Longevity Papers

Aging is the primary risk factor for most neurodegenerative diseases, yet the cell-type-specific progression of brain aging remains poorly understood. Here, human cell-type-specific transcriptomic aging clocks are developed using high-quality single-nucleus RNA sequencing data from post mortem human prefrontal cortex tissue of 31 donors aged 18-94 years, encompassing 73,941 high-quality nuclei. Distinct transcriptomic changes are observed across major cell types, including upregulation of inflammatory response genes in microglia from older samples. Aging clocks trained on each major cell type accurately predict chronological age, capture biologically relevant pathways, and remain robust in independent single-nucleus RNA-sequencing datasets, underscoring their broad applicability. Notably, cell-type-specific age acceleration is identified in individuals with Alzheimer's disease and schizophrenia, suggesting altered aging trajectories in these conditions. These findings demonstrate the feasibility of cell-type-specific transcriptomic clocks to measure biological aging in the human brain and highlight potential mechanisms of selective vulnerability in neurodegenerative diseases.

The biological feasibility of human rejuvenation remains a subject of intense debate, yet answering this question is critical for guiding research strategies. Should aging research focus on reversing aging in older individuals, or on pausing its progression at earlier ages? We address this question with evolutionary biology. Classic evolutionary theories of aging - damage accumulation, antagonistic pleiotropy, and the disposable soma - consider aging as a detrimental byproduct of evolution. From this perspective, rejuvenation should confer strong fitness advantages and therefore be expected to evolve in species experiencing substantial aging in the wild. Its rarity in nature should thus be interpreted as evidence of its mechanistic implausibility. Yet, rejuvenation does occur in a few species, and, paradoxically, it is typically induced by stress but not used under optimal conditions. Using mathematical modeling of lifespan plasticity in eusocial insects, we show that this pattern cannot be reconciled with classic theories of aging, revealing an internal contradiction between these theories and the observed avoidance of rejuvenation. By contrast, the pathogen control hypothesis - which interprets aging as an adaptive, programmed process -offers a consistent evolutionary framework for understanding and potentially achieving rejuvenation.

Biological age refers to a person's overall health in aging, as distinct from their chronological age. Diverse measures of biological age, referred to as "clocks", have been developed in recent years and enable risk assessments, and an estimation of the efficacy of longevity interventions in animals and humans. While most clocks are trained to predict chronological age, clocks have been developed to predict more complex composite biological age outcomes, at least in humans. These composite outcomes can be made up of a combination of phenotypic data, chronological age, and disease or mortality risk. Here, we develop the first such composite biological age measure for mice: the mouse phenotypic age model (Mouse PhenoAge). This outcome is based on frailty measures, complete blood counts, and mortality risk in a longitudinally assessed cohort of male and female C57BL/6 mice. We then develop clocks to predict Mouse PhenoAge, based on multi-omic models using metabolomic and DNA methylation data. Our models accurately predict Mouse PhenoAge, and residuals of the models are associated with remaining lifespan, even for mice of the same chronological age. These methods offer novel ways to accurately predict mortality in laboratory mice thus reducing the need for lengthy and costly survival studies.

The mechanisms through which mutations in splicing factor genes drive clonal hematopoiesis (CH) and myeloid malignancies, and their close association with advanced age, remain poorly understood. Here we show that telomere maintenance plays an important role in this phenomenon. First, by studying 454,098 UK Biobank participants, we find that, unlike most CH subtypes, splicing-factor-mutant CH is more common in those with shorter genetically predicted telomeres, as is CH with mutations in PPM1D and the TERT gene promoter. We go on to show that telomere attrition becomes an instrument for clonal selection in advanced age, with splicing factor mutations 'rescuing' HSCs from critical telomere shortening. Our findings expose the lifelong influence of telomere maintenance on hematopoiesis and identify a potential shared mechanism through which different splicing factor mutations drive leukemogenesis. Understanding the mechanistic basis of these observations can open new therapeutic avenues against splicing-factor-mutant CH and hematological or other cancers.

Aging varies widely across species yet exhibits universal statistical regularities, such as Gompertzian mortality and scaling laws, challenging efforts to link microscopic mechanisms with macroscopic outcomes. We present a minimal phenomenological model that captures these patterns by reducing complex physiology to three variables: a dynamic factor characterizing reversible physiological responses to stress, an entropic damage variable reflecting irreversible information loss, and a regulatory noise term. This framework reveals two fundamental aging regimes. In stable species, including humans, aging is driven by linear damage accumulation that gradually erodes resilience, producing a hyperbolic trajectory toward a maximum lifespan. In unstable species, such as mice and flies, intrinsic instability drives exponential divergence of biomarkers and mortality. Model predictions agree with DNA methylation dynamics, biomarker autocorrelation, and survival curves across taxa. Crucially, this regime-based view informs intervention strategies at three levels: (i) targeting dynamic hallmarks, (ii) reducing physiological noise, and (iii) slowing or reversing entropic damage - offering a roadmap from near-term healthspan gains to potential extension of human lifespan beyond current limits.

Background: Cognitive reserve (CR) explains individual resilience to age-related cognitive decline, yet its neurobiological basis remains elusive. Current CR proxies lack direct mechanistic links, necessitating a system-level approach integrating brain structure-function interactions. Methods: We developed a novel CR metric using structural MRI and resting-state fMRI from 1,280 older adults. A youth-derived structural-functional prediction model estimated maximal attainable brain function in elders. CR was quantified as the deviation between observed and predicted function. Cross-sectional and longitudinal analyses assessed CR's spatial distribution, cognitive associations, and pathological relevance in MCI/AD cohorts. Results: CR hubs localized to prefrontal, cingulate, and precuneus regions, organized within high-order networks. Higher CR predicted slower cognitive decline (r = -0.21, p < 0.001) and correlated with reduced A{beta} deposition (r = -0.63, p < 0.001). CR demonstrated domain-specific associations with memory, attention, and processing speed. MCI exhibited broader CR reductions than AD, particularly in frontotemporal regions, likely reflecting stage-specific neuroplastic dynamics: early MCI retains partial compensatory capacity but inefficient CR utilization under mounting pathological stress, whereas advanced AD transitions to irreversible structural damage that disrupts CR's adaptive "software" mechanisms. Conclusions: This study establishes CR as a dynamic neuroprotective framework, bridging functional resilience and structural integrity. CR's spatial specificity and inverse link to amyloid pathology highlight its potential as an early biomarker for resisting pathological aging.