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Background Epigenetic age acceleration (EAA) and epigenetic gestational age acceleration (EGAA) are biomarkers of physiological development and may be affected by the perinatal environment. The aim of this study was to evaluate performance of epigenetic clocks and to identify biological and sociodemographic correlates of EGAA and EAA at birth and in childhood. In the Project Viva pre-birth cohort, DNA methylation was measured in nucleated cells in cord blood (leukocytes and nucleated red blood cells, N = 485) and leukocytes in early (N = 120, median age = 3.2 years) and mid-childhood (N = 460, median age = 7.7 years). We calculated epigenetic gestational age (EGA; Bohlin and Knight clocks) and epigenetic age (EA; Horvath and skin & blood clocks), and respective measures of EGAA and EAA. We evaluated the performance of clocks relative to chronological age using correlations and median absolute error. We tested for associations of maternal-child characteristics with EGAA and EAA using mutually adjusted linear models controlling for estimated cell type proportions. We also tested associations of Horvath EA at birth with childhood EAA. Results Bohlin EGA was strongly correlated with chronological gestational age (Bohlin EGA r  = 0.82, p  < 0.001). Horvath and skin & blood EA were weakly correlated with gestational age, but moderately correlated with chronological age in childhood ( r  = 0.45–0.65). Maternal smoking during pregnancy was associated with higher skin & blood EAA at birth [ B (95% CI) = 1.17 weeks (− 0.09, 2.42)] and in early childhood [0.34 years (0.03, 0.64)]. Female newborns and children had lower Bohlin EGAA [− 0.17 weeks (− 0.30, − 0.04)] and Horvath EAA at birth [ B (95% CI) = − 2.88 weeks (− 4.41, − 1.35)] and in childhood [early childhood: − 0.3 years (− 0.60, 0.01); mid-childhood: − 0.48 years (− 0.77, − 0.18)] than males. When comparing self-reported Asian, Black, Hispanic, and more than one race or other racial/ethnic groups to White, we identified significant differences in EGAA and EAA at birth and in mid-childhood, but associations varied across clocks. Horvath EA at birth was positively associated with childhood Horvath and skin & blood EAA. Conclusions Maternal smoking during pregnancy and child sex were associated with EGAA and EAA at multiple timepoints. Further research may provide insight into the relationship between perinatal factors, pediatric epigenetic aging, and health and development across the lifespan.

Background Chronological age is a prominent risk factor for many types of cancers including colorectal cancer (CRC). Yet, the risk of CRC varies substantially between individuals, even within the same age group, which may reflect heterogeneity in biological tissue aging between people. Epigenetic clocks based on DNA methylation are a useful measure of the biological aging process with the potential to serve as a biomarker of an individual’s susceptibility to age-related diseases such as CRC. Methods We conducted a genome-wide DNA methylation study on samples of normal colon mucosa ( N = 334). Subjects were assigned to three cancer risk groups (low, medium, and high) based on their personal adenoma or cancer history. Using previously established epigenetic clocks (Hannum, Horvath, PhenoAge, and EpiTOC), we estimated the biological age of each sample and assessed for epigenetic age acceleration in the samples by regressing the estimated biological age on the individual’s chronological age. We compared the epigenetic age acceleration between different risk groups using a multivariate linear regression model with the adjustment for gender and cell-type fractions for each epigenetic clock. An epigenome-wide association study (EWAS) was performed to identify differential methylation changes associated with CRC risk. Results Each epigenetic clock was significantly correlated with the chronological age of the subjects, and the Horvath clock exhibited the strongest correlation in all risk groups ( r > 0.8, p < 1 × 10 −30 ). The PhenoAge clock ( p = 0.0012) revealed epigenetic age deceleration in the high-risk group compared to the low-risk group. Conclusions Among the four DNA methylation-based measures of biological age, the Horvath clock is the most accurate for estimating the chronological age of individuals. Individuals with a high risk for CRC have epigenetic age deceleration in their normal colons measured by the PhenoAge clock, which may reflect a dysfunctional epigenetic aging process.

Background Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease worldwide, but its pathophysiological mechanisms remain elusive. It is a progressive disease, encompassing hepatic steatosis, steatohepatitis with (out) fibrosis, and ultimately cirrhosis and hepatocellular carcinoma. DNA methylation (DNAm) is dysregulated in MASLD and may play a central role in its pathogenesis. Additionally, aging is associated with MASLD and shares common processes of chronic inflammation and oxidative stress. Therefore, this study focuses on DNAm changes in relation to MASLD progression and epigenetic age acceleration (EAA). Results Liver biopsies from 22 individuals with varying MASLD status were analyzed using Infinium MethylationEPIC BeadChip arrays. Strikingly, progression of MASLD was characterized by gradual DNAm changes, revealing multiple associated KEGG pathways. Additionally, Horvath’s EAA significantly correlated with MASLD stage and individual histological MASLD parameters while LiverClock’s EAA correlated only with MASLD stage. In contrast, both Horvath’s intrinsic EAA and HepClock’s EAA showed no significant correlations. Integrative analyses, leveraging both gradual MASLD and Horvath’s EAA DNAm signatures, gene expression ( n  = 118), and a MASLD-specific transcriptional regulatory network, identified (regulon-specific) transcription factors implicated in MASLD and EAA progression, representing a transcription factor-network of redox (ferroptosis), immune, and metabolic/endocrine related epigenetic processes. Conclusion Gradual DNAm changes were found to align with progression of MASLD and EAA, with EAA a potential nonbiased quantitative biomarker for MASLD. Integrative analysis highlighted potential new therapeutic transcription factor targets, with special emphasis on AEBP1 and emerging nuclear receptors including CAR(NR1I3), MR(NR3C2), GR(NR3C1), and ESRRG, underscoring the potential of epigenetic redox-metabolic therapies for MASLD. Graphical abstract

Objective The epigenetic clock has been regarded as a highly accurate predictor of capturing the complexity between aging and the epigenome. However, there is limited understanding of the epigenetic clock in allergic diseases. The aim of this study was to explore the causal relationship between epigenetic age acceleration and allergic diseases by conducting a bidirectional two-sample Mendelian randomization (MR) study. Methods Pleiotropy analysis was conducted using the MR-Egger intercept test and the MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) test. Instrumental variables were constructed using single nucleotide polymorphisms. The statistics for epigenetic age acceleration and allergic diseases were derived from genome-wide association studies (GWAS) of European ancestry. MR analysis was performed using inverse variance weighted, weighted median, and MR-Egger methods. Results Based on the inverse variance weighted method, the forward MR analysis showed that intrinsic epigenetic age acceleration (IEAA) was associated with an increased risk of allergic asthma (OR = 1.051, 95% CI 1.006 to 1.098, p  = 0.025). The reverse MR analysis also indicated a significant causal relationship between allergic asthma and IEAA (OR = 1.410, 95% CI 1.111 to 1.791, p  = 0.005). However, there was a lack of evidence supporting a causal relationship between IEAA and allergic conjunctivitis, atopic dermatitis, allergic rhinitis and allergic urticaria (all p  > 0.05). Quality control assessments demonstrated that our study results were reliable and robust. Conclusions This study revealed bidirectional causal relationships between intrinsic epigenetic age acceleration and allergic asthma, highlighting potential prevention strategies.

The current study examines the application of the Pediatric-Buccal-Epigenetic (PedBE) clock, designed for buccal epithelial cells, to endothelia. We evaluate the association of PedBE epigenetic age and age acceleration estimated from human umbilical vein endothelial cells (HUVECs) with length of gestation and birthweight in a racially and ethnically diverse sample (analytic sample n = 333). PedBE age was positively associated with gestational age at birth (r = 0.22, p < .001) and infant birth weight (r = 0.20, p < .001). Multivariate models revealed infants with higher birth weight (adjusted for gestational age) had greater PedBE epigenetic age acceleration (b = 0.0002, se = 0.0007, p = 0.002), though this effect was small; findings were unchanged excluding preterm infants born before 37 weeks’ gestation. In conclusion, the PedBE clock may have application to endothelial cells and provide utility as an anchoring sampling point at birth to examine epigenetic aging in infancy.

Epigenetic age acceleration (AA) has been associated with adverse environmental exposures and many chronic conditions. We estimated, in the NINFEA birth cohort, infant saliva epigenetic age, and investigated whether parental socio-economic position (SEP) and pregnancy outcomes are associated with infant epigenetic AA. A total of 139 saliva samples collected at on average 10.8 (range 7–17) months were used to estimate Horvath’s DNA methylation age. Epigenetic AA was defined as the residual from a linear regression of epigenetic age on chronological age. Linear regression models were used to test the associations of parental SEP and pregnancy outcomes with saliva epigenetic AA. A moderate positive association was found between DNA methylation age and chronological age, with the median absolute difference of 6.8 months (standard deviation [SD] 3.9). The evidence of the association between the indicators of low SEP and epigenetic AA was weak; infants born to unemployed mothers or with low education had on average 1 month higher epigenetic age than infants of mothers with high education and employment (coefficient 0.78 months, 95% confidence intervals [CIs]: −0.79 to 2.34 for low/medium education; 0.96, 95% CI: −1.81 to 3.73 for unemployment). There was no evidence for association of gestational age, birthweight or caesarean section with infant epigenetic AA. Using the Horvath’s method, DNA methylation age can be fairly accurately predicted from saliva samples already in the first months of life. This study did not reveal clear associations between either pregnancy outcomes or parental socio-economic characteristics and infant saliva epigenetic AA.

Induced pluripotent stem cells (IPSCs), with their unlimited regenerative capacity, carry the promise for tissue replacement to counter age‐related decline. However, attempts to realize in vivo iPSC have invariably resulted in the formation of teratomas. Partial reprogramming in prematurely aged mice has shown promising results in alleviating age‐related symptoms without teratoma formation. Does partial reprogramming lead to rejuvenation (i.e., “younger” cells), rather than dedifferentiation, which bears the risk of cancer? Here, we analyse the dynamics of cellular age during human iPSC reprogramming and find that partial reprogramming leads to a reduction in the epigenetic age of cells. We also find that the loss of somatic gene expression and epigenetic age follows different kinetics, suggesting that they can be uncoupled and there could be a safe window where rejuvenation can be achieved with a minimized risk of cancer.

Background Previous studies have developed models predicting methylation age from DNA methylation in blood and other tissues (epigenetic clock) and suggested the difference between DNA methylation and chronological ages as a marker of healthy aging. The goal of this study was to confirm and expand such observations by investigating whether different concepts of the epigenetic clocks in a population-based cohort are associated with cancer, cardiovascular, and all-cause mortality. Results DNA methylation age was estimated in a cohort of 1863 older people, and the difference between age predicted by DNA methylation and chronological age (Δ age ) was calculated. A case-cohort design and weighted proportional Cox hazard models were used to estimate associations of Δ age with cancer, cardiovascular, and all-cause mortality. Hazard ratios for Δ age (per 5 years) calculated using the epigenetic clock developed by Horvath were 1.23 (95 % CI 1.10–1.38) for all-cause mortality, 1.22 (95 % CI 1.03–1.45) for cancer mortality, and 1.19 (95 % CI 0.98–1.43) for cardiovascular mortality after adjustment for batch effects, age, sex, educational level, history of chronic diseases, hypertension, smoking status, body mass index, and leucocyte distribution. Associations were similar but weaker for Δ age calculated using the epigenetic clock developed by Hannum. Conclusions These results show that age acceleration in terms of the difference between age predicted by DNA methylation and chronological age is an independent predictor of all-cause and cause-specific mortality and may be useful as a general marker of healthy aging.

Ageing is an inevitable condition that afflicts all humans. Recent achievements, such as the generation of induced pluripotent stem cells, have delivered preliminary evidence that slowing down and reversing the ageing process might be possible. However, these techniques usually involve complete dedifferentiation, i.e. somatic cell identity is lost as cells are converted to a pluripotent state. Separating the rejuvenative properties of reprogramming from dedifferentiation is a promising prospect, termed epigenetic rejuvenation. Reprogramming-induced rejuvenation strategies currently involve using Yamanaka factors (typically transiently expressed to prevent full dedifferentiation) and are promising candidates to safely reduce biological age. Here, we review the development and potential of reprogramming-induced rejuvenation as an anti-ageing strategy.

Background Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan‐tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue. Methods To address this, we developed a more accurate, muscle‐specific epigenetic clock based on the genome‐wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18–89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome‐wide association study of age‐associated DNA methylation patterns in skeletal muscle. Results The newly developed clock uses 200 cytosine‐phosphate–guanine dinucleotides to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 cytosine‐phosphate–guanine dinucleotides of the pan‐tissue clock. The muscle clock outperformed the pan‐tissue clock, with a median error of only 4.6 years across datasets (vs. 13.1 years for the pan‐tissue clock, P < 0.0001) and an average correlation of ρ = 0.62 between actual and predicted age across datasets (vs. ρ = 0.51 for the pan‐tissue clock). Lastly, we identified 180 differentially methylated regions with age in skeletal muscle at a false discovery rate < 0.005. However, gene set enrichment analysis did not reveal any enrichment for gene ontologies. Conclusions We have developed a muscle‐specific epigenetic clock that predicts age with better accuracy than the pan‐tissue clock. We implemented the muscle clock in an r package called Muscle Epigenetic Age Test available on Bioconductor to estimate epigenetic age in skeletal muscle samples. This clock may prove valuable in assessing the impact of environmental factors, such as exercise and diet, on muscle‐specific biological ageing processes.