Unveiling lipoprotein subfractions signature in high-FNPO PCOS: implications for PCOM diagnosis and risk assessment using advanced machine learning models.

Journal: BMC medicine
Published Date: May 19, 2025

Abstract

BACKGROUND: Polycystic ovary syndrome (PCOS) is a common reproductive and metabolic disorder in the reproductive-age women. The international evidence-based guideline for the assessment and management of PCOS 2023 now suggests raising the follicle number per ovary (FNPO) threshold from 12 to 20 to define its key feature, polycystic ovarian morphology (PCOM). However, understanding of low- and high-FNPO PCOS cases defined in this cutoff is very limited. Given that the measures of lipoprotein subfractions are the biomarkers of several common diseases, this study aims to explore clinical characteristics and lipoprotein subfractions in low- and high-FNPO PCOS, and develop a diagnostic model.

Authors

  • Xueqi Yan
    State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China.
  • Ziyi Yang
    Microsoft Research, Redmond, WA, USA.
  • Hui Zhao
    School of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong, 723000, Shaanxi, China.
  • Gengchen Feng
    State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China.
  • Shumin Li
    School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China.
  • Yimeng Li
    School of Electric and Control Engineering, North China University of Technology, Beijing100144, China.
  • Yu Sun
    Department of Neurology, China-Japan Friendship Hospital, Beijing, China.
  • Jinlong Ma
    School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, China.
  • Han Zhao
  • Xueying Gao
    State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China. gaoxueyingzye@126.com.
  • Shigang Zhao
    State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China. zsg0108@126.com.

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