Longevity Papers

Craniomaxillofacial bone marrow mesenchymal stromal cells (BMSCs) retaining neural crest-derived neurogenic niche is driven by lineage memory and niche homeostasis. Elucidating how the neurogenic potential is maintained is critical for neurological health. Here, we explored a neural crest-like progenitor niche in BMSCs with high neurogenic and proliferative capacity by single-cell transcriptomics. In which, ANKRD1 is a pivotal regulator sustaining the neurogenic reservoir. Importantly, ANKRD1 expression in this niche declines with aging and lineage commitment, coinciding with its redistribution from a diffuse nucleoplasmic pattern to perinuclear enrichment along the nuclear lamina and loss of neural potential. Mechanistically, ANKRD1 preserves neurogenic capacity by directly binding super-enhancers of neural marker genes (SOX2, NESTIN) and maintaining open chromatin architecture. Critically, neuron-targeted ANKRD1 delivery rescues spatial memory deficits in aged mice. These findings establish ANKRD1 as a therapeutically tractable regulator that sustains neurogenic chromatin reservoirs to support neurocognitive resilience, opening avenues to counter cognitive aging.

Cellular senescence drives aging-related tissue dysfunction in part through the senescence-associated secretory phenotype (SASP), an inflammatory secretome linked to retrotransposable element (RTE) derepression. Transcriptomic and proteomic approaches have characterized the senescent program extensively, but mRNA abundance does not predict protein output well, and limited proteomic depth constrains the detection of low-abundance SASP factors and RTE-derived proteins. To bridge this gap, we used AHARibo, a metabolic labeling-based method that selectively enriches mRNAs associated with actively elongating ribosomes, to generate translatome profiles in human fibroblasts across proliferating, early senescent, and late senescent states. Comparison of total and ribosome-associated mRNA pools reveals marked translational uncoupling in early senescence: transcriptomic changes explain only 34% of translatomic variance, compared to 70% in late senescence, indicating that early senescence is substantially shaped by post-transcriptional regulation. Key senescence programs are actively regulated at the translational level: cell cycle and extracellular matrix remodeling genes are translationally suppressed and enhanced, respectively, while inflammatory SASP components are translationally depleted in early senescence - a depletion relieved in late senescence. Translationally depleted SASP genes are enriched for binding motifs of the ZFP36 family (ZFP36, ZFP36L1, ZFP36L2), implicating these RNA-binding proteins in the post-transcriptional gating of inflammatory signaling. More broadly, translational efficiency is associated with 3'UTR GC content and codon optimality, and translationally depleted mRNAs are enriched for numerous RBP and microRNA target motifs. Finally, we detect robust, locus-resolved translation of evolutionarily young LINE-1 retrotransposons, identifying full-length elements with stage-specific translational activity. Together, these findings establish translational control as a pervasive regulatory layer shaping the senescent phenotype.

Aging is accompanied by conserved hallmarks including genomic instability, epigenetic alterations, loss of proteostasis, and mitochondrial dysfunction, but how these processes emerge and become mechanistically linked remains unclear. Here we leverage a proteome-wide, single-cell, subcellular atlas of protein expression, localization, and aggregation across yeast replicative aging to map hallmark-linked remodeling in its spatial context. We identify hundreds of previously unappreciated molecular changes that underlie major hallmarks of aging and show that hallmark phenotypes frequently manifest as compartment-specific erosion of spatial confinement, relocalization, and aggregation. 91.6% human orthologs of these hallmark-linked yeast proteins also change during human aging. Integrating these spatial phenotypes reveals many molecular connections linking different hallmarks. Temporal analysis suggests that disorganization of nucleolar ribosome biogenesis, proteostasis decline, and mitochondrial dysfunction precede other hallmarks. Together, our findings substantially deepen the molecular underpinnings of aging hallmarks and provide a framework for linking them into a hierarchical sequence of cellular failures. Keywords: aging, protein localization, protein concentration, protein aggregation, hallmarks of aging, ribosome biogenesis, aging pathways.

Systemic inflammation ("inflammaging") accelerates biological aging and drives cardiovascular, metabolic, and neurodegenerative disease. Circadian rhythms regulate the amplitude and timing of immune responses, yet their mechanistic role in inflammation and longevity remains unexplored. In 62,000 adults with 7-day wearable accelerometry, interpretable machine learning model identified rhythm amplitude, stability, and moderate-to-vigorous physical activity (MVPA) as dominant predictors of accelerated aging. In a subset of 1521 participants (35% male) with available data on the systemic immune-inflammation index (SII), we further examined the associations between behavioral rhythmicity and inflammation. Low amplitude and poor rhythm stability were associated with 0.31 and 0.18 SD higher SII; low MVPA to 0.33 SD higher SII in men (all p < 0.05). Adding 15-min bout to daily MVPA or improving rhythm stability by 10-14% mitigated these effects. Sex-stratified mediation analysis revealed that inflammation accounted for 26% of the mortality risk associated with insufficient MVPA, 14% with rhythm irregularity, and 8% with low amplitude only in men. These findings position rest-activity rhythms as digital biomarkers linking daily rhythmicity to inflammation and survival and identify inflammation as a modifiable target for personalized interventions to foster healthy aging.

Quantifying biological aging is crucial for understanding functional decline before the onset of morbidity. While many accelerated aging and frailty measures based on clinical data exist for humans and several for rodent models of aging, there are few options for non-human primates (NHPs). NHP clinical data has several unique features including a lack of clinically delineated normative values for features and variability in data collection over long lifespans. There are also wide discrepancies in the number of available clinical measures and number of animals across data sets. To address these challenges, we developed and validated "Aging Resilience" (AR) metrics using longitudinal, routine clinical data from two distinct non-human primate cohorts: 4,328 baboons and 281 rhesus macaques. We trained five computational models, including Linear Mixed-Effects Models, Random Forest, and Recurrent Neural Networks (RNN), to predict chronological age, subsequently deriving AR metrics that represent the velocity (Rate of Aging) and cumulative burden (Normalized Cumulative Aging) of physiological deviation. While linear models achieved high precision in predicting chronological age (test R2 up to 0.99), they correlated poorly with actual lifespan. In contrast, AR metrics derived from non-linear models (RNN and Random Forest) displayed strong predictive validity for mortality (Pearson's r > 0.8). These findings highlight a critical paradox: models that best predict chronological age do not necessarily capture the biological resilience determining healthspan. This study establishes a scalable framework for monitoring biological aging in translational models using standard veterinary records.

To investigate organism-wide cellular alterations and epigenomic dynamics during aging, we constructed a single-cell chromatin accessibility atlas spanning 21 mouse tissues across three age groups and both sexes. We found that around one-quarter of 536 organ-specific cell types and 1828 finer-grained subtypes exhibited considerable age-related population shifts. Cellular states from broadly distributed lineages displayed synchronized dynamics with age, indicating systemic signals that coordinate these changes. Molecular analyses identified both intrinsic regulators (chromatin peaks, transcription factor activity) and extrinsic factors (cytokine programs) underlying these shifts. Moreover, ~40% of aging-associated population dynamics were sex-dependent, with tens of thousands of peaks altered exclusively in one sex. Together, these findings present a comprehensive framework for how aging reshapes the chromatin landscape and cellular composition across diverse tissues.

Diet is an essential factor influencing biological aging, yet few exsiting dietary indices were specifically developed to target biological aging. We developed a data-driven food-based Empirical Dietary Index for Slower Epigenetic Aging (EDISEA) in the US Health and Retirement Study (HRS, n=7,398), which predicted deceleration of GrimAge, an established DNA methylation-based epigenetic clock. Participants in the highest versus lowest EDISEA quintile had 4.65-year deceleration in GrimAge (P value <0.001). We externally validated EDISEA in an independent US cohort (n=23,830), where it showed consistent associations with several epigenetic clocks and lower all-cause mortality risk. In HRS and a UK aging cohort (n=4,895), EDISEA was associated with lower risks of several aging-related diseases and functional limitations. Outcome-wide analyses in the UK Biobank (n=187,035), together with integrative proteomic, metabolic, and neuroimaging assessments, revealed biological signatures of EDISEA implicating broad vascular, inflammatory, metabolic, and brain-structural pathways through which EDISEA was associated with biological aging. EDISEA provides a scalable, biologically anchored tool to inform the development of precision nutrition strategies aimed at slowing epigenetic aging and mitigating aging-related disease burden.

Macrophage senescence drives inflammaging, a chronic, age-related inflammation. To date, the protective mechanisms against inflammaging are poorly defined. Here, we identify DNA-PK-mediated phosphorylation of murine STAT6 at serine 807 (Ser807) as a crucial post-translational modification for preventing macrophage senescence. Ser807 phosphorylation blocks STAT6 ubiquitination-mediated degradation and promotes STAT6 partnering with PU.1 to activate DNA repair genes. Macrophages lacking Ser807 phosphorylation exhibit DNA repair defects, undergo senescence, and fuel inflammaging. In vivo, the phosphor-null STAT6 mutant (STAT6(S807A)) accelerates macrophage senescence, tissue fibrosis, and systemic aging. Adoptive transfer of phosphomimetic STAT6(S807E)-expressing macrophages rescues accelerated aging. Importantly, phosphorylation of human STAT6 at the homologous residue (Ser817) is significantly reduced in the lungs of patients with chronic obstructive pulmonary disease (COPD), correlating with increased DNA damage and senescence. Thus, our findings reveal a DNA-PK-STAT6 axis enacting a non-canonical type 2 immunity via DNA repair to prevent macrophage senescence, presenting a therapeutic target for healthy aging.

Biological aging reflects complex cellular and biochemical processes that can be measured across multiple omic layers. Using routine clinical laboratory data from ~31,000 participants in the Mass General Brigham Biobank, we developed EMRAge, a biomarker of mortality risk that can be broadly recapitulated across electronic medical records. Here we show that EMRAge can be modeled using elastic net regression with DNA methylation and multi-omics to generate DNAmEMRAge and OMICmAge, respectively. Both biomarkers are strongly associated with incident and prevalent chronic diseases and mortality, performing comparably or better than current biomarkers across discovery (Massachusetts General Brigham Aging Biobank Cohort, n = 3,451) and validation cohorts (TruDiagnostic, n = 14,213; Generation Scotland, n = 18,672). Importantly, OMICmAge leverages epigenetic biomarker proxies to integrate proteomic, metabolomic and clinical domains while remaining quantifiable from DNA methylation alone. This framework establishes an accessible, scalable measure of biological aging with potential to reveal molecular interconnections that shape healthspan and disease risk.

Stem cells maintain tissue integrity through a balance of self-renewal, differentiation, and loss of function due to aging or stress. Recent studies demonstrate that the stem cell hierarchy is not fixed. Transit-amplifying or terminally differentiated cells can dedifferentiate back into stem-like states. Such plasticity supports regeneration but, when combined with damage accumulation, may also accelerate aging and increase cancer risk. Motivated by these findings, we develop a damage-structured PDE model of a two-compartment lineage consisting of stem and terminally differentiated cells. The model incorporates dedifferentiation, together with a nonlocal δ-function kernel partitioning scheme that conserves total damage and encodes biologically motivated asymmetries. Methodologically, we emphasize reproducibility and robustness on three fronts. First, the δ-kernel partitioning prevents the unbounded drift that arises in local models while preserving conservation. Second, a conservative finite-volume discretization with upwind fluxes and verified first-order accuracy ensures stability and exact mass balance, as confirmed by manufactured-solution tests. Third, distributional metrics and systematic parameter sweeps provide reproducible ways to quantify lineage-level damage dynamics under varying dedifferentiation and repair conditions. These analyses show that threshold-dependent and repair-modulated dedifferentiation both act as protective mechanisms: the former functions as a 'detoxification loop' that recycles high-damage cells, and the latter reduces the damage burden imported during dedifferentiation. Together, they mitigate aging-inducing effects. Parameter sweeps further delineate when dedifferentiation stabilizes tissue maintenance versus when it drives aging-like dynamics. Overall, our reproducible framework integrates biological insights on stem-cell plasticity and damage segregation with rigorous mathematical modeling, providing a foundation for experimental validation and therapeutic strategies targeting stem-cell aging and cancer initiation.

Aging is accompanied by a progressive decline in protein synthesis and ribosome abundance, yet paradoxically, genetic or pharmacological attenuation of translation extends lifespan across species. Whether the age-associated decline in translation is adaptive or reflects a pathological failure of ribosome homeostasis remains unclear. Here, we show that shortened lifespan is driven by dysregulated ribosome biogenesis (RiBi) and impaired ribosome assembly. Using Caenorhabditis elegans ncl-1 loss-of-function mutants as a model of accelerated aging, we find that nucleolar enlargement coincides with decoupling of precursor and mature rRNA, ribosomal protein (RP) transcripts, and protein abundance, loss of RP stoichiometry, defective ribosomal subunit joining, and compromised proteostasis. Strikingly, lifespan can be restored downstream of the nucleolus by targeting either the RNAse P/MRP complex or the mitochondrial ribosome. These interventions rebalance mature rRNA and RP abundance, improve ribosomal assembly, and reduce protein aggregation despite persistent nucleolar enlargement and elevated pre-rRNA levels. Our findings identify accelerated age-associated ribosome dysfunction as a qualitative failure of ribosomal biogenesis, and demonstrate that restoring ribosomal homeostasis is sufficient to improve proteostasis and extend lifespan.

Lifespan varies widely among individuals, yet the extent to which such variation persists when genetic and environmental differences are minimized remains unclear. Here we quantify such stochastic lifespan variation in a naturally clonal vertebrate and test whether and how this variation is linked to early-life behavioral individuality. We followed N = 33 genetically identical Amazon mollies (Poecilia formosa), separated on day 1 of their life into highly standardized environments, from birth to death. Despite genetic uniformity and environmental standardization, lifespan varies markedly, spanning 502 to 826 days. Continuous high-resolution behavioral tracking during the first four weeks of life reveals that seemingly stochastic early-life activity differences explain 32.5% of this variation. Higher activity predicts shorter lifespan during the first two weeks, but as activity levels and among-individual variation in activity decline over early development, a U-shaped relationship emerges, with both low- and high-activity individuals outliving those with intermediate activity. These findings show that signatures of lifespan emerge within days of birth, even among genetically identical individuals, highlighting developmental stochasticity and early-life contingencies as major contributors to variation in life-history outcomes.