Key result
Exercise detraining drives unique cardiac regression, altering ~6,000 genes distinct from other regression models.
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RNA sequencing of four cardiac regression models reveals distinct transcriptional signatures and pathways, identifying FSTL3 as a potential biomarker for maladaptive versus beneficial remodeling.
Background: Pathological cardiac hypertrophy is a major risk factor for cardiovascular disease. While regression of hypertrophy improves cardiac function, the transcriptional signatures that differentiate beneficial from maladaptive remodeling remain unclear, and the molecular mechanisms distinguishing physiological from pathological regression are not well defined. Methods: RNA sequencing (RNA-seq) was performed on four cardiac regression models: (1) Debanding after transverse aortic constriction (TAC), representing physiological regression; (2) Activin Overexpression, associated with pathological regression; (3) Detraining after exercise training; and (4) Fasting, an adaptive metabolic response. Result: Principal component analysis (PCA) revealed distinct clustering among models, with Debanding separating along PC1 (44% variance), linked to upregulated aerobic metabolism. Activin and Fasting clustered in PC2 (39% variance), driven by increased protein ubiquitination, while PC3 (17% variance) distinguished Fasting via suppression of fatty acid metabolism. Differential gene expression analysis showed that Detraining had the highest number of unique differentially expressed genes (DEGs) (5,970), followed by Debanding (3,188), Activin (1,995), and Fasting (1,404). Reactome pathway enrichment identified proteostasis as a key feature of Debanding, autonomic tone and angiogenesis in Detraining, microautophagy in Fasting, and Complex I/ETC suppression in Activin-induced regression. FSTL3 was upregulated in Activin and downregulated in Debanding, making it a potential biomarker for maladaptive vs. beneficial regression. Regulatory network analysis identified key transcription factors (Mef2a, Srf, Stat5b, Zfp143, Batf3) with distinct activation patterns in different regression states. Conclusion: These findings highlight the molecular heterogeneity of cardiac regression, identifying key pathways, genes, and transcriptional regulators that distinguish adaptive from maladaptive remodeling. Understanding these differences may inform therapeutic strategies to selectively promote beneficial regression while mitigating maladaptive responses.
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Yuan et al. (2025) studied Pathological cardiac hypertrophy. Cardiac regression models (Debanding, Activin Overexpression, Detraining, Fasting) was evaluated on Differential gene expression and transcriptional signatures. Four cardiac regression models exhibited distinct transcriptional signatures, with Detraining yielding 5,970 unique differentially expressed genes compared to Debanding, Activin, and Fasting.
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