Longevity Papers

As the most abundant human cell and the foundation of transfusion medicine, red blood cells (RBCs) offer a unique readout of systemic health, yet they have never been characterized at population scale. We generated a proteome atlas of 13,091 blood donors with multi-omics longitudinal phenotyping, characterizing the influence of demographics and genetic variation on the reproducibility of RBC proteomes across donations. Elastic-net aging clocks captured biological aging with high accuracy and uncovered genetic regulators of {Delta}Age at FN1, C4/IKZF1, CRAT, PFAS, TRIM58. Across independent cohorts, {Delta}Age was accelerated in G6PD deficiency, sickle cell trait/disease, and iron deficiency, reversed by iron repletion, and slowed in high-frequency donors, linking molecular aging to brain iron/myelin and cognitive performance. Molecular aging signatures predicted storage, osmotic, and oxidative hemolysis, hemoglobin increments after transfusion, and long-term donor activity over 12-years. These results establish RBC proteomics as a scalable biomarker of aging, donor healthspan, and transfusion outcomes.

In many countries, lifespan has been increasing faster than healthspan, leading to more years spent with late-life disease and highlighting the need for reliable biomarkers to measure biological aging.

Aging is a primary risk factor for chronic diseases, with cellular senescence as an effective target to delay, prevent or alleviate age-related disorders. Here we report in vitro screening outputs from a natural medicinal agent library, wherein dihydromyricetin, a natural flavonoid, showed senotherapeutic potential. Dihydromyricetin protects senescent fibroblasts against further DNA damage and attenuates the senescence-associated secretory phenotype, acting as a senomorphic agent. Proteomics suggests that dihydromyricetin promotes nuclear translocation of peroxiredoxin 2 (PRDX2) to facilitate DNA repair in senescent cells. In prematurely aged mice, dihydromyricetin administration mitigates tissue aging and age-related physiological decline. In anticancer regimens, dihydromyricetin improves outcomes of chemotherapy. However, dihydromyricetin demonstrates senolytic activity against senescent microglial cells, whose basal PRDX2 expression remains low, by impairing mitochondrial function to promote apoptosis. In mice developing Alzheimer's disease, dihydromyricetin eliminates senescent microglial cells from amyloid β-protein plaques and alleviates neurodegenerative symptoms. Together, our study proposes dihydromyricetin as a natural senotherapeutic agent for mitigating age-related morbidities, including but not limited to cancers and Alzheimer's disease.

The human striatum is a central hub for a diverse array of motor, cognitive, and affective behaviors, yet it lacks obvious cytoarchitectural boundaries that define functional territories. Here, we uncover a robust and molecularly defined mesoscale architecture in the human striatum. Using Slide-tags, a scalable single-nucleus spatial transcriptomics technology, we profiled 1.1 million cells across the full span of the anterior striatum of 19 postmortem donors, spatially mapping all striatal populations. Our data uncover a natural subdivision of the striatum into six zones, each defined by molecularly distinct populations of medium spiny neurons, and featuring spatially coordinated neuron-astrocyte signaling. Relative to MSNs in ventral zones, MSNs in dorsal zones exhibit higher expression of genes for synaptic remodeling and plasticity via ephrin and TGF-beta, while the ventral zone is defined by greater expression of semaphorin, protein chaperone, and hedgehog signaling pathways. By imputing zonal identities onto a larger single-nucleus RNA-seq cohort of 131 donors, we find that the dorsal zones exhibit greater age-related transcriptional changes, and that overall, the gene-expression differences that define spatial zonation patterns are attenuated with advancing age. This atlas provides a mesoscale molecular definition of human striatal anatomy, linking cell type identity to functional specialization and aging susceptibility.

The reduction in number and decreased differentiation capacity of oligodendrocyte progenitor cells (OPCs) directly affect myelination in demyelinating diseases and aging, but the underlying mechanisms remain incompletely characterized. Here we observed a marked decline in the number of OPCs during aging, notably within the subpopulation highly expressing Acss2, which encodes acetyl-CoA synthetase 2 (ACSS2). Deletion of ACSS2 in the oligodendrocyte lineage resulted in a reduced OPC population, defective myelinogenesis during development, impaired myelin maintenance in adulthood and aging, and exacerbated age-related cognitive deficits. Mechanistically, ACSS2-mediated acetylation of H4K12 and H3K27 enhances the expression of Gria2, an AMPA receptor subunit critical for OPC proliferation. Furthermore, supplementation with the ACSS2 substrate acetate preserved the number of OPCs, promoted remyelination after injury and improved cognitive function in aged mice. Together, our findings highlight the essential role of ACSS2-mediated acetate utilization in maintaining the OPC population and promoting myelin production during development, demyelination and aging.

Aging is associated with progressive tissue dysfunction, leading to frailty and mortality. Characterizing aging features, such as changes in gene expression and dynamics, shared across tissues or specific to each tissue, is crucial for understanding systemic and local factors contributing to the aging process. We performed RNA sequencing on 13 tissues at six different ages in male and female African turquoise killifish, the shortest-lived vertebrate that can be raised in captivity. This comprehensive, sex-balanced 'atlas' dataset revealed varying strength of sex-age interactions across killifish tissues and age-altered genes and biological pathways that are evolutionarily conserved in mice and humans. We discovered a female-biased myeloid shift with age in the killifish hematopoietic organ, developed tissue-specific 'transcriptomic clocks' and identified biomarkers predictive of chronological age. We showed the importance of sex-specific clocks for selected tissues, validated the tissue clocks with an independent transcriptomic dataset and used them to evaluate different lifespan interventions in the killifish. Our work provides a comprehensive resource for studying aging dynamics across tissues in the killifish, a powerful vertebrate aging model.

Epigenetic clocks estimate biological age from DNA methylation patterns at CpG sites, providing robust predictions of mortality and morbidity risk. "Blue zones"-regions of exceptional longevity-offer a unique opportunity to investigate how biological aging diverges from chronological age. However, standard clocks are typically trained on large, heterogeneous datasets, reflecting average population trends rather than region-specific dynamics. Using data from the Costa Rican Longevity and Healthy Aging Study (CRELES), we profiled DNA methylation from residents of the Nicoya blue zone (n = 206) and a comparison population in other parts of Costa Rica (n = 875). We propose training a SuperLearner, an ensemble machine learning approach, on the non-Nicoyan Costa Ricans to optimize predictive performance across existing clocks and flexible machine learners. Theoretically justified by its Oracle property, SuperLearner performs asymptotically as well as the best candidate predictor in the ensemble, resulting in a weighted combination of algorithms used to predict age. We then used this trained model to construct a calibrated hypothesis test comparing residual age distributions between the blue zone region and the comparison population. Comparing our approach to the five top-performing epigenetic clocks (ranked by MSE) in the Costa Rican cohort, only SuperLearner suggested age deceleration (an average of ~ 1 year) in the non-Nicoyan reference group. Before calibration, SuperLearner showed the strongest evidence for slowed biological aging among blue zone Nicoyans, estimating a three-year reduction (-3.05, 95% CI: [-3.64,-2.46]) in epigenetic age. Calibrating with non-Nicoyan Costa Ricans improved consistency between estimates in all clocks, decreasing the estimated aging advantage in Nicoyans to about two years (-1.96, 95% CI: [-2.56,-1.37]). This approach provides a robust framework for estimating longevity in distinct regions when a relevant comparison population is available.

Biological age provides a more direct reflection of physiological status than chronological age, serving as a vital measure to evaluate health risks and aging interventions. While steroid metabolomics offers rich information for exploring aging mechanisms, the complex and nonlinear interactions within metabolic networks remain challenging in modeling. Here, we propose and describe METRON as a deep learning framework to predict biological ages from steroid metabolomics. Specifically, a Metabolite Interaction Perception Module (MIPM) is proposed to capture the interactions. Subsequently, a Group-Rational Kolmogorov-Arnold Network is also integrated to capture intricate dependencies and enhance the representation capability. We demonstrate that METRON achieves promising performance as compared to other machine learning and deep learning methods. Beyond performance, METRON offers interpretability by recovering the established markers such as Dehydroepiandrosterone (DHEA) and identifying 17-hydroxyprogesterone (17-OH-P4) as the key signature linked to hypothalamic-pituitary-adrenal axis dynamics. These results support the capacity of METRON not only to estimate biological age but also to uncover underappreciated metabolic drivers behind aging.

Vascular senescence is a key contributor to ageing-related diseases, including atherosclerosis. Initial intervention is based on aggressive management of traditional risk factors, yet microbial metabolites remain underestimated as modifiable factors. We recently identified phenylacetate (PAA), a gut microbiota-linked metabolite, as a potent accelerator of endothelial senescence, raising the question of its causal role in atherosclerosis. Here, we show that PAA promotes vascular niche senescence and perivascular adipose tissue (PVAT) dysfunction, associated with atherosclerosis in humans and mice. Furthermore, PAA administration to atherosclerosis-prone mice was sufficient to drive atherosclerosis without altering lipid profile. Mechanistically, we found that PAA induces senescence-messaging secretome, containing IL6, from endothelial cells, which stimulates Notch1 and disrupts insulin signaling in adipocytes. Blocking the PAA-IL6-Notch1 axis as well as senolytics rescued adipocyte senescence and dysfunction. Identification of the strong link between PAA and atherosclerosis opens new avenues for microbiome-targeted preventive and therapeutic strategies in ageing.