Cell-Free Transcriptomic Profiles and Mechanism Insights in Female Androgenetic Alopecia

    November 2025 in “ Clinical and Translational Medicine ”
    Lingling Jia, Mingyang Lu, Siwei Deng, Yongcheng Jin, Changjiang Zhao, Ruiyu Luo, Yuan Zhu, Zihan Li, Zixuan An, Hua Jiang, Yufei Li, Lingling Jia, Mingyang Lu, Siwei Deng, Yongcheng Jin, Changjiang Zhao, Ruiyu Luo, Yuan Zhu, Zihan Li, Zixuan An, Hua Jiang, Yufei Li
    Studysummary This study found that cell-free RNA, particularly DNAJB9, shows potential as a biomarker for diagnosing and prognosing female androgenetic alopecia using a machine learning model.
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    The study investigates the use of plasma cell-free RNA (cfRNA) and machine learning to enhance the diagnosis and prognosis of female androgenetic alopecia (FAGA). Involving 65 FAGA patients and 41 controls, the research identified distinct cfRNA expression profiles, with significant findings including the downregulation of DNAJB9, which is linked to increased FAGA severity. The study also highlighted the involvement of JAK-STAT and WNTs pathways. A machine learning model demonstrated moderate predictive power with an AUC of 0.707. The research suggests cfRNA, particularly DNAJB9, as a promising biomarker and potential therapeutic target for FAGA.
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