Aims: Human leukocyte antigen (HLA) polymorphism influences immunity by balancing protection against pathogens with the preservation of self-tolerance. This balance has been proposed to affect longevity, and associations with HLA variants have been reported. However, studies in this field have often yielded inconsistent findings due to small sample sizes and low-resolution genotyping methods. We aimed to identify HLA alleles linked to longevity while overcoming these previous limitations.

Methods: We performed high-resolution HLA genotyping using targeted sequencing (HLA-seq) in 1,265 long-lived individuals (long-lived individuals (LLI); ≥ 94 years) from Germany and compared their HLA allele frequencies with those of a large control population of 3.4 million individuals from the German Bone Marrow Donor Registry (DKMS) using χ² (chi-square) tests.

Results: Six HLA alleles were significantly associated with longevity. Of those, two exhibited the most robust associations: A*01:01g (odds ratio (OR) = 0.87; 95% confidence interval (CI): 0.80-0.95; adj. P = 0.02) and DRB1*13:02g (OR = 1.24; 95% CI: 1.10-1.41; P = 0.01). DRB1*13:02g was replicated in the UK Biobank after Bonferroni correction, whereas A*01:01g showed directionally concordant nominal support but did not remain significant after multiple-testing correction.

Conclusion: Both DRB1*13:02g and A*01:01g have previously been implicated in dementia-related phenotypes. These observations support the hypothesis that HLA variation may influence longevity partly through pathways linked to neurodegeneration. This study provides a high-resolution (2-field) HLA dataset for a longevity cohort, which should be valuable for future investigations.

Hormesis, the biphasic dose-response by which mild stressors trigger adaptive programs that leave cells better defended, has become the standard lens through which geroscience interprets lifespan-extending interventions. However, the supporting evidence comes largely from young or middle-aged animals. This review argues that the hormetic window, i.e., the range of stimulus intensities that an organism can convert into net benefit, is set not by chronological age but by integrated adaptive reserve, which is shaped jointly by aging biology, cumulative life-history exposures, and comorbidity burden. Because stress-response pathways involving nuclear factor erythroid 2-related factor 2 (NRF2), heat shock factor 1 (HSF1), forkhead box O (FOXO), adenosine monophosphate (AMP)-activated protein kinase (AMPK), autophagy, and the telomere-associated DNA damage response are progressively attenuated, and because immune resilience governs the sensing, resolution, and repair phases of any adaptive response, the window both narrows and shifts toward lower doses. Doses clearly restorative in youth can therefore fall on the damaging side of the curve in old age, and two individuals of identical chronological age may respond very differently. We apply this framework to five paradigms: mitohormesis, caloric restriction, thermal stress, exercise, and genotoxic stress, and show that the stimulus generally retains its signal in old age while the downstream amplification machinery becomes rate-limiting. Interventions with explicitly age-dependent effects, including senolytics, nicotinamide adenine dinucleotide (NAD⁺) precursors, partial reprogramming, B-cell lymphoma-extra large (Bcl-xL) overexpression, and stem-cell-derived extracellular vesicles, are examined as complementary probes of the same principle. The review closes with implications for geriatric trial design: comprehensive geriatric assessment combined with molecular biomarkers, longitudinal monitoring of a moving window, explicit safety thresholds, and sex-disaggregated analysis.

Cellular senescence is increasingly recognized as a key contributor to many age-related disorders and diseases, and senotherapeutics, therapies that target senescent cells (SCs), have indicated benefits in multiple preclinical models, including models of obesity, metabolic syndrome/diabetes, and their complications. Importantly, SCs are not a uniform population. They differ by originating cell type, stimuli by which senescence was induced, time since induction of senescence, and the tissue and microenvironment in which senescent cells are located, including the composition and magnitude of the senescence-associated secretory phenotype (SASP). Recent studies have indicated that senescent cell populations comprise cells that release inflammatory SASP factors and less inflammatory senescent cells that release growth factors. Senolytics, agents that eliminate senescent cells, preferentially remove the more inflammatory senescent cells while sparing the less inflammatory senescent cells that arise during processes such as acute wound healing. In another study, senescent cell heterogeneity was investigated in adipose tissue impacted by obesity, with a focus on senescence marker expression and cell-type specificity. p16⁺ senescent endothelial cells were a key source of SASP factors within adipose tissue, but p21⁺ senescent preadipocytes and immune cells also contributed substantially to the inflammatory milieu. Identifying and selectively targeting the more pathogenic, pro-inflammatory senescent cell populations may be facilitated by single-cell-level analyses to elucidate the extent of senescent cell heterogeneity and markers of different senescent cell subpopulations. Appreciating the diversity of senescent cells may be critical, since refining senotherapies based on specific SC subtypes may lead to the development of individualized and personalized therapies, potentially improving upon existing broader-spectrum strategies.

We are entering a historic demographic transition: within decades, one-third of our lives will unfold after age 60, and functional decline typically begins ten to twenty years before disease onset. Yet aging is increasingly malleable: today’s 68-year-olds show the functional profile 62-year-olds showed in earlier cohorts, a measured gain in intrinsic capacity. This gain has not yet translated into a matching compression of morbidity, and the gap between lifespan and healthspan continues to widen. Closing it through geroscience-based prevention is both a scientific opportunity and a public health necessity.This Call to Action synthesizes contributions from 60 experts convened at the Paris Healthy Longevity Summit (May 20, 2026, French National Academy of Medicine, Paris) under the High Patronage of President Emmanuel Macron, organized around one guiding question: how to make healthy longevity accessible to the greatest number of people. Contributions were synthesized into five priority pillars and fifteen actions.Five priority pillars emerged: embedding prevention across the life course; large-scale deployment of the WHO’s ICOPE program; adapting health care professional training; investing in geroscience research and biomarker validation; and changing the cultural image of aging while reorganizing care around healthy longevity. Key recommendations include a healthy longevity check-up from age 50, systematizing ICOPE assessment at every point of contact with the population, a geroscience biomarker-validation consortium, and territorial Healthy Aging Coalitions to reduce socioeconomic gaps in healthy life expectancy.It is addressed to public authorities, health care institutions, research funders, employers, insurers, and civil society: the evidence is converging, and stakeholders are ready to act.

Aims: Δ133p53α is a naturally occurring isoform of the human p53 protein that inhibits p53-mediated cellular senescence. We previously reported that transgenic expression of this senescence-inhibitory p53 isoform counteracts aging-associated pathological changes in progeria model mice (heterozygous Lmna^G609G/+). The anti-aging effect of Δ133p53α was attributed in part to reduced levels of the proinflammatory cytokine IL-6. This study aims to comprehensively profile Δ133p53α-induced changes in cytokines and chemokines.

Methods: A Luminex-based multiplex quantitative assay was performed using mouse serum samples from transgenic Δ133p53α-expressing Lmna^G609G/+ mice and non-expressing controls. Quantitative RT-PCR and RNA in situ hybridization assays were used to assess Cxcl10 expression in mouse tissues. In addition, gene expression datasets from human tissues were analyzed.

Results: In the Luminex assay, used as an exploratory screen, transgenic Δ133p53α expression was suggestively associated with reduced serum levels of not only IL-6 but also CXCL1, IL-1α, and CXCL10. We further characterized CXCL10, which has not previously been linked to progeria in mice or humans. Consistent with reduced serum CXCL10 levels, both young (15-week-old) and old (10-month-old) Δ133p53α-expressing Lmna^G609G/+ mice showed reduced Cxcl10 expression in the liver, spleen, and brain, major organs that produce CXCL10, compared with age-matched non-expressing controls. In naturally aged wild-type mice (2 years old), transgenic Δ133p53α expression also significantly repressed Cxcl10 expression in the spleen and brain. An inverse association between CXCL10 and Δ133p53α levels was observed in human spleen tissues.

Conclusion: CXCL10, a proinflammatory chemokine elevated in both accelerated and natural aging, is a potential target of the anti-inflammatory activity of Δ133p53α.