Spatiotemporal analysis of human ovarian aging at single-cell resolution

Abstract Our understanding of how aging affects the cellular and molecular components of the human ovary and contributes to age-related fertility decline is still limited. Here, we link single-cell RNA sequencing and spatial transcriptomics to characterize human ovarian aging. Changes of the molecular signatures of eight types of ovarian cells during aging were defined. We combined single cell types with their spatial location information to divide ovarian granulosa cells into three subtypes and theca & stroma cells into five subtypes. Further analysis revealed increased cellular senescence with age and characterized the transcription factor FOXP1 as a master regulatory gene during ovarian aging. Inhibition of FOXP1 in ovarian cells increased cellular senescence which was alleviated by pharmacological treatment with quercetin or fisetin. These findings provide a comprehensive understanding of the spatiotemporal variability of human ovarian aging, providing resources for developing new diagnostic biomarkers and therapeutic strategies against ovarian aging.