Metabolic profiling of follicular fluid and plasma from natural cycle in vitro fertilization patients—a pilot study  

Oleh:

McRae, Cassey ; Baskind, N. Ellissa ; Orsi, Nicolas M. ; Sharma, Vinay ; Fisher, Julie

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Fertility and Sterility (keterangan: ada di ClinicalKey) vol. 98 no. 06 (Dec. 2012), page 1449-1457.
Topik: metabolomics; Blood plasma; follicular fluid; in vitro fertilization (IVF); metabolomics; nuclear magnetic resonance (NMR)

Ketersediaan

Perpustakaan FK Nomor Panggil: F02.K.2012.03 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

Objective To investigate changes in follicular fluid (FF) and plasma composition during the follicular and periovulatory phases of the menstrual cycle in patients undergoing assisted conception, using proton nuclear magnetic resonance (1H-NMR) spectroscopy–based metabolite profiling. Design A pilot prospective laboratory study. Setting Assisted conception clinic in a university hospital. Patient(s) Ten women undergoing natural-cycle (NC) in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) with either male factor subfertility or unexplained subfertility. Intervention(s) FF and plasma were collected during the midfollicular phase or at the LH-surge and at the time of oocyte collection. Main Outcome Measure(s) 1H-NMR spectroscopy was performed on the fluids and the metabolic profiles compared across the phases with the use of principal components analysis (PCA). Result(s) LH-surge FF resembled periovulatory FF more than midfollicular FF, with higher levels of lactate and pyruvate and lower glucose. Periovulatory plasma contained higher levels of glucose and acetate and lower glycoprotein, trimethylamine, and glycine compared with midfollicular and LH-surge plasma. Conclusion(s) NMR-based metabolite profiling of FF and plasma has potential for identifying changes across menstrual stages, studying the impact of exogenous hCG administration, and in the pursuit of biomarkers to predict fertility treatment outcome.

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