Genping Zeng, Mengyuan Chu, Jiaqi Yang, Yunfei Han, Qianyi Zhou, Han Zhang, Ying Yan
Ovarian aging has emerged as a major challenge to female reproductive health worldwide, primarily characterized by a decline in oocyte quality and/or quantity, diminished granulosa cell function, and impairment of the surrounding microenvironment. Within this microenvironment, glucose metabolism participates in the synergistic regulation of ovarian homeostasis through specific metabolic networks and metabolite-driven signaling. Metabolic disruption can impair intercellular communication mechanisms, induce oxidative stress and mitochondrial dysfunction, and ultimately drive ovarian aging. Ovarian granulosa cells surround the oocyte and facilitate bidirectional communication via gap junctions or molecular signaling. These cells continuously supply energy substrates to support oocyte growth and maturation, while the oocyte, in turn, promotes granulosa cell proliferation and differentiation. Impairment of glycolysis in granulosa cells leads to energy deficits and triggers apoptosis. Concurrently, metabolic reprogramming in the oocyte links glucose metabolic homeostasis with mechanisms governing developmental competence. Glucose-derived metabolites drive various post-translational modifications (PTMs), including glycosylation, acetylation, phosphorylation, and succinylation, that contribute to ovarian function and intersect with pathological processes such as oxidative stress, chronic inflammation, and autophagy. Therefore, therapeutic strategies targeting glucose metabolism, such as modulating metabolic pathways, metabolite signaling, and associated PTMs, offer promising avenues for treating ovarian aging. However, the glucose metabolic network within the ovarian microenvironment is highly complex, and targeting a single node is often insufficient to restore metabolic homeostasis. A comprehensive approach that integrates multiple strategies to simultaneously intervene at different regulatory levels is needed. This review summarizes recent advances in understanding the ovarian glucose metabolic network, metabolite-driven post-translational modifications, and the interplay among various pathological mechanisms. We further explore potential regulators that could restore glucose metabolic balance and propose that future efforts should focus on developing precision strategies, guided by artificial intelligence and multi-omics data to modulate the metabolic reprogramming of both the microenvironment and functional cells, ultimately translating these insights into clinical interventions for ovarian aging.