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REVIEW article

Front. Neurosci.
Sec. Neurodevelopment
Volume 18 - 2024 | doi: 10.3389/fnins.2024.1514678

Mapping the Structure of Biomarkers in Autism Spectrum Disorder: A Review of the Most Influential Studies

Provisionally accepted
Fang Jin Fang Jin Zhidan Wang Zhidan Wang *
  • Jiangsu Normal University, Xuzhou, China

The final, formatted version of the article will be published soon.

    Background: Autism spectrum disorder is a distinctive developmental condition which is caused by an interaction between genetic vulnerability and environmental factors. Biomarkers play a crucial role in understanding disease characteristics for diagnosis, prognosis, and treatment. This study employs bibliometric analysis to identify and review the 100 top-cited articles' characteristics, current research hotspots and future directions of autism biomarkers.: A comprehensive search of autism biomarkers studies was retrieved from the Web of Science Core Collection database with a combined keyword search strategy. A comprehensive analysis of the top 100 articles was conducted with CiteSpace, VOSviewer, and Excel, including citations, countries, authors, and keywords. Results: The top 100 cited studies were published between 1988 and 2021, with the USA led in productivity. Core biomarkers such as genetics, children, oxidative stress, and mitochondrial dysfunction are well-established. Potential trends for future research may include brain studies, metabolomics, and associations with other psychiatric disorders. Conclusion: This pioneering bibliometric analysis provides a comprehensive compilation of the 100 most-cited studies on autism, which not only offers a valuable resource for doctors, and researchers but shedding insights into current shortcomings and future endeavors. Future research should prioritize the application of emerging technologies for biomarkers, longitudinal study of biomarkers, and specificity of autism biomarkers to advance the precision of ASD diagnosis and treatment.

    Keywords: Autism biomarkers, bibliometric analysis, Genetics, Brain, Metabolomics, Oxidative Stress, Mitochondrial dysfunction

    Received: 21 Oct 2024; Accepted: 02 Dec 2024.

    Copyright: © 2024 Jin and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Zhidan Wang, Jiangsu Normal University, Xuzhou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.