Demirel Metin, Alim Mehtap, Koktasoglu Fatmanur, Atakul Nil, Guner Ebru, Aydın Ayse Nur Işık, Kafali Sanem Naz, Atamer Yildız, Selek Sahabettin
Department of Medical Biochemistry, Bezmialem Vakif University Faculty of Medicine, 34093, Istanbul, Turkey.
Health Sciences Institute, Bezmialem Vakif University, Istanbul, Turkey.
Reprod Sci. 2025 Jun 19. doi: 10.1007/s43032-025-01908-5.
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.
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.
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.
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.
不孕症影响着约15%的育龄夫妇，多囊卵巢综合征和卵巢储备功能低下是主要的促成因素。卵泡液的代谢组学分析有助于深入了解与这些不孕症表型相关的潜在代谢紊乱。本研究旨在识别区分多囊卵巢综合征、卵巢储备功能低下和男性因素不孕症的代谢生物标志物，这可能有助于改进诊断和治疗策略。
总共119名参与者被分为三组：多囊卵巢综合征组（n = 39）、卵巢储备功能低下组（n = 40）和正常组（n = 40）。采用液相色谱-高分辨率质谱法进行非靶向代谢组学分析。使用人类代谢组数据库（HMDB）、质谱数据库（MassBank）和天然产物小分子数据库（MoNA）鉴定代谢物，同时使用京都基因与基因组百科全书（KEGG）进行通路分析。使用R和Python进行统计分析，包括单因素方差分析、t检验和曼-惠特尼U检验，并应用错误发现率校正。
各组之间观察到明显的代谢改变。海藻糖-6-磷酸、牛磺胆酸盐和N，N-二甲基甘氨酸成为改变最显著的代谢物，在多囊卵巢综合征和卵巢储备功能低下之间显示出很强的鉴别潜力。多囊卵巢综合征患者的牛磺胆酸盐、肌钙蛋白和海藻糖-6-磷酸水平降低，而正常组患者的N，N-二甲基甘氨酸和精氨琥珀酸水平升高。卵巢储备功能低下组的1-甲基-2-吡咯烷酮和哈普洛平水平升高，代谢物分布更广泛。
本研究揭示了多囊卵巢综合征和卵巢储备功能低下中特定表型的代谢特征，确定牛磺胆酸盐、肌钙蛋白和N，N-二甲基甘氨酸为潜在的卵泡生物标志物。这些发现有助于更深入地了解不孕症的代谢基础，并突出卵泡液代谢组学在生殖健康精准医学中的潜力。
