Blood DNA methylation age is not associated with cognitive functioning in middle-aged monozygotic twins

Epigenetic Aging Associations With Psychoneurological Symptoms and Social Functioning in Adults With Sickle Cell Disease

Objective: Sickle cell disease (SCD), the most common inherited blood disorder in the United States, is associated with severe psychoneurological symptoms. While epigenetic age acceleration has been linked to psychoneurological symptom burden in other diseases, this connection is unexplored in SCD. This study aimed to assess the association between epigenetic age acceleration and psychoneurological symptom burden in SCD. Methods: In this cross-sectional study, emotional impact, pain impact, sleep impact, social functioning, and cognitive function were assessed in 87 adults living with SCD. DNA methylation data were generated from blood specimens and used to calculate epigenetic age using five clocks (Horvath, Hannum, PhenoAge, GrimAge, & DunedinPACE). Associations between epigenetic age acceleration and symptoms were assessed. Results: The sample (N = 87) had a mean (SD) chronologic age was 30.6 (8.1) years. Epigenetic age acceleration was associated with several symptom outcomes. GrimAge age acceleration (β = -0.49, p = .03) and increased DunedinPACE (β = -2.23, p = .004) were associated with worse emotional impact scores. PhenoAge (β = -0.32, p = .04) and the GrimAge (β = -0.48, p = .05) age acceleration were associated with worse pain impact scores. Increased DunedinPACE (β = -2.07 p = .04) were associated with worse sleep impact scores. Increased DunedinPACE (β = -2.87, p = .005) was associated with worse social functioning scores. We did not find associations between epigenetic age acceleration and cognitive function in this sample. Conclusion: Epigenetic age acceleration was associated with worse symptom experiences, suggesting the potential for epigenetic age acceleration as a biomarker to aid in risk stratification or targets for intervention to mitigate symptom burden in SCD.

Accelerated epigenetic age is associated with whole-brain functional connectivity and impaired cognitive performance in older adults

While chronological age is a strong predictor for health-related risk factors, it is an incomplete metric that fails to fully characterize the unique aging process of individuals with different genetic makeup, neurodevelopment, and environmental experiences. Recent advances in epigenomic array technologies have made it possible to generate DNA methylation-based biomarkers of biological aging, which may be useful in predicting a myriad of cognitive abilities and functional brain network organization across older individuals. It is currently unclear which cognitive domains are negatively correlated with epigenetic age above and beyond chronological age, and it is unknown if functional brain organization is an important mechanism for explaining these associations. In this study, individuals with accelerated epigenetic age (i.e. AgeAccelGrim) performed worse on tasks that spanned a wide variety of cognitive faculties including both fluid and crystallized intelligence (N = 103, average age = 68.98 years, 73 females, 30 males). Additionally, fMRI connectome-based predictive models suggested a mediating mechanism of functional connectivity on epigenetic age acceleration-cognition associations primarily in medial temporal lobe and limbic structures. This research highlights the important role of epigenetic aging processes on the development and maintenance of healthy cognitive capacities and function of the aging brain.

Methylation Array Signals are Predictive of Chronological Age Without Bisulfite Conversion

DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. Here, we demonstrate how another hallmark of aging, genomic instability, influences methylation measurements in both bisulfite sequencing and methylation arrays. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.

Utility of DNA Methylation as a Biomarker in Aging and Alzheimer's Disease

Epigenetic mechanisms such as DNA methylation have been implicated in a number of diseases including cancer, heart disease, autoimmune disorders, and neurodegenerative diseases. While it is recognized that DNA methylation is tissue-specific, a limitation for many studies is the ability to sample the tissue of interest, which is why there is a need for a proxy tissue such as blood, that is reflective of the methylation state of the target tissue. In the last decade, DNA methylation has been utilized in the design of epigenetic clocks, which aim to predict an individual's biological age based on an algorithmically defined set of CpGs. A number of studies have found associations between disease and/or disease risk with increased biological age, adding weight to the theory of increased biological age being linked with disease processes. Hence, this review takes a closer look at the utility of DNA methylation as a biomarker in aging and disease, with a particular focus on Alzheimer's disease.

Epigenome-Wide Association Study in Peripheral Tissues Highlights DNA Methylation Profiles Associated with Episodic Memory Performance in Humans

The decline in episodic memory (EM) performance is a hallmark of cognitive aging and an early clinical sign in Alzheimer’s disease (AD). In this study, we conducted an epigenome-wide association study (EWAS) using DNA methylation (DNAm) profiles from buccal and blood samples for cross-sectional (n = 1019) and longitudinal changes in EM performance (n = 626; average follow-up time 5.4 years) collected under the auspices of the Lifebrain consortium project. The mean age of participants with cross-sectional data was 69 ± 11 years (30−90 years), with 50% being females. We identified 21 loci showing suggestive evidence of association (p < 1 × 10−5) with either or both EM phenotypes. Among these were SNCA, SEPW1 (both cross-sectional EM), ITPK1 (longitudinal EM), and APBA2 (both EM traits), which have been linked to AD or Parkinson’s disease (PD) in previous work. While the EM phenotypes were nominally significantly (p < 0.05) associated with poly-epigenetic scores (PESs) using EWASs on general cognitive function, none remained significant after correction for multiple testing. Likewise, estimating the degree of “epigenetic age acceleration” did not reveal significant associations with either of the two tested EM phenotypes. In summary, our study highlights several interesting candidate loci in which differential DNAm patterns in peripheral tissue are associated with EM performance in humans.

Assessing brain and biological aging trajectories associated with Alzheimer’s disease

The development of effective treatments to prevent and slow Alzheimer’s disease (AD) pathogenesis is needed in order to tackle the steady increase in the global prevalence of AD. This challenge is complicated by the need to identify key health shifts that precede the onset of AD and cognitive decline as these represent windows of opportunity for intervening and preventing disease. Such shifts may be captured through the measurement of biomarkers that reflect the health of the individual, in particular those that reflect brain age and biological age. Brain age biomarkers provide a composite view of the health of the brain based on neuroanatomical analyses, while biological age biomarkers, which encompass the epigenetic clock, provide a measurement of the overall health state of an individual based on DNA methylation analysis. Acceleration of brain and biological ages is associated with changes in cognitive function, as well as neuropathological markers of AD. In this mini-review, we discuss brain age and biological age research in the context of cognitive decline and AD. While more research is needed, studies show that brain and biological aging trajectories are variable across individuals and that such trajectories are non-linear at older ages. Longitudinal monitoring of these biomarkers may be valuable for enabling earlier identification of divergent pathological trajectories toward AD and providing insight into points for intervention.

Association of Pace of Aging Measured by Blood-Based DNA Methylation With Age-Related Cognitive Impairment and Dementia

BACKGROUND AND OBJECTIVES

DNA methylation algorithms are increasingly used to estimate biological aging; however, how these proposed measures of whole-organism biological aging relate to aging in the brain is not known. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Framingham Heart Study (FHS) Offspring Cohort to test the association between blood-based DNA methylation measures of biological aging and cognitive impairment and dementia in older adults.

METHODS

We tested 3 "generations" of DNA methylation age algorithms (first generation: Horvath and Hannum clocks; second generation: PhenoAge and GrimAge; and third generation: DunedinPACE, Dunedin Pace of Aging Calculated from the Epigenome) against the following measures of cognitive impairment in ADNI: clinical diagnosis of dementia and mild cognitive impairment, scores on Alzheimer disease (AD) / Alzheimer disease and related dementias (ADRD) screening tests (Alzheimer's Disease Assessment Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment), and scores on cognitive tests (Rey Auditory Verbal Learning Test, Logical Memory test, and Trail Making Test). In an independent replication in the FHS Offspring Cohort, we further tested the longitudinal association between the DNA methylation algorithms and the risk of developing dementia.

RESULTS

In ADNI (N = 649 individuals), the first-generation (Horvath and Hannum DNA methylation age clocks) and the second-generation (PhenoAge and GrimAge) DNA methylation measures of aging were not consistently associated with measures of cognitive impairment in older adults. By contrast, a third-generation measure of biological aging, DunedinPACE, was associated with clinical diagnosis of Alzheimer disease (beta [95% CI] = 0.28 [0.08-0.47]), poorer scores on Alzheimer disease/ADRD screening tests (beta [Robust SE] = -0.10 [0.04] to 0.08[0.04]), and cognitive tests (beta [Robust SE] = -0.12 [0.04] to 0.10 [0.03]). The association between faster pace of aging, as measured by DunedinPACE, and risk of developing dementia was confirmed in a longitudinal analysis of the FHS Offspring Cohort (N = 2,264 individuals, hazard ratio [95% CI] = 1.27 [1.07-1.49]).

DISCUSSION

Third-generation blood-based DNA methylation measures of aging could prove valuable for measuring differences between individuals in the rate at which they age and in their risk for cognitive decline, and for evaluating interventions to slow aging.

Epigenetic aging as a biomarker of dementia and related outcomes: a systematic review

Background: Biological aging may be a robust biomarker of dementia or cognitive performance. This systematic review synthesized the evidence for an association between epigenetic aging and dementia, mild cognitive impairment and cognitive function. Methods: A systematic search was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: 30 eligible articles were included. There was no strong evidence that accelerated epigenetic aging was associated with dementia/mild cognitive impairment (n = 7). There was some evidence of an association with poorer cognition (n = 20), particularly with GrimAge acceleration, but this was inconsistent and varied across cognitive domains. A meta-analysis was not performed due to high study heterogeneity. Conclusion: There is insufficient evidence to indicate that current epigenetic aging clocks can be clinically useful biomarkers of dementia or cognitive aging.

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer's Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer's disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.

Blood DNA methylation patterns in older adults with evolving dementia

Dementia and cognitive disorders are major aging-associated pathologies. The prevalence and severity of these conditions are influenced by both genetic and environmental factors. Reflecting this, epigenetic alterations have been associated with each of these processes, especially at the level of DNA methylation, and such changes may help explain the observed interindividual variability in the development of the 2 pathologies. However, the importance of epigenetic alterations in explaining their etiology is unclear because little is known about the timing of when they appear. Here, using Illumina MethylationEPIC arrays, we have longitudinally analyzed the peripheral blood methylomes of cognitively healthy older adults (>70 year), some of whom went on to develop dementia while others stayed healthy. We have characterized 34 individuals at the prediagnosis stage and at a 4-year follow-up in the postdiagnosis stage (total n = 68). Our results show multiple DNA methylation alterations linked to dementia status, particularly at the level of differentially methylated regions. These loci are associated with several dementia-related genes, including PON1, AP2A2, MAGI2, POT1, ITGAX, PACSIN1, SLC2A8, and EIF4E. We also provide validation of the previously reported epigenetic alteration of HOXB6 and PM20D1. Importantly, we show that most of these regions are already altered in the prediagnosis stage of individuals who go on to develop dementia. In conclusion, our observations suggest that dementia-associated epigenetic patterns that have specific biological features are already present before diagnosis, and thus may be important in the design of epigenetic biomarkers for disease detection based on peripheral tissues.

Many chronological aging clocks can be found throughout the epigenome: Implications for quantifying biological aging

Epigenetic alterations are a hallmark of aging and age-related diseases. Computational models using DNA methylation data can create "epigenetic clocks" which are proposed to reflect "biological" aging. Thus, it is important to understand the relationship between predictive clock sites and aging biology. To do this, we examined over 450,000 methylation sites from 9,699 samples. We found ~20% of the measured genomic cytosines can be used to make many different epigenetic clocks whose age prediction performance surpasses that of telomere length. Of these predictive sites, the average methylation change over a lifetime was small (~1.5%) and these sites were under-represented in canonical regions of epigenetic regulation. There was only a weak association between "accelerated" epigenetic aging and disease. We also compare tissue-specific and pan-tissue clock performance. This is critical to applying clocks both to new sample sets in basic research, as well as understanding if clinically available tissues will be feasible samples to evaluate "epigenetic aging" in unavailable tissues (e.g., brain). Despite the reproducible and accurate age predictions from DNA methylation data, these findings suggest they may have limited utility as currently designed in understanding the molecular biology of aging and may not be suitable as surrogate endpoints in studies of anti-aging interventions. Purpose-built clocks for specific tissues age ranges or phenotypes may perform better for their specific purpose. However, if purpose-built clocks are necessary for meaningful predictions, then the utility of clocks and their application in the field needs to be considered in that context.

In vivo biomarkers of structural and functional brain development and aging in humans

Brain aging is a major determinant of aging. Along with the aging population, prevalence of neurodegenerative diseases is increasing, therewith placing economic and social burden on individuals and society. Individual rates of brain aging are shaped by genetics, epigenetics, and prenatal environmental. Biomarkers of biological brain aging are needed to predict individual trajectories of aging and the risk for age-associated neurological impairments for developing early preventive and interventional measures. We review current advances of in vivo biomarkers predicting individual brain age. Telomere length and epigenetic clock, two important biomarkers that are closely related to the mechanistic aging process, have only poor deterministic and predictive accuracy regarding individual brain aging due to their high intra- and interindividual variability. Phenotype-related biomarkers of global cognitive function and brain structure provide a much closer correlation to age at the individual level. During fetal and perinatal life, autonomic activity is a unique functional marker of brain development. The cognitive and structural biomarkers also boast high diagnostic specificity for determining individual risks for neurodegenerative diseases.

Epigenetic Age Acceleration and Cognitive Decline: A Twin Study

BACKGROUND

Little is known about the role of DNA methylation (DNAm) epigenetic age acceleration in cognitive decline. Using a twin study design, we examined whether DNAm age acceleration is related to cognitive decline measured longitudinally in persons without a clinical diagnosis of dementia.

METHODS

We studied 266 paired male twins (133 pairs) with a mean age of 56 years at baseline. Of these, 114 paired twins returned for a follow-up after an average of 11.5 years. We obtained 6 indices of DNAm age acceleration based on epigenome-wide data from peripheral blood lymphocytes. At both baseline and follow-up, we administered a battery of cognitive measures and constructed 2 composite scores, one for executive function and one for memory function. We fitted multivariable mixed regression models to examine the association of DNAm age acceleration markers with cognitive function within pairs.

RESULTS

In cross-sectional analyses at baseline, there was no association between DNAm age acceleration and cognitive function scores. In longitudinal analyses, however, comparing twins within pairs, each additional year of age acceleration using the Horvath's method was associated with a 3% decline (95% CI, 1%-5%) in the composite executive function score and a 2.5% decline (95% CI, 0.01%-4.9%) in the memory function score. These results did not attenuate after adjusting for education and other risk factors.

CONCLUSIONS

Middle-aged men who had older DNAm age relative to their brothers of the same demographic age showed a faster rate of cognitive decline in the subsequent 11.5 years. These results point to the role of epigenetic modifications in cognitive aging.

Role of DNA Methylation in Mediating Genetic Risk of Psychiatric Disorders

Psychiatric disorders are common, complex, and heritable conditions estimated to be the leading cause of disability worldwide. The last decade of research in genomics of psychiatry, performed by multinational, and multicenter collaborative efforts on hundreds of thousands of mental disorder cases and controls, provided invaluable insight into the genetic risk variants of these conditions. With increasing cohort sizes, more risk variants are predicted to be identified in the near future, but there appears to be a knowledge gap in understanding how these variants contribute to the pathophysiology of psychiatric disorders. Majority of the identified common risk single-nucleotide polymorphisms (SNPs) are non-coding but are enriched in regulatory regions of the genome. It is therefore of great interest to study the impact of identified psychiatric disorders' risk SNPs on DNA methylation, the best studied epigenetic modification, playing a pivotal role in the regulation of transcriptomic processes, brain development, and functioning. This work outlines the mechanisms through which risk SNPs can impact DNA methylation levels and provides a summary of current evidence on the role of DNA methylation in mediating the genetic risk of psychiatric disorders.

A Systematic Review and Meta-analysis of Environmental, Lifestyle, and Health Factors Associated With DNA Methylation Age

DNA methylation (DNAm) algorithms of biological age provide a robust estimate of an individual's chronological age and can predict their risk of age-related disease and mortality. This study reviewed the evidence that environmental, lifestyle and health factors are associated with the Horvath and Hannum epigenetic clocks. A systematic search identified 61 studies. Chronological age was correlated with DNAm age in blood (median .83, range .13-.99). In a meta-analysis body mass index (BMI) was associated with increased DNAm age (Hannum β: 0.07, 95% CI 0.04 to 0.10; Horvath β: 0.06, 95% CI 0.02 to 0.10), but there was no association with smoking (Hannum β: 0.12, 95% CI -0.50 to 0.73; Horvath β:0.18, 95% CI -0.10 to 0.46). DNAm age was positively associated with frailty (three studies, n = 3,093), and education was negatively associated with the Hannum estimate of DNAm age specifically (four studies, n = 13,955). For most other exposures, findings were too inconsistent to draw conclusions. In conclusion, BMI was positively associated with biological aging measured using DNAm, with some evidence that frailty also increased aging. More research is needed to provide conclusive evidence regarding other exposures. This field of research has the potential to provide further insights into how to promote slower biological aging and ultimately prolong healthy life.

Epigenetic Age Acceleration and Cognitive Function in African American Adults in Midlife: The Atherosclerosis Risk in Communities Study

Methylation levels measured at defined sites across the genome have recently been shown to be correlated with an individual's chronological age. Age acceleration, or the difference between age estimated from DNA methylation status and chronological age, has been proposed as a novel biomarker of aging. In this study, the cross-sectional association between two different measures of age acceleration and cognitive function was investigated using whole blood samples from 2,157 African American participants 47-70 years of age in the population-based Atherosclerosis Risk in Communities (ARIC) Study. Cognition was evaluated using three domain-specific tests. A significant inverse association between a 1-year increase in age acceleration calculated using a blood-based age predictor and scores on the Word Fluency Test was found using a general linear model adjusted for chronological age, gender, and years of education (β = -0.140 words; p = .001) and after adding other potential confounding variables (β = -0.104 words, p = .023). The results were replicated in 1,670 European participants in the Generation Scotland: Scottish Family Health Study (fully adjusted model: β = -0.199 words; p = .034). A significant association was also identified in a trans-ethnic meta-analysis across cohorts that included an additional 708 European American ARIC study participants (fully adjusted model: β = -0.110 words, p = .003). There were no associations found using an estimate of age acceleration derived from multiple tissues. These findings provide evidence that age acceleration is a correlate of performance on a test of verbal fluency in middle-aged adults.

DNA Methylation Age and Physical and Cognitive Aging

BACKGROUND

DNA methylation (DNAm) age acceleration (AgeAccel) has been shown to be predictive of all-cause mortality but it is unclear what functional aspect(s) of aging it captures. We examine associations between four measures of AgeAccel in adults aged 45-87 years and physical and cognitive performance and their age-related decline.

METHODS

AgeAccelHannum, AgeAccelHorvath, AgeAccelPheno, and AgeAccelGrim were calculated in the Medical Research Council National Survey of Health and Development (NSHD), National Child Development Study (NCDS) and TwinsUK. Three measures of physical (grip strength, chair rise speed, and forced expiratory volume in one second [FEV1]) and two measures of cognitive (episodic memory and mental speed) performance were assessed.

RESULTS

AgeAccelPheno and AgeAccelGrim, but not AgeAccelHannum and AgeAccelHorvath were related to performance in random effects meta-analyses (n = 1,388-1,685). For example, a 1-year increase in AgeAccelPheno or AgeAccelGrim was associated with a 0.01 mL (95% confidence interval [CI]: 0.01, 0.02) or 0.03 mL (95% CI: 0.01, 0.05) lower mean FEV1 respectively. In NSHD, AgeAccelPheno and AgeAccelGrim at 53 years were associated with age-related decline in performance between 53 and 69 years as tested by linear mixed models (p < .05). In a subset of NSHD participants (n = 482), there was little evidence that change in any AgeAccel measure was associated with change in performance conditional on baseline performance.

CONCLUSIONS

We found little evidence to support associations between the first generation of DNAm-based biomarkers of aging and age-related physical or cognitive performance in midlife to early old age. However, there was evidence that the second generation biomarkers, AgeAccelPheno and AgeAccelGrim, could act as makers of an individual's healthspan as proposed.

Accelerated epigenetic age and cognitive decline among urban-dwelling adults

OBJECTIVES

Epigenetic modifications are closely linked with aging, but their relationship with cognition remains equivocal. Given known sex differences in epigenetic aging, we explored sex-specific associations of 3 DNA methylation (DNAm)-based measures of epigenetic age acceleration (EAA) with baseline and longitudinal change in cognitive performance among middle-aged urban adults.

METHODS

We used exploratory data from a subgroup of participants in the Healthy Aging in Neighborhoods of Diversity across the Life Span study with complete DNA samples and whose baseline ages were >50.0 years (2004-2009) to estimate 3 DNAm EAA measures: (1) universal EAA (AgeAccel); (2) intrinsic EAA (IEAA); and (3) extrinsic EAA (EEAA). Cognitive performance was measured at baseline visit (2004-2009) and first follow-up (2009-2013) with 11 test scores covering global mental status and specific domains such as learning/memory, attention, visuospatial, psychomotor speed, language/verbal, and executive function. A series of mixed-effects regression models were conducted adjusting for covariates and multiple testing (n = 147-156, ∼51% men, k = 1.7-1.9 observations/participant, mean follow-up time ∼4.7 years).

RESULTS

EEAA, a measure of both biological age and immunosenescence, was consistently associated with greater cognitive decline among men on tests of visual memory/visuoconstructive ability (Benton Visual Retention Test: γ₁₁ = 0.0512 ± 0.0176, p = 0.004) and attention/processing speed (Trail-Making Test, part A: γ₁₁ = 0.219 ± 0.080, p = 0.007). AgeAccel and IEAA were not associated with cognitive change in this sample.

CONCLUSIONS

EEAA capturing immune system cell aging was associated with faster decline among men in domains of attention and visual memory. Larger longitudinal studies are needed to replicate our findings.

Association between epigenetic age acceleration and depressive symptoms in a prospective cohort study of urban-dwelling adults

OBJECTIVE

This study tests associations of DNA methylation-based (DNAm) measures of epigenetic age acceleration (EAA) with cross-sectional and longitudinal depressive symptoms in an urban sample of middle-aged adults.

METHODS

White and African-American adult participants in the Healthy Aging in Neighborhoods of Diversity across the Life Span study for whom DNA samples were analyzed (baseline age: 30-65 years) we included. We estimated three DNAm based EAA measures: (1) universal epigenetic age acceleration (AgeAccel); (2) intrinsic epigenetic age acceleration (IEAA); and (3) extrinsic epigenetic age acceleration (EEAA). Depressive symptoms were assessed using the 20-item Center for Epidemiological Studies-Depression scale total and sub-domain scores at baseline (2004-2009) and follow-up visits (2009-2013). Linear mixed-effects regression models were conducted, adjusting potentially confounding covariates, selection bias and multiple testing (N = 329 participants, ∼52% men, k = 1.9 observations/participant, mean follow-up time∼4.7 years).

RESULTS

None of the epigenetic age acceleration measures were associated with total depressive symptom scores at baseline or over time. IEAA - a measure of cellular epigenetic age acceleration irrespective of white blood cell composition - was cross-sectionally associated with decrement in "positive affect" in the total population (γ₀₁₁± SE = -0.090 ± 0.030, P = 0.003, Cohen's D: -0.16) and among Whites (γ₀₁₁ ± SE = -0.135 ± 0.048, P = 0.005, Cohen's D: -0.23), after correction for multiple testing. Baseline "positive affect" was similarly associated with AgeAccel.

LIMITATIONS

Limitations included small sample size, weak-moderate effects and measurement error.

CONCLUSIONS

IEAA and AgeAccel, two measures of EAA using Horvath algorithm, were linked to a reduced "positive affect", overall and among Whites. Future studies are needed to replicate our findings and test bi-directional relationships.

Epigenome-wide association study of depression symptomatology in elderly monozygotic twins

Depression is a severe and debilitating mental disorder diagnosed by evaluation of affective, cognitive and physical depression symptoms. Severity of these symptoms strongly impacts individual's quality of life and is influenced by a combination of genetic and environmental factors. One of the molecular mechanisms allowing for an interplay between these factors is DNA methylation, an epigenetic modification playing a pivotal role in regulation of brain functioning across lifespan. The aim of this study was to investigate if there are DNA methylation signatures associated with depression symptomatology in order to identify molecular mechanisms contributing to pathophysiology of depression. We performed an epigenome-wide association study (EWAS) of continuous depression symptomatology score measured in a cohort of 724 monozygotic Danish twins (346 males, 378 females). Through EWAS analyses adjusted for sex, age, flow-cytometry based blood cell composition, and twin relatedness structure in the data we identified depression symptomatology score to be associated with blood DNA methylation levels in promoter regions of neuropsin (KLK8, p-value = 4.7 × 10^-7) and DAZ associated protein 2 (DAZAP2, p-value = 3.13 × 10^-8) genes. Other top associated probes were located in gene bodies of MAD1L1 (p-value = 5.16 × 10^-6), SLC29A2 (p-value = 6.15 × 10^-6) and AKT1 (p-value = 4.47 × 10^-6), all genes associated before with development of depression. Additionally, the following three measures (a) DNAmAge (calculated with Horvath and Hannum epigenetic clock estimators) adjusted for chronological age, (b) difference between DNAmAge and chronological age, and (c) DNAmAge acceleration were not associated with depression symptomatology score in our cohort. In conclusion, our data suggests that depression symptomatology score is associated with DNA methylation levels of genes implicated in response to stress, depressive-like behaviors, and recurrent depression in patients, but not with global DNA methylation changes across the genome.

DNA Methylation Age-Environmental Influences, Health Impacts, and Its Role in Environmental Epidemiology

PURPOSE OF REVIEW

DNA methylation-based aging biomarkers are valuable tools for evaluating the aging process from a molecular perspective. These epigenetic aging biomarkers can be evaluated across the lifespan and are tissue specific. This review examines the literature relating environmental exposures to DNA methylation-based aging biomarkers and also the literature evaluating these biomarkers as predictors of health outcomes.

RECENT FINDINGS

Multiple studies evaluated the association between air pollution and DNA methylation age and consistently observed that higher exposures are associated with elevated DNA methylation age. Psychosocial exposures, e.g., traumas and adolescent adversity, and infections are also associated with epigenetic aging. DNA methylation age has been repeatedly associated with mortality, cancer, and cognitive impairment. DNA methylation age is responsive to the environment and predictive of health outcomes. Studies are still needed to evaluate whether DNA methylation age acts as a mediator or modifier of environmental health effects and to understand the impact of factors such as race, gender, and genetics.

The epigenetic clock as a predictor of disease and mortality risk: a systematic review and meta-analysis

BACKGROUND

Ageing is one of the principal risk factors for many chronic diseases. However, there is considerable between-person variation in the rate of ageing and individual differences in their susceptibility to disease and death. Epigenetic mechanisms may play a role in human ageing, and DNA methylation age biomarkers may be good predictors of age-related diseases and mortality risk. The aims of this systematic review were to identify and synthesise the evidence for an association between peripherally measured DNA methylation age and longevity, age-related disease, and mortality risk.

METHODS

A systematic search was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Using relevant search terms, MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsychINFO databases were searched to identify articles meeting the inclusion criteria. Studies were assessed for bias using Joanna Briggs Institute critical appraisal checklists. Data was extracted from studies measuring age acceleration as a predictor of age-related diseases, mortality or longevity, and the findings for similar outcomes compared. Using Review Manager 5.3 software, two meta-analyses (one per epigenetic clock) were conducted on studies measuring all-cause mortality.

RESULTS

Twenty-three relevant articles were identified, including a total of 41,607 participants. Four studies focused on ageing and longevity, 11 on age-related disease (cancer, cardiovascular disease, and dementia), and 11 on mortality. There was some, although inconsistent, evidence for an association between increased DNA methylation age and risk of disease. Meta-analyses indicated that each 5-year increase in DNA methylation age was associated an 8 to 15% increased risk of mortality.

CONCLUSION

Due to the small number of studies and heterogeneity in study design and outcomes, the association between DNA methylation age and age-related disease and longevity is inconclusive. Increased epigenetic age was associated with mortality risk, but positive publication bias needs to be considered. Further research is needed to determine the extent to which DNA methylation age can be used as a clinical biomarker.

Exploration of unsupervised feature selection methods to predict chronological age of individuals by utilising CpG dinucleotics from whole blood

Identification of the age of individuals from epigenetic biomarkers can reveal vital information for criminal investigation, disease prevention, and extension of life. DNA methylation changes are highly associated with chronological age and the process of disease development. Computational methods such as clustering, feature selection and regression can be utilised to construct quantitative model of aging. In this study, we utilised 473034 CpG biomarkers from whole blood of 656 individuals aged 19 to 101 to construct predictive models and we treat the development of this age predictive model as extremely high-dimensional regression problem that is relatively understudied. Unlike semi-supervised and supervised feature selection methods, unsupervised feature selection methods are generally good at removing irrelevant features that can act as noise. In this study, along with the entire feature set, four different unsupervised feature selection methods (USFSMs) are therefore considered for the quantitative prediction of human ages. Since USFSMs are independent of any predictive method, support vector regression is then used to evaluate the prediction performances of the unsupervised feature selection methods. We proposed a novel k-means based unsupervised feature selection method to predict human ages by utilising CpG dinucleotides. Experimental results have validated the effectiveness of the proposed method as the optimum number of the CpG dinucleotides is found to be only 41 that corresponds to only 0.0087% of the entire feature space. To the best of our knowledge, this is the first study that presents exploration and comprehensive comparison of USFSMs in very high dimensional regression problems, particularly in epigenetic biomedical domain for the prediction of chronological age from changes in DNA methylation.

Peripheral DNA methylation, cognitive decline and brain aging: pilot findings from the Whitehall II imaging study

Aim:

The present study investigated the link between peripheral DNA methylation (DNAm), cognitive impairment and brain aging.

Methods:

We tested the association between blood genome-wide DNAm profiles using the Illumina 450K arrays, cognitive dysfunction and brain MRI measures in selected participants of the Whitehall II imaging sub-study.

Results:

Eight differentially methylated regions were associated with cognitive impairment. Accelerated aging based on the Hannum epigenetic clock was associated with mean diffusivity and global fractional anisotropy. We also identified modules of co-methylated loci associated with white matter hyperintensities. These co-methylation modules were enriched among pathways relevant to β-amyloid processing and glutamatergic signaling.

Conclusion:

Our data support the notion that blood DNAm changes may have utility as a biomarker for cognitive dysfunction and brain aging.

Back to the future: Epigenetic clock plasticity towards healthy aging

Aging is the most important risk factor for major human lifestyle diseases, including cancer, neurological and cardiometabolic disorders. Due to the complex interplay between genetics, lifestyle and environmental factors, some individuals seem to age faster than others, whereas centenarians seem to have a slower aging process. Therefore, a biochemical biomarker reflecting the relative biological age would be helpful to predict an individual's health status and aging disease risk. Although it is already known for years that cumulative epigenetic changes occur upon aging, DNA methylation patterns were only recently used to construct an epigenetic clock predictor for biological age, which is a measure of how well your body functions compared to your chronological age. Moreover, the epigenetic DNA methylation clock signature is increasingly applied as a biomarker to estimate aging disease susceptibility and mortality risk. Finally, the epigenetic clock signature could be used as a lifestyle management tool to monitor healthy aging, to evaluate preventive interventions against chronic aging disorders and to extend healthy lifespan. Dissecting the mechanism of the epigenetic aging clock will yield valuable insights into the aging process and how it can be manipulated to improve health span.

DNA methylation age and perceived age in elderly Danish twins

Perceived age is an easily accessible biomarker of aging. Here, we studied its relation to DNA methylation age (DNAm age) as introduced in (Horvath, 2013) in 180 elderly Danish twins. We found perceived age and DNAm age to be associated with chronological age (P=0.04 resp. P=2.2e-10) when correcting for gender, but did not see an association between perceived age and DNAm age (P=0.44). Intrapair-analysis showed that the proportion of pairs where the twin with the highest perceived age also had the highest DNAm age was not different from 0.5 (P=1), and we did not see a trend when dividing pairs according to their difference in perceived age (P=0.36). Hence, intrapair analysis did not reveal links between perceived age and DNAm age. Moreover, none of the 353 CpGs underlying DNAm age was individually associated with perceived age after correction for multiple-testing (P>6e-4, FDR>0.21). Finally, when constructing an epigenetic signature based on these CpGs to predict perceived age, we only found a correlation of 0.18 (95%CI: -0.06 to 0.40) and a mean square error of 13.6 years2 between observed and predicted values in the test dataset, indicating poor predictive strength. Altogether, our results suggest that perceived age and DNAm age capture different aging aspects.

Are objective measures of physical capability related to accelerated epigenetic age? Findings from a British birth cohort

OBJECTIVES

Our aim was to investigate the association of epigenetic age and physical capability in later life. Having a higher epigenetic than chronological age (known as age acceleration (AA)) has been found to be associated with an increased rate of mortality. Similarly, physical capability has been proposed as a marker of ageing due to its consistent associations with mortality.

SETTING

The MRC National Survey of Health and Development (NSHD) cohort study.

PARTICIPANTS

We used data from 790 women from the NSHD who had DNA methylation data available.

DESIGN

Epigenetic age was calculated using buccal cell (n=790) and matched blood tissue (n=152) from 790 female NSHD participants. We investigated the association of AA at age 53 with changes in physical capability in women from ages 53 to 60-64. Regression models of change in each measure of physical capability on AA were conducted. Secondary analysis focused on the relationship between AA and smoking, alcohol, body mass index (BMI) and socioeconomic position.

OUTCOME MEASURES

Three objective measures of physical capability were used: grip strength, standing balance time and chair rise speed.

RESULTS

Epigenetic age was lower than chronological age (mean 53.4) for both blood (50.3) and buccal cells (42.8). AA from blood was associated with a greater decrease in grip strength from ages 53 to 60-64 (0.42 kg decrease per year of AA, 95% CI 0.03, 0.82 kg; p=0.03, n=152), but no associations were observed with standing balance time or chair rise speed. Current smoking and lower BMI were associated with lower epigenetic age from buccal cells.

CONCLUSIONS

We found evidence that AA in blood is associated with a greater decrease in grip strength in British females aged between 53 and 60-64, but no association with standing balance time or chair rise speed was found.

Biological Age Predictors

The search for reliable indicators of biological age, rather than chronological age, has been ongoing for over three decades, and until recently, largely without success. Advances in the fields of molecular biology have increased the variety of potential candidate biomarkers that may be considered as biological age predictors. In this review, we summarize current state-of-the-art findings considering six potential types of biological age predictors: epigenetic clocks, telomere length, transcriptomic predictors, proteomic predictors, metabolomics-based predictors, and composite biomarker predictors. Promising developments consider multiple combinations of these various types of predictors, which may shed light on the aging process and provide further understanding of what contributes to healthy aging. Thus far, the most promising, new biological age predictor is the epigenetic clock; however its true value as a biomarker of aging requires longitudinal confirmation.

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Telomere length is the most well studied biological age predictor, but many new predictors are emerging.

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The epigenetic clock is currently the best biological age predictor, as it correlates well with age and predicts mortality.

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The various biological age predictors tend to reflect different aspects of the aging process.