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Background <p>Infertility affects approximately 15% of reproductive-age couples, with polycystic ovary syndrome and poor ovarian reserve being major contributing factors. Metabolomic profiling of follicular fluid offers insights into the underlying metabolic disturbances associated with these infertility phenotypes. This study aims to identify metabolic biomarkers distinguishing PCOS, POR, and male factor infertility, which may facilitate improved diagnostic and therapeutic strategies.</p> Methods <p>A total of 119 participants were categorized into three groups: PCOS (<i>n</i> = 39), POR (<i>n</i> = 40), and NOR (<i>n</i> = 40). Liquid chromatography–high-resolution mass spectrometry was used for untargeted metabolomic profiling. Metabolites were identified using HMDB, MassBank, and MoNA, while pathway analysis was performed using KEGG. Statistical analyses were conducted using R and Python, including one-way ANOVA, t-tests, and Mann-Whitney U tests, with False Discovery Rate correction applied.</p> Results <p>Distinct metabolic alterations were observed among the groups. Trehalose-6-phosphate, taurocholate, and N,N-dimethylglycine emerged as the most significantly altered metabolites, showing strong discriminatory potential between PCOS and POR. PCOS patients exhibited reduced levels of taurocholate, mycalemide, and trehalose-6-phosphate, whereas NOR patients showed elevated levels of N,N-dimethylglycine and argininosuccinate. The POR group demonstrated increased levels of 1-methyl-2-pyrrolidone and haplopine, along with a broader metabolite distribution.</p> Conclusion <p>This study reveals phenotype-specific metabolic signatures in PCOS and POR, identifying taurocholate, mycalemide, and N,N-dimethylglycine as potential follicular biomarkers. These findings contribute to a deeper understanding of the metabolic basis of infertility and highlight the potential of follicular fluid metabolomics for precision medicine in reproductive health.</p>

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Mass Spectrometry-Based Untargeted Metabolomics Identifies Distinct Metabolic Signatures in Infertility: A Comparative Analysis of PCOS, POR, and NOR

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月19日

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  • Metin Demirel,
  • Mehtap Alim,
  • Fatmanur Koktasoglu,
  • Nil Atakul,
  • Ebru Guner,
  • Ayse Nur Işık Aydın,
  • Sanem Naz Kafali,
  • Yildız Atamer,
  • Sahabettin Selek

摘要

Background

Infertility affects approximately 15% of reproductive-age couples, with polycystic ovary syndrome and poor ovarian reserve being major contributing factors. Metabolomic profiling of follicular fluid offers insights into the underlying metabolic disturbances associated with these infertility phenotypes. This study aims to identify metabolic biomarkers distinguishing PCOS, POR, and male factor infertility, which may facilitate improved diagnostic and therapeutic strategies.

Methods

A total of 119 participants were categorized into three groups: PCOS (n = 39), POR (n = 40), and NOR (n = 40). Liquid chromatography–high-resolution mass spectrometry was used for untargeted metabolomic profiling. Metabolites were identified using HMDB, MassBank, and MoNA, while pathway analysis was performed using KEGG. Statistical analyses were conducted using R and Python, including one-way ANOVA, t-tests, and Mann-Whitney U tests, with False Discovery Rate correction applied.

Results

Distinct metabolic alterations were observed among the groups. Trehalose-6-phosphate, taurocholate, and N,N-dimethylglycine emerged as the most significantly altered metabolites, showing strong discriminatory potential between PCOS and POR. PCOS patients exhibited reduced levels of taurocholate, mycalemide, and trehalose-6-phosphate, whereas NOR patients showed elevated levels of N,N-dimethylglycine and argininosuccinate. The POR group demonstrated increased levels of 1-methyl-2-pyrrolidone and haplopine, along with a broader metabolite distribution.

Conclusion

This study reveals phenotype-specific metabolic signatures in PCOS and POR, identifying taurocholate, mycalemide, and N,N-dimethylglycine as potential follicular biomarkers. These findings contribute to a deeper understanding of the metabolic basis of infertility and highlight the potential of follicular fluid metabolomics for precision medicine in reproductive health.