Longevity Papers

Macroautophagy/autophagy protects muscle from proteotoxic stress and maintains tissue homeostasis, yet skeletal muscle relies on it more than most organs. Adult fibers endure constant mechanical strain and require continuous turnover of long-lived proteins, while muscle stem cells (MuSCs) depend on autophagy to remain quiescent, activate after injury, and regenerate effectively. How autophagy is transcriptionally regulated in muscle has been unclear. We identified DEAF1 as a transcriptional brake on autophagy. In MuSCs, DEAF1 controls activation and regeneration and becomes aberrantly elevated with age, promoting protein aggregate formation and cell death. In muscle fibers, DEAF1 is chronically induced during aging, suppressing autophagy and driving functional decline. Exercise reverses DEAF1 induction, restoring autophagy and muscle function. These findings reveal DEAF1 as a key regulator linking autophagy to regeneration and aging, highlighting a therapeutically tractable axis for preserving muscle health.

Cerebral small vessel disease (CSVD) is a leading cause of age-related cognitive decline and neurological disorders, yet its precise characterization in large populations has been constrained by reliance on subjective neuroimaging ratings. To address this, we developed CSVDtransformer, a foundation model that simultaneously quantifies six key CSVD biomarkers from structural brain MRI. In 3,718 subjects, the model achieved excellent accuracy (mean AUC = 0.904) in measuring periventricular and deep white matter hyperintensities, Fazekas scores, enlarged perivascular spaces, lacunar infarcts, and cerebral microbleeds. Validation across two independent, external datasets (N=568) confirmed its robust generalizability. As a clinical decision-support tool, it augmented neurologist assessment relative accuracy by 20%. Application to 59,772 UK Biobank participants revealed distinct associations of these quantified biomarkers with incident stroke, dementia, and psychiatric disorders. Large-scale multi-omics analysis identified 1,365 significant plasma protein correlates and 14 novel genetic loci for these CSVD biomarkers. These associations implicate pathways of endothelial dysfunction, inflammation, and lipid metabolism. Mendelian randomization analyses provided evidence for causal relationships between specific vascular-metabolic proteins and CSVD biomarkers, such as positive effect of EFEMP1 and negative effect of EPO on CSVD. Furthermore, drug-target enrichment analysis highlighted the potential for targeting TFPI and EPO to address vascular dysfunction associated with CSVD. Our study establishes CSVDtransformer as a scalable foundation model that deciphers the complex systemic biology of cerebral microvascular health.

Inflammaging, the sustained chronic inflammation, is a hallmark of aging, yet its sustained activation mechanism remains elusive. Here, we identified muscle stem cells (MuSCs) as a driver of systemic inflammaging, evidenced by the multi-organ inflammation and aging phenotypes in MuSC specific Tet2 knockout mice. Tet2-Hdac11-Acod1-SDH axis maintained normal succinate level in MuSCs. Tet2 knockout disrupted this enzymatic cascade and led to succinate accumulation, fueling H4K31succ elevation to directly activate inflammatory gene transcription in MuSCs. The excess succinate was delivered to muscle fibers by sporadic fusion of Tet2 knockout MuSCs during muscle homeostasis, activated pro-inflammatory program, and transformed muscle to a persistent pro-inflammatory factor secretory organ, sustaining systemic inflammaging. Moreover, Tet2 was downregulated in aged MuSCs suggesting that this coupled metabolic-epigenetic mechanism was active in physiological aging. These findings reveal that a small subset of dysregulated MuSCs activate sustained whole-body inflammaging and multi-organ aging, providing new targets for rejuvenation strategy development.

Liver fibrosis is a major global health burden with no approved therapies. Transient expression of reprogramming factors Oct4, Sox2, and Klf4 (OSK) promotes tissue regeneration without inducing full pluripotency, which represents an attractive regenerative therapy. Here, we introduce a hepatocyte-specific mRNA delivery strategy for in vivo partial cellular reprogramming using a chemically defined lipid nanoparticle (LNP) platform. We synthesized a series of natural unsaturated fatty alcohol-based ionizable lipids and identified a lead compound, H4T3, with mRNA delivery efficacy comparable to SM102. Further formulation optimization led to a simplified, phospholipid-free, three-component LNP formulation, H4T3_F6 that exhibits high potency and enhanced hepatocyte selectivity, alongside minimal immunogenicity and an overall favorable safety profile. Hepatocyte-specific delivery of OSK mRNA via H4T3_F6 LNPs transiently reprogrammed fibrotic hepatocytes into progenitor-like cells, rejuvenated hepatic gene expression, and promoted functional regeneration. This rejuvenation process downregulates fibrogenic mediators (Tgfb1, Pdgfb), disrupting hepatocyte-stellate cell signaling and halting extracellular matrix (ECM) deposition. The integrated reprogramming and paracrine modulation collectively shift the liver microenvironment from a fibrotic to a regenerative state in a CCl

There is growing interest in the use of molecular features as predictors of age, age-related disease risk and mortality. A major shortcoming of this field, however, is the lack of suitable translational research models to identify and understand the underlying mechanisms of these predictive biomarkers in human populations. In particular, we lack a system which, like humans, is genetically variable, lives in diverse environments, and experiences aging-related chronic conditions treated in the context of a sophisticated health care system. Here, we present results from our analysis of data from the Dog Aging Project (DAP), a long-term longitudinal study of aging in companion dogs. Using longitudinal survival models on data from 937 dogs of the deeply phenotyped Precision Cohort within the DAP, we present the striking finding of a strong, highly significant positive correlation between the effect of individual metabolites on all-cause mortality in humans, and the association of those same metabolites on all-cause mortality in dogs. We also find that across these independent human studies, the biomarkers identified are also highly correlated, strongly suggesting a general signature of mortality within the plasma metabolome across humans, and now in dogs as well. Given the many similarities between dogs and humans with respect to genetics, environment, disease, and disease treatment, and the fact that dogs are so much shorter lived than humans, we argue that dogs represent an extremely valuable translational model in our ongoing effort to understand the underlying molecular causes and consequences of age-related morbidity and mortality in humans.

Cellular senescence, defined as the irreversible arrest of cell proliferation in response to stress, contributes to tissue dysfunction and drives the progression of age-related diseases. Accurate detection of senescent states is therefore essential for understanding aging mechanisms and identifying therapeutic targets. However, conventional laboratory assays are time-consuming and difficult to scale. Here, we present SenSeqNet, a deep learning framework that predicts cellular senescence directly from protein sequences. SenSeqNet integrates embeddings from the Evolutionary Scale Modeling (ESM-2) with a hybrid LSTM-CNN architecture to capture both sequential and higher-order structural features. The model achieved 86.43% accuracy in independent testing, outperforming traditional machine learning and deep learning approaches. Importantly, the high-confidence genes predicted by SenSeqNet were significantly enriched in canonical senescence-associated pathways, indicating that the model captures biologically coherent regulatory programs rather than overfitting to sequence labels. These results establish SenSeqNet as a robust and biologically informed tool for senescence detection and provide a foundation for accelerating research into aging and age-related therapeutics.

Hematopoiesis, the process of generating blood cells, is essential for maintaining immune functions in responding to systemic challenges. Disruption of this process, driven by inflammation or aging, often results in myeloid-biased hematopoiesis and impaired lymphoid lineage output. In this study, we identify interleukin-4 (IL-4) signaling as an important modulator of the lymphoid lineage commitment in hematopoietic multipotent progenitors (MPPs). We show that IL-4 promotes MPP differentiation from myelopoiesis to lymphopoiesis via the STAT6 signaling pathway. Transcriptomic analysis reveals that IL-4 signaling upregulates lymphoid-specific pathways while suppressing myeloid differentiation programs in MPPs, but not in hematopoietic stem cells (HSCs). Mechanistically, FLT3-a class III receptor tyrosine kinase highly expressed in MPPs-interacts functionally with IL-4 signaling to facilitate STAT6 phosphorylation and activation. Notably, IL-4 treatment rejuvenates aged hematopoietic stem and progenitor cells, restoring B and T cell output and counteracting inflammaging-associated myeloid bias. These changes are associated with improved immune, metabolic, physical, and cognitive functions, positioning IL-4 signaling-FLT3 cooperation in MPPs as a critical regulator of organism-wide immune fitness. Our findings highlight IL-4 as a potential therapeutic agent for restoring balanced hematopoiesis in the context of aging and inflammation.