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An open benchmark and language models for AI in aging biology.

Over the past two decades, human aging has been characterized across DNA methylation, transcriptomic, proteomic, and clinical modalities, yet no benchmark evaluates whether AI systems can interpret these heterogeneous data types in the context of aging biology. We introduce LongevityBench, an open suite of 17 tasks spanning five biodata domains, and use it to assess 18 frontier AI systems from six developer teams. Despite recent advances in AI, no single model dominates all tasks, with omics-based age prediction being the hardest task regardless of scale. To test whether these gaps can be closed without frontier-scale resources, we fine-tuned a family of five multitask Longevity-LLMs on domain-specific aging data. The compact (0.6B-9B parameters) Longevity-LLMs matched or exceeded far larger frontier systems on LongevityBench, showing that general-purpose language models can be adapted to structured-omics tasks. We publicly release the benchmark, models, and Longevity Claw, an agentic research interface for aging researchers.

Aging

DNA methylation-based ageing in a deuterostome invertebrate: an epigenetic clock for the crown-of-thorns seastar (Acanthaster cf. solaris).

Accurate and reliable ageing tools are essential for wildlife conservation and management. While DNA methylation has emerged as a promising tool for age estimation in vertebrates, its application to invertebrates remains contested and has been limited to arthropods. Here, we develop an epigenetic clock for the Pacific crown-of-thorns seastar (CoTS; Acanthaster cf. solaris), a destructive coral predator contributing to habitat degradation across Indo-Pacific reefs. Using Oxford Nanopore Technologies, we generated whole-genome DNA methylation profiles across five age groups and identified 1910 CpG sites with methylation patterns significantly associated with age. We then fitted age prediction models using elastic net regression and evaluated predictive performance with leave-one-out cross-validation (LOOCV), achieving a mean absolute error of 0.31 ± 0.22 years, corresponding to 4-6% of the CoTS lifespan (5-8 years). This accuracy suggests the potential to differentiate annual cohorts, supporting future management-relevant inference. To facilitate practical implementation, we constructed an optimized epigenetic clock from 14 CpG sites consistently selected across LOOCV iterations. Our results demonstrate that DNA methylation-based age estimation is feasible in a deuterostome invertebrate, extending epigenetic ageing approaches beyond arthropods and establishing their potential to advance age determination and management in invertebrates that lack reliable ageing methods.

Animals

A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.

BACKGROUND: DNA methylation (DNAm) provides a window to characterize the impacts of environmental exposures and the biological aging process. Epigenetic clocks are often trained on DNAm using penalized regression of CpG sites, but recent evidence suggests potential benefits of training epigenetic predictors on principal components. METHODOLOGY/FINDINGS: We developed a pipeline to simultaneously train three epigenetic predictors; a traditional CpG Clock, a PCA Clock, and a SuperLearner PCA Clock (SL PCA). We gathered publicly available DNAm datasets to generate i) a novel childhood epigenetic clock, ii) a reconstructed Hannum adult blood clock, and iii) as a proof of concept, a predictor of polybrominated biphenyl exposure using the three developmental methodologies. We used correlation coefficients and median absolute error to assess fit between predicted and observed measures, as well as agreement between duplicates. The SL PCA clocks improved fit with observed phenotypes relative to the PCA clocks or CpG clocks across several datasets. We found evidence for higher agreement between duplicate samples run on alternate DNAm arrays when using SL PCA clocks relative to traditional methods. Analyses examining associations between relevant exposures and epigenetic age acceleration (EAA) produced more precise effect estimates when using predictions derived from SL PCA clocks. CONCLUSIONS: We introduce a novel method for the development of DNAm-based predictors that combines the improved reliability conferred by training on principal components with advanced ensemble-based machine learning. Coupling SuperLearner with PCA in the predictor development process may be especially relevant for studies with longitudinal designs utilizing multiple array types, as well as for the development of predictors of more complex phenotypic traits.

DNA Methylation

[Research Advances on Mechanisms and Interventions of DNA Methylation-Regulated Aging-Related Imbalance in Bone Metabolism].

Aging can induce age-related bone diseases such as osteoporosis. DNA methylation, a core epigenetic regulatory mechanism, participate in the pathological process of aging-induced bone metabolism imbalance by modulating gene expression at the epigenetic level. Using S-adenosylmethionine as a methyl donor, it exhibits characteristics of hypomethylation in genomic repetitive regions and abnormal methylation in CpG islands of promoters of key bone metabolism genes with advancing age. The "epigenetic clock" constructed based on these features can accurately predict an individual's biological age. In bone metabolism, DNA methylation disrupts the osteoblast-osteoclast balance by targeting key factors. Such abnormalities are driven by aging-related inflammation and oxidative stress, while bone loss feedback exacerbates epigenetic disorders, forming a vicious cycle. Targeted intervention strategies have demonstrated significant potential in addressing bone metabolism-related issues. Low-dose DNA methyltransferase inhibitors can improve bone metabolism; nutrients such as folate and cobalamin maintain methylation homeostasis by optimizing one-carbon metabolism pathways; while CRISPR/dCas technology enables precise regulation in the cellular and animal levels, thereby affecting bone metabolism. However, existing strategies still face challenges such as off-target effects and low delivery efficiency. Future research needs to deepen mechanistic studies, optimize intervention methods, and promote their translation into clinical prevention and treatment of osteoporosis.

DNA Methylation

Age-related changes in the immune system of mice of eight medium and long-lived strains and hybrids. I. Organ, cellular, and activity changes.

Fifty-three organ, cellular and activity indices were assessed in aging mice of 8 strains and hybrids (5 inbred strains, 1 random bred strain and 2 hybrids of inbred strains) in an attempt to determine which aspects of immunologic aging are characteristic of the species. The results indicate that thymic weight, cellular, and activity indices exhibit a statistically significant negative correlation with age for mice of all 8 strains and hybrids; and B cell cellular indices show a statistically significant positive correlation with age for all mice, while the B cell activity index, lipopolysaccharide response, is dependent on the strain or hybrid. This correlation study supports the view that the T cell component of the immune system deteriorates with age while the B cell component remains relatively intact. Further, the results suggest that thymic aging is a characteristic of the mouse species and that the intrinsic "clock" for immunologic aging resides in the thymus, because most splenic and lymph node T cell activity and cellular indices are associated with thymic weight and cellular indices. Finally, the findings that indices which correlate best with age show the same trend for all strains and hybrids examined suggest that (a) if randomly occurring somatic mutation does play a role in immunologic aging, its influence is limited, and (b) genetic factors not easily influenced by environmental factors regulate immunologic aging.

Aging

Adult age and the rate of an internal clock.

Two experiments were conducted to determine whether young and old adults differ in the rate of a hypothetical internal clock. Clock rate was measured as the slope of the function relating actual duration to perceived duration. No age differences were apparent when subjects were asked to judge the duration of a flash of light in Exp. I, or to judge the duration of a dark interval between two light flashes in Exp. II. It was concluded that there is no evidence to support the hypothesis that perceptual and motor speed differences associated with increased age can be attributable to a slower rate of internal time.

Adolescent

Clonal haematopoiesis of indeterminate potential and epigenetic age acceleration: Systematic review and meta-analysis.

Clonal haematopoiesis of indeterminate potential (CHIP) represents somatic mutations in haematopoietic stem cells that drive clonal expansion. Epigenetic age acceleration (EAA), estimated from DNA methylation (DNAm) clocks, may capture age-related changes in haematopoiesis. This systematic review and meta-analysis was conducted to synthesise evidence on associations between CHIP and EAA and explore shared biological mechanisms that may underlie this relationship. Six databases were searched from January 1, 2011, to June 6, 2025, adhering to PRISMA 2020. Random-effects meta-analyses were performed. Five studies comprising 7483 individuals (ages 55-79, 67.1% female) assessing associations between CHIP and DNAm clocks were included. Across studies, CHIP individuals had higher EAA than no-CHIP individuals, and larger clones were associated with higher EAA. Meta-analysis of three cross-sectional studies (n = 6946) showed that CHIP had higher EAA versus no-CHIP for Horvath1Age IEAA (mean difference, MD=2.84 years, 95% confidence interval, CI: 1.49-4.19), HannumAge EEAA (MD=2.31 years, 95% CI: 1.14-3.49), PhenoAge (MD=1.84 years, 95% CI: 0.96-2.71), and GrimAge (MD=1.20 years, 95% CI: 0.80-1.61). Both DNMT3A- and TET2-mutated CHIP were associated with higher EAA with TET2-mutated CHIP showing larger effect sizes and more consistent associations than DNMT3A-mutated CHIP across DNAm clocks tested. Higher EAA may also act as an effect modifier for morbidity and mortality in CHIP. Larger longitudinal studies are needed to verify a temporal relationship and determine whether EAA provides incremental prognostic value for morbidity and mortality in CHIP.

Humans

Accelerated Biological Aging Increases the Risk of Head and Neck Cancer: Insights From Genetic Instruments of Epigenetic Clocks.

Epigenetic clocks are robust biomarkers of biological aging and have been associated with cancer susceptibility. However, the relationship between genetically predicted epigenetic age acceleration and head and neck cancer risk remains unclear. Using a large case-control study of 2189 head and neck squamous cell carcinoma (HNSCC) cases and 2189 age- and sex-matched controls, we investigated the associations between polygenic scores (PGSs) for multiple epigenetic clocks and HNSCC risk, and evaluated their potential causal roles using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS)-identified single nucleotide polymorphisms (SNPs) associated with four epigenetic clocks (HannumAge, HorvathAge, GrimAge, and PhenoAge) were used to construct clock-specific PGSs. Logistic regression models were applied to assess associations between PGSs and HNSCC risk, while MR analyses, including inverse-variance weighted (IVW), weighted median, and MR-Egger methods, were used to infer potential causal relationships. Among the 48 epigenetic clock-associated SNPs, 12 showed nominal associations with HNSCC risk, and one variant (rs2275558 in PBX1) remained significant after Bonferroni correction (OR = 0.67, 95% CI: 0.60-0.76). PGSs for all four epigenetic clocks were higher in cases than in controls. In logistic regression analyses, each standard deviation increase in HannumAge PGS was associated with a 25% higher risk of HNSCC (OR = 1.25, 95% CI: 1.10-1.41), whereas HorvathAge, GrimAge, and PhenoAge PGSs showed weaker positive associations (ORs ranging from 1.06 to 1.10). Individuals in the highest PGS quartile for all four epigenetic clocks exhibiting 14%-25% higher risk than those in the lower three quartiles. MR analyses supported potential causal effects of genetically predicted HannumAge (IVW OR = 1.24 per SD increase, 95% CI: 1.09-1.42) and GrimAge (IVW OR = 1.23 per SD increase, 95% CI: 0.98-1.56) on HNSCC risk, with consistent estimates in weighted median analyses. Our results highlight biological aging as a potential etiologic mechanism for HNSCC and suggest that epigenetic clock-related genetic profiles may improve HNSCC risk stratification.

Humans

Epigenetic age acceleration is not strongly associated with cardiorespiratory fitness in heart failure: a pilot study.

BACKGROUND: In heart failure (HF), standard measures such as left ventricular ejection fraction and cardiopulmonary exercise testing incompletely capture interindividual differences in disease status or prognosis. DNA methylation (DNAm) epigenetic clocks, which estimate biological age and epigenetic age acceleration (EAA), may provide complementary insight into cardiorespiratory fitness and systemic aging in HF. RESEARCH DESIGN AND METHODS: We analyzed peripheral blood DNAm from fourteen patients enrolled in REDHART2, a clinical trial of interleukin-1 blockade following hospitalization for acute systolic HF. Genome-wide DNAm was assayed using Illumina EPIC arrays and several clocks were applied to these data. Associations between biological age or EAA and cardiorespiratory fitness measures, inflammatory markers, and clinical parameters were evaluated. RESULTS: All epigenetic clocks demonstrated moderate to strong correlations with chronological age. Biological age was consistently associated with measures of cardiorespiratory fitness, particularly oxygen consumption normalized to fat free mass (VO2_FFM). However, chronological age showed similar associations, and biological age did not significantly improve prediction of VO2 parameters beyond chronological age alone. EAA was not significantly associated with cardiorespiratory fitness for any clock. CONCLUSIONS: In this pilot study, neither biological age nor EAA provided significant predictive value beyond chronological age for cardiorespiratory fitness in patients with HF. CLINICAL TRIAL REGISTRATION NUMBER: NCT03797001.

DNA methylation

Molecular clocks, molecular profiles, and optimum diets: three approaches to the problem of aging.

It has been hypothesized that the deamidation of glutaminyl and asparaginyl residues serves as a molecular clock for many biological processes including protein turnover, development, and aging. At present, this hypothesis has passed some experimental tests which are necessary but not sufficient for its acceptance. The current state of evidence about deamidation as a molecular clock is discussed. In addition, since the molecular biology of aging, especially in humans, is only partly understood, it is of value to develop quantitative, empirical measures of physiological human age and to use these measures to evaluate alternative human living conditions, especially easily adopted alternatives like variations in diet. This may allow some decrease in the suffering and loss from human aging until such time as molecular biology provides superior and more intellectually satisfying answers. An empirical system which consists of quantitative measurement of several hundred human chemical constituents followed by computerized pattern recognition is described. It is hoped that this system will eventually become an aid in the minimization of the rate of human aging through changes in diet and other factors.

Adult

Form and function of actin impacts actin health and aging.

The actin cytoskeleton is a fundamental and highly conserved structure that functions in diverse cellular processes, yet its direct contribution to organismal aging remains unclear. Here, we systematically interrogated how genetic and pharmacologic perturbations of actin structure and function influence lifespan and various hallmarks of aging in Caenorhabditis elegans. Whole-animal and tissue-specific knockdown of actin and key actin-binding proteins (ABPs)-arx-2 (Arp2/3), unc-60 (cofilin), and lev-11 (tropomyosin)-led to premature disruption of filament organization, reduced lifespan, and tissue-specific physiological defects. Actin dysfunction also displayed a more "aged" transcriptome using previously validated transcriptomics clocks, and broadly exacerbated many age-associated phenotypes, including mitochondrial dysfunction, lipid dysregulation, loss of proteostasis, impaired autophagy, and intestinal barrier failure. Pharmacological destabilization with Latrunculin A mirrored genetic knockdowns, while mild stabilization with Jasplakinolide modestly extended lifespan, emphasizing that optimal and finely tuned actin function is critical for healthy aging. Finally, analysis of human genome-wide association data revealed that common ACTB polymorphisms correlate with differences in age-related decline in gait speed, suggesting some links between aging and actin across organisms. Taken together, our results provide a comprehensive and publicly accessible resource that maps, for the first time, how changes in actin integrity correlate with diverse aging phenotypes across tissues. This descriptive framework is intended to enable future mechanistic discovery by offering a deep, unbiased dataset that can be integrated with emerging studies to define how actin dynamics can potentially influence aging.

actin

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University M&#xfc;nster.

Journal Article

Age and early life adversity shape heterogeneity of the epigenome across tissues in macaques.

Age and early life adversity (ELA) are key determinants of health, but whether they affect similar physiological mechanisms across tissues is unknown. We generated DNA methylation (DNAm) profiles across 14 tissues in 237 semi-free-ranging rhesus macaques with naturally occurring ELA. Age-associated DNAm was predominantly tissue dependent, yet tissue-specific epigenetic clocks showed that epigenetic aging was relatively consistent within individuals. ELA effects were adversity dependent, but each ELA exerted coordinated effects across tissues. Although ELA targeted many of the same loci as age, the directions of effects differed, which indicates that ELA does not uniformly increase epigenetic age. Instead, ELA leaves a coordinated, cross-tissue epigenetic signature that is distinct from-yet intertwined with-age-related differences, which advances our understanding of how early environments sculpt the molecular foundations of aging and disease.

Animals

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University M&#xfc;nster.

Journal Article

Epigenetic aging and autosomal methylation remodeling in Anderson-Fabry disease.

Anderson-Fabry disease (AFD) is a rare X-linked lysosomal storage disorder characterized by marked clinical heterogeneity and incompletely understood genotype-phenotype correlations. While X-chromosome inactivation has been extensively investigated, the contribution of autosomal epigenetic mechanisms to phenotypic variability remains poorly defined. Here, we performed an exploratory genome-wide DNA methylation analysis in 32 AFD patients (22 females and 10 males; mean age 51.7&#xa0;years) recruited within a multicenter regional research project in Calabria (Italy). DNA methylation profiling was conducted using the Infinium MethylationEPIC v2.0 array. The analysis integrated two complementary approaches: differential methylation analysis and evaluation of biological aging through multiple epigenetic clocks, including Horvath, Hannum, PhenoAge, Skin & Blood, GrimAge, and DunedinPACE. Exploratory methylome-wide analysis identified a limited set of CpG loci showing nominal evidence of methylation differences between carriers of pathogenic and non-pathogenic variants; however, none remained statistically significant after correction for multiple testing. Annotation of the top-ranking nominal CpG associations highlighted genes involved in biological processes including vascular regulation, intracellular trafficking, cytoskeletal organization, immune signaling, and lipid metabolism. No significant differences between groups were observed for the conventional epigenetic age-acceleration measures examined. In contrast, carriers of pathogenic variants showed significantly higher DunedinPACE values (p&#xa0;=&#xa0;0.0328), indicating a faster estimated pace of biological aging. This finding suggests that DunedinPACE may capture aspects of the cumulative systemic burden associated with pathogenic GLA variants, although confirmation in larger independent cohorts is required. Overall, this pilot epigenomic study provides preliminary evidence that autosomal epigenetic remodeling and biological aging acceleration may contribute to phenotypic heterogeneity in AFD.

Anderson-Fabry disease

GT-Mamba: a Topology-Aware Graph-State space model for robust and interpretable epigenetic age prediction.

MOTIVATION: Current epigenetic clocks face a trade-off between predictive accuracy and biological interpretability, often relying on dataset-specific correction to generalize across cohorts. We propose GT-Mamba, a novel architecture that integrates a Structure-Aware Graph Transformer with the Mamba state space model. This design captures CpG topological correlations and genome-wide long-range dependencies. RESULTS: GT-Mamba demonstrates strong out-of-the-box robustness across heterogeneous independent validation cohorts, achieving a weighted average MAE of 4.43&#x2009;years. Notably, it effectively generalizes to EPIC 850k arrays despite partial feature missingness, and maintains consistent performance across homologous age distribution shifts (MAE 2.94&#x2009;years in a young cohort). Ablation studies confirm that graph topology contributes to improved robustness against noise. Mechanistic analysis suggests that the model captures methylation patterns associated with both developmental and functional processes. AVAILABILITY: Source code and pre-trained models are freely available at https://github.com/NENUBioCompute/GT-Mamba and archived on Zenodo (DOI: 10.5281/zenodo.19703155).

Epigenesis, Genetic