Genetic and environmental causes of variation in epigenetic aging across the lifespan

Neuroinflammaging: A Tight Line Between Normal Aging and Age-Related Neurodegenerative Disorders

Aging in the healthy brain is characterized by a low-grade, chronic, and sterile inflammatory process known as neuroinflammaging. This condition, mainly consisting in an up-regulation of the inflammatory response at the brain level, contributes to the pathogenesis of age-related neurodegenerative disorders. Development of this proinflammatory state involves the interaction between genetic and environmental factors, able to induce age-related epigenetic modifications. Indeed, the exposure to environmental compounds, drugs, and infections, can contribute to epigenetic modifications of DNA methylome, histone fold proteins, and nucleosome positioning, leading to epigenetic modulation of neuroinflammatory responses. Furthermore, some epigenetic modifiers, which combine and interact during the life course, can contribute to modeling of epigenome dynamics to sustain, or dampen the neuroinflammatory phenotype. The aim of this review is to summarize current knowledge about neuroinflammaging with a particular focus on epigenetic mechanisms underlying the onset and progression of neuroinflammatory cascades in the central nervous system; furthermore, we describe some diagnostic biomarkers that may contribute to increase diagnostic accuracy and help tailor therapeutic strategies in patients with neurodegenerative diseases.

Curcumin improves atrial fibrillation susceptibility by regulating tsRNA expression in aging mouse atrium

Age is an independent risk factor for atrial fibrillation (AF), and curcumin can delay aging related disease through reducing oxidative stress and inflammation. However, its target in aging-related AF remains unclear. Transfer RNA-derived small RNA (tsRNA) is a novel short non-coding RNA (sncRNA), and exerts a potential regulatory function in aging. This study was to explore the therapeutic targets of curcumin in atrium of aged mice by PANDORA-seq. Aged mice (18 month) were treated with curcumin (100 mg/kg). Rapid transjugular atrial pacing was performed to observe AF inducibility. SA-β-gal staining, reactive oxygen species (ROS) detection and qRT-PCR were used to assess the degree of aging and oxidative stress/inflammation levels. PANDORA-seq was performed to reveal the differentially expressed sncRNAs in the atrium of mice. The results showed that curcumin reduced the susceptibility AF of aged mice by improving aging-related atrial fibrosis. Compared to young mice (5 month) group, aged mice yielded 473 significantly altered tsRNA sequences, while 947 tsRNA sequences were significantly altered after treated with curcumin. Enrichment analysis revealed that the target genes were mainly related to DNA damage and protein modification. Compared with the 5 month group, the expression levels of mature-mt_tRNA-Val-TAC_CCA_end, mature-mt_tRNA-Glu-TTC_CCA_end, and mature-tRNA-Asp-GTC_CCA_end were up-regulated in the 18 month group, while the expression of mature-mt_tRNA-Thr-TGT_5_end was down-regulated. This trend was reversed in the 18 month + curcumin group. Increased cellular ROS levels, inflammation expression and senescence in aged mice atrium were improved by the down-regulation of mature-mt_tRNA-Val-TAC_CCA_end. In conclusion, our findings identified mature-mt_tRNA-Val-TAC_CCA_end participated in the mechanism of aging-related atrial fibrosis, providing new intervention target of aging-related AF.

Sociodemographic and Lifestyle Factors and Epigenetic Aging in US Young Adults: NIMHD Social Epigenomics Program

Importance

Epigenetic clocks represent molecular evidence of disease risk and aging processes and have been used to identify how social and lifestyle characteristics are associated with accelerated biological aging. However, most research is based on samples of older adults who already have measurable chronic disease.

Objective

To investigate whether and how sociodemographic and lifestyle characteristics are associated with biological aging in a younger adult sample across a wide array of epigenetic clock measures.

Design, Setting, and Participants

This cohort study was conducted using data from the National Longitudinal Study of Adolescent to Adult Health, a US representative cohort of adolescents in grades 7 to 12 in 1994 followed up for 25 years to 2018 over 5 interview waves. Participants who provided blood samples at wave V (2016-2018) were analyzed, with samples tested for DNA methylation (DNAm) in 2021 to 2024. Data were analyzed from February 2023 to May 2024.

Exposure

Sociodemographic (sex, race and ethnicity, immigrant status, socioeconomic status, and geographic location) and lifestyle (obesity status by body mass index [BMI] in categories of reference range or underweight [<25], overweight [25 to <30], obesity [30 to <40], and severe obesity [≥40]; exercise level; tobacco use; and alcohol use) characteristics were assessed.

Main Outcome and Measure

Biological aging assessed from banked blood DNAm using 16 epigenetic clocks.

Results

Data were analyzed from 4237 participants (mean [SD] age, 38.4 [2.0] years; percentage [SE], 51.3% [0.01] female and 48.7% [0.01] male; percentage [SE], 2.7% [<0.01] Asian or Pacific Islander, 16.7% [0.02] Black, 8.7% [0.01] Hispanic, and 71.0% [0.03] White). Sociodemographic and lifestyle factors were more often associated with biological aging in clocks trained to estimate morbidity and mortality (eg, PhenoAge, GrimAge, and DunedinPACE) than clocks trained to estimate chronological age (eg, Horvath). For example, the β for an annual income less than $25 000 vs $100 000 or more was 1.99 years (95% CI, 0.45 to 3.52 years) for PhenoAgeAA, 1.70 years (95% CI, 0.68 to 2.72 years) for GrimAgeAA, 0.33 SD (95% CI, 0.17 to 0.48 SD) for DunedinPACE, and -0.17 years (95% CI, -1.08 to 0.74 years) for Horvath1AA. Lower education, lower income, higher obesity levels, no exercise, and tobacco use were associated with faster biological aging across several clocks; associations with GrimAge were particularly robust (no college vs college or higher: β = 2.63 years; 95% CI, 1.67-3.58 years; lower vs higher annual income: <$25 000 vs ≥$100 000: β = 1.70 years; 95% CI, 0.68-2.72 years; severe obesity vs no obesity: β = 1.57 years; 95% CI, 0.51-2.63 years; no weekly exercise vs ≥5 bouts/week: β = 1.33 years; 95% CI, 0.67-1.99 years; current vs no smoking: β = 7.16 years; 95% CI, 6.25-8.07 years).

Conclusions and Relevance

This study found that important social and lifestyle factors were associated with biological aging in a nationally representative cohort of younger adults. These findings suggest that molecular processes underlying disease risk may be identified in adults entering midlife before disease is manifest and inform interventions aimed at reducing social inequalities in heathy aging and longevity.

Sex-Specific Deflection of Age-Related DNA Methylation and Gene Expression in Mouse Heart by Perinatal Toxicant Exposures

Background

Global and site-specific changes in DNA methylation and gene expression are associated with cardiovascular aging and disease, but how toxicant exposures during early development influence the normal trajectory of these age-related molecular changes, and whether there are sex differences, has not yet been investigated.

Objectives

We used an established mouse model of developmental exposures to investigate the effects of perinatal exposure to either lead (Pb) or diethylhexyl phthalate (DEHP), two ubiquitous environmental contaminants strongly associated with CVD, on age-related cardiac DNA methylation and gene expression.

Methods

Dams were randomly assigned to receive human physiologically relevant levels of Pb (32 ppm in water), DEHP (25 mg/kg chow), or control water and chow. Exposures started two weeks prior to mating and continued until weaning at postnatal day 21 (3 weeks of age). Approximately one male and one female offspring per litter were followed to 3 weeks, 5 months, or 10 months of age, at which time whole hearts were collected (n ≥ 5 per sex per exposure). Enhanced reduced representation bisulfite sequencing (ERRBS) was used to assess the cardiac DNA methylome at 3 weeks and 10 months, and RNA-seq was conducted at all 3 time points. MethylSig and edgeR were used to identify age-related differentially methylated regions (DMRs) and differentially expressed genes (DEGs), respectively, within each sex and exposure group. Cell type deconvolution of bulk RNA-seq data was conducted using the MuSiC algorithm and publicly available single cell RNA-seq data.

Results

Thousands of DMRs and hundreds of DEGs were identified in control, DEHP, and Pb-exposed hearts across time between 3 weeks and 10 months of age. A closer look at the genes and pathways showing differential DNA methylation revealed that the majority were unique to each sex and exposure group. Overall, pathways governing development and differentiation were most frequently altered with age in all conditions. A small number of genes in each group showed significant changes in DNA methylation and gene expression with age, including several that were altered by both toxicants but were unchanged in control. We also observed subtle, but significant changes in the proportion of several cell types due to age, sex, and developmental exposure.

Discussion

Together these data show that perinatal Pb or DEHP exposures deflect normal age-related gene expression, DNA methylation programs, and cellular composition across the life course, long after cessation of exposure, and highlight potential biomarkers of developmental toxicant exposures. Further studies are needed to investigate how these epigenetic and transcriptional changes impact cardiovascular health across the life course.

The Sociodemographic and Lifestyle Correlates of Epigenetic Aging in a Nationally Representative U.S. Study of Younger Adults

Importance

Epigenetic clocks represent molecular evidence of disease risk and aging processes and have been used to identify how social and lifestyle characteristics are associated with accelerated biological aging. However, most of this research is based on older adult samples who already have measurable chronic disease.

Objective

To investigate whether and how sociodemographic and lifestyle characteristics are related to biological aging in a younger adult sample across a wide array of epigenetic clock measures.

Design

Nationally representative prospective cohort study.

Setting

United States (U.S.).

Participants

Data come from the National Longitudinal Study of Adolescent to Adult Health, a national cohort of adolescents in grades 7-12 in U.S. in 1994 followed for 25 years over five interview waves. Our analytic sample includes participants followed-up through Wave V in 2016-18 who provided blood samples for DNA methylation (DNAm) testing (n=4237) at Wave V.

Exposure

Sociodemographic (sex, race/ethnicity, immigrant status, socioeconomic status, geographic location) and lifestyle (obesity status, exercise, tobacco, and alcohol use) characteristics.

Main Outcome

Biological aging assessed from blood DNAm using 16 epigenetic clocks when the cohort was aged 33-44 in Wave V.

Results

While there is considerable variation in the mean and distribution of epigenetic clock estimates and in the correlations among the clocks, we found sociodemographic and lifestyle factors are more often associated with biological aging in clocks trained to predict current or dynamic phenotypes (e.g., PhenoAge, GrimAge and DunedinPACE) as opposed to clocks trained to predict chronological age alone (e.g., Horvath). Consistent and strong associations of faster biological aging were found for those with lower levels of education and income, and those with severe obesity, no weekly exercise, and tobacco use.

Conclusions and Relevance

Our study found important social and lifestyle factors associated with biological aging in a nationally representative cohort of younger-aged adults. These findings indicate that molecular processes underlying disease risk can be identified in adults entering midlife before disease is manifest and represent useful targets for interventions to reduce social inequalities in heathy aging and longevity.

Key Points

Question: Are epigenetic clocks, measures of biological aging developed mainly on older-adult samples, meaningful for younger adults and associated with sociodemographic and lifestyle characteristics in expected patterns found in prior aging research?Findings: Sociodemographic and lifestyle factors were associated with biological aging in clocks trained to predict morbidity and mortality showing accelerated aging among those with lower levels of education and income, and those with severe obesity, no weekly exercise, and tobacco use.Meaning: Age-related molecular processes can be identified in younger-aged adults before disease manifests and represent potential interventions to reduce social inequalities in heathy aging and longevity.

Mother adversity and co-residence time impact mother-child similarity in genome-wide and gene-specific methylation profiles

BACKGROUND

The effects of adverse life events on physical and psychological health, with DNA methylation (DNAm) as a critical underlying mechanism, have been extensively studied. However, the epigenetic resemblance between mother and child in the context of neglectful caregiving, and whether it may be shaped by the emotional impact of maternal stressful events and the duration of co-residence (indexed by child age), remains unknown. The present study examined mother-child similarity in methylation profiles, considering the potential effect of mother adversity, mother empathy, neglect-control group, child age (an index of years of mother-child co-residence), and mother age. Using Illumina Epic arrays, we quantified DNAm in 115 mother-child saliva samples. We obtained a methylation similarity index by computing correlation coefficients between methylation profiles within dyads, for the entire epigenome, and five specific genes related to stress and empathy: NR3C1, FKPB5, OXTR, SCL6A4, and BDNF.

RESULTS

The methylation profiles of the mother-child familial pairs significantly correlated as compared to mother-child random pairs for the entire epigenome and NR3C1, FKBP5, OXTR and BDNF genes. Next, multiple linear regression models observed associations of mother adversity, child age, and neglect-control group on mother-child methylation similarity, only significant in mother-child familial pairs, after correcting for multiple comparisons. Higher mother adversity was associated with lower mother-child methylation similarity for the epigenome-wide analysis, for the BDNF gene, and in the neglect-control group for the OXTR gene. In turn, being an older child (longer co-residence) was associated with higher mother-child methylation similarity.

CONCLUSIONS

Mother adversity and co-residence time are modulating factors in the intergenerational methylation process that offer a window into development-dependent adaptations that can be affected by both hereditary and environmental factors, significantly observed only in biological dyads. A twofold implication for child well-being emerges, one is positive in that children of mothers exposed to life adversity or neglect did not necessarily inherit their methylation patterns. The other is concerning due to the influence of time spent living together, which affects similarity with the mother and potentially increases the risk of inheriting an epigenetic profile associated with future dysfunctional parenting patterns. This underscores the importance of the 'the earlier, the better' recommendation by the Child Protection System, which is not always followed.

Host fecal DNA specific methylation signatures mark gut dysbiosis and inflammation in children affected by autism spectrum disorder

The gut-brain axis involves several bidirectional pathway communications including microbiome, bacterial metabolites, neurotransmitters as well as immune system and is perturbed both in brain and in gastrointestinal disorders. Consistently, microbiota-gut-brain axis has been found altered in autism spectrum disorder (ASD). We reasoned that such alterations occurring in ASD may impact both on methylation signatures of human host fecal DNA (HFD) and possibly on the types of human cells shed in the stools from intestinal tract giving origin to HFD. To test this hypothesis, we have performed whole genome methylation analysis of HFD from an age-restricted cohort of young children with ASD (N = 8) and healthy controls (N = 7). In the same cohort we have previously investigated the fecal microbiota composition and here we refined such analysis and searched for eventual associations with data derived from HFD methylome analysis. Our results showed that specific epigenetic signatures in human fecal DNA, especially at genes related to inflammation, associated with the disease. By applying methylation-based deconvolution algorithm, we found that the HFD derived mainly from immune cells and the relative abundance of those differed between patients and controls. Consistently, most of differentially methylated regions fitted with genes involved in inflammatory response. Interestingly, using Horvath epigenetic clock, we found that ASD affected children showed both epigenetic and microbiota age accelerated. We believe that the present unprecedented approach may be useful for the identification of the ASD associated HFD epigenetic signatures and may be potentially extended to other brain disorders and intestinal inflammatory diseases.

Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks

BACKGROUND

The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered.

DEVELOPMENT

We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID's building block is variance in risk, Δ2, where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(rΔ2). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher's classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors.

APPLICATION

For female breast cancer, VALID quantified how much variance in risk is explained-at different ages-by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors.

CONCLUSION

VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk.

Low birthweight is associated with epigenetic age acceleration in the first 3 years of life

Background and objectives

The Developmental Origins of Health and Disease hypothesis posits that early life adversity is associated with poor adult health outcomes. Epidemiological evidence has supported this framework by linking low birthweight with adult health and mortality, but the mechanisms remain unclear. Accelerated epigenetic aging may be a pathway to connect early life experiences with adult health outcomes, based on associations of accelerated epigenetic aging with increased morbidity and mortality.

Methodology

Sixty-seven mother-infant dyads were recruited in the eastern Democratic Republic of Congo. Birthweight data were collected at birth, and blood samples were collected at birth and follow-up visits up to age 3. DNA methylation data were generated with the Illumina MethylationEPIC array and used to estimate epigenetic age. A multilevel model was used to test for associations between birthweight and epigenetic age acceleration.

Results

Chronological age was highly correlated with epigenetic age from birth to age 3 (r = 0.95, p < 2.2 × 10-16). Variation in epigenetic age acceleration increased over time. Birthweight, dichotomized around 2500 g, predicted epigenetic age acceleration over the first 3 years of life (b = -0.39, p = 0.005).

Conclusions and implications

Our longitudinal analysis provides the first evidence for accelerated epigenetic aging that emerges between birth and age 3 and associates with low birthweight. These results suggest that early life experiences, such as low birthweight, may shape the trajectory of epigenetic aging in early childhood. Furthermore, accelerated epigenetic aging may be a pathway that links low birthweight and poor adult health outcomes.

Association between the epigenetic lifespan predictor GrimAge and history of suicide attempt in bipolar disorder

Bipolar disorder (BD) has been previously associated with premature mortality and aging, including acceleration of epigenetic aging. Suicide attempts (SA) are greatly elevated in BD and are associated with decreased lifespan, biological aging, and poorer clinical outcomes. We investigated the relationship between GrimAge, an epigenetic clock trained on time-to-death and associated with mortality and lifespan, and SA in two independent cohorts of BD individuals (discovery cohort - controls (n = 50), BD individuals with (n = 77, BD/SA) and without (n = 67, BD/non-SA) lifetime history of SA; replication cohort - BD/SA (n = 48) and BD/non-SA (n = 47)). An acceleration index for the GrimAge clock (GrimAgeAccel) was computed from blood DNA methylation (DNAm) and compared between groups with multiple general linear models. Differences in epigenetic aging from the discovery cohort were validated in the independent replication cohort. In the discovery cohort, controls, BD/non-SA, and BD/SA significantly differed on GrimAgeAccel (F = 5.424, p = 0.005), with the highest GrimAgeAccel in BD/SA (p = 0.004, BD/SA vs. controls). Within the BD individuals, BD/non-SA and BD/SA differed on GrimAgeAccel in both cohorts (p = 0.008) after covariate adjustment. Finally, DNAm-based surrogates revealed possible involvement of plasminogen activator inhibitor 1, leptin, and smoking pack-years in driving accelerated epigenetic aging. These findings pair with existing evidence that not only BD, but also SA, may be associated with an accelerated biological aging and provide putative biological mechanisms for morbidity and premature mortality in this population.

Forensic Age Estimation through a DNA Methylation-Based Age Prediction Model in the Italian Population: A Pilot Study

DNA methylation is one of the epigenetic marks which has been studied intensively in recent years for age predicting purposes in the forensic area. In order to integrate age prediction into routine forensic workflow, the purpose of this study was to standardize and optimize a DNA methylation-based protocol tailored to the Italian context. A previously published protocol and age-predictive method was implemented for the analysis of 84 blood samples originating from Central Italy. The study here presented is based on the Single Base Extension method, considering five genes: ELOVL2, FHL2, KLF14, C1orf132, now identified as MIR29B2C, and TRIM59. The precise and specific steps consist of DNA extraction and quantification, bisulfite conversion, amplification of converted DNA, first purification, single base extension, second purification, capillary electrophoresis, and analysis of the results to train and test the tool. The prediction error obtained, expressed as mean absolute deviation, showed a value of 3.12 years in the training set and 3.01 years in the test set. Given that population-based differences in DNA methylation patterns have been previously reported in the literature, it would be useful to further improve the study implementing additional samples representative of the entire Italian population.

A new blood based epigenetic age predictor for adolescents and young adults

Children have special rights for protection compared to adults in our society. However, more than 1/4 of children globally have no documentation of their date of birth. Hence, there is a pressing need to develop biological methods for chronological age prediction, robust to differences in genetics, psychosocial events and physical living conditions. At present, DNA methylation is the most promising biological biomarker applied for age assessment. The human genome contains around 28 million DNA methylation sites, many of which change with age. Several epigenetic clocks accurately predict chronological age using methylation levels at age associated GpG-sites. However, variation in DNA methylation increases with age, and there is no epigenetic clock specifically designed for adolescents and young adults. Here we present a novel age Predictor for Adolescents and Young Adults (PAYA), using 267 CpG methylation sites to assess the chronological age of adolescents and young adults. We compared different preprocessing approaches and investigated the effect on prediction performance of the epigenetic clock. We evaluated performance using an independent validation data set consisting of 18-year-old individuals, where we obtained a median absolute deviation of just below 0.7 years. This tool may be helpful in age assessment of adolescents and young adults. However, there is a need to investigate the robustness of the age predictor across geographical and disease populations as well as environmental effects.

Tracing Slow Phenoptosis to the Prenatal Stage in Social Vertebrates

Vladimir Skulachev's coining of the term "phenoptosis" 25 years ago (Skulachev, V. P., Biochemistry (Moscow), 62, 1997) highlighted the theoretical possibility that aging is a programmed process to speed the exit of individuals posing some danger to their social group. While rapid "acute phenoptosis" might occur at any age (e.g., to prevent spread of deadly infections), "slow phenoptosis" is generally considered to occur later in life in the form of chronic age-related disorders. However, recent research indicates that risks for such chronic disorders can be greatly raised by early life adversity, especially during the prenatal stage. Much of this research uses indicators of biological aging, the speeding or slowing of natural physiological deterioration in response to environmental inputs, leading to divergence from chronological age. Studies using biological aging indicators commonly find it is accelerated not only in older individuals with chronic disorders, but also in very young individuals with health problems. This review will explain how accelerated biological aging equates to slow phenoptosis. Its occurrence even in the prenatal stage is theoretically supported by W. D. Hamilton's proposal that offsprings detecting they have dangerous mutations should then automatically speed their demise, in order to improve their inclusive fitness by giving their parents the chance to produce other fitter siblings.

Sex differences in ocular biometric measurements: A twin study

Objective

Gender differences in ocular biometric measurements of opposite-sex and same-sex twin pairs are still unclear. We aimed to investigate the difference between ocular biometric measurements in adolescent twin pairs.

Materials and methods

This retrospective study included a total of 64 eyes of 64 adolescents from 32 twins. The ocular biometric measurements and refractive prediction error (RE) were acquired from four groups of dizygotic (DZ) twins: boys from same-sex twin-pairs (SSM, n = 20), boys from opposite-sex twin-pairs (OSM, n = 8), girls from opposite-sex twin-pairs (OSF, n = 8), and girls from same-sex twin-pairs (SSF, n = 29).

Results

The mean age of the patient was 9.92 ± 2.84 (range: 6–18) years. Overall, boys had higher height, AL, WTW, but lower Ks, and Kf than girls (p &lt; 0.05). Specifically, SSF was found to have the lowest lens thickness (LT), anterior chamber depth (ACD), central corneal thickness (CCT), white to white (WTW), and axial length (AL) levels, while the highest keratometry readings in the flat (Kf) and steep (Ks) levels compared with OSM, OSF, and SSM adolescents (p &lt; 0.05). Compared with the OSF adolescents, ACD levels of the SSF adolescents were significantly lower [(2.99 ± 0.35) and (3.26 ± 0.15) mm, p = 0.033)], but Kf indicator was significantly larger [(43.93 ± 1.64) and (42.91 ± 1.75), p = 0.016)].

Conclusion

Our study indicates that there was a significant difference in ocular biometric measurements between twin pairs, and sharing the uterus with a DZ twin SSF has smaller ocular indicator measurements. Our findings provide information on the eyeball and refractive development in adolescents.

Differences in DNA Methylation-Based Age Prediction Within Twin Pairs Discordant for Cancer

DNA methylation-based age acceleration (DNAmAA) is associated with cancer, with both cancer tissue and blood showing increased DNAmAA. We aimed to investigate whether DNAmAA is associated with cancer risk within twin pairs discordant for cancer, and whether DNAmAA has the potential to serve as a biomarker for such. The study included 47 monozygotic and 48 same-sex-dizygotic cancer-discordant twin pairs from the Finnish Twin Cohort study with blood samples available between 17 and 31 years after the cancer diagnosis. We studied all cancers (95 pairs), then separately breast cancer (24 pairs) and all sites other than breast cancer (71 pairs). DNAmAA was calculated for seven models: Horvath, Horvath intrinsic epigenetic age acceleration, Hannum, Hannum intrinsic epigenetic age acceleration, Hannum extrinsic epigenetic age acceleration, PhenoAge and GrimAge. Within-pair differences in DNAmAA were analyzed by paired t tests and linear regression. Twin pairs sampled before cancer diagnosis did not differ significantly in DNAmAA. However, the within-pair differences in DNAmAA before cancer diagnosis increased significantly the closer the cancer diagnosis was, and this acceleration extended for years after the diagnosis. Pairs sampled after the diagnosis differed for DNAmAA with the Horvath models capturing cancer diagnosis-associated DNAmAA across all three cancer groupings. The results suggest that DNAmAA in blood is associated with cancer diagnosis. This may be due to epigenetic alterations in relation to cancer, its treatment or associated lifestyle changes. Based on the current study, the biomarker potential of DNAmAA in blood appears to be limited.

The Heritability of Kidney Function Using an Older Australian Twin Population

Introduction

Twin studies are unique population models which estimate observed rather than inferred genetic components of complex traits. Nonmonogenic chronic kidney disease (CKD) is a complex disease process with strong genetic and environmental influences, amenable to twin studies. We aimed to assess the heritability of CKD using twin analysis and modeling within Older Australian Twin Study (OATS) data.

Methods

OATS had 109 dizygotic (DZ) and 126 monozygotic (MZ) twin pairs with paired serum creatinine levels. Heritability of kidney function as estimated glomerular filtration rate (eGFR CKD Epidemiology Collaboration [CKD-EPI]) was modeled using the ACE model to estimate additive heritability (A), common (C), and unique (E) environmental factors. Intratwin pair analysis using mixed effects logistic regression allowed analysis of variation in eGFR from established CKD risk factors.

Results

The median age was 69.71 (interquartile range 78.4-83.0) years, with 65% female, and a mean CKD-EPI of 82.8 ml/min (SD 6.7). The unadjusted ACE model determined kidney function to be 33% genetically determined (A), 18% shared genetic-environmental (C), and 49% because of unique environment (E). This remained unchanged when adjusted for age, hypertension, and sex. Hypertension was associated with eGFR; however, intertwin variance in hypertension did not explain variance in eGFR. Two or more hypertension medications were associated with decreased eGFR (P = 0.009).

Conclusion

This study estimates observed heritability at 33%, notably higher than inferred heritability in genome-wide association study (GWAS) (7.1%-18%). Epigenetics and other genomic phenomena may explain this heritability gap. Difference in antihypertension medications explains part of unique environmental exposures, though discordance in hypertension and diabetes does not.

Counteracting aged DNA methylation states to combat ageing and age-related diseases

DNA methylation (DNAm) overwrites information about multiple extrinsic factors on the genome. Age is one of these factors. Age causes characteristic DNAm changes that are thought to be not only major drivers of normal ageing but also precursors to diseases, cancer being one of these. Although there is still much to learn about the relationship between ageing, age-related diseases and DNAm, we now know how to interpret some of the effects caused by age in the form of changes in methylation marks at specific loci. In fact, these changes form the basis of the so called "epigenetic clocks", which translate the genomic methylation profile into an "epigenetic age". Epigenetic age does not only estimate chronological age but can also predict the risk of chronic diseases and mortality. Epigenetic age is believed to be one of the most accurate metrics of biological age. Initial evidence has recently been gathered pointing to the possibility that the rate of epigenetic ageing can be slowed down or even reversed. In this review, we discuss some of the most relevant advances in this field. Expected outcome is that this approach can provide insights into how to preserve health and reduce the impact of ageing diseases in humans.

Early life affects late-life health through determining DNA methylation across the lifespan: A twin study

Background

Previous findings for the genetic and environmental contributions to DNA methylation variation were for limited age ranges only. We investigated the lifespan contributions and their implications for human health for the first time.

Methods

1,720 monozygotic twin (MZ) pairs and 1,107 dizygotic twin (DZ) pairs aged 0-92 years were included. Familial correlations (i.e., correlations between twins) for 353,681 methylation sites were estimated and modelled as a function of twin pair cohabitation history.

Findings

The methylome average familial correlation was around zero at birth (MZ pair: -0.01; DZ pair: -0.04), increased with the time of twins living together during childhood at rates of 0.16 (95%CI: 0.12-0.20) for MZ pairs and 0.13 (95%CI: 0.07-0.20) for DZ pairs per decade, and decreased with the time of living apart during adulthood at rates of 0.026 (95%CI: 0.019-0.033) for MZ pairs and 0.027 (95%CI: 0.011-0.043) for DZ pairs per decade. Neither the increasing nor decreasing rate differed by zygosity (both P>0.1), consistent with cohabitation environment shared by twins, rather than genetic factors, influencing the methylation familial correlation changes. Familial correlations for 6.6% (23,386/353,681) sites changed with twin pair cohabitation history. These sites were enriched for high heritability, proximal promoters, and epigenetic/genetic associations with various early-life factors and late-life health conditions.

Interpretation

Early life strongly influences DNA methylation variation across the lifespan, and the effects are stronger for heritable sites and sites biologically relevant to the regulation of gene expression. Early life could affect late-life health through influencing DNA methylation.

Funding

Victorian Cancer Agency, Cancer Australia, Cure Cancer Foundation.

SHOX2 methylation in Vietnamese patients with lung cancer

BACKGROUND

DNA methylation on cytosine in the CpG dinucleotides is one of the most common epigenetic perturbations taking place during cancer initiation, progression, occurrence and resistance therapy. DNA methylation seems to be sufficiently stable epigenetic modification to be utilized as a cancer biomarker in in vitro diagnostic (IVD) settings. Nowadays, the SHOX2 methylation (mSHOX2) is one of the most valuable DNA methylation biomarkers of lung cancer that is the leading cause of cancer death. It is being continuously validated across ethnicities, lifestyles and lifespan. This study focused on characteristics of mSHOX2 in Vietnamese patients with lung cancer since a lack of investigation and evidence of its utility in this country.

METHODS

The probe and primer sets were designed according to the MethyLight method for quantitative assessment of the mSHOX2 in 214 formalin-fixed paraffin-embedded (FFPE) lung tissues and 57 plasma samples.

RESULTS

mSHOX2 in FFPE tissues allowed discriminating benign and malignant lung diseases with 60% (95% CI 50.7-68.8%) sensitivity and 90.4% (95% CI 82.6-95.5%) specificity. Importantly, based on mSHOX2 in plasma, lung cancer could be detected with 83.3% (95% CI 65.3-94.4%) sensitivity and 92.6% (95% CI 75.7-99.1%) specificity, respectively. There were insignificant associations between mSHOX2 with age, cancer stage, EGFR mutation and serum CEA, CYFRA21-1 concentrations except for that gender.

CONCLUSION

Our study indicated that mSHOX2 was satisfactory for distinguishing malignant from benign lung tissue and noninvasively detecting lung cancer.

Genome-wide association study for four measures of epigenetic age acceleration and two epigenetic surrogate markers using DNA methylation data from Taiwan biobank

To highlight the genetic architecture for epigenetic aging, McCartney et al. recently identified 137 significant SNPs based on genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and two epigenetic surrogate markers. However, none Asian ancestry studies have been included in this or previous meta-analyses. I performed a GWAS on blood DNA methylation (DNAm) levels of 2309 Taiwan Biobank (TWB) participants. Owing to the fact that the sample size of an individual GWAS of DNAm data is still not large, I adopted the "prioritized subset analysis" (PSA) method to boost the power of a GWAS. The four epigenetic clocks and the two epigenetic surrogate markers were investigated, respectively. I replicated 21 out of the 137 aging-associated genetic loci by applying the PSA method to the TWB DNAm data. Moreover, I identified five novel loci, including rs117530284 that was associated with the "epigenetic age acceleration" (EAA) according to Lu et al.'s GrimAge (called "GrimEAA"). Considering 16 covariates (sex, BMI, smoking status, drinking status, regular exercise, educational attainment, and the first 10 ancestry principal components), each "A" allele of rs117530284 in the IBA57 gene was found to be associated with a 1.5943-year GrimEAA (95% C.I. = [1.0748, 2.1138]). IBA57 is a protein coding gene and is associated with multiple mitochondrial dysfunctions syndromes. A decline in mitochondrial activity and quality is associated with aging and many age-related diseases. This is one of the first DNAm GWAS for individuals of Asian ancestry.

Advances in Genetics and Epigenetic Alterations in Alzheimer's Disease: A Notion for Therapeutic Treatment

Alzheimer's disease (AD) is a disabling neurodegenerative disorder that leads to long-term functional and cognitive impairment and greatly reduces life expectancy. Early genetic studies focused on tracking variations in genome-wide DNA sequences discovered several polymorphisms and novel susceptibility genes associated with AD. However, despite the numerous risk factors already identified, there is still no fully satisfactory explanation for the mechanisms underlying the onset of the disease. Also, as with other complex human diseases, the causes of low heritability are unclear. Epigenetic mechanisms, in which changes in gene expression do not depend on changes in genotype, have attracted considerable attention in recent years and are key to understanding the processes that influence age-related changes and various neurological diseases. With the recent use of massive sequencing techniques, methods for studying epigenome variations in AD have also evolved tremendously, allowing the discovery of differentially expressed disease traits under different conditions and experimental settings. This is important for understanding disease development and for unlocking new potential AD therapies. In this work, we outline the genomic and epigenomic components involved in the initiation and development of AD and identify potentially effective therapeutic targets for disease control.

Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology

In this issue, Kresovich and colleagues have published a hallmark paper in Molecular, Environmental, Genetic and Analytic Epidemiology. By applying artificial intelligence to the Sister Study they created a new methylation-based breast cancer risk score (mBCRS) based on blood DNA methylation. Using a prospective design and after accounting for age and questionnaire-based breast cancer risk factors, the Odds PER Adjusted standard deviation (OPERA) for mBCRS and polygenic risk score (PRS) was 1.58 (95% CI: 1.38, 1.81) and 1.58 (95% CI: 1.36, 1.83), respectively, and the corresponding area under the receiver operating curve was 0.63 for both. Therefore, mBCRS could be as powerful as the current best PRS in differentiating women of the same age in terms of their breast cancer risk. These risk scores are among the strongest known breast cancer risk-stratifiers, shaded only by new mammogram risk scores based on measures other than conventional mammographic density, such as Cirrocumulus and Cirrus, which when combined have an OPERA as high as 2.3. The combination of PRS and mBCRS with the other measured risk factors gave an OPERA of 2.2. OPERA has many advantages over changes in areas under the receiver operator curve because the latter depend on the order in which risk factors are considered. Although more replication is needed using prospective data to protect against reverse causation, there are many novel molecular and analytic aspects to this paper which uncovers a potential mechanism for how genetic and environmental factors combine to cause breast cancer.

Exposure to ionizing radiation disrupts normal epigenetic aging in Japanese medaka

Alterations to the epigenome are a hallmark of biological aging and age-dependent patterning of the DNA methylome ("epigenetic aging") can be modeled to produce epigenetic age predictors. Rates of epigenetic aging vary amongst individuals and correlate to the onset of age-related disease and all-cause mortality. Yet, the origins of epigenetic-to-chronological age discordance are not empirically resolved. Here, we investigate the relationship between aging, DNA methylation, and environmental exposures in Japanese medaka (Oryzias latipes). We find age-associated DNA methylation patterning enriched in genomic regions of low CpG density and that, similar to mammals, most age-related changes occur during early life. We construct an epigenetic clock capable of predicting chronological age with a mean error of 61.1 days (~8.4% of average lifespan). To test the role of environmental factors in driving epigenetic age variation, we exposed medaka to chronic, environmentally relevant doses of ionizing radiation. Because most organisms share an evolutionary history with ionizing radiation, we hypothesized that exposure would reveal fundamental insights into environment-by-epigenetic aging interactions. Radiation exposure disrupted epigenetic aging by accelerating and decelerating normal age-associated patterning and was most pronounced in cytosines that were moderately associated with age. These findings empirically demonstrate the role of DNA methylation in integrating environmental factors into aging trajectories.

Impact of excessive alcohol abuse on age prediction using the VISAGE enhanced tool for epigenetic age estimation in blood

DNA methylation-based clocks provide the most accurate age estimates with practical implications for clinical and forensic genetics. However, the effects of external factors that may influence the estimates are poorly studied. Here, we evaluated the effect of alcohol consumption on epigenetic age prediction in a cohort of extreme alcohol abusers. Blood samples from deceased alcohol abusers and age- and sex-matched controls were analyzed using the VISAGE enhanced tool for age prediction from somatic tissues that enables examination of 44 CpGs within eight age markers. Significantly altered DNA methylation was recorded for alcohol abusers in MIR29B2CHG. This resulted in a mean predicted age of 1.4 years higher compared to the controls and this trend increased in older individuals. The association of alcohol abuse with epigenetic age acceleration, as determined by the prediction analysis performed based on MIR29B2CHG, was small but significant (β = 0.190; P-value = 0.007). However, the observed alteration in DNA methylation of MIR29B2CHG had a non-significant effect on age estimation with the VISAGE age prediction model. The mean absolute error in the alcohol-abusing cohort was 3.1 years, compared to 3.3 years in the control group. At the same time, upregulation of MIR29B2CHG expression may have a biological function, which merits further studies.

Surrounding Greenness and Biological Aging Based on DNA Methylation: A Twin and Family Study in Australia

BACKGROUND

High surrounding greenness has many health benefits and might contribute to slower biological aging. However, very few studies have evaluated this from the perspective of epigenetics.

OBJECTIVES

We aimed to evaluate the association between surrounding greenness and biological aging based on DNA methylation.

METHODS

We derived Horvath's DNA methylation age (DNAmAge), Hannum's DNAmAge, PhenoAge, and GrimAge based on DNA methylation measured in peripheral blood samples from 479 Australian women in 130 families. Measures of DNAmAge acceleration (DNAmAgeAC) were derived from the residuals after regressing each DNAmAge metric on chronological age. Greenness was represented by satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) metrics within 300-, 500-, 1,000-, and 2,000-m buffers surrounding participant addresses. Greenness-DNAmAgeAC associations were estimated using a within-sibship design fitted by linear mixed effect models, adjusting for familial clustering and important covariates.

RESULTS

Greenness metrics were associated with significantly lower DNAmAgeAC based on GrimAge acceleration, suggesting slower biological aging with higher greenness based on both NDVI and EVI in 300-2,000m buffer areas. For example, each interquartile range increase in NDVI within 1,000m was associated with a 0.59 (95% CI: 0.18, 1.01)-year decrease in GrimAge acceleration. Greenness was also inversely associated with three of the eight components of GrimAge, specifically, DNA methylation-based surrogates of serum cystatin-C, serum growth differentiation factor 15, and smoking pack years. Associations between greenness and biological aging measured by Horvath's and Hannum's DNAmAgeAC were less consistent, and depended on neighborhood socioeconomic status. No significant associations were estimated for PhenoAge acceleration.

DISCUSSION

Higher surrounding greenness was associated with slower biological aging, as indicated by GrimAge age acceleration, in Australian women. Associations were also evident for three individual components of GrimAge, but were inconsistent for other measures of biological aging. Additional studies are needed to confirm our results. https://doi.org/10.1289/EHP8793.

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study

Background

We previously investigated the association between 5 "first-generation" measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length.

Methods

We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity.

Results

We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively).

Conclusions

The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.