Face photo-based age provides a cost-effective and readily accessible tool for biological age studies. However, artificial intelligence-based face photo age models were usually trained on a single front-view photo per subject. Here, we hypothesized that face photo-based age prediction performance might be improved by using multiple photos of the same subject at the same time, captured from different angles. To test this hypothesis, we used an available dataset containing mugshots and developed age prediction models trained on (a) only front-view images, (b) only the side-view images, and (c) both front and side images. We found that accurate age prediction is possible using side photos despite the smaller facial area compared to front-facing photos [mean absolute error (MAE) = 3.1 years for the front-view and MAE = 3.7 years for the side-view images]. The age prediction performance further improved by using 2 images from one person at the same time, captured from 2 different angles, front and side (MAE = 2.88 years). We found that subjects who age faster based on front-view face photos generally age faster based on side-view face photos. We also found that side-view models handle the rotation of the face better compared to the front-view model. In summary, we showed that 2 photos of the face at different angles can slightly improve age prediction and may provide a more robust and better approximation of biological age compared to single photos, serving as a useful tool for personalized medicine, aging intervention, and rejuvenation studies. The models are available for academic research purposes at https://photoage.sztaki.hu/ .

Physical fitness is a key determinant of health, yet the molecular pathways linking fitness to the risk of aging-related diseases remain unclear. We examined associations between DNA methylation-based protein level estimates (EpiScores) and five fitness traits-VO2max, GripStrength, JumpMax, body mass index (BMI), and cognition-in a cohort of 290 mostly old individuals (mean age of 60 ± 11 years). EpiScores for 109 plasma proteins were obtained using the MethylDetectR tool and tested for associations with fitness traits. We found 33 significant fitness predictor-EpiScore associations independent from age and sex. Integration with available EpiScore-disease associations revealed overlapping pathways linking fitness and chronic disease risk. We found 51 fitness predictor-disease associations based on EpiScores. The BMI was positively associated with diabetes, stroke, ischemic heart disease, lung cancer, COPD, IBD, and depression, while showing a negative association with rheumatoid arthritis. Cognition was negatively associated with rheumatoid arthritis, depression, and COPD. GripStrength showed negative associations with diabetes and COPD. Finally, jump performance was negatively associated with diabetes, stroke, lung cancer, rheumatoid arthritis, and COPD. We also developed a workflow for evaluating patient-level disease risk by using DNA methylation and fitness measurements. The patient-level risk scores showed strong positive correlations with an independent external CVD EpiScore benchmark supporting validity. Our findings highlight the link between cognitive and physical fitness and protein EpiScores as interpretable molecular markers with potential value for early disease risk stratification and for personalized prevention of aging-related diseases.

Napjaink egyik legjelentősebb demográfiai folyamata a népesség elöregedése. Az idősödő populációban a szív-ér rendszeri betegségek előfordulása jelentősen gyakoribb, aminek kiemelt klinikai jelentősége van. Nemzetközi összehasonlításban Magyarországon nemcsak a várható élettartam, hanem az egészségben eltöltött évek száma is kedvezőtlenebb, mint számos nyugat-európai országban. A kardiovaszkuláris megbetegedések növekvő prevalenciája egyre nagyobb terhet ró az egészségügyi ellátórendszerre mind a diagnosztika, mind a kezelés és a hosszú távú gondozás tekintetében. Az öregedés egyénenként eltérő ütemben zajlik, ami különbséget eredményez a kronológiai és a biológiai életkor között. A modern képalkotó eljárások lehetőséget biztosítanak a kardiovaszkuláris rendszer öregedési folyamatainak részletes vizsgálatára. A strukturális változások és az ezekhez társuló funkcionális eltérések megítélése a standard módszerek mellett korszerű, fejlett technikák alkalmazásával pontosabban értékelhető. Összefoglaló közleményünkben áttekintjük a szív öregedésének biológiai alapjait és képalkotó jellemzőit, valamint bemutatjuk a biológiai életkor meghatározásának jelenlegi lehetőségeit és klinikai perspektíváit.

Abstract Introduction. DACH1 is expressed in renal glomerular podocytes and distal tubules. DACH1 has been described as either a tumor suppressor or oncogene, with increased or decreased abundance depending upon the tissue type. Recent studies showed that poor outcome of prostate cancer was correlated with the deletion of the DACH1 gene, within the 13q21 region, and prostate-specific deletion promoted prostatic intraepithelial neoplasia in prostate onco-mice. DACH1 generates several splice variant isoforms with a common carboxyl (C) terminus that cross-reacts with commercially available antibodies. Methods. We characterized the function of three DACH1 isoforms. We developed a DACH1a isoform-specific antibody. We assessed DACH1a variant vs. DACH1 common C terminal immune reactivity in prostate cancer. Analysis included patient gene expression, tumor histology, tissue culture, and tissue-specific gene knockout transgenic mice. Findings. Expression of DACH1a inhibited AR activity. DACH1a inhibited DNA synthesis and indicators of EMT, contrasting with the effects of DACH1b and DACH1c. Compared to normal tissue, DACH1 expression was reduced in urogenital cancer (kidney cancer (chromophobe, clear cell, papillary) and testicular germ cell), sarcomas, and lung cancer, but increased in acute leukemia, lymphoma, colon and ovarian tumors. The relative levels of expression of the three isoforms of DACH1 (DACH1a, 1b, 1c), however, varied substantially between cancer types. The C terminal antibody cross-reacted with each isoform-generated DACH1 protein. Monoclonal DACH1a specific antibody, which detected DACH1a in the kidney glomerular podocyte and distal tubule, showed a substantially different subcellular distribution to C terminal antibody immune reactivity in benign prostate vs. cancer. We conducted quantitative immunofluorescence at a single cell level using the opal multi-fluorophore technology, using the DACH1a specific antibody and additional DACH1a candidate interactors. Immunofluorescent staining of DACH1a showed reduced staining in prostate cancer compared to adjacent benign tissue. Conclusions. Functional analysis shows DACH1 conveys isoform-specific tumor suppressor functions. Since the DACH1a isoform conveys specific and distinct functions, compared to other DACH1 isoforms, DACH1a isoform specific analysis may be required to predict patient outcome. Citation Format: Kenneth A. Iczkowski, Zhiping Li, HIdetoshi Mori, Danni Li, Samiha Nasser, Csaba Kerepesi, Andras Benczur, Hallgeir Rui, Ritika Harish, Xuanmao Jiao, Fred Saad, Richard G. Pestell. DACH1 conveys isoform specific tumor suppressor functions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 606.

Abstract • Introduction: Patients with metastatic prostate cancer have poor survival with DNA damage repair pathway abnormalities. The cell fate determination factor DACH1 is deleted (shallow or deep deletion) in ∼5-12% of PCa patients, but up to 65% of metastatic PCa. WEE1 kinase is one of the most upregulated kinases in the human prostate cancer kinome associated with metastatic progression in prostate cancer (mCRPC). We determined the potential for differential sensitivity of PCa to Wee1 Kinase inhibitors (WEE1Ki) based on DACH1 expression profiles. • Methods: Analysis of patient gene expression, tumor histology, organoids derived from prostate epithelial cell-specific DACH1 deletion prostate onco-mice, DNA replication fork assays, tissue culture. • Findings: DACH1 deficient (Dach1-/-) cells showed enhanced cell killing by WEE1Ki, that was reversed by reintroduction of DACH1a. Increased sensitivity to WEE1Ki was shown in fibroblasts, prostate cancer cell lines and in organoids derived from human prostate cancer cell lines or the prostate epithelium of Dach1 deletion onco-mice. DACH1 deletion dramatically enhanced non replicating S phase in the presence of WEE1Ki. Dach1-/- cells showed increased replication fork stress, that was reversed by reintroduction of the DACH1a isoform. DACH1 epithelial cell deletion onco-mice, and the prostate organoids derived therefrom, was associated with the induction of epithelial mesenchymal transition (EMT) with a corresponding increase in AKTSer473P, ATRThr1989p and CHK1 Ser345P. Increased sensitivity to WEE1Ki is associated with reduced SETD2 or NSD1/KMT3B expression, and reduced RRM2, a ribonucleotide reductase subunit, thereby inducing dNTP starvation. DACH1 expression was highly correlated with SETD2, NSD1 and RRM2. Gene ontology terms associated with DACH1 DNA binding templates included nucleoside metabolic processes. Like several other tumor suppressor genes (RB, FOXO3), DACH1 restrained dNTP production. dNTP production also requires NDPK (Nucleoside Diphosphate Kinase) encoded by NME genes. Consistent with the inhibition of dNTP production, DACH1a expression in prostate cancer PC3 cells reduced NME1 and NME7 (NDPKA expression), and DACH1 was strongly inversely correlated with NME1 in human prostate cancer (N=491. P 9.9e-24). • Conclusions: As DACH1 deletion PCa subclass conveys specific therapeutic sensitivities, that is dependent upon the DACH1a isoform, testing for DACH1a in patient samples may be warranted. Citation Format: Danni Li, Arijit Ghosh, Zhiping Li, Kenneth Iczkowski, Hidetoshi Mori, Samiha Nasser, Csaba Kerepesi, Andras Benczur, Hallgeir Rui, Ritika Harish, Li Lan, Xuanmao Jiao, Fred Saad, Janne Purhonen, Anthony W. Ashton, Richard G. Pestell. Deletion of the DACH1 gene tumor suppressor increases replication fork stress, epithelial mesenchymal transition and sensitivity to WEE1 kinase inhibitors in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1751.

While scientists argue what aging is and what drives aging, it is widely accepted that our face changes drastically with age and that mortality increases in late life. We hypothesize that people of the same age can be biologically older than others and that the human face may reflect accelerated molecular aging. To test this hypothesis we examine the associations of face photo-based age acceleration with mortality and lifestyle. For this purpose, we trained and tested artificial intelligence models on 442,110 photos of famous people. We found that face photo-based age predicts all-cause mortality for middle-aged and older individuals meaning that those age faster based on their face photo die sooner. We also found that, based on face photos, sport is the slowest aging occupation among famous people consistently to previous findings showing the benefits of exercise to epigenetic aging. Overall, we demonstrate that the face photo-base age model approaches biological age in some extent and provides a low-cost and fast complementary measurement for personalized medicine, as well as aging and rejuvenation studies. The model is available for demonstration and academic research purposes at . ### Competing Interest Statement The authors have declared no competing interest. The project was supported by the European Union project RRF-2.3.1-21-2022-00004 within the framework of the Artificial Intelligence National Laboratory, and the National Research, Development and Innovation Office - NKFIH, FK-146113., ,

Decades of publicly available molecular studies have generated millions of samples testing diverse interventions, yet these datasets were rarely analyzed for their effects on aging. Aging clocks now enable biological age estimation and life outcome prediction from molecular data, creating an opportunity to systematically mine this untapped resource. We developed ClockBase Agent, a publicly accessible platform that reanalyzes millions of human and mouse methylation and RNA-seq samples by integrating them with over 40 aging clock predictions. ClockBase Agent employs specialized AI agents that autonomously generate aging-focused hypotheses, evaluate intervention effects on biological age, conduct literature reviews, and produce scientific reports across all datasets. Reanalyzing 43,602 intervention-control comparisons through multiple aging biomarkers revealed thousands of age-modifying effects missed by original investigators, including over 500 interventions that significantly reduce biological age (e.g., ouabain, KMO inhibitor, fenofibrate, and NF1 knockout). Large-scale systematic analysis reveals fundamental patterns: significantly more interventions accelerate rather than decelerate aging, disease states predominantly accelerate biological age, and loss-of-function genetic approaches systematically outperform gain-of-function strategies in decelerating aging. As validation, we show that identified interventions converge on canonical longevity pathways and with strong concordance to independent lifespan databases. We further experimentally validated ouabain, a top-scoring AI-identified candidate, demonstrating reduced frailty progression, decreased neuroinflammation, and improved cardiac function in aged mice. ClockBase Agent establishes a paradigm where specialized AI agents systematically reanalyze all prior research to identify age-modifying interventions autonomously, transforming how we extract biological insights from existing data to advance human healthspan and longevity.

Aging clocks have emerged as the primary tools for measuring biological aging and have been developed for a wide range of single-omic measurements. Epigenetic aging clocks showed high accuracy in age prediction, however, their biological interpretation is still a challenging task. Transcriptomics aging clocks provide better interpretability but worse age prediction accuracy. To exploit the benefits of both omics techniques, the main goal of this study was to develop the first multi-omics aging clocks based on combined epigenetics and transcriptomics features. For this purpose, we utilized a dataset where reduced representation bisulfite sequencing (RRBS) and RNA-seq measurements were measured at the same time for peripheral blood samples of 182 individuals. Then we trained machine learning models (ElasticNet) using the methylation and gene expression features at the same time. While the most accurate models tended to use exclusively methylation features, we were able to develop highly accurate multi-omics aging clocks too (called CpGenAge). Both the canonical and the non-canonical Nf-κB signaling pathways, with the genes EDA, EDA2R, EDARADD, and CD70, were overrepresented among the gene expression features of the multi-omics aging clocks. The EDARADD, which is a unique hallmark of aging, was represented among both the gene expression and methylation features. By developing single-omic clocks on the same multi-omics dataset, we found that epigenetic age acceleration and transcriptomics age acceleration do not correlate with each other, further supporting the benefits of our multi-omics approach. In summary, here, we demonstrate that multi-omics aging clocks are useful tools to investigate aging and biological age at the multi-omics level. ### Competing Interest Statement The authors have declared no competing interest. HUN-REN, TKCS-2024/37 European Union project within the framework of the Artificial Intelligence National Laboratory., RRF-2.3.1-21-2022-00004 National Research, Development and Innovation Office, https://ror.org/03g2am276, FK-146113

Aging and COVID- 19 are known to influence DNA methylation, potentially affecting the rate of aging and the risk of disease. The physiological functions of 54 volunteers—including maximal oxygen uptake (VO₂ max), grip strength, and vertical jump—were assessed just before the COVID- 19 pandemic and again 3 years later. Of these volunteers, 27 had contracted COVID- 19. Eight epigenetic clocks were used to assess the rate of aging during the 3-year period: DNAmAge showed accelerated aging, and five clocks showed slowed aging (DNAmAgeSkinBlood, DNAmAgeHannum, DNAmFitAge, PhenoAge, and DNAmTL). When we considered only females, we observed a stronger effect in the increase of DNAmAge acceleration, while we observed slowed aging in the case of SkinBloodClock, and DNAmTL. The methylation of the promoter region of the H1 FNT genes, which encodes testis-specific histone H1 family member N (H1fnt) and plays a crucial role in spermatogenesis decreased the most significantly. In contrast, the promoter of CSTL1, which encodes Cystatin-like 1, showed the most significant increase. We found that having COVID- 19 during the 3-year study period significantly increased the progress of aging assessed by DNAmGrimAge, DNAmGrimAge2, and DNAmFitAge (p = 0.024, 0.047, 0.032, respectively, after we adjusted the analysis for baseline variables). The data suggest that COVID- 19 may have a mild long-term effect on epigenetic aging.

Background: The prevalence of cardiovascular disease increases exponentially with advancing age. However, biological age may differ from chronological age, and the mechanisms contributing to accelerated aging remain unclear.: We hypothesized that biological age and accelerated aging are independently associated with acute myocardial infarction (AMI) and may correlate with traditional cardiovascular risk factors. Methods: We analyzed biological age and aging patterns in patients with acute myocardial infarction using data from the prospective VMAJOR-MI-BIOAGE registry. Biological age was estimated via three artificial intelligence (AI)-based models (Visual Geometry Group [VGG], Residual Network [ResNet], and Prisoner), all validated for all-cause mortality prediction, using portrait photographs and laboratory data. Patients were classified as showing accelerated biological aging or not. Groups were compared by medical history, demographic and lifestyle factors, and clinical characteristics of myocardial infarction. A subgroup analysis focused on patients under 65 years. Use of automated AI tools was documented in the methodology per AHA and WAME guidelines. These contributed to age estimation only and did not participate in study design or data interpretation. Results: A total of 267 patients were enrolled; 38% were women. 49% were younger than 65 years. In the overall population (all p<0.05): Women gender aligned with accelerated aging (ResNet, VGG). Single individuals aged more slowly (ResNet). Retirees aged faster than those in managerial roles (Prisoner, ResNet). Physical inactivity was associated with faster aging (VGG). Participants sleeping <7 hours/day had older biological age (ResNet, Prisoner). Heart failure was associated with accelerated aging (Lab model). Among patients under 65 (all p<0.05): Those without prior cardiovascular disease aged more slowly (ResNet). Prior myocardial infarction and cancer were linked to higher biological age (Prisoner): Heart failure (based on lab-based estimates) and high stress levels (Lab model, VGG) were both associated with accelerated aging. Conclusions: Our findings suggest that biological age and age acceleration are relevant risk indicators in patients with acute myocardial infarction. AI-based biological age estimation may provide valuable insights beyond traditional risk factors in cardiovascular risk assessment. This research was supported by the Artificial Intelligence National Laboratory. Grant number: RRF-2.3.1-21-2022-00004

Epigenetic drift, which is gradual age-related changes in DNA methylation patterns, plays a significant role in aging and age-related diseases. However, the relationship between exercise, epigenetics, and aging, and the molecular mechanisms underlying their interactions are poorly understood. Here, we investigated the relationship between cardiorespiratory fitness (CRF), epigenetic aging, and promoter methylation of individual genes across multiple organs in selectively bred low- and high-capacity runner (LCR and HCR) aged rats. Epigenetic clocks, trained on available rat blood-derived reduced representation bisulfite sequencing data, did not reflect differences in CRF between LCR and HCR rats across all four organs. However, we observed organ-specific differences in global mean DNA methylation and mean methylation entropy between LCR and HCR rats, and the direction of these differences was the opposite compared to the age-related changes in the rat blood. Notably, the soleus muscle exhibited the most pronounced differences in promoter methylation due to CRF. We also identified seven genes whose promoter methylation was consistently influenced by CRF in all four organs. Moreover, we found that age acceleration of the soleus muscle was significantly higher compared to the heart and the hippocampus, and significantly lower compared to the large intestine. Finally, we found that the age acceleration was not consistent across organs. Our data suggest that CRF associates with epigenetic aging in an organ-specific and organ-common manner. Our findings provide important insights into the biology of aging and emphasize the need to validate rejuvenation strategies in the context of the organ-specific nature of epigenetic aging.

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.

Epigenetic ‘clocks’ based on DNA methylation have emerged as the most robust and widely used aging biomarkers, but conventional methods for applying them are expensive and laborious. Here we develop tagmentation-based indexing for methylation sequencing (TIME-seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-seq, we applied multi-tissue and tissue-specific epigenetic clocks in over 1,800 mouse DNA samples from eight tissue and cell types. We show that TIME-seq clocks are accurate and robust, enriched for polycomb repressive complex 2-regulated loci, and benchmark favorably against conventional methods despite being up to 100-fold less expensive. Using dietary treatments and gene therapy, we find that TIME-seq clocks reflect diverse interventions in multiple tissues. Finally, we develop an economical human blood clock ( R > 0.96, median error = 3.39 years) in 1,056 demographically representative individuals. These methods will enable more efficient epigenetic clock measurement in larger-scale human and animal studies.

PURPOSE:We develop blood test-based aging clocks and examine how these clocks reflect high-volume sports activity. METHODS:We use blood tests and body metrics data of 421 Hungarian athletes and 283 age-matched controls (mean age, 24.1 and 23.9 yr, respectively), the latter selected from a group of healthy Caucasians of the National Health and Nutrition Examination Survey (NHANES) to represent the general population ( n = 11,412). We train two age prediction models (i.e., aging clocks) using the NHANES dataset: the first model relies on blood test parameters only, whereas the second one additionally incorporates body measurements and sex. RESULTS:We find lower age acceleration among athletes compared with the age-matched controls with a median value of -1.7 and 1.4 yr, P < 0.0001. BMI is positively associated with age acceleration among the age-matched controls ( r = 0.17, P < 0.01) and the unrestricted NHANES population ( r = 0.11, P < 0.001). We find no association between BMI and age acceleration within the athlete dataset. Instead, age acceleration is positively associated with body fat percentage ( r = 0.21, P < 0.05) and negatively associated with skeletal muscle mass (Pearson r = -0.18, P < 0.05) among athletes. The most important blood test features in age predictions were serum ferritin, mean cell volume, blood urea nitrogen, and albumin levels. CONCLUSIONS:We develop and apply blood test-based aging clocks to adult athletes and healthy controls. The data suggest that high-volume sports activity is associated with slowed biological aging. Here, we propose an alternative, promising application of routine blood tests.

To gain insight into how researchers of aging perceive the process they study, we conducted a survey among experts in the field. While highlighting some common features of aging, the survey exposed broad disagreement on the foundational issues. What is aging? What causes it? When does it begin? What constitutes rejuvenation? Not only was there no consensus on these and other core questions, but none of the questions received a majority opinion-even regarding the need for consensus itself. Despite many researchers believing they understand aging, their understanding diverges considerably. Importantly, as different processes are labeled as "aging" by researchers, different experimental approaches are prioritized. The survey shed light on the need to better define which aging processes this field should target and what its goals are. It also allowed us to categorize contemporary views on aging and rejuvenation, revealing critical, yet largely unanswered, questions that appear disconnected from the current research focus. Finally, we discuss ways to address the disagreement, which we hope will ultimately aid progress in the field.

Although cancer is an age-related disease, how the processes of aging contribute to cancer progression is not well understood. In this study, we uncovered how mouse B cell lymphoma develops as a consequence of a naturally aged system. We show here that this malignancy is associated with an age-associated clonal B cell (ACBC) population that likely originates from age-associated B cells. Driven by c-Myc activation, promoter hypermethylation and somatic mutations, IgM+ ACBCs clonally expand independently of germinal centers and show increased biological age. ACBCs become self-sufficient and support malignancy when transferred into young recipients. Inhibition of mTOR or c-Myc in old mice attenuates pre-malignant changes in B cells during aging. Although the etiology of mouse and human B cell lymphomas is considered distinct, epigenetic changes in transformed mouse B cells are enriched for changes observed in human B cell lymphomas. Together, our findings characterize the spontaneous progression of cancer during aging through both cell-intrinsic and microenvironmental changes and suggest interventions for its prevention. Castro, Shindyapina et al. explore how aging promotes B cell lymphoma in mice, identifying a population of age-associated clonal B cells that expands through mutation, c-Myc activation and epigenetic alterations to drive age-associated malignancy.

The lifestyle patterns of top athletes are highly disciplined, featuring strict exercise regimens, nutrition plans, and mental preparation, often beginning at a young age. Recently, it was shown that physically active individuals exhibit slowed epigenetic aging and better age-related outcomes. Here, we investigate whether the extreme intensity of physical activity of Olympic champions still has a beneficial effect on epigenetic aging. To test this hypothesis, we examined the epigenetic aging of 59 Hungarian Olympic champions and of the 332 control subjects, 205 were master rowers. We observed that Olympic champions exhibit slower epigenetic aging, applying seven state-of-the-art epigenetic aging clocks. Additionally, male champions who won any medal within the last 10 years showed slower epigenetic aging compared to other male champions, while female champions exhibited the opposite trend. We also found that wrestlers had higher age acceleration compared to gymnasts, fencers, and water polo players. We identified the top 20 genes that showed the most remarkable difference in promoter methylation between Olympic champions and non-champions. The hypo-methylated genes are involved in synaptic health, glycosylation, metal ion membrane transfer, and force generation. Most of the hyper-methylated genes were associated with cancer promotion. The data suggest that rigorous and long-term exercise from adolescence to adulthood has beneficial effects on epigenetic aging.

Epigenetic clocks can measure aging and predict the incidence of diseases and mortality. Higher levels of physical fitness are associated with a slower aging process and a healthier lifespan. Microbiome alterations occur in various diseases and during the aging process, yet their relation to epigenetic clocks is not explored. To fill this gap, we collected metagenomic (from stool), epigenetic (from blood), and exercise-related data from physically active individuals and, by applying epigenetic clocks, we examined the relationship between gut flora, blood-based epigenetic age acceleration, and physical fitness. We revealed that an increased entropy in the gut microbiome of physically active middle-aged/old individuals is associated with accelerated epigenetic aging, decreased fitness, or impaired health status. We also observed that a slower epigenetic aging and higher fitness level can be linked to altered abundance of some bacterial species often linked to anti-inflammatory effects. Overall our data suggest that alterations in the microbiome can be associated with epigenetic age acceleration and physical fitness.

PURPOSE:Recent evidence has shown that higher tumor mutational burden strongly correlates with an increased risk of immune-related adverse events (irAEs). By using an integrated multiomics approach, we further studied the association between relevant tumor immune microenvironment (TIME) features and irAEs. METHODS:Leveraging the US Food and Drug Administration Adverse Event Reporting System, we extracted cases of suspected irAEs to calculate the reporting odds ratios (RORs) of irAEs for cancers treated with immune checkpoint inhibitors (ICIs). TIME features for 32 cancer types were calculated on the basis of the cancer genomic atlas cohorts and indirectly correlated with each cancer's ROR for irAEs. A separate ICI-treated cohort of non-small-cell lung cancer (NSCLC) was used to evaluate the correlation between tissue-based immune markers (CD8+, PD-1/L1+, FOXP3+, tumor-infiltrating lymphocytes [TILs]) and irAE occurrence. RESULTS:The analysis of 32 cancers and 33 TIME features demonstrated a significant association between irAE RORs and the median number of base insertions and deletions (INDEL), neoantigens (r = 0.72), single-nucleotide variant neoantigens (r = 0.67), and CD8+ T-cell fraction (r = 0.51). A bivariate model using the median number of INDEL neoantigens and CD8 T-cell fraction had the highest accuracy in predicting RORs (adjusted r2 = 0.52, P = .002). Immunoprofile assessment of 156 patients with NSCLC revealed a strong trend for higher baseline median CD8+ T cells within patients' tumors who experienced any grade irAEs. Using machine learning, an expanded ICI-treated NSCLC cohort (n = 378) further showed a treatment duration-independent association of an increased proportion of high TIL (>median) in patients with irAEs (59.7% v 44%, P = .005). This was confirmed by using the Fine-Gray competing risk approach, demonstrating higher baseline TIL density (>median) associated with a higher cumulative incidence of irAEs (P = .028). CONCLUSION:Our findings highlight a potential role for TIME features, specifically INDEL neoantigens and baseline-immune infiltration, in enabling optimal irAE risk stratification of patients.