Genetic and environmental exposures constrain epigenetic drift over the human life course

NRN1 genetic variability and methylation changes as biomarkers for cognitive remediation therapy response in schizophrenia

Cognitive remediation therapy (CRT) demonstrates potential in enhancing cognitive function in schizophrenia (SZ), though the identification of molecular biomarkers remains challenging. The Neuritin-1 gene (NRN1) emerges as a promising candidate gene due to its association with SZ, cognitive performance and response to neurotherapeutic treatments. We aimed to investigate whether NRN1 genetic variability and methylation changes following CRT are related to cognitive improvements. Twenty-five SZ patients were randomly assigned to CRT or treatment-as-usual (TAU) groups, with cognitive function and NRN1 methylation assessed pre- and post-intervention using the MATRICS Consensus Cognitive Battery and EpiTYPER. Besides, eleven NRN1 polymorphisms were genotyped. Methylation changes (Δm = post - pre) were analyzed via sparse Partial Least Square Discriminant Analysis (sPLS-DA) to identify latent components (LCs) distinguishing CRT from TAU. To further explore methylation patterns of these LCs, CpG units were grouped into two subsets, yielding Δm means for those with increased and decreased methylation. Cognitive changes (Δcog = post - pre) were used to identify CRT improvers (CRTI, Δcog ≥1), and the association between methylation changes and cognitive improvements post-therapy was also tested. We identified two LCs that differentiated CRT from TAU with a classification error rate of 0.28. The main component, LC1, included 25 CpG units. The subsets of CpG units with increased and decreased post-therapy methylation differed significantly between the two treatment arms, suggesting that differences were not merely data-driven but reflected meaningful biological variation. Additionally, CpG units linked to therapy were also associated with cognitive improvement, with LC1 and the subset of CpG units showing increased methylation post-therapy distinguishing CRT-I from the rest of the patients across multiple cognitive domains. Furthermore, the effect of LC1 on speed processing improvement after CRT was enhanced by considering the NRN1-rs9405890 polymorphism. Notably, these CpG units, particularly those with increased methylation after CRT, overlapped with key gene regulatory elements. Our model, integrating genetics and epigenetics, boosts the understanding of CRT response variability and highlights this multi-level approach as a promising strategy for identifying potential NRN1-related biomarkers of CRT effects, though further studies with larger samples are needed.

Genetic control of DNA methylation is largely shared across European and East Asian populations

DNA methylation is an ideal trait to study the extent of the shared genetic control across ancestries, effectively providing hundreds of thousands of model molecular traits with large QTL effect sizes. We investigate cis DNAm QTLs in three European (n = 3701) and two East Asian (n = 2099) cohorts to quantify the similarities and differences in the genetic architecture across populations. We observe 80,394 associated mQTLs (62.2% of DNAm probes with significant mQTL) to be significant in both ancestries, while 28,925 mQTLs (22.4%) are identified in only a single ancestry. mQTL effect sizes are highly conserved across populations, with differences in mQTL discovery likely due to differences in allele frequency of associated variants and differing linkage disequilibrium between causal variants and assayed SNPs. This study highlights the overall similarity of genetic control across ancestries and the value of ancestral diversity in increasing the power to detect associations and enhancing fine mapping resolution.

Data science using the human epigenome for predicting multifactorial diseases and symptoms

Tweetable abstract This article reviews machine learning models that leverages epigenomic data for predicting multifactorial diseases and symptoms as well as how such models can be utilized to explore new research questions.

Expression of CYP2B6 Enzyme in Human Liver Tissue of HIV and HCV Patients

Background and Objectives: Hepatitis C virus (HCV) and human immunodeficiency virus (HIV) infections present significant public health challenges worldwide. The management of these infections is complicated by the need for antiviral and antiretroviral therapies, which are influenced by drug metabolism mediated by metabolic enzymes and transporters. This study focuses on the gene expression of CYP2B6, CYP3A4, and ABCB1 transporters in patients with HIV, HCV, and HIV/HCV co-infection, aiming to assess their potential association with the choice of therapy, patohistological and clinical parameters of liver damage such as the stage of liver fibrosis, serum levels of ALT and AST, as well as the grade of liver inflammation and other available biochemical parameters. Materials and Methods: The study included 54 patients who underwent liver biopsy, divided into HIV-infected, HCV-infected, and co-infected groups. The mRNA levels of CYP2B6, CYP3A4, and ABCB1 was quantified and compared between the groups, along with the analysis of liver fibrosis and inflammation levels. Results: The results indicated a significant increase in CYP2B6 mRNA levels in co-infected patients, a significant association with the presence of HIV infection with an increase in CYP3A4 mRNA levels. A trend towards downregulation of ABCB1 expression was observed in patients using lamivudine. Conclusions: This study provides insight into gene expression of CYP2B6 CYP3A4, and ABCB1 in HIV, HCV, and HIV/HCV co-infected patients. The absence of correlation with liver damage, inflammation, and specific treatment interventions emphasises the need for additional research to elucidate the complex interplay between gene expression, viral co-infection, liver pathology, and therapeutic responses in these particular patients population.

Rare genetic variants underlie outlying levels of DNA methylation and gene-expression

Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations-the Lothian Birth Cohorts of 1921 and 1936-and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic single nucleotide polymorphisms (SNPs) within 1 kb of DNAm sites in individuals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related individuals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels toward the tails of the population distribution. This study demonstrates the role of rare SNPs in the phenotypic variation of DNAm and the effect of extreme levels of DNAm on gene expression.

DNA Methylation Analysis in Monozygotic Twins Discordant for ALS in Blood Cells

ALS is a fatal motor neuron disease that displays a broad variety of phenotypes ranging from early fatal courses to slowly progressing and rather benign courses. Such divergence can also be seen in genetic ALS cases with varying phenotypes bearing specific mutations, suggesting epigenetic mechanisms like DNA methylation act as disease modifiers. However, the epigenotype dictated by, in addition to other mechanisms, DNA methylation is also strongly influenced by the individual's genotype. Hence, we performed a DNA methylation study using EPIC arrays on 7 monozygotic (MZ) twin pairs discordant for ALS in whole blood, which serves as an ideal model for eliminating the effects of the genetic-epigenetic interplay to a large extent. We found one CpG site showing intra-pair hypermethylation in the affected co-twins, which maps to the Glutamate Ionotropic Receptor Kainate Type Subunit 1 gene (GRIK1). Additionally, we found 4 DMPs which were subsequently confirmed using 2 different statistical approaches. Differentially methylated regions or blocks could not be detected within the scope of this work. In conclusion, we revealed that despite a low sample size, monozygotic twin studies discordant for the disease can bring new insights into epigenetic processes in ALS, pointing to new target loci for further investigations.

Is adiposity related to repeat measures of blood leukocyte DNA methylation across childhood and adolescence?

Epigenetic modifications such as DNA methylation may influence gene expression and phenotypes, including obesity in childhood. The directionality of this relationship is nevertheless unclear, and some evidence suggests that adiposity modifies the epigenome, rather than the other way around. In this pilot study, we utilize data from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) study to examine whether measures of adiposity in childhood and early adolescence are associated with repeated measures of blood leukocyte DNA methylation at LINE-1 repetitive elements and two genes implicated in growth and adiposity: H19 and HSD11B2. Longitudinal epigenetic data were generated from cord blood and blood from follow-up visits in early and late adolescence. We assessed interactions between age and measures of body mass index (BMI) at 5 years of age and weight, BMI and waist circumference in early adolescence to infer whether adiposity deflects age-related DNA methylation changes throughout childhood. Applying linear mixed-effects models, we found an inverse association between measures of childhood BMI (kg/m2 ) and early-teen weight (kg) with repeat measures of H19 DNA methylation. We did not observe any statistically significant associations (p-value <.05) between any anthropometric measures and DNA methylation at LINE-1 or HSD11B2. We did not demonstrate statistically significant evidence in support of deflection of age-related DNA methylation trajectories by adiposity-related measures (age by adiposity interaction term). Given the pilot nature of this study, the relationships between repeat measures of DNA methylation and adiposity-measures across childhood merit further exploration in larger study populations.

An overview of DNA methylation-derived trait score methods and applications

Microarray technology has been used to measure genome-wide DNA methylation in thousands of individuals. These studies typically test the associations between individual DNA methylation sites ("probes") and complex traits or diseases. The results can be used to generate methylation profile scores (MPS) to predict outcomes in independent data sets. Although there are many parallels between MPS and polygenic (risk) scores (PGS), there are key differences. Here, we review motivations, methods, and applications of DNA methylation-based trait prediction, with a focus on common diseases. We contrast MPS with PGS, highlighting where assumptions made in genetic modeling may not hold in epigenetic data.

Epigenetics and the Exposome: DNA Methylation as a Proxy for Health Impacts of Prenatal Environmental Exposures

The accumulation of every day exposures can impact health across the life course, but our understanding of such exposures is impeded by our ability to delineate the relationship between an individual's early life exposome and later life health effects. Measuring the exposome is challenging. Exposure assessed at a given time point captures a snapshot of the exposome but does not represent the full spectrum of exposures across the life course. In addition, the assessment of early life exposures and their effects is often further challenged by lack of relevant samples and the time gap between exposures and related health outcomes in later life. Epigenetics, specifically DNA methylation, has the potential to overcome these barriers as environmental epigenetic perturbances can be retained through time. In this review, we describe how DNA methylation can be framed in the world of the exposome. We offer three compelling examples of common environmental exposures, including cigarette smoke, the endocrine active compound bisphenol A (BPA), and the metal lead (Pb), to illustrate the application of DNA methylation as a proxy to measure the exposome. We discuss areas for future explorations and current limitations of this approach. Epigenetic profiling is a promising and rapidly developing tool and field of study, offering us a unique and powerful way to assess the early life exposome and its effects across different life stages.

Perinatal Lead Exposure Promotes Sex-Specific Epigenetic Programming of Disease-Relevant Pathways in Mouse Heart

Environmental contaminants such as the metal lead (Pb) are associated with cardiovascular disease, but the underlying molecular mechanisms are poorly understood. In particular, little is known about how exposure to Pb during early development impacts the cardiac epigenome at any point across the life course and potential differences between sexes. In a mouse model of human-relevant perinatal exposures, we utilized RNA-seq and Enhanced Reduced Representation Bisulfite Sequencing (ERRBS) to investigate the effects of Pb exposure during gestation and lactation on gene expression and DNA methylation, respectively, in the hearts of male and female mice at weaning. For ERRBS, we identified differentially methylated CpGs (DMCs) or differentially methylated 1000 bp regions (DMRs) based on a minimum absolute change in methylation of 10% and an FDR < 0.05. For gene expression data, an FDR < 0.05 was considered significant. No individual genes met the FDR cutoff for gene expression; however, we found that Pb exposure leads to significant changes in the expression of gene pathways relevant to cardiovascular development and disease. We further found that Pb promotes sex-specific changes in DNA methylation at hundreds of gene loci (280 DMCs and 99 DMRs in males, 189 DMCs and 121 DMRs in females), and pathway analysis revealed that these CpGs and regions collectively function in embryonic development. In males, differential methylation also occurred at genes related to immune function and metabolism. We then investigated whether genes exhibiting differential methylation at weaning were also differentially methylated in hearts from a cohort of Pb-exposed mice at adulthood. We found that a single gene, Galnt2, showed differential methylation in both sexes and time points. In a human cohort investigating the influence of prenatal Pb exposure on the epigenome, we also observed an inverse association between first trimester Pb concentrations and adolescent blood leukocyte DNA methylation at a locus in GALNT2, suggesting that this gene may represent a biomarker of Pb exposure across species. Together, these data, across two time points in mice and in a human birth cohort study, collectively demonstrate that Pb exposure promotes sex-specific programming of the cardiac epigenome, and provide potential mechanistic insight into how Pb causes cardiovascular disease.

A Race-Specific, DNA Methylation Analysis of Aging in Normal Rectum: Implications for the Biology of Aging and Its Relationship to Rectal Cancer

Approximately 90% of colorectal cancer (CRC) develop over the age of 50, highlighting the important role of aging in CRC risk. African Americans (AAs) shoulder a greater CRC burden than European Americans (EA) and are more likely to develop CRC at a younger age. The effects of aging in AA and EA normal rectal tissue have yet to be defined. Here, we performed epigenome-wide DNA methylation analysis in the first, large-scale biracial cohort of normal rectum (n = 140 samples). We identified increased epigenetic age acceleration in EA than AA rectum (p = 3.91 × 10^-4) using linear regression. We also identified differentially methylated regions (DMRs) associated with chronological aging in AA and EA, separately using DMRcate. Next, a consensus set of regions associated with cancer was identified through DMR analysis of two rectal cancer cohorts. The vast majority of AA DMRs were present in our analysis of aging in rectum of EA subjects, though rates of epigenetic drift were significantly greater in AA (p = 1.94 × 10^-45). However, 3.66-fold more DMRs were associated with aging in rectum of EA subjects, many of which were also associated with rectal cancer. Our findings reveal a novel relationship between race, age, DNA methylation and rectal cancer risk that warrants further investigation.

Life-course exposure to air pollution and biological ageing in the Lothian Birth Cohort 1936

BACKGROUND

Exposure to air pollution is associated with a range of diseases. Biomarkers derived from DNA methylation (DNAm) offer potential mechanistic insights into human health differences, connecting disease pathogenesis and biological ageing. However, little is known about sensitive periods during the life course where air pollution might have a stronger impact on DNAm, or whether effects accumulate over time. We examined associations between air pollution exposure across the life course and DNAm-based markers of biological ageing.

METHODS

Data were derived from the Scotland-based Lothian Birth Cohort 1936. Participants' residential history was linked to annual levels of fine particle (PM_2.5), sulphur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) around 1935, 1950, 1970, 1980, 1990, and 2001; pollutant concentrations were estimated using the EMEP4UK atmospheric chemistry transport model. Blood samples were obtained between ages of 70 and 80 years, and Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, DNAmGrimAge, and DNAm telomere length (DNAmTL) were computed. We applied the structured life-course modelling approach: least angle regression identified best-fit life-course models for a composite measure of air pollution (air quality index [AQI]), and mixed-effects regression estimated selected models for AQI and single pollutants.

RESULTS

We included 525 individuals with 1782 observations. In the total sample, increased air pollution around 1970 was associated with higher epigenetic age (AQI: b = 0.322 year, 95 %CI: 0.088, 0.555) measured with Horvath DNAmAge in late adulthood. We found shorter DNAmTL among males with higher air pollution around 1980 (AQI: b = -0.015 kilobase, 95 %CI: -0.027, -0.004) and among females with higher exposure around 1935 (AQI: b = -0.017 kilobase, 95 %CI: -0.028, -0.006). Findings were more consistent for the pollutants PM_2.5, SO₂ and NO₂.

DISCUSSION

We tested the life-course relationship between air pollution and DNAm-based biomarkers. Air pollution around birth and in young-to-middle adulthood is linked to accelerated epigenetic ageing and telomere-associated ageing in later life.

A comparison of blood and brain-derived ageing and inflammation-related DNA methylation signatures and their association with microglial burdens

Inflammation and ageing-related DNA methylation patterns in the blood have been linked to a variety of morbidities, including cognitive decline and neurodegenerative disease. However, it is unclear how these blood-based patterns relate to patterns within the brain and how each associates with central cellular profiles. In this study, we profiled DNA methylation in both the blood and in five post mortem brain regions (BA17, BA20/21, BA24, BA46 and hippocampus) in 14 individuals from the Lothian Birth Cohort 1936. Microglial burdens were additionally quantified in the same brain regions. DNA methylation signatures of five epigenetic ageing biomarkers ('epigenetic clocks'), and two inflammatory biomarkers (methylation proxies for C-reactive protein and interleukin-6) were compared across tissues and regions. Divergent associations between the inflammation and ageing signatures in the blood and brain were identified, depending on region assessed. Four out of the five assessed epigenetic age acceleration measures were found to be highest in the hippocampus (β range = 0.83-1.14, p ≤ 0.02). The inflammation-related DNA methylation signatures showed no clear variation across brain regions. Reactive microglial burdens were found to be highest in the hippocampus (β = 1.32, p = 5 × 10-4 ); however, the only association identified between the blood- and brain-based methylation signatures and microglia was a significant positive association with acceleration of one epigenetic clock (termed DNAm PhenoAge) averaged over all five brain regions (β = 0.40, p = 0.002). This work highlights a potential vulnerability of the hippocampus to epigenetic ageing and provides preliminary evidence of a relationship between DNA methylation signatures in the brain and differences in microglial burdens.

Local CpG density affects the trajectory and variance of age-associated DNA methylation changes

BACKGROUND

DNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in human disease. However, the molecular mechanisms underpinning age-associated DNA methylation changes remain unknown. Local DNA sequence can program steady-state DNA methylation levels, but how it influences age-associated methylation changes is unknown.

RESULTS

We analyze longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs. We show that changes in methylation with age occur at 182,760 loci largely independently of variation in cell type proportions. These changes are especially apparent at 8322 low CpG density loci. Using SNP data from the same individuals, we demonstrate that methylation trajectories are affected by local sequence polymorphisms at 1487 low CpG density loci. More generally, we find that low CpG density regions are particularly prone to change and do so variably between individuals in people aged over 65. This differs from the behavior of these regions in younger individuals where they predominantly lose methylation.

CONCLUSIONS

Our results, which we reproduce in two independent groups of individuals, demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions.

Epigenetics, DNA damage, and aging

Over the course of a human lifespan, genome integrity erodes, leading to an increased abundance of several types of chromatin changes. The abundance of DNA lesions (chemical perturbations to nucleotides) increases with age, as does the number of genomic mutations and transcriptional disruptions caused by replication or transcription of those lesions, respectively. At the epigenetic level, precise DNA methylation patterns degrade, likely causing increasingly stochastic variations in gene expression. Similarly, the tight regulation of histone modifications begins to unravel. The genomic instability caused by these mechanisms allows transposon element reactivation and remobilization, further mutations, gene dysregulation, and cytoplasmic chromatin fragments. This cumulative genomic instability promotes cell signaling events that drive cell fate decisions and extracellular communications known to disrupt tissue homeostasis and regeneration. In this Review, we focus on age-related epigenetic changes and their interactions with age-related genomic changes that instigate these events.

DNA methylation-based predictors of health: applications and statistical considerations

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

Braf mutation induces rapid neoplastic transformation in the aged and aberrantly methylated intestinal epithelium

OBJECTIVE

Sessile serrated lesions (SSLs) are common across the age spectrum, but the BRAF mutant cancers arising occur predominantly in the elderly. Aberrant DNA methylation is uncommon in SSL from young patients. Here, we interrogate the role of ageing and DNA methylation in SSL initiation and progression.

DESIGN

We used an inducible model of Braf mutation to direct recombination of the oncogenic Braf V637E allele to the murine intestine. BRAF mutation was activated after periods of ageing, and tissue was assessed for histological, DNA methylation and gene expression changes thereafter. We also investigated DNA methylation alterations in human SSLs.

RESULTS

Inducing Braf mutation in aged mice was associated with a 10-fold relative risk of serrated lesions compared with young mice. There were extensive differences in age-associated DNA methylation between animals induced at 9 months versus wean, with relatively little differential Braf-specific methylation. DNA methylation at WNT pathway genes scales with age and Braf mutation accelerated age-associated DNA methylation. In human SSLs, increased epigenetic age was associated with high-risk serrated colorectal neoplasia.

CONCLUSIONS

SSLs arising in the aged intestine are at a significantly higher risk of spontaneous neoplastic progression. These findings provide support for a new conceptual model for serrated colorectal carcinogenesis, whereby risk of Braf-induced neoplastic transformation is dependent on age and may be related to age-associated molecular alterations that accumulate in the ageing intestine, including DNA methylation. This may have implications for surveillance and chemopreventive strategies targeting the epigenome.

A robust mean and variance test with application to high-dimensional phenotypes

Most studies of continuous health-related outcomes examine differences in mean levels (location) of the outcome by exposure. However, identifying effects on the variability (scale) of an outcome, and combining tests of mean and variability (location-and-scale), could provide additional insights into biological mechanisms. A joint test could improve power for studies of high-dimensional phenotypes, such as epigenome-wide association studies of DNA methylation at CpG sites. One possible cause of heterogeneity of variance is a variable interacting with exposure in its effect on outcome, so a joint test of mean and variability could help in the identification of effect modifiers. Here, we review a scale test, based on the Brown-Forsythe test, for analysing variability of a continuous outcome with respect to both categorical and continuous exposures, and develop a novel joint location-and-scale score (JLSsc) test. These tests were compared to alternatives in simulations and used to test associations of mean and variability of DNA methylation with gender and gestational age using data from the Accessible Resource for Integrated Epigenomics Studies (ARIES). In simulations, the Brown-Forsythe and JLSsc tests retained correct type I error rates when the outcome was not normally distributed in contrast to the other approaches tested which all had inflated type I error rates. These tests also identified > 7500 CpG sites for which either mean or variability in cord blood methylation differed according to gender or gestational age. The Brown-Forsythe test and JLSsc are robust tests that can be used to detect associations not solely driven by a mean effect.

DNA methylome-wide association study of genetic risk for depression implicates antigen processing and immune responses

BACKGROUND

Depression is a disabling and highly prevalent condition where genetic and epigenetic, such as DNA methylation (DNAm), differences contribute to disease risk. DNA methylation is influenced by genetic variation but the association between polygenic risk of depression and DNA methylation is unknown.

METHODS

We investigated the association between polygenic risk scores (PRS) for depression and DNAm by conducting a methylome-wide association study (MWAS) in Generation Scotland (N = 8898, mean age = 49.8 years) with replication in the Lothian Birth Cohorts of 1921 and 1936 and adults in the Avon Longitudinal Study of Parents and Children (ALSPAC) (Ncombined = 2049, mean age = 79.1, 69.6 and 47.2 years, respectively). We also conducted a replication MWAS in the ALSPAC children (N = 423, mean age = 17.1 years). Gene ontology analysis was conducted for the cytosine-guanine dinucleotide (CpG) probes significantly associated with depression PRS, followed by Mendelian randomisation (MR) analysis to infer the causal relationship between depression and DNAm.

RESULTS

Widespread associations (NCpG = 71, pBonferroni < 0.05, p < 6.3 × 10-8) were found between PRS constructed using genetic risk variants for depression and DNAm in CpG probes that localised to genes involved in immune responses and neural development. The effect sizes for the significant associations were highly correlated between the discovery and replication samples in adults (r = 0.79) and in adolescents (r = 0.82). Gene Ontology analysis showed that significant CpG probes are enriched in immunological processes in the human leukocyte antigen system. Additional MWAS was conducted for each lead genetic risk variant. Over 47.9% of the independent genetic risk variants included in the PRS showed associations with DNAm in CpG probes located in both the same (cis) and distal (trans) locations to the genetic loci (pBonferroni < 0.045). Subsequent MR analysis showed that there are a greater number of causal effects found from DNAm to depression than vice versa (DNAm to depression: pFDR ranged from 0.024 to 7.45 × 10-30; depression to DNAm: pFDR ranged from 0.028 to 0.003).

CONCLUSIONS

PRS for depression, especially those constructed from genome-wide significant genetic risk variants, showed methylome-wide differences associated with immune responses. Findings from MR analysis provided evidence for causal effect of DNAm to depression.

Environmentally sensitive hotspots in the methylome of the early human embryo

In humans, DNA methylation marks inherited from gametes are largely erased following fertilisation, prior to construction of the embryonic methylome. Exploiting a natural experiment of seasonal variation including changes in diet and nutritional status in rural Gambia, we analysed three datasets covering two independent child cohorts and identified 259 CpGs showing consistent associations between season of conception (SoC) and DNA methylation. SoC effects were most apparent in early infancy, with evidence of attenuation by mid-childhood. SoC-associated CpGs were enriched for metastable epialleles, parent-of-origin-specific methylation and germline differentially methylated regions, supporting a periconceptional environmental influence. Many SoC-associated CpGs overlapped enhancers or sites of active transcription in H1 embryonic stem cells and fetal tissues. Half were influenced but not determined by measured genetic variants that were independent of SoC. Environmental 'hotspots' providing a record of environmental influence at periconception constitute a valuable resource for investigating epigenetic mechanisms linking early exposures to lifelong health and disease.

The genetic and epigenetic profile of serum S100β in the Lothian Birth Cohort 1936 and its relationship to Alzheimer’s disease

Background: Circulating S100 calcium-binding protein (S100β) is a marker of brain inflammation that has been associated with a range of neurological conditions. To provide insight into the molecular regulation of S100β and its potential causal associations with Alzheimer’s disease, we carried out genome- and epigenome-wide association studies (GWAS/EWAS) of serum S100β levels in older adults and performed Mendelian randomisation with Alzheimer’s disease. Methods: GWAS (N=769, mean age 72.5 years, sd = 0.7) and EWAS (N=722, mean age 72.5 years, sd = 0.7) of S100β levels were performed in participants from the Lothian Birth Cohort 1936. Conditional and joint analysis (COJO) was used to identify independent loci. Expression quantitative trait locus (eQTL) analyses were performed for lead loci that had genome-wide significant associations with S100β. Bidirectional, two-sample Mendelian randomisation was used to test for causal associations between S100β and Alzheimer’s disease. Colocalisation between S100β and Alzheimer’s disease GWAS loci was also examined. Results: We identified 154 SNPs from chromosome 21 that associated (P<5x10-8) with S100β protein levels. The lead variant was located in the S100β gene (rs8128872, P=5.0x10-17). We found evidence that two independent causal variants existed for both transcription of S100β and S100β protein levels in our eQTL analyses. No CpG sites were associated with S100β levels at the epigenome-wide significant level (P<3.6x10-8); the lead probe was cg06833709 (P=5.8x10-6), which mapped to the LGI1 gene. There was no evidence of a causal association between S100β levels and Alzheimer’s disease or vice versa and no evidence for colocalisation between S100β and Alzheimer’s disease loci. Conclusions: These data provide insight into the molecular regulators of S100β levels. This context may aid in understanding the role of S100β in brain inflammation and neurological disease.

Blood-based epigenome-wide analyses of cognitive abilities

BACKGROUND

Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia.

RESULTS

Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g). A DNAm predictor explains ~4% of the variance, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes.

CONCLUSIONS

As sample sizes increase, the ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.

The genetic and epigenetic profile of serum S100β in the Lothian Birth Cohort 1936 and its relationship to Alzheimer's disease

Background: Circulating S100 calcium-binding protein (S100β) is a marker of brain inflammation that has been associated with a range of neurological conditions. To provide insight into the molecular regulation of S100β and its potential causal associations with Alzheimer's disease, we carried out genome- and epigenome-wide association studies (GWAS/EWAS) of serum S100β levels in older adults and performed Mendelian randomisation with Alzheimer's disease. Methods: GWAS (N=769, mean age 72.5 years, sd = 0.7) and EWAS (N=722, mean age 72.5 years, sd = 0.7) of S100β levels were performed in participants from the Lothian Birth Cohort 1936. Conditional and joint analysis (COJO) was used to identify independent loci. Expression quantitative trait locus (eQTL) analyses were performed for lead loci that had genome-wide significant associations with S100β. Bidirectional, two-sample Mendelian randomisation was used to test for causal associations between S100β and Alzheimer's disease. Colocalisation between S100β and Alzheimer's disease GWAS loci was also examined. Results: We identified 154 SNPs from chromosome 21 that associated (P<5x10 ^-8) with S100β protein levels. The lead variant was located in the S100β gene (rs8128872, P=5.0x10 ^-17). We found evidence that two independent causal variants existed for both transcription of S100β and S100β protein levels in our eQTL analyses . No CpG sites were associated with S100β levels at the epigenome-wide significant level (P<3.6x10 ^-8); the lead probe was cg06833709 (P=5.8x10 ^-6), which mapped to the LGI1 gene. There was no evidence of a causal association between S100β levels and Alzheimer's disease or vice versa and no evidence for colocalisation between S100β and Alzheimer's disease loci. Conclusions: These data provide insight into the molecular regulators of S100β levels. This context may aid in understanding the role of S100β in brain inflammation and neurological disease.

Epigenetic scores for the circulating proteome as tools for disease prediction

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNA methylation (DNAm) signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample (Generation Scotland; n = 9537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore-disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors, and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.

Culture-Associated DNA Methylation Changes Impact on Cellular Function of Human Intestinal Organoids

BACKGROUND & AIMS

Human intestinal epithelial organoids (IEOs) are a powerful tool to model major aspects of intestinal development, health, and diseases because patient-derived cultures retain many features found in vivo. A necessary aspect of the organoid model is the requirement to expand cultures in vitro through several rounds of passaging. This is of concern because the passaging of cells has been shown to affect cell morphology, ploidy, and function.

METHODS

Here, we analyzed 173 human IEO lines derived from the small and large bowel and examined the effect of culture duration on DNA methylation (DNAm). Furthermore, we tested the potential impact of DNAm changes on gene expression and cellular function.

RESULTS

Our analyses show a reproducible effect of culture duration on DNAm in a large discovery cohort as well as 2 publicly available validation cohorts generated in different laboratories. Although methylation changes were seen in only approximately 8% of tested cytosine-phosphate-guanine dinucleotides (CpGs) and global cellular function remained stable, a subset of methylation changes correlated with altered gene expression at baseline as well as in response to inflammatory cytokine exposure and withdrawal of Wnt agonists. Importantly, epigenetic changes were found to be enriched in genomic regions associated with colonic cancer and distant to the site of replication, indicating similarities to malignant transformation.

CONCLUSIONS

Our study shows distinct culture-associated epigenetic changes in mucosa-derived human IEOs, some of which appear to impact gene transcriptomic and cellular function. These findings highlight the need for future studies in this area and the importance of considering passage number as a potentially confounding factor.

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

An epigenetic predictor of death captures multi-modal measures of brain health

Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm). A novel epigenetic clock, termed 'DNAm GrimAge' has outperformed its predecessors in predicting the risk of mortality as well as many age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n = 709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over the eighth decade (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10-16). Higher DNAm GrimAge was associated with lower age 11 IQ (β = -0.11), lower age 73 general cognitive ability (β = -0.18), decreased brain volume (β = -0.25) and increased brain white matter hyperintensities (β = 0.17). There was tentative evidence for a longitudinal association between DNAm GrimAge and cognitive decline from age 70 to 79. Sixty-nine of 137 health- and brain-related phenotypes tested were significantly associated with GrimAge. Adjusting all models for childhood intelligence attenuated to non-significance a small number of associations (12/69 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge associates with lower cognitive ability and brain vascular lesions in older age, independently of early-life cognitive ability. This epigenetic predictor of mortality associates with different measures of brain health and may aid in the prediction of age-related cognitive decline.

Epigenetic Changes Associated With Exposure to Glyphosate-Based Herbicides in Mammals

Glyphosate is a phosphonomethyl amino acid derivative present in a number of non-selective and systemic herbicides. During the last years the use of glyphosate-based herbicide (GBH) has been increasing exponentially around the world, including Argentina. This fact added to the detection of glyphosate, and its main metabolite, amino methylphosphonic acid (AMPA), in environmental matrices such as soil, sediments, and food, has generated great concern about its risks for humans, animals, and environment. During the last years, there were controversy and intense debate regarding the toxicological effects of these compounds associated with the endocrine system, cancer, reproduction, and development. The mechanisms of action of GBH and their metabolites are still under investigation, although recent findings have shown that they could comprise epigenetic modifications. These are reversible mechanisms linked to tissue-specific silencing of gene expression, genomic imprinting, and tumor growth. Particularly, glyphosate, GBH, and AMPA have been reported to produce changes in global DNA methylation, methylation of specific genes, histone modification, and differential expression of non-coding RNAs in human cells and rodents. Importantly, the epigenome could be heritable and could lead to disease long after the exposure has ended. This mini-review summarizes the epigenetic changes produced by glyphosate, GBHs, and AMPA in humans and rodents and proposes it as a potential mechanism of action through which these chemical compounds could alter body functions.

Epigenetic predictors of lifestyle traits applied to the blood and brain

Modifiable lifestyle factors influence the risk of developing many neurological diseases. These factors have been extensively linked with blood-based genome-wide DNA methylation, but it is unclear if the signatures from blood translate to the target tissue of interest-the brain. To investigate this, we apply blood-derived epigenetic predictors of four lifestyle traits to genome-wide DNA methylation from five post-mortem brain regions and the last blood sample prior to death in 14 individuals in the Lothian Birth Cohort 1936. Using these matched samples, we found that correlations between blood and brain DNA methylation scores for smoking, high-density lipoprotein cholesterol, alcohol and body mass index were highly variable across brain regions. Smoking scores in the dorsolateral prefrontal cortex had the strongest correlations with smoking scores in blood (r = 0.5, n = 14, P = 0.07) and smoking behaviour (r = 0.56, n = 9, P = 0.12). This was also the brain region which exhibited the largest correlations for DNA methylation at site cg05575921 - the single strongest correlate of smoking in blood-in relation to blood (r = 0.61, n = 14, P = 0.02) and smoking behaviour (r = -0.65, n = 9, P = 0.06). This suggested a particular vulnerability to smoking-related differential methylation in this region. Our work contributes to understanding how lifestyle factors affect the brain and suggest that lifestyle-related DNA methylation is likely to be both brain region dependent and in many cases poorly proxied for by blood. Though these pilot data provide a rarely-available opportunity for the comparison of methylation patterns across multiple brain regions and the blood, due to the limited sample size available our results must be considered as preliminary and should therefore be used as a basis for further investigation.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Creating and validating a DNA methylation-based proxy for interleukin-6

Background

Studies evaluating the relationship between chronic inflammation and cognitive functioning have produced heterogeneous results. A potential reason for this is the variability of inflammatory mediators which could lead to misclassifications of individuals’ persisting levels of inflammation. DNA methylation (DNAm) has shown utility in indexing environmental exposures and could be leveraged to provide proxy signatures of chronic inflammation.

Method

We conducted an elastic net regression of interleukin-6 (IL-6) in a cohort of 875 older adults (Lothian Birth Cohort 1936; mean age: 70 years) to develop a DNAm-based predictor. The predictor was tested in an independent cohort (Generation Scotland; N = 7028 [417 with measured IL-6], mean age: 51 years).

Results

A weighted score from 35 CpG sites optimally predicted IL-6 in the independent test set (Generation Scotland; R² = 4.4%, p = 2.1 × 10⁻⁵). In the independent test cohort, both measured IL-6 and the DNAm proxy increased with age (serum IL-6: n = 417, β = 0.02, SE = 0.004, p = 1.3 × 10⁻⁷; DNAm IL-6 score: N = 7028, β = 0.02, SE = 0.0009, p < 2 × 10⁻¹⁶). Serum IL-6 did not associate with cognitive ability (n = 417, β = −0.06, SE = 0.05, p = .19); however, an inverse association was identified between the DNAm score and cognitive functioning (N = 7028, β = −0.16, SE = 0.02, p_FDR < 2 × 10⁻¹⁶).

Conclusions

These results suggest methylation-based predictors can be used as proxies for inflammatory markers, potentially allowing for further insight into the relationship between inflammation and pertinent health outcomes.

Epigenetic Markers Associated with Schistosomiasis

It is important to consider the use of the epigenome as source of complementary data for genome knowledge, which is suitable for the diagnosis of schistosomiasis. Usually, a laboratory diagnosis of schistosomiasis is performed by means of 1. Egg detection in the stool or urine by microscopy remains with limited sensitivity; 2. Immunological screening, in which positivity persists after treatment, and 3. Molecular appraisals prevail over the disadvantages of the currently used methods. In this sense, molecular methodologies are being developed based on epigenetic biomarkers, aiming to improve the diagnosis of the disease and clinical treatment as early as possible to prevent the occurrence of serious liver damage.

Epigenome-wide change and variation in DNA methylation in childhood: trajectories from birth to late adolescence

DNA methylation (DNAm) is known to play a pivotal role in childhood health and development, but a comprehensive characterization of genome-wide DNAm trajectories across this age period is currently lacking. We have therefore performed a series of epigenome-wide association studies in 5019 blood samples collected at multiple time-points from birth to late adolescence from 2348 participants of two large independent cohorts. DNAm profiles of autosomal CpG sites (CpGs) were generated using the Illumina Infinium HumanMethylation450 BeadChip. Change over time was widespread, observed at over one-half (53%) of CpGs. In most cases, DNAm was decreasing (36% of CpGs). Inter-individual variation in linear trajectories was similarly widespread (27% of CpGs). Evidence for non-linear change and inter-individual variation in non-linear trajectories was somewhat less common (11 and 8% of CpGs, respectively). Very little inter-individual variation in change was explained by sex differences (0.4% of CpGs) even though sex-specific DNAm was observed at 5% of CpGs. DNAm trajectories were distributed non-randomly across the genome. For example, CpGs with decreasing DNAm were enriched in gene bodies and enhancers and were annotated to genes enriched in immune-developmental functions. In contrast, CpGs with increasing DNAm were enriched in promoter regions and annotated to genes enriched in neurodevelopmental functions. These findings depict a methylome undergoing widespread and often non-linear change throughout childhood. They support a developmental role for DNA methylation that extends beyond birth into late adolescence and has implications for understanding life-long health and disease. DNAm trajectories can be visualized at http://epidelta.mrcieu.ac.uk.

Genetic Determinism Exists for the Global DNA Methylation Rate in Sheep

Recent studies showed that epigenetic marks, including DNA methylation, influence production and adaptive traits in plants and animals. So far, most studies dealing with genetics and epigenetics considered DNA methylation sites independently. However, the genetic basis of the global DNA methylation rate (GDMR) remains unknown. The main objective of the present study was to investigate genetic determinism of GDMR in sheep. The experiment was conducted on 1,047 Romane sheep allocated into 10 half-sib families. After weaning, all the lambs were phenotyped for global GDMR in blood as well as for production and adaptive traits. GDMR was measured by LUminometric Methylation Analysis (LUMA) using a pyrosequencing approach. Association analyses were conducted on some of the lambs (n = 775) genotyped by using the Illumina OvineSNP50 BeadChip. Blood GDMR varied among the animals (average 70.7 ± 6.0%). Female lambs had significantly higher GDMR than male lambs. Inter-individual variability of blood GDMR had an additive genetic component and heritability was moderate (h² = 0.20 ± 0.05). No significant genetic correlation was found between GDMR and growth or carcass traits, birthcoat, or social behaviors. Association analyses revealed 28 QTLs associated with blood GDMR. Seven genomic regions on chromosomes 1, 5, 11, 17, 24, and 26 were of most interest due to either high significant associations with GDMR or to the relevance of genes located close to the QTLs. QTL effects were moderate. Genomic regions associated with GDMR harbored several genes not yet described as being involved in DNA methylation, but some are already known to play an active role in gene expression. In addition, some candidate genes, CHD1, NCO3A, KDM8, KAT7, and KAT6A have previously been described to be involved in epigenetic modifications. In conclusion, the results of the present study indicate that blood GDMR in domestic sheep is under polygenic influence and provide new insights into DNA methylation genetic determinism.

Epigenome-wide association study on diffusing capacity of the lung

BACKGROUND

Epigenetics may play an important role in the pathogenesis of lung diseases. However, little is known about the epigenetic factors that influence impaired gas exchange at the lung.

AIM

To identify the epigenetic signatures of the diffusing capacity of the lung measured by carbon monoxide uptake (the diffusing capacity of the lung for carbon monoxide (D LCO)).

METHODS

An epigenome-wide association study (EWAS) was performed on diffusing capacity, measured by carbon monoxide uptake (D LCO) and per alveolar volume (V A) (as D LCO/V A), using the single-breath technique in 2674 individuals from two population-based cohort studies. These were the Rotterdam Study (RS, the "discovery panel") and the Framingham Heart Study (FHS, the "replication panel"). We assessed the clinical relevance of our findings by investigating the identified sites in whole blood and by lung tissue specific gene expression.

RESULTS

We identified and replicated two CpG sites (cg05575921 and cg05951221) that were significantly associated with D LCO/V A and one (cg05575921) suggestively associated with D LCO. Furthermore, we found a positive association between aryl hydrocarbon receptor repressor (AHRR) gene (cg05575921) hypomethylation and gene expression of exocyst complex component 3 (EXOC3) in whole blood. We confirmed that the expression of EXOC3 in lung tissue is positively associated with D LCO/V A and D LCO.

CONCLUSIONS

We report on epigenome-wide associations with diffusing capacity in the general population. Our results suggest EXOC3 to be an excellent candidate, through which smoking-induced hypomethylation of AHRR might affect pulmonary gas exchange.

Robustness during Aging-Molecular Biological and Physiological Aspects

Understanding the process of aging is still an important challenge to enable healthy aging and to prevent age-related diseases. Most studies in age research investigate the decline in organ functionality and gene activity with age. The focus on decline can even be considered a paradigm in that field. However, there are certain aspects that remain surprisingly stable and keep the organism robust. Here, we present and discuss various properties of robust behavior during human and animal aging, including physiological and molecular biological features, such as the hematocrit, body temperature, immunity against infectious diseases and others. We examine, in the context of robustness, the different theories of how aging occurs. We regard the role of aging in the light of evolution.

Toward an Integrative Model of Sources of Personality Stability and Change

There is now compelling evidence that people’s typical patterns of thinking, feeling, striving, and behaving are both consistent and malleable. Therefore, researchers have begun to examine the distinct sources of personality stability and change. In this article, we discuss traditional classifications of sources, review key findings, and highlight limitations and open questions in research on personality stability and change. We conclude by describing an integrative model and by outlining important directions for future research.

The multifaceted functional role of DNA methylation in immune-mediated rheumatic diseases

Genomic predisposition cannot explain the onset of complex diseases, as well illustrated by the largely incomplete concordance among monozygotic twins. Epigenetic mechanisms, including DNA methylation, chromatin remodelling and non-coding RNA, are considered to be the link between environmental stimuli and disease onset on a permissive genetic background in autoimmune and chronic inflammatory diseases. The paradigmatic cases of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), Sjogren's syndrome (SjS) and type-1 diabetes (T1D) share the loss of immunological tolerance to self-antigen influenced by several factors, with a largely incomplete role of individual genomic susceptibility. The most widely investigated epigenetic mechanism is DNA methylation which is associated with gene silencing and is due to the binding of methyl-CpG binding domain (MBD)-containing proteins, such as MECP2, to 5-methylcytosine (5mC). Indeed, a causal relationship occurs between DNA methylation and transcription factors occupancy and recruitment at specific genomic locus. In most cases, the results obtained in different studies are controversial in terms of DNA methylation comparison while fascinating evidence comes from the comparison of the epigenome in clinically discordant monozygotic twins. In this manuscript, we will review the mechanisms of epigenetics and DNA methylation changes in specific immune-mediated rheumatic diseases to highlight remaining unmet needs and to identify possible shared mechanisms beyond different tissue involvements with common therapeutic opportunities. Key Points • DNA methylation has a crucial role in regulating and tuning the immune system. • Evidences suggest that dysregulation of DNA methylation is pivotal in the context of immune-mediated rheumatic diseases. • DNA methylation dysregulation in FOXP3 and interferons-related genes is shared within several autoimmune diseases. • DNA methylation is an attractive marker for diagnosis and therapy.

Associations between Brief Resilience Scale scores and ageing-related domains in the Lothian Birth Cohort 1936

[Correction Notice: An Erratum for this article was reported online in Psychology and Aging on Mar 5 2020 (see record 2020-16850-001). This article should have been published under the terms of the Creative Commons Attribution License (CC BY 3.0). Therefore, the article was amended to list the authors as copyright holders, and information about the terms of the CC BY 3.0 was added to the author note. In addition, the article is now open access. All versions of this article have been corrected.] It is unclear how scores on self-report resilience scales relate to key ageing-related domains in older age and if they truly measure resilience. We examined antecedents and outcomes of age-76 Brief Resilience Scale (BRS) scores in participants of the Lothian Birth Cohort 1936 (n = 655). We found bivariate associations between age-76 BRS scores and ageing-relevant antecedent variables measured at least 3 years earlier, from domains of cognitive ability, physical fitness, and wellbeing and, additionally, sociodemographics and personality (absolute r's from .082 to .49). Biological health variables were not associated with BRS scores. Age-73 cognitive ability (largest β = 0.14), physical fitness (largest β = 0.084), and wellbeing variables (largest β = 0.26) made positive independent contributions to age-76 BRS scores in multivariate models. In a conservative model including all variables as covariates, corrected for multiple comparisons, only emotional stability (neuroticism) significantly independently contributed to BRS score (β = 0.33). An exploratory backward elimination model indicated more wellbeing and personality associates of BRS scores (βs from .087 to .32). We used latent difference score modeling to assess outcomes of BRS scores; we examined associations between age-76 BRS and change in latent factors of age-related domains between age 76 and 79. Whereas BRS scores were related cross-sectionally to levels of latent cognitive ability (r = .19), physical fitness (r = .20), and wellbeing (r = .60) factors, they were not related to declines in these domains. The independence of the BRS construct from established wellbeing and personality factors is unclear. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Deary I, Liu Q, Liu S, Elosua R, DeMeo DL, Ordovás JM. Epigenomic Assessment of Cardiovascular Disease Risk and Interactions With Traditional Risk Metrics

Background Epigenome-wide association studies for cardiometabolic risk factors have discovered multiple loci associated with incident cardiovascular disease (CVD). However, few studies have sought to directly optimize a predictor of CVD risk. Furthermore, it is challenging to train multivariate models across multiple studies in the presence of study- or batch effects. Methods and Results Here, we analyzed existing DNA methylation data collected using the Illumina HumanMethylation450 microarray to create a predictor of CVD risk across 3 cohorts: Women's Health Initiative, Framingham Heart Study Offspring Cohort, and Lothian Birth Cohorts. We trained Cox proportional hazards-based elastic net regressions for incident CVD separately in each cohort and used a recently introduced cross-study learning approach to integrate these individual scores into an ensemble predictor. The methylation-based risk score was associated with CVD time-to-event in a held-out fraction of the Framingham data set (hazard ratio per SD=1.28, 95% CI, 1.10-1.50) and predicted myocardial infarction status in the independent REGICOR (Girona Heart Registry) data set (odds ratio per SD=2.14, 95% CI, 1.58-2.89). These associations remained after adjustment for traditional cardiovascular risk factors and were similar to those from elastic net models trained on a directly merged data set. Additionally, we investigated interactions between the methylation-based risk score and both genetic and biochemical CVD risk, showing preliminary evidence of an enhanced performance in those with less traditional risk factor elevation. Conclusions This investigation provides proof-of-concept for a genome-wide, CVD-specific epigenomic risk score and suggests that DNA methylation data may enable the discovery of high-risk individuals who would be missed by alternative risk metrics.

DNA methylation outlier burden, health, and ageing in Generation Scotland and the Lothian Birth Cohorts of 1921 and 1936

BACKGROUND

DNA methylation outlier burden has been suggested as a potential marker of biological age. An outlier is typically defined as DNA methylation levels at any one CpG site that are three times beyond the inter-quartile range from the 25th or 75th percentiles compared to the rest of the population. DNA methylation outlier burden (the number of such outlier sites per individual) increases exponentially with age. However, these findings have been observed in small samples.

RESULTS

Here, we showed an association between age and log10-transformed DNA methylation outlier burden in a large cross-sectional cohort, the Generation Scotland Family Health Study (N = 7010, β = 0.0091, p < 2 × 10-16), and in two longitudinal cohort studies, the Lothian Birth Cohorts of 1921 (N = 430, β = 0.033, p = 7.9 × 10-4) and 1936 (N = 898, β = 0.0079, p = 0.074). Significant confounders of both cross-sectional and longitudinal associations between outlier burden and age included white blood cell proportions, body mass index (BMI), smoking, and batch effects. In Generation Scotland, the increase in epigenetic outlier burden with age was not purely an artefact of an increase in DNA methylation level variability with age (epigenetic drift). Log10-transformed DNA methylation outlier burden in Generation Scotland was not related to self-reported, or family history of, age-related diseases, and it was not heritable (SNP-based heritability of 4.4%, p = 0.18). Finally, DNA methylation outlier burden was not significantly related to survival in either of the Lothian Birth Cohorts individually or in the meta-analysis after correction for multiple testing (HRmeta = 1.12; 95% CImeta = [1.02; 1.21]; pmeta = 0.021).

CONCLUSIONS

These findings suggest that, while it does not associate with ageing-related health outcomes, DNA methylation outlier burden does track chronological ageing and may also relate to survival. DNA methylation outlier burden may thus be useful as a marker of biological ageing.

Alterations in 5hmC level and genomic distribution in aging-related epigenetic drift in human adipose stem cells

Aim: To clarify mechanisms affecting the level and distribution of 5-hydroxymethylcytosine (5hmC) during aging. Materials & methods: We examined levels and genomic distribution of 5hmC along with the expression of ten-eleven translocation methylcytosine dioxygenases (TETs) in adipose stem cells in young and age-advanced individuals. Results: 5hmC levels were higher in adipose stem cells of age-advanced than young individuals (p = 0.0003), but were not associated with age-related changes in expression of TETs. 5hmC levels correlated with population doubling time (r = 0.62; p = 0.01). We identified 58 differentially hydroxymethylated regions. Hypo-hydroxymethylated differentially hydroxymethylated regions were approximately twofold enriched in CCCTC-binding factor binding sites. Conclusion: Accumulation of 5hmC in aged cells can result from inefficient active demethylation due to altered TETs activity and reduced passive demethylation due to slower proliferation.

Attitudes to ageing, biomarkers of ageing and mortality: the Lothian Birth Cohort 1936

Objective

To investigate whether people with more positive attitudes to ageing are biologically younger as defined by leucocyte telomere length, accelerated DNA methylation GrimAge (AgeAccelGrim) and brain-predicted age difference, and whether these biomarkers explain relationships between attitudes to ageing and mortality.

Methods

We used linear regression to examine cross-sectionally attitudes to ageing (measured using the Attitudes to Ageing Questionnaire) and the three biomarkers in 758 adults, mean age 72.5 years, from the Lothian Birth Cohort 1936. We used Cox proportional hazards models to examine longitudinally attitudes to ageing and mortality and the role of the biomarkers.

Results

More positive attitude to physical change was associated with younger biological age, as measured by AgeAccelGrim and brain-predicted age difference in age-adjusted and sex-adjusted models: for an SD higher score, AgeAccelGrim was lower by -0.73 (95% CI -1.03 to -0.42) of a year, and brain-predicted age difference was lower by -0.87 (1.51 to 0.23) of a year. Both associations were attenuated by adjustment for covariates and not significant after simultaneous adjustment for all covariates and correction for multiple testing. More positive attitudes to physical change were associated with lower mortality: for an SD higher score the age-adjusted and sex-adjusted HR (95% CI) was 0.66 (0.56 to 0.78). Adjustment for AgeAccelGrim or brain-predicted age difference attenuated this association slightly. It remained significant after adjustment for all covariates.

Conclusion

We found partial evidence that attitudes to ageing are linked with ageing biomarkers but they accounted for only a little of the association between attitudes and mortality.

Childhood intelligence attenuates the association between biological ageing and health outcomes in later life

The identification of biomarkers that discriminate individual ageing trajectories is a principal target of ageing research. Some of the most promising predictors of biological ageing have been developed using DNA methylation. One recent candidate, which tracks age-related phenotypes in addition to chronological age, is 'DNAm PhenoAge'. Here, we performed a phenome-wide association analysis of this biomarker in a cohort of older adults to assess its relationship with a comprehensive set of both historical, and contemporaneously-measured, phenotypes. Higher than expected DNAm PhenoAge compared with chronological age, known as epigenetic age acceleration, was found to associate with a number of blood, cognitive, physical fitness and lifestyle variables, and with mortality. Notably, DNAm PhenoAge, assessed at age 70, was associated with cognitive ability at age 11, and with educational attainment. Adjusting for age 11 cognitive ability attenuated the majority of the cross-sectional later-life associations between DNAm PhenoAge and health outcomes. These results highlight the importance of early life factors on healthy older ageing.

DNA methylation changes in infants between 6 and 52 weeks

Infants undergo extensive developments during their first year of life. Although the biological mechanisms involved are not yet fully understood, changes in the DNA methylation in mammals are believed to play a key role. This study was designed to investigate changes in infant DNA methylation that occurs between 6 and 52 weeks. A total of 214 infant saliva samples from 6 or 52 weeks were assessed using principal component analyses and t-distributed stochastic neighbor-embedding algorithms. Between the two time points, there were clear differences in DNA methylation. To further investigate these findings, paired two-sided student’s t-tests were performed. Differently methylated regions were defined as at least two consecutive probes that showed significant differences, with a q-value < 0.01 and a mean difference > 0.2. After correcting for false discovery rates, changes in the DNA methylation levels were found in 42 genes. Of these, 36 genes showed increased and six decreased DNA methylation. The overall DNA methylation changes indicated decreased gene expression. This was surprising because infants undergo such profound developments during their first year of life. The results were evaluated by taking into consideration the extensive development that occurs during pregnancy. During the first year of life, infants have an overall three-fold increase in weight, while the fetus develops from a single cell into a viable infant in 9 months, with an 875-million-fold increase in weight. It is possible that the findings represent a biological slowing mechanism in response to extensive fetal development. In conclusion, our study provides evidence of DNA methylation changes during the first year of life, representing a possible biological slowing mechanism. We encourage future studies of DNA methylation changes in infants to replicate the findings by using a repeated measures model and less stringent criteria to see if the same genes can be found, as well as investigating whether other genes are involved in development during this period.

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.

A meta-analysis of genome-wide association studies of epigenetic age acceleration

'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father's age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.

A meta-analysis of genome-wide association studies of epigenetic age acceleration

'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father's age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.

Epigenetic signatures of smoking associate with cognitive function, brain structure, and mental and physical health outcomes in the Lothian Birth Cohort 1936

Recent advances in genome-wide DNA methylation (DNAm) profiling for smoking behaviour have given rise to a new, molecular biomarker of smoking exposure. It is unclear whether a smoking-associated DNAm (epigenetic) score has predictive value for ageing-related health outcomes which is independent of contributions from self-reported (phenotypic) smoking measures. Blood DNA methylation levels were measured in 895 adults aged 70 years in the Lothian Birth Cohort 1936 (LBC1936) study using the Illumina 450K assay. A DNA methylation score based on 230 CpGs was used as a proxy for smoking exposure. Associations between smoking variables and health outcomes at age 70 were modelled using general linear modelling (ANCOVA) and logistic regression. Additional analyses of smoking with brain MRI measures at age 73 (n = 532) were performed. Smoking-DNAm scores were positively associated with self-reported smoking status (P < 0.001, eta-squared ɳ2 = 0.63) and smoking pack years (r = 0.69, P < 0.001). Higher smoking DNAm scores were associated with variables related to poorer cognitive function, structural brain integrity, physical health, and psychosocial health. Compared with phenotypic smoking, the methylation marker provided stronger associations with all of the cognitive function scores, especially visuospatial ability (P < 0.001, partial eta-squared ɳp2 = 0.022) and processing speed (P < 0.001, ɳp2 = 0.030); inflammatory markers (all P < 0.001, ranges from ɳp2 = 0.021 to 0.030); dietary patterns (healthy diet (P < 0.001, ɳp2 = 0.052) and traditional diet (P < 0.001, ɳp2 = 0.032); stroke (P = 0.006, OR 1.48, 95% CI 1.12, 1.96); mortality (P < 0.001, OR 1.59, 95% CI 1.42, 1.79), and at age 73; with MRI volumetric measures (all P < 0.001, ranges from ɳp2 = 0.030 to 0.052). Additionally, education was the most important life-course predictor of lifetime smoking tested. Our results suggest that a smoking-associated methylation biomarker typically explains a greater proportion of the variance in some smoking-related morbidities in older adults, than phenotypic measures of smoking exposure, with some of the accounted-for variance being independent of phenotypic smoking status.

Ageing and epigenetics: linking neurodevelopmental and neurodegenerative disorders

Epigenetics has classically been recognized as crucial to neurodevelopment and neurodevelopmental disorders. More recently its role in ageing processes, including neurodegenerative disorders has emerged, although far more research is required in this area, particularly in humans. Epigenetic processes that regulate gene expression comprise strata of DNA modification (e.g. methylation), histone modification (e.g. histone acetylation), and mRNA translation (e.g. by microRNAs). These strata are progressively more fluid whereby changes in DNA methylation may persist for many years whilst expression of microRNAs fluctuates over short periods. There is considerable 'cross-talk' between these epigenetic strata. Epigenetic mechanisms are open to parental imprinting and thus they are candidates for linking diseases, not just over the life course, but also intergenerationally. There is a genetic overlap between intellectual disability and cognitive ageing. Epigenetic pathways may strengthen the links between neurodevelopmental disorders and neurodegenerative diseases. WHAT THIS PAPER ADDS: DNA methylation has relevance to both neurological development and neurodegeneration. Links between epigenetics, genotype and phenotype are emerging.