Biological Age Predictors

Current State of Saliva Biomarkers for Aging and Alzheimer's Disease

INTRODUCTION

Aging is the primary risk factor for major human pathologies, including cancer, diabetes, cardiovascular diseases, and neurodegenerative diseases such as Alzheimer's Disease (AD). AD is a progressive degenerative disorder of the brain and is the most common form of dementia.

METHODS

To-date no simple, inexpensive and minimally invasive procedure is available to confirm with certainty the early diagnosis of AD prior to the manifestations of symptoms characteristic of the disease. Therefore, if population screening of individuals is to be performed, easily accessible tissues would need to be used for a diagnostic test that would identify those who exhibit altered or aberrant aging profiles that may be indicative of AD risk, so that they can be prioritized for primary prevention. This need for minimally invasive tests could be achieved by targeting saliva, since it is now well recognized that many aging diseases including AD are associated with peripheral biomarkers that are not only restricted to pathology and biomarkers within the brain.

RESULTS

Therefore, the aim of this review is to summarize some of the main findings of salivary biomarkers of aging and AD; including various proteins, metabolites, and alterations to DNA and miRNA. The future of healthy aging resides in innovative platforms, biosensors and point-of-care devices that can extract real time information on the health status of an individual. Those platforms may be achieved through the development and validation of novel biomarkers of health using saliva which, although being the least explored for biomedical purposes, has the distinct advantage that it can be self-collected in a non-invasive manner.

The Effect of Tobacco Smoking Differs across Indices of DNA Methylation-Based Aging in an African American Sample: DNA Methylation-Based Indices of Smoking Capture These Effects

Smoking is one of the leading preventable causes of morbidity and mortality worldwide, prompting interest in its association with DNA methylation-based measures of biological aging. Considerable progress has been made in developing DNA methylation-based measures that correspond to self-reported smoking status. In addition, assessment of DNA methylation-based aging has been expanded to better capture individual differences in risk for morbidity and mortality. Untested to date, however, is whether smoking is similarly related to older and newer indices of DNA methylation-based aging, and whether DNA methylation-based indices of smoking can be used in lieu of self-reported smoking to examine effects on DNA methylation-based aging measures. In the current investigation we examine mediation of the impact of self-reported cigarette consumption on accelerated, intrinsic DNA methylation-based aging using indices designed to predict chronological aging, phenotypic aging, and mortality risk, as well as a newly developed DNA methylation-based measure of telomere length. Using a sample of 500 African American middle aged smokers and non-smokers, we found that a) self-reported cigarette consumption was associated with accelerated intrinsic DNA methylation-based aging on some but not all DNA methylation-based aging indices, b) for those aging outcomes associated with self-reported cigarette consumption, DNA methylation-based indicators of smoking typically accounted for greater variance than did self-reported cigarette consumption, and c) self-reported cigarette consumption effects on DNA methylation-based aging indices typically were fully mediated by DNA methylation-based indicators of smoking (e.g., PACKYRS from GrimAge; or cg05575921 CpG site). Results suggest that when DNA methylation-based indices of smoking are substituted for self-reported assessments of smoking, they will typically fully reflect the varied impact of cigarette smoking on intrinsic, accelerated DNA methylation-based aging.

Composite Measure of Physiological Dysregulation as a Predictor of Mortality: The Long Life Family Study

Biological aging results in changes in an organism that accumulate over age in a complex fashion across different regulatory systems, and their cumulative effect manifests in increased physiological dysregulation (PD) and declining robustness and resilience that increase risks of health disorders and death. Several composite measures involving multiple biomarkers that capture complex effects of aging have been proposed. We applied one such approach, the Mahalanobis distance (D_M), to baseline measurements of various biomarkers (inflammation, hematological, diabetes-associated, lipids, endocrine, renal) in 3,279 participants from the Long Life Family Study (LLFS) with complete biomarker data. We used D_M to estimate the level of PD by summarizing information about multiple deviations of biomarkers from specified “norms” in the reference population (here, LLFS participants younger than 60 years at baseline). An increase in D_M was associated with significantly higher mortality risk (hazard ratio per standard deviation of D_M: 1.42; 95% confidence interval: [1.3, 1.54]), even after adjustment for a composite measure summarizing 85 health-related deficits (disabilities, diseases, less severe symptoms), age, and other covariates. Such composite measures significantly improved mortality predictions especially in the subsample of participants from families enriched for exceptional longevity (the areas under the receiver operating characteristic curves are 0.88 vs. 0.85, in models with and without the composite measures, p = 2.9 × 10⁻⁵). Sensitivity analyses confirmed that our conclusions are not sensitive to different aspects of computational procedures. Our findings provide the first evidence of association of PD with mortality and its predictive performance in a unique sample selected for exceptional familial longevity.

Accelerated extrinsic epigenetic aging and increased natural killer cells in blood of suicide completers

BACKGROUND

Studies suggest aberrant DNA methylation in victims of suicide. Recently, DNA methylation profiles have been developed for determining "epigenetic age," which is the most accurate estimate of biological age. Subsequently, two refined measures of epigenetic age acceleration have been expanded for blood samples as intrinsic and extrinsic epigenetic age acceleration (IEAA and EEAA, respectively). IEAA involves pure epigenetic aging independent of blood cell composition, whereas EEAA involves immunosenescence in association with blood cell composition.

METHODS

We investigated epigenetic age acceleration using two independent DNA methylation datasets: a brain dataset from 16 suicide completers and 15 non-psychiatric controls and a blood dataset compiled using economical DNA pooling technique from 56 suicide completers and 60 living healthy controls. In the blood dataset, we considered IEAA and EEAA, as well as DNA methylation-based blood cell composition.

RESULTS

There was no significant difference in universal epigenetic age acceleration between suicide completers and controls in both brain and blood datasets. Blood of suicide completers exhibited an increase in EEAA, but not in IEAA. We additionally found that suicide completers had more natural killer cells but fewer granulocytes compared to controls.

CONCLUSION

This study provides novel evidence for accelerated extrinsic epigenetic aging in suicide completers and for the potential application of natural killer cells as a biomarker for suicidal behavior.

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.

Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up

Biological age measurements (BAs) assess aging-related physiological change and predict health risks among individuals of the same chronological age (CA). Multiple BAs have been proposed and are well studied individually but not jointly. We included 845 individuals and 3973 repeated measurements from a Swedish population-based cohort and examined longitudinal trajectories, correlations, and mortality associations of nine BAs across 20 years follow-up. We found the longitudinal growth of functional BAs accelerated around age 70; average levels of BA curves differed by sex across the age span (50-90 years). All BAs were correlated to varying degrees; correlations were mostly explained by CA. Individually, all BAs except for telomere length were associated with mortality risk independently of CA. The largest effects were seen for methylation age estimators (GrimAge) and the frailty index (FI). In joint models, two methylation age estimators (Horvath and GrimAge) and FI remained predictive, suggesting they are complementary in predicting mortality.

Measuring biological aging in humans: A quest

The global population of individuals over the age of 65 is growing at an unprecedented rate and is expected to reach 1.6 billion by 2050. Most older individuals are affected by multiple chronic diseases, leading to complex drug treatments and increased risk of physical and cognitive disability. Improving or preserving the health and quality of life of these individuals is challenging due to a lack of well-established clinical guidelines. Physicians are often forced to engage in cycles of "trial and error" that are centered on palliative treatment of symptoms rather than the root cause, often resulting in dubious outcomes. Recently, geroscience challenged this view, proposing that the underlying biological mechanisms of aging are central to the global increase in susceptibility to disease and disability that occurs with aging. In fact, strong correlations have recently been revealed between health dimensions and phenotypes that are typical of aging, especially with autophagy, mitochondrial function, cellular senescence, and DNA methylation. Current research focuses on measuring the pace of aging to identify individuals who are "aging faster" to test and develop interventions that could prevent or delay the progression of multimorbidity and disability with aging. Understanding how the underlying biological mechanisms of aging connect to and impact longitudinal changes in health trajectories offers a unique opportunity to identify resilience mechanisms, their dynamic changes, and their impact on stress responses. Harnessing how to evoke and control resilience mechanisms in individuals with successful aging could lead to writing a new chapter in human medicine.

Clinical epigenetics: a primer for the practitioner

Disruption of epigenetic modifications and the factors that maintain these modifications is rapidly emerging as a cause of developmental disorders. Here we summarize some of the major principles of epigenetics including how epigenetic modifications are: (1) normally reset in the germ line, (2) form an additional layer of interindividual variation, (3) are environmentally sensitive, and (4) change over time in humans. We also briefly discuss the disruption of growth and intellect associated with the Mendelian disorders of the epigenetic machinery and the classical imprinting disorders (such as Beckwith-Wiedemann syndrome, Silver-Russell syndrome, Prader-Willi syndrome, and Angelman syndrome), as well as suggesting some diagnostic considerations for the clinicians taking care of these patients. Finally, we discuss novel therapeutic strategies targeting epigenetic modifications, which may offer a safe alternative to up and coming genome editing strategies for the treatment of genetic diseases. This review provides a starting point for clinicians interested in epigenetics and the role epigenetic disruption plays in human disease. WHAT THIS PAPER ADDS: Clinicians are introduced to four main principles of epigenetics. Clinical features of imprinting disorders and Mendelian disorders of epigenetic machinery are presented.

Maternal cardiometabolic factors and genetic ancestry influence epigenetic aging of the placenta

Disruption of physiological aging of the placenta can lead to pregnancy complications and increased risk for cardiometabolic diseases during childhood and adulthood. Maternal metabolic and genetic factors need to operate in concert with placental development for optimal pregnancy outcome. However, it is unknown whether maternal cardiometabolic status and genetic ancestry contribute to differences in placental epigenetic age acceleration (PAA). We investigated whether maternal prepregnancy obesity, gestational weight gain (GWG), blood pressure, and genetic ancestry influence PAA. Among 301 pregnant women from 4 race/ethnic groups who provided placenta samples at delivery as part of the National Institute of Child Health and Human Development Fetal Growth Studies, placental DNA methylation age was estimated using 62 CpGs known to predict placental aging. PAA was defined to be the difference between placental DNA methylation age and gestational age at birth. Percentage of genetic ancestries was estimated using genotype data. We found that a 1 kg/week increase in GWG was associated with up to 1.71 (95% CI: -3.11, -0.32) week lower PAA. Offspring Native American ancestry and African ancestry were associated, respectively, with higher and lower PAA among Hispanics, and maternal East Asian ancestry was associated with lower PAA among Asians (p < 0.05). Among mothers with a male offspring, blood pressure was associated with lower PAA across all three trimesters (p < 0.05), prepregnancy obesity compared to normal weight was associated with 1.24 (95% CI: -2.24, -0.25) week lower PAA. In summary, we observed that maternal cardiometabolic factors and genetic ancestry influence placental epigenetic aging and some of these influences may be male offspring-specific.

Ensemble Learning of Convolutional Neural Network, Support Vector Machine, and Best Linear Unbiased Predictor for Brain Age Prediction: ARAMIS Contribution to the Predictive Analytics Competition 2019 Challenge

We ranked third in the Predictive Analytics Competition (PAC) 2019 challenge by achieving a mean absolute error (MAE) of 3.33 years in predicting age from T1-weighted MRI brain images. Our approach combined seven algorithms that allow generating predictions when the number of features exceeds the number of observations, in particular, two versions of best linear unbiased predictor (BLUP), support vector machine (SVM), two shallow convolutional neural networks (CNNs), and the famous ResNet and Inception V1. Ensemble learning was derived from estimating weights via linear regression in a hold-out subset of the training sample. We further evaluated and identified factors that could influence prediction accuracy: choice of algorithm, ensemble learning, and features used as input/MRI image processing. Our prediction error was correlated with age, and absolute error was greater for older participants, suggesting to increase the training sample for this subgroup. Our results may be used to guide researchers to build age predictors on healthy individuals, which can be used in research and in the clinics as non-specific predictors of disease status.

Biological Aging and the Cellular Pathogenesis of Huntington's Disease

Huntington's disease (HD) is a fatal, inherited neurodegenerative disorder caused by a mutation in the huntingtin gene (HTT). While mutant HTT is present ubiquitously throughout life, HD onset typically occurs in mid-life, suggesting that aging may play an active role in pathogenesis. Cellular aging is defined as the slow decline in stress resistance and accumulation of damage over time. While different cells and tissues can age at different rates, 9 hallmarks of aging have emerged to better define the cellular aging process. Strikingly, many of the hallmarks of aging are also hallmarks of HD pathology. Models of HD and HD patients possess markers of accelerated aging, and processes that decline during aging also decline at a more rapid rate in HD, further implicating the role of aging in HD pathogenesis. Furthermore, accelerating aging in HD mouse and patient-derived neurons unmasks HD-specific phenotypes, suggesting an active role for the aging process in the onset and progression of HD. Here, we review the overlap between the hallmarks of aging and HD and discuss how aging may contribute to pathogenesis in HD.

The Development of Epigenetics in the Study of Disease Pathogenesis

The study of epigenetics has its roots in the study of organism change over time and response to environmental change, although over the past several decades the definition has been formalized to include heritable alterations in gene expression that are not a result of alterations in underlying DNA sequence. In this chapter, we discuss first the history and milestones in the 100+ years of epigenetic study, including early discoveries of DNA methylation, histone posttranslational modification, and noncoding RNA. We then discuss how epigenetics has changed the way that we think of both health and disease, offering as examples studies examining the epigenetic contributions to aging, including the recent development of an epigenetic "clock", and explore how antiaging therapies may work through epigenetic modifications. We then discuss a nonpathogenic role for epigenetics in the clinic: epigenetic biomarkers. We conclude by offering two examples of modern state-of-the-art integrated multi-omics studies of epigenetics in disease pathogenesis, one which sought to capture shared mechanisms among multiple diseases, and another which used epigenetic big data to better understand the pathogenesis of a single tissue from one disease.

Epigenetic mortality predictors and incidence of breast cancer

Measures derived using blood DNA methylation are increasingly under investigation as indicators of disease and mortality risk. Three existing epigenetic age measures or “epigenetic clocks” appear associated with breast cancer. Two newly-developed epigenetic mortality predictors may be related to all-cancer incidence, but associations with specific cancers have not been examined in large studies. Using HumanMethylation450 BeadChips to measure blood DNA methylation in 2,773 cancer-free women enrolled in the Sister Study, we calculated two epigenetic mortality predictors: ‘GrimAgeAccel’ and the ‘mortality score’ (MS). Using Cox proportional hazard models, neither GrimAgeAccel nor the MS were associated with overall breast cancer incidence (GrimAgeAccel hazard ratio [HR]: 1.06, 95% confidence interval [CI]: 0.98-1.14, P=0.17; MS HR: 0.99, 95% CI: 0.92-1.07, P=0.85); however, a weak, positive association was observed for GrimAgeAccel and invasive breast cancer (HR: 1.08, 95% CI: 0.99-1.17, P=0.08). Stratification of invasive cancers by menopause status at diagnoses revealed the association was predominantly observed for postmenopausal breast cancer (HR: 1.10, 95% CI: 1.01, 1.20, P=0.04). Although the MS was unrelated to breast cancer risk, we find evidence that GrimAgeAccel may be weakly associated with invasive breast cancer, particularly for women diagnosed after menopause.

Alternative splicing in aging and longevity

Alternative pre-mRNA splicing increases the complexity of the proteome that can be generated from the available genomic coding sequences. Dysregulation of the splicing process has been implicated in a vast repertoire of diseases. However, splicing has recently been linked to both the aging process itself and pro-longevity interventions. This review focuses on recent research towards defining RNA splicing as a new hallmark of aging. We highlight dysfunctional alternative splicing events that contribute to the aging phenotype across multiple species, along with recent efforts toward deciphering mechanistic roles for RNA splicing in the regulation of aging and longevity. Further, we discuss recent research demonstrating a direct requirement for specific splicing factors in pro-longevity interventions, and specifically how nutrient signaling pathways interface to splicing factor regulation and downstream splicing targets. Finally, we review the emerging potential of using splicing profiles as a predictor of biological age and life expectancy. Understanding the role of RNA splicing components and downstream targets altered in aging may provide opportunities to develop therapeutics and ultimately extend healthy lifespan in humans.

Reversal of epigenetic aging and immunosenescent trends in humans

Epigenetic “clocks” can now surpass chronological age in accuracy for estimating biological age. Here, we use four such age estimators to show that epigenetic aging can be reversed in humans. Using a protocol intended to regenerate the thymus, we observed protective immunological changes, improved risk indices for many age‐related diseases, and a mean epigenetic age approximately 1.5 years less than baseline after 1 year of treatment (−2.5‐year change compared to no treatment at the end of the study). The rate of epigenetic aging reversal relative to chronological age accelerated from −1.6 year/year from 0–9 month to −6.5 year/year from 9–12 month. The GrimAge predictor of human morbidity and mortality showed a 2‐year decrease in epigenetic vs. chronological age that persisted six months after discontinuing treatment. This is to our knowledge the first report of an increase, based on an epigenetic age estimator, in predicted human lifespan by means of a currently accessible aging intervention.

Viewpoint on the role of tissue maintenance in ageing: focus on biomarkers of bone, cartilage, muscle, and brain tissue maintenance

Specific hallmarks are thought to underlie the ageing process and age-related functional decline. In this viewpoint, we put forward the hypothesis that disturbances in the process of tissue maintenance are an important common denominator that may lie in between specific hallmarks of ageing (i.e. damage and responses to damage) and their ultimate (patho)physiological consequences (i.e. functional decline and age-related disease). As a first step towards verifying or falsifying this hypothesis, it will be important to measure biomarkers of tissue maintenance in future studies in different study populations. The main aim of the current paper is to discuss potential biomarkers of tissue maintenance that could be used in such future studies. Among the many tissues that could have been chosen to explore our hypothesis, to keep the paper manageable, we chose to focus on a selected number of tissues, namely bone, cartilage, muscle, and the brain, which are important for mobility and cognition and affected in several common age-related diseases, including osteoporosis, osteoarthritis, sarcopenia, and neurodegenerative diseases. Furthermore, we discuss the advantages and limitations of potential biomarkers for use in (pre)clinical studies. The proposed biomarkers should be validated in future research, for example by measuring these in humans with different rates of ageing.

DNA methylation aging clocks: challenges and recommendations

Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.

DNA methylation profile is a quantitative measure of biological aging in children

DNA methylation changes within the genome can be used to predict human age. However, the existing biological age prediction models based on DNA methylation are predominantly adult-oriented. We established a methylation-based age prediction model for children (9-212 months old) using data from 716 blood samples in 11 DNA methylation datasets. Our elastic net model includes 111 CpG sites, mostly in genes associated with development and aging. The model performed well and exhibited high precision, yielding a 98% correlation between the DNA methylation age and the chronological age, with an error of only 6.7 months. When we used the model to assess age acceleration in children based on their methylation data, we observed the following: first, the aging rate appears to be fastest in mid-childhood, and this acceleration is more pronounced in autistic children; second, lead exposure early in life increases the aging rate in boys, but not in girls; third, short-term recombinant human growth hormone treatment has little effect on the aging rate of children. Our child-specific methylation-based age prediction model can effectively detect epigenetic changes and health imbalances early in life. This may thus be a useful model for future studies of epigenetic interventions for age-related diseases.

Association between sleep disordered breathing and epigenetic age acceleration: Evidence from the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Sleep disordered breathing (SDB) is a common disorder that results in oxidative stress and inflammation and is associated with multiple age-related health outcomes. Epigenetic age acceleration is a DNA methylation (DNAm)-based marker of fast biological aging. We examined the associations of SDB traits with epigenetic age acceleration.

METHODS

A sample of 622 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) had blood DNAm measured and underwent Type 2 in-home polysomnography that assessed apnea-hypopnea index (AHI), percentage of sleep time with oxygen saturation lower than 90% (Per90), and arousal index. DNAm data provided measures of DNAm-Age acceleration and DNAm-PhenoAge acceleration. The association of each SDB trait with age acceleration was estimated using linear regression, controlling for covariates. In secondary analyses, we studied the associations of SDB traits with epigenetic age acceleration 2-10 years after sleep study in 530 individuals from the Framingham Heart Study (FHS).

FINDINGS

In MESA, AHI was associated with greater DNAm-PhenoAge acceleration (β = 0.03; 95% CI [0.001, 0.06]). Arousal index was associated with greater DNAm-Age acceleration (β = 0.04; 95% CI [0.01, 0.07]). Both associations were stronger in women than men. In the secondary FHS analyses, Per90 was associated with greater DNAm-Age acceleration and this association was stronger in men.

INTERPRETATION

More severe SDB was associated with epigenetic age acceleration in both cohorts. Future work should prospectively study short- and long-term effects of SDB, and whether treatment reduces epigenetic age acceleration among those individuals with SBD.

FUNDING

National Institutes of Health.

Psychosocial stress and epigenetic aging

Aging is the single most important risk factor for diseases that are currently the leading causes of morbidity and mortality. However, there is considerable inter-individual variability in risk for aging-related disease, and studies suggest that biological age can be influenced by multiple factors, including exposure to psychosocial stress. Among markers of biological age that can be affected by stress, the present article focuses on the so-called measures of epigenetic aging: DNA methylation-based age predictors that are measured in a range of tissues, including the brain, and can predict lifespan and healthspan. We review evidence linking exposure to diverse types of psychosocial stress, including early-life stress, cumulative stressful experiences, and low socioeconomic status, with accelerated epigenetic aging as a putative mediator of the effects of psychosocial environment on health and disease. The chapter also discusses methodological differences that may contribute to discordant findings across studies to date and plausible mechanisms that may underlie the effects of stress on the aging epigenome. Future studies examining the effects of adversity on epigenetic and other indicators of biological weathering may provide important insights into the pathogenesis of aging-related disease states.

Epigenetic Aging: More Than Just a Clock When It Comes to Cancer

The incidence of cancer, adjusted for secular trends, is directly related to age, and advanced chronologic age is one of the most significant risk factors for cancer. Organismal aging is associated with changes at the molecular, cellular, and tissue levels and is affected by both genetic and environmental factors. The specific mechanisms through which these age-associated molecular changes contribute to the increased risk of aging-related disease, such as cancer, are incompletely understood. DNA methylation, a prominent epigenetic mark, also changes over a lifetime as part of an "epigenetic aging" process. Here, we give an update and review of epigenetic aging, in particular, the phenomena of epigenetic drift and epigenetic clock, with regard to its implication in cancer etiology. We discuss the discovery of the DNA methylation-based biomarkers for biological tissue age and the construction of various epigenetic age estimators for human clinical outcomes and health/life span. Recent studies in various types of cancer point to the significance of epigenetic aging in tumorigenesis and its potential use for cancer risk prediction. Future studies are needed to assess the potential clinical impact of strategies focused on lowering cancer risk by preventing premature aging or promoting healthy aging.

Independent and Combined Effects of Telomere Shortening and mtDNA4977 Deletion on Long-term Outcomes of Patients with Coronary Artery Disease

Aging is one of the main risk factors for cardiovascular disease, resulting in a progressive organ and cell decline. This study evaluated a possible joint impact of two emerging hallmarks of aging, leucocyte telomere length (LTL) and common mitochondrial DNA deletion (mtDNA⁴⁹⁷⁷), on major adverse cardiovascular events (MACEs) and all-cause mortality in patients with coronary artery disease (CAD). We studied 770 patients (673 males, 64.8 ± 8.3 years) with known or suspected stable CAD. LTL and mtDNA⁴⁹⁷⁷ deletion were assessed in peripheral blood using qRT-PCR. During a median follow-up of 5.4 ± 1.2 years, MACEs were 140 while 86 deaths were recorded. After adjustments for confounding risk factors, short LTLs and high mtDNA⁴⁹⁷⁷ deletion levels acted independently as predictors of MACEs (HR: 2.2, 95% CI: 1.2-3.9, p = 0.01 and HR: 1.7, 95% CI: 1.1-2.9, p = 0.04; respectively) and all-cause mortality events (HR: 2.1, 95% CI: 1.1-4.6, p = 0.04 and HR: 2.3, 95% CI: 1.1-4.9, p = 0.02; respectively). Patients with both short LTLs and high mtDNA⁴⁹⁷⁷ deletion levels had an increased risk for MACEs (HR: 4.3; 95% CI: 1.9-9.6; p = 0.0006) and all-cause mortality (HR: 6.0; 95% CI: 2.0-18.4; p = 0.001). The addition of mtDNA⁴⁹⁷⁷ deletion to a clinical reference model was associated with a significant net reclassification improvement (NRI = 0.18, p = 0.01). Short LTL and high mtDNA⁴⁹⁷⁷ deletion showed independent and joint predictive value on adverse cardiovascular outcomes and all-cause mortality in patients with CAD. These findings strongly support the importance of evaluating biomarkers of physiological/biological age, which can predict disease risk and mortality more accurately than chronological age.

Epigenetic Clock and Relative Telomere Length Represent Largely Different Aspects of Aging in the Berlin Aging Study II (BASE-II)

DNA methylation age (DNAm age; "epigenetic clock") has recently been described as highly correlated with chronological age. Several studies suggest that DNAm age reflects, at least in part, biological age. Here, we adapted a recently published methylation-sensitive single nucleotide primer extension method for epigenetic age estimation and calculated the DNAm age based on only seven cytosine-phosphate-guanine sites in 1,895 DNA samples of the Berlin Aging Study II. In a second step, we explored the relationship between this new potential measure of biological age with an established marker of biological age, relative leukocyte telomere length (rLTL), in the same cohort. Our results showed a positive and significant correlation between DNAm age estimation and chronological age (N = 1,895, Rs2 = .47), which persisted after adjustment for covariates (sex, leukocyte distribution, alcohol and smoking). We found a significant but weak negative association between DNAm age acceleration and rLTL in linear regression analysis adjusted for age, sex, alcohol and smoking (β = -0.002, p = .007). Therefore, DNAm age appears to be a promising biomarker in the analysis of phenotypes of aging, which are not (only) related to pathways associated with mitotic age as measured by rLTL.

The Possible Role of Telomere Length and Chemokines in the Aging Process: A Transdiagnostic Review in Psychiatry

Background:

Psychiatric disorders are common, reaching a worldwide prevalence of 29.2%. They are associated with a high risk of premature death and with accelerated aging in clinical, molecular and neuroimaging studies. Recently, there is strong evidence suggesting a possible role of telomere length and chemokines in aging processes in psychiatric disorders.

Objective:

We aimed to review the literature on telomere length and chemokines and its association with early aging in mental illnesses on a transdiagnostic approach.

Results:

The review highlights the association between psychiatric disorders and early aging. Several independent studies have reported shorter telomere length and dysregulations on levels of circulating chemokines in schizophrenia, bipolar disorder, major depressive disorder, and anxiety disorders, suggesting a complex interaction between these markers in a transdiagnostic level. However, studies have investigated the inflammatory markers and telomere shortening separately and associated with a particular diagnosis, rather than as a transdiagnostic biological feature.

Conclusion:

There is consistent evidence supporting the relationship between accelerated aging, telomere length, and chemokines in mental disorders, but they have been studied individually. Thus, more research is needed to improve the knowledge of accelerated senescence and its biomarkers in psychiatry, not only individually in each diagnosis, but also based on a transdiagnostic perspective. Moreover, further research should try to elucidate how the intricate association between the chemokines and telomeres together may contribute to the aging process in psychiatric disorders.

Hallmarks of senescence and aging

The complex process of biological aging, as an intrinsic feature of living beings, is the result of genetic and, to a greater extent, environmental factors and time. For many of the changes taking place in the body during aging, three factors are important: inflammation, immune aging and senescence (cellular aging, biological aging). Senescence is an irreversible form of long-term cell-cycle arrest, caused by excessive intracellular or extracellular stress or damage. The purpose of this cell-cycles arrest is to limit the proliferation of damaged cells, to eliminate accumulated harmful factors and to disable potential malignant cell transformation. As the biological age does not have to be in accordance with the chronological age, it is important to find specific hallmarks and biomarkers that could objectively determine the rate of age of a person. These biomarkers might be a valuable measure of physiological, i.e. biological age. Biomarkers should meet several criteria. For example, they have to predict the rate of aging, monitor a basic process that underlies the aging process, be able to be tested repeatedly without harming the person. In addition, biomarkers have to be indicators of biological processes, pathogenic processes or pharmacological responses to therapeutic intervention. It is considered that the telomere length is the weak biomarker (with poor predictive accuracy), and there is currently no reliable biomarker that meets all the necessary criteria.

Epigenetic Clocks and Allostatic Load Reveal Potential Sex-Specific Drivers of Biological Aging

Allostatic load (AL) and epigenetic clocks both attempt to characterize the accelerated aging of biological systems, but at present it is unclear whether these measures are complementary or distinct. This study examines the cross-sectional association of AL with epigenetic age acceleration (EAA) in a subsample of 490 community-dwelling older adults participating in The Irish Longitudinal study on Aging (TILDA). A battery of 14 biomarkers representing the activity of four different physiological systems: immunological, cardiovascular, metabolic, renal, was used to construct the AL score. DNA methylation age was computed according to the algorithms described by Horvath, Hannum, and Levine allowing for estimation of whether an individual is experiencing accelerated or decelerated aging. Horvath, Hannum, and Levine EAA correlated 0.05, 0.03, and 0.21 with AL, respectively. Disaggregation by sex revealed that AL was more strongly associated with EAA in men compared with women as assessed using Horvath’s clock. Metabolic dysregulation was a strong driver of EAA in men as assessed using Horvath and Levine’s clock, while metabolic and cardiovascular dysregulation were associated with EAA in women using Levine’s clock. Results indicate that AL and the epigenetic clocks are measuring different age-related variance and implicate sex-specific drivers of biological aging.

Testing Life Course Models Whereby Juvenile and Adult Adversity Combine to Influence Speed of Biological Aging

The present study extends prior research on the links between social adversity and aging by employing more comprehensive measures of adversity and a new gene expression index of aging. Hierarchical regression and 20 years of data from a sample of 381 black Americans were used to test models regarding the impact of social adversity on speed of aging. Consistent with the early life sensitivity model, early adversity continued to predict accelerated aging after controlling for adult adversity. Contrary to the pathway model, adult adversity was not related to aging following controls for early adversity. The cumulative stress model received partial support as high adversity during adulthood amplified the effect of early adversity on aging. Finally, consonant with the social change model, low adversity during adulthood buffered the effect of early adversity on aging. These findings held after controlling for health behaviors such as smoking, diet, and exercise.

Sex differences in the association between salivary telomere length and multimorbidity within the US Health & Retirement Study

Background

Telomere length is associated with several physical and mental health conditions, but whether it is a marker of multimorbidity is unclear. We investigated associations between telomere length and multimorbidity by sex.

Methods

Data from adults (N = 5,495) aged ≥50 years were taken from the US Health and Retirement Study (2008–14). Telomere length was measured in 2008 from salivary samples. The cross-sectional associations between telomere length and eight chronic health conditions were explored using logistic regression, adjusting for confounders and stratified by sex. Logistic, ordinal and multinomial regression models were calculated to explore relationships between telomere length and multimorbidity (using a binary variable and a sum of the number of health conditions) and the type of multimorbidity (no multimorbidity, physical multimorbidity, or multimorbidity including psychiatric problems). Using multilevel logistic regression, prospective relationships between telomere length and incident multimorbidity were also explored.

Results

In cross-sectional analyses, longer telomeres were associated with reduced likelihood of lung disease and psychiatric problems among men, but not women. Longer telomeres were associated with lower risk of multimorbidity that included psychiatric problems among men (OR=0.521, 95% CI: 0.284 to 0.957), but not women (OR=1.188, 95% CI: 0.771 to 1.831). Prospective analyses suggested little association between telomere length and the onset of multimorbidity in men (OR=1.378, 95% CI: 0.931 to 2.038) nor women (OR=1.224, 95% CI: 0.825 to 1.815).

Conclusions

Although telomere length does not appear to be a biomarker of overall multimorbidity, further exploration of the relationships is merited particularly for multimorbidity including psychiatric conditions among men.

Role of physical exercise in the regulation of epigenetic mechanisms in inflammation, cancer, neurodegenerative diseases, and aging process

The genetic heritage for decades has been considered to respond only to gene promoters or suppressors, with specific roles for oncogenes or tumor-suppressor genes. Epigenetics is progressively attracting increasing interest because it has demonstrated the capacity of these regulatory processes to regulate the gene expression without modifying gene sequence. Several factors may influence epigenetics, such as lifestyles including food selection. A role for physical exercise is emerging in the epigenetic regulation of gene expression. In this review, we resume physiological and pathological implications of epigenetic modification induced by the physical activity (PA). Inflammation and cancer mechanisms, immune system, central nervous system, and the aging process receive benefits due to PA through epigenetic mechanisms. Thus, the modulation of epigenetic processes by physical exercise positively influences prevention, development, and the course of inflammatory and cancer diseases, as well as neurodegenerative illnesses. This growing field of studies gives rise to a new role for PA as an option in prevention strategies and to integrate pharmacological therapeutic treatments.

The contribution of childhood adversity to cortisol measures of early life stress amongst infants in rural India: Findings from the early life stress sub-study of the SPRING cluster randomised controlled trial (SPRING-ELS)

BACKGROUND

The majority of the world's children live in low- and middle-income countries and face multiple obstacles to optimal wellbeing. The mechanisms by which adversities - social, cultural, psychological, environmental, economic - get 'under the skin' in the early days of life and become biologically embedded remain an important line of enquiry. We therefore examined the contribution of childhood adversity through pregnancy and the first year of life to hair and salivary cortisol measures of early life stress in the India SPRING home visits cluster RCT which aims to improve early childhood development.

METHODS

We assessed 22 adversities across four domains: socioeconomic, maternal stress, family-child relationship, and child and summed them to make a cumulative adversity score & quintiles, and four subscale scores. We cut 3 cm of hair from the posterior vertex and took three saliva samples from morning till late afternoon on each of two days (total six samples). We analysed both for cortisol concentration using ELISA techniques. We used multiple linear regression techniques to assess the relationship between cumulative adversity and log hair cortisol concentration and saliva diurnal slope and area under the curve.

RESULTS

We assessed 712 children for hair, and 752 children for saliva cortisol at 12 months of age. We found a strong positive relationship between adversity and hair cortisol; each additional adversity factor was associated with hair cortisol increases of 6.1% (95% CI 2.8, 9.4, p < 0.001) and the increase from adversity quintile one to five was 59.4%. Socioeconomic, relationship and child scales were independent predictors of hair cortisol (socioeconomic 6.4% (95% CI -0.4, 13.6); relationship 11.8% (95% CI 1.4, 23.2); child 7.9% (95% CI -0.5, 16.9). We did not find any association between any measures of adversity and either of the saliva cortisol outcomes.

DISCUSSION

This is the largest study of hair cortisol in young children, and the first in a low- and middle-income country setting. Whilst the short-term diurnal measures of cortisol did not appear to be linked with adversity, chronic exposure over several months appears to be strongly associated with cumulative adversity. These findings should spur further work to understand the specific ways in which adversity becomes biologically embedded, and how this can be tackled. They also lend support to ongoing action to tackle childhood adversity in communities around the world.

Network analysis of canine brain morphometry links tumour risk to oestrogen deficiency and accelerated brain ageing

Structural ‘brain age’ is a valuable but complex biomarker for several brain disorders. The dog is an unrivalled comparator for neurological disease modeling, however canine brain morphometric diversity creates computational and statistical challenges. Using a data-driven approach, we explored complex interactions between patient metadata, brain morphometry, and neurological disease. Twenty-four morphometric parameters measured from 286 canine brain magnetic resonance imaging scans were combined with clinical parameters to generate 9,438 data points. Network analysis was used to cluster patients according to their brain morphometry profiles. An ‘aged-brain’ profile, defined by a small brain width and volume combined with ventriculomegaly, was revealed in the Boxer breed. Key features of this profile were paralleled in neutered female dogs which, relative to un-neutered females, had an 11-fold greater risk of developing brain tumours. Boxer dog and geriatric dog groups were both enriched for brain tumour diagnoses, despite a lack of geriatric Boxers within the cohort. Our findings suggest that advanced brain ageing enhances brain tumour risk in dogs and may be influenced by oestrogen deficiency—a risk factor for dementia and brain tumours in humans. Morphometric features of brain ageing in dogs, like humans, might better predict neurological disease risk than patient chronological age.

The Older Finnish Twin Cohort - 45 Years of Follow-up

The older Finnish Twin Cohort (FTC) was established in 1974. The baseline survey was in 1975, with two follow-up health surveys in 1981 and 1990. The fourth wave of assessments was done in three parts, with a questionnaire study of twins born during 1945-1957 in 2011-2012, while older twins were interviewed and screened for dementia in two time periods, between 1999 and 2007 for twins born before 1938 and between 2013 and 2017 for twins born in 1938-1944. The content of these wave 4 assessments is described and some initial results are described. In addition, we have invited twin-pairs, based on response to the cohortwide surveys, to participate in detailed in-person studies; these are described briefly together with key results. We also review other projects based on the older FTC and provide information on the biobanking of biosamples and related phenotypes.

DNA methylation-based estimator of telomere length

Telomere length (TL) is associated with several aging-related diseases. Here, we present a DNA methylation estimator of TL (DNAmTL) based on 140 CpGs. Leukocyte DNAmTL is applicable across the entire age spectrum and is more strongly associated with age than measured leukocyte TL (LTL) (r ~-0.75 for DNAmTL versus r ~ -0.35 for LTL). Leukocyte DNAmTL outperforms LTL in predicting: i) time-to-death (p=2.5E-20), ii) time-to-coronary heart disease (p=6.6E-5), iii) time-to-congestive heart failure (p=3.5E-6), and iv) association with smoking history (p=1.21E-17). These associations are further validated in large scale methylation data (n=10k samples) from the Framingham Heart Study, Women's Health Initiative, Jackson Heart Study, InChianti, Lothian Birth Cohorts, Twins UK, and Bogalusa Heart Study. Leukocyte DNAmTL is also associated with measures of physical fitness/functioning (p=0.029), age-at-menopause (p=0.039), dietary variables (omega 3, fish, vegetable intake), educational attainment (p=3.3E-8) and income (p=3.1E-5). Experiments in cultured somatic cells show that DNAmTL dynamics reflect in part cell replication rather than TL per se. DNAmTL is not only an epigenetic biomarker of replicative history of cells, but a useful marker of age-related pathologies that are associated with it.

The metabolomics side of frailty: Toward personalized medicine for the aged

Frailty encompasses several domains (i.e., metabolic, physical, cognitive). The multisystem derangements underlying frailty pathophysiology, its phenotypic heterogeneity, and the fluctuations of individuals across severity states have hampered a comprehensive appraisal of the condition. Circulating biomarkers emerged as an alleged tool for capturing this complexity and, as proxies for organismal metabolic changes, may hold the advantages of: 1) supporting diagnosis, 2) tracking the progression, 3) assisting healthcare professionals in clinical and therapeutic decision-making, and 4) verifying the efficacy of an intervention before measurable clinical manifestations occur. Among available analytical tools, metabolomics are able to identify and quantify the (ideally) whole repertoire of small molecules in biological matrices (i.e., cells, tissues, and biological fluids). Results of metabolomics analysis may define the final output of genome-environment interactions at the individual level. This entire collection of metabolites is called "metabolome" and is highly dynamic. Here, we discuss how monitoring the dynamics of metabolic profiles may provide a read-out of the environmental and clinical disturbances affecting cell homeostasis in frailty-associated conditions.

Age-Related DNA Methylation Changes: Potential Impact on Skeletal Muscle Aging in Humans

Human aging is accompanied by a decline in muscle mass and muscle function, which is commonly referred to as sarcopenia. Sarcopenia is associated with detrimental clinical outcomes, such as a reduced quality of life, frailty, an increased risk of falls, fractures, hospitalization, and mortality. The exact underlying mechanisms of sarcopenia are poorly delineated and the molecular mechanisms driving the development and progression of this disorder remain to be uncovered. Previous studies have described age-related differences in gene expression, with one study identifying an age-specific expression signature of sarcopenia, but little is known about the influence of epigenetics, and specially of DNA methylation, in its pathogenesis. In this review, we will focus on the available knowledge in literature on the characterization of DNA methylation profiles during skeletal muscle aging and the possible impact of physical activity and nutrition. We will consider the possible use of the recently developed DNA methylation-based biomarkers of aging called epigenetic clocks in the assessment of physical performance in older individuals. Finally, we will discuss limitations and future directions of this field.

Accelerating research on biological aging and mental health: Current challenges and future directions

Aging is associated with complex biological changes that can be accelerated, slowed, or even temporarily reversed by biological and non-biological factors. This article focuses on the link between biological aging, psychological stressors, and mental illness. Rather than comprehensively reviewing this rapidly expanding field, we highlight challenges in this area of research and propose potential strategies to accelerate progress in this field. This effort requires the interaction of scientists across disciplines - including biology, psychiatry, psychology, and epidemiology; and across levels of analysis that emphasize different outcome measures - functional capacity, physiological, cellular, and molecular. Dialogues across disciplines and levels of analysis naturally lead to new opportunities for discovery but also to stimulating challenges. Some important challenges consist of 1) establishing the best objective and predictive biological age indicators or combinations of indicators, 2) identifying the basis for inter-individual differences in the rate of biological aging, and 3) examining to what extent interventions can delay, halt or temporarily reverse aging trajectories. Discovering how psychological states influence biological aging, and vice versa, has the potential to create novel and exciting opportunities for healthcare and possibly yield insights into the fundamental mechanisms that drive human aging.

Health and Aging: Unifying Concepts, Scores, Biomarkers and Pathways

Despite increasing research efforts, there is a lack of consensus on defining aging or health. To understand the underlying processes, and to foster the development of targeted interventions towards increasing one's health, there is an urgent need to find a broadly acceptable and useful definition of health, based on a list of (molecular) features; to operationalize features of health so that it can be measured; to identify predictive biomarkers and (molecular) pathways of health; and to suggest interventions, such as nutrition and exercise, targeted at putative causal pathways and processes. Based on a survey of the literature, we propose to define health as a state of an individual characterized by the core features of physiological, cognitive, physical and reproductive function, and a lack of disease. We further define aging as the aggregate of all processes in an individual that reduce its wellbeing, that is, its health or survival or both. We define biomarkers of health by their attribute of predicting future health better than chronological age. We define healthspan pathways as molecular features of health that relate to each other by belonging to the same molecular pathway. Our conceptual framework may integrate diverse operationalizations of health and guide precision prevention efforts.

Comparability of biological aging measures in the National Health and Nutrition Examination Study, 1999-2002

BACKGROUND

Biological processes of aging are thought to be modifiable causes of many different chronic diseases. Measures of biological aging could provide sensitive endpoints for studies of risk factors hypothesized to shorten healthy lifespan and/or interventions that extend it. But uncertainty remains about how to measure biological aging and if proposed measures assess the same thing.

METHOD

We tested four proposed measures of biological aging that could be quantified with available data from the National Health and Nutrition Examination Survey (NHANES), Klemera-Doubal method (KDM) Biological Age, homeostatic dysregulation, Levine Method (LM) Biological Age, and leukocyte telomere length.

RESULTS

We analyzed data collected during 1999-2002, when all four biological aging meausres could be taken. Participants' KDM biological ages, homeostatic dysregulation levels, LM biological ages, and telomere length were all correlated with their chronological ages. KDM Biological Age, homeostatic dysregulation, and LM Biological Age were all correlated with one another, but these measures were uncorrelated with telomere length. Participants' with more advanced biological aging performed worse on tests of physical, cognitive, and perceptual functioning and reported more limitations to their daily activities and more pain, and rated themselves as being in worse health. In parallel, participants with risk factors for shorter healthy lifespan exhibited more advanced biological aging. In both sets of analyses, effect-sizes tended to be larger for KDM Biological Age, homeostatic dysregulation, and LM Biological Age as compared to telomere length.

DISCUSSION

The cellular-level aging biomarker telomere length may measure different aspects of the aging process as compared to the patient-level physiological composite measures KDM Biological Age, homeostatic dysregulation, and LM Biological Age. Studies aiming to test if risk factors accelerate aging or if interventions may slow aging should not treat proposed measures of aging as interchangeable.

The effect of early discrimination on accelerated aging among African Americans

OBJECTIVE

This study examined the role of depressive symptoms in mediating the relationship between early life experiences of racial discrimination and accelerated aging in adulthood for African Americans (i.e., prediction over a 19-year period, from ages 10 to 29) after adjusting for gender and health behaviors.

METHOD

Longitudinal self-report data over 7 waves of data collection from the Family and Community Health Study were utilized. The sample included 368 African Americans with usable gene expression data to compute accelerated aging, as well as complete data on all self-report variables including racial discrimination (Schedule of Racist Events) and depression (Diagnostic Interview Schedule for Children-Version 4). Blood was collected by antecubital blood draws from participants at age 29. The proposed model was tested by path analysis.

RESULTS

Findings revealed that high discrimination at ages 10-15 was associated with depression at ages 20-29 (β = .19, p = .001), controlling for depression at ages 10-15, which, in turn, was related to accelerated cellular-level aging (β = .11, p = .048) after controlling for gender, alcohol consumption, and cigarette use. The indirect effect of racial discrimination on aging through depression at ages 20-29 was significant (β = .021, 95% confidence interval [.001, .057]), accounting for 32.3% of the total variance.

CONCLUSION

These findings support research conceptualizations that early life stress due to racial discrimination lead to sustained negative affective states continuing into young adulthood that confer risk for accelerated aging and possibly premature disease and mortality in African Americans. These findings advance knowledge of potential underlying mechanisms that influence racial health disparities. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Optimism is not associated with two indicators of DNA methylation aging

Evidence indicates associations between higher optimism and reduced risk of age-related conditions and premature mortality. This suggests optimism is a positive health asset, but research identifying potential biological mechanisms underlying these associations remains limited. One potential pathway is slower cellular aging, which may delay age-related deterioration in health. Data were from the Women’s Health Initiative (WHI) (N=3,298) and the Veterans Affairs Normative Aging Study (NAS) (N=514), and included dispositional and explanatory style optimism measures. We evaluated whether higher optimism was associated with metrics suggestive of less cellular aging, as indicated by two DNA methylation algorithms, intrinsic (IEAA) and extrinsic epigenetic age acceleration (EEAA); these algorithms represent accelerated biologic aging that exceeds chronological age. We used linear regression models to test our hypothesis while considering several covariates (sociodemographics, depressive symptoms, health behaviors). In both cohorts, we found consistently null associations of all measures of optimism with both measures of DNA methylation aging, regardless of covariates considered. For example, in fully-adjusted models, dispositional optimism was not associated with either IEAA (WHI:β=0.02; 95% Confidence Interval [CI]:-0.15-0.20; NAS:β=-0.06; 95% CI:-0.56-0.44) or EEAA (WHI:β=-0.04; 95% CI: -0.26-0.17; NAS:β=-0.17; 95% CI: -0.80-0.46). Higher optimism was not associated with reduced cellular aging as measured in this study.

DNA methylation-based biomarkers and the epigenetic clock theory of ageing

Identifying and validating molecular targets of interventions that extend the human health span and lifespan has been difficult, as most clinical biomarkers are not sufficiently representative of the fundamental mechanisms of ageing to serve as their indicators. In a recent breakthrough, biomarkers of ageing based on DNA methylation data have enabled accurate age estimates for any tissue across the entire life course. These 'epigenetic clocks' link developmental and maintenance processes to biological ageing, giving rise to a unified theory of life course. Epigenetic biomarkers may help to address long-standing questions in many fields, including the central question: why do we age?

Envisioning Arti's 'Cadillac study' to assess aging trajectories in cancer survivors

The "Cadillac Study" was the term Arti Hurria, MD often used to articulate her vision of the optimal study to investigate the effects of cancer and its treatments on aging trajectories. In her opinion, this study needed to be designed for near-term clinical translation and have the ability to discern subpopulations of cancer survivors at greatest risk for poor outcomes. The purpose of this commentary is to describe, to the best of our knowledge, Arti's Cadillac Study based on personal conversations, group discussions, and her substantial portfolio of research. We describe the necessary study components of the Cadillac Study and discuss approaches to circumvent perceived barriers. In Arti's honor, our goal is to bring awareness and new perspectives to research on the aging consequences of cancer and cancer treatment to move the field forward.

Risk-period-cohort approach for averting identification problems in longitudinal models

In epidemiology, gerontology, human development and the social sciences, age-period-cohort (APC) models are used to study the variability in trajectories of change over time. A well-known issue exists in simultaneously identifying age, period and birth cohort effects, namely that the three characteristics comprise a perfectly collinear system. That is, since age = period-cohort, only two of these effects are estimable at a time. In this paper, we introduce an alternative framework for considering effects relating to age, period and birth cohort. In particular, instead of directly modeling age in the presence of period and cohort effects, we propose a risk modeling approach to characterize age-related risk (i.e., a hybrid of multiple biological and sociological influences to evaluate phenomena associated with growing older). The properties of this approach, termed risk-period-cohort (RPC), are described in this paper and studied by simulations. We show that, except for pathological circumstances where risk is uniquely determined by age, using such risk indices obviates the problem of collinearity. We also show that the size of the chronological age effect in the risk prediction model associates with the correlation between a risk index and chronological age and that the RPC approach can satisfactorily recover cohort and period effects in most cases. We illustrate the advantages of RPC compared to traditional APC analysis on 27496 individuals from NHANES survey data (2005-2016) to study the longitudinal variability in depression screening over time. Our RPC method has broad implications for examining processes of change over time in longitudinal studies.

Public health research needs for molecular epidemiology and to emphasize homeostasis - could the omnipotent endopeptidase inhibitor α-2-macroglobulin be a meaningful biomarker?

Public health authorities in low- and middle-income countries face dramatic challenges in handling rapidly increasing non-communicable diseases (NCDs), due to the epidemiological- and particularly nutritional transition. Among major reasons for the development of NCDs are smoking and alcohol, but overnutrition and obesity are also major threats to population health. Obesity is related to diabetes and cancer, but also has a genetic background. It is difficult to recommend a healthy nutrition. This is because of conflicting nutritional conceptions, and given the complexity of human metabolism understanding this topic can be difficult for the laymen.  Public health measures advocating physical activity and refraining from high intake of energy, sugar and soft drinks need to be enhanced by supporting the ‘intrinsic motivation’ to preserve a good health. The mission of public health should be to increase awareness about the complexity of human metabolism, and the involvement of genetic and epigenetics in health and diseases. To maintain homeostasis, means to keep an optimal relationship between catabolism and synthesis, seems to be of particular interest. Preconditions for this is, that public health institutions within the administration- and academic sector follow up developments in life science and molecular biology and conduct population-based research making use of molecular epidemiology, especially those related to key metabolic steps and maintenance of ‘homeostasis’, in balancing catabolism and anabolism. A prospective biomarker for this situation might be α-2-macroglobulin.

Further defence of legal age change: a reply to the critics

In 'Moral case for legal age change', I argue that sometimes people should be allowed to change their age. I refute six immediate objections against the view that age change is permissible. I argue that the objections cannot show that legal age change should always be prohibited. In this paper, I consider some further objections against legal age change raised by Iain Brassington, Toni Saad and William Simkulet. I argue that the objections fail to show that age change should never be allowed.