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Gladyshev, V.

Publications and source records attributed to Gladyshev, V..

3 recordsLinked to original sources

Mammalian aging involves genome-wide splicing degeneration leading to functional decline

Alternative splicing exhibits significant changes during development and aging, affecting the composition and variance in the transcriptome. However, it is unclear whether and how age-associated splicing dysregulation leads to functional consequences. Here, an integrative analysis of transcriptome data across mouse and human tissues revealed that aging is characterized by systematic deterioration of the fidelity of RNA splicing, here termed splicing degeneration, a measure of functional alteration of reading frame and domain configuration of protein products. Genes with higher aging-associated splicing degeneration were more conserved and enriched for processes such as RNA metabolism and antigen presentation. By assessing alternative splicing events associated with functional deterioration, we quantified the degree of splicing degeneration. Its level increased with age but was alleviated following calorie restriction or rapamycin treatment, indicating that it can serve as a new molecular hallmark of aging. Mechanistically, through a comprehensive meta-data analysis, we discovered that splicing degeneration is associated with age-associated changes in specific splicing factors, which in turn showed a strong association with age-related transcriptome changes. Overall, our study demonstrates the intricate relationship between aging and genome-wide splicing degeneration, revealing a promising target for aging interventions acting to reverse splicing degeneration.

Systems Biology↗

Multi-tissue spatial transcriptomics reveals biological age hotspots in mouse and human aging

Aging proceeds heterogeneously across tissues, yet how biological age varies within the spatial architecture of individual organs remains poorly understood. Here, we introduce stAge, a framework that quantifies localized transcriptomic age (tAge) from spatial transcriptomics data in mouse and human samples during natural aging and in response to injury, infection, neurodegeneration, and cancer. stAge captures age differences among samples and provides a single multi-tissue model for assessing aging within and across organs. Across tissues and conditions, stAge uncovers robust spatial gradients of biological age and shows that injury and neurodegeneration induce pronounced age acceleration, with stronger responses in older organisms and partial normalization during recovery. With advancing age, tissues develop pronounced hotspots of accelerated aging and coldspots of preserved resilience. Hotspots are enriched for metabolic and immune aging signatures, whereas chromatin-related signatures are associated with coldspots. These findings show that aging is spatially structured within tissues and lay a foundation for developing spatially targeted rejuvenation strategies.

bioinformatics↗

DNA Methylation Ageing Atlas Across 17 Human Tissues

Aging involves widespread epigenetic remodeling across tissues, yet the nature and consistency of these changes remain unclear. We conducted a meta-analysis of more than 15,000 human methylomes spanning 17 tissues, identifying both conserved and tissue-specific aging signatures. We examined linear changes via differentially methylated positions, variability shifts via variably methylated positions, and Shannon-entropy to capture methylation disorder. Network analysis revealed fragile co-methylation modules largely resistant to beneficial perturbation. Key disruptors, including PCDHGA1, MEST, HDAC4, and HOX genes, exacerbated aging signals across tissues. Notably, a resilient module enriched for NAD{square} salvage metabolism supports therapeutic targeting of NAD{square} in aging. PCDHGA1 emerged as a conserved cross-tissue driver, suggesting protocadherin-mediated adhesion plays a broader role in maintaining structural and signaling stability in multiple organ systems. Our open-access atlas provides a foundational resource for dissecting the molecular architecture of human aging and identifying testable targets for intervention, biomarkers, and translational epigenetic therapies.

bioinformatics↗