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Cytokines are key regulators of ovarian physiology, particularly in relation to folliculogenesis and ovulation, where they contribute to creating an environment supporting follicle selection and growth. Their manifold functions include regulating cellular proliferation/differentiation, follicular survival/atresia, and oocyte maturation. Several cytokines, such as TGF-β-superfamily members, are involved at all stages of folliculogenesis while the production of others is stage-dependent. This review draws upon evidence from both human and animal models to highlight the species-specific roles at each milestone of follicular development. Given these pivotal roles and their ease of detection in follicular fluid, cytokines have been considered as attractive biomarkers of oocyte maturational status and of successful assisted reproductive outcome. Despite this, our understanding of cytokines and their interactions remains incomplete, and is still frequently limited to overly simplistic descriptions of their interrelationships. Given our increased appreciation of cytokine activity in complex and highly regulated networks, we put forward the case for using Bayesian modelling approaches to describe their hierarchical relationships in order to predict causal physiological interactions in vivo.

Cytokines are key regulators of ovarian physiology, particularly in relation to folliculogenesis and ovulation, where they contribute to creating an environment supporting follicle selection and growth. Their manifold functions include regulating cellular proliferation/differentiation, follicular survival/atresia, and oocyte maturation. Several cytokines, such as TGF-β-superfamily members, are involved at all stages of folliculogenesis while the production of others is stage-dependent. This review draws upon evidence from both human and animal models to highlight the species-specific roles at each milestone of follicular development. Given these pivotal roles and their ease of detection in follicular fluid, cytokines have been considered as attractive biomarkers of oocyte maturational status and of successful assisted reproductive outcome. Despite this, our understanding of cytokines and their interactions remains incomplete, and is still frequently limited to overly simplistic descriptions of their interrelationships. Given our increased appreciation of cytokine activity in complex and highly regulated networks, we put forward the case for using Bayesian modelling approaches to describe their hierarchical relationships in order to predict causal physiological interactions in vivo.