AUTHOR=Šmak Pavel , Juřica Jan , Gregorová Jana , Porokh Volodymyr , Peš Ondřej , Holubcová Zuzana 

TITLE=The quest for metabolic biomarkers of IVF outcomes: a meta-analysis and critical review

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2025.1640807

DOI=10.3389/fcell.2025.1640807

ISSN=2296-634X

ABSTRACT=Spent culture media (SCM) analysis offers a promising, non-invasive strategy for assessing embryo viability and implantation potential in in vitro fertilization (IVF). By profiling the consumption and secretion of low molecular weight metabolites, SCM analysis may offer valuable insights into embryonic metabolic activity and developmental competence. Identifying reliable biomarkers in SCM has the potential to support more objective embryo selection and reduce time to pregnancy. This Bayesian meta-analysis synthesizes quantitative evidence from studies reporting metabolite concentrations in SCM in relation to IVF outcomes. From a comprehensive literature search identifying 175 studies, 10 met strict inclusion criteria, providing concentration-based data suitable for standardized effect size estimation. Using a multilevel modeling approach, we integrated data across heterogeneous study designs and found seven metabolites positively and ten negatively associated with favorable IVF outcomes. To complement this quantitative synthesis, we critically appraised 14 additional studies excluded from the meta-analysis due to missing calibration data or insufficient methodological transparency. This dual approach highlights recurring methodological challenges and underscores the need for standardized protocols, validated analytical methods, and transparent reporting in SCM research. Overall, the findings illustrate both the potential and the current limitations of SCM metabolic profiling. We provide practical recommendations for improving study design and reproducibility, with the goal of advancing SCM analysis toward clinically relevant biomarker validation.