Ribosomal DNA copy number variation associates with hematological profiles and renal function in the UK Biobank.

The phenotypic impact of genetic variation of repetitive features in the human genome is currently understudied. One such feature is the multi-copy 47S ribosomal DNA (rDNA) that codes for rRNA components of the ribosome. Here, we present an analysis of rDNA copy number (CN) variation in the UK Biobank (UKB). From the first release of UKB whole-genome sequencing (WGS) data, a discovery analysis in White British individuals reveals that rDNA CN associates with altered counts of specific blood cell subtypes, such as neutrophils, and with the estimated glomerular filtration rate, a marker of kidney function. Similar trends are observed in other ancestries. A range of analyses argue against reverse causality or common confounder effects, and all core results replicate in the second UKB WGS release. Our work demonstrates that rDNA CN is a genetic influence on trait variance in humans.

Genetic variation at mouse and human ribosomal DNA influences associated epigenetic states.

BACKGROUND: Ribosomal DNA (rDNA) displays substantial inter-individual genetic variation in human and mouse. A systematic analysis of how this variation impacts epigenetic states and expression of the rDNA has thus far not been performed. RESULTS: Using a combination of long- and short-read sequencing, we establish that 45S rDNA units in the C57BL/6J mouse strain exist as distinct genetic haplotypes that influence the epigenetic state and transcriptional output of any given unit. DNA methylation dynamics at these haplotypes are dichotomous and life-stage specific: at one haplotype, the DNA methylation state is sensitive to the in utero environment, but refractory to post-weaning influences, whereas other haplotypes entropically gain DNA methylation during aging only. On the other hand, individual rDNA units in human show limited evidence of genetic haplotypes, and hence little discernible correlation between genetic and epigenetic states. However, in both species, adjacent units show similar epigenetic profiles, and the overall epigenetic state at rDNA is strongly positively correlated with the total rDNA copy number. Analysis of different mouse inbred strains reveals that in some strains, such as 129S1/SvImJ, the rDNA copy number is only approximately 150 copies per diploid genome and DNA methylation levels are < 5%. CONCLUSIONS: Our work demonstrates that rDNA-associated genetic variation has a considerable influence on rDNA epigenetic state and consequently rRNA expression outcomes. In the future, it will be important to consider the impact of inter-individual rDNA (epi)genetic variation on mammalian phenotypes and diseases.

The DNA methylome of human sperm is distinct from blood with little evidence for tissue-consistent obesity associations.

Epidemiological research suggests that paternal obesity may increase the risk of fathering small for gestational age offspring. Studies in non-human mammals indicate that such associations could be mediated by DNA methylation changes in spermatozoa that influence offspring development in utero. Human obesity is associated with differential DNA methylation in peripheral blood. It is unclear, however, whether this differential DNA methylation is reflected in spermatozoa. We profiled genome-wide DNA methylation using the Illumina MethylationEPIC array in a cross-sectional study of matched human blood and sperm from lean (discovery n = 47; replication n = 21) and obese (n = 22) males to analyse tissue covariation of DNA methylation, and identify obesity-associated methylomic signatures. We found that DNA methylation signatures of human blood and spermatozoa are highly discordant, and methylation levels are correlated at only a minority of CpG sites (~1%). At the majority of these sites, DNA methylation appears to be influenced by genetic variation. Obesity-associated DNA methylation in blood was not generally reflected in spermatozoa, and obesity was not associated with altered covariation patterns or accelerated epigenetic ageing in the two tissues. However, one cross-tissue obesity-specific hypermethylated site (cg19357369; chr4:2429884; P = 8.95 × 10-8; 2% DNA methylation difference) was identified, warranting replication and further investigation. When compared to a wide range of human somatic tissue samples (n = 5,917), spermatozoa displayed differential DNA methylation across pathways enriched in transcriptional regulation. Overall, human sperm displays a unique DNA methylation profile that is highly discordant to, and practically uncorrelated with, that of matched peripheral blood. We observed that obesity was only nominally associated with differential DNA methylation in sperm, and therefore suggest that spermatozoal DNA methylation is an unlikely mediator of intergenerational effects of metabolic traits.

DNA methylation clocks as a predictor for ageing and age estimation in naked mole-rats, Heterocephalus glaber.

The naked mole-rat, Heterocephalus glaber (NMR), the longest-lived rodent, is of significance and interest in the study of biomarkers for ageing. Recent breakthroughs in this field have revealed 'epigenetic clocks' that are based on the temporal accumulation of DNA methylation at specific genomic sites. Here, we validate the hypothesis of an epigenetic clock in NMRs based on changes in methylation of targeted CpG sites. We initially analysed 51 CpGs in NMR livers spanning an age range of 39-1,144 weeks and found 23 to be significantly associated with age (p<0.05). We then built a predictor of age using these sites. To test the accuracy of this model, we analysed an additional set of liver samples, and were successfully able to predict their age with a root mean squared error of 166 weeks. We also profiled skin samples with the same age range, finding a striking correlation between their predicted age versus their actual age (R=0.93), but which was lower when compared to the liver, suggesting that skin ages slower than the liver in NMRs. Our model will enable the prediction of age in wild-caught and captive NMRs of unknown age, and will be invaluable for further mechanistic studies of mammalian ageing.

DNA methylation aging clocks: challenges and recommendations.

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

Early life diet conditions the molecular response to post-weaning protein restriction in the mouse.

BACKGROUND: Environmental influences fluctuate throughout the life course of an organism. It is therefore important to understand how the timing of exposure impacts molecular responses. Herein, we examine the responses of two key molecular markers of dietary stress, namely variant-specific methylation at ribosomal DNA (rDNA) and small RNA distribution, including tRNA fragments, in a mouse model of protein restriction (PR) with exposure at pre- and/or post-weaning. RESULTS: We first confirm that pre-weaning PR exposure modulates the methylation state of rDNA in a genotype-dependent manner, whereas post-weaning PR exposure has no such effect. Conversely, post-weaning PR induces a shift in small RNA distribution, but there is no effect in the pre-weaning PR model. Intriguingly, mice exposed to PR throughout their lives show neither of these two dietary stress markers, similar to controls. CONCLUSIONS: The results show that the timing of the insult affects the nature of the molecular response but also, critically, that 'matching' diet exposure either side of weaning eliminates the stress response at the level of rDNA methylation and small RNA in sperm.

Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci.

Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

Ageing-associated DNA methylation dynamics are a molecular readout of lifespan variation among mammalian species.

BACKGROUND: Mammalian species exhibit a wide range of lifespans. To date, a robust and dynamic molecular readout of these lifespan differences has not yet been identified. Recent studies have established the existence of ageing-associated differentially methylated positions (aDMPs) in human and mouse. These are CpG sites at which DNA methylation dynamics show significant correlations with age. We hypothesise that aDMPs are pan-mammalian and are a dynamic molecular readout of lifespan variation among different mammalian species. RESULTS: A large-scale integrated analysis of aDMPs in six different mammals reveals a strong negative relationship between rate of change of methylation levels at aDMPs and lifespan. This relationship also holds when comparing two different dog breeds with known differences in lifespans. In an ageing cohort of aneuploid mice carrying a complete copy of human chromosome 21, aDMPs accumulate far more rapidly than is seen in human tissues, revealing that DNA methylation at aDMP sites is largely shaped by the nuclear trans-environment and represents a robust molecular readout of the ageing cellular milieu. CONCLUSIONS: Overall, we define the first dynamic molecular readout of lifespan differences among mammalian species and propose that aDMPs will be an invaluable molecular tool for future evolutionary and mechanistic studies aimed at understanding the biological factors that determine lifespan in mammals.

eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data.

Epigenome-wide association studies (EWAS) provide an alternative approach for studying human disease through consideration of non-genetic variants such as altered DNA methylation. To advance the complex interpretation of EWAS, we developed eFORGE (http://eforge.cs.ucl.ac.uk/), a new standalone and web-based tool for the analysis and interpretation of EWAS data. eFORGE determines the cell type-specific regulatory component of a set of EWAS-identified differentially methylated positions. This is achieved by detecting enrichment of overlap with DNase I hypersensitive sites across 454 samples (tissues, primary cell types, and cell lines) from the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of eFORGE to 20 publicly available EWAS datasets identified disease-relevant cell types for several common diseases, a stem cell-like signature in cancer, and demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. Our approach bridges the gap between large-scale epigenomics data and EWAS-derived target selection to yield insight into disease etiology.

Increased DNA methylation variability in type 1 diabetes across three immune effector cell types.

The incidence of type 1 diabetes (T1D) has substantially increased over the past decade, suggesting a role for non-genetic factors such as epigenetic mechanisms in disease development. Here we present an epigenome-wide association study across 406,365 CpGs in 52 monozygotic twin pairs discordant for T1D in three immune effector cell types. We observe a substantial enrichment of differentially variable CpG positions (DVPs) in T1D twins when compared with their healthy co-twins and when compared with healthy, unrelated individuals. These T1D-associated DVPs are found to be temporally stable and enriched at gene regulatory elements. Integration with cell type-specific gene regulatory circuits highlight pathways involved in immune cell metabolism and the cell cycle, including mTOR signalling. Evidence from cord blood of newborns who progress to overt T1D suggests that the DVPs likely emerge after birth. Our findings, based on 772 methylomes, implicate epigenetic changes that could contribute to disease pathogenesis in T1D.

Correlation of an epigenetic mitotic clock with cancer risk.

BACKGROUND: Variation in cancer risk among somatic tissues has been attributed to variations in the underlying rate of stem cell division. For a given tissue type, variable cancer risk between individuals is thought to be influenced by extrinsic factors which modulate this rate of stem cell division. To date, no molecular mitotic clock has been developed to approximate the number of stem cell divisions in a tissue of an individual and which is correlated with cancer risk. RESULTS: Here, we integrate mathematical modeling with prior biological knowledge to construct a DNA methylation-based age-correlative model which approximates a mitotic clock in both normal and cancer tissue. By focusing on promoter CpG sites that localize to Polycomb group target genes that are unmethylated in 11 different fetal tissue types, we show that increases in DNA methylation at these sites defines a tick rate which correlates with the estimated rate of stem cell division in normal tissues. Using matched DNA methylation and RNA-seq data, we further show that it correlates with an expression-based mitotic index in cancer tissue. We demonstrate that this mitotic-like clock is universally accelerated in cancer, including pre-cancerous lesions, and that it is also accelerated in normal epithelial cells exposed to a major carcinogen. CONCLUSIONS: Unlike other epigenetic and mutational clocks or the telomere clock, the epigenetic clock proposed here provides a concrete example of a mitotic-like clock which is universally accelerated in cancer and precancerous lesions.

Early-life nutrition modulates the epigenetic state of specific rDNA genetic variants in mice.

A suboptimal early-life environment, due to poor nutrition or stress during pregnancy, can influence lifelong phenotypes in the progeny. Epigenetic factors are thought to be key mediators of these effects. We show that protein restriction in mice from conception until weaning induces a linear correlation between growth restriction and DNA methylation at ribosomal DNA (rDNA). This epigenetic response remains into adulthood and is restricted to rDNA copies associated with a specific genetic variant within the promoter. Related effects are also found in models of maternal high-fat or obesogenic diets. Our work identifies environmentally induced epigenetic dynamics that are dependent on underlying genetic variation and establishes rDNA as a genomic target of nutritional insults.

A donor-specific epigenetic classifier for acute graft-versus-host disease severity in hematopoietic stem cell transplantation.

BACKGROUND: Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative treatment for many hematological conditions. Acute graft-versus-host disease (aGVHD) is a prevalent immune-mediated complication following HSCT. Current diagnostic biomarkers that correlate with aGVHD severity, progression, and therapy response in graft recipients are insufficient. Here, we investigated whether epigenetic marks measured in peripheral blood of healthy graft donors stratify aGVHD severity in human leukocyte antigen (HLA)-matched sibling recipients prior to T cell-depleted HSCT. METHODS: We measured DNA methylation levels genome-wide at single-nucleotide resolution in peripheral blood of 85 HSCT donors, matched to recipients with various transplant outcomes, with Illumina Infinium HumanMethylation450 BeadChips. RESULTS: Using genome-wide DNA methylation profiling, we showed that epigenetic signatures underlying aGVHD severity in recipients correspond to immune pathways relevant to aGVHD etiology. We discovered 31 DNA methylation marks in donors that associated with aGVHD severity status in recipients, and demonstrated strong predictive performance of these markers in internal cross-validation experiments (AUC = 0.98, 95% CI = 0.96-0.99). We replicated the top-ranked CpG classifier using an alternative, clinical DNA methylation assay (P = 0.039). In an independent cohort of 32 HSCT donors, we demonstrated the utility of the epigenetic classifier in the context of a T cell-replete conditioning regimen (P = 0.050). CONCLUSIONS: Our findings suggest that epigenetic typing of HSCT donors in a clinical setting may be used in conjunction with HLA genotyping to inform both donor selection and transplantation strategy, with the ultimate aim of improving patient outcome.

The senescent methylome and its relationship with cancer, ageing and germline genetic variation in humans.

BACKGROUND: Cellular senescence is a stable arrest of proliferation and is considered a key component of processes associated with carcinogenesis and other ageing-related phenotypes. Here, we perform methylome analysis of actively dividing and deeply senescent normal human epithelial cells. RESULTS: We identify senescence-associated differentially methylated positions (senDMPs) from multiple experiments using cells from one donor. We find that human senDMP epigenetic signatures are positively and significantly correlated with both cancer and ageing-associated methylation dynamics. We also identify germline genetic variants, including those associated with the p16INK4A locus, which are associated with the presence of in vivo senDMP signatures. Importantly, we also demonstrate that a single senDMP signature can be effectively reversed in a newly-developed protocol of transient senescence reversal. CONCLUSIONS: The senDMP signature has significant potential for understanding some of the key (epi)genetic etiological factors that may lead to cancer and age-related diseases in humans.

Sexually dimorphic gene expression emerges with embryonic genome activation and is dynamic throughout development.

BACKGROUND: As sex determines mammalian development, understanding the nature and developmental dynamics of the sexually dimorphic transcriptome is important. To explore this, we generated 76 genome-wide RNA-seq profiles from mouse eight-cell embryos, late gestation and adult livers, together with 4 ground-state pluripotent embryonic (ES) cell lines from which we generated both RNA-seq and multiple ChIP-seq profiles. We complemented this with previously published data to yield 5 snap-shots of pre-implantation development, late-gestation placenta and somatic tissue and multiple adult tissues for integrative analysis. RESULTS: We define a high-confidence sex-dimorphic signature of 69 genes in eight-cell embryos. Sex-chromosome-linked components of this signature are largely conserved throughout pre-implantation development and in ES cells, whilst the autosomal component is more dynamic. Sex-biased gene expression is reflected by enrichment for activating and repressive histone modifications. The eight-cell signature is largely non-overlapping with that defined from fetal liver, neither was it correlated with adult liver or other tissues analysed. The number of sex-dimorphic genes increases throughout development. We identified many more dimorphic genes in adult compared to fetal liver. However, approximately two thirds of the dimorphic genes identified in fetal liver were also dimorphic in adult liver. Sex-biased expression differences unique to adult liver were enriched for growth hormone-responsiveness. Sexually dimorphic gene expression in pre-implantation development is driven by sex-chromosome based transcription, whilst later development is characterised by sex dimorphic autosomal transcription. CONCLUSION: This systematic study identifies three distinct phases of sex dimorphism throughout mouse development, and has significant implications for understanding the developmental origins of sex-specific phenotypes and disease in mammals.

Maternal gestational diabetes is associated with genome-wide DNA methylation variation in placenta and cord blood of exposed offspring.

Exposure of a developing foetus to maternal gestational diabetes (GDM) has been shown to programme future risk of diabetes and obesity. Epigenetic variation in foetal tissue may have a mechanistic role in metabolic disease programming through interaction of the pregnancy environment with gene function. We aimed to identify genome-wide DNA methylation variation in cord blood and placenta from offspring born to mothers with and without GDM. Pregnant women of South Asian origin were studied and foetal tissues sampled at term delivery. The Illumina HumanMethylation450 BeadChip was used to assay genome-wide DNA methylation in placenta and cord blood from 27 GDM exposed and 21 unexposed offspring. We identified 1485 cord blood and 1708 placenta methylation variable positions (MVPs) achieving genome-wide significance (adjusted P-value <0.05) with methylation differences of >5%. MVPs were disproportionately located within first exons. A bioinformatic co-methylation algorithm was used to detect consistent directionality of methylation in 1000 bp window around each MVP was observed at 74% of placenta and 59% of cord blood MVPs. KEGG pathway analysis showed enrichment of pathways involved in endocytosis, MAPK signalling and extracellular triggers to intracellular metabolic processes. Replication studies should integrate genomics and transcriptomics with longitudinal sampling to elucidate stability, determine causality for translation into biomarker and prevention studies.

The human blood DNA methylome displays a highly distinctive profile compared with other somatic tissues.

In mammals, DNA methylation profiles vary substantially between tissues. Recent genome-scale studies report that blood displays a highly distinctive methylomic profile from other somatic tissues. In this study, we sought to understand why blood DNA methylation state is so different to the one found in other tissues. We found that whole blood contains approximately twice as many tissue-specific differentially methylated positions (tDMPs) than any other somatic tissue examined. Furthermore, a large subset of blood tDMPs showed much lower levels of methylation than tDMPs for other tissues. Surprisingly, these regions of low methylation in blood show no difference regarding genomic location, genomic content, evolutionary rates, or histone marks when compared to other tDMPs. Our results reveal why blood displays a distinctive methylation profile relative to other somatic tissues. In the future, it will be important to study how these blood specific tDMPs are mechanistically involved in blood-specific functions.

Novel DNA methylation profiles associated with key gene regulation and transcription pathways in blood and placenta of growth-restricted neonates.

Fetal growth is determined by the feto-placental genome interacting with the maternal in utero environment. Failure of this interplay leads to poor placental development and fetal growth restriction (FGR), which is associated with future metabolic disease. We investigated whether whole genome methylation differences existed in umbilical cord blood and placenta, between gestational-matched, FGR, and appropriately grown (AGA) neonates. Using the Infinium HumanMethylation450 BeadChip®, we found that DNA from umbilical cord blood of FGR born at term (n = 19) had 839 differentially methylated positions (DMPs) that reached genome-wide significance compared with AGA (n = 18). Using gestational age as a continuous variable, we identified 76,249 DMPs in cord blood (adj. P < 0.05) of which 121 DMPs were common to the 839 DMPs and were still evident when comparing 12 FGR with 12 AGA [39.9 ± 1.2 vs. 40.0 ± 1.0 weeks (mean ± SD), respectively]. A total of 53 DMPs had a ß methylation difference >10% and 25 genes were co-methylated more than twice within 1000 base pairs. Gene Ontology (GO) analysis of DMPs supported their involvement in gene regulation and transcription pathways related to organ development and metabolic function. A similar profile of DMPs was found across different cell types in the cord blood. At term, no DMPs between FGR and AGA placentae reached genome-wide significance, validated with an external dataset. GO analysis of 284 pre-term, placental DMPs associated with autophagy, oxidative stress and hormonal responses. Growth restricted neonates have distinct DNA methylation profiles in pre-term placenta and in cord blood at birth, which may predispose to future adult disease.

Correcting for cell-type composition bias in epigenome-wide association studies.

Recent epigenome-wide association studies have indicated a potential role for epigenetic variation in the etiology of complex human diseases. However, one major challenge is to distinguish true epigenetic variation from changes caused by differences in cellular composition between the disease and non-disease state, a problem that is particularly relevant when analyzing whole blood. For studies with large numbers of samples, it can be expensive and very time consuming to perform cell sorting, and it is often not clear which is the correct cell type to profile. Two recently published papers have attempted to address this confounding issue using bioinformatics.