6B) reveals the temporal progression of research themes. Early studies (2000–2010) predominantly focused on genetic and molecular mechanisms, including “IV collagen”, “mutations”, and “hereditary nephritis”. Over time, there has been a noticeable transition toward clinical applications (e.g., “genotype-phenotype correlations” and “proteinuria”) and therapeutic advancements, including keywords like “guidelines” and “therapy”, which gained prominence after 2018. The thematic timeline analysis (Figure 6C) reveals that research on Alport syndrome has progressed from early genetic and structural investigations (e.g., family inheritance, basement membrane, genetic testing) to more clinically and translationally oriented topics (e.g., chronic kidney disease, monoclonal antibodies). In recent years, emerging themes such as hematuria and blood pressure highlight an increasing emphasis on clinical management and precision medicine.

Citation burst analysis (Figure 6D) identified three research phases: Early (2004–2010) featured “identification” (strength = 8.41), “hereditary nephritis” (strength = 11.34), and “collagen” (strength = 6.36), reflecting foundational genetic studies; Intermediate (2010–2018) highlighted “hematuria” (strength = 5.65), “basement membrane nephropathy” (strength = 12.24), and “renal failure” (strength = 11.03) focusing on disease progression; Recent (2018–2024) emphasized “digenic inheritance” (strength = 5.83), “guidelines” (strength = 8.92), and “ramipril” (strength = 4.88), marking advancements in precision medicine and targeted therapies.

Discussion

This bibliometric analysis provides an overview of the Alport syndrome research landscape by describing how publications are distributed across countries, institutions, journals, and collaboration networks. The steady rise in research output, particularly over the last two decades, likely reflects increasing clinical awareness and advances in molecular diagnostics, as well as broader rare-disease trends that facilitate multicenter research.

Importantly, the primary knowledge gap addressed by this study is not biological mechanism discovery, but evidence-generation structure: where Alport syndrome research is produced, how collaborative communities are organized, and how these structures may shape what clinical evidence becomes available and generalizable—particularly for pediatric populations that require long follow-up. By mapping institutional and international collaboration clusters and linking them to thematic emphases, our findings can support practical study planning (e.g., partner identification for multicenter pediatric cohorts, registry expansion, and endpoint harmonization) rather than making causal claims about clinical effectiveness or policy impact.

Overall summary of the field

Our results identify the United States as the largest contributor to Alport syndrome research. This observation is a bibliometric description of publication concentration rather than proof of superiority in clinical practice (22). The prominence of U.S. output may relate to sustained research funding, the presence of rare-disease infrastructures, and participation in national or international networks such as the NIH Rare Diseases Clinical Research Network (23). The role of top institutions, including Harvard University and the University of Minnesota, is amplified by their capacity for interdisciplinary and multi-institutional collaboration, which is reflected in dense co-authorship and international-link patterns in our network maps. We also note that a small number of industry-affiliated institutions and industry-academia collaborative addresses were present in the WoSCC dataset, consistent with translational interest in therapeutic development for Alport syndrome. Although these industry institutions were low-frequency nodes in our institution-level network under the applied visualization threshold, recent industry-linked studies illustrate active drug discovery and preclinical development efforts in this space (24).

China’s rapid growth in publication output is striking, yet its lower MCP ratio suggests unique policy and language factors at play. While major government investment in biomedical research and the establishment of large genomic centers have fueled output (25), international collaboration is sometimes limited by language barriers and publication preferences for Chinese-language journals. Similar trends are observed in other fast-developing scientific economies, where national priorities may emphasize rapid domestic growth before broader global integration. International collaboration, evidenced by dense North American, European, and Asian networks, remains a cornerstone of progress in this rare disease field. These collaborations facilitate resource sharing, diversify perspectives, and accelerate the adoption of new technologies (26). Importantly, high-impact journals such as Kidney International and the Journal of the American Society of Nephrology serve as critical nodes for disseminating both foundational and translational research (27,28). Citation efficiency analysis confirms that publishing in these journals can amplify the influence of research findings, even for smaller research groups or countries.

Prominent authors such as Tryggvason K and Sado Y have played pivotal roles in shaping the field’s direction. Tryggvason K’s pioneering work on type IV collagen genetics has not only advanced understanding of disease mechanisms but also fostered cross-institutional and international collaborations that have broadened the translational impact of these discoveries (29). These collaborative patterns echo developments in related nephrology fields, where research consortia and patient registries have become the norm for tackling complex, genetically heterogeneous diseases. The role of patient advocacy groups and rare disease consortia is increasingly significant, as they shape research priorities, facilitate data sharing, and support the inclusion of geographically or economically underrepresented populations. Their efforts help bridge gaps in global collaboration and ensure the research agenda aligns with patient needs.

A notable finding is the underrepresentation of low- and middle-income countries in collaborative networks, a trend common to rare disease research globally. Integration of these countries is essential for global health equity and for ensuring that diagnostic and therapeutic advances are accessible worldwide. International rare disease consortia, such as EURORDIS and global patient advocacy groups, are increasingly influential in bridging these gaps by facilitating data sharing, patient recruitment, and advocacy for funding (26). Their coordinated efforts, along with support from funding agencies, are critical for expanding research participation and ensuring that breakthroughs benefit diverse patient populations.

Thematic clusters: trends and context

Cluster 1: genetic and molecular mechanisms

The co-occurrence analysis of keywords identified three major thematic clusters. Among them, foundational research on the genetic and molecular underpinnings of Alport syndrome continues to be a dominant theme, with recurring keywords such as “identification”, “IV collagen”, and “hereditary nephritis” (22). Early gene discovery efforts identified COL4A3, COL4A4, and COL4A5 mutations as causal and highlighted the central role of type IV collagen in glomerular basement membrane integrity (30,31). As in other hereditary nephropathies, molecular characterization has shifted from Sanger sequencing to NGS, greatly improving diagnostic accuracy and revealing more complex inheritance patterns, including digenic inheritance (32,33).

However, bibliometric prominence of genetic keywords should be interpreted descriptively rather than as evidence of clinical translation. The persistence of molecular terms likely reflects ongoing needs in variant interpretation, genotype-phenotype refinement, and functional validation, rather than definitive progress toward routine genotype-guided therapy. Moreover, our bibliometric dataset captures publication and citation patterns, not the quality or completeness of underlying genetic evidence; therefore, any inference about “precision medicine readiness” should be made cautiously.

Emerging therapeutic concepts linked to genetics—such as gene editing, viral gene delivery, and RNA-based approaches—appear in the literature, but most remain preclinical. In this context, exon-skipping using antisense oligonucleotides (ASOs) represents a mutation-specific strategy that is conceptually closer to near-term translation than genome editing for some COL4A5 truncating variants. Preclinical work has shown that ASO-mediated exon skipping can partially restore collagen IV chain expression and ameliorate disease phenotypes in Alport models (34). Importantly, recent experimental designs have also explored inducible/post-onset settings, suggesting that exon-skipping may retain benefit even when initiated after disease onset, a scenario more consistent with real-world diagnosis timing (24).

Cluster 2: clinical features and genotype-phenotype correlations

The second cluster revolves around clinical features, disease progression, and genotype-phenotype correlations. The variability in disease severity and renal outcomes, even among patients with the same mutation, underscores the complexity of the syndrome. Recent research has begun to unravel the prognostic value of specific genetic variants, as well as the early role of biomarkers such as HMGB1 and TGF-β1 in predicting disease progression (8,9). The strong gender effect in X-linked Alport syndrome, where males typically experience more rapid progression to ESRD, mirrors findings in other sex-linked nephropathies (5). From a treatment perspective, our bibliometric findings primarily indicate sustained attention to renoprotective management rather than proving therapeutic effectiveness. RAAS blockade (ACE inhibitors/ARBs) remains a cornerstone of current care and frequently appears across clinical keyword and citation landscapes (12). Beyond conventional RAAS inhibition, newer antiproteinuric strategies are increasingly discussed in the broader CKD/glomerular disease field. One example is sparsentan, a dual endothelin-angiotensin receptor antagonist that has shown strong antiproteinuric effects in proteinuric kidney diseases and is being considered as a potential next-generation option for Alport syndrome-related proteinuria where appropriate evidence emerges (35).

Cluster 3: animal models and pathophysiology

Animal models, particularly genetically engineered mouse models, remain central for studying glomerular basement membrane abnormalities, fibrotic pathways (e.g., TGF-β and Wnt/β-catenin), and progression to kidney failure (8,9,30,31). These platforms support preclinical testing of RAAS blockade and anti-fibrotic concepts, but positive preclinical signals do not necessarily predict clinical benefit (36). The field has also adopted advanced systems such as patient-derived iPSCs and organ-on-chip approaches (37), which may improve mechanistic resolution. Nevertheless, current models may not fully reproduce human heterogeneity and extra-renal disease, highlighting a continuing need for complementary experimental and clinical datasets.

Future hotspots: integrating complex genetic mechanisms and clinical translation

Our citation burst analysis highlights several emerging hotspots: complex inheritance mechanisms (such as digenic or polygenic inheritance), new clinical guidelines, and the move toward precision medicine. The identification of digenic inheritance—mutations in two COL4 genes within the same patient—has challenged traditional diagnostic paradigms and revealed the need for comprehensive genetic screening and nuanced clinical counseling (33,38,39). Here, bibliometric “hotspots” should be interpreted as shifts in research focus and discourse, not as confirmation that these approaches have already improved outcomes.

The recent prominence of the keyword “guidelines” likely reflects maturation of consensus around diagnosis and management pathways (6). Rather than claiming policy impact, we interpret this as evidence that the field is increasingly standardizing terminology and clinical workflows. Future progress toward clinically actionable precision medicine will require prospective cohorts, registries, and studies that link genotype, interventions, and patient-centered outcomes.

Although kidney outcomes dominate the literature, sensorineural hearing loss is a major contributor to morbidity and quality-of-life impairment in Alport syndrome. Current management is largely supportive, relying on early screening, audiology follow-up, and timely hearing-aid fitting; cochlear implantation is considered in selected cases when indicated (23). The absence of disease-specific pharmacologic therapies for hearing loss remains an unmet need, and future translational work should evaluate whether emerging molecular interventions that target the underlying collagen IV defect can modify auditory outcomes.

Anemia is a common and clinically meaningful complication as kidney function declines, contributing to fatigue, reduced exercise tolerance, and overall disease burden. While anemia is not specific to Alport syndrome, it is relevant for comprehensive care in patients who progress to CKD stages where erythropoiesis becomes impaired. Management generally follows CKD anemia principles (evaluation of iron status, iron supplementation when indicated, and use of erythropoiesis-stimulating agents or newer agents per guideline-based indications). Because our bibliometric approach prioritizes Alport-specific keywords, anemia-related care may be underrepresented despite its clinical importance, and future reviews could integrate complication-focused perspectives alongside genotype and nephroprotection.

Limitations

Several limitations of this bibliometric analysis should be acknowledged. First, the exclusive reliance on the WoSCC may have excluded relevant publications indexed in other databases (e.g., Scopus, PubMed, Embase), resulting in potential database coverage bias. Given WoSCC’s standardized citation indexing and its compatibility with VOSviewer and CiteSpace, we selected WoSCC as the primary data source to ensure data consistency, reproducibility, and tool compatibility. However, this choice may bias results toward journals preferentially indexed by WoSCC and may alter country/institution rankings, co-citation patterns, and collaboration networks, particularly for regions or disciplines that are better covered elsewhere. Second, restricting the analysis to English-language articles introduces language bias. This restriction may systematically underrepresent research outputs from non-English-speaking countries and regional journals, thereby potentially underestimating their productivity, thematic contributions, and international collaboration profiles. Third, we limited inclusion to original research articles to maintain a relatively homogeneous document set for quantitative comparison. However, excluding non-article document types (e.g., reviews, guidelines/consensus statements, editorials/letters, conference proceedings, and preprints) may reduce the visibility of rapidly emerging or practice-shaping evidence. In particular, omitting conference proceedings may lead to under-capture of early-stage or frontier research, and excluding highly cited secondary publications may affect citation-based indicators and co-citation structures. Fourth, citation-based indicators can be influenced by self-citations and field-specific citation practices; in addition, excluding non-article document types may alter the visibility of high-impact secondary publications (e.g., guidelines, consensus statements, and reviews), which often accumulate citations faster than original articles. Fifth, while bibliometric analyses provide quantitative insights, they do not capture qualitative dimensions such as methodological rigor, clinical impact, or patient-centered outcomes. Sixth, bibliometric maps and network analyses reflect associations and structural patterns but cannot establish causation or the underlying drivers of research trends. Seventh, our reliance on automated filtering, while ensuring reproducibility, may have allowed the inclusion of a small number of irrelevant records. Finally, the temporal cutoff (1961–2024) may not fully capture the most recent therapeutic advances (e.g., gene editing or RNA-based interventions), which are rapidly evolving. Future work should incorporate multi-database searches where feasible, include non-English literature, consider sensitivity analyses for self-citation, and integrate advanced text-mining and/or qualitative review to more fully characterize the evolving Alport syndrome research landscape.

Conclusions

This bibliometric analysis demonstrates that research on Alport syndrome has not only grown steadily over the past six decades but has also become increasingly globalized and interdisciplinary. However, collaboration networks remain uneven—future efforts should specifically target the integration of low- and middle-income countries and encourage cross-continental partnerships, especially between Asian, European, and North American research groups. The analysis also highlights a persistent translational gap between genetic discoveries and their implementation in clinical care. To address this, the research community should prioritize large-scale, multiethnic cohort studies, investment in functional validation of genetic variants, and the development of mutation-specific therapeutic strategies. For clinicians, these findings underscore the importance of staying current with evolving genetic testing guidelines and incorporating comprehensive genetic screening—including consideration of digenic inheritance—into diagnostic and management pathways. Moving forward, funding agencies and professional societies should use bibliometric trends to strategically support underexplored research themes (such as long-term patient outcomes, new therapeutic approaches, and health equity initiatives) and to facilitate the dissemination and uptake of evidence-based clinical guidelines.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0334/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0334/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0334/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Savige J. Alport syndrome: an update. Curr Opin Nephrol Hypertens 2025;34:206-11. [Crossref] [PubMed]
2. Reiterová J, Tesař V. Current and Future Therapeutical Options in Alport Syndrome. Int J Mol Sci 2023;24:5522. [Crossref] [PubMed]
3. Torra R, Lipska-Zietkiewicz B, Acke F, et al. Diagnosis, management and treatment of the Alport syndrome - 2024 guideline on behalf of ERKNet, ERA and ESPN. Nephrol Dial Transplant 2025;40:1091-106. [Crossref] [PubMed]
4. Nozu K, Nakanishi K, Abe Y, et al. A review of clinical characteristics and genetic backgrounds in Alport syndrome. Clin Exp Nephrol 2019;23:158-68. [Crossref] [PubMed]
5. Watson S, Padala SA, Hashmi MF, et al. Alport Syndrome. Treasure Island (FL): StatPearls Publishing; 2025.
6. Savige J, Lipska-Zietkiewicz BS, Watson E, et al. Guidelines for Genetic Testing and Management of Alport Syndrome. Clin J Am Soc Nephrol 2022;17:143-54. [Crossref] [PubMed]
7. Warady BA, Agarwal R, Bangalore S, et al. Alport Syndrome Classification and Management. Kidney Med 2020;2:639-49. [Crossref] [PubMed]
8. Chimenz R, Chirico V, Basile P, et al. HMGB-1 and TGFβ-1 highlight immuno-inflammatory and fibrotic processes before proteinuria onset in pediatric patients with Alport syndrome. J Nephrol 2021;34:1915-24. [Crossref] [PubMed]
9. Gomes AM, Lopes D, Almeida C, et al. Potential Renal Damage Biomarkers in Alport Syndrome-A Review of the Literature. Int J Mol Sci 2022;23:7276. [Crossref] [PubMed]
10. Savige J, Ariani F, Mari F, et al. Expert consensus guidelines for the genetic diagnosis of Alport syndrome. Pediatr Nephrol 2019;34:1175-89. [Crossref] [PubMed]
11. Mahrous NN, Jamous YF, Almatrafi AM, et al. A Current Landscape on Alport Syndrome Cases: Characterization, Therapy and Management Perspectives. Biomedicines 2023;11:2762. [Crossref] [PubMed]
12. Zhang Y, Böckhaus J, Wang F, et al. Genotype-phenotype correlations and nephroprotective effects of RAAS inhibition in patients with autosomal recessive Alport syndrome. Pediatr Nephrol 2021;36:2719-30. [Crossref] [PubMed]
13. Reichelt AC, Suarez-Ibarrola R, Herrmann TRW, et al. Laser procedures in the treatment of BPH: a bibliometric study. World J Urol 2021;39:2903-11. [Crossref] [PubMed]
14. Zheng Q, Xu J, Gao Y, et al. Past, present and future of living systematic review: a bibliometrics analysis. BMJ Glob Health 2022;7:e009378. [Crossref] [PubMed]
15. Adunlin G, Diaby V, Xiao H. Application of multicriteria decision analysis in health care: a systematic review and bibliometric analysis. Health Expect 2015;18:1894-905.
16. van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010;84:523-38. [Crossref] [PubMed]
17. Chen CM. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology 2006;57:359-77.
18. Aria M, Cuccurullo C. <i>bibliometrix</i>: An R-tool for comprehensive science mapping analysis. Journal of Informetrics 2017;11:959-75.
19. Bertoli-Barsotti L, Lando T. A theoretical model of the relationship between the h-index and other simple citation indicators. Scientometrics 2017;111:1415-48. [Crossref] [PubMed]
20. Hirsch JE. An index to quantify an individual's scientific research output. Proc Natl Acad Sci U S A 2005;102:16569-72. [Crossref] [PubMed]
21. Moustafa K. Variations in Citations Across Databases: Implications for Journal Impact Factors. Semin Ophthalmol 2024;39:400-3. [Crossref] [PubMed]
22. Wang J, Wang X, Cai X, et al. Global trends and hotspots in IgA nephropathy: a bibliometric analysis and knowledge map visualization from 2012 to 2023. Int Urol Nephrol 2023;55:3197-207. [Crossref] [PubMed]
23. Kashtan C. Multidisciplinary Management of Alport Syndrome: Current Perspectives. J Multidiscip Healthc 2021;14:1169-80. [Crossref] [PubMed]
24. Hashikami K, Kobayashi R, Hori R, et al. Podocyte specific exon skipping after disease onset improves kidney pathology and function in a mouse model of Alport syndrome. Sci Rep 2025;15:41766. [Crossref] [PubMed]
25. Shang S, Peng F, Wang T, et al. Genotype-phenotype correlation and prognostic impact in Chinese patients with Alport Syndrome. Mol Genet Genomic Med 2019;7:e00741. [Crossref] [PubMed]
26. Chen T, Claure-Del Granado R, Hendricks K, et al. Nephrology Worldwide: A Perspective from the International Society of Nephrology. In: Moura-Neto JA, Divino-Filho JC, Ronco C, editors. Nephrology Worldwide. Cham: Springer International Publishing; 2021:11-22.
27. Kashtan CE, Gross O. Clinical practice recommendations for the diagnosis and management of Alport syndrome in children, adolescents, and young adults-an update for 2020. Pediatr Nephrol 2021;36:711-9. [Crossref] [PubMed]
28. Puapatanakul P, Miner JH. Alport syndrome and Alport kidney diseases - elucidating the disease spectrum. Curr Opin Nephrol Hypertens 2024;33:283-90. [Crossref] [PubMed]
29. Tryggvason K. Complex genetics of Alport and Goodpasture syndromes. Nat Rev Nephrol 2021;17:635-6. [Crossref] [PubMed]
30. Gregorio V, Caparali EB, Shojaei A, et al. Alport Syndrome: Clinical Spectrum and Therapeutic Advances. Kidney Med 2023;5:100631. [Crossref] [PubMed]
31. Savige J, Storey H, Watson E, et al. Consensus statement on standards and guidelines for the molecular diagnostics of Alport syndrome: refining the ACMG criteria. Eur J Hum Genet 2021;29:1186-97. [Crossref] [PubMed]
32. Igarashi N, Honjo M, Aihara M. mTOR inhibitors potentially reduce TGF-β2-induced fibrogenic changes in trabecular meshwork cells. Sci Rep 2021;11:14111. [Crossref] [PubMed]
33. Zhou JX, Li X. Non-Coding RNAs in Hereditary Kidney Disorders. Int J Mol Sci 2021;22:3014. [Crossref] [PubMed]
34. Yamamura T, Horinouchi T, Adachi T, et al. Development of an exon skipping therapy for X-linked Alport syndrome with truncating variants in COL4A5. Nat Commun 2020;11:2777. [Crossref] [PubMed]
35. Lo Re C, Kim JJ, Fornoni A. From RAAS blockade to regenerative medicine: evolving treatment strategies in Alport syndrome. Pediatr Nephrol 2026;41:607-19. [Crossref] [PubMed]
36. Martínez-Pulleiro R, García-Murias M, Fidalgo-Díaz M, et al. Molecular Basis, Diagnostic Challenges and Therapeutic Approaches of Alport Syndrome: A Primer for Clinicians. Int J Mol Sci 2021;22:11063. [Crossref] [PubMed]
37. Hirayama R, Toyohara K, Watanabe K, et al. iPSC-derived type IV collagen α5-expressing kidney organoids model Alport syndrome. Commun Biol 2023;6:854. [Crossref] [PubMed]
38. Chavez E, Goncalves S, Rheault MN, et al. Alport Syndrome. Adv Kidney Dis Health 2024;31:170-9. [Crossref] [PubMed]
39. Chavez E, Rodriguez J, Drexler Y, et al. Novel Therapies for Alport Syndrome. Front Med (Lausanne) 2022;9:848389. [Crossref] [PubMed]