Methylomic survival predictors, frailty, and mortality

The epigenetics of frailty

The conceptual change of frailty, from a physical to a biopsychosocial phenotype, expanded the field of frailty, including social and behavioral domains with critical interaction between different frailty models. Environmental exposures - including physical exercise, psychosocial factors and diet - may play a role in the frailty pathophysiology. Complex underlying mechanisms involve the progressive interactions of genetics with epigenetics and of multimorbidity with environmental factors. Here we review the literature on possible mechanisms explaining the association between epigenetic hallmarks (i.e., global DNA methylation, DNA methylation age acceleration and microRNAs) and frailty, considered as biomarkers of aging. Frailty could be considered the result of environmental epigenetic factors on biological aging, caused by conflicting DNA methylation age and chronological age.

Frailty and the Interactions between Skeletal Muscle, Bone, and Adipose Tissue-Impact on Cardiovascular Disease and Possible Therapeutic Measures

Frailty is a global health problem that impacts clinical practice. It is complex, having a physical and a cognitive component, and it is the result of many contributing factors. Frail patients have oxidative stress and elevated proinflammatory cytokines. Frailty impairs many systems and results in a reduced physiological reserve and increased vulnerability to stress. It is related to aging and to cardiovascular diseases (CVD). There are few studies on the genetic factors of frailty, but epigenetic clocks determine age and frailty. In contrast, there is genetic overlap of frailty with cardiovascular disease and its risk factors. Frailty is not yet considered a risk factor for CVD. It is accompanied by a loss and/or poor functioning of muscle mass, which depends on fiber protein content, resulting from the balance between protein breakdown and synthesis. Bone fragility is also implied, and there is a crosstalk between adipocytes, myocytes, and bone. The identification and assessment of frailty is difficult, without there being a standard instrument to identify or treat it. Measures to prevent its progression include exercises, as well as supplementing the diet with vitamin D and K, calcium, and testosterone. In conclusion, more research is needed to better understand frailty and to avoid complications in CVD.

Beyond Chronological Age: A Multidimensional Approach to Survival Prediction in Older Adults

BACKGROUND

There is a growing interest in generating precise predictions of survival to improve the assessment of health and life-improving interventions. We aimed to (a) test if observable characteristics may provide a survival prediction independent of chronological age; (b) identify the most relevant predictors of survival; and (c) build a metric of multidimensional age.

METHODS

Data from 3 095 individuals aged ≥60 from the Swedish National Study on Aging and Care in Kungsholmen. Eighty-three variables covering 5 domains (diseases, risk factors, sociodemographics, functional status, and blood tests) were tested in penalized Cox regressions to predict 18-year mortality.

RESULTS

The best prediction of mortality at different follow-ups (area under the receiver operating characteristic curves [AUROCs] 0.878-0.909) was obtained when 15 variables from all 5 domains were tested simultaneously in a penalized Cox regression. Significant prediction improvements were observed when chronological age was included as a covariate for 15- but not for 5- and 10-year survival. When comparing individual domains, we find that a combination of functional characteristics (ie, gait speed, cognition) gave the most accurate prediction, with estimates similar to chronological age for 5- (AUROC 0.836) and 10-year (AUROC 0.830) survival. Finally, we built a multidimensional measure of age by regressing the predicted mortality risk on chronological age, which displayed a stronger correlation with time to death (R = -0.760) than chronological age (R = -0.660) and predicted mortality better than widely used geriatric indices.

CONCLUSIONS

Combining easily accessible characteristics can help in building highly accurate survival models and multidimensional age metrics with potentially broad geriatric and biomedical applications.

Associations of DNA methylation algorithms of aging and cancer risk: Results from a prospective cohort study

Background

Previous studies have shown that three DNA methylation (DNAm) based algorithms of aging, DNAm PhenoAge acceleration (AgeAccelPheno), DNAm GrimAge acceleration (AgeAccelGrim), and mortality risk score (MRscore), to be strong predictors of mortality and aging related outcomes. We aimed to investigate if and to what extent these algorithms predict cancer.

Methods

In four subsets (n = 727, 1003, 910, and 412) of a population-based cohort from Germany, DNA methylation in whole blood was measured using the Infinium Methylation EPIC BeadChip kit or the Infinium HumanMethylation450K BeadChip Assay (Illumina.Inc, San Diego, CA, USA). AgeAccelPheno, AgeAccelGrim, and a revised MRscore based on 8 CpGs only (MRscore-8CpGs), were calculated. Hazard ratios (HRs) were calculated to assess associations of the three DNAm algorithms with total cancer risk and risk of invasive breast, lung, prostate, and colorectal cancer incidence.

Findings

During 17 years of follow-up, a total of 697 malignant tumors (thereof breast cancer = 75, lung cancer = 146, prostate cancer = 114, colorectal cancer = 155) were observed. All three algorithms showed strong positive associations with lung cancer risk in a dose response manner, with adjusted HRs per SD increase in AgeAccelPheno, AgeAccelGrim, and MRscore-8CpGs, of 1·37 (1·03-1·82), 1·74 (1·11-2·73), and 2·06 (1·39-3·06), respectively. By contrast, strong inverse associations were seen with breast cancer risk [adjusted HRs 0·65 (0·49-0·86), 0·45 (0·25-0·80), and 0·42 (0·25-0·70), respectively]. Weak positive associations of MRscore-8CpGs were seen with total cancer risk.

Interpretation

The DNAm algorithms, particularly the MRscore-8CpGs, have potential to contribute to site-specific cancer risk prediction.

Funding

The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany). The work of Xiangwei Li was supported by a grant from Fondazione Cariplo (Bando Ricerca Malattie invecchiamento, #2017-0653).

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

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

Seven-CpG DNA Methylation Age Determined by Single Nucleotide Primer Extension and Illumina's Infinium MethylationEPIC Array Provide Highly Comparable Results

DNA methylation age (DNAm age, epigenetic clock) is a novel and promising biomarker of aging. It is calculated from the methylation fraction of specific cytosine phosphate guanine sites (CpG sites) of genomic DNA. Several groups have proposed epigenetic clock algorithms and these differ mostly regarding the number and location of the CpG sites considered and the method used to assess the methylation status. Most epigenetic clocks are based on a large number of CpGs, e.g. as measured by DNAm microarrays. We have recently evaluated an epigenetic clock based on the methylation fraction of seven CpGs that were determined by methylation-sensitive single nucleotide primer extension (MS-SNuPE). This method is more cost-effective when compared to array-based technologies as only a few CpGs need to be examined. However, there is only little data on the correspondence in epigenetic age estimation using the 7-CpG clock and other algorithms. To bridge this gap, in this study we measured the 7-CpG DNAm age using two methods, via MS-SNuPE and via the MethylationEPIC array, in a sample of 1,058 participants of the Berlin Aging Study II (BASE-II), assessed as part of the GendAge study. On average, participants were 75.6 years old (SD: 3.7, age range: 64.9-90.0, 52.6% female). Agreement between methods was assessed by Bland-Altman plots. DNAm age was highly correlated between methods (Pearson's r = 0.9) and Bland-Altman plots showed a difference of 3.1 years. DNAm age by the 7-CpG formula was 71.2 years (SD: 6.9 years, SNuPE) and 68.1 years (SD: 6.4 years, EPIC array). The mean of difference in methylation fraction between methods for the seven individual CpG sites was between 0.7 and 13 percent. To allow direct conversion of DNAm age obtained from both methods we developed an adjustment formula with a randomly selected training set of 529 participants using linear regression. After conversion of the Illumina data in a second and independent validation set, the adjusted DNAm age was 71.44 years (SD: 6.1 years, n = 529). In summary, we found the results of DNAm clocks to be highly comparable. Furthermore, we developed an adjustment formula that allows for direct conversion of DNAm age estimates between methods and enables one singular clock to be used in studies that employ either the Illumina or the SNuPE method.

Epidemiological and genetic overlap among biological aging clocks: New challenges in biogerontology

Estimators of biological age (BA) - defined as the hypothetical underlying age of an organism - have attracted more and more attention in the last years, especially after the advent of new algorithms based on machine learning and genetic markers. While different aging clocks reportedly predict mortality in the general population, very little is known on their overlap. Here we review the evidence reported so far to support the existence of a partial overlap among different BA acceleration estimators, both from an epidemiological and a genetic perspective. On the epidemiological side, we review evidence supporting shared and independent influence on mortality risk of different aging clocks - including telomere length, brain, blood and epigenetic aging - and provide an overview of how an important exposure like diet may affect the different aging systems. On the genetic side, we apply linkage disequilibrium score regression analyses to support the existence of partly shared genomic overlap among these aging clocks. Through multivariate analysis of published genetic associations with these clocks, we also identified the most associated variants, genes, and pathways, which may affect common mechanisms underlying biological aging of different systems within the body. Based on our analyses, the most implicated pathways were involved in inflammation, lipid and carbohydrate metabolism, suggesting them as potential molecular targets for future anti-aging interventions. Overall, this review is meant as a contribution to the knowledge on the overlap of aging clocks, trying to clarify their shared biological basis and epidemiological implications.

Comparative validation of three DNA methylation algorithms of ageing and a frailty index in relation to mortality: results from the ESTHER cohort study

Background

Three DNA methylation (DNAm) based algorithms, DNAm PhenoAge acceleration (AgeAccelPheno), DNAm GrimAge acceleration (AgeAccelGrim), and mortality risk score (MRscore), based on methylation in 513, 1030, and 10 CpGs, respectively, were established to predict health outcomes and mortality. We aimed to compare and validate the predictive ability of these scores and frailty in relation to mortality in a population-based cohort from Germany.

Methods

DNA methylation in whole blood was measured by the Infinium Methylation EPIC BeadChip kit (EPIC, Illumina, San Diego, CA, USA) in two random subsets of the ESTHER cohort study (n = 741 and n = 1030). AgeAccelPheno, AgeAccelGrim, and a revised MRscore to adapt EPIC, the MRscore with 8 CpGs (MRscore-8CpGs), were calculated. Frailty was assessed by a frailty index (FI).

Findings

During 17 years of follow-up, 458 deaths were observed. All DNAm algorithms and FI were positively correlated with each other. AgeAccelPheno, AgeAccelGrim, MRscore, and FI showed independent associations with all-cause mortality [hazard ratio (95% CI) per SD increase = 1·32 (1·19-1·46), 1·47 (1·32-1·64), 1·73 (1·49-2·01), and 1·31 (1·20-1·43), respectively]. Harrell's C-statistic was 0·710 for a model predicting mortality by age, sex, and leukocyte composition and increased to 0·759 in a model including MRscore-8CpGs and FI. The predictive performance was further improved (Harrell's C-statistic = 0·766) when additionally including AgeAccelPheno and AgeAccelGrim into the model.

Interpretation

The combination of a DNA methylation score based on 8 CpGs only and an easy to ascertain frailty index may strongly enhance mortality prediction beyond age and sex.

Funding

The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany). The work of Xiangwei Li was supported by a grant from Fondazione Cariplo (Bando Ricerca Malattie invecchiamento, #2017-0653).

Epigenetic age is associated with baseline and 3-year change in frailty in the Canadian Longitudinal Study on Aging

BACKGROUND

The trajectory of frailty in older adults is important to public health; therefore, markers that may help predict this and other important outcomes could be beneficial. Epigenetic clocks have been developed and are associated with various health-related outcomes and sociodemographic factors, but associations with frailty are poorly described. Further, it is uncertain whether newer generations of epigenetic clocks, trained on variables other than chronological age, would be more strongly associated with frailty than earlier developed clocks. Using data from the Canadian Longitudinal Study on Aging (CLSA), we tested the hypothesis that clocks trained on phenotypic markers of health or mortality (i.e., Dunedin PoAm, GrimAge, PhenoAge and Zhang in Nat Commun 8:14617, 2017) would best predict changes in a 76-item frailty index (FI) over a 3-year interval, as compared to clocks trained on chronological age (i.e., Hannum in Mol Cell 49:359-367, 2013, Horvath in Genome Biol 14:R115, 2013, Lin in Aging 8:394-401, 2016, and Yang Genome Biol 17:205, 2016).

RESULTS

We show that in 1446 participants, phenotype/mortality-trained clocks outperformed age-trained clocks with regard to the association with baseline frailty (mean = 0.141, SD = 0.075), the greatest of which is GrimAge, where a 1-SD increase in ΔGrimAge (i.e., the difference from chronological age) was associated with a 0.020 increase in frailty (95% CI 0.016, 0.024), or ~ 27% relative to the SD in frailty. Only GrimAge and Hannum (Mol Cell 49:359-367, 2013) were significantly associated with change in frailty over time, where a 1-SD increase in ΔGrimAge and ΔHannum 2013 was associated with a 0.0030 (95% CI 0.0007, 0.0050) and 0.0028 (95% CI 0.0007, 0.0050) increase over 3 years, respectively, or ~ 7% relative to the SD in frailty change.

CONCLUSION

Both prevalence and change in frailty are associated with increased epigenetic age. However, not all clocks are equally sensitive to these outcomes and depend on their underlying relationship with chronological age, healthspan and lifespan. Certain clocks were significantly associated with relatively short-term changes in frailty, thereby supporting their utility in initiatives and interventions to promote healthy aging.

No association between frailty index and epigenetic clocks in Italian semi-supercentenarians

Centenarians experience successful ageing, although they still present high heterogeneity in their health status. The frailty index is a biomarker of biological age, able to capture such heterogeneity, even at extreme old age. At the same time, other biomarkers (e.g., epigenetic clocks) may be informative the biological age of the individual and potentially describe the ageing status in centenarians. In this article, we explore the relationship between epigenetic clocks and frailty index in a cohort of Italian centenarians. No association was reported, suggesting that these two approaches may describe different aspects of the same ageing process.

Frailty in Lung Transplantation - Candidate Assessment and Optimization

The concept of frailty has gained considerable interest in clinical solid organ transplantation over the past decade. Frailty as a phenotypic construct to describe a patient's risk from biologic stresses, has an impact on posttransplant survival. There is keen interest in characterizing frailty in lung transplantation, both to determine which patients are suitable candidates for listing and also to prepare for their care in the aftermath of lung transplantation. Here we review the current status of research on frailty in lung transplant candidates and recipients. This review will highlight areas of uncertainty for frailty in clinical lung transplantation which are likely to impact the state-of-the-art in the field for the next decade.

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.

Whole blood DNA methylation aging markers predict colorectal cancer survival: a prospective cohort study

Background

Blood DNA methylation-based aging algorithms predict mortality in the general population. We investigated the prognostic value of five established DNA methylation aging algorithms for patients with colorectal cancer (CRC).

Methods

AgeAccelHorvath, AgeAccelHannum, DNAmMRscore, AgeAccelPheno and AgeAccelGrim were constructed using whole blood epi-genomic data from 2206 CRC patients. After a median follow-up of 6.2 years, 1079 deaths were documented, including 596 from CRC. Associations of the aging algorithms with survival outcomes were evaluated using the Cox regression and survival curves. Harrell’s C-statistics were computed to investigate predictive performance.

Results

Adjusted hazard ratios (95% confidence intervals) of all-cause mortality for patients in the third compared to the first tertile were 1.66 (1.32, 2.09) for the DNAmMRscore, 1.35 (1.14, 1.59) for AgeAccelPheno and 1.65 (1.37, 2.00) for AgeAccelGrim, even after adjustment for age, sex and stage. AgeAccelHorvath and AgeAccelHannum were not associated with all-cause or CRC-specific mortality. In stage-specific analyses, associations were much stronger for patients with early or intermediate stage cancers (stages I, II and III) than for patients with metastatic (stage IV) cancers. Associations were weaker and less often statistically significant for CRC-specific mortality. Adding DNAmMRscore, AgeAccelPheno or AgeAccelGrim to models including age, sex and tumor stage improved predictive performance moderately.

Conclusions

DNAmMRscore, AgeAccelPheno and AgeAccelGrim could serve as non-invasive CRC prognostic biomarkers independent of other commonly used markers. Further research should aim for tailoring and refining such algorithms for CRC patients and to explore their value for enhanced prediction of treatment success and treatment decisions.

Childhood exposure to hunger: associations with health outcomes in later life and epigenetic markers

Aim: To assess associations of early exposure to hunger with depressive symptoms and cardiovascular disease (CVD) and to investigate possible epigenetic pathways. Patients & methods: Data were based on a German population-based cohort of older adults (n = 9631). Regression models were performed for health outcomes in later life. An epigenome-wide association study for early-life exposure to hunger was performed in a subgroup (n = 2221) with whole blood DNA methylation data. Results: Childhood exposure to hunger was associated with CVD and depressive symptoms in later life. Prenatal or infant exposure was strongly associated with depressive symptoms. No CpG reached epigenome-wide significance after multiple testing correction. Conclusion: Childhood hunger is a risk factor for depressive symptoms and CVD at older age. DNA methylation could not explain this association.

A simple, rapid, interpretable, actionable and implementable digital PCR based mortality index

Mortality assessments are conducted for both civil and commercial purposes. Recent advances in epigenetics have resulted in DNA methylation tools to assess risk and aid in this task. However, widely available array-based algorithms are not readily translatable into clinical tools and do not provide a good foundation for clinical recommendations. Further, recent work shows evidence of heritability and possible racial bias in these indices. Using a publicly available array data set, the Framingham Heart Study (FHS), we develop and test a five-locus mortality-risk algorithm using only previously validated methylation biomarkers that have been shown to be free of racial bias, and that provide specific assessments of smoking, alcohol consumption, diabetes and heart disease. We show that a model using age, sex and methylation measurements at these five loci outperforms the 513 probe Levine index and approximates the predictive power of the 1030 probe GrimAge index. We then show each of the five loci in our algorithm can be assessed using a more powerful, reference-free digital PCR approach, further demonstrating that it is readily clinically translatable. Finally, we show the loci do not reflect ethnically specific variation. We conclude that this algorithm is a simple, yet powerful tool for assessing mortality risk. We further suggest that the output from this or similarly derived algorithms using either array or digital PCR can be used to provide powerful feedback to patients, guide recommendations for additional medical assessments, and help monitor the effect of public health prevention interventions.

Subjective mental health, incidence of depressive symptoms in later life, and the role of epigenetics: results from two longitudinal cohort studies

The role of self-perceived general health in predicting morbidity and mortality among older people is established. The predictive value of self-perceived mental health and of its possible biological underpinnings for future depressive symptoms is unexplored. This study aimed to assess the role of mental health-related quality of life (HRQOL) and of its epigenetic markers in predicting depressive symptoms among older people without lifetime history of depression. Data were based on a subgroup (n = 1 492) of participants of the longitudinal ESTHER study. An epigenome-wide association study (EWAS) of mental HRQOL was conducted using DNA from baseline whole blood samples and logistic regression analyses were performed to assess the predictive value of methylation beta values of EWAS identified CpGs for incidence of depressive symptoms in later life. The methylation analyses were replicated in the independent KORA cohort (n = 890) and a meta-analysis of the two studies was conducted. Results of the meta-analysis showed that participants with beta values of cg27115863 within quartile 1 (Q₁) had nearly a two-fold increased risk of developing depressive symptoms compared to participants with beta values within Q₄ (OR_Q1vsQ4= 1.80; CI 1.25-2.61). In the ESTHER study the predictive value of subjective mental health for future depressive symptoms was also assessed and for 10-unit increase in mental HRQOL scores the odds for incident depressive symptoms were reduced by 54% (OR 0.46; CI 0.40-0.54). These findings suggest that subjective mental health and hypomethylation at cg27115863 are predictive of depressive symptoms, possibly through the activation of inflammatory signaling pathway.

"Epigenetic clocks": Theory and applications in human biology

All humans age, but how we age-and how fast-differs considerably from person to person. This deviation between apparent age and chronological age is often referred to as "biological age" (BA) and until recently robust tools for studying BA have been scarce. "Epigenetic clocks" are starting to change this. Epigenetic clocks use predictable changes in the epigenome, usually DNA methylation, to estimate chronological age with unprecedented accuracy. More importantly, deviations between epigenetic age and chronological age predict a broad range of health outcomes and mortality risks better than chronological age alone. Thus, epigenetic clocks appear to capture fundamental molecular processes tied to BA and can serve as powerful tools for studying health, development, and aging across the lifespan. In this article, I review epigenetic clocks, especially as they relate to key theoretical and applied issues in human biology. I first provide an overview of how epigenetic clocks are constructed and what we know about them. I then discuss emerging applications of particular relevance to human biologists-those related to reproduction, life-history, stress, and the environment. I conclude with an overview of the methods necessary for implementing epigenetic clocks, including considerations of study design, sample collection, and technical considerations for processing and interpreting epigenetic clocks. The goal of this review is to highlight some of the ways that epigenetic clocks can inform questions in human biology, and vice versa, and to provide human biologists with the foundational knowledge necessary to successfully incorporate epigenetic clocks into their research.

Blood-derived DNA methylation predictors of mortality discriminate tumor and healthy tissue in multiple organs

Evidence has shown that certain methylation markers derived from blood can mirror corresponding methylation signatures in internal tissues. In the current study, we aimed to investigate two strong epigenetic predictors for life span, derived from blood DNA methylation data, in tissue samples of solid cancer patients. Using data from the Cancer Genome Atlas (TCGA) and the German DACHS study, we compared a mortality risk score (MRscore) and DNAmPhenoAge in paired tumor and adjacent normal tissue samples of patients with lung (N = 69), colorectal (n = 299), breast (n = 90), head/neck (n = 50), prostate (n = 50), and liver (n = 50) cancer. To explore the concordance across tissue and blood, we additionally assessed the two markers in blood samples of colorectal cancer (CRC) cases and matched controls (n = 93) in the DACHS+ study. The MRscore was significantly elevated in tumor tissues compared to normal tissues of all cancers except prostate cancer, for which an opposite pattern was observed. DNAmPhenoAge was consistently higher in all tumor tissues. The MRscore discriminated lung, colorectal, and prostate tumor tissues from normal tissues with very high accuracy [AUCs of 0.87, 0.99 (TCGA) /0.94 (DACHS), and 0.92, respectively]. DNAmPhenoAge accurately discriminated five types of tumor tissues from normal tissues (except prostate cancer), with AUCs of 0.82–0.93. The MRscore was also significantly higher in blood samples of CRC cases than in controls, with areas under the curve (AUC) of 0.74, whereas DNAmPhenoAge did not distinguish cases from controls, with AUC of 0.54. This study provides compelling evidence that blood‐derived DNAm markers could reflect methylation changes in less accessible tissues. Further research should explore the potential use of these findings for cancer diagnosis and early detection.

Array-Based Epigenetic Aging Indices May Be Racially Biased

Epigenetic aging (EA) indices are frequently used as predictors of mortality and other important health outcomes. However, each of the commonly used array-based indices has significant heritable components which could tag ethnicity and potentially confound comparisons across racial and ethnic groups. To determine if this was possible, we examined the relationship of DNA methylation in cord blood from 203 newborns (112 African American (AA) and 91 White) at the 513 probes from the Levine PhenoAge Epigenetic Aging index to ethnicity. Then, we examined all sites significantly associated with race in the newborn sample to determine if they were also associated with an index of ethnic genetic heritage in a cohort of 505 AA adults. After Bonferroni correction, methylation at 50 CpG sites was significantly associated with ethnicity in the newborn cohort. The five most significant sites predicted ancestry with a receiver operator characteristic area under the curve of 0.97. Examination of the top 50 sites in the AA adult cohort showed that methylation status at 11 of those sites was also associated with percentage European ancestry. We conclude that the Levine PhenoAge Index is influenced by cryptic ethnic-specific genetic influences. This influence may extend to similarly constructed EA indices and bias cross-race comparisons.

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.

AHRR methylation predicts smoking status and smoking intensity in both saliva and blood DNA

Many existing DNA repositories do not have robust characterizations of smoking, while for many currently ongoing studies, the advent of vaping has rendered traditional cotinine-based methods of determining smoking status unreliable. Previously, we have shown that methylation status at cg05575921 in whole blood DNA can reliably predict cigarette consumption. However, whether methylation status in saliva can be used similarly has yet to be established. Herein, we use DNA from 418 biochemically confirmed smokers or nonsmokers to compare and contrast the utility of cg05575921 in classifying and quantifying cigarette smoking. Using whole blood DNA, a model incorporating age, gender, and methylation status had a receiver operating characteristic (ROC) area under the curve (AUC) for predicting smoking status of 0.995 with a nonlinear demethylation response to smoking. Using saliva DNA, the ROC AUC for predicting smoking was 0.971 with the plot of the relationship of DNA methylation to daily cigarette consumption being very similar to that seen for whole blood DNA. The addition of information from another methylation marker designed to correct for cellular heterogeneity improved the AUC for saliva DNA to 0.981. Finally, in 31 subjects who reported quitting smoking 10 or more years previously, cg05575921 methylation was nonsignificantly different from controls. We conclude that DNA methylation status at cg05575921 in DNA from whole blood or saliva predicts smoking status and daily cigarette consumption. We suggest these epigenetic assessments for objectively ascertaining smoking status will find utility in research, clinical, and civil applications.

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.

Oxidative stress and epigenetic mortality risk score: associations with all-cause mortality among elderly people

Oxidative stress (OS) has been found to be related to accelerated aging and many aging-related health outcomes. Recently, an epigenetic "mortality risk score" (MS) based on whole blood DNA methylation at 10 mortality-related CpG sites has been demonstrated to be associated with all-cause mortality. This study aimed to address the association between OS and MS, and to assess and compare their performance in the prediction of all-cause mortality. For 1448 participants aged 50-75 of the German ESTHER cohort study, the MS was derived from the DNA methylation profiles measured by Illumina HumanMethylation450K Beadchip and the levels of two urinary OS markers, 8-isoprostane (8-iso) and oxidized guanine/guanosine [including 8-hydroxy-2'-deoxyguanosine (8-oxo)], were measured by ELISA kits. Associations between OS markers and the MS were evaluated by linear and ordinal logistic regression models, and their associations with all-cause mortality were examined by Cox regression models. Both OS markers were associated with the MS at baseline. The 8-iso levels and MS, but not 8-oxo levels, were associated with all-cause mortality during a median follow-up of 15.1 years. Fully-adjusted hazard ratios (95% CI) were 1.56 (1.13-2.16) for the 4th quartile of 8-iso levels compared with the 1st, 1.71 (1.27-2.29) and 2.92 (2.03-4.18) for the moderate and high MS defined by 2-5 and > 5 CpG sites with aberrant methylation compared with a MS of 0-1, respectively. After controlling for 8-iso levels, the hazard ratios of MS remained essentially unchanged while the association of 8-iso levels with mortality was attenuated. This study demonstrates that OS is highly associated with the epigenetic MS, and the latter at the same time has a higher predictive value for all-cause mortality.

The associations of DNA methylation alterations in oxidative stress-related genes with cancer incidence and mortality outcomes: a population-based cohort study

Background

Reactive oxygen species may be involved in epigenetic gene activation or silencing. We aimed to identify CpG sites, at which DNA methylation is related to urinary 8-isoprostane levels (biomarker of lipid peroxidation) and cancer or mortality outcomes. This investigation was based on a German, population-based cohort with linkage to cancer and mortality registry data (2000–2016).

Results

Blood DNA methylation in promoter regions of 519 genes, known to be involved in pathways from oxidative stress (OS) to cancer, was obtained at the cohort's baseline examination. Inverse associations of DNA methylation at cg25365794 (ALOXE3) and cg08862778 (MTOR) with 8-isoprostane levels were observed in a derivation set (n = 1000) and validated in two independent subsets of the cohort (n = 548 and n = 741). Multivariate regression models were used to evaluate the associations of DNA methylation at the two CpG sites with lung, colorectal, prostate, breast, and overall cancer incidence as well as CVD, cancer, and all-cause mortality. DNA methylation at cg25365794 (ALOXE3) was inversely associated with lung and prostate cancer incidence. DNA methylation at cg08862778 (MTOR) was associated with a 43% lower breast cancer incidence in the top vs. bottom tertile.

Conclusion

The finding for ALOXE3 may not be causal. As ALOXE3 is mainly expressed in skin tissue, the observed association might reflect the fact that both DNA methylation at the ALOXE3 gene and urinary 8-isoprostane concentrations depend on the level of OS in tissues. Contrarily, the finding for the MTOR gene and breast cancer is biologically plausible because the MTOR protein plays an important role in PI3K/Akt signaling, which is a pathway related to cancer development and cell senescence.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0604-y) contains supplementary material, which is available to authorized users.

A Direct Comparison of the Relationship of Epigenetic Aging and Epigenetic Substance Consumption Markers to Mortality in the Framingham Heart Study

A number of studies have examined the relationship of indices of epigenetic aging (EA) to key health outcomes. Unfortunately, our understanding of the relationship of EA to mortality and substance use-related health variables is unclear. In order to clarify these interpretations, we analyzed the relationship of the Levine EA index (LEA), as well as established epigenetic indices of cigarette (cg05575921) and alcohol consumption (cg04987734), to all-cause mortality in the Framingham Heart Study Offspring Cohort (n = 2256) Cox proportional hazards regression. We found that cg05575921 and cg04987734 had an independent effect relative to LEA and vice versa, with the model including all the predictors having better performance than models with either LEA or cg05575921 and cg04987734 alone. After correction for multiple comparisons, 195 and 327, respectively, of the 513 markers in the LEA index, as well as the overall index itself, were significantly associated with cg05575921 and cg04987734 methylation status. We conclude that the epigenetic indices of substance use have an independent effect over and above LEA, and are slightly stronger predictors of mortality in head-to-head comparisons. We also conclude that the majority of the strength of association conveyed by the LEA is secondary to smoking and drinking behaviors, and that efforts to promote healthy aging should continue to focus on addressing substance use.