Epigenetic Clock Research Articles

An interpretable machine learning-based cerebrospinal fluid proteomics clock for predicting age reveals novel insights into brain aging.

Machine learning can be used to create "biologic clocks" that predict age. However, organs, tissues, and biofluids may age at different rates from the organism as a whole. We sought to understand how cerebrospinal fluid (CSF) changes with age to inform the development of brain aging-related disease mechanisms and identify potential anti-aging therapeutic targets. Several epigenetic clocks exist based on plasma and neuronal tissues; however, plasma may not reflect brain aging specifically and tissue-based clocks require samples that are difficult to obtain from living participants. To address these problems, we developed a machine learning clock that uses CSF proteomics to predict the chronological age of individuals with a 0.79 Pearson correlation and mean estimated error (MAE) of 4.30 years in our validation cohort. Additionally, we analyzed proteins highly weighted by the algorithm to gain insights into changes in CSF and uncover novel insights into brain aging. We also demonstrate a novel method to create a minimal protein clock that uses just 109 protein features from the original clock to achieve a similar accuracy (0.75 correlation, MAE 5.41). Finally, we demonstrate that our clock identifies novel proteins that are highly predictive of age in interactions with other proteins, but do not directly correlate with chronological age themselves. In conclusion, we propose that our CSF protein aging clock can identify novel proteins that influence the rate of aging of the central nervous system (CNS), in a manner that would not be identifiable by examining their individual relationships with age.

Epigenetic age acceleration in follicular fluid and markers of ovarian response among women undergoing IVF.

Are markers of epigenetic age acceleration in follicular fluid associated with outcomes of ovarian stimulation? Increased epigenetic age acceleration of follicular fluid using the Horvath clock, but not other epigenetic clocks (GrimAge and Granulosa Cell), was associated with lower peak estradiol levels and decreased number of total and mature oocytes. In granulosa cells, there are inconsistent findings between epigenetic age acceleration and ovarian response outcomes. Our study included 61 women undergoing IVF at an academic fertility clinic in the New England area who were part of the Environment and Reproductive Health Study (2006-2016). Participants provided a follicular fluid sample during oocyte retrieval. DNA methylation of follicular fluid was assessed using a genome-wide methylation screening tool. Three established epigenetic clocks (Horvath, GrimAge, and Granulosa Cell) were used to predict DNA-methylation-based epigenetic age. To calculate the age acceleration, we regressed epigenetic age on chronological age and extracted the residuals. The association between epigenetic age acceleration and ovarian response outcomes (peak estradiol levels, follicle stimulation hormone, number of total, and mature oocytes) was assessed using linear and Poisson regression adjusted for chronological age, three surrogate variables (to account for cellular heterogeneity), race, smoking status, initial infertility diagnosis, and stimulation protocol. Compared to the median chronological age of our participants (34 years), the Horvath clock predicted, on an average, a younger epigenetic age (median: 24.2 years) while the GrimAge (median: 38.6 years) and Granulosa Cell (median: 39.0 years) clocks predicted, on an average, an older epigenetic age. Age acceleration based on the Horvath clock was associated with lower peak estradiol levels (-819.4 unit decrease in peak estradiol levels per standard deviation increase; 95% CI: -1265.7, -373.1) and fewer total (% change in total oocytes retrieved per standard deviation increase: -21.8%; 95% CI: -37.1%, -2.8%) and mature oocytes retrieved (% change in mature oocytes retrieved per standard deviation increase: -23.8%; 95% CI: -39.9%, -3.4%). The age acceleration based on the two other epigenetic clocks was not associated with markers of ovarian response. Our sample size was small and we did not specifically isolate granulosa cells from follicular fluid samples so our samples could have included mixed cell types. Our results highlight that certain epigenetic clocks may be predictive of ovarian stimulation outcomes when applied to follicular fluid; however, the inconsistent findings for specific clocks across studies indicate a need for further research to better understand the clinical utility of epigenetic clocks to improve IVF treatment. The study was supported by grants ES009718, ES022955, ES000002, and ES026648 from the National Institute of Environmental Health Sciences (NIEHS) and a pilot grant from the NIEHS-funded HERCULES Center at Emory University (P30 ES019776). RBH was supported by the Emory University NIH Training Grant (T32-ES012870). N/A.

The influence of epigenetic biological age on key complications and outcomes in aneurysmal subarachnoid haemorrhage

BackgroundWe aimed to investigate the association between DNA-methylation biological age (B-age) calculated as age acceleration (ageAcc) and key aneurysmal subarachnoid haemorrhage (aSAH) complications such as vasospasm, delayed cerebral ischaemia (DCI),...

Conserved epigenetic hallmarks of T cell aging during immunity and malignancy

Chronological aging correlates with epigenetic modifications at specific loci, calibrated to species lifespan. Such ‘epigenetic clocks’ appear conserved among mammals, but whether they are cell autonomous and restricted by maximal organismal lifespan remains unknown. We used a multilifetime murine model of repeat vaccination and memory T cell transplantation to test whether epigenetic aging tracks with cellular replication and if such clocks continue ‘counting’ beyond species lifespan. Here we found that memory T cell epigenetic clocks tick independently of host age and continue through four lifetimes. Instead of recording chronological time, T cells recorded proliferative experience through modification of cell cycle regulatory genes. Applying this epigenetic profile across a range of human T cell contexts, we found that naive T cells appeared ‘young’ regardless of organism age, while in pediatric patients, T cell acute lymphoblastic leukemia appeared to have epigenetically aged for up to 200 years. Thus, T cell epigenetic clocks measure replicative history and can continue to accumulate well-beyond organismal lifespan.

High-Impact Pain Is Associated With Epigenetic Aging Among Middle-Aged and Older Adults: Findings From the Health and Retirement Study.

Chronic pain has been associated with accelerated biological aging, which may be related to epigenetic alterations. We evaluated the association of high-impact pain (ie, pain that limits activities and function) with epigenetic aging, a measure of biological aging, in a nationally representative sample of middle-aged and older adults in the United States. Cross-sectional analysis of adults 50 years of age and older from the 2016 Health and Retirement Study. Epigenetic aging was derived from 13 epigenetic clocks based on DNA methylation patterns that predict aging correlates of morbidity and mortality. Ordinary least squares regressions were performed to test for differences in the epigenetic clocks, adjusting for the complex survey design, as well as biological, social, and behavioral factors. The analysis consisted of 3855 adults with mean age of 68.5 years, including 59.8% with no pain and 25.8% with high-impact pain. Consistent with its operational definition, high-impact pain was associated with greater functional and activity limitations. High-impact pain was associated with accelerated epigenetic aging compared to no pain, as measured via second (Zhang, PhenoAge, GrimAge) and third (DunedinPoAm) generation epigenetic clocks. Additionally, GrimAge was accelerated in high-impact pain as compared to low-impact pain. High-impact pain is associated with accelerated epigenetic aging among middle-aged and older adults in the United States. These findings highlight aging-associated epigenetic alterations in high-impact chronic pain and suggest a potential for epigenetic therapeutic approaches for pain management and the preservation of physical function in older adults.

A case-control study: epigenetic age acceleration in psoriasis.

Psoriasis (PsO) is a chronic inflammatory skin condition, often accompanied by psoriatic arthritis (PsA) and linked to various comorbidities and increased mortality rates. This study aimed to explore the relationship between PsO and accelerated biological aging, specifically focusing on epigenetic DNA methylation clocks. Using a matched case-control design, 20 PsO cases were selected along with age, race, and sex-matched 20 controls without PsO from the Skin Disease Biorepository at Brown Dermatology, Inc, Providence, Rhode Island. Blood samples retrieved from both groups were analyzed for DNA methylation, and epigenetic ages were calculated using DNA methylation clocks, including Horvath, Hannum, Pheno, SkinBlood, and Grim ages. Generalized estimation equations were employed to test the differences in epigenetic and chronological ages between PsO cases and controls, as well as within various subgroups in comparison to their respective controls. There were no statistically significant differences in epigenetic ages between PsO cases and controls. However, notably, PsO cases with PsA demonstrated an accelerated PhenoAge, compared to their matched controls. This study represents a pioneering investigation into the potential link between PsO and epigenetic aging, shedding light on the possibility of accelerated epigenetic aging in PsA, possibly associated with heightened inflammatory burden. These findings emphasize the systemic impact of PsA on the aging process, prompting the need for deeper exploration into autoimmune pathways, inflammation, and epigenetic modifications underlying PsO pathogenesis and aging mechanisms. Larger-scale studies with diverse populations are imperative to discern PsO subgroups experiencing accelerated biological aging and decipher the intricate interplay between PsO, inflammation, and aging pathways.

Genetic association of the gut microbiota with epigenetic clocks mediated by inflammatory cytokines: a Mendelian randomization analysis.

A new aging biomarker epigenetic clock has been developed. There exists a close link between aging and gut microbiota, which may be mediated by inflammatory cytokines. However, the relationship between the epigenetic clock, gut microbiota, and the mediating substances is unclear. Two large genome-wide association meta-analyses were analyzed by two-sample Mendelian randomization. The results between gut microbiota and epigenetic clock were investigated using the four methods (Inverse variance weighted, MR-Egger, weighted median, MR-PRESSO). Genetic correlation was measured by Linked disequilibrium score regression (LDSC). The correctness of the study direction was checked by the Steiger test. Cochran's Q statistic and MR-Egger intercept were used as sensitivity analyses of the study. The two-step method was used to examine the mediating role of inflammatory cytokines. We use the Benjamini-Hochberg correction method to correct the P value. After FDR correction, multiple bacterial genera were significantly or suggestively associated with four epigenetic clocks (GrimAge, HannumAge, IEAA, PhenoAge). And we detected several inflammatory factors acting as mediators of gut microbiota and epigenetic clocks. This study provides genetic evidence for a positive and negative link between gut microbiota and aging risk. We hope that by elucidating the genetic relationship and potential mechanisms between aging and gut microbiota, we will provide new avenues for continuing aging-related research and treatment.

Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate.

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

Accelerated biological aging six decades after prenatal famine exposure

To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N = 951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944 to 1945, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.

Human Brain Aging is Associated with Dysregulation of Cell-Type Epigenetic Identity.

Significant links between aging and DNA methylation are emerging from recent studies. On the one hand, DNA methylation undergoes changes with age, a process termed as epigenetic drift. On the other hand, DNA methylation serves as a readily accessible and accurate biomarker for aging. A key missing piece of information, however, is the molecular mechanisms underlying these processes, and how they are related, if any. Addressing the limitations of previous research due to the limited number of investigated CpGs and the heterogeneous nature of tissue samples, here we have examined DNA methylation of over 20 million CpGs across a broad age span in neurons and non-neuronal cells, primarily oligodendrocytes. We show that aging is a primary predictor of DNA methylation variation, surpassing the influence of factors such as sex and schizophrenia diagnosis, among others. On the genome-wide scale, epigenetic drift manifests as significant yet subtle trends that are influenced by the methylation level of individual CpGs. We reveal that CpGs that are highly differentiated between cell types are especially prone to age-associated DNA methylation alterations, leading to the divergence of epigenetic cell type identities as individuals age. On the other hand, CpGs that are included in commonly used epigenetic clocks tend to be those sites that are not highly cell type differentiated. Therefore, dysregulation of epigenetic cell-type identities and current DNA epigenetic clocks represent distinct features of age-associated DNA methylation alterations.

A miRNA-based epigenetic molecular clock for biological skin-age prediction

Skin aging is one of the visible characteristics of the aging process in humans. In recent years, different biological clocks have been generated based on protein or epigenetic markers, but few have focused on biological age in the skin. Arrest the aging process or even being able to restore an organism from an older to a younger stage is one of the main challenges in the last 20 years in biomedical research. We have implemented several machine learning models, including regression and classification algorithms, in order to create an epigenetic molecular clock based on miRNA expression profiles of healthy subjects to predict biological age-related to skin. Our best models are capable of classifying skin samples according to age groups (18–28; 29–39; 40–50; 51–60 or 61–83 years old) with an accuracy of 80% or predict age with a mean absolute error of 10.89 years using the expression levels of 1856 unique miRNAs. Our results suggest that this kind of epigenetic clocks arises as a promising tool with several applications in the pharmaco-cosmetic industry.

Microbiome signature, immune landscape and global methylation in early onset colorectal cancer.

3580 Background: The incidence of colorectal cancer (CRC) in young adults (age at diagnosis < 50 years old) has been rapidly increasing. Approximately 20% of early-onset (EO) CRC cases are due to germline gene mutations. However, the etiology of sporadic EO CRC remains poorly understood. Research suggests that environmental factors such as Western diet may be associated with increased incidence of sporadic EO CRC. The gut microbiota decomposes and ferments dietary fibers to produce microbial metabolites, which play important roles in maintaining the intestinal epithelium integrity. A high-fat, low-fiber diet has been associated with intestinal dysbiosis, which disrupts intestinal bacterial homeostasis. An increased inflammation state characterizes dysbiosis and may promote an immunosuppressive tumor microenvironment (TME) and suppress antitumor immune surveillance. In addition, epigenetic modifications are influenced by environmental changes and therefore epigenetics may bridge the knowledge gap in understanding the development of sporadic EOCRC. Methods: We obtained RNA sequencing data from the Cancer Genome Atlas (TCGA) and the Oncology Research Information Exchange Network (ORIEN) from the Ohio State University biospecimen services to characterize intra-tumor microbiota composition, tumor-infiltrating lymphocytes (TILs) and differential pathways in EO CRC. We used Infinium HM450 methylation array in The Cancer Genome Atlas (TCGA) and performed genome-wide analyses using reduced representation bisulfite sequencing (RRBS) method to identify differentially methylated regions (DMRs) in EO CRC. Results: Gene expression analysis is consistent with Fusobacterium promoting inflammation in EO CRC. Intra-tumor microbes are positively correlated with M2 macrophages. Compared to late onset (LO) CRC, EO CRC patients have unique gene signatures of phagosome formation, S100 family signaling pathway and CREB signaling in neurons by using ingenuity pathway analysis (IPA). In addition, we found that methylation ages predicted by epigenetic clocks in EO CRC patients were 15 years older on average than their chronological ages, whereas methylation ages in late onset (LO) CRC patients were comparable with chronological ages. The enriched pathways based on DMRs associated with EO CRC have significant overlap with canonical pathways based on differentially expressed genes (DEGs), including CREB signaling in neurons and S100 family signaling pathways. Conclusions: These data suggest that pathogenic microbes may induce inflammation, which leads to accelerated aging in EO CRC.

Adaptive predictor-set linear model: An imputation-free method for linear regression prediction on data sets with missing values.

Linear regression (LR) is vastly used in data analysis for continuous outcomes in biomedicine and epidemiology. Despite its popularity, LR is incompatible with missing data, which frequently occur in health sciences. For parameter estimation, this shortcoming is usually resolved by complete-case analysis or imputation. Both work-arounds, however, are inadequate for prediction, since they either fail to predict on incomplete records or ignore missingness-induced reduction in prediction accuracy and rely on (unrealistic) assumptions about the missing mechanism. Here, we derive adaptive predictor-set linear model (aps-lm), capable of making predictions for incomplete data without the need for imputation. It is derived by using a predictor-selection operation, the Moore-Penrose pseudoinverse, and the reduced QR decomposition. aps-lm is an LR generalization that inherently handles missing values. It is applied on a reference data set, where complete predictors and outcome are available, and yields a set of privacy-preserving parameters. In a second stage, these are shared for making predictions of the outcome on external data sets with missing entries for predictors without imputation. Moreover, aps-lm computes prediction errors that account for the pattern of missing values even under extreme missingness. We benchmark aps-lm in a simulation study. aps-lm showed greater prediction accuracy and reduced bias compared to popular imputation strategies under a wide range of scenarios including variation of sample size, goodness of fit, missing value type, and covariance structure. Finally, as a proof-of-principle, we apply aps-lm in the context of epigenetic aging clocks, linear models that predict a person's biological age from epigenetic data with promising clinicalapplications.

Accelerated epigenetic aging and risk of chemotoxicity in older adults with early breast cancer.

1624 Background: Older adults with breast cancer have considerable heterogeneity in their risk of chemotoxicity; two people with the same chronological age have different risks of chemotoxicity. This heterogeneity in chemotoxicity may be due to older adults having variable rates of biological aging. Some older adults age faster biologically compared with their chronological age (i.e., accelerated epigenetic aging [AEA]), while others do not. AEA is a blood biomarker of aging, but its utility as a biomarker of chemotoxicity is unknown. Here, we evaluated the association between AEA and risk of chemotoxicity in older adults with early breast cancer. Methods: In a prospective multicenter study of 397 women age >65 with stage I-III breast cancer treated with neo/adjuvant chemo, we extracted genomic DNA from blood to estimate the participant’s rate of biological aging at baseline (prior to chemotherapy). Using two established epigenetic clocks (AgeAccelGrim and DunedinPACE), we classified individuals as either having AEA or not (dichotomized as a yes/no variable) for each clock. Our primary endpoint was grade 3+ chemotoxicity (yes/no, yes defined as any grade 3+ toxicity attributed to chemo). Using multivariable logistic regression, we examined the association between AEA and grade 3+ chemotoxicity, adjusting for sociodemographic, geriatric, and clinical covariates. Results: The median (range) pretreatment chronological age was 70 (65-85), AgeAccelGrim was -0.88 (-10.4-15.7), and DunedinPACE was 1.03 (0.69-1.45). Of the 397 women, 31 (8%) had AEA per AgeAccelGrim, 63 (16%) had AEA per DunedinPACE, and 184 (46%) experienced grade 3+ chemotoxicity. Women who had evidence of AEA as measured by AgeAccelGrim (≥6.83 years, adjusted OR = 2.73, 95% CI 1.17-6.41, p = 0.02) or DunedinPACE (≥1.17 biological years per chronological year, adjusted OR = 2.20, 95% CI 1.18-4.10, p = 0.01) had greater odds of having grade 3+ chemotoxicity compared to women without AEA (AgeAccelGrim <6.83 or DunedinPACE <1.17, respectively). Conclusions: In this cohort of older women with early breast cancer, those with pre-chemo AEA had increased odds of chemotoxicity compared to women without any evidence of AEA. Future research is needed to examine whether measures of biological age can be translated to the clinical care of older patients with breast cancer. Clinical trial information: NCT01472094 . [Table: see text]

Epigenetic Clocks: Using DNA to Estimate the Age of Dolphins

Epigenetic Clocks: Using DNA to Estimate the Age of Dolphins

The Latent Aging of Cells.

As epigenetic clocks have evolved from powerful estimators of chronological aging to predictors of mortality and disease risk, it begs the question of what role DNA methylation plays in the aging process. We hypothesize that while it has the potential to serve as an informative biomarker, DNA methylation could also be a key to understanding the biology entangled between aging, (de)differentiation, and epigenetic reprogramming. Here we use an unsupervised approach to analyze time associated DNA methylation from both in vivo and in vitro samples to measure an underlying signal that ties these phenomena together. We identify a methylation pattern shared across all three, as well as a signal that tracks aging in tissues but appears refractory to reprogramming, suggesting that aging and reprogramming may not be fully mirrored processes.

Epigenetics in Alzheimer's Disease: A Critical Overview.

Epigenetic modifications have been implicated in a number of complex diseases as well as being a hallmark of organismal aging. Several reports have indicated an involvement of these changes in Alzheimer's disease (AD) risk and progression, most likely contributing to the dysregulation of AD-related gene expression measured by DNA methylation studies. Given that DNA methylation is tissue-specific and that AD is a brain disorder, the limitation of these studies is the ability to identify clinically useful biomarkers in a proxy tissue, reflective of the tissue of interest, that would be less invasive, more cost-effective, and easily obtainable. The age-related DNA methylation changes have also been used to develop different generations of epigenetic clocks devoted to measuring the aging in different tissues that sometimes suggests an age acceleration in AD patients. This review critically discusses epigenetic changes and aging measures as potential biomarkers for AD detection, prognosis, and progression. Given that epigenetic alterations are chemically reversible, treatments aiming at reversing these modifications will be also discussed as promising therapeutic strategies for AD.

Healthy Japanese dietary pattern is associated with slower biological aging in older men: WASEDA’S health study

Aging is the greatest risk factor for numerous diseases and mortality, and establishing geroprotective interventions targeting aging is required. Previous studies have suggested that healthy dietary patterns, such as the Mediterranean diet, are associated with delayed biological aging; however, these associations depend on nationality and sex. Therefore, this study aimed to investigate the relationship between dietary patterns identified through principal component analysis and biological aging in older men of Japan, one of the countries with the longest life expectancies. Principal component analysis identified two dietary patterns: a healthy Japanese dietary pattern and a Western-style dietary pattern. Eight epigenetic clocks, some of the most accurate aging biomarkers, were identified using DNA methylation data from whole-blood samples. Correlation analyses revealed that healthy Japanese dietary patterns were significantly negatively or positively correlated with multiple epigenetic age accelerations (AgeAccel), including AgeAccelGrim, FitAgeAccel, and age-adjusted DNAm-based telomere length (DNAmTLAdjAge). Conversely, the Western-style dietary pattern was observed not to correlate significantly with any of the examined AgeAccels or age-adjusted values. After adjusting for covariates, the healthy Japanese dietary pattern remained significantly positively correlated with DNAmTLAdjAge. Regression analysis showed that healthy Japanese dietary pattern contributed less to epigenetic age acceleration than smoking status. These findings suggest that a Western-style dietary pattern may not be associated with biological aging, whereas a healthy Japanese dietary pattern is associated with delayed biological aging in older Japanese men. Our findings provide evidence that healthy dietary patterns may have mild beneficial effects on delayed biological aging in older Japanese men.

Decreased but persistent epigenetic age acceleration is associated with changes in T-cell subsets after initiation of highly active antiretroviral therapy in persons living with HIV.

Persons living with HIV (PLWH) experience the early onset of age-related illnesses, even in the setting of successful human immunodeficiency virus (HIV) suppression with highly active antiretroviral therapy (HAART). HIV infection is associated with accelerated epigenetic aging as measured using DNA methylation (DNAm)-based estimates of biological age and of telomere length (TL). DNAm levels (Infinium MethylationEPIC BeadChip) from peripheral blood mononuclear cells from 200 PLWH and 199 HIV-seronegative (SN) participants matched on chronologic age, hepatitis C virus, and time intervals were used to calculate epigenetic age acceleration, expressed as age-adjusted acceleration residuals from 4 epigenetic clocks [Horvath's pan-tissue age acceleration residual (AAR), extrinsic epigenetic age acceleration (EEAA), phenotypic epigenetic age acceleration (PEAA), and grim epigenetic age acceleration (GEAA)] plus age-adjusted DNAm-based TL (aaDNAmTL). Epigenetic age acceleration was compared for PLWH and SN participants at two visits: up to 1.5years prior and 2-3years after HAART (or equivalent visits). Flow cytometry was performed in PLWH and SN participants at both visits to evaluate T-cell subsets. Epigenetic age acceleration in PLWH decreased after the initiation of HAART but remained greater post-HAART than that in age-matched SN participants, with differences in medians of 6.6, 9.1, and 7.7 years for AAR, EEAA, and PEAA, respectively, and 0.39 units of aaDNAmTL shortening (all p < 0.001). Cumulative HIV viral load after HAART initiation was associated with some epigenetic acceleration (EEAA, PEAA, and aaDNAmTL), but even PLWH with undetectable HIV post-HAART showed persistent epigenetic age acceleration compared to SN participants (p < 0.001). AAR, EEAA, and aaDNAmTL showed significant associations with total, naïve, and senescent CD8 T-cell counts; the total CD4 T-cell counts were associated with AAR, EEAA, and PEAA (p = 0.04 to <0.001). In an epigenome-wide analysis using weighted gene co-methylation network analyses, 11 modules demonstrated significant DNAm differences pre- to post-HAART initiation. Of these, nine were previously identified as significantly different from pre- to post-HIV infection but in the opposite direction. In this large longitudinal study, we demonstrated that, although the magnitude of the difference decreases with HAART is associated with the cumulative viral load, PLWH are persistently epigenetically older than age-matched SN participants even after the successful initiation of HAART, and these changes are associated with changes in T-cell subsets.

Predicting exacerbation of renal function by DNA methylation clock and DNA damage of urinary shedding cells: a pilot study

Recent reports have shown the feasibility of measuring biological age from DNA methylation levels in blood cells from specific regions identified by machine learning, collectively known as the epigenetic clock or DNA methylation clock. While extensive research has explored the association of the DNA methylation clock with cardiovascular diseases, cancer, and Alzheimer's disease, its relationship with kidney diseases remains largely unexplored. In particular, it is unclear whether the DNA methylation clock could serve as a predictor of worsening kidney function. In this pilot study involving 20 subjects, we investigated the association between the DNA methylation clock and subsequent deterioration of renal function. Additionally, we noninvasively evaluated DNA damage in urinary shedding cells using a previously reported method to examine the correlation with the DNA methylation clock and worsening kidney function. Our findings revealed that patients with an accelerated DNA methylation clock exhibited increased DNA damage in urinary shedding cells, along with a higher rate of eGFR decline. Moreover, in cases of advanced CKD (G4-5), the DNA damage in urinary shedding cells was significantly increased, highlighting the interplay between elevated DNA damage and eGFR decline. This study suggests the potential role of the DNA methylation clock and urinary DNA damage as predictive markers for the progression of chronic kidney disease.