The epigenome—the chemical modifications and chromatin-related packaging of the genome—enables the same genetic template to be activated or repressed in different cellular settings. This ...multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological ‘clocks’ constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.
Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans ...and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.
Objective
Analysis of the epigenome—the chemical modifications and packaging of the genome that can influence or indicate its activity—enables molecular insight into cell type‐specific machinery. It ...can, therefore, reveal the pathophysiological mechanisms at work in disease. Detected changes can also represent physiological responses to adverse environmental exposures, thus enabling the epigenetic mark of DNA methylation to act as an epidemiological biomarker, even in surrogate tissue. This makes epigenomic analysis an attractive prospect to further understand the pathobiology and epidemiological aspects of obesity. Furthermore, integrating epigenomic data with known obesity‐associated common genetic variation can aid in deciphering their molecular mechanisms.
Methods and Conclusions
This review primarily examines epidemiological or population‐based studies of epigenetic modifications in relation to adiposity traits, as opposed to animal or cell models. It discusses recent work exploring the epigenome with respect to human obesity, which to date has predominately consisted of array‐based studies of DNA methylation in peripheral blood. It is of note that highly replicated BMI DNA methylation associations are not causal, but strongly driven by coassociations for more precisely measured intertwined outcomes and factors, such as hyperlipidemia, hyperglycemia, and inflammation. Finally, the potential for the future exploration of the epigenome in obesity and related disorders is considered.
Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the ...epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease.
We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes.
Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy.
This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy.
Integrating epigenetic data with genome-wide association study (GWAS) results can reveal disease mechanisms. The genome sequence itself also shapes the epigenome, with CpG density and transcription ...factor binding sites (TFBSs) strongly encoding the DNA methylome. Therefore, genetic polymorphism impacts on the observed epigenome. Furthermore, large genetic variants alter epigenetic signal dosage. Here, we identify DNA methylation variability between GWAS-SNP risk and non-risk haplotypes. In three subsets comprising 3128 MeDIP-seq peripheral-blood DNA methylomes, we find 7173 consistent and functionally enriched Differentially Methylated Regions. 36.8% can be attributed to common non-SNP genetic variants. CpG-SNPs, as well as facilitative TFBS-motifs, are also enriched. Highlighting their functional potential, CpG-SNPs strongly associate with allele-specific DNase-I hypersensitivity sites. Our results demonstrate strong DNA methylation allelic differences driven by obligatory or facilitative genetic effects, with potential direct or regional disease-related repercussions. These allelic variations require disentangling from pure tissue-specific modifications, may influence array studies, and imply underestimated population variability in current reference epigenomes.
Monozygotic (MZ) twin pair discordance for childhood-onset Type 1 Diabetes (T1D) is ∼50%, implicating roles for genetic and non-genetic factors in the aetiology of this complex autoimmune disease. ...Although significant progress has been made in elucidating the genetics of T1D in recent years, the non-genetic component has remained poorly defined. We hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology and, thus, performed an epigenome-wide association study (EWAS) for this disease. We generated genome-wide DNA methylation profiles of purified CD14+ monocytes (an immune effector cell type relevant to T1D pathogenesis) from 15 T1D-discordant MZ twin pairs. This identified 132 different CpG sites at which the direction of the intra-MZ pair DNA methylation difference significantly correlated with the diabetic state, i.e. T1D-associated methylation variable positions (T1D-MVPs). We confirmed these T1D-MVPs display statistically significant intra-MZ pair DNA methylation differences in the expected direction in an independent set of T1D-discordant MZ pairs (P = 0.035). Then, to establish the temporal origins of the T1D-MVPs, we generated two further genome-wide datasets and established that, when compared with controls, T1D-MVPs are enriched in singletons both before (P = 0.001) and at (P = 0.015) disease diagnosis, and also in singletons positive for diabetes-associated autoantibodies but disease-free even after 12 years follow-up (P = 0.0023). Combined, these results suggest that T1D-MVPs arise very early in the etiological process that leads to overt T1D. Our EWAS of T1D represents an important contribution toward understanding the etiological role of epigenetic variation in type 1 diabetes, and it is also the first systematic analysis of the temporal origins of disease-associated epigenetic variation for any human complex disease.
The epigenome has been shown to deteriorate with age, potentially impacting on ageing-related disease. tRNA, while arising from only ˜46 kb (<0.002% genome), is the second most abundant cellular ...transcript. tRNAs also control metabolic processes known to affect ageing, through core translational and additional regulatory roles. Here, we interrogate the DNA methylation state of the genomic loci of human tRNA. We identify a genomic enrichment for age-related DNA hypermethylation at tRNA loci. Analysis in 4,350 MeDIP-seq peripheral-blood DNA methylomes (16-82 years), identifies 44 and 21 hypermethylating specific tRNAs at study-and genome-wide significance, respectively, contrasting with none hypomethylating. Validation and replication (450k array and independent targeted Bisuphite-sequencing) supported the hypermethylation of this functional unit. Tissue-specificity is a significant driver, although the strongest consistent signals, also independent of major cell-type change, occur in tRNA-iMet-CAT-1-4 and tRNA-Ser-AGA-2-6. This study presents a comprehensive evaluation of the genomic DNA methylation state of human tRNA genes and reveals a discreet hypermethylation with advancing age.
DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Here we perform genome-wide methylated DNA immunoprecipitation sequencing ...(MeDIP-seq) in whole-blood-derived DNA from 27 monozygotic twin pairs and follow up results with replication and integrated omics analyses. We identify predominately hypermethylated T2D-related differentially methylated regions (DMRs) and replicate the top signals in 42 unrelated T2D cases and 221 controls. The strongest signal is in the promoter of the MALT1 gene, involved in insulin and glycaemic pathways, and related to taurocholate levels in blood. Integrating the DNA methylome findings with T2D GWAS meta-analysis results reveals a strong enrichment for DMRs in T2D-susceptibility loci. We also detect signals specific to T2D-discordant twins in the GPR61 and PRKCB genes. These replicated T2D associations reflect both likely causal and consequential pathways of the disease. The analysis indicates how an integrated genomics and epigenomics approach, utilizing an MZ twin design, can provide pathogenic insights as well as potential drug targets and biomarkers for T2D and other complex traits.
Polymorphisms in FKBP51 are associated with stress-related psychiatric disorders and influence the severity of pain symptoms experienced after trauma. We report that FKBP51 (FK506 binding protein 51) ...is crucial for the full development and maintenance of long-term pain states. Indeed, FKBP51 knockout mice, as well as mice in which silencing of FKBP51 is restricted to the spinal cord, showed reduced hypersensitivity in several persistent pain models in rodents. FKBP51 deletion did not compromise the detection of acute painful stimuli, a critical protective mechanism. Moreover, the intrathecal administration of the specific FKBP51 inhibitor SAFit2 reduced the severity of an established pain state, confirming the crucial role of spinal FKBP51 in nociceptive processing. Finally, glucocorticoid signaling, which is known to modulate persistent pain states in rodents, was impaired in FKBP51 knockout mice. This finding suggested that FKBP51 regulates chronic pain by modulation of glucocorticoid signaling. Thus, FKBP51 is a central mediator of chronic pain, likely in humans as well as rodents, and is a new pharmacologically tractable target for the treatment of long-term pain states.
Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined ...genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10(-4), permutation p = 1.0×10(-3)). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10(-7)). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.
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