Abstract
Adrenal glands, vital for steroid secretion and the regulation of metabolism, stress responses and immune activation, experience age-related decline, impacting systemic health. However, the regulatory mechanisms underlying adrenal aging remain largely uninvestigated. Here we established a single-nucleus transcriptomic atlas of both young and aged primate suprarenal glands, identifying lipid metabolism and steroidogenic pathways as core processes impacted by aging. We found dysregulation in centripetal adrenocortical differentiation in aged adrenal tissues and cells in the zona reticularis region, responsible for producing dehydroepiandrosterone sulfate (DHEA-S), were highly susceptible to aging, reflected by senescence, exhaustion and disturbed hormone production. Remarkably, LDLR was downregulated in all cell types of the outer cortex, and its targeted inactivation in human adrenal cells compromised cholesterol uptake and secretion of dehydroepiandrosterone sulfate, as observed in aged primate adrenal glands. Our study provides crucial insights into endocrine physiology, holding therapeutic promise for addressing aging-related adrenal insufficiency and delaying systemic aging.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation, with accession number HRA004042 (human adrenocortical cells, https://ngdc.cncb.ac.cn/gsa-human/browse/HRA004042) and CRA009996 (monkey adrenal glands, https://ngdc.cncb.ac.cn/gsa/browse/CRA009996). The reference genomes of Macaca_fascicularis_6.0 and hg19 were downloaded from ensembl genome database (https://ensembl.org/). Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding authors upon reasonable request.
Code availability
The code used to perform bioinformatics analysis in this study is available at GitHub (https://github.com/wxb1998/R_adrenal).
References
Lerario, A. M., Mohan, D. R. & Hammer, G. D. Update on biology and genomics of adrenocortical carcinomas: rationale for emerging therapies. Endocr. Rev. 43, 1051–1073 (2022).
Hozumi, Y. et al. Expression and localization of the diacylglycerol kinase family and of phosphoinositide signaling molecules in adrenal gland. Cell Tissue Res. 362, 295–305 (2015).
Val, P. & Martinez, A. Editorial: adrenal cortex: from physiology to disease. Front. Endocrinol. 7, 51 (2016).
Dumbell, R., Matveeva, O. & Oster, H. Circadian clocks, stress, and immunity. Front. Endocrinol. 7, 37 (2016).
Nanba, K., Vaidya, A. & Rainey, W. E. Aging and adrenal aldosterone production. Hypertension 71, 218–223 (2018).
Deutschbein, T. et al. Age-dependent and sex-dependent disparity in mortality in patients with adrenal incidentalomas and autonomous cortisol secretion: an international, retrospective, cohort study. Lancet Diabetes Endocrinol. 10, 499–508 (2022).
Ng, T. P. et al. Dysregulated homeostatic pathways in sarcopenia among frail older adults. Aging Cell 17, e12842 (2018).
Weinstein, R. S. et al. Endogenous glucocorticoids decrease skeletal angiogenesis, vascularity, hydration, and strength in aged mice. Aging Cell 9, 147–161 (2010).
Michalakis, K. et al. Obesity in the ageing man. Metab. Clin. Experiment. 62, 1341–1349 (2013).
Tsui, A., Richards, M., Singh-Manoux, A., Udeh-Momoh, C. & Davis, D. Longitudinal associations between diurnal cortisol variation and later-life cognitive impairment. Neurology 94, e133–e141 (2020).
Chen, Y. C., Chen, Y. C., Chou, L. F., Chen, T. J. & Hwang, S. J. Adrenal insufficiency in the elderly: a nationwide study of hospitalizations in Taiwan. Tohoku J. Exp. Med. 221, 281–285 (2010).
Klouche, K. et al. Hypothalamic-pituitary-adrenal axis reactivity and dehydroepiandrosterone sulfate plasma concentrations in the critically ill elderly. Age Ageing 36, 686–689 (2007).
Pihlajoki, M., Dörner, J., Cochran, R. S., Heikinheimo, M. & Wilson, D. B. Adrenocortical zonation, renewal, and remodeling. Front. Endocrinol. 6, 27 (2015).
Rainey, W. E. & Nakamura, Y. Regulation of the adrenal androgen biosynthesis. J. Steroid Biochem. Mol. Biol. 108, 281–286 (2008).
Nguyen, A. D. & Conley, A. J. Adrenal androgens in humans and nonhuman primates: production, zonation and regulation. Endocr. Dev. 13, 33–54 (2008).
Vinson, G. P. Functional zonation of the adult mammalian adrenal cortex. Front. Neurosci. 10, 238 (2016).
Rainey, W. E., Carr, B. R., Sasano, H., Suzuki, T. & Mason, J. I. Dissecting human adrenal androgen production. Trends Endocrinol. Metab. 13, 234–239 (2002).
Hornsby, P. J. Aging of the human adrenal cortex. Sci. Aging Knowledge Environ. 2004, re6 (2004).
Muehlenbein, M. P. et al. Dehydroepiandrosterone-sulfate as a biomarker of senescence in male non-human primates. Exp. Gerontol. 38, 1077–1085 (2003).
Orentreich, N., Brind, J. L., Vogelman, J. H., Andres, R. & Baldwin, H. Long-term longitudinal measurements of plasma dehydroepiandrosterone sulfate in normal men. J. Clin. Endocrinol. Metab. 75, 1002–1004 (1992).
Zhang, H. et al. Single-nucleus transcriptomic landscape of primate hippocampal aging. Protein Cell 12, 695–716 (2021).
Ma, S. et al. Caloric restriction reprograms the single-cell transcriptional landscape of Rattus norvegicus aging. Cell 180, 984–1001.e22 (2020).
Jing, Y. et al. Single-nucleus profiling unveils a geroprotective role of the FOXO3 in primate skeletal muscle aging. Protein Cell 14, 497–512 (2023).
Zhang, Y. et al. Single-nucleus transcriptomics reveals a gatekeeper role for FOXP1 in primate cardiac aging. Protein Cell 14, 279–293 (2023).
Huang, D. et al. A single-nucleus transcriptomic atlas of primate testicular aging reveals exhaustion of the spermatogonial stem cell reservoir and loss of Sertoli cell homeostasis. Protein Cell 14, 888–907 (2022).
Dumontet, T. et al. Adrenocortical development: lessons from mouse models. Ann. Endocrinol. 79, 95–97 (2018).
Quinn, T. A. et al. Adrenal steroidogenesis following prenatal dexamethasone exposure in the spiny mouse. J. Endocrinol. 221, 347–362 (2014).
Conley, A. J. et al. Defining adrenarche in the rhesus macaque (Macaca mulatta), a non-human primate model for adrenal androgen secretion. Mol. Cell. Endocrinol. 336, 110–116 (2011).
Kemnitz, J. W. et al. Serum dehydroepiandrosterone sulfate concentrations across the life span of laboratory-housed rhesus monkeys. J. Med. Primatol. 29, 330–337 (2000).
Zhang, W. et al. A single-cell transcriptomic landscape of primate arterial aging. Nat. Commun. 11, 2202 (2020).
Li, J. et al. A single-cell transcriptomic atlas of primate pancreatic islet aging. Natl Sci. Rev. 8, nwaa127 (2021).
Wang, S. et al. Single-cell transcriptomic atlas of primate ovarian aging. Cell 180, 585–600.e19 (2020).
Kopito, R. R. Aggresomes, inclusion bodies and protein aggregation. Trends Cell Biol. 10, 524–530 (2000).
Suda, M. et al. Glycoprotein nonmetastatic melanoma protein B regulates lysosomal integrity and lifespan of senescent cells. Sci. Rep. 12, 6522 (2022).
Gulcan, H. O. & Duffel, M. W. Substrate inhibition in human hydroxysteroid sulfotransferase SULT2A1: studies on the formation of catalytically non-productive enzyme complexes. Arch. Biochem. Biophys. 507, 232–240 (2011).
Bergman, J. et al. The human adrenal gland proteome defined by transcriptomics and antibody-based profiling. Endocrinology 158, 239–251 (2017).
Huang, L. et al. Single-cell transcriptomes reveal characteristic features of cell types within the human adrenal microenvironment. J. Cell. Physiol. 236, 7308–7321 (2021).
Karimaa, M. et al. First-in-class small molecule to inhibit Cyp11a1 and steroid hormone biosynthesis. Mol. Cancer Ther. 21, 1765–1776 (2022).
Sheftel, A. D. et al. Humans possess two mitochondrial ferredoxins, Fdx1 and Fdx2, with distinct roles in steroidogenesis, heme, and Fe/S cluster biosynthesis. Proc. Natl Acad. Sci. USA 107, 11775–11780 (2010).
Trejter, M. et al. Visinin-like peptide 1 in adrenal gland of the rat. Gene expression and its hormonal control. Peptides 63, 22–29 (2015).
Lin, C. W. et al. VSNL1 co-expression networks in aging include calcium signaling, synaptic plasticity, and Alzheimer’s disease pathways. Front. Psychiatry 6, 30 (2015).
Freedman, B. D. et al. Adrenocortical zonation results from lineage conversion of differentiated zona glomerulosa cells. Dev. Cell 26, 666–673 (2013).
Ghosh, A. Cytophysiology of the avian adrenal medulla. Int. Rev. Cytol. 49, 253–284 (1977).
Košir, R. et al. Circadian expression of steroidogenic cytochromes P450 in the mouse adrenal gland-involvement of cAMP-responsive element modulator in epigenetic regulation of Cyp17a1. FEBS J. 279, 1584–1593 (2012).
Grabek, A. et al. The adult adrenal cortex undergoes rapid tissue renewal in a sex-specific manner. Cell Stem Cell 25, 290–296.e2 (2019).
Kim, J. H. & Choi, M. H. Embryonic development and adult regeneration of the adrenal gland. Endocrinol. Metab. 35, 765–773 (2020).
Shaikh, L. H. et al. LGR5 activates noncanonical Wnt signaling and inhibits aldosterone production in the human adrenal. J. Clin. Endocrinol. Metab. 100, E836–E844 (2015).
Nogueira, E. F. et al. Angiotensin-II acute regulation of rapid response genes in human, bovine, and rat adrenocortical cells. J. Mol. Endocrinol. 39, 365–374 (2007).
Devendran, A., Kar, S., Bailey, R. & Trivieri, M. G. The role of bone morphogenetic protein receptor type 2 (BMPR2) and the prospects of utilizing induced pluripotent stem cells (iPSCs) in pulmonary arterial hypertension disease modeling. Cells 11, 3823 (2022).
Liu, G.-H. et al. Aging Atlas: a multi-omics database for aging biology. Nucleic Acids Res. 49, D825–D830 (2021).
Richards, J. et al. A role for the circadian clock protein Per1 in the regulation of aldosterone levels and renal Na+ retention. Am J. Physiol. Renal Physiol. 305, F1697–F1704 (2013).
Manna, P. R., Dyson, M. T. & Stocco, D. M. Regulation of the steroidogenic acute regulatory protein gene expression: present and future perspectives. Mol. Hum. Reprod. 15, 321–333 (2009).
Hwang, W. C. et al. PLD1 and PLD2 differentially regulate the balance of macrophage polarization in inflammation and tissue injury. J. Cell. Physiol. 236, 5193–5211 (2021).
Qin, S. et al. Novel insight into the underlying dysregulation mechanisms of immune cell-to-cell communication by analyzing multitissue single-cell atlas of two COVID-19 patients. Cell Death Dis. 14, 286 (2023).
Zhang, Y., Liu, Q., Yang, S. & Liao, Q. CD58 immunobiology at a glance. Front. Immunol. 12, 705260 (2021).
Go, G. W. & Mani, A. Low-density lipoprotein receptor (LDLR) family orchestrates cholesterol homeostasis. Yale J. Biol. Med. 85, 19–28 (2012).
Hu, J., Zhang, Z., Shen, W. J. & Azhar, S. Cellular cholesterol delivery, intracellular processing and utilization for biosynthesis of steroid hormones. Nutr. Metab. 7, 47 (2010).
Spady, D. K., Bilheimer, D. W. & Dietschy, J. M. Rates of receptor-dependent and -independent low density lipoprotein uptake in the hamster. Proc. Natl Acad. Sci. USA 80, 3499–3503 (1983).
Nielsen, F. K. et al. H295R cells as a model for steroidogenic disruption: a broader perspective using simultaneous chemical analysis of 7 key steroid hormones. Toxicol. In Vitro 26, 343–350 (2012).
Petroglou, D. et al. The LDL-receptor and its molecular properties: from theory to novel biochemical and pharmacological approaches in reducing LDL-cholesterol. Curr. Med. Chem. 27, 317–333 (2020).
Lee, E. H. et al. Low dehydroepiandrosterone (DHEA) level is associated with poor immunologic response among people living with HIV/AIDS. J. Clin. Med. 11, 6077 (2022).
Stucker, S., De Angelis, J. & Kusumbe, A. P. Heterogeneity and dynamics of vasculature in the endocrine system during aging and disease. Front. Physiol. 12, 624928 (2021).
Dong, R. et al. Single-cell characterization of malignant phenotypes and developmental trajectories of adrenal neuroblastoma. Cancer Cell 38, 716–733.e6 (2020).
Lopez, J. P. et al. Single-cell molecular profiling of all three components of the HPA axis reveals adrenal ABCB1 as a regulator of stress adaptation. Sci. Adv. 7, eabe4497 (2021).
Rosenfield, R. L. Normal and premature adrenarche. Endocr. Rev. 42, 783–814 (2021).
Enge, M. et al. Single-cell analysis of human pancreas reveals transcriptional signatures of aging and somatic mutation patterns. Cell 171, 321–330.e14 (2017).
Hornsby, P. J. Biosynthesis of DHEAS by the human adrenal cortex and its age-related decline. Ann. N. Y. Acad. Sci. 774, 29–46 (1995).
Lin, X. L., Xiao, L. L., Tang, Z. H., Jiang, Z. S. & Liu, M. H. Role of PCSK9 in lipid metabolism and atherosclerosis. Biomed. Pharmacother. 104, 36–44 (2018).
Yu, H. et al. GPR146 deficiency protects against hypercholesterolemia and atherosclerosis. Cell 179, 1276–1288.e14 (2019).
Wang, S. et al. Deciphering primate retinal aging at single-cell resolution. Protein Cell 12, 889–898 (2021).
Li, J. et al. Determining a multimodal aging clock in a cohort of Chinese women. Med 4, 825–848.e13 (2023).
Li, H. et al. HALL: a comprehensive database for human aging and longevity studies. Nucleic Acids Res. 52, D909–D918 (2024).
Pandit, L., Kolodziejska, K. E., Zeng, S. & Eissa, N. T. The physiologic aggresome mediates cellular inactivation of iNOS. Proc. Natl Acad. Sci. USA 106, 1211–1215 (2009).
Georgakopoulou, E. A. et al. Specific lipofuscin staining as a novel biomarker to detect replicative and stress-induced senescence. A method applicable in cryo-preserved and archival tissues. Aging 5, 37–50 (2013).
Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).
Angelidis, I. et al. An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics. Nat. Commun. 10, 963 (2019).
Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).
Huynh-Thu, V. A., Irrthum, A., Wehenkel, L. & Geurts, P. Inferring regulatory networks from expression data using tree-based methods. PLoS ONE 5, e12776 (2010).
Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods 14, 1083–1086 (2017).
Efremova, M., Vento-Tormo, M., Teichmann, S. A. & Vento-Tormo, R. CellPhoneDB: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes. Nat. Protoc. 15, 1484–1506 (2020).
Acknowledgements
We thank Y. Liu, X. Xu, D. Huang, C. Liang and Z. Liu for their help in the experimental conduction. We thank J. Jia and S. Meng from the Institute of Biophysics, Chinese Academy of Sciences for their help in fluorescence-activated cell sorting (FACS), and S. Li from the Institute of Zoology, Chinese Academy of Sciences for her help in image scanning of immunohistochemical staining. We are also grateful to L. Bai, J. Chen, Q. Chu, J. Lu, Y. Yang, R. Bai, L. Tian and X. Li for administrative assistance. This work was supported by the National Key Research and Development Program of China (2022YFA1103700), the National Natural Science Foundation of China (82125011, 81921006, 92149301, 82122024, 92168201, 92049116 and 82361148131), the National Key Research and Development Program of China (2020YFA0804000, 2020YFA0112200, 2021YFF1201000, 2022YFA1103800, the STI2030-Major Projects-2021ZD0202400 and 2021YFA1101000), the National Key Research and Development Program of China (82330044, 32341001, 92049304, 32121001, 82192863, 82361148130, 82301758, 82271600, 82322025 and 82071588), CAS Project for Young Scientists in Basic Research (YSBR-076 and YSBR-012), the Program of the Beijing Natural Science Foundation (Z230011), the Informatization Plan of Chinese Academy of Sciences (CAS-WX2022SDC-XK14), New Cornerstone Science Foundation through the XPLORER PRIZE (2021-1045), Youth Innovation Promotion Association of CAS (E1CAZW0401, 2022083 and 2023092), Young Elite Scientists Sponsorship Program by CAST (2021QNRC001), Excellent Young Talents Program of Capital Medical University (12300927), the Project for Technology Development of Beijing-affiliated Medical Research Institutes (11000023T000002036310), and Excellent Young Talents Training Program for the Construction of Beijing Municipal University Teacher Team (BPHR202203105), the Quzhou Technology Projects (2022K46).
Author information
Authors and Affiliations
Contributions
W. Z., G.-H.L., and J.Q. designed and coordinated the studies. Q.W. performed the majority of experiments; X.W. performed the snRNA-seq and RNA-seq analyses. S.M. provided guidance on snRNA-seq and RNA-seq analyses. Q.W., X.W. and B.L. wrote the first draft of the manuscript, and B.L. wrote the revised draft of the manuscript. F.Z. and Q.Z. aided human plasma sample collection. Y.F. helped on immunohistochemical studies. Y.J. provided the guidance for isolating cell nuclei and prepared samples for snRNA-seq. Y.D., M.X., G.X. and J. Yang helped on experiments, such as western blot and in vitro experiments. J.L., Y.Z. and C.L. helped on snRNA-seq analysis. S.S., J. Ye, S.W. and J.C.I.B. supervised the project. All authors contributed critical review of the paper.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Aging thanks Antonio Lerario and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Phenotypic features underlying adrenal aging in cynomolgus monkeys.
(a) Dot plots showing the correlations between DHEA-S, aldosterone, cortisol, and age in human plasma, respectively (men, n = 141; women, n = 111). The color of dot indicates the sex of plasma-derived volunteers. (b) Plasma adrenal hormone levels (DHEA-S, aldosterone, cortisol) in young (4–6 years, n = 17), and elderly (16–18 years, n = 17) cynomolgus macaques. (c) Representative image, weight, and adrenal gland/body ratio of the intact adrenal gland tissues from young (n = 12) and old (n = 16) cynomolgus monkeys. (d) IHC staining for p21Cip1 in cynomolgus monkey adrenal tissues, representative images of tissue patterns (left) and quantification (right) are shown. The percentage of p21Cip1-positive cells is normalized to the young group as the reference for calculating fold change. Young, 4-5 years, n = 12; middle-aged, 10–12 years, n = 6; and elderly, 16–18 years, n = 17. (e) IHC staining for Aβ1-40 in cynomolgus monkey adrenal tissues, representative images of tissue patterns (left) and quantification (right) are shown. Aβ1-40-positive area is normalized to the young group as the reference for calculating fold change. Young, n = 12; middle-aged, n = 6; and elderly, n = 17. (f) Sudan black staining of cynomolgus monkey adrenal tissues (Young, n = 7; old, n = 8 monkeys). For bar graphs, data are presented as mean ± s.e.m. Statistical significance is determined in b, c, P value by two-tailed unpaired Student’s t-test, in d-f using a two-tailed non-parametric Mann-Whitney U test. c, scale bars, 1 cm. d-f scale bar = 20 µm.
Extended Data Fig. 2 Molecular features of adrenal aging in cynomolgus monkeys.
(a) Bar plot showing the number of cells across different samples. Line charts showing the fraction of reads mapped to genome across different samples. (b) Box plots showing the distribution of nUMI (left) and gene number (right) per cell across different samples. (c) Scatter plot showing the Spearman correlation between different cell types. The size and color of dots represent the correlation between different cell types. (d) Stacked bar plot showing the cell type proportions in the young and old groups. (e) IHC staining for CYB5A in cynomolgus monkey adrenal tissues (Young, n = 12; old, n = 17 monkeys). Representative images of tissue patterns for the whole and zoom (left) and quantification (right) are shown. The dashed lines indicate the boundary of the ZG, ZF, ZR and M, respectively. Width ratio of CYB5A-positive area/cortex is normalized to the young group as the reference for calculating fold change. For bar graphs, data are presented as mean ± s.e.m. Statistical significance is determined in e using a two-tailed non-parametric Mann-Whitney U test. e, scale bar = 50 µm. For boxplots, the lower and upper hinges represent the first and third quartiles, the horizontal line in the box is the median, and the whiskers extend from the hinge to the largest (smallest) value no further than 1.5 × inter-quartile range from the hinge. Data beyond the end of the whiskers are categorized as ‘outlying’ points.
Extended Data Fig. 3 Transcriptional fluctuations in aged NHP adrenal glands.
(a) Curve charts and dot plots showing the expression of the representative DEGs across different clusters along the pseudotime trajectory. (b) Box plots showing the gene set scores of representative pathways across different clusters in young and aged groups during regeneration of adrenocortical cells. (c) Dot plots showing the correlation between the cell identity score and transcriptional noise in the young and aged monkey adrenal glands. (d) Dot plots showing the correlation between the average gene expression level of the transcription noise correlated genes and transcriptional noise in ZR between old and young samples.
Extended Data Fig. 4 Molecular signatures underpinning NHP adrenal gland aging.
(a) Heatmap showing the aging-related DEGs included in Aging Atlas database. (b) Bar plots showing representative pathways of upregulated (left) and downregulated (right) DEGs included in Aging Atlas database. (c) Heatmap showing expression of upregulated DEGs in bulk RNA-seq across different cell types of young and aged groups. Gene expression levels across different DEGs are Z-score transformed. (d) Box plot showing the gene set scores of CREM target genes across different cell types in young and aged groups. (e) Bar plot showing representative pathways of CREM target genes.
Extended Data Fig. 5 Chronic inflammation within NHP adrenal aging.
(a) IHC staining for CD45 in cynomolgus monkey adrenal tissues, representative images of tissue patterns for the whole and zoom (left) and quantification (right) are shown. The percentage of CD45-positive cells is quantified as fold changes (old vs. young). Young, n = 7; and elderly, n = 8. (b) IHC staining for CD3 in cynomolgus monkey adrenal tissues, representative images of tissue patterns for the whole and zoom (left) and quantification (right) are shown. The percentage of CD3-positive cells is quantified as fold changes (old vs. young). Young, n = 7; elderly, n = 8. (c) IHC staining for CD163 in cynomolgus monkey adrenal tissues, representative images of tissue patterns for the whole and zoom (left) and quantification (right) are shown. The percentage of CD163-positive cells is quantified as fold changes (old vs. young). Young, n = 7; elderly, n = 8. (d) Dot plot showing the age-specific cell–cell interaction pairs in indicated cell types between young and aged groups. The font colors of cell interactions correspond to different age groups. Blue represents young-specific cell pairs, while red represents old-specific cell pairs. The size of the dots represents the -Log10 P value and the color of dots indicates the mean value of expression levels. (e) Bar plot showing representative pathways of upregulated (up) and downregulated (bottom) DEGs across different cell types with aging. (f) Left, upset map showing the distribution of common and unique upregulated aging-related DEGs among different adrenocortical cell types. Right, heatmaps showing the representative pathways of DEGs across different modules. For bar graphs, data are presented as mean ± s.e.m. Statistical significance is determined in a-c, P value by two-tailed non-parametric Mann-Whitney test. a-c, the dashed lines indicate the boundary of the ZG, ZF, ZR and M, respectively. a-c, scale bar = 20 µm.
Extended Data Fig. 6 Reduced LDLR hinders DHEA-S secretion in adrenocortical cells.
(a) Western blot images (left) and quantification (right) showing LDLR protein level in young (n = 4), middle-aged (n = 3) and old (n = 4) cynomolgus monkey adrenal gland tissues. (b) GSEA enrichment curves show no significant change in the aging-related pathway after LDLR knockout in NCI-H295R cell. (c) Volcano plot showing the results of differential expression analysis by bulk RNA-seq in NCI-H295R cells transfected with CRISPRko sg-NTC and sg-LDLR lentivirus. Each dot represents a gene. For the western blot analysis, in a, GAPDH is used as the loading control. For bar graphs, data are presented as mean ± s.e.m. b, c, n = 4 biological replicates. Statistical significance is determined in a, P value by two-tailed unpaired Student’s t-test.
Supplementary information
Supplementary Information
Supplementary methods, Fig. 1 (the uncropped blots) and Fig. 2 (examples of gating strategy) and the full legends for Supplementary Tables 1–12.
Supplementary Tables 1–12
Legends and descriptive captions of all the supplementary tables listed in Supplementary Information.
Source data
Source Data Fig. 1
Statistical source data.
Source Data Fig. 2
Statistical source data.
Source Data Fig. 6
Statistical source data.
Source Data Extended Data Fig. 1
Statistical source data.
Source Data Extended Data Fig. 2
Statistical source data.
Source Data Extended Data Fig. 5
Statistical source data.
Source Data Extended Data Fig. 6
Statistical source data.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Wang, Q., Wang, X., Liu, B. et al. Aging induces region-specific dysregulation of hormone synthesis in the primate adrenal gland. Nat Aging 4, 396–413 (2024). https://doi.org/10.1038/s43587-024-00588-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s43587-024-00588-1