Research trends and thematic evolution in uric acid and depression: a bibliometric analysis from 2000 to 2025
- 1Department of Graduate School, Heilongjiang University of Chinese Medicine
- 2Department of Acupuncture and Moxibustion, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine
Abstract
Background: Research on uric acid and depression has expanded across psychiatry, metabolic medicine, neuroscience, and public health, but its contributors, knowledge base, and thematic evolution have not been systematically mapped.
Methods: Publications indexed in the Web of Science Core Collection (WoSCC) from 2000 to 2025 were retrieved, with 354 included in the primary bibliometric analysis. An independent PubMed search retained 289 publications for cross-database comparison. Microsoft Excel, bibliometrix/Biblioshiny, VOSviewer, and CiteSpace were used to analyze publication trends, collaboration networks, journal and author contributions, co-citation patterns, author keywords, citation bursts, journal dual-map overlays, and trend topics. Annual trends, record coverage, author keywords, and thematic structures were compared between databases.
Results: Publication output increased markedly after 2015, reaching 58 publications in WoSCC and 56 in PubMed in 2025. Annual counts showed strong monotonic covariation (Spearman’s ρ = 0.976, P < 0.001), although absolute coverage differed. China was the most productive country, the United Kingdom had the strongest international co-authorship links, and Peking University and Deakin University jointly led institutional output. The Journal of Affective Disorders was the leading source and most frequently co-cited journal, while Michael Maes was the most productive and most frequently co-cited author. Major themes included oxidative stress and inflammation, biomarkers and metabolomics, medical and neurological comorbidities, and mood disorders. Relatively recent publication year distributions were observed for terms related to population-based datasets, composite metabolic indicators, causal inference methods, specific clinical populations, and prediction models. Cross-database matching identified 260 shared publications. Eighteen of the top 20 author keywords were shared (Jaccard coefficient, 0.818; overlap coefficient, 0.900). PubMed showed thematic similarities to WoSCC while emphasizing clinical comorbidities, population-based datasets, composite metabolic indicators, and prediction models.
Conclusion: Research on uric acid and depression has developed into a multidisciplinary field linking affective disorders with oxidative stress, inflammation, and metabolism. Serum uric acid may be better viewed as a context-dependent peripheral indicator than as a standalone diagnostic biomarker or established causal factor. Future studies should use longitudinal and mechanistic designs and validate composite indicators and prediction models in independent populations.
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BibTeX
@article{zhao2026research,
title = {{Research trends and thematic evolution in uric acid and depression: a bibliometric analysis from 2000 to 2025}},
author = {Wei Zhao and Baiyi Jiang and Xinyang Fang and Xue Xia and Long Wang},
journal = {Frontiers in Psychiatry},
year = {2026},
month = nov,
doi = {10.3389/fpsyt.2026.1947640},
url = {https://www.frontiersin.org/articles/10.3389/fpsyt.2026.1947640/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Research trends and thematic evolution in uric acid and depression: a bibliometric analysis from 2000 to 2025
AU - Wei Zhao
AU - Baiyi Jiang
AU - Xinyang Fang
AU - Xue Xia
AU - Long Wang
PY - 2026
DA - 2026/11/02
JO - Frontiers in Psychiatry
DO - 10.3389/fpsyt.2026.1947640
UR - https://www.frontiersin.org/articles/10.3389/fpsyt.2026.1947640/full
AB - Background: Research on uric acid and depression has expanded across psychiatry, metabolic medicine, neuroscience, and public health, but its contributors, knowledge base, and thematic evolution have not been systematically mapped. Methods: Publications indexed in the Web of Science Core Collection (WoSCC) from 2000 to 2025 were retrieved, with 354 included in the primary bibliometric analysis. An independent PubMed search retained 289 publications for cross-database comparison. Microsoft Excel, bibliometrix/Biblioshiny, VOSviewer, and CiteSpace were used to analyze publication trends, collaboration networks, journal and author contributions, co-citation patterns, author keywords, citation bursts, journal dual-map overlays, and trend topics. Annual trends, record coverage, author keywords, and thematic structures were compared between databases. Results: Publication output increased markedly after 2015, reaching 58 publications in WoSCC and 56 in PubMed in 2025. Annual counts showed strong monotonic covariation (Spearman’s ρ = 0.976, P < 0.001), although absolute coverage differed. China was the most productive country, the United Kingdom had the strongest international co-authorship links, and Peking University and Deakin University jointly led institutional output. The Journal of Affective Disorders was the leading source and most frequently co-cited journal, while Michael Maes was the most productive and most frequently co-cited author. Major themes included oxidative stress and inflammation, biomarkers and metabolomics, medical and neurological comorbidities, and mood disorders. Relatively recent publication year distributions were observed for terms related to population-based datasets, composite metabolic indicators, causal inference methods, specific clinical populations, and prediction models. Cross-database matching identified 260 shared publications. Eighteen of the top 20 author keywords were shared (Jaccard coefficient, 0.818; overlap coefficient, 0.900). PubMed showed thematic similarities to WoSCC while emphasizing clinical comorbidities, population-based datasets, composite metabolic indicators, and prediction models. Conclusion: Research on uric acid and depression has developed into a multidisciplinary field linking affective disorders with oxidative stress, inflammation, and metabolism. Serum uric acid may be better viewed as a context-dependent peripheral indicator than as a standalone diagnostic biomarker or established causal factor. Future studies should use longitudinal and mechanistic designs and validate composite indicators and prediction models in independent populations.
SN - 1664-0640
ER -