Multi‐Omics Integration Reveals Incomplete Reactivation of Developmental Cell‐Cycle Programs in Adult Human Infarcted Hearts

Figures

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  FIGURE 1. Multi‐omics integration framework for characterizing incomplete cell‐cycle program reactivation in adult infarcted hearts. Developmental datasets (left) comprising snRNA‐seq, bulk RNA‐seq, and ATAC‐seq were used to define fetal and pediatric cell‐cycle signatures. Adult datasets (right) comprising snRNA‐seq and spatial transcriptomics were analyzed in parallel. In both contexts, cardiomyocytes were classified into cell‐cycle‐active (ccCM+) and cell‐cycle‐inactive (ccCM−) states, and co‐expression networks were constructed using hdWGCNA. Cross‐dataset integration (bottom) identified developmental programs with insufficient adult reactivation, which were further characterized through regulatory network inference (SCENIC), intercellular communication analysis (CellChat), and functional enrichment.

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  FIGURE 2. Identification and characterization of cell‐cycle‐active cardiomyocytes in adult infarct zone. (A) Cell‐type composition across conditions. (B) UMAP visualization of cardiomyocytes colored by tissue region. (C) Per‐donor ccCM+ proportion (n = 4 control, n = 5 RZ, n = 4 IZ). Kruskal–Wallis test with post hoc Mann–Whitney U tests (Holm‐adjusted). (D) Dot plot of selected dedifferentiation and stress‐adaptation markers across regions and cell‐cycle states. Dot size indicates percentage of expressing cells; color intensity represents average expression level. (E) KEGG pathway enrichment of ccCM+ differentially expressed genes. (F) Module–trait correlation heatmap from hdWGCNA. Modules M5 and M6 show positive associations with the ccCM+ state. (G) Venn diagram defining AMI hub genes as the intersection of M5/M6 module genes and ccCM+‐upregulated DEGs (right: Functional enrichment of hub genes).

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  FIGURE 3. Multi‐omics characterization of cell‐cycle‐active cardiomyocytes during cardiac development. (A) Cell‐type composition across developmental stages. (B) UMAP visualization of cardiomyocytes by sample origin (fetal and pediatric). (C) Left: Cardiomyocyte subclustering into 15 transcriptionally distinct groups. Right: CcCM+ and ccCM− classification. (D) Volcano plot of differential gene expression between ccCM+ and ccCM− in developmental hearts. Representative proliferation markers and maturation markers are labeled. (E) Venn diagram showing overlap among fetal‐upregulated genes identified across three data modalities (bulk RNA‐seq, snRNA‐seq, and ATAC‐seq), defining the developmental cross‐validated gene set. Right: KEGG pathway enrichment of the cross‐validated set. (F) Module–trait correlation heatmap from hdWGCNA. Modules M3 and M6 show positive correlations with the ccCM+ state. (G) Venn diagram defining developmental hub genes as the intersection of M3/M6 module genes and ccCM+‐upregulated DEGs (right: GO and KEGG enrichment of hub genes).

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  FIGURE 4. Cross‐context comparison of cell‐cycle programs and regulatory networks. (A) Venn diagram showing overlap between AMI (M5/M6) and developmental (M3/M6) hdWGCNA module genes, defining hdWGCNA‐shared genes (bottom: GO and KEGG enrichment). (B) Venn diagram showing overlap between AMI and developmental ccCM+‐upregulated DEGs, defining DEG‐shared genes (bottom: GO and KEGG enrichment). (C) Sequential multi‐omics filtering flowchart for candidate gene identification. Developmental inclusion criteria (top) and adult exclusion filters were applied as described in Methods; gene counts at each step are indicated. (D) Network visualization integrating the five candidate genes with SCENIC‐identified transcription factors and enriched pathways in adult hearts. Node shapes distinguish candidate genes, transcription factors associated with ccCM+ or ccCM− states, and enriched GO/KEGG terms (see inset legend). (E) CellChat pathway‐level incoming signaling strength to each cell type in adult AMI (left) versus controls (right). Color intensity denotes relative signaling strength.

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  FIGURE 5. Spatial validation and experimental characterization of candidate genes. (A) Proportion of spots expressing MKI67 and each candidate gene in IZ versus RZ from 10× Visium spatial transcriptomic data. Wilcoxon rank‐sum tests with Benjamini–Hochberg correction. (B) Experimental timeline for iPSC‐CM differentiation and treatment conditions. (C) qPCR analysis of candidate gene expression in iPSC‐CMs at Day 14 (immature) and Day 90 (mature) under normoxic and 12‐h hypoxic conditions. Day 14 cardiomyocytes were additionally treated with or without CHIR99021 (2 μM) under both oxygen conditions. Data represent mean ± SEM (n = 8 biological replicates). Two‐way ANOVA with Tukey's post hoc test; significance symbols are defined in the panel. *P < 0.05, **P < 0.01, ***P < 0.001 vs Day14 Normoxia; # P < 0.05, ## P < 0.01, ### P < 0.001 vs Day14 Hypoxia; † P < 0.05, †† P < 0.01, ††† P < 0.001 vs Day90 Normoxia; § P < 0.05, §§ P < 0.01, §§§ P < 0.001 vs Day14 CHIR Normoxia.