Longevity Papers

Aging is a well-recognized risk factor in cardiovascular diseases (CVDs), primarily due to its association with the gradual decline in cardiac function. This decline significantly influences the pathogenesis of common CVDs such as myocardial infarction and heart failure. Despite the existence of several proteomic atlases of the heart, the spatially resolved proteomic dynamics essential for understanding region-specific aging mechanisms in cardiac tissue remain incompletely characterized. In this study, we conducted a region-resolved quantitative proteomic profiling for various murine cardiac regions at three distinct stages of aging (3, 12, and 20-month-old), quantifying 6 650 proteins in the heart. Leveraging integrated bioinformatics and machine learning frameworks, we uncovered that FTL1 and SERPINA3K exhibit strong age-associated expression changes across all cardiac regions. Mechanistically, the knockdown of Ftl1 led to cardiomyocyte ferroptosis and senescence, phenotypes that were ameliorated by the ferroptosis inhibitor Ferrostatin-1. Furthermore, the depletion of Serpina3k exacerbated senescence and collagen deposition through the activation of the cGAS-STING-PERK axis, effects that can be reversed via the overexpression of Serpina3k or the knockdown of Sting. The protective effect of SERPINA3K was also demonstrated in vivo through AAV9-mediated cardiomyocyte-specific overexpression in middle-aged mice, which attenuated the cGAS-STING-PERK axis and mitigated age-related fibrosis. These results strongly demonstrated that FTL1 and SERPINA3K function as key regulators of cardiac aging. Collectively, this study provides a valuable region-resolved proteomic atlas of cardiac aging and identifies key protein regulators, thereby uncovering potential targets for cardio-protective interventions against age-related cardiovascular disorders.

Chronological age incompletely captures heterogeneity in biological aging. In this prospective study of 45,819 UK Biobank participants, we developed a multimodal ocular aging index (MOAI) by integrating ophthalmic phenotypes with plasma proteomic and metabolomic profiles using machine learning. The MOAI quantifies divergence between ocular biological and chronological age. Over 13.80 years of follow-up, accelerated ocular aging was significantly associated with higher risks of incident age-related macular degeneration and cataract, even after adjustment for chronological age and established risk factors. Incorporation of the MOAI significantly improved risk reclassification beyond traditional predictors. Explainable modeling and pathway enrichment analyses identified inflammation-related proteins and pathways, including cytokine-cytokine receptor interactions and PI3K-Akt signaling, as key drivers of accelerated ocular aging. These findings establish a multimodal framework for quantifying organ-specific biological aging, link ocular aging to systemic inflammatory processes, and highlight the eye as a sensitive readout of aging biology with implications for healthspan.

Somatic stem cells are characterized by their low overall protein-synthesis rates, a feature implicated in driving their stemness. However, how aging reshapes the translational landscape of stem cells remains poorly understood. Here, we present an in vivo single-cell ribosome profiling strategy to monitor tissue-wide translational landscapes of the epidermis during aging. By implementing ribosomal elongation-inhibited cell isolation and switching to RNase I, we expand the applicability of single-cell ribosome profiling to in vivo systems and facilitate the evaluation of triplet periodicity, a hallmark of high-quality data. Leveraging this strategy, we document the in vivo translational landscapes of the major epidermal cell types, outline cell-type-specific translational efficiencies, and identify a pronounced translational reprogramming of AP-1 subunits specifically in aged epidermal stem cells. Our study illustrates the power of in vivo single-cell ribosome profiling to map cell-type-specific translational programs and offers a scalable strategy for tissue-wide interrogation of translational landscapes.

Aging is accompanied by a progressive decline in physiological function that contributes to chronic disease development. Biological clocks estimated from high-dimensional clinical and biological measurements may provide more granular tracking of the aging processes. Current biological clocks, however, have limited cross-ancestry generalizability and clinical applicability. Here, we developed a multi-ancestry biological clock (ClinBAG) using 22 routine blood and anthropometric biomarkers in 14,328 age- and sex-balanced individuals from the All of Us Research Program. We tested the association of ClinBAG with 434 traits and evaluated its ability to predict incident disease in 152,733 non-overlapping individuals. We also conducted genome-wide association studies in European (N=74,675), African (N=22,315), and Admixed American ancestry individuals (N=19,940). Among 190 neurological phenotypes, elevated ClinBAG was associated with cognitive decline, increased incidence of dementia (HR=1.020, p=1.6x10-5) and Parkinson's disease (HR=1.014, p=0.023), and decreased risk of migraine (HR=0.991, p=8.7x10-4). We also identified common (NPRL3) and ancestry-specific genetic loci (HBB in African-ancestry and FADS1/FADS2 in European-ancestry) for ClinBAG. Single-cell enrichment revealed that ClinBAG-associated genes are overexpressed in double-negative (DN) T cells in an age-dependent manner. This study presents a clinically applicable multi-ancestry biological age clock predicting neurological disease risk. Our findings also uncover population-specific genetic drivers, particularly involving erythropoiesis and DN T-cell-mediated neuroinflammation.

Transfer RNA (tRNA) halves (tRHs) are generated via the cleavage of tRNAs, but their roles in aging and longevity remain poorly understood. Here, we demonstrate a direct role of tRHs in aging in metazoans. Through a genetic screen using Caenorhabditis elegans, we identify DIS-3/DIS3 as a ribonuclease that catalyzes tRH generation, including 5'-tRH-Gln and 5'-tRH-Asp, from tRNAs. Among them, 5'-tRH-Gln is essential for longevity conferred by various interventions, including dietary restriction. Generation of 5'-tRH-Gln reduces translation via ribosomal protein binding and upregulates the SKN-1/NRF transcription factor responsible for lifespan extension. We further show that mammalian DIS3 contributes to tRH generation and delays cellular senescence through translation downregulation by another tRH, 5'-tRH-Cys. Overall, our data demonstrate that DIS-3/DIS3 is an evolutionarily conserved tRH-generating ribonuclease that counteracts organismal and cellular aging.

Older adults are highly vulnerable to infectious diseases, and vaccines are often less effective in this population because of diminished B and T cell memory responses driven by impaired autophagy, immunosenescence, and chronic low-grade inflammation. Spermidine has been shown to counteract immunosenescence and induce autophagy in preclinical models, and its levels decline with age in humans. We conducted a double-blind, randomised, placebo-controlled pilot study in 40 adults over 65 years of age following their third SARS-CoV-2 vaccine dose to assess the safety of Spermidine and its effects on vaccine-induced immunity. Daily oral supplementation (6 mg, 13 weeks) was well-tolerated. Vaccine non-responsiveness was common, and non-responders exhibited a distinct immune-senescence signature marked by elevated p16, mTOR signalling, and γ-H2AX+ DNA damage in lymphocytes. Spermidine reversed these features and significantly enhanced spike-specific IgG secretion, memory B cell recall responses and neutralising antibody activity, specifically in non-responders. Single-cell RNA-seq after treatment revealed increased expression of TFEB targets and autophagy-related genes in B cells, in line with elevated autophagic flux. These findings suggest that targeting immune cell senescence with Spermidine may improve vaccine responsiveness in older adults and highlight immune-senescence markers as potential predictors of vaccine failure in ageing populations.

Epigenetic clocks, developed using blood DNA methylation data, can be used to estimate biological ages and pace of aging. We aimed to identify potential determinants of the pace of aging, estimated using blood DNA methylation, and to investigate the association between the pace of aging and all-cause mortality in a population-based Norwegian cohort with repeated DNA methylation measurements.

DNA methylation changes are reliable biomarkers of aging, but the driving mechanisms remain poorly understood. Here we present SCARLET (Stem Cells and Age-ReLated Epigenetic Trajectories), a parsimonious mathematical model that describes how methylation changes in blood arise and propagate through hematopoietic stem cell divisions. Using a large human cohort, we demonstrate that seemingly distinct age-related methylation patterns can be explained by a unifying mechanistic model. We show that SCARLET captures known drivers of epigenetic aging, with accelerated individuals showing reduced ratios of stem cell pool size to division rate (N/s). Applying SCARLET to methylation data from 11 mammalian species reveals that N/s scales with maximum lifespan, suggesting that evolutionary adjustments to stem cell dynamics, rather than epigenetic maintenance efficiency, drive the previously observed relationship between methylation rates and lifespan. Our findings provide a quantitative framework for understanding epigenetic aging and suggest that stem cell dynamics may be a key driver of aging across mammals.

Reprogramming-induced rejuvenation (RIR) reverses cellular aging by transiently engaging early reprogramming states without full dedifferentiation. This review examines current developments in the molecular mechanisms, technological advances, and tissue-specific applications of RIR. Recent mechanistic insights highlight persisting questions in timing, heterogeneity, and pathways engaged in the epigenetic response. New technological advances have expanded RIR modalities beyond traditional Yamanaka factors to include mRNA-based delivery, CRISPRa, and chemical cocktails, while high-throughput screening platforms are systematically identifying novel rejuvenation factors with improved safety profiles. Recent tissue-specific applications demonstrate functional restoration across brain, liver, intestine, cardiovascular, and epithelial systems through reversal of cellular senescence, reduction of DNA damage and epigenetic age, and enhanced regenerative capacity. However, clinical translation faces challenges including narrow therapeutic windows, incomplete mechanistic understanding, and limited biomarker standardization. We discuss how single-cell technologies, computational prediction tools, and systematic in vivo testing may advance RIR toward geroscience therapies for age-related diseases.

Cellular aging is characterized by the progressive accumulation of intracellular damage, declining repair capacity, and altered mechanochemical signaling, ultimately leading to cellular senescence and loss of tissue homeostasis. Despite extensive experimental and theoretical efforts, the fundamental origin of senescence and its irreversible nature remain incompletely understood. In particular, it is unclear whether senescence must be imposed as a predefined cellular state or can instead emerge dynamically from more basic damage-repair mechanisms. In this work, we propose a unified age-damage structured mathematical framework for cellular aging that integrates intracellular damage accumulation, biochemical signaling, mechanical stress, and population renewal within a thermodynamically consistent variational structure. The model combines continuum thermodynamics with age-structured population dynamics, ensuring compliance with the second law of thermodynamics and providing a rigorous basis for irreversible aging processes. A central result of the model is the emergence of a damage-driven loss of homeostasis at a critical threshold of effective load, beyond which no steady intracellular damage state exists. This transition generates irreversibility at the single-cell level and propagates to the population scale through transport in age-damage space, leading naturally to the emergence of cellular senescence without introducing ad hoc senescence rules. Mechanical stress enters the model through a quadratic contribution to the effective damage load, producing a pronounced nonlinear sensitivity and predicting abrupt acceleration of aging beyond a critical stress level. To facilitate analysis and computation, we derive a reduced ODE-PDE system that retains the essential couplings between damage accumulation, biochemical signaling, mechanical stress, and population renewal. Analytical arguments and numerical illustrations demonstrate how transient mechanical or biochemical perturbations can induce persistent senescence at the population level. Overall, the proposed framework provides a mechanistic and thermodynamically grounded explanation of irreversible senescence as an emergent phenomenon in age-structured cell populations.

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