Molecular and genetic insights into human ovarian aging from single-nuclei multi-omics analyses

被引:4
作者
Jin, Chen [1 ]
Wang, Xizhe [1 ]
Yang, Jiping [1 ]
Kim, Seungsoo [1 ]
Hudgins, Adam D. [1 ]
Gamliel, Amir [2 ,3 ]
Pei, Mingzhuo [1 ]
Contreras, Daniela [1 ]
Devos, Melody [1 ]
Guo, Qinghua [1 ]
Vijg, Jan [4 ]
Conti, Marco [5 ,6 ,7 ]
Hoeijmakers, Jan [8 ,9 ,10 ]
Campisi, Judith [11 ]
Lobo, Rogerio [1 ]
Williams, Zev [1 ]
Rosenfeld, Michael G. [2 ,3 ]
Suh, Yousin [1 ,12 ]
机构
[1] Columbia Univ, Irving Med Ctr, Dept Obstet & Gynecol, New York, NY 10032 USA
[2] Univ Calif San Diego, Howard Hughes Med Inst, Dept Med, La Jolla, CA USA
[3] Univ Calif San Diego, Sch Med, La Jolla, CA USA
[4] Albert Einstein Coll Med, Dept Genet, New York, NY 10461 USA
[5] Univ Calif San Francisco, Ctr Reprod Sci, San Francisco, CA USA
[6] Univ Calif San Francisco, Eli & Edythe Broad Ctr Regenerat Med & Stem Cell R, San Francisco, CA USA
[7] Univ Calif San Francisco, Dept Obstet Gynecol & Reprod Sci, San Francisco, CA USA
[8] Erasmus Univ, Med Ctr Rotterdam, Dept Mol Genet, Rotterdam, Netherlands
[9] Oncode Inst, Princess Maxima Ctr Pediat Oncol, Utrecht, Netherlands
[10] Univ Hosp Cologne, Inst Genome Stabil Ageing & Dis, Cologne Excellence Cluster Cellular Stress Respons, Cologne, Germany
[11] Buck Inst Res Aging, Novato, CA USA
[12] Columbia Univ, Irving Med Ctr, Dept Genet & Dev, New York, NY 10032 USA
来源
NATURE AGING | 2025年 / 5卷 / 02期
基金
美国国家卫生研究院;
关键词
CELLULAR SENESCENCE; LIFE-SPAN; AGE; ASSOCIATION; EXPRESSION; TOOL; ANNOTATION; PROVIDES; DECLINE; DISEASE;
D O I
10.1038/s43587-024-00762-5
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
The ovary is the first organ to age in the human body, affecting both fertility and overall health. However, the biological mechanisms underlying human ovarian aging remain poorly understood. Here we present a comprehensive single-nuclei multi-omics atlas of four young (ages 23-29 years) and four reproductively aged (ages 49-54 years) human ovaries. Our analyses reveal coordinated changes in transcriptomes and chromatin accessibilities across cell types in the ovary during aging, notably mTOR signaling being a prominent ovary-specific aging pathway. Cell-type-specific regulatory networks reveal enhanced activity of the transcription factor CEBPD across cell types in the aged ovary. Integration of our multi-omics data with genetic variants associated with age at natural menopause demonstrates a global impact of functional variants on gene regulatory networks across ovarian cell types. We nominate functional non-coding regulatory variants, their target genes and ovarian cell types and regulatory mechanisms. This atlas provides a valuable resource for understanding the cellular, molecular and genetic basis of human ovarian aging. The molecular and cellular mechanisms underlying ovarian aging are incompletely understood. Here the authors provide single-nuclei RNA and ATAC-seq of human ovarian tissue from four young and four reproductively aged donors, revealing coordinated transcriptomic and epigenomic changes across cell types and highlighting a role for mTOR signaling in reproductive aging.
引用
收藏
页码:275 / 290
页数:30
相关论文
共 77 条
  • [61] Skene N.G., Grant S.G., Identification of vulnerable cell types in major brain disorders using single cell transcriptomes and expression weighted cell type enrichment, Front. Neurosci, 10, (2016)
  • [62] Skene N.G., Et al., Genetic identification of brain cell types underlying schizophrenia, Nat. Genet, 50, pp. 825-833, (2018)
  • [63] Loh P.-R., Kichaev G., Gazal S., Schoech A.P., Price A.L., Mixed-model association for biobank-scale datasets, Nat. Genet, 50, pp. 906-908, (2018)
  • [64] Backman J.D., Et al., Exome sequencing and analysis of 454,787 UK Biobank participants, Nature, 599, pp. 628-634, (2021)
  • [65] Day F., Et al., Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria, PLoS Genet, 14, (2018)
  • [66] Tyrmi J.S., Et al., Leveraging Northern European population history: novel low-frequency variants for polycystic ovary syndrome, Hum. Reprod, 37, pp. 352-365, (2022)
  • [67] Rashkin S.R., Et al., Pan-cancer study detects genetic risk variants and shared genetic basis in two large cohorts, Nat. Commun, 11, (2020)
  • [68] Phelan C.M., Et al., Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer, Nat. Genet, 49, pp. 680-691, (2017)
  • [69] Jiang L., Zheng Z., Fang H., Yang J., A generalized linear mixed model association tool for biobank-scale data, Nat. Genet, 53, pp. 1616-1621, (2021)
  • [70] A global reference for human genetic variation, Nature, 526, pp. 68-74, (2015)