Using epigenome-wide association scans of DNA methylation in age-related complex human traits

Hypomethylation of AHRR (cg05575921) Is Related to Smoking Status in the Mexican Mestizo Population

Tobacco smoking results in a multifactorial disease involving environmental and genetic factors; epigenome-wide association studies (EWAS) show changes in DNA methylation levels due to cigarette consumption, partially reversible upon tobacco smoking cessation. Therefore, methylation levels could predict smoking status. This study aimed to evaluate the DNA methylation level of cg05575921 (AHRR) and cg23771366 (PRSS23) and their correlation with lung function variables, cigarette consumption, and nicotine addiction in the Mexican smoking population. We included 114 non-smokers (NS) and 102 current tobacco smokers (TS); we then further subclassified them as heavy smokers (HS) (n = 53) and light smokers (LS) (n = 49). We used restriction enzymes (MspI/HpaII) and qPCR to determine the DNA methylation level. We observed significant hypomethylation of cg05575921 in smokers compared to NS (p = 0.003); further analysis found a difference between HS and NS (p = 0.02). We did not observe differences between other groups or a positive correlation between methylation levels and age, BMI, cigarette consumption, nicotine addiction, or lung function. In conclusion, the cg05575921 site of AHRR is significantly hypomethylated in Mexican smokers, especially in HS (≥20 cigarettes per day).

Identification and validation of DNA methylation changes in pre-eclampsia

INTRODUCTION

Pre-eclampsia (PE) is a dangerous placental condition that can lead to premature labour, seizures and death of mother and infant. Several studies have identified altered placental DNA methylation in PE; however, there is widespread inconsistency between studies and most findings have not been replicated. This study aimed to identify and validate consistent differences in methylation across multiple PE cohorts.

METHODS

Seven publicly available 450K methylation array datasets were analysed to identify consistent differentially methylated positions (DMPs) in PE. DMPs were identified based on methylation difference (≥10%) and significance (p-value ≤ 1 × 10^-7). Targeted deep bisulfite sequencing was then performed to validate a subset of DMPs in an additional independent PE cohort.

RESULTS

Stringent analysis of the seven 450K datasets identified 25 DMPs (associated with 11 genes) in only one dataset. Using more relaxed criteria confirmed 19 of the stringent 25 DMPs in at least four of the remaining six datasets. Targeted deep bisulfite sequencing of eight DMPs (associated with three genes; CMIP, ST3GAL1 and DAPK3) in an independent PE cohort validated two DMPs in the CMIP gene. Seven additional CpG sites in CMIP were found to be significantly differentially methylated in PE.

DISCUSSION

The identification and validation of significant differential methylation in CMIP suggests that the altered DNA methylation of this gene may be associated with the pathogenesis of PE, and may have the potential to serve as diagnostic biomarkers for this dangerous condition of pregnancy.

Intergenerational transmission: Theoretical and methodological issues and an introduction to four Dutch cohorts

Behaviors, traits and characteristics are transmitted from parents to offspring because of complex genetic and non-genetic processes. We review genetic and non-genetic mechanisms of intergenerational transmission of psychopathology and parenting and focus on recent methodological advances in disentangling genetic and non-genetic factors. In light of this review, we propose that future studies on intergenerational transmission should aim to disentangle genetic and non-genetic transmission, take a long-term longitudinal perspective, and focus on paternal and maternal intergenerational transmission. We present four large longitudinal cohort studies within the Consortium on Individual Development, which together address many of these methodological challenges. These four cohort studies aim to examine the extent to which genetic and non-genetic transmission from the parental generation shapes parenting behavior and psychopathology in the next generation, as well as the extent to which self-regulation and social competence mediate this transmission. Conjointly, these four cohorts provide a comprehensive approach to the study of intergenerational transmission.

The relationship between DNA methylation in neurotrophic genes and age as evidenced from three independent cohorts: differences by delirium status

We previously reported the association between DNA methylation (DNAm) of pro-inflammatory cytokine genes and age. In addition, neurotrophic factors are known to be associated with age and neurocognitive disorders. Therefore, we hypothesized that DNAm of neurotrophic genes change with age, especially in delirium patients. DNAm was analyzed using the Illumina HumanMethylation450 or HumanMethylationEPIC BeadChip Kit in 3 independent cohorts: blood from 383 Grady Trauma Project subjects, brain from 21 neurosurgery patients, and blood from 87 inpatients with and without delirium. Both blood and brain samples showed that most of the DNAm of neurotrophic genes were positively correlated with age. Furthermore, DNAm of neurotrophic genes was more positively correlated with age in delirium cases than in non-delirium controls. These findings support our hypothesis that the neurotrophic genes may be epigenetically modulated with age, and this process may be contributing to the pathophysiology of delirium.

Methylome-wide association study provides evidence of particulate matter air pollution-associated DNA methylation

BACKGROUND

DNA methylation (DNAm) may contribute to processes that underlie associations between air pollution and poor health. Therefore, our objective was to evaluate associations between DNAm and ambient concentrations of particulate matter (PM) ≤2.5, ≤10, and 2.5-10 μm in diameter (PM2.5; PM10; PM2.5-10).

METHODS

We conducted a methylome-wide association study among twelve cohort- and race/ethnicity-stratified subpopulations from the Women's Health Initiative and the Atherosclerosis Risk in Communities study (n = 8397; mean age: 61.5 years; 83% female; 45% African American; 9% Hispanic/Latino American). We averaged geocoded address-specific estimates of daily and monthly mean PM concentrations over 2, 7, 28, and 365 days and 1 and 12 months before exams at which we measured leukocyte DNAm in whole blood. We estimated subpopulation-specific, DNAm-PM associations at approximately 485,000 Cytosine-phosphate-Guanine (CpG) sites in multi-level, linear, mixed-effects models. We combined subpopulation- and site-specific estimates in fixed-effects, inverse variance-weighted meta-analyses, then for associations that exceeded methylome-wide significance and were not heterogeneous across subpopulations (P < 1.0 × 10-7; PCochran's Q > 0.10), we characterized associations using publicly accessible genomic databases and attempted replication in the Cooperative Health Research in the Region of Augsburg (KORA) study.

RESULTS

Analyses identified significant DNAm-PM associations at three CpG sites. Twenty-eight-day mean PM10 was positively associated with DNAm at cg19004594 (chromosome 20; MATN4; P = 3.33 × 10-8). One-month mean PM10 and PM2.5-10 were positively associated with DNAm at cg24102420 (chromosome 10; ARPP21; P = 5.84 × 10-8) and inversely associated with DNAm at cg12124767 (chromosome 7; CFTR; P = 9.86 × 10-8). The PM-sensitive CpG sites mapped to neurological, pulmonary, endocrine, and cardiovascular disease-related genes, but DNAm at those sites was not associated with gene expression in blood cells and did not replicate in KORA.

CONCLUSIONS

Ambient PM concentrations were associated with DNAm at genomic regions potentially related to poor health among racially, ethnically and environmentally diverse populations of U.S. women and men. Further investigation is warranted to uncover mechanisms through which PM-induced epigenomic changes may cause disease.

Data-Driven-Based Approach to Identifying Differentially Methylated Regions Using Modified 1D Ising Model

Background

DNA methylation is essential for regulating gene expression, and the changes of DNA methylation status are commonly discovered in disease. Therefore, identification of differentially methylation patterns, especially differentially methylated regions (DMRs), in two different groups is important for understanding the mechanism of complex diseases. Few tools exist for DMR identification through considering features of methylation data, but there is no comprehensive integration of the characteristics of DNA methylation data in current methods.

Results

Accounting for the characteristics of methylation data, such as the correlation characteristics of neighboring CpG sites and the high heterogeneity of DNA methylation data, we propose a data-driven approach for DMR identification through evaluating the energy of single site using modified 1D Ising model. Applied to both simulated and publicly available datasets, our approach is compared with other popular methods in terms of performance. Simulated results show that our method is more sensitive than competing methods. Applied to the real data, our method can identify more common DMRs than DMRcate, ProbeLasso, and Wang's methods with a high overlapping ratio. Also, the necessity of integrating the heterogeneity and correlation characteristics in identifying DMR is shown through comparing results with only considering mean or variance signals and without considering relationship of neighboring CpG sites, respectively. Through analyzing the number of DMRs identified in real data located in different genomic regions, we find that about 90% DMRs are located in CGI which always regulates the expression of genes. It may help us understand the functional effect of DNA methylation on disease.

armDNA: A functional beta model for detecting age-related genomewide DNA methylation marks

DNA methylation has been shown to play an important role in many complex diseases. The rapid development of high-throughput DNA methylation scan technologies provides great opportunities for genomewide DNA methylation-disease association studies. As methylation is a dynamic process involving time, it is quite plausible that age contributes to its variation to a large extent. Therefore, in analyzing genomewide DNA methylation data, it is important to identify age-related DNA methylation marks and delineate their functional relationship. This helps us to better understand the underlying biological mechanism and facilitate early diagnosis and prognosis analysis of complex diseases. We develop a functional beta model for analyzing DNA methylation data and detecting age-related DNA methylation marks on the whole genome by naturally taking sampling scheme into account and accommodating flexible age-methylation dynamics. We focus on DNA methylation data obtained through the widely used bisulfite conversion technique and propose to use a beta model to relate the DNA methylation level to the age. Adjusting for certain confounders, the functional age effect is left completely unspecified, offering great flexibility and allowing extra data dynamics. An efficient algorithm is developed for estimating unknown parameters, and the Wald test is used to detect age-related DNA methylation marks. Simulation studies and several real data applications were provided to demonstrate the performance of the proposed method.

Associations between body size, nutrition and socioeconomic position in early life and the epigenome: A systematic review

Background

Body size, nutrition and socioeconomic position (SEP) in early life have been associated with a wide range of long-term health effects. Epigenetics is one possible mechanism through which these early life exposures can impact later life health. We conducted a systematic review examining the observational evidence for the impact of body size, nutrition and SEP in early life on the epigenome in humans.

Methods

This systematic review is registered with the PROSPERO database (registration number: CRD42016050193). Three datasets were simultaneously searched using Ovid and the resulting studies were evaluated by at least two independent reviewers. Studies measuring epigenetic markers either at the same time as, or after, the early life exposure and have a measure of body size, nutrition or SEP in early life (up to 12 years), written in English and from a community-dwelling participants were included.

Results

We identified 90 eligible studies. Seventeen of these papers examined more than one early life exposure of interest. Fifty six papers examined body size, 37 nutrition and 17 SEP. All of the included papers examined DNA methylation (DNAm) as the epigenetic marker. Overall there was no strong evidence for a consistent association between these early life variables in DNAm which may be due to the heterogeneous study designs, data collection methods and statistical analyses.

Conclusions

Despite these inconclusive results, the hypothesis that the early life environment can impact DNAm, potentially persisting into adult life, was supported by some studies and warrants further investigation. We provide recommendations for future studies.

Identification of novel hyper- or hypomethylated CpG sites and genes associated with atherosclerotic plaque using an epigenome-wide association study

DNA methylation is an important epigenetic modification that has been implicated in the pathogenesis of atherosclerosis. Although previous studies have identified various CpG sites and genes whose methylation is associated with atherosclerosis in populations with European or Mexican ancestry, the genome‑wide pattern of DNA methylation in the atherosclerotic human aorta is yet to be elucidated in Japanese individuals. In the present study, a genome‑wide analysis of DNA methylation at ~853,000 CpG sites was performed using 128 postmortem aortic intima specimens obtained from 64 Japanese patients. To avoid the effects of interindividual variation, intraindividual paired comparisons were performed between atheromatous plaque lesions and corresponding plaque‑free tissue for each patient. Bisulfite‑modified genomic DNA was analyzed using a specific microarray for DNA methylation. DNA methylation at each CpG site was calculated as the β value, where β = (intensity of the methylated allele)/(intensity of the methylated allele + intensity of the unmethylated allele + 100). Bonferroni's correction for statistical significance of association was applied to compensate for multiple comparisons. The methylation of 2,679 CpG sites differed significantly (P<5.86x10‑8) between atheromatous plaque lesions and the corresponding plaque‑free intima, with 2,272 and 407 CpG sites in atheromatous plaques being hyper‑ or hypomethylated, respectively. A total of 5 hypermethylated CpG sites in atheromatous plaques were demonstrated to have a difference in β value of >0.15 (plaque lesion‑plaque‑free intima) and 11 had a β ratio of >1.50 (plaque/plaque‑free intima). A further 15 and 17 hypomethylated CpG sites in atheromatous plaques were observed to have a difference in β value of <‑0.15 or a β ratio of <0.67, respectively. According to these limits, a total of 16 novel genes that were significantly hyper‑ or hypomethylated in atheromatous plaque lesions compared with the plaque‑free intima were identified in the present study. The results of the present study suggest that the methylation of these genes may contribute to the pathogenesis of atherosclerosis in the Japanese population.

Estimation of a significance threshold for epigenome-wide association studies

Epigenome-wide association studies (EWAS) are designed to characterise population-level epigenetic differences across the genome and link them to disease. Most commonly, they assess DNA-methylation status at cytosine-guanine dinucleotide (CpG) sites, using platforms such as the Illumina 450k array that profile a subset of CpGs genome wide. An important challenge in the context of EWAS is determining a significance threshold for declaring a CpG site as differentially methylated, taking multiple testing into account. We used a permutation method to estimate a significance threshold specifically for the 450k array and a simulation extrapolation approach to estimate a genome-wide threshold. These methods were applied to five different EWAS datasets derived from a variety of populations and tissue types. We obtained an estimate of α=2.4×10-7 for the 450k array, and a genome-wide estimate of α=3.6×10-8. We further demonstrate the importance of these results by showing that previously recommended sample sizes for EWAS should be adjusted upwards, requiring samples between ∼10% and ∼20% larger in order to maintain type-1 errors at the desired level.

Ischemic stroke patients are biologically older than their chronological age

Ischemic stroke is associated with aging. It is possible to predict chronological age by measuring age-related changes in DNA methylation from multiple CpG sites across the genome, known as biological age. The difference between biological age and actual chronological age would indicate an individual's level of aging. Our aim was to determine the biological age of ischemic stroke patients and compare their aging with controls of the same chronological age. A total of 123 individuals, 41 controls and 82 patients with ischemic stroke were paired by chronological age, ranging from 39 to 82 years. Illumina HumanMethylation450 BeadChip array was used to measure DNA methylation in CpG sites in both groups, and biological age was estimated using methylation values of specific CpGs. Ischemic stroke patients were biologically an average 2.5 years older than healthy controls (p-value=0.010). Stratified by age tertiles, younger stroke patients (≤57 years old) were biologically older than controls (OR=1.19; 95%CI 1.00-1.41, p-value=0.046). The older groups showed no biological age differences between cases and controls, but were close to reaching the significance level. Ischemic stroke patients are biologically older than controls. Biological age should be considered as a potential new biomarker of stroke risk.

New insights into molecular mechanisms of epigenetic regulation in kidney disease

The number of patients with kidney failure has increased in recent years. Different factors contribute to the progression of chronic kidney disease, including glomerular sclerosis, atherosclerosis of the renal arteries and tubulointerstitial fibrosis. Tubulointerstitial injury is induced by hypoxia and other inflammatory signals, leading to fibroblast activation. Technological advances using high-throughput sequencing has enabled the determination of the expression profile of almost all genes, revealing that gene expression is intricately regulated by DNA methylation, histone modification, changes in chromosome conformation, long non-coding RNAs and microRNAs. These epigenetic modifications are stored as cellular epigenetic memory. Epigenetic memory leads to adult-onset disease or ageing in the long term and may possibly play an important role in the kidney disease process. Herein we emphasize the importance of clarifying the molecular mechanisms underlying epigenetic modifications because this may lead to the development of new therapeutic targets in kidney disease.

Dual Effects of a RETN Single Nucleotide Polymorphism (SNP) at -420 on Plasma Resistin: Genotype and DNA Methylation

CONTEXT

We previously reported that single nucleotide polymorphism (SNP)-420 C>G (rs1862513) in the promoter region of RETN was associated with type 2 diabetes. Plasma resistin was tightly correlated with SNP-420 genotypes. SNP-420 is a CpG-SNP affecting the sequence of cytosine-phosphate-guanine dinucleotides.

OBJECTIVE

To examine whether methylation at SNP-420 affects plasma resistin, we analyzed plasma resistin and methylation at RETN SNP-420.

DESIGN AND METHODS

Genomic DNA was extracted from peripheral white blood cells in 2078 Japanese subjects. Quantification of the methylation was performed by pyrosequencing after DNA bisulfite conversion.

RESULTS

Methylation at SNP-420 was highest in the C/C genotype (36.9 ± 5.7%), followed by C/G (21.4 ± 3.5%) and G/G (2.9 ± 1.4%; P < 0.001). When assessed in each genotype, methylation at SNP-420 was inversely associated with plasma resistin in the C/C (β = -0.134, P < 0.001) or C/G (β = -0.227, P < 0.001) genotype. In THP-1 human monocytes intrinsically having the C/C genotype, a demethylating reagent, 5-aza-dC, decreased the methylation at SNP-420 and increased RETN messenger RNA. SNP+1263 (rs3745369), located in the 3' untranslated region of RETN, was also associated with methylation at SNP-420. In addition, highly sensitive C-reactive protein was inversely associated with methylation at SNP-420 in the C/C genotype, whereas body mass index was positively associated.

CONCLUSIONS

Plasma resistin was inversely associated with the extent of methylation at SNP-420 mainly dependent on the SNP-420 genotype. The association can also be explained partially independent of SNP-420 genotypes. SNP-420 could have dual, genetic and epigenetic effects on plasma resistin.

Mitochondria in the spotlight of aging and idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic age-related lung disease with high mortality that is characterized by abnormal scarring of the lung parenchyma. There has been a recent attempt to define the age-associated changes predisposing individuals to develop IPF. Age-related perturbations that are increasingly found in epithelial cells and fibroblasts from IPF lungs compared with age-matched cells from normal lungs include defective autophagy, telomere attrition, altered proteostasis, and cell senescence. These divergent processes seem to converge in mitochondrial dysfunction and metabolic distress, which potentiate maladaptation to stress and susceptibility to age-related diseases such as IPF. Therapeutic approaches that target aging processes may be beneficial for halting the progression of disease and improving quality of life in IPF patients.

The epigenomics of polycystic ovarian syndrome: from pathogenesis to clinical manifestations

Polycystic ovarian syndrome (PCOS) is a complex condition of ovarian dysfunction and metabolic abnormalities with widely varying clinical manifestations resulting from interference of the genome and the environment through integrative biological mechanisms with the emerging field of epigenetics offering an appealing tool for studying the nature and nurture of the disease. We review the current literature of epigenetic studies on PCOS from disease development to the association analysis of the DNA methylome and to exploratory studies on the molecular mechanisms of disease heterogeneity and comorbidity. Recent data based on profiling of the DNA methylome of PCOS in different tissues provided consistent molecular evidence in support of epidemiological findings on disease comorbidity suggesting a possible autoimmune basis in the pathogenesis of the disease. We show that the field of epigenetics and epigenomics could serve to link molecular regulatory mechanisms with disease development and disease manifestation which could contribute to PCOS prevention and treatment and eventually promote reproductive health in fertile age women. We summarize the up-to-date findings and discuss the implications of various studies and point to new avenues of research on PCOS in the rapidly developing field of epigenetics and epigenomics.

Genome-Wide Epigenetic Studies in Human Disease: A Primer on -Omic Technologies

Epigenetic information encoded in covalent modifications of DNA and histone proteins regulates fundamental biological processes through the action of chromatin regulators, transcription factors, and noncoding RNA species. Epigenetic plasticity enables an organism to respond to developmental and environmental signals without genetic changes. However, aberrant epigenetic control plays a key role in pathogenesis of disease. Normal epigenetic states could be disrupted by detrimental mutations and expression alteration of chromatin regulators or by environmental factors. In this primer, we briefly review the epigenetic basis of human disease and discuss how recent discoveries in this field could be translated into clinical diagnosis, prevention, and treatment. We introduce platforms for mapping genome-wide chromatin accessibility, nucleosome occupancy, DNA-binding proteins, and DNA methylation, primarily focusing on the integration of DNA methylation and chromatin immunoprecipitation-sequencing technologies into disease association studies. We highlight practical considerations in applying high-throughput epigenetic assays and formulating analytical strategies. Finally, we summarize current challenges in sample acquisition, experimental procedures, data analysis, and interpretation and make recommendations on further refinement in these areas. Incorporating epigenomic testing into the clinical research arsenal will greatly facilitate our understanding of the epigenetic basis of disease and help identify novel therapeutic targets.

Epigenetic effects of selenium and their implications for health

Alterations of epigenetic marks are linked to normal development and cellular differentiation as well as to the progression of common chronic diseases. The plasticity of these marks provides potential for disease therapies and prevention strategies. Macro- and micro-nutrients have been shown to modulate disease risk in part via effects on the epigenome. The essential micronutrient selenium affects human health outcomes, e.g., cancers, cardiovascular and autoimmune diseases, via selenoproteins and through a range of biologically active dietary selenocompounds and metabolism products thereof. This review provides an assessment of the current literature regarding epigenetic effects of dietary and synthetic selenocompounds, which include the modulation of marks and editors of epigenetic information and interference with one-carbon metabolism, which provides the methyl donor for DNA methylation. The relevance of a selenium-epigenome interaction for human health is discussed, and we also indicate where future studies will be helpful to gain a deeper understanding of epigenetic effects elicited by selenium.

Structural Properties of Gene Promoters Highlight More than Two Phenotypes of Diabetes

Genome-wide association studies (GWAS) published in the last decade raised the number of loci associated with type 1 (T1D) and type 2 diabetes (T2D) to more than 50 for each of these diabetes phenotypes. The environmental factors seem to play an important role in the expression of these genes, acting through transcription factors that bind to promoters. Using the available databases we examined the promoters of various genes classically associated with the two main diabetes phenotypes. Our comparative analyses have revealed significant architectural differences between promoters of genes classically associated with T1D and T2D. Nevertheless, five gene promoters (about 16%) belonging to T1D and six gene promoters (over 19%) belonging to T2D have shown some intermediary structural properties, suggesting a direct relationship to either LADA (Latent Autoimmune Diabetes in Adults) phenotype or to non-autoimmune type 1 phenotype. The distribution of these promoters in at least three separate classes seems to indicate specific pathogenic pathways. The image-based patterns (DNA patterns) generated by promoters of genes associated with these three phenotypes support the clinical observation of a smooth link between specific cases of typical T1D and T2D. In addition, a global distribution of these DNA patterns suggests that promoters of genes associated with T1D appear to be evolutionary more conserved than those associated with T2D. Though, the image based patterns obtained by our method might be a new useful parameter for understanding the pathogenetic mechanism and the diabetogenic gene networks.

LINE-1 DNA methylation: A potential forensic marker for discriminating monozygotic twins

Discriminating individuals within a pair of monozygotic (MZ) twins using genetic markers remains unresolved. This inability causes problems in criminal or paternity cases involving MZ twins as suspects or alleged fathers. Our previous study showed DNA methylation differences in interspersed repeat sequences such as Alu and LINE-1 within pairs of newborn MZ twins. To further evaluate the possible value of LINE-1 DNA methylation for discriminating MZ twins, this study investigated the LINE-1 DNA methylation of a large number of twins. We collected blood samples and buccal cell samples from 119 pairs of MZ and 57 pairs of dizygotic (DZ) twins. Genomic DNA was extracted and LINE-1 methylation level was detected using bisulfite pyrosequencing. The mean methylation level of the three CpG sites in the blood sample among the 176 unrelated individuals was 76.60% and 70.08% in buccal samples. This difference was significant, indicating the tissue specificity of LINE-1 DNA methylation. Among 119 pairs of MZ twins, 15 pairs could be discriminated according to the difference of CpG methylation level between them, which accounted for 12.61% of total number of MZ pairs. As for DZ twins, 10 pairs had significant differences between two individuals, which accounted for 17.54% of the total 57 DZ pairs. In conclusion, there are global DNA methylation differences within some healthy concordant monozygotic (MZ) twin pairs. LINE-1 DNA methylation might be a potential marker for helping to discriminate individuals within MZ twin pairs, and the tissue specificity must be considered in practice.

From inflammaging to healthy aging by dietary lifestyle choices: is epigenetics the key to personalized nutrition?

The progressively older population in developed countries is reflected in an increase in the number of people suffering from age-related chronic inflammatory diseases such as metabolic syndrome, diabetes, heart and lung diseases, cancer, osteoporosis, arthritis, and dementia. The heterogeneity in biological aging, chronological age, and aging-associated disorders in humans have been ascribed to different genetic and environmental factors (i.e., diet, pollution, stress) that are closely linked to socioeconomic factors. The common denominator of these factors is the inflammatory response. Chronic low-grade systemic inflammation during physiological aging and immunosenescence are intertwined in the pathogenesis of premature aging also defined as ‘inflammaging.’ The latter has been associated with frailty, morbidity, and mortality in elderly subjects. However, it is unknown to what extent inflammaging or longevity is controlled by epigenetic events in early life. Today, human diet is believed to have a major influence on both the development and prevention of age-related diseases. Most plant-derived dietary phytochemicals and macro- and micronutrients modulate oxidative stress and inflammatory signaling and regulate metabolic pathways and bioenergetics that can be translated into stable epigenetic patterns of gene expression. Therefore, diet interventions designed for healthy aging have become a hot topic in nutritional epigenomic research. Increasing evidence has revealed that complex interactions between food components and histone modifications, DNA methylation, non-coding RNA expression, and chromatin remodeling factors influence the inflammaging phenotype and as such may protect or predispose an individual to many age-related diseases. Remarkably, humans present a broad range of responses to similar dietary challenges due to both genetic and epigenetic modulations of the expression of target proteins and key genes involved in the metabolism and distribution of the dietary constituents. Here, we will summarize the epigenetic actions of dietary components, including phytochemicals, and macro- and micronutrients as well as metabolites, that can attenuate inflammaging. We will discuss the challenges facing personalized nutrition to translate highly variable interindividual epigenetic diet responses to potential individual health benefits/risks related to aging disease.

Acceleration of age-associated methylation patterns in HIV-1-infected adults

Patients with treated HIV-1-infection experience earlier occurrence of aging-associated diseases, raising speculation that HIV-1-infection, or antiretroviral treatment, may accelerate aging. We recently described an age-related co-methylation module comprised of hundreds of CpGs; however, it is unknown whether aging and HIV-1-infection exert negative health effects through similar, or disparate, mechanisms. We investigated whether HIV-1-infection would induce age-associated methylation changes. We evaluated DNA methylation levels at >450,000 CpG sites in peripheral blood mononuclear cells (PBMC) of young (20-35) and older (36-56) adults in two separate groups of participants. Each age group for each data set consisted of 12 HIV-1-infected and 12 age-matched HIV-1-uninfected samples for a total of 96 samples. The effects of age and HIV-1 infection on methylation at each CpG revealed a strong correlation of 0.49, p<1 x 10(-200) and 0.47, p<1 x 10(-200). Weighted gene correlation network analysis (WGCNA) identified 17 co-methylation modules; module 3 (ME3) was significantly correlated with age (cor=0.70) and HIV-1 status (cor=0.31). Older HIV-1+ individuals had a greater number of hypermethylated CpGs across ME3 (p=0.015). In a multivariate model, ME3 was significantly associated with age and HIV status (Data set 1: βage=0.007088, p=2.08 x 10(-9); βHIV=0.099574, p=0.0011; Data set 2: βage=0.008762, p=1.27 x 10(-5); βHIV=0.128649, p=0.0001). Using this model, we estimate that HIV-1 infection accelerates age-related methylation by approximately 13.7 years in data set 1 and 14.7 years in data set 2. The genes related to CpGs in ME3 are enriched for polycomb group target genes known to be involved in cell renewal and aging. The overlap between ME3 and an aging methylation module found in solid tissues is also highly significant (Fisher-exact p=5.6 x 10(-6), odds ratio=1.91). These data demonstrate that HIV-1 infection is associated with methylation patterns that are similar to age-associated patterns and suggest that general aging and HIV-1 related aging work through some common cellular and molecular mechanisms. These results are an important first step for finding potential therapeutic targets and novel clinical approaches to mitigate the detrimental effects of both HIV-1-infection and aging.

Aging and cardiovascular diseases: the role of gene-diet interactions

In the study of longevity, increasing importance is being placed on the concept of healthy aging rather than considering the total number of years lived. Although the concept of healthy lifespan needs to be defined better, we know that cardiovascular diseases (CVDs) are the main age-related diseases. Thus, controlling risk factors will contribute to reducing their incidence, leading to healthy lifespan. CVDs are complex diseases influenced by numerous genetic and environmental factors. Numerous gene variants that are associated with a greater or lesser risk of the different types of CVD and of intermediate phenotypes (i.e., hypercholesterolemia, hypertension, diabetes) have been successfully identified. However, despite the close link between aging and CVD, studies analyzing the genes related to human longevity have not obtained consistent results and there has been little coincidence in the genes identified in both fields. The APOE gene stands out as an exception, given that it has been identified as being relevant in CVD and longevity. This review analyzes the genomic and epigenomic factors that may contribute to this, ranging from identifying longevity genes in model organisms to the importance of gene-diet interactions (outstanding among which is the case of the TCF7L2 gene).

DNA methylation biomarkers: cancer and beyond

Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient's response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.

Genomics of ageing in twins

Ageing is a complex multifactorial process, reflecting the progression of all degenerative pathways within an organism. Due to the increase of life expectancy, in recent years, there is a pressing need to identify early-life events and risk factors that determine health outcomes in later life. So far, genetic variation only explains ~20–25 % of the variability of human survival to age 80+. This clearly implies that other factors (environmental, epigenetic and lifestyle) contribute to lifespan and the rate of healthy ageing within an individual. Twin studies in the past two decades proved to be a very powerful tool to discriminate the genetic from the environmental component. The aim of this review is to describe the basic concepts of the twin study design and to report some of the latest studies in which high-throughput technologies (e.g. genome/epigenome-wide assay, next generation sequencing, MS metabolic profiling) combined with the classical twin design have been applied to the analysis of novel ‘omics’ to further understand the molecular mechanisms of human ageing.

Methylation of leukocyte DNA and ovarian cancer: relationships with disease status and outcome

Background

Genome-wide interrogation of DNA methylation (DNAm) in blood-derived leukocytes has become feasible with the advent of CpG genotyping arrays. In epithelial ovarian cancer (EOC), one report found substantial DNAm differences between cases and controls; however, many of these disease-associated CpGs were attributed to differences in white blood cell type distributions.

Methods

We examined blood-based DNAm in 336 EOC cases and 398 controls; we included only high-quality CpG loci that did not show evidence of association with white blood cell type distributions to evaluate association with case status and overall survival.

Results

Of 13,816 CpGs, no significant associations were observed with survival, although eight CpGs associated with survival at p < 10^-3, including methylation within a CpG island located in the promoter region of GABRE (p = 5.38 x 10^-5, HR = 0.95). In contrast, 53 CpG methylation sites were significantly associated with EOC risk (p <5 x10^-6). The top association was observed for the methylation probe cg04834572 located approximately 315 kb upstream of DUSP13 (p = 1.6 x10^-14). Other disease-associated CpGs included those near or within HHIP (cg14580567; p =5.6x10^-11), HDAC3 (cg10414058; p = 6.3x10^-12), and SCR (cg05498681; p = 4.8x10^-7).

Conclusions

We have identified several CpGs in leukocytes that are differentially methylated by case-control status. Since a retrospective study design was used, we cannot differentiate whether DNAm was etiologic or resulting from EOC; thus, prospective studies of EOC-associated loci are the critical next step.

Quantitative identification of differentially methylated loci based on relative entropy for matched case–control data

Aim: As an important epigenetic modification, DNA methylation plays a critical role in regulating multiple biological processes and diseases. Many efforts have been devoted to identifying differentially methylated loci (DML) between cases and controls. Materials & methods: However, most present methods are statistical and are limited in handling methylation data with characteristics of high heterogeneity and non-normal distribution. Here, a quantitative method, quantitative DML (QDML), based on modified relative entropy is introduced to face these challenges, which can identify DML, hypermethylated loci and hypomethylated loci simultaneously. QDML, compared with some statistical methods, does not require a presupposed distribution of methylation data. Furthermore, QDML is more powerful in handling highly heterogeneous data, owing to the difference in sensitivity on every matched sample pair in case–control groups rather than the overall difference of all samples. Results: Simulation studies and real-data application show that QDML has a higher accuracy and a lower false-positive rate when identifying DML than statistical methods. Conclusion: QDML is developed to identify DML based on relative entropy that can quantify the difference in methylation status between cases and controls. Its applications are not limited to methylation data and can be extended to other case–control studies.

DNA hypermethylation and DNA hypomethylation is present at different loci in chronic kidney disease

Genetic risk factors for chronic kidney disease (CKD) are being identified through international collaborations. By comparison, epigenetic risk factors for CKD have only recently been considered using population-based approaches. DNA methylation is a major epigenetic modification that is associated with complex diseases, so we investigated methylome-wide loci for association with CKD. A total of 485,577 unique features were evaluated in 255 individuals with CKD (cases) and 152 individuals without evidence of renal disease (controls). Following stringent quality control, raw data were quantile normalized and β values calculated to reflect the methylation status at each site. The difference in methylation status was evaluated between cases and controls with resultant P values adjusted for multiple testing. Genes with significantly increased and decreased levels of DNA methylation were considered for biological relevance by functional enrichment analysis using KEGG pathways in Partek Genomics Suite. Twenty-three genes, where more than one CpG per loci was identified with Padjusted<10(-8), demonstrated significant methylation changes associated with CKD and additional support for these associated loci was sought from published literature. Strong biological candidates for CKD that showed statistically significant differential methylation include CUX1, ELMO1, FKBP5, INHBA-AS1, PTPRN2, and PRKAG2 genes; several genes are differentially methylated in kidney tissue and RNA-seq supports a functional role for differential methylation in ELMO1 and PRKAG2 genes. This study reports the largest, most comprehensive, genome-wide quantitative evaluation of DNA methylation for association with CKD. Evidence confirming methylation sites influence development of CKD would stimulate research to identify epigenetic therapies that might be clinically useful for CKD.

Epigenetic biomarkers: a step forward for understanding periodontitis

Periodontitis is a common oral disease that is characterized by infection and inflammation of the tooth supporting tissues. While its incidence is highly associated with outgrowth of the pathogenic microbiome, some patients show signs of predisposition and quickly fall into recurrence after treatment. Recent research using genetic associations of candidates as well as genome-wide analysis highlights that variations in genes related to the inflammatory response are associated with an increased risk of periodontitis. Intriguingly, some of the genes are regulated by epigenetic modifications, supposedly established and reprogrammed in response to environmental stimuli. In addition, the treatment with epigenetic drugs improves treatment of periodontitis in a mouse model. In this review, we highlight some of the recent progress identifying genetic factors associated with periodontitis and point to promising approaches in epigenetic research that may contribute to the understanding of molecular mechanisms involving different responses in individuals and the early detection of predispositions that may guide in future oral treatment and disease prevention.