Reproductive medicine and biology · 2026
Decoding the Follicular Fluid Microenvironment: Integrative Biomarkers and Multiomics Signatures to Predict IVF Outcomes.
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Muraoka Ayako, Kajiyama Hiroaki
Аннотация
BACKGROUND: With the increase in the number of patients with infertility, the number of patients requiring in vitro fertilization and embryo transfer (IVF-ET) is also increasing. No established method exists for predicting pregnancy rates under IVF-ET, and the urgent development of pregnancy predictive biomarkers is required. Follicular fluid (FF) can be collected noninvasively during oocyte retrieval and contains numerous substances indicative of follicular status, making it a strong candidate for such biomarkers.
METHODS: This review summarizes the predictive potential of several biomarkers in FF for pregnancy. We focused on FF components such as hormones, proteins, growth factors, inflammatory markers, oxidative stress markers, metabolomics, and nucleic acids.
MAIN FINDINGS: FF contains stem cell factors, interleukin-6, coenzyme Q10, vitamin D, cell-free deoxyribonucleic acid, and micro ribonucleic acids within extracellular vesicles, which can predict in vitro fertilization (IVF) success. Recently, omics has enabled the analysis of a wide range of constituents, contributing to the search for potential biomarkers.
CONCLUSION: This review presents a comprehensive overview of relevant FF biomarkers for predicting IVF outcomes. Reliable FF predictive biomarkers are expected to improve future IVF success rates and embryo selection, thereby enhancing overall assisted reproductive technology outcomes.
METHODS: This review summarizes the predictive potential of several biomarkers in FF for pregnancy. We focused on FF components such as hormones, proteins, growth factors, inflammatory markers, oxidative stress markers, metabolomics, and nucleic acids.
MAIN FINDINGS: FF contains stem cell factors, interleukin-6, coenzyme Q10, vitamin D, cell-free deoxyribonucleic acid, and micro ribonucleic acids within extracellular vesicles, which can predict in vitro fertilization (IVF) success. Recently, omics has enabled the analysis of a wide range of constituents, contributing to the search for potential biomarkers.
CONCLUSION: This review presents a comprehensive overview of relevant FF biomarkers for predicting IVF outcomes. Reliable FF predictive biomarkers are expected to improve future IVF success rates and embryo selection, thereby enhancing overall assisted reproductive technology outcomes.