Epigenetic Aging Signatures in People with Hemophilia

The factor VIII treatment history of non‐severe hemophilia A—Response from original authors Abdi et al

Background and Aims Chronic kidney disease (CKD) shares important features of a dysregulated ageing process with other common “burden of lifestyle” diseases, which aggregates into the diseasome of ageing. Typically, this is hallmarked by an acceleration of epigenetic (DNA methylation-based) clocks. It remains to be determined if current therapeutic interventions, such as renal transplantation or dialysis, can slow this clock, and thus the rate of biological ageing, in CKD. We therefore assessed the rate of biological ageing in CKD patients and whether these therapies impact on it, by measuring epigenetic age before and 1 year after treatment. Methods Whole blood samples were taken from CKD 5 patients at baseline and 1 year after renal transplantation (n=12) or dialysis (n=11; peritoneal dialysis n=7, haemodialysis n=4) as well as from age and sex-matched population-based controls (n=24). DNA methylation was measured using the Illumina Infinium Human Methylation 450K BeadChip and epigenetic age was calculated using three independent DNA methylation clocks: the Horvath, Hannum, and PhenoAge clocks. Additionally, a novel composite clock incorporating these three clocks was evaluated. We then calculated the age acceleration (difference between epigenetic and chronological age) for each clock and compared average age acceleration between groups and across time points. Results Incident dialysis patients displayed accelerated ageing versus chronologically age-matched controls (p<0.001). We observed a PhenoAge age acceleration difference in both the transplant (8.5 years, p=0.001) and dialysis (9.7 years, p<0.001) groups at baseline compared to control. After 1 year, we also observed a decrease of the age acceleration in the transplant group (mean reduced by 4.4 years, p=0.016), but not in the dialysis group (mean reduced by 0.7 years, p=0.668). Conclusion CKD 5 patients display an increased biological (i.e. epigenetic) age. This age acceleration is mitigated one year after renal transplantation, but not in patients undergoing dialysis. Neither therapy reverses high biological age.

Gestational Epigenetics and Risk of Childhood Leukemia

Age and Inflammation: Insights on "Age Three Ways" from Midlife in the United States Study.

For the prevention of diabetic retinopathy, it is important to study risk factors, among which, along with the duration of type 2 diabetes mellitus, the level of glycemia, obesity, chronological age is indicated, but biological age is not considered as a potential risk factor, although biological age more objectively than chronological characterizes pathological changes at the cellular level and processes apoptosis. Purpose: to study biological age as a new risk factor for diabetic retinopathy in patients with type 2 diabetes mellitus. 580 patients aged 45–59 years with diabetic retinopathy and type 2 diabetes mellitus, whose biological age was calculated according to the Voitenko V.P. et al. methodology, took part in the study on the basis of the S.N. Fedorov National medical research center “MNTK Eye Microsurgery”. The correspondence of biological and chronological age was established in 124 patients, the excess (acceleration) of the chronological biological age in 357 patients and the excess of the biological chronological age in 99 patients. In the subsequent analysis, the first two groups were considered. Among 45–59­year­old patients with type 2 diabetes mellitus, the incidence of diabetic retinopathy was 19.82 ± 1,32 cases per 100 examined, which is statistically significantly higher (p < 0.001) compared to patients of the same age with type 2 diabetes mellitus with a chronological biological age — 10.24 ± 1.51 cases per 100 examined. Significant differences in the compared groups were also revealed in the values of the chronological age of diagnosis of diabetic retinopathy in this endocrine disease — 47.69 ± 1.24 years in patients with accelerated biological age and 50.23 ± 0.92 years in patients with matching biological and chronological age (p < 0.01). The biological age of diagnosis of diabetic retinopathy, respectively, was 56.13 ± 0.83 years and 49.61 ± 1.11 years (p < 0.001). The difference in the development of diabetic retinopathy in patients 45–59 years old with type 2 diabetes mellitus by biological age was 6,52 ± 1,24 years among patients with accelerated biological age and 0.62 ± 0.09 years among patients with matching biological and chronological age (p < 0.001). Consequently, the acceleration of biological age is a significant and new risk factor for diabetic retinopathy in patients aged 45–59 years with type 2 diabetes mellitus.

The health profile of African Americans clearly shows that stress works to worsen chronic conditions. To improve the health of aging African Americans, interventions need to address how effects of stress are reduced by individual resilience factors and exacerbated by anxiety or other traits. We will characterize the effects of stress by measuring rate of biological aging (RBA) over thirty years in a Black cohort (aged 18-30 at baseline) of approximately 2,000 individuals from the longitudinal CARDIA study. Biological aging (BA) captures premature physiological aging beyond that predicted by an individual’s chronological age. RBA will be characterized by within person change in BA over 30 years. We will measure the association between RBA and anxiety and will further measure the extent to which various forms of individual resilience factors mitigate the effects of anxiety on BA. We will also explore how intersectionality is evinced in sex differences in RBA.

The definition, diagnosis and management of mild hemophilia A: communication from the SSC of the ISTH

In this research, we delve into the association between epigenetic aging and idiopathic pulmonary fibrosis (IPF), a debilitating lung disease that progresses over time. Utilizing the Illumina MethylationEPIC array, we assessed DNA methylation levels in donated human lung tissue from patients with IPF, categorizing the disease into mild, moderate, and severe stages based on clinical assessments. We used seven epigenetic clocks to determine age acceleration, which is the discrepancy between biological (epigenetic) and chronological age. Our findings revealed a notable acceleration of biological aging in IPF tissues compared with healthy controls, with four clocks-Horvath's, Hannum's, PhenoAge, and DunedinPACE-showing significant correlations. DunedinPACE, in particular, indicated a more rapid aging process in the more severe regions within the lungs of IPF cases. These results suggest that the biological aging process in IPF is expedited and closely tied to the severity of the disease. The study underscores the potential of DNA methylation as a biomarker for IPF, providing valuable insights into the underlying methylation patterns and the dynamics of epigenetic aging in affected lung tissue. This research supports the broader application of epigenetic clocks in clinical prognosis and highlights the critical role of biological age in the context of medical research and healthcare.NEW & NOTEWORTHY Using epigenetic clocks, we found a notable acceleration of biological aging in IPF tissues, particularly in DunedinPACE, suggesting that the biological aging process in IPF is accelerated and closely related to the severity of the disease. The study also underscores DNA methylation's potential as a biomarker for IPF, as well as the dynamics of epigenetic aging and the need to consider biological age in medical research and healthcare.

ImportanceThe practice of oncology will increasingly involve the care of a growing population of individuals with midlife and late-life cancers. Managing cancer in these individuals is complex, based on differences in biological age at diagnosis. Biological age is a measure of accumulated life course damage to biological systems, loss of reserve, and vulnerability to functional deterioration and death. Biological age is important because it affects the ability to manage the rigors of cancer therapy, survivors’ function, and cancer progression. However, biological age is not always clinically apparent. This review presents a conceptual framework of life course biological aging, summarizes candidate measures, and describes a research agenda to facilitate clinical translation to oncology practice.ObservationsMidlife and late-life cancers are chronic diseases that may arise from cumulative patterns of biological aging occurring over the life course. Before diagnosis, each new patient was on a distinct course of biological aging related to past exposures, life experiences, genetics, and noncancer chronic disease. Cancer and its treatments may also be associated with biological aging. Several measures of biological age, including p16INK4a, epigenetic age, telomere length, and inflammatory and body composition markers, have been used in oncology research. One or more of these measures may be useful in cancer care, either alone or in combination with clinical history and geriatric assessments. However, further research will be needed before biological age assessment can be recommended in routine practice, including determination of situations in which knowledge about biological age would change treatment, ascertaining whether treatment effects on biological aging are short-lived or persistent, and testing interventions to modify biological age, decrease treatment toxic effects, and maintain functional abilities.Conclusions and RelevanceUnderstanding differences in biological aging could ultimately allow clinicians to better personalize treatment and supportive care, develop tailored survivorship care plans, and prescribe preventive or ameliorative therapies and behaviors informed by aging mechanisms.

Although dermatologic conditions primarily manifest on the skin, an increasing amount of evidence demonstrates that these inflammatory conditions can have a deeper impact on our systemic health. The use of epigenetics to measure biological age, instead of chronological age, can give us insight into the systemic burden of these diseases on aging. We aimed to understand the degree to which each dermatological condition affects biological aging. A systematic review was performed of PubMed, Embase, and Web of Science to identify all publications that measured biological age in dermatological patients using epigenetic clocks. Six articles involved the following conditions: atopic dermatitis (AD) (1), hidradenitis suppurativa (HS) (1), and psoriasis (PsO) (4). Notably, patients with psoriatic arthritis, but not psoriasis alone, demonstrated significantly increased epigenetic aging compared to controls. Pediatric AD patients had an increase in the rate of biological aging as measured by the Horvath, Skin and Blood, PhenoAge, and GrimAge clocks. HS patients were found to have an increased biological age when assessing tissue from affected skin. Further research is needed to investigate correlations between disease severity and epigenetic aging, and for expansion into other dermatological diseases. Additionally, epigenetic clocks need to be developed that utilize different subsets of inflammation more broadly and skin biomarkers to provide a more accurate estimation for chronic inflammatory dermatological conditions.

Study question Can a simplified and validated peripheral epigenetic clock, that test the methylation pattern of CpG sites at five genes, predict in vitro fertilization (IVF) success? Summary answer Epigenetic clocks may serve as reliable predictors of IVF success, particularly in women aged 31–35, and they could enhance the accuracy of multiparametric prediction models. What is known already In IVF, finding reliable success predictors is challenging. In recent years, the concept of fertility as a ‘sixth vital sign’ or as a ‘proxy for overall health’ has gained traction, suggesting that fertility may reflect a broader set of factors, including genetic predisposition, environmental exposures, and lifestyle influences. Within this context, epigenetic mechanisms are emerging as promising biomarkers of biological age, offering more accuracy than chronological age alone. Epigenetic clocks, which measure biological age through DNA methylation, could show potential as IVF success predictors, though their role in reproductive outcomes requires further research. Study design, size, duration The project was a single-center, observational prospective study involving 379 women who underwent IVF between 03-2022 and 06-2023. The primary outcome was to assess the predictive accuracy of the epigenetic clock on live birth (LB) rate through multivariate and subgroup analyses. We investigated whether women with a LB after IVF had a younger epigenetic age or exhibited epigenetic deceleration compared to those without, and whether this difference provided additional predictive value beyond ovarian reserve markers. Participants/materials, setting, methods Women of reproductive age who underwent IVF treatment were recruited without age restrictions. Exclusion criteria included severe male factor infertility and any systemic diseases that could affect pregnancy outcomes. A whole blood sample in EDTA was collected prior to ovarian stimulation protocols. The “Zbiec-Piekarska2” epigenetic clock model was applied, analyzing the methylation status of five key genes associated with biological aging (C1orf132, ELOVL2, KLF14, FHL2, TRIM59) from DNA extracted from peripheral leukocytes. Main results and the role of chance Among 379 women, those with a LB (n = 204) were younger, had better ovarian reserve markers, and retrieved more oocytes, compared to those without a LB (n = 175). Women with LB were epigenetically younger (36 ± 5 vs. 39 ± 5 years, p < 0.001), and epigenetic age showed moderate predictive power (AUC 0.663, 95%CI: 0.599-0.726). After adjusting for ovarian reserve parameters (follicular stimulating hormon-FSH, antral follicular count-AFC) both epigenetic age and epigenetic age acceleration differed significantly: the adjusted odds-ratio (adjOR) for LB per year of age was 0.90 (95%CI: 0.86-0.95, p < 0.001) and 0.92 (95%CI: 0.87-0.98, p = 0.01) respectively, suggesting that IVF success was more likely in epigenetically younger women, beyond their ovarian reserve. This difference was lost in subgroup analysis based on infertility cause. When comparing epigenetic age performance with other parameters across chronological age groups, epigenetic age and epigenetic age acceleration were the most accurate predictors in women aged 31–35, with AUCs of 0.689 (95% CI: 0.564-0.814) and 0.695 (95% CI: 0.575-0.816), respectively. Multiparametric models combining epigenetic age with ovarian reserve markers slightly improved predictive accuracy: AUC was of 0.692 (95% CI: 0.637-0.747) with AFC, and of 0.693 (95% CI: 0.635-0.750) with AMH. Limitations, reasons for caution The subgroup analyses based on infertility diagnosis may have been underpowered due to small sample sizes. Larger studies are needed, particularly for idiopathic infertility, where epigenetic disruption may play a role. Additionally, the use of different epigenetic clocks, especially fertility-specific models, could enhance performance in the reproductive field. Wider implications of the findings Our findings highlight the potential of epigenetic clocks as IVF success predictors, particularly in specific age-groups and within multiparametric models. They contribute to the growing evidence of the key role of epigenetic mechanisms in reproductive aging. Further research could integrate epigenetic clocks into fertility assessments, enabling personalized approaches and tailored counseling. Trial registration number No

Peter W. Collins, Elizabeth Chalmers, Daniel P. Hart, Ri Liesner, Savita Rangarajan, Kate Talks, Mike Williams and Charles R. Hay School of Medicine, Cardiff University, University Hospital of Wales, Wales, Royal Hospital for Sick Children, Glasgow, The London School of Medicine and Dentistry, Royal London Hospital, Barts, Queen Mary University, London, Great Ormond Street NHS Trust, London, Hampshire Hospital NHS Foundation Trust, Basingstoke & North Hampshire Hospital, Basingstoke, Royal Victoria Infirmary, Newcastle upon Tyne, Birmingham Childrens’ Hospital NHS Foundation Trust, Birmingham and Central Manchester University Hospitals, Manchester, UK

Background: Older adults with early breast cancer can have very different risks of chemotoxicity despite similar chronological age. This heterogeneity may be due to differences in biological age. However, few studies have evaluated whether epigenetic indicators of biological age can stratify the risk of chemotoxicity in older adults with early breast cancer. Methods: In a prospective multicenter study of 394 adults age >65 with stage I-III breast cancer treated with neo/adjuvant chemo, we analyzed DNA methylation patterns from peripheral blood to estimate epigenetic age acceleration (EAA) prior to chemo. We tested three generations of epigenetic age algorithms (1st gen: Horvath and Hannum; 2nd gen: PhenoAge and GrimAge; 3rd gen: DunedinPACE). We calculated EAA as the residual that results from regressing epigenetic age on chronological age. The primary endpoint was grade 2+ chemotoxicity (yes/no, yes defined as any grade 2+ toxicity attributed to chemo). Using multivariable logistic regression, we examined the association between EAA (analyzed as continuous and categorical [quartiles] variables) and grade 2+ chemotoxicity, adjusting for demographic, geriatric, and clinical covariates. Results: The median (range) pre-treatment chronological age was 70 (65-85), 65% had stage II/III disease, 38% had anthracycline, and 75% received G-CSF prophylaxis. A total of 334 (84.8%) participants experienced a grade 2+ toxicity. After adjusting for age, cell composition, stage, race/ethnicity, education, regimen, organ function, and geriatric assessment variables, there was no significant association between the measures of EAA and grade 2+ chemotoxicity (Table). Conclusions: In this cohort of older adults with early breast cancer, there was no significant association between pre-treatment EAA and grade 2+ chemotoxicity. Further research is needed to examine how measures of biological age can be translated to the clinical care of older patients with breast cancer. Citation Format: Jingran Ji, Canlan Sun, Marla Lipsyc-Sharf, Nikita V. Baclig, Yulia A. Zektser, Ali Al Saleem, Joseph D. Olivera, Kelly S. Synold, Lauren R. Zelman, Alexandra M. Binder, Mina S. Sedrak. Epigenetic age acceleration measures and chemotoxicity in older adults with early breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 623.

Older chronological age is associated with decreased multiple sclerosis (MS) relapse rates and increased risk of progressive disease. Measurement of biological age may be more precise than birthdate in understanding these aging effects. In addition to normal aging, MS-related accelerated aging may contribute. Measurement of biological age in adults may be confounded by the effects of natural aging and age-related comorbidities. Examining age extremes can be informative, and demonstrating accelerated biological aging in children would support a hypothesis of MS driving premature aging. We sought to compare epigenetic age in participants with pediatric-onset MS (POMS) and age-similar controls. We performed a multicenter case-control analysis of epigenetic age in a prospectively collected set of whole blood DNA samples and clinical data. Quantitative methylation scores were derived for approximately 850,000 cytosine-phosphate-guanine (CpG) sites. Epigenetic age was calculated based on 4 established epigenetic clock algorithms. Epigenetic age and age acceleration residual (AAR) were compared between participants with POMS and age-similar controls using multivariate regression analysis, adjusted for demographic variables. Epigenetic age and AAR were greater in cases (n = 125, mean age 15.7 years [SD = 2.6], 63.2% female) compared with controls (n = 145, mean age 15.3 years [SD = 3.4], 63.5% female) after adjusting for age, sex, body mass index, tobacco exposure, and socioeconomic status. This difference was statistically significant for 2 of the 4 epigenetic clocks used (Horvath β = 0.31 years [CI = -0.32-0.94], p = 0.33; Hannum β = 1.50 years [CI = 0.58-2.42], p = 0.002; GrimAge β = 0.33 years [CI = -0.30-0.96], p = 0.29; PhenoAge β = 1.72 years [CI = 0.09-3.35], p = 0.004). We observed greater point estimates of epigenetic age in participants with POMS compared with healthy controls in all epigenetic clocks tested. This difference was statistically significant for the Hannum and PhenoAge clocks after multivariable modeling. These results are consistent with those of studies in adult MS and suggest that accelerated aging may be present even in the youngest people living with MS.

Evidence of accelerated aging among African Americans and its implications for mortality