Genetic variants that associate with DNA methylation at CpG sites (methylation quantitative trait loci, meQTLs) offer a potential biological mechanism of action for disease associated SNPs. We investigated whether meQTLs exist in abdominal subcutaneous adipose tissue (SAT) and if CpG methylation associates with metabolic syndrome (MetSyn) phenotypes. We profiled 27,718 genomic regions in abdominal SAT samples of 38 unrelated individuals using differential methylation hybridization (DMH) together with genotypes at 5,227,243 SNPs and expression of 17,209 mRNA transcripts. Validation and replication of significant meQTLs was pursued in an independent cohort of 181 female twins. We find that, at 5% false discovery rate, methylation levels of 149 DMH regions associate with at least one SNP in a ±500 kilobase cis-region in our primary study. We sought to validate 19 of these in the replication study and find that five of these significantly associate with the corresponding meQTL SNPs from the primary study. We find that none of the 149 meQTL top SNPs is a significant expression quantitative trait locus in our expression data, but we observed association between expression levels of two mRNA transcripts and cis-methylation status. Our results indicate that DNA CpG methylation in abdominal SAT is partly under genetic control. This study provides a starting point for future investigations of DNA methylation in adipose tissue.

Recent studies have identified both heritable DNA methylation effects and differential methylation in disease-discordant identical twins. Larger sample sizes, replication, genetic-epigenetic analyses and longitudinal assays are now needed to establish the role of epigenetic variants in disease.

Using whole blood from 15 twin pairs discordant for breast cancer and high-resolution (450K) DNA methylation analysis, we identified 403 differentially methylated CpG sites including known and novel potential breast cancer genes. Confirming the results in an independent validation cohort of 21 twin pairs determined the docking protein DOK7 as a candidate for blood-based cancer diagnosis. DNA hypermethylation of the promoter region was also seen in primary breast cancer tissues and cancer cell lines. Hypermethylation of DOK7 occurs years before tumor diagnosis, suggesting a role as a powerful epigenetic blood-based biomarker as well as providing insights into breast cancer pathogenesis.

Summary

In the presence of epistasis multilocus association tests of human complex traits can provide powerful methods to detect susceptibility variants. We undertook multilocus analyses in 1924 type 2 diabetes cases and 2938 controls from the Wellcome Trust Case Control Consortium (WTCCC). We performed a two-dimensional genome-wide association (GWA) scan using joint two-locus tests of association including main and epistatic effects in 70,236 markers tagging common variants. We found two-locus association at 79 SNP-pairs at a Bonferroni-corrected P-value = 0.05 (uncorrected P-value = 2.14 × 10−11). The 79 pair-wise results always contained rs11196205 in TCF7L2 paired with 79 variants including confirmed variants in FTO, TSPAN8, and CDKAL1, which are associated in the absence of epistasis. However, the majority (82%) of the 79 variants did not have compelling single-locus association signals (P-value = 5 × 10−4). Analyses conditional on the single-locus effects at TCF7L2 established that the joint two-locus results could be attributed to single-locus association at TCF7L2 alone. Interaction analyses among the peak 80 regions and among 23 previously established diabetes candidate genes identified five SNP-pairs with case-control and case-only epistatic signals. Our results demonstrate the feasibility of systematic scans in GWA data, but confirm that single-locus association can underlie and obscure multilocus findings.

Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype–phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes.

Author Summary

Epigenetic patterns vary during healthy ageing and development. Age-related DNA methylation changes have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To understand the biological mechanisms involved in potential longevity and rate of healthy ageing, we performed genome-wide association of epigenetic and genetic variation with both chronological age and age-related phenotypes. We identified hundreds of DNA methylation variants significantly associated with age and replicated these in an independent sample of young adult twins. Only a small proportion of these variants were also associated with age-related phenotypes. Therefore, the majority of age-related epigenetic changes do not contribute to rate of healthy ageing at later stages in life. Our results suggest that age-related changes in methylation occur throughout an individual's lifespan and that a proportion of these may be initiated from an early age. Intriguingly, a fraction of the age differentially methylated regions also associated with genetic variants in our sample, suggesting that DNA methylation may be a candidate mechanism of mediating not only environmental but also genetic effects on age-related phenotypes.

Dehydroepiandrosterone sulphate (DHEAS) is the most abundant circulating steroid secreted by adrenal glands—yet its function is unknown. Its serum concentration declines significantly with increasing age, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. We conducted a meta-analysis of genome-wide association data with 14,846 individuals and identified eight independent common SNPs associated with serum DHEAS concentrations. Genes at or near the identified loci include ZKSCAN5 (rs11761528; p = 3.15×10−36), SULT2A1 (rs2637125; p = 2.61×10−19), ARPC1A (rs740160; p = 1.56×10−16), TRIM4 (rs17277546; p = 4.50×10−11), BMF (rs7181230; p = 5.44×10−11), HHEX (rs2497306; p = 4.64×10−9), BCL2L11 (rs6738028; p = 1.72×10−8), and CYP2C9 (rs2185570; p = 2.29×10−8). These genes are associated with type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins. Several SNPs were associated with changes in gene expression levels, and the related genes are connected to biological pathways linking DHEAS with ageing. This study provides much needed insight into the function of DHEAS.

Author Summary

Dehydroepiandrosterone sulphate (DHEAS), mainly secreted by the adrenal gland, is the most abundant circulating steroid in humans. It shows a significant physiological decline after the age of 25 and diminishes about 95% by the age of 85 years, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. Twin- and family-based studies have shown that there is a substantial genetic effect with heritability estimate of 60%, but no specific genes regulating serum DHEAS concentration have been identified to date. Here we take advantage of recent technical and methodological advances to examine the effects of common genetic variants on serum DHEAS concentrations. By examining 14,846 Caucasian individuals, we show that eight common genetic variants are associated with serum DHEAS concentrations. Genes at or near these genetic variants include BCL2L11, ARPC1A, ZKSCAN5, TRIM4, HHEX, CYP2C9, BMF, and SULT2A1. These genes have various associations with steroid hormone metabolism—co-morbidities of ageing including type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins—suggesting a wider functional role for DHEAS than previously thought.

The regulation of gene expression plays a pivotal role in complex phenotypes, and epigenetic mechanisms such as DNA methylation are essential to this process. The availability of next-generation sequencing technologies allows us to study epigenetic variation at an unprecedented level of resolution. Even so, our understanding of the underlying sources of epigenetic variability remains limited. Twin studies have played an essential role in estimating phenotypic heritability, and these now offer an opportunity to study epigenetic variation as a dynamic quantitative trait. High monozygotic twin discordance rates for common diseases suggest that unexplained environmental or epigenetic factors could be involved. Recent genome-wide epigenetic studies in disease-discordant monozygotic twins emphasize the power of this design to successfully identify epigenetic changes associated with complex traits. We describe how large-scale epigenetic studies of twins can improve our understanding of how genetic, environmental and stochastic factors impact upon epigenetics, and how such studies can provide a comprehensive understanding of how epigenetic variation affects complex traits.

The modification of DNA by methylation is an important epigenetic mechanism that affects the spatial and temporal regulation of gene expression. Methylation patterns have been described in many contexts within and across a range of species. However, the extent to which changes in methylation might underlie inter-species differences in gene regulation, in particular between humans and other primates, has not yet been studied. To this end, we studied DNA methylation patterns in livers, hearts, and kidneys from multiple humans and chimpanzees, using tissue samples for which genome-wide gene expression data were also available. Using the multi-species gene expression and methylation data for 7,723 genes, we were able to study the role of promoter DNA methylation in the evolution of gene regulation across tissues and species. We found that inter-tissue methylation patterns are often conserved between humans and chimpanzees. However, we also found a large number of gene expression differences between species that might be explained, at least in part, by corresponding differences in methylation levels. In particular, we estimate that, in the tissues we studied, inter-species differences in promoter methylation might underlie as much as 12%–18% of differences in gene expression levels between humans and chimpanzees.

Author Summary

It has long been hypothesized that changes in gene regulation have played an important role in primate evolution. However, despite the wealth of comparative gene expression data, there are still only few studies that focus on the mechanisms underlying inter-primate differences in gene regulation. In particular, we know relatively little about the degree to which changes in epigenetic profiles might explain differences in gene expression levels between primates. To this end, we studied DNA methylation and gene expression levels in livers, hearts, and kidneys from multiple humans and chimpanzees. Using these comparative data, we were able to study the evolution of gene regulation in the context of conservation of or changes in DNA methylation profiles across tissues and species. We found that inter-tissue methylation patterns are often conserved between humans and chimpanzees. In addition, we also found a large number of gene expression differences between species, which might be explained, at least in part, by corresponding differences in methylation levels. We estimate that, in the tissues we studied, inter-species differences in methylation levels might underlie as much as 12%–18% of differences in gene expression levels between humans and chimpanzees.

While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL), skin, and fat. The samples (156 LCL, 160 skin, 166 fat) were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes). In addition, we apply factor analysis (FA) to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes). The unique study design (Matched Co-Twin Analysis—MCTA) permits immediate replication of eQTLs using co-twins (93%–98%) and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%–20%) have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.

Author Summary

Regulation of gene expression is a fundamental cellular process determining a large proportion of the phenotypic variance. Previous studies have identified genetic loci influencing gene expression levels (eQTLs), but the complexity of their tissue-specific properties has not yet been well-characterized. In this study, we perform cis-eQTL analysis in a unique matched co-twin design for three human tissues derived simultaneously from the same set of individuals. The study design allows validation of the substantial discoveries we make in each tissue. We explore in depth the tissue-dependent features of regulatory variants and estimate the proportions of shared and specific effects. We use continuous measures of eQTL sharing to circumvent the statistical power limitations of comparing direct overlap of eQTLs in multiple tissues. In this framework, we demonstrate that 30% of eQTLs are shared among tissues, while 29% are exclusively tissue-specific. Furthermore, we show that the fold change in expression between eQTL genotypic classes differs between tissues. Even among shared eQTLs, we report a substantial proportion (10%–20%) of significant tissue differences in magnitude of these effects. The complexities we highlight here are essential for understanding the impact of regulatory variants on complex traits.

Background

DNA methylation is an essential epigenetic mechanism involved in gene regulation and disease, but little is known about the mechanisms underlying inter-individual variation in methylation profiles. Here we measured methylation levels at 22,290 CpG dinucleotides in lymphoblastoid cell lines from 77 HapMap Yoruba individuals, for which genome-wide gene expression and genotype data were also available.

Results

Association analyses of methylation levels with more than three million common single nucleotide polymorphisms (SNPs) identified 180 CpG-sites in 173 genes that were associated with nearby SNPs (putatively in cis, usually within 5 kb) at a false discovery rate of 10%. The most intriguing trans signal was obtained for SNP rs10876043 in the disco-interacting protein 2 homolog B gene (DIP2B, previously postulated to play a role in DNA methylation), that had a genome-wide significant association with the first principal component of patterns of methylation; however, we found only modest signal of trans-acting associations overall. As expected, we found significant negative correlations between promoter methylation and gene expression levels measured by RNA-sequencing across genes. Finally, there was a significant overlap of SNPs that were associated with both methylation and gene expression levels.

Conclusions

Our results demonstrate a strong genetic component to inter-individual variation in DNA methylation profiles. Furthermore, there was an enrichment of SNPs that affect both methylation and gene expression, providing evidence for shared mechanisms in a fraction of genes.

Background

High-resolution magnetic resonance imaging (cine-MRI) is well suited for determining global cardiac function longitudinally in genetically or surgically manipulated mice, but in practice it is seldom used to its full potential. In this study, male and female guanidinoacetate N-methyltransferase (GAMT) knockout, and wild type littermate mice were subjected to a longitudinal cine-MRI study at four time points over the course of one year. GAMT is an essential enzyme in creatine biosynthesis, such that GAMT deficient mice are entirely creatine-free. Since creatine plays an important role in the buffering and transfer of high-energy phosphate bonds in the heart, it was hypothesized that lack of creatine would be detrimental for resting cardiac performance during ageing.

Methods

Measurements of cardiac structure (left ventricular mass and volumes) and function (ejection fraction, stroke volume, cardiac output) were obtained using high-resolution cine-MRI at 9.4 T under isoflurane anaesthesia.

Results

There were no physiologically significant differences in cardiac function between wild type and GAMT knockout mice at any time point for male or female groups, or for both combined (for example ejection fraction: 6 weeks (KO vs. WT): 70 ± 6% vs. 65 ± 7%; 4 months: 70 ± 6% vs. 62 ± 8%; 8 months: 62 ± 11% vs. 62 ± 6%; 12 months: 61 ± 7% vs. 59 ± 11%, respectively).

Conclusion

These findings suggest the presence of comprehensive adaptations in the knockout mice that can compensate for a lack of creatine. Furthermore, this study clearly demonstrates the power of cine-MRI for accurate non-invasive, serial cardiac measurements. Cardiac growth curves could easily be defined for each group, in the same set of animals for all time points, providing improved statistical power, and substantially reducing the number of mice required to conduct such a study. This technique should be eminently useful for following changes of cardiac structure and function during ageing.

We performed a genome-wide search for pairs of susceptibility loci that jointly contribute to rheumatoid arthritis in families recruited by the North American Rheumatoid Arthritis Consortium. A complete two-dimensional (2D) non-parametric linkage scan was carried out using 380 autosomal microsatellite markers in 511 families. At each 2D peak we obtained the most likely underlying genetic model explaining the two-locus effects, defining epistasis as a departure from an additive or a multiplicative two-locus penetrance function. The highest peak in the surface identified an epistatic interaction between loci 6p21 and 16p12 (two-locus lod score = 18.02, epistasis P < 0.012). Significant and suggestive two-locus effects were also obtained for region 6p21 in combination with loci 18q21, 8p23, 1q41, and 6p22, while the highest 2D peaks excluding region 6p21 were observed at locus pairs 8p23-18q21 and 1p21-18q21. The 2D peaks were further examined using combined microsatellite and single-nucleotide polymorphism (SNP) marker genotypes in 744 families. The two-locus evidence for linkage increased for region pairs 6p21-18q12, 6p21-16p12, 6p21-8p23, 1q41-6p21, and 6p21-6p22, but decreased for pairs of regions that did not include locus 6p21. In conclusion, we obtained evidence for multi-locus interactions in rheumatoid arthritis that are mediated by the major susceptibility locus at 6p21.

High-resolution genetic maps are required for mapping complex traits and for the study of recombination. We report the highest density genetic map yet created for any organism, except humans. Using more than 10,000 single nucleotide polymorphisms evenly spaced across the mouse genome, we have constructed genetic maps for both outbred and inbred mice, and separately for males and females. Recombination rates are highly correlated in outbred and inbred mice, but show relatively low correlation between males and females. Differences between male and female recombination maps and the sequence features associated with recombination are strikingly similar to those observed in humans. Genetic maps are available from http://gscan.well.ox.ac.uk/#genetic_map and as supporting information to this publication.

A high-density SNP map based on outbred and inbred mice with male and female separation suggests a high degree of homology between mouse and human recombination.