Scientists decode ovarian aging with groundbreaking molecular atlas

Discover how cutting-edge single-nucleus multi-omics reveals the secrets of ovarian aging, paving the way for breakthroughs in fertility and health longevity.

In a recent study published in the journal Nature Aging, researchers from various institutions across the United States used several next-generation single-nucleus multi-omics analyses to unravel the biological mechanisms driving ovarian aging. They compared the molecular and genetic profiles of young (ages 23–29) and reproductively aged (49–54) human ovaries and revealed that chromatin accessibility and gene expression evolve in highly coordinated regimes across all major ovarian cell types, including granulosa, theca, and epithelial cells.

The study identified 3,455 aging-associated differentially expressed genes (DEGs), including RICTOR, MAP3K5, IGF1R, and APOE, and functional non-coding regulatory variants and transcription factors (e.g., CEBPD) with hitherto unknown impacts on ovarian aging. Notably, the study highlighted the role of mTOR signaling as a unique, ovary-specific aging pathway. It used this data to generate a detailed publicly available atlas describing the molecular and genetic framework elucidating ovarian aging. This atlas will form an essential resource for future aging-associated investigations, allowing for progress in fertility preservation and age-associated health interventions.

Background

mTOR signaling as a unique ovarian aging hallmark: The study identifies mTOR signaling as an ovary-specific pathway, highlighting its central role in aging and its potential as a therapeutic target to delay ovarian decline.

Ovaries are a pair of glands in the female reproductive system that produce eggs and hormones essential for fertility and reproduction. In humans, ovaries are well known to be the first tissues experiencing age-associated evolution, characterized by the systematic decline in the number and quality of oocytes, the precursor cells of fertile eggs.

Decades of research have revealed that ~37 years represents a tipping point of greatly accelerated ovarian aging, substantially exacerbating infertility and aneuploidy risk. Furthermore, studies on genomic variation have shown that this natural aging process can trigger congenital disabilities in offspring born following the onset of age at natural menopause (ANM).

Genome-wide association studies (GWAS) have found strong correlations between genetics and the pace of ovarian aging, with even twins demonstrating variation in ANM outcomes. Unfortunately, the limitations of conventional molecular analysis techniques prevented a detailed understanding of the mechanisms underpinning these age-associated ovarian declines. These investigations were further confounded by the influence of environmental factors, including radiation exposure and chemotherapy, which can further accelerate the aging process, as observable by extensive variation in ANM.

Progress in next-generation sequencing techniques now enables comprehensive characterization of the genomic and epigenomic mechanisms underpinning ANM observations, particularly by identifying cell-specific regulatory pathways and genes. Unraveling these hitherto hidden aspects would bolster our understanding of the biology of ovarian aging, paving the path for future anti-infertility interventions.

About the Study

The present study leverages a multi-omics approach to elucidate the epigenomic and transcriptomic changes governing ovarian aging. It subsequently integrates GWAS-produced ANM variant data to create a novel atlas of the ovarian aging process, detailing functional regulatory elements (including non-coding) and critical genes across ovarian cell types, such as granulosa and theca cells, which showed substantial changes in aging-related gene expression.

Study data was obtained from eight flash-frozen human ovaries, all with normal histology and minimal expression of post-mortem interval (PMI)-related genes. The dataset comprised both young (23–29 yrs; n = 4) and reproductively aged (49–54 yrs; n = 4). Researchers employed the high-throughput Illumina platform for single-nuclei RNA sequencing (snRNA-seq) alongside single-nuclei assay for transposase-accessible chromatin using sequencing (snATAC-seq), revealing distinct transcriptional and chromatin accessibility profiles for eight and seven major somatic cell clusters, respectively.

High coordination in ovarian aging: Unlike other tissues, ovarian cells exhibit remarkably synchronized transcriptomic changes during aging, reflecting a unique coordination in gene expression and cellular pathways.

These sequencing techniques allow for the description of differentially accessible chromatin regions (DARs) for each identified cell type, facilitating their effective demarcation. Comparison between young and reproductively aged snRNA-seq data was subsequently used to elucidate the dynamic changes accompanying the natural ovarian aging process. Differentially expressed genes (DEGs) identified in the present dataset were compared with previous GWAS literature, enabling researchers to compute the gene expression changes governing ANM onset with a particular focus on histone modification, senescence, and associated transcriptomic signaling pathways.

The study also explored intercellular communication changes using the CellChat platform, finding age-associated reductions in communication strength between key ovarian cell types such as granulosa and theca cells and oocytes. Finally, to identify specific cell types at the highest ANM risk (future targets of pharmacological infertility research), researchers compared their results to open-source GWAS data, leveraging a technique called Multivariate Analysis of Genomic Annotation (MAGMA) analysis.

Study Findings

Researchers obtained 42,568 single nuclei and 41,550 single nuclei for snRNA-seq (8 clusters) and snATAC-seq analyses (7 clusters), respectively. Comparisons between cell type proportions in young and reproductively aged ovaries revealed that granulosa and theca cells were substantially reduced in the latter. In contrast, reproductively aged ovaries demonstrated significantly higher epithelial cell concentrations than their younger counterparts.

Differential gene expression analysis identified 3,455 ovarian genes responsible for ANM, most of which were expressed in the granulosa cells. The researchers emphasized that ovarian cells, unlike most organ systems, demonstrate remarkable coordination in their age-associated transcriptomic changes."Aged epithelial cells exhibited significantly elevated expression of cell-cycle-associated genes, whereas aged granulosa cells, theca cells, and endothelial cells showed increased expression of apoptosis-associated genes and/or decreased expression of cell-cycle-associated genes compared to young counterparts," the researchers noted. "These results indicate that aging substantially remodels the cellular architecture of the human ovary."

Finally, the study identified both upstream (CCAAT/enhancer-binding protein delta [CEBPD]) and downstream effectors (mTOR signaling) intrinsic to ovarian aging. Notably, most of the functional variation between young and reproductively aged ovaries was observed in the non-coding region of the genome.

Conclusions

The present study identifies the molecular, cellular, and genetic underpinnings of human ovarian aging, highlighting the highly coordinated and potentially generalizable changes accompanying the natural aging process. They use their findings to develop a comprehensive atlas of the molecular ovarian aging process, thereby providing future researchers in the field with a compendium of the cell types and specific genes requiring future investigation. These findings offer a foundation for developing interventions targeting mTOR signaling and other pathways to delay ovarian aging and improve fertility preservation.

This research represents crucial progress in our quest to delay or even reverse ovarian aging, combatting its adverse fertility and congenital outcomes.

Journal reference:

• Jin, C., Wang, X., Yang, J., Kim, S., Hudgins, A. D., Gamliel, A., Pei, M., Contreras, D., Devos, M., Guo, Q., Vijg, J., Conti, M., Hoeijmakers, J., Campisi, J., Lobo, R., Williams, Z., Rosenfeld, M. G., & Suh, Y. (2024). Molecular and genetic insights into human ovarian aging from single-nuclei multi-omics analyses. Nature Aging, 1-16. DOI: 10.1038/s43587-024-00762-5, https://www.nature.com/articles/s43587-024-00762-5