Increased epigenetic age and granulocyte counts in the blood of Parkinson's disease patients

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 clocks reveal a rejuvenation event during embryogenesis followed by aging

The notion that the germ line does not age goes back to the 19th-century ideas of August Weismann. However, being metabolically active, the germ line accumulates damage and other changes over time, i.e., it ages. For new life to begin in the same young state, the germ line must be rejuvenated in the offspring. Here, we developed a multi-tissue epigenetic clock and applied it, together with other aging clocks, to track changes in biological age during mouse and human prenatal development. This analysis revealed a significant decrease in biological age, i.e., rejuvenation, during early stages of embryogenesis, followed by an increase in later stages. We further found that pluripotent stem cells do not age even after extensive passaging and that the examined epigenetic age dynamics is conserved across species. Overall, this study uncovers a natural rejuvenation event during embryogenesis and suggests that the minimal biological age (ground zero) marks the beginning of organismal aging.

Human methylome variation across Infinium 450K data on the Gene Expression Omnibus

While DNA methylation (DNAm) is the most-studied epigenetic mark, few recent studies probe the breadth of publicly available DNAm array samples. We collectively analyzed 35 360 Illumina Infinium HumanMethylation450K DNAm array samples published on the Gene Expression Omnibus. We learned a controlled vocabulary of sample labels by applying regular expressions to metadata and used existing models to predict various sample properties including epigenetic age. We found approximately two-thirds of samples were from blood, one-quarter were from brain and one-third were from cancer patients. About 19% of samples failed at least one of Illumina's 17 prescribed quality assessments; signal distributions across samples suggest modifying manufacturer-recommended thresholds for failure would make these assessments more informative. We further analyzed DNAm variances in seven tissues (adipose, nasal, blood, brain, buccal, sperm and liver) and characterized specific probes distinguishing them. Finally, we compiled DNAm array data and metadata, including our learned and predicted sample labels, into database files accessible via the recountmethylation R/Bioconductor companion package. Its vignettes walk the user through some analyses contained in this paper.

Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders

BACKGROUND

People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease.

RESULTS

We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson's disease (and none with Alzheimer's disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights.

CONCLUSIONS

We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.

Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex

Human DNA methylation data have been used to develop biomarkers of ageing, referred to as ‘epigenetic clocks’, which have been widely used to identify differences between chronological age and biological age in health and disease including neurodegeneration, dementia and other brain phenotypes. Existing DNA methylation clocks have been shown to be highly accurate in blood but are less precise when used in older samples or in tissue types not included in training the model, including brain. We aimed to develop a novel epigenetic clock that performs optimally in human cortex tissue and has the potential to identify phenotypes associated with biological ageing in the brain. We generated an extensive dataset of human cortex DNA methylation data spanning the life course (n = 1397, ages = 1 to 108 years). This dataset was split into ‘training’ and ‘testing’ samples (training: n = 1047; testing: n = 350). DNA methylation age estimators were derived using a transformed version of chronological age on DNA methylation at specific sites using elastic net regression, a supervised machine learning method. The cortical clock was subsequently validated in a novel independent human cortex dataset (n = 1221, ages = 41 to 104 years) and tested for specificity in a large whole blood dataset (n = 1175, ages = 28 to 98 years). We identified a set of 347 DNA methylation sites that, in combination, optimally predict age in the human cortex. The sum of DNA methylation levels at these sites weighted by their regression coefficients provide the cortical DNA methylation clock age estimate. The novel clock dramatically outperformed previously reported clocks in additional cortical datasets. Our findings suggest that previous associations between predicted DNA methylation age and neurodegenerative phenotypes might represent false positives resulting from clocks not robustly calibrated to the tissue being tested and for phenotypes that become manifest in older ages. The age distribution and tissue type of samples included in training datasets need to be considered when building and applying epigenetic clock algorithms to human epidemiological or disease cohorts.

A geroscience approach for Parkinson's disease: Conceptual framework and design of PROPAG-AGEING project

Advanced age is the major risk factor for idiopathic Parkinson's disease (PD), but to date the biological relationship between PD and ageing remains elusive. Here we describe the rationale and the design of the H2020 funded project "PROPAG-AGEING", whose aim is to characterize the contribution of the ageing process to PD development. We summarize current evidences that support the existence of a continuum between ageing and PD and justify the use of a Geroscience approach to study PD. We focus in particular on the role of inflammaging, the chronic, low-grade inflammation characteristic of elderly physiology, which can propagate and transmit both locally and systemically. We then describe PROPAG-AGEING design, which is based on the multi-omic characterization of peripheral samples from clinically characterized drug-naïve and advanced PD, PD discordant twins, healthy controls and "super-controls", i.e. centenarians, who never showed clinical signs of motor disability, and their offspring. Omic results are then validated in a large number of samples, including in vitro models of dopaminergic neurons and healthy siblings of PD patients, who are at higher risk of developing PD, with the final aim of identifying the molecular perturbations that can deviate the trajectories of healthy ageing towards PD development.

Aging and rejuvenation - a modular epigenome model

The view of aging has evolved in parallel with the advances in biomedical sciences. Long considered as an irreversible process where interventions were only aimed at slowing down its progression, breakthrough discoveries like animal cloning and cell reprogramming have deeply changed our understanding of postnatal development, giving rise to the emerging view that the epigenome is the driver of aging. The idea was significantly strengthened by the converging discovery that DNA methylation (DNAm) at specific CpG sites could be used as a highly accurate biomarker of age defined by an algorithm known as the Horvath clock. It was at this point where epigenetic rejuvenation came into play as a strategy to reveal to what extent biological age can be set back by making the clock tick backwards. Initial evidence suggests that when the clock is forced to tick backwards in vivo, it is only able to drag the phenotype to a partially rejuvenated condition. In order to explain the results, a bimodular epigenome is proposed, where module A represents the DNAm clock component and module B the remainder of the epigenome. Epigenetic rejuvenation seems to hold the key to arresting or even reversing organismal aging.

Differential blood DNA methylation across Lewy body dementias

INTRODUCTION

Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) are characterized by cognitive alterations, visual hallucinations, and motor impairment. Diagnosis is based on type and timing of clinical manifestations; however, determination of clinical subtypes is challenging. The utility of blood DNA methylation as a biomarker for Lewy body disorders (LBD) is mostly unexplored.

METHODS

We performed a cross-sectional analysis of blood methylation in 42 DLB and 50 PDD cases applying linear models to compare groups and logistic least absolute shrinkage and selection operator regression to explore the discriminant power of methylation signals.

RESULTS

DLB blood shows differential methylation compared to PDD. Some methylation changes associate with core features of LBD. Sets of probes show high predictive value to discriminate between variants.

DISCUSSION

Our study is the first to explore LBD blood methylation. Despite overlapping clinical presentation, we detected differential epigenetic signatures that, if confirmed in independent cohorts, could be developed into useful biomarkers.

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.

Biological aging in schizophrenia and psychosis severity: DNA methylation analysis

The physiological changes associated with normal aging are known to occur earlier in individuals with schizophrenia (SCZ). One of the phenomena linked with normal aging is the change in patterns of epigenetic modifications. We recruited 138 individuals with SCZ spectrum disorders and extracted DNA from white blood cells. The combinations of pre-selected DNA methylation sites were utilized to estimate the 'methylation age' (DNAm age) and evaluate evidence of epigenetic age acceleration. We investigated the correlation between the epigenetic age acceleration measures and psychosis severity; furthermore, we estimated blood cell counts based on DNA methylation levels. The extrinsic epigenetic age acceleration showed a significant correlation with the Brief Psychiatric Rating Scale (BPRS) disorganization subscale(r=0.222, p=0.039).Both Horvath age acceleration and Hannum age acceleration showed a significant correlation (r=0.221, p=0.029; r=0.242, p=0.017 respectively) with the Symptom Checklist 90 (SCL-90) psychotic domain. Overall, this study shows some evidence of epigenetic age acceleration associated with psychosis severity using two different algorithms for DNAm age analysis.

Epigenetic Clock Analysis in Children With Fetal Alcohol Spectrum Disorder

BACKGROUND

Fetal alcohol spectrum disorder (FASD) is characterized by severe clinical impairment, considerable social burden, and high mortality and morbidity, which are due to various malformations, sepsis, and cancer. As >50% of deaths from FASD occur during the first year of life, we hypothesized that there is the acceleration of biological aging in FASD. Several recent studies have established genome-wide DNA methylation (DNAm) profiles as "epigenetic clocks" that can estimate biological aging, and FASD has been associated with differential DNAm patterns. Therefore, we tested this hypothesis using epigenetic clocks.

METHODS

We investigated 5 DNAm-based measures of epigenetic age (HorvathAge, HannumAge, SkinBloodAge, PhenoAge, and GrimAge) and telomere length (DNAmTL) using 4 independent publicly available DNAm datasets; 2 datasets were derived from buccal epithelium, and the other 2 datasets were derived from peripheral blood.

RESULTS

Compared with controls, children with FASD exhibited an acceleration of GrimAge in 1 buccal and 2 blood datasets. No significant difference was found in other DNAm ages and DNAmTL. Meta-analyses showed a significant acceleration of GrimAge in the blood samples but not in the buccal samples.

CONCLUSIONS

This study provides novel evidence regarding accelerated epigenetic aging in children with FASD.

Early-Onset Alzheimer's Disease: What Is Missing in Research?

PURPOSE OF REVIEW

Early-onset Alzheimer's disease (EOAD), defined as Alzheimer's disease (AD) occurring before age 65, is significantly less well studied than the late-onset form (LOAD) despite EOAD often presenting with a more aggressive disease progression. The aim of this review is to summarize the current understanding of the etiology of EOAD, their translation into clinical practice, and to suggest steps to be taken to move our understanding forward.

RECENT FINDINGS

EOAD cases make up 5-10% of AD cases but only 10-15% of these cases show known mutations in the APP, PSEN1, and PSEN2, which are linked to EOAD. New data suggests that these unexplained cases following a non-Mendelian pattern of inheritance is potentially caused by a mix of common and newly discovered rare variants. However, only a fraction of this genetic variation has been identified to date leaving the molecular mechanisms underlying this type of AD and their association with clinical, biomarker, and neuropathological changes unclear. While great advancements have been made in characterizing EOAD, much work is needed to disentangle the molecular mechanisms underlying this type of AD and to identify putative targets for more precise disease screening, diagnosis, prevention, and treatment.

DNA methylation age as a biomarker for cancer

Cancer is well established as an age-associated disease, and there is substantial overlap in the molecular, cellular and physiological changes observed with both ageing and the progression of cancer. Age-specific declines in resilience mechanisms such as DNA repair or epigenetic maintenance may contribute to the development of cancer. These declines may be assessed through biomarkers that measure biological age and through the related concept of "age acceleration". Epigenetic clocks, assessed through DNA methylation levels, are among the most widely used biological age markers in cancer studies. In this review, we discuss the use of DNA methylation ageing measures to predict population cancer incidence, mortality and survival. Blood-based DNA methylation age estimators appear to be promising measures of increased cancer risk and mortality, although their reported effects are generally weak, thus its clinical relevance remains to be validated in large case-cohort and longitudinal studies. Future development of epigenetic and other biological age biomarkers will likely further elucidate the links between ageing and cancer.

Advancing Food Allergy Through Omics Sciences

Since the publication of the first draft of the human genome, there has been an explosion of new technologies with increasing power to interrogate the totality of biological molecules (eg, DNA, RNA, proteins, metabolites) and their modifications (eg, DNA methylation, histone modifications). These technologies, collectively called omics, have been widely applied in the last 2 decades to study biological systems to gain deeper insight into mechanisms driving the physiology and pathophysiology of human health and disease. Because of its complex, multifactorial nature, food allergy is especially well suited to be investigated using omics approaches. In this rostrum, we review how omic technologies have been applied to explore diverse aspects of food allergy, including adaptive and innate immune processes in food-allergic responses, the role of the microbiome in food allergy risk, metabolic changes in the gut and blood associated with food allergy, and the identification of biomarkers and potential therapeutic targets for the condition. We discuss the strengths and limitations of the studies performed thus far and the need to adopt systems biology approaches that integrate data from multiple omics to fully leverage the potential of these technologies to advance food allergy research and care.

DNA methylation-based biomarkers of age acceleration and all-cause death, myocardial infarction, stroke, and cancer in two cohorts: The NAS, and KORA F4

Background

DNA methylation (DNAm) may play a role in age-related outcomes. It is not yet known which DNAm-based biomarkers of age acceleration (BoAA) has the strongest association with age-related endpoints.

Methods

We collected the blood samples from two independent cohorts: the Normative Ageing Study, and the Cooperative Health Research in the Region of Augsburg cohort. We measured epigenome-wide DNAm level, and generated five DNAm BoAA at baseline. We used Cox proportional hazards model to analyze the relationships between BoAA and all-cause death. We applied the Fine and Gray competing risk model to estimate the risk of BoAA on myocardial infarction (MI), stroke, and cancer, accounting for death of other reasons as the competing risks. We used random-effects meta-analyses to pool the individual results, with adjustment for multiple testing.

Findings

The mean chronological ages in the two cohorts were 74, and 61, respectively. Baseline GrimAgeAccel, and DNAm-related mortality risk score (DNAmRS) both had strong associations with all-cause death, MI, and stroke, independent from chronological age. For example, a one standard deviation (SD) increment in GrimAgeAccel was significantly associated with increased risk of all-cause death [hazard ratio (HR): 2.01; 95% confidence interval (CI), 1.15, 3.50], higher risk of MI (HR: 1.44; 95% CI, 1.16, 1.79), and elevated risk of stroke (HR: 1.42; 95% CI, 1.06, 1.91). There were no associations between any BoAA and cancer.

Interpretation

From the public health perspective, GrimAgeAccel is the most useful tool for identifying at-risk elderly, and evaluating the efficacy of anti-aging interventions.

Funding

National Institute of Environmental Health Sciences of U.S., Harvard Chan-NIEHS Center for Environmental Health, German Federal Ministry of Education and Research, and the State of Bavaria in Germany.

Promising biomarkers of human aging: In search of a multi-omics panel to understand the aging process from a multidimensional perspective

The aging process has been linked to the occurrence of chronic diseases and functional impairments, including cancer, sarcopenia, frailty, metabolic, cardiovascular, and neurodegenerative diseases. Nonetheless, aging is highly variable and heterogeneous and represents a challenge for its characterization. In this sense, intrinsic capacity (IC) stands as a novel perspective by the World Health Organization, which integrates the individual wellbeing, environment, and risk factors to understand aging. However, there is a lack of quantitative and qualitative attributes to define it objectively. Therefore, in this review we attempt to summarize the most relevant and promising biomarkers described in clinical studies at date over different molecular levels, including epigenomics, transcriptomics, proteomics, metabolomics, and the microbiome. To aid gerontologists, geriatricians, and biomedical researchers to understand the aging process through the IC. Aging biomarkers reflect the physiological state of individuals and the underlying mechanisms related to homeostatic changes throughout an individual lifespan; they demonstrated that aging could be measured independently of time (that may explain its heterogeneity) and to be helpful to predict age-related syndromes and mortality. In summary, we highlight the areas of opportunity and gaps of knowledge that must be addressed to fully integrate biomedical findings into clinically useful tools and interventions.

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.

Prediction of Lung Function in Adolescence Using Epigenetic Aging: A Machine Learning Approach

Epigenetic aging has been found to be associated with a number of phenotypes and diseases. A few studies have investigated its effect on lung function in relatively older people. However, this effect has not been explored in the younger population. This study examines whether lung function in adolescence can be predicted with epigenetic age accelerations (AAs) using machine learning techniques. DNA methylation based AAs were estimated in 326 matched samples at two time points (at 10 years and 18 years) from the Isle of Wight Birth Cohort. Five machine learning regression models (linear, lasso, ridge, elastic net, and Bayesian ridge) were used to predict FEV₁ (forced expiratory volume in one second) and FVC (forced vital capacity) at 18 years from feature selected predictor variables (based on mutual information) and AA changes between the two time points. The best models were ridge regression (R² = 75.21% ± 7.42%; RMSE = 0.3768 ± 0.0653) and elastic net regression (R² = 75.38% ± 6.98%; RMSE = 0.445 ± 0.069) for FEV₁ and FVC, respectively. This study suggests that the application of machine learning in conjunction with tracking changes in AA over the life span can be beneficial to assess the lung health in adolescence.

Hippocampal and cortical tissue-specific epigenetic clocks indicate an increased epigenetic age in a mouse model for Alzheimer's disease

Epigenetic clocks are based on age-associated changes in DNA methylation of CpG-sites, which can accurately measure chronological age in different species. Recently, several studies have indicated that the difference between chronological and epigenetic age, defined as the age acceleration, could reflect biological age indicating functional decline and age-associated diseases. In humans, an epigenetic clock associated Alzheimer's disease (AD) pathology with an acceleration of the epigenetic age. In this study, we developed and validated two mouse brain region-specific epigenetic clocks from the C57BL/6J hippocampus and cerebral cortex. Both clocks, which could successfully estimate chronological age, were further validated in a widely used mouse model for AD, the triple transgenic AD (3xTg-AD) mouse. We observed an epigenetic age acceleration indicating an increased biological age for the 3xTg-AD mice compared to non-pathological C57BL/6J mice, which was more pronounced in the cortex as compared to the hippocampus. Genomic region enrichment analysis revealed that age-dependent CpGs were enriched in genes related to developmental, aging-related, neuronal and neurodegenerative functions. Due to the limited access of human brain tissues, these epigenetic clocks specific for mouse cortex and hippocampus might be important in further unravelling the role of epigenetic mechanisms underlying AD pathology or brain aging in general.

Epigenetic mutation load is weakly correlated with epigenetic age acceleration

DNA methylation (DNAm) age estimators are widely used to study aging-related conditions. It is not yet known whether DNAm age is associated with the accumulation of stochastic epigenetic mutations (SEMs), which reflect dysfunctions of the epigenetic maintenance system. Here, we defined epigenetic mutation load (EML) as the total number of SEMs per individual. We assessed associations between EML and DNAm age acceleration estimators using biweight midcorrelations in four population-based studies (total n = 6,388). EML was not only positively associated with chronological age (meta r = 0.171), but also with four measures of epigenetic age acceleration: the Horvath pan tissue clock, intrinsic epigenetic age acceleration, the Hannum clock, and the GrimAge clock (meta-analysis correlation ranging from r = 0.109 to 0.179). We further conducted pathway enrichment analyses for each participant's SEMs. The enrichment result demonstrated the stochasticity of epigenetic mutations, meanwhile implicated several pathways: signaling, neurogenesis, neurotransmitter, glucocorticoid, and circadian rhythm pathways may contribute to faster DNAm age acceleration. Finally, investigating genomic-region specific EML, we found that EMLs located within regions of transcriptional repression (TSS1500, TSS200, and 1stExon) were associated with faster age acceleration. Overall, our findings suggest a role for the accumulation of epigenetic mutations in the aging process.

Patient-Derived Midbrain Organoids to Explore the Molecular Basis of Parkinson's Disease

Induced pluripotent stem cell-derived organoids offer an unprecedented access to complex human tissues that recapitulate features of architecture, composition and function of in vivo organs. In the context of Parkinson's Disease (PD), human midbrain organoids (hMO) are of significant interest, as they generate dopaminergic neurons expressing markers of Substantia Nigra identity, which are the most vulnerable to degeneration. Combined with genome editing approaches, hMO may thus constitute a valuable tool to dissect the genetic makeup of PD by revealing the effects of risk variants on pathological mechanisms in a representative cellular environment. Furthermore, the flexibility of organoid co-culture approaches may also enable the study of neuroinflammatory and neurovascular processes, as well as interactions with other brain regions that are also affected over the course of the disease. We here review existing protocols to generate hMO, how they have been used so far to model PD, address challenges inherent to organoid cultures, and discuss applicable strategies to dissect the molecular pathophysiology of the disease. Taken together, the research suggests that this technology represents a promising alternative to 2D in vitro models, which could significantly improve our understanding of PD and help accelerate therapeutic developments.

Association of Epigenetic Metrics of Biological Age With Cortical Thickness

IMPORTANCE

Magnetic resonance imaging (MRI) studies of aging adults have shown substantial intersubject variability across various brain metrics, and some of this variability is likely attributable to chronological age being an imprecise measure of age-related change. Accurately quantifying one's biological age could allow better quantification of healthy and pathological changes in the aging brain.

OBJECTIVE

To investigate the association of DNA methylation (DNAm)-based biological age with cortical thickness and to assess whether biological age acceleration compared with chronological age captures unique variance in cortical thinning.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used high-resolution structural brain MRI data collected from a sample of healthy aging adults who were participating in a larger ongoing neuroimaging study that began in May 2014. This population-based study accrued participants from the greater Omaha, Nebraska, metropolitan area. One hundred sixty healthy adults were contacted for the MRI component, 82 of whom participated in both DNAm and MRI study components. Data analysis was performed from March to June 2019.

MAIN OUTCOMES AND MEASURES

Vertexwise cortical thickness, DNAm-based biological age, and biological age acceleration compared with chronological age were measured. A pair of multivariable regression models were computed in which cortical thickness was regressed on DNAm-based biological age, controlling for sex in the first model and also controlling for chronological age in the second model.

RESULTS

Seventy-nine adult participants (38 women; mean [SD] age, 43.82 [14.50] years; age range, 22-72 years) were included in all final analyses. Advancing biological age was correlated with cortical thinning across frontal, superior temporal, inferior parietal, and medial occipital regions. In addition, biological age acceleration relative to chronological age was associated with cortical thinning in orbitofrontal, superior and inferior temporal, somatosensory, parahippocampal, and fusiform regions. Specifically, for every 1 year of biological age acceleration, cortical thickness would be expected to decrease by 0.024 mm (95% CI, -0.04 to -0.01 mm) in the left orbitofrontal cortex (partial r, -0.34; P = .002), 0.014 mm (95% CI, -0.02 to -0.01 mm) in the left superior temporal gyrus (partial r, -0.36; P = .001), 0.015 mm (95% CI, -0.02 to -0.01 mm) in the left fusiform gyrus (partial r, -0.38; P = .001), 0.015 mm (95% CI, -0.02 to -0.01 mm) in the right fusiform gyrus (partial r, -0.43; P < .001), 0.019 mm (95% CI, -0.03 to -0.01 mm) in the right inferior temporal sulcus (partial r, -0.34; P = .002), and 0.011 mm (95% CI, -0.02 to -0.01 mm) in the right primary somatosensory cortex (partial r, -0.37; P = .001).

CONCLUSIONS AND RELEVANCE

To our knowledge, this is the first study to investigate vertexwise cortical thickness in relation to DNAm-based biological age, and the findings suggest that this metric of biological age may yield additional insight on healthy and pathological cortical aging compared with standard measures of chronological age alone.

Biological age is a novel biomarker to predict stroke recurrence

BACKGROUND

Stroke recurrence (SR) after an ischemic stroke is an important cause of death and disability. We conducted a hospital-based study to evaluate the role of biological age (b-Age: age-related DNA-methylation changes) as a risk factor for SR.

METHODS

We included 587 patients in the acute phase of stroke, assessed at one tertiary stroke center (Hospital del Mar: Barcelona, Spain). B-Age was estimated with 5 different methods based on DNA methylation, and Hannum's method was the one that better performed. We analyzed the relationships between b-Age, chronological age, sex, vascular risk factors, coronary and peripheral arterial disease, atrial fibrillation, initial neurological severity assessed by National Institutes of Health Stroke Scale (NIHSS), transient ischemic attack (TIA) in the 7 days preceding the index stroke, and symptomatic atherosclerosis. Stroke recurrence definition include: new symptoms that suggest a new ischemic event had occurred within 3 months after stroke onset and worsening by four points in the initial neurological severity (measured by National Institutes of Health Stroke Scale (NIHSS) score).

RESULTS

Logistic regression analysis associated b-Age with SR [p = 0.003; OR = 1.06 (95% CI: 1.02-1.09)], independently of chronological age [p = 0.022; OR = 0.96 (95% CI 0.94-1.00)], symptomatic atherosclerosis (stenosis > 50% in the symptomatic territory), transient ischemic attack (TIA) in the 7 days preceding the index stroke, and initial NIHSS. The b-Age of patients with SR was 2.7 years older than patients without SR.

CONCLUSIONS

Patients with SR were biologically older than those without SR. B-Age was independently associated with high risk of developing SR.

Analysis of epigenetic aging in vivo and in vitro: Factors controlling the speed and direction

IMPACT STATEMENT

Aging is associated with DNA methylation (DNAm) changes. Recent advancement of the whole-genome DNAm analysis technology allowed scientists to develop DNAm-based age estimators. A majority of these estimators use DNAm data from a single tissue type such as blood. In 2013, a multi-tissue age estimator using DNAm pattern of 353 CpGs was developed by Steve Horvath. This estimator was named "epigenetic clock", and the improved version using DNAm pattern of 391 CpGs was developed in 2018. The estimated age by epigenetic clock is named DNAmAge. DNAmAge can be used as a biomarker of aging predicting the risk of age-associated diseases and mortality. Although the DNAm-based age estimators were developed, the mechanism of epigenetic aging is still enigmatic. The biological significance of epigenetic aging is not well understood, either. This minireview discusses the current understanding of the mechanism of epigenetic aging and the future direction of aging research.

Targeted bisulfite sequencing for biomarker discovery

Cytosine methylation is one of the best studied epigenetic modifications. In mammals, DNA methylation patterns vary among cells and is mainly found in the CpG context. DNA methylation is involved in important processes during development and differentiation and its dysregulation can lead to or is associated with diseases, such as cancer, loss-of-imprinting syndromes and neurological disorders. It has been also shown that DNA methylation at the cellular, tissue and organism level varies with age. To overcome the costs of Whole-Genome Bisulfite Sequencing, the gold standard method to detect 5-methylcytosines at a single base resolution, DNA methylation arrays have been developed and extensively used. This method allows one to assess the status of a fraction of the CpG sites present in the genome of an organism. In order to combine the relatively low cost of Methylation Arrays and digital signals of bisulfite sequencing, we developed a Targeted Bisulfite Sequencing method that can be applied to biomarker discovery for virtually any phenotype. Here we describe a comprehensive step-by-step protocol to build a DNA methylation-based epigenetic clock.

Epigenetic measures of ageing predict the prevalence and incidence of leading causes of death and disease burden

BACKGROUND

Individuals of the same chronological age display different rates of biological ageing. A number of measures of biological age have been proposed which harness age-related changes in DNA methylation profiles. These measures include five 'epigenetic clocks' which provide an index of how much an individual's biological age differs from their chronological age at the time of measurement. The five clocks encompass methylation-based predictors of chronological age (HorvathAge, HannumAge), all-cause mortality (DNAm PhenoAge, DNAm GrimAge) and telomere length (DNAm Telomere Length). A sixth epigenetic measure of ageing differs from these clocks in that it acts as a speedometer providing a single time-point measurement of the pace of an individual's biological ageing. This measure of ageing is termed DunedinPoAm. In this study, we test the association between these six epigenetic measures of ageing and the prevalence and incidence of the leading causes of disease burden and mortality in high-income countries (n ≤ 9537, Generation Scotland: Scottish Family Health Study).

RESULTS

DNAm GrimAge predicted incidence of clinically diagnosed chronic obstructive pulmonary disease (COPD), type 2 diabetes and ischemic heart disease after 13 years of follow-up (hazard ratios = 2.22, 1.52 and 1.41, respectively). DunedinPoAm predicted the incidence of COPD and lung cancer (hazard ratios = 2.02 and 1.45, respectively). DNAm PhenoAge predicted incidence of type 2 diabetes (hazard ratio = 1.54). DNAm Telomere Length associated with the incidence of ischemic heart disease (hazard ratio = 0.80). DNAm GrimAge associated with all-cause mortality, the prevalence of COPD and spirometry measures at the study baseline. These associations were present after adjusting for possible confounding risk factors including alcohol consumption, body mass index, deprivation, education and tobacco smoking and surpassed stringent Bonferroni-corrected significance thresholds.

CONCLUSIONS

Our data suggest that epigenetic measures of ageing may have utility in clinical settings to complement gold-standard methods for disease assessment and management.

Attempt to Predict A/T/N-Based Alzheimer's Disease Cerebrospinal Fluid Biomarkers Using a Peripheral Blood DNA Methylation Clock

Background:

Although aging is the strongest risk factor for the development of Alzheimer’s disease (AD), it remains uncertain if the blood DNA methylation clock, which reflects the effect of biological aging on DNA methylation (DNAme) status of blood cells, may be used as a surrogate biomarker for AD pathology in the central nervous system (CNS).

Objective:

We aimed to develop a practical model to predict for A/T/N-based AD biomarkers as the prediction targets using the aging acceleration of blood cells.

Methods:

We obtained data of North American ADNI study participants (n = 317) whose blood DNA methylation microarray (Illumina HumanMethylation EPIC Beadchips) and cerebrospinal fluid (CSF) AD biomarkers (Aβ, t-tau, and p-tau) were recorded simultaneously. Methylation clock was calculated to conduct machine learning, in order to predict binary statuses (+ or –) for A (corresponding to the lowered CSF Aβ), T (the elevated CSF p-tau), or N (the elevated CSF t-tau). The predictive performance of the models was evaluated by area under curve (AUC) in the test subset within ADNI.

Results:

Among the 317 included samples, 194 (61.2%) were A+, 247 (77.9%) were T+, and 104 (32.8%) were N+. The degree of blood aging acceleration showed weak positive correlation with the CSF Aβ levels, even after adjustment with APOE genotype and other covariates. However, the contribution of aging acceleration to improve the predictive performance of models was not significant for any of A+, T+, or N+.

Conclusion:

Our exploratory attempts could not demonstrate the substantial utility of the peripheral blood cells’ methylation clock as a predictor for A/T/N-based CSF biomarkers of AD, and further additional work should be conducted to determine whether the blood DNAme signatures including methylation clock have substantial utility in detecting underlying amyloid, tau or neurodegeneration pathology of AD.

Epigenetic age acceleration and clinical outcomes in gliomas

Epigenetic age acceleration-the difference between an individual's DNA methylation age and chronological age-is associated with many diseases including cancer. This study aims to evaluate epigenetic age acceleration as a prognostic biomarker for gliomas. DNA methylation data of gliomas patients (516 low-grade and intermediate-grade gliomas and 140 glioblastoma) were obtained from The Cancer Genome Atlas (TCGA) and patient epigenetic ages were computed using Horvath's age prediction model. We used multivariate linear regression to assess the association of epigenetic age acceleration with tumor molecular subtypes, including Codel, Classic-like, G-CIMP-high, G-CIMP-low, Mesenchymal-like and PA-like. Compared with Codel subtype, epigenetic ages in other molecular subtypes show deceleration after controlling age and race. Age deceleration for Classic-like, G-CIMP-high, G-CIMP-low, Mesenchymal-like and PA-like were 15.42 years (CI: 7.98-22.86, p = 5.38E-05), 25.00 years (CI: 20.79-29.22, p = 4.06E-28), 28.56 years (CI: 14.37-42.74, p = 8.75E-05), 45.34 years (CI: 38.80-51.88, p = 2.15E-36), and 53.58 years (CI: 44.90-62.26, p = 4.81E-30), respectively. Then, Cox proportional hazards regression was used to assess the association of epigenetic age acceleration with patient overall survival. Our results show epigenetic age acceleration is positively associated with patient overall survival (per 10-year age acceleration, HR = 0.89; 95%CI: 0.82-0.97; p = 9.04E-03) in multivariate analysis. When stratified by molecular subtypes, epigenetic age acceleration remains positively associated with patient survival after adjusting age and tumor grade. In conclusion, epigenetic age acceleration is significantly associated with molecular subtypes and patient overall survival in gliomas, indication that epigenetic age acceleration has potential as a quantitative prognostic biomarker for gliomas.

DNA Methylation Clocks and Their Predictive Capacity for Aging Phenotypes and Healthspan

The number of age predictors based on DNA methylation (DNAm) profile is rising due to their potential in predicting healthspan and application in age-related illnesses, such as neurodegenerative diseases. The cumulative assessment of DNAm levels at age-related CpGs (DNAm clock) may reflect biological aging. Such DNAm clocks have been developed using various training models and could mirror different aspects of disease/aging mechanisms. Hence, evaluating several DNAm clocks together may be the most effective strategy in capturing the complexity of the aging process. However, various confounders may influence the outcome of these age predictors, including genetic and environmental factors, as well as technical differences in the selected DNAm arrays. These factors should be taken into consideration when interpreting DNAm clock predictions. In the current review, we discuss 15 reported DNAm clocks with consideration for their utility in investigating neurodegenerative diseases and suggest research directions towards developing a more optimal measure for biological aging.

Comparative validation of an epigenetic mortality risk score with three aging biomarkers for predicting mortality risks among older adult males

BACKGROUND

A 'mortality risk score' (MS) based on ten prominent mortality-related cytosine-phosphate-guanine (CpG) sites was previously associated with all-cause mortality, but has not been verified externally. We aimed to validate the association of MS with mortality and to compare MS with three aging biomarkers: telomere length (TL), DNA methylation age (DNAmAge) and phenotypic age (DNAmPhenoAge) to explore whether MS can serve as a reliable measure of biological aging and mortality.

METHODS

Among 534 males aged 55-85 years from the US Normative Aging Study, the MS, DNAmAge and DNAmPhenoAge were derived from blood DNA methylation profiles from the Illumina HumanMethylation450 BeadChip, and TL was measured by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

A total of 147 participants died during a median follow-up of 9.4 years. The MS showed strong associations with all-cause, cardiovascular disease (CVD) and cancer mortality. After controlling for all potential covariates, participants with high MS (>5 CpG sites with aberrant methylation) had almost 4-fold all-cause mortality (hazard ratio: 3.84, 95% confidence interval: 1.92-7.67) compared with participants with a low MS (0-1 CpG site with aberrant methylation). Similar patterns were observed with respect to CVD and cancer mortality. MS was associated with TL and DNAmPhenoAge acceleration but not with DNAmAge acceleration. Although the MS and DNAmPhenoAge acceleration were independently associated with all-cause mortality, the former exhibited a higher predictive accuracy of mortality than the latter.

CONCLUSIONS

MS has the potential to be a prominent predictor of mortality that could enhance survival prediction in clinical settings.

Epigenetic clocks may come out of rhythm-implications for the estimation of chronological age in forensic casework

There is a growing perception that DNA methylation may be influenced by exogenous and endogenous parameters. Knowledge of these factors is of great relevance for the interpretation of DNA-methylation data for the estimation of chronological age in forensic casework. We performed a literature review to identify parameters, which might be of relevance for the prediction of chronological age based on DNA methylation. The quality of age predictions might particularly be influenced by lifetime adversities (chronic stress, trauma/post-traumatic stress disorder (PTSD), violence, low socioeconomic status/education), cancer, obesity and related diseases, infectious diseases (especially HIV and Cytomegalovirus (CMV) infections), sex, ethnicity and exposure to toxins (alcohol, smoking, air pollution, pesticides). Such factors may alter the DNA methylation pattern and may explain the partly high deviations between epigenetic age and chronological age in single cases (despite of low mean absolute deviations) that can also be observed with “epigenetic clocks” comprising a high number of CpG sites. So far, only few publications dealing with forensic age estimation address these confounding factors. Future research should focus on the identification of further relevant confounding factors and the development of models that are “robust” against the influence of such biological factors by systematic investigations under targeted inclusion of diverse and defined cohorts.

An epigenome-wide association study of ambient pyrethroid pesticide exposures in California's central valley

BACKGROUND

Pyrethroid pesticide use is increasing worldwide, although the full extent of associated health effects is unknown. An epigenome-wide association study (EWAS) with exploratory pathway analysis may help identify potential pyrethroid-related health effects.

METHODS

We performed an exploratory EWAS of chronic ambient pyrethroid exposure using control participants' blood in the Parkinson's Environment and Genes Study in the Central Valley of California (N = 237). We estimated associations of living and working near agricultural pyrethroid pesticide applications in the past 5 years (binary) with site-specific differential methylation, and used a false discovery rate (FDR) cut off of 0.05 for significance. We controlled for age, sex, education, cell count, and an ancestral marker for Hispanic ethnicity. We normalized methylation values for Type I/II probe bias using Beta-Mixture Quantile (BMIQ) normalization, filtered out cross-reactive probes, and evaluated for remaining bias with Surrogate Variable Analysis (SVA). We also evaluated the effects of controlling for cell count and normalizing for Type I/II probe bias by comparing changes in effect estimates and p-values for the top hits across BMIQ and GenomeStudio normalization methods, and controlling for cell count. To facilitate broader interpretation, we annotated genes to the CpG sites and performed gene set overrepresentation analysis, using genes annotated to CpG sites that were associated with pyrethroids at a raw p < 0.05, and controlling for background representation of CpG sites on the chip. We did this for both a biological process context (Gene Ontology terms) using missMethyl, and a disease set context using WebGestalt. For these gene set overrepresentation analyses we also used an FDR cut off of 0.05 for significance of gene sets.

RESULTS

After controlling for cell count and applying BMIQ normalization, 4 CpG sites were differentially methylated in relation to pyrethroid exposures. When using GenomeStudio's Illumina normalization, 415 CpG sites were differentially methylated, including all four identified with the BMIQ method. In the gene set overrepresentation analyses, we identified 6 GO terms using BMIQ normalization, and 76 using Illumina normalization, including the 6 identified by BMIQ. For disease sets, we identified signals for Alzheimer's disease, leukemia and several other cancers, diabetes, birth defects, and other diseases, for both normalization methods. We identified minimal changes in effect estimates after controlling for cell count, and controlling for cell count generally weakened p-values. BMIQ normalization, however, resulted in different beta coefficients and weakened p-values.

CONCLUSIONS

Chronic ambient pyrethroid exposure is associated with differential methylation at CpG sites that annotate to a wide variety of disease states and biological mechanisms that align with prior research. However, this EWAS also implicates several novel diseases for future investigation, and highlights the relative importance of different background normalization methods in identifying associations.

Genome-wide epigenetic analyses in Japanese immigrant plantation workers with Parkinson's disease and exposure to organochlorines reveal possible involvement of glial genes and pathways involved in neurotoxicity

Background

Parkinson’s disease (PD) is a disease of the central nervous system that progressively affects the motor system. Epidemiological studies have provided evidence that exposure to agriculture-related occupations or agrichemicals elevate a person’s risk for PD. Here, we sought to examine the possible epigenetic changes associated with working on a plantation on Oahu, HI and/or exposure to organochlorines (OGC) in PD cases.

Results

We measured genome-wide DNA methylation using the Illumina Infinium HumanMethylation450K BeadChip array in matched peripheral blood and postmortem brain biospecimens in PD cases (n = 20) assessed for years of plantation work and presence of organochlorines in brain tissue. The comparison of 10+ to 0 years of plantation work exposure detected 7 and 123 differentially methylated loci (DML) in brain and blood DNA, respectively (p < 0.0001). The comparison of cases with 4+ to 0–2 detectable levels of OGCs, identified 8 and 18 DML in brain and blood DNA, respectively (p < 0.0001). Pathway analyses revealed links to key neurotoxic and neuropathologic pathways related to impaired immune and proinflammatory responses as well as impaired clearance of damaged proteins, as found in the predominantly glial cell population in these environmental exposure-related PD cases.

Conclusions

These results suggest that distinct DNA methylation biomarker profiles related to environmental exposures in PD cases with previous exposure can be found in both brain and blood.

Epigenetics in Lewy Body Diseases: Impact on Gene Expression, Utility as a Biomarker, and Possibilities for Therapy

Lewy body disorders (LBD) include Parkinson's disease (PD) and dementia with Lewy bodies (DLB). They are synucleinopathies with a heterogeneous clinical manifestation. As a cause of neuropathological overlap with other neurodegenerative diseases, the establishment of a correct clinical diagnosis is still challenging, and clinical management may be difficult. The combination of genetic variation and epigenetic changes comprising gene expression-modulating DNA methylation and histone alterations modifies the phenotype, disease course, and susceptibility to disease. In this review, we summarize the results achieved in the deciphering of the LBD epigenome. To provide an appropriate context, first LBD genetics is briefly outlined. Afterwards, a detailed review of epigenetic modifications identified for LBD in human cells, postmortem, and peripheral tissues is provided. We also focus on the difficulty of identifying epigenome-related biomarker candidates and discuss the results obtained so far. Additionally, epigenetic changes as therapeutic targets, as well as different epigenome-based treatments, are revised. The number of studies focusing on PD is relatively limited and practically inexistent for DLB. There is a lack of replication studies, and some results are even contradictory, probably due to differences in sample collection and analytical techniques. In summary, we show the current achievements and directions for future research.

Nutritional Epigenomics and Age-Related Disease

Recent advances in epigenetic research have enabled the development of epigenetic clocks, which have greatly enhanced our ability to investigate molecular processes that contribute to aging and age-related disease. These biomarkers offer the potential to measure the effect of environmental exposures linked to dynamic changes in DNA methylation, including nutrients, as factors in age-related disease. They also offer a compelling insight into how imbalances in the supply of nutrients, particularly B-vitamins, or polymorphisms in regulatory enzymes involved in 1-carbon metabolism, the key pathway that supplies methyl groups for epigenetic reactions, may influence epigenetic age and interindividual disease susceptibility. Evidence from recent studies is critically reviewed, focusing on the significant contribution of the epigenetic clock to nutritional epigenomics and its impact on health outcomes and age-related disease. Further longitudinal studies and randomized nutritional interventions are required to advance the field.

Analysis of Epigenetic Age Predictors in Pain-Related Conditions

Chronic pain prevalence is high worldwide and increases at older ages. Signs of premature aging have been associated with chronic pain, but few studies have investigated aging biomarkers in pain-related conditions. A set of DNA methylation (DNAm)-based estimates of age, called “epigenetic clocks,” has been proposed as biological measures of age-related adverse processes, morbidity, and mortality. The aim of this study is to assess if different pain-related phenotypes show alterations in DNAm age. In our analysis, we considered three cohorts for which whole-blood DNAm data were available: heat pain sensitivity (HPS), including 20 monozygotic twin pairs discordant for heat pain temperature threshold; fibromyalgia (FM), including 24 cases and 20 controls; and headache, including 22 chronic migraine and medication overuse headache patients (MOH), 18 episodic migraineurs (EM), and 13 healthy subjects. We used the Horvath's epigenetic age calculator to obtain DNAm-based estimates of epigenetic age, telomere length, levels of 7 proteins in plasma, number of smoked packs of cigarettes per year, and blood cell counts. We did not find differences in epigenetic age acceleration, calculated using five different epigenetic clocks, between subjects discordant for pain-related phenotypes. Twins with high HPS had increased CD8+ T cell counts (nominal p = 0.028). HPS thresholds were negatively associated with estimated levels of GDF15 (nominal p = 0.008). FM patients showed decreased naive CD4+ T cell counts compared with controls (nominal p = 0.015). The severity of FM manifestations expressed through various evaluation tests was associated with decreased levels of leptin, shorter length of telomeres, and reduced CD8+ T and natural killer cell counts (nominal p < 0.05), while the duration of painful symptoms was positively associated with telomere length (nominal p = 0.034). No differences in DNAm-based estimates were detected for MOH or EM compared with controls. In summary, our study suggests that HPS, FM, and MOH/EM do not show signs of epigenetic age acceleration in whole blood, while HPS and FM are associated with DNAm-based estimates of immunological parameters, plasma proteins, and telomere length. Future studies should extend these observations in larger cohorts.

Biomarkers of aging and lung function in the normative aging study

Elderly individuals who are never smokers but have the same height and chronological age can have substantial differences in lung function. The underlying biological mechanisms are unclear. To evaluate the associations of different biomarkers of aging (BoA) and lung function, we performed a repeated-measures analysis in the Normative Aging Study using linear mixed-effect models. We generated GrimAgeAccel, PhenoAgeAccel, extrinsic and intrinsic epigenetic age acceleration using a publically available online calculator. We calculated Zhang's DNAmRiskScore based on 10 CpGs. We measured telomere length (TL) and mitochondrial DNA copy number (mtDNA-CN) using quantitative real-time polymerase chain reaction. A pulmonary function test was performed measuring forced expiratory volume in 1 second / forced vital capacity (FEV₁/FVC), FEV₁, and maximum mid-expiratory flow (MMEF). Epigenetic-based BoA were associated with lower lung function. For example, a one-year increase in GrimAgeAccel was associated with a 13.64 mL [95% confidence interval (CI), 5.11 to 22.16] decline in FEV₁; a 0.2 increase in Zhang's DNAmRiskScore was associated with a 0.009 L/s (0.005 to 0.013) reduction in MMEF. No association was found between TL/mtDNA-CN and lung function. Overall, this paper shows that epigenetics might be a potential mechanism underlying pulmonary dysfunction in the elderly.

Epigenetic clock analysis of human fibroblasts in vitro: effects of hypoxia, donor age, and expression of hTERT and SV40 largeT

Aging is associated with a genome-wide change of DNA methylation (DNAm). "DNAm age" is defined as the predicted chronological age by the age estimator based on DNAm. The estimator is called the epigenetic clock. The molecular mechanism underlining the epigenetic clock is still unknown. Here, we evaluated the effects of hypoxia and two immortalization factors, hTERT and SV40-LargeT (LT), on the DNAm age of human fibroblasts in vitro. We detected the cell division-associated progression of DNAm age after >10 population doublings. Moreover, the progression of DNAm age was slower under hypoxia (1% oxygen) compared to normoxia (21% oxygen), suggesting that oxygen levels determine the speed of the epigenetic aging. We show that the speed of cell division-associated DNAm age progression depends on the chronological age of the cell donor. hTERT expression did not arrest cell division-associated progression of DNAm age in most cells. SV40LT expression produced inconsistent effects, including rejuvenation of DNAm age. Our results show that a) oxygen and the targets of SV40LT (e.g. p53) modulate epigenetic aging rates and b) the chronological age of donor cells determines the speed of mitosis-associated DNAm age progression in daughter cells.

Rapamycin retards epigenetic ageing of keratinocytes independently of its effects on replicative senescence, proliferation and differentiation

The advent of epigenetic clocks has prompted questions about the place of epigenetic ageing within the current understanding of ageing biology. It was hitherto unclear whether epigenetic ageing represents a distinct mode of ageing or a manifestation of a known characteristic of ageing. We report here that epigenetic ageing is not affected by replicative senescence, telomere length, somatic cell differentiation, cellular proliferation rate or frequency. It is instead retarded by rapamycin, the potent inhibitor of the mTOR complex which governs many pathways relating to cellular metabolism. Rapamycin, however, is also an effective inhibitor of cellular senescence. Hence cellular metabolism underlies two independent arms of ageing - cellular senescence and epigenetic ageing. The demonstration that a compound that targets metabolism can slow epigenetic ageing provides a long-awaited point-of-entry into elucidating the molecular pathways that underpin the latter. Lastly, we report here an in vitro assay, validated in humans, that recapitulates human epigenetic ageing that can be used to investigate and identify potential interventions that can inhibit or retard it.

The acute effects of adjuvant radiation and chemotherapy on peripheral blood epigenetic age in early stage breast cancer patients

Survival has increased in early stage breast cancer (BC), and the late effects of treatment persist for decades. Molecular mechanisms underlying the acceleration of age-related diseases after chemotherapy and radiotherapy are poorly understood. We examined epigenetic changes in peripheral whole blood cells in early stage BC patients undergoing surgery followed by adjuvant radiotherapy, or surgery followed by adjuvant chemotherapy and radiotherapy. DNA methylation experiments were performed on whole blood samples collected before and after adjuvant therapy. Methylation profiles were used to estimate four measures of epigenetic age acceleration-intrinsic, extrinsic, phenotypic, and Grim-and cell counts. We found significant increases in extrinsic, phenotypic, and Grim epigenetic age acceleration and in estimated proportions of senescent T lymphocytes from pre- to post-treatment. When examining differential effects by treatment category, most of these increases were significant only in women undergoing radiation alone. Further studies are needed to examine whether these effects are related to the risk of cognitive and functional decline in BC survivors.

Improvements to Healthspan Through Environmental Enrichment and Lifestyle Interventions: Where Are We Now?

Environmental enrichment (EE) is an experimental paradigm that is used to explore how a complex, stimulating environment can impact overall health. In laboratory animal experiments, EE housing conditions typically include larger-than-standard cages, abundant bedding, running wheels, mazes, toys, and shelters which are rearranged regularly to further increase stimulation. EE has been shown to improve multiple aspects of health, including but not limited to metabolism, learning and cognition, anxiety and depression, and immunocompetence. Recent advances in lifespan have led some researchers to consider aging as a risk factor for disease. As such, there is a pressing need to understand the processes by which healthspan can be increased. The natural and predictable changes during aging can be reversed or decreased through EE and its underlying mechanisms. Here, we review the use of EE in laboratory animals to understand mechanisms involved in aging, and comment on relative areas of strength and weakness in the current literature. We additionally address current efforts toward applying EE-like lifestyle interventions to human health to extend healthspan. Although increasing lifespan is a clear goal of medical research, improving the quality of this added time also deserves significant attention. Despite hurdles in translating experimental results toward clinical application, we argue there is great potential in using features of EE toward improving human healthy life expectancy or healthspan, especially in the context of increased global longevity.

Epigenetic regulation in the pathophysiology of Lewy body dementia

Lewy body dementia encompasses both dementia with Lewy bodies and Parkinson's disease dementia. Although both are common causes of dementia, they remain relatively understudied. The review summarises the clinico-pathologic characteristics of Lewy Body dementia and discusses the genetic and environmental evidence contributing to the risk of developing the condition. Considering that the pathophysiology of Lewy body dementia is not yet fully understood, here we focus on the role of epigenetic mechanisms as potential key mediators of gene-environment interactions in the development of the disease. We examine available important data on genomics, epigenomics, gene expression and proteomic studies in Lewy body dementia on human post-mortem brain and peripheral tissues. Genetic variation and epigenetic modifications in key genes involved in the disorder, such as apolipoprotein E (APOE), α-synuclein (SNCA) and glucocerobrosidase (GBA), suggest a central involvement of epigenetics in DLB but conclusive evidence is scarce. This is due to limitations of existing literature, such as small sample sizes, lack of replication and lack of studies interrogating cell-type specific epigenetic modifications in the brain. Future research in the field can improve the understanding of this common but complex and rapidly progressing type of dementia and potentially open early diagnostic and effective therapeutic targets.

Current advances in the development of novel polymeric nanoparticles for the treatment of neurodegenerative diseases

Effective intervention is essential to combat the coming epidemic of neurodegenerative (ND) diseases. Nanomedicine can overcome restrictions of CNS delivery imposed by the blood-brain barrier, and thus be instrumental in preclinical discovery and therapeutic intervention of ND diseases. Polymeric nanoparticles (PNPs) have shown great potential and versatility to encapsulate several compounds simultaneously in controlled drug-delivery systems and target them to the deepest brain regions. Here, we critically review recent advances in the development of drugs incorporated into PNPs and summarize the molecular changes and functional effects achieved in preclinical models of the most common ND disorders. We also briefly discuss the many challenges remaining to translate these findings and technological advances successfully to current clinical settings.

Decelerated epigenetic aging associated with mood stabilizers in the blood of patients with bipolar disorder

There is high mortality among patients with bipolar disorder (BD). Studies have reported accelerated biological aging in patients with BD. Recently, Horvath and Hannum et al. independently developed DNA methylation (DNAm) profiles as "epigenetic clocks," which are the most accurate biological age estimate. This led to the development of two accomplished measures of epigenetic age acceleration (EAA) using blood samples, namely, intrinsic and extrinsic EAA (IEAA and EEAA, respectively). IEAA, which is based on Horvath's clock, is independent of blood cell counts and indicates cell-intrinsic aging. On the other hand, EEAA, which is based on Hannum's clock, is associated with age-dependent changes in blood cell counts and indicates immune system aging. Further, Lu et al. developed the "GrimAge" clock, which can strongly predict the mortality risk, and DNAm-based telomere length (DNAmTL). We used a DNAm dataset from whole blood samples obtained from 30 patients with BD and 30 healthy controls. We investigated Horvath EAA, IEAA, Hannum EAA, EEAA, Grim EAA, DNAmTL, and DNAm-based blood cell composition. Compared with controls, there was a decrease in Horvath EAA and IEAA in patients with BD. Further, there was a significant decrease in Horvath EAA and IEAA in patients with BD taking medication combinations of mood stabilizers (including lithium carbonate, sodium valproate, and carbamazepine) than in those taking no medication/monotherapy. This study provides novel evidence indicating decelerated epigenetic aging associated with mood stabilizers in patients with BD.

Longitudinal Epigenome-Wide Methylation Study of Cognitive Decline and Motor Progression in Parkinson's Disease

BACKGROUND

DNA methylation studies in Parkinson's disease (PD) thus far have focused on disease susceptibility but not progression.

OBJECTIVE

In this epigenome-wide association study (EWAS), we aim to identify methylation markers associated with faster cognitive decline or motor progression in PD.

METHODS

We included 232 PD patients from the Parkinson's Environment and Gene follow-up study who provided blood samples at enrolment. Information on cognitive and motor function was collected using the Mini-Mental State Examination (MMSE) and Unified Parkinson's Disease Rating Scale (UPDRS). For EWAS analyses, we used a robust measure of correlation: biweight midcorrelations, t-tests, and Cox proportional hazard models. We also conducted weighted correlation network analysis (WGCNA) to identify CpG modules associated with cognitive decline or motor progression in PD.

RESULTS

Among 197 individuals of European ancestry, with our EWAS approach we identified 7 genome-wide significant CpGs associated with a MMSE 4-point decline and 8 CpGs associated with faster motor progression (i.e., rate of UPDRS increase ≥5-point/year). The most interesting CpGs for cognitive decline include cg17445913 in KCNB1 (cor = 0.36, p = 6.85×10-7) and cg02920897 in DLEU2 (cor = 0.34, p = 3.23×10-6), while for motor progression it was cg01754178 in PTPRN2 (cor = - 0.34, p = 2.07×10-6). In WGCNA, motor progression related modules were enriched for genes related to neuronal synaptic functions, Wnt signaling pathway, and mitochondrial apoptosis.

CONCLUSIONS

Our study provides the first epigenetic evidence that differential methylation in genes previously identified as being associated with cognitive impairment, neuronal synaptic function, Wnt signaling pathway, and mitochondrial apoptosis is associated with cognitive and motor progression in PD.

Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing

BACKGROUND

Epigenome-wide association studies (EWAS), which seek the association between epigenetic marks and an outcome or exposure, involve multiple hypothesis testing. False discovery rate (FDR) control has been widely used for multiple testing correction. However, traditional FDR control methods do not use auxiliary covariates, and they could be less powerful if the covariates could inform the likelihood of the null hypothesis. Recently, many covariate-adaptive FDR control methods have been developed, but application of these methods to EWAS data has not yet been explored. It is not clear whether these methods can significantly improve detection power, and if so, which covariates are more relevant for EWAS data.

RESULTS

In this study, we evaluate the performance of five covariate-adaptive FDR control methods with EWAS-related covariates using simulated as well as real EWAS datasets. We develop an omnibus test to assess the informativeness of the covariates. We find that statistical covariates are generally more informative than biological covariates, and the covariates of methylation mean and variance are almost universally informative. In contrast, the informativeness of biological covariates depends on specific datasets. We show that the independent hypothesis weighting (IHW) and covariate adaptive multiple testing (CAMT) method are overall more powerful, especially for sparse signals, and could improve the detection power by a median of 25% and 68% on real datasets, compared to the ST procedure. We further validate the findings in various biological contexts.

CONCLUSIONS

Covariate-adaptive FDR control methods with informative covariates can significantly increase the detection power for EWAS. For sparse signals, IHW and CAMT are recommended.

DNA methylation GrimAge strongly predicts lifespan and healthspan

It was unknown whether plasma protein levels can be estimated based on DNA methylation (DNAm) levels, and if so, how the resulting surrogates can be consolidated into a powerful predictor of lifespan. We present here, seven DNAm-based estimators of plasma proteins including those of plasminogen activator inhibitor 1 (PAI-1) and growth differentiation factor 15. The resulting predictor of lifespan, DNAm GrimAge (in units of years), is a composite biomarker based on the seven DNAm surrogates and a DNAm-based estimator of smoking pack-years. Adjusting DNAm GrimAge for chronological age generated novel measure of epigenetic age acceleration, AgeAccelGrim.Using large scale validation data from thousands of individuals, we demonstrate that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E-75), time-to-coronary heart disease (Cox P=6.2E-24), time-to-cancer (P= 1.3E-12), its strong relationship with computed tomography data for fatty liver/excess visceral fat, and age-at-menopause (P=1.6E-12). AgeAccelGrim is strongly associated with a host of age-related conditions including comorbidity count (P=3.45E-17). Similarly, age-adjusted DNAm PAI-1 levels are associated with lifespan (P=5.4E-28), comorbidity count (P= 7.3E-56) and type 2 diabetes (P=2.0E-26). These DNAm-based biomarkers show the expected relationship with lifestyle factors including healthy diet and educational attainment.Overall, these epigenetic biomarkers are expected to find many applications including human anti-aging studies.

One-year Mediterranean diet promotes epigenetic rejuvenation with country- and sex-specific effects: a pilot study from the NU-AGE project

Mediterranean diet has been proposed to promote healthy aging, but its effects on aging biomarkers have been poorly investigated. We evaluated the impact of a 1-year Mediterranean-like diet in a pilot study including 120 elderly healthy subjects from the NU-AGE study (60 Italians, 60 Poles) by measuring the changes in their epigenetic age, assessed by Horvath's clock. We observed a trend towards epigenetic rejuvenation of participants after nutritional intervention. The effect was statistically significant in the group of Polish females and in subjects who were epigenetically older at baseline. A genome-wide association study of epigenetic age changes after the intervention did not return significant (adjusted p value < 0.05) loci. However, we identified small-effect alleles (nominal p value < 10-4), mapping in genes enriched in pathways related to energy metabolism, regulation of cell cycle, and of immune functions. Together, these findings suggest that Mediterranean diet can promote epigenetic rejuvenation but with country-, sex-, and individual-specific effects, thus highlighting the need for a personalized approach to nutritional interventions.

DNA Methylation Biomarkers in Aging and Age-Related Diseases

Recent research efforts provided compelling evidence of genome-wide DNA methylation alterations in aging and age-related disease. It is currently well established that DNA methylation biomarkers can determine biological age of any tissue across the entire human lifespan, even during development. There is growing evidence suggesting epigenetic age acceleration to be strongly linked to common diseases or occurring in response to various environmental factors. DNA methylation based clocks are proposed as biomarkers of early disease risk as well as predictors of life expectancy and mortality. In this review, we will summarize key advances in epigenetic clocks and their potential application in precision health. We will also provide an overview of progresses in epigenetic biomarker discovery in Alzheimer's, type 2 diabetes, and cardiovascular disease. Furthermore, we will highlight the importance of prospective study designs to identify and confirm epigenetic biomarkers of disease.