Decoding Aging: Multi-Omics Insights into Oxidative Stress, Mitochondrial Dysfunction, and Cellular Senescence in Fibroblasts

Published: 08 Aug 2025, Last Modified: 03 May 2026IEEE Computational Intelligence and Bioinformatics and Computational BiologyEveryoneRevisionsCC BY 4.0
Abstract: This research investigates the complex biochemical mechanisms underlying aging by analyzing primary human fibroblasts using a longitudinal multi-omics dataset. This dataset includes cytology, DNA methylation and epigenetic clocks, bioenergetics, and cytokine profiling. Key findings indicate that mitochondrial efficiency declines with age, while glycolysis becomes more prevalent to compensate for energy demands. Epigenetic clocks, such as Hannum and PhenoAge, showed strong correlations with biological age (ρ > 0.650, p < 1e-6), validating the experimental setup and confirming that the cultured fibroblasts were aging appropriately. Fibroblasts with SURF1 mutations exhibited accelerated aging, marked by bioenergetic deficits, increased cell volume, and reduced proliferative capacity, underscoring the pivotal role of mitochondrial dysfunction in cellular senescence. Novel insights were gained from analyzing cytokines like IL-18 and PCSK9, some of which were linked to age-related diseases such as Alzheimer’s and cardiovascular disorders. Experimental treatments revealed distinct effects on cellular aging. Dexamethasone reduced inflammation but also increased DNA methylation, induced metabolic inefficiencies, and shortened cellular lifespan. By uncovering connections between mitochondrial dysfunction, epigenetic biomarkers, and immune dysregulation, this research identifies potential therapeutic targets for age-related diseases.
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