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ORIGINAL RESEARCH article

Front. Mol. Biosci.
Sec. Molecular Diagnostics and Therapeutics
Volume 12 - 2025 | doi: 10.3389/fmolb.2025.1536477

Identifying potential biomarkers and molecular mechanisms related to arachidonic acid metabolism in vitiligo

Provisionally accepted
Lijun Sun Lijun Sun 1*Xiaoqing Li Xiaoqing Li 1Li Yang Li Yang 1Longfei Zhu Longfei Zhu 2Jingying Sun Jingying Sun 1Xu Cuixiang Xu Cuixiang 1
  • 1 Shaanxi Provincial People's Hospital, Xi'an, China
  • 2 The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

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

    Related studies have reported that dysregulation of fatty acid metabolic pathways is associated with the pathogenesis of vitiligo, in which arachidonic acid metabolism (AAM) plays an important role in this process. However, the molecular mechanism of AAM involved in the pathogenesis of vitiligo has not been clarified. Therefore, this study aimed to identify biomarkers and molecular mechanisms associated with arachidonic acid metabolism in vitiligo using bioinformatics methods. GSE75819 and GSE65127 datasets were utilized as training and validation sets, respectively, alongside 58 AAM-related genes (AAM-RGs). Differentially expressed genes (DEGs) between the lesional and control groups in the training set were identified by differential expression analysis. Then, 15 candidate genes were obtained by overlapping DEGs and AAM-RGs. Next, machine learning algorithms identified six key genes, including PTGDS, PNPLA8, FAAH, ABHD12, PTGS1, and MGLL. In both the training and validation sets, PTGDS, PNPLA8 and MGLL were regarded as biomarkers. A nomogram based on these biomarkers showed promise in predicting vitiligo risk.Functional enrichment, immune cell infiltration, and regulatory network analyses elucidated the molecular mechanisms. In conclusion, PTGDS, PNPLA8, and MGLL were implicated in AAM, influencing vitiligo pathogenesis. These findings offer insights into vitiligo treatment, although further research is needed for a comprehensive understanding.

    Keywords: Vitiligo, arachidonic acid metabolism, key genes, machine learning, biomarker

    Received: 29 Nov 2024; Accepted: 30 Jan 2025.

    Copyright: © 2025 Sun, Li, Yang, Zhu, Sun and Cuixiang. 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: Lijun Sun, Shaanxi Provincial People's Hospital, Xi'an, China

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