Data availability
All sequencing data generated in this study, including RNA-seq, ATAC-seq and CUT&Tag-seq data, have been deposited in the Genome Sequence Archive (GSA) at the National Genomics Data Center, China National Center for Bioinformation, under BioProject accession number PRJCA047902. Public datasets were downloaded from Gene Expression Omnibus database (accession codes GSE54651, GSE98965 and GSE84580). Source data are provided with this paper.
Code availability
The code of performing all analyses is available at Zenodo at https://doi.org/10.5281/zenodo.7683896 (ref. 75).
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Acknowledgements
This work was supported by grants from the National Key Research and Development Project of China, including nos. 2024YFA1803203 (H.-Z.C.) and 2021YFA0804903 (D.-P.L.); the National Natural Science Foundation of China, including nos. 82271615 (J.-F.P.), 82225007 (H.-Z.C.), 32501040 (X.W.), 32300987 (S.-Y.Q.), 82571778 (X.W.) and 82400469 (X.-K.L.); the National Science and Technology Major Project, including nos. 2024ZD0537700 (D.-P.L.) and 2023ZD0504500 (X.W.); Natural Science Foundation of Liaoning Province of China-Youth Fund Category A, no. 2026JH6/101100008 (J.-F.P.); the Xing Liao Ying Cai Programs-Young Talents (J.-F.P.); the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, no. CIFMS2021-I2M-1-016 (D.-P.L.). We thank State Key Laboratory of Common Mechanism Research of Major Diseases Platform for consultation and instrument availability that supported this work.
Ethics declarations
Competing interests
J.-F.P., S.-Y.Q., S.-S.C., X.-Q.F., L.-Y.L., J.Y. and A.T. are inventors on a granted patent related to this work (CN 118831075 B; applicant, China Medical University), which covers a compound pharmaceutical composition for delaying skeletal muscle ageing and its applications. The other authors declare no competing interests.
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Extended data
Extended Data Fig. 1 Quality control of the diurnal transcriptome of eight tissues from young and aged mice.
a, Heatmap showing the Pearson correlations (colour) across individual samples ordered via hierarchical clustering. Columns are annotated by time and age group, and the rows are annotated by the tissue type of individual samples. b, Uniform manifold approximation and projection (UMAP) plot showing the samples from in-house data (triangle) and GSE54651 (circle). Dot colour indicates tissue origin. c, Box plot comparing the differences in entropy between the young and aged groups within the same tissue (n = 18 per group per tissue). d, PCA plot of all gene expression profiles for the eight organs from young (blue) and aged mice (red) across all time points, with the percentage of explained variance shown on the axes. e, Cumulative distribution of the phases of rhythmic gene expression in different tissues (colours) from young (left) and aged mice (right) throughout the day-night cycle. Heatmap showing z-score scaled ratio (colour) of rhythmic genes reaching peak time in individual tissues (bottom panel). f, Number of rhythmic genes in individual tissues from young and aged mice. Data are presented as median values +/- SEM (c). The center line indicates the median; the box represents the interquartile range (25th-75th percentiles); whiskers extend to 1.5-fold of the interquartile range. P values were calculated from (c) two-sided Wilcoxon test (* P < 0.05, ** P < 0.005, *** P < 0.001, **** P < 0.0001).
Extended Data Fig. 2 Diurnal transcriptomes of individual tissues and sub-tissues exhibited heterogeneous alterations during ageing.
a-l, 24-hour oscillating genes in various tissues are displayed as follows: (a) liver (LV), (b) skeletal muscle (SM), (c) white adipose tissue (WAT), (d) brown fat (BF), (e) kidney (KD), (f) spleen (SP), (g) aortic arch (AR), (h) thoracic aorta (TA), (i) abdominal aorta (AA), (j) tip of the heart (TH), (k) left heart (LH), and (l) right heart (RH). Data for each tissue are presented from top left to bottom right according to absolute numbers, relative ratios, amplitude distributions, phase distributions, and transcriptomic expressions of oscillating genes.
Extended Data Fig. 3 Ageing reprogrammed diurnal alignment.
a, Proportions of significant intra-tissue correlations between rhythmic genes relative to all pairwise correlations in young (blue) and aged (red) mice. Correlations with B–H adjusted P values < 0.05 are considered significant. b, Proportion (log2) (colours) of common rhythmic pathways between tissues in the young (top right corner) and aged groups (bottom left corner). c, Bar plot at the top showing the number of significant oscillating pathways in each tissue from young and aged mice. Heatmap showing the z-score normalized activities (colours) of significant rhythmic pathways in individual tissues from young and aged mice. Pathway activities were calculated by GSVA tools and significant oscillatory pathways were inferred by JTK cycle algorithm. d, Phases of significantly representative rhythmic pathways in glucose metabolism-related GO terms across young and aged tissues. Circle colour and sector size denote pathway phases. Pathway phases were calculated by JTK cycle algorithm. e, Glucose tolerance was determined using the GTT in young and aged mice throughout the diurnal cycle. Blood glucose levels of GTT were measured at multiple time points after intraperitoneal injection of glucose at individual zeitgeber time points (left), and the corresponding AUC was determined (Young: ZT2/6 n = 8, ZT10 n = 14, ZT14 n = 10, ZT18 n = 12, ZT22 n = 9; Aged: ZT2 n = 8, ZT6 n = 6, ZT10 n = 12, ZT14 n = 10, ZT18/22 n = 7) (right). Data are presented as means ± SEM. P values were from (a) Spearman correlation, (e) JTK cycle algorithm.
Extended Data Fig. 4 Diurnal trends of redox-related signalling were commonly reprogrammed by ageing across tissues.
a, Bar plot showing the B–H adjusted significance (-log10 P value) of the associations between all identified factors from the MEFISTO tool and zeitgeber time. b, Bar plot showing the number of core clock components oscillating in individual tissues from young and aged mice (top). Heatmap showing the z-score-normalized expressions of the core clock components in 12 tissues. Columns are annotated by age group and tissue type. c, WGCNA analysis identified coexpression modules from multi-organ diurnal transcriptomes. The modules were categorized into 27 tissue-specific and 57 cross-tissue groups based on the proportions of tissue-specific genes. Each column indicates each module. The modules are organized by hierarchical clustering and display from top to bottom according to the proportions of tissue-specific genes, proportions of oscillating genes, mean eigengene values in the young and aged groups, and significantly enriched pathways (coloured squares) in the GO database. Among the cross-tissue modules, those enriched in Ageing pathways or Circadian rhythm pathways in the GO database were selected for further analysis in Extended Data Fig. 4d–f. d-e, Identification of age-associated cross-tissue modules. Significance and corresponding ranks of each module associated with ages (d). B–H adjusted P values (-log10) were calculated by comparing the differences in module eigengenes between the young and aged groups using the two-sided Wilcoxon test. Labelled dots are the modules that were enriched in Ageing pathways in GO database in Extended Data Fig. 4c. (**** P < 0.0001) (e). f, Identification of rhythm-associated cross-tissue modules. Rhythmic ratios and corresponding ranks among all the modules. Rhythmic ratios were the proportion of rhythmic genes to all genes in the module. Labelled dots are modules that were enriched in Circadian rhythm pathways in GO database in Extended Data Fig. 4c. g-h, Scatter plot showing the pairwise Pearson correlations of pathway activities of the three pathways, including Ageing, Circadian rhythm, and Response to oxidative stress in GO database across diverse mouse (g) and baboon (GSE98965) (h) tissues, coloured by tissue type. i, Bar plot showing the enriched pathways of genes whose rhythmicity was reprogrammed by ageing in epidermal stem cells (GSE84580). The colour denotes the B–H adjusted P value, and the dot size denotes the gene count. Panels g, h and i created in BioRender; Lab 5. https://biorender.com/j831mdj (2026). P values were from (a, d) Spearman correlation with B–H corrections, (g, h) Spearman correlation, or (i) one-sided hypergeometric test with B–H correction.
Extended Data Fig. 5 Redox rhythms exhibited tissue-shared disruptions with age and OP1-NM restored redox rhythms in liver (LV) and skeletal muscle (SM).
a, Relative H2O2 levels throughout the diurnal cycle in six tissues from young (upper panel) and aged (lower panel) mice (Young: SP, KD, Heart, BF, WAT n = 5; AA n = 3; Aged: SP, KD, Heart, WAT n = 6; AA n = 4; BF n = 5 per time point). b-c, Quantification of NADH (b, Young/Aged n = 5, OP1-NM n = 6 per time point) and NAD+ (c, n = 5 per time point) levels across diurnal cycle in LV of young, aged mice, and OP1-NM-treated aged mice. d-e, Quantification of NADH (d) and NAD+ (e) levels across diurnal cycle in SM of young, aged mice, and OP1-NM-treated aged mice (n = 5 per time point). f, Bar plot showing the assessment of overall physical and locomotion functions by metabolic cages, including total water consumed, total food consumed, total activity and rectal temperature of OW and OP1-NM-treated aged mice (n = 4 per group). g, Fasting blood glucose concentrations were measured in individual groups after fasting mice for 4 h (YW/OP1-NM n = 8, OW/OP3-NM n = 9, OP2-NM n = 7). h, The ratio of muscle fibres of different sizes to the total number of fibres (n = 4 per group). Data are presented as means ± SEM. P values were calculated using (f) two-tailed unpaired t-test, (g) Kruskal–Wallis test followed by Dunn’s multiple comparisons hoc test, (h) two-way analysis of variance (ANOVA) with Bonferroni post-hoc corrections, or (a-e) JTK_Cycle algorithm. Only significant comparisons are labelled (* YW vs. OW, # OP1-NM vs. OW, $ OP2-NM vs. OW, & OP3-NM vs. OW; # P < 0.05, ** or ## P < 0.005, *** or $$$ P < 0.001, **** or &&&& P < 0.0001).
Extended Data Fig. 6 Impact of altering absolute redox levels by oxidant or pro-oxidant on physical function in aged mice.
a-b, Blood glucose levels of ITT (a, YW n = 8, OW n = 9, ON n = 6, OM n = 3) and GTT (b, YW/OM n = 6, OW/ON n = 5) were measured across time after injection at active phase, and with corresponding AUC (right) shown. c-d, Serum insulin concentrations (c, n = 5 per group) and fasting blood glucose concentrations (d, YW n = 8, OW n = 9, ON n = 6, OM n = 3) in individual groups after fasting for 4 h. e-i, Bar plots showing the assessment of overall physical and locomotion functions, including grip strength (e, YW n = 14, OW n = 8, ON n = 6, OM n = 5), running distance on the treadmill (f, YW n = 9, OW n = 14, ON n = 6, OM n = 4), latency to fall (g, YW n = 13, OW n = 15, ON/OM n = 4), forelimb and hindlimb stride lengths (h-i, YW n = 17, OW n = 7, ON n = 6, OM n = 3) in individual groups. Data are presented as means ± SEM. P values were calculated using (a-right panel, b-right panel, c-i) one-way or (a-left panel, b-left panel) two-way analysis of variance (ANOVA) with Bonferroni post-hoc corrections. Only significant comparisons are labelled (*, YW vs. OW; * P < 0.05, **** P < 0.0001).
Extended Data Fig. 7 Impact of altering absolute redox levels on ageing-related dysregulations in LV and SM.
a, Representative images of ageing-associated alterations in SM in YW, OW, ON, and OM groups: Hematoxylin and Eosin (H&E) staining (left; bar = 100 μm), Sirius red staining (middle; bar = 100 μm), and transmission electron microscopy (right; bar = 2 μm). b-d, Quantification of ageing-associated alterations in SM across groups. Fibre cross-sectional area (CSA) for assessing myofibre size by H&E staining (b, n = 4 per group). The ratio of muscle fibres of different sizes to the total number of fibres (c, n = 4 per group). Interstitial fibrosis was measured by Sirius red staining (d, YW n = 8, OW n = 11, ON n = 6, OM n = 3). e-f, Mitochondria morphology in SM assessed by transmission electron microscopy. Average area of mitochondria under different regimens (e). Proportional distribution of mitochondrial area in individual groups (f, n = 4 per group). g, Relative mitochondrial DNA copy number, determined as the ratio of mitochondrial genes (D-loop and Cytb) to nuclear DNA (18S) in SM of individual groups (YW n = 8, OW n = 7, ON n = 4, OM n = 5). h-i, o-p, Representative images of ageing markers (p21, p53 and p16) by western blot in SM (h) and LV (o). Statistical analyses are shown in SM (i, internal control: OW lane 1) and LV (p, internal control: YW lane 1) from the individual groups (n = 4 per group for p53 and p21, YW n = 10, OW n = 8, ON/ON n = 7 for p16). j-n, Representative images and quantification of ageing-associated alterations in LV. Interstitial fibrosis for measuring hepatic fibrosis was measured by Sirius red staining (k, YW n = 7, OW n = 8, ON n = 4, OM n = 3, bar = 100 μm). SA-β-gal-positive area for detecting senescent cells by SA-β-gal staining (l, YW/ON n = 6, OW n = 11, OM n = 4, bar = 200 μm). Expression of inflammatory cytokines (Il1b and Il6) assessed by qPCR (m, YW n = 6, OW n = 8, ON/OM n = 5). IL-6 concentrations in plasma were measured by ELISA (n, YW n = 6, OW/OM n = 7, ON n = 4). Data are presented as means ± SEM. P values were calculated using (d-e, i-p16, p-p53 and p16, l, m-Il6) Kruskal–Wallis test followed by Dunn’s multiple comparisons hoc test, (b, d, g, i-p53 and p21, k, m–Il1b, n, p-p21) one-way, (c, f) two-way analysis of variance (ANOVA) with Bonferroni post-hoc corrections. Only significant comparisons are labelled (*, YW vs. OW; $, ON vs. OW; &, OM vs. OW; $ P < 0.05, ** or $$ or && P < 0.005, **** P < 0.0001).
Extended Data Fig. 8 OP1-ND intervention significantly reversed the ageing-related features in liver and skeletal muscle.
a, Relative H2O2 levels at ZT18 in LV (left) and SM (right) of aged mice treated with DS from ZT10.5 to ZT18 for one week, compared to water controls (n = 4 per group). b, Body weight of mice from different groups (YW n = 15, OW/OP1-ND n = 20, OD n = 12). c, Blood glucose levels in GTT were measured at multiple time points after intraperitoneal injection of glucose (left), and corresponding AUC were shown (right) (YW n = 10, OW n = 13, OP1-ND/OD n = 12). d, The ratio of skeletal muscle fibres of different sizes to the total number of fibres (YW n = 5, OW/OP1-ND n = 9, OD n = 8). e, Proportional distribution of the mitochondrial area in individual groups, assessed by transmission electron microscopy (YW n = 3, OW/OP1-ND/OD n = 4). f, Relative mitochondrial DNA copy number, determined as the ratio of mitochondrial genes (D-loop and Cytb) to nuclear DNA (18S) in SM of individual groups (YW n = 7, OW/OP1-ND n = 9, OD n = 5). g, IL-6 concentrations in plasma were measured by ELISA (YW/OP1-ND/OD n = 7, OW n = 8). Data are presented as means ± SEM. P values were calculated using (a) two-tailed unpaired t-test, (b, f–Cytb, g) Kruskal–Wallis followed by Dunn’s multiple comparisons hoc test or (c-right panel, f–D-loop) one-way or (c-left panel, d-e) two-way analysis of variance (ANOVA) with Bonferroni post-hoc corrections. Only significant comparisons are labelled (*, YW vs. OW; #, OP1-ND vs. OW; * or # P < 0.05, ## P < 0.005, *** or ### P < 0.001, **** or #### P < 0.0001).
Extended Data Fig. 9 Redox rhythm restoration partially reprogrammed gene expressions and chromatin accessibilities in ageing-related functional pathways.
a, Principal component analysis (PCA) plot of gene expression profiles from the five indicated groups (colours) in skeletal muscle (SM). b, Bar plot showing the number of differentially expressed genes (DEGs) in skeletal muscle for each intervention compared with OW, separated into downregulated (blue) and upregulated (red) DEGs. c, Venn diagrams showing the overlap of DEGs between each intervention and the YW group, separated into downregulated (top) and upregulated (bottom) genes. d, Dot plot showing GO enrichment of ageing-related and downregulated DEGs in SM from OP1-NM, OP2-NM, and OP3-NM groups. Ageing-related downregulated DEGs were defined as the common subset of downregulated genes shared between YW and each intervention group (OP1-NM, OP2-NM, or OP3-NM). Colour denotes B–H adjusted P values, and dot size denotes gene ratio. e, Heatmaps showing the z-score-scaled pathway activities (GSVA score) of ageing-related pathways in SM. Ageing-related pathways were defined as the pathways with different GSVA scores in OW and YW groups. f, Number of gained rhythmic genes in YW, OP1-NM, and OP2-NM groups, compared with OW group. g, Phase distribution of commonly gained rhythmic genes in both OP1-NM and OP2-NM groups. Colour indicates the group. h, Heatmap showing the z-score-scaled GSVA score of OP1-NM-rhythmic pathways in OP1-NM and OP2-NM groups. i-j, Density plot (top) shows the normalized reads density (axis) across genomic coordinates (x axis) from 2 kb upstream to 2 kb downstream relative to the reference point, including TES region (transcription end site, i) and center (the midpoint of each gene, j) in five groups. Heatmaps (bottom) show signal intensity (colour) of ATAC-seq data across the detected regions, with brighter colours indicating lower signal intensity. k, Number of DEPs in individual groups versus OW, separated into downregulated and upregulated peaks. l, Venn diagrams showing the percentage of ageing-related peaks (DEPs of YW) in DEPs of OP1-NM, OP2-NM, and OP3-NM interventions, separated into downregulated (top) and upregulated peaks (bottom). m, GO enrichment analysis of ageing-related downregulated DEPs in individual groups. P values were from (d, m) one-sided hypergeometric test with B–H correction.
Extended Data Fig. 10 ClockC195S mutation was significantly associated with ageing characteristics.
a-b, Representative motifs enriched among gained rhythmic genes of YW (a) and OP2-NM groups (b) relative to OW group in RNA-seq data. c, Representative motifs enriched in ageing-related upregulated DEPs in ATAC-seq data from OP1-NM livers. d, Representative immunoblot showing the reduced thiol of cysteine (Cys-SH) of CLOCK proteins in the liver over a 24-hour period for YW, OW, OP1-ND, and OD groups throughout the diurnal cycle (n = 3 per group; internal control: YW ZT6). e, Density plot showing the density of CLOCK occupancy across the genome in OW (blue) and OP1-NM group (red). f, Bar plot indicating numbers of the upregulated (red) or downregulated (blue) CLOCK occupancy in OP1-NM group across genomic features in CUT&Tag data (n = 3 per group). g, Dot plot showing the enriched GO pathways of downregulated CLOCK-binding regions in OP1-NM group. h, H2O2 levels throughout diurnal cycle in liver of ClockC195S and ClockWT mice at 3–4 months (ClockWT: ZT0/6/12/18 n = 6, ZT24 n = 5; ClockC195S: ZT0 n = 4, ZT6 n = 6, ZT12/18/24 n = 5). i, PCA plot showing individual samples in ClockC195S and ClockWT groups in ATAC-seq (left) and RNA-seq (right). j, Violin plot comparing the open accessibilities of genes whose rhythmicity was reprogrammed by ageing (left) and random genes with the same number (right) in ClockC195S and ClockWT group (3–4 months; n = 3 per group). The expression for each gene is represented by log2 count per million (CPM) of sequencing reads. k-l qPCR analysis of Ucp1 (k) and Il6 (l) expression in brown fat (BF) from indicated groups (YW n = 7, OW/OP2-NM n = 8, OP1-NM n = 9), with young mice (YW, 3–6 months) and old mice (OW, OP1-NM and OP2-NM, 18-21 months) following the same experimental protocol as described in Fig. 2a. Data are presented as (d, h, k, l) means ± SEM and (j) median values +/- SEM. The center line indicates the median; the box represents the interquartile range (25th-75th percentiles); whiskers extend to 1.5-fold of the interquartile range. P values were calculated using (a-c) hypergeometric test, (g) one-sided hypergeometric test with B–H correction, (h) JTK_Cycle algorithm, (j) Wilcoxon test, and (k-l) Kruskal–Wallis test followed by Dunn’s multiple comparisons hoc test.
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Wang, X., Cui, SS., Li, XK. et al. Redox rhythms promote fitness by modulating ageing-dependent reprogramming. Nat Metab (2026). https://doi.org/10.1038/s42255-026-01515-x
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DOI: https://doi.org/10.1038/s42255-026-01515-x