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<p>Menstrual pain affects women’s quality of life and productivity, yet objective molecular markers for its severity have not been established owing to the variability in blood levels and chemical properties of potential markers such as plasma steroid hormones, lipid mediators, and hydrophilic metabolites. To address this, we conducted a metabolomics study using five analytical methods to identify biomarkers that differentiate menstrual pain severity. This study included 20 women, divided into mild (<i>N</i> = 12) and severe (<i>N</i> = 8) pain groups based on their numerical pain rating scale. We developed pretreatment procedures that allowed all analyses from only 100 µL of finger-prick blood collected across the menstrual cycle. Among the 692 quantified metabolites, branched-chain amino acids and specific phosphatidylinositol (PI), especially PI(36:2), were identified as potential biomarkers. Furthermore, the ratio of PI(36:2) to each BCAA or total BCAA effectively discriminated between the severity levels of menstrual pain. These ratios correlated positively with NPRS, indicating high accuracy in pain assessment. This study highlights the potential of small molecular markers to objectively assess menstrual pain severity, aiding evidence-based support and intervention.</p>

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Branched-chain amino acids and specific phosphatidylinositols are plasma metabolite pairs associated with menstrual pain severity

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月25日

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  • Atsushi Sato,
  • Kanako Yuyama,
  • Yuko Ichiba,
  • Yasushi Kakizawa,
  • Yuki Sugiura

摘要

Menstrual pain affects women’s quality of life and productivity, yet objective molecular markers for its severity have not been established owing to the variability in blood levels and chemical properties of potential markers such as plasma steroid hormones, lipid mediators, and hydrophilic metabolites. To address this, we conducted a metabolomics study using five analytical methods to identify biomarkers that differentiate menstrual pain severity. This study included 20 women, divided into mild (N = 12) and severe (N = 8) pain groups based on their numerical pain rating scale. We developed pretreatment procedures that allowed all analyses from only 100 µL of finger-prick blood collected across the menstrual cycle. Among the 692 quantified metabolites, branched-chain amino acids and specific phosphatidylinositol (PI), especially PI(36:2), were identified as potential biomarkers. Furthermore, the ratio of PI(36:2) to each BCAA or total BCAA effectively discriminated between the severity levels of menstrual pain. These ratios correlated positively with NPRS, indicating high accuracy in pain assessment. This study highlights the potential of small molecular markers to objectively assess menstrual pain severity, aiding evidence-based support and intervention.