Integrative follicular fluid biomarkers for oocyte competence and IVF outcomes: from molecular networks to multianalyte panels.

Accurate assessment of oocyte developmental competence remains a major challenge in assisted reproductive technology because conventional morphological grading and ovarian-reserve markers provide limited information about the molecular state of individual follicles. Follicular fluid offers a minimally invasive window into this microenvironment, integrating systemic endocrine inputs with bidirectional oocyte-somatic cell communication, steroidogenesis, metabolic coupling, extracellular-matrix remodeling, periovulatory inflammation, redox homeostasis, mitochondrial function, and angiogenesis. This narrative review synthesizes mechanistic and clinical evidence concerning follicular-fluid biomarkers associated with oocyte maturity, fertilization, embryo development, blastocyst formation, implantation, and live birth. Particular attention is given to granulosa cell-associated signaling networks involving epidermal growth factor-like ligands, pentraxin 3, transforming growth factor-β and bone morphogenetic protein family members, activins and follistatin, glial cell line-derived neurotrophic factor, cytokines, steroid hormones, metabolic intermediates, lipids, oxidative-damage markers, and extracellular-matrix components. Available evidence indicates that individual analytes generally lack sufficient reproducibility, discrimination, and calibration for routine clinical prediction because their concentrations are influenced by patient phenotype, ovarian-stimulation regimen, follicular stage, sampling strategy, preanalytical handling, analytical platform, and outcome definition. Follicular heterogeneity and the statistical non-independence of multiple oocytes obtained from the same patient further complicate biomarker evaluation. We therefore propose a transition from single-analyte measurements toward mechanism-informed, outcome-specific multianalyte panels integrating follicular-fluid measurements with cumulus- or granulosa-cell transcriptomic, proteomic, metabolomic, and lipidomic features. Phenotype-specific models, particularly for polycystic ovary syndrome, may further improve biological interpretation. Clinical translation will require standardized individual-follicle sampling, one-to-one linkage between biomarkers and oocyte or embryo outcomes, targeted assay development, multilevel statistical modeling, independent prospective validation, and demonstration of incremental clinical utility beyond established patient and embryological variables. The ultimate goal is a parsimonious and reproducible biomarker panel that complements, rather than replaces, conventional embryological assessment and supports more individualized IVF decision-making.