Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus

Tissue-specific alterations of methyl group metabolism with DNA hypermethylation in the Zucker (type 2) diabetic fatty rat

BACKGROUND

Altered methyl group and homocysteine metabolism were tissue-specific, persistent, and preceded hepatic DNA hypomethylation in type 1 diabetic rats. Similar metabolic perturbations have been shown in the Zucker (type 2) diabetic fatty (ZDF) rat in the pre-diabetic and early diabetic stages, but tissue specificity and potential impact on epigenetic marks are unknown, particularly during pathogenesis.

METHODS

ZDF (fa/fa) and lean (+/?) control rats were killed at 12 and 21 weeks of age, representing early and advanced diabetic conditions. Blood and tissues were analysed with respect to methyl group and homocysteine metabolism, including DNA methylation.

RESULTS

At 12 weeks, hepatic glycine N-methyltransferase (GNMT), methionine synthase, and cystathionine β-synthase (CBS) activity and/or abundance were increased in ZDF rats. At 21 weeks, GNMT activity was increased in liver and kidney; however, only hepatic CBS protein abundance (12 weeks) and betaine-homocysteine S-methyltransferase mRNA expression (21 weeks) were significantly elevated (78 and 100%, respectively). Hepatic phosphatidylethanolamine N-methyltransferase expression was also elevated in the ZDF rat. Homocysteine concentrations were decreased in plasma and kidney, but not in liver, at 12 and 21 weeks. In contrast to hepatic DNA hypomethylation in the type 1 diabetic rat, genomic DNA was hypermethylated at 12 and 21 weeks in the liver of ZDF rats, concomitant with an increase in DNA methyltransferase 1 expression at 21 weeks.

CONCLUSIONS

The pathogenesis of type 2 diabetes in the ZDF rat was associated with tissue and disease stage-specific aberrations of methyl group and homocysteine metabolism, with persistent hepatic global DNA hypermethylation.

DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patients

In addition to genetic predisposition, environmental and lifestyle factors contribute to the pathogenesis of type 2 diabetes (T2D). Epigenetic changes may provide the link for translating environmental exposures into pathological mechanisms. In this study, we performed the first comprehensive DNA methylation profiling in pancreatic islets from T2D and non-diabetic donors. We uncovered 276 CpG loci affiliated to promoters of 254 genes displaying significant differential DNA methylation in diabetic islets. These methylation changes were not present in blood cells from T2D individuals nor were they experimentally induced in non-diabetic islets by exposure to high glucose. For a subgroup of the differentially methylated genes, concordant transcriptional changes were present. Functional annotation of the aberrantly methylated genes and RNAi experiments highlighted pathways implicated in β-cell survival and function; some are implicated in cellular dysfunction while others facilitate adaptation to stressors. Together, our findings offer new insights into the intricate mechanisms of T2D pathogenesis, underscore the important involvement of epigenetic dysregulation in diabetic islets and may advance our understanding of T2D aetiology.

Genome-wide methylation analysis

The disruption and alteration of genomic methylation patterns is a hallmark of cancer and other disease states. Understanding and characterizing genome-wide methylation will have a profound effect on our understanding of tumorigenesis and provide novel avenues for therapy. This chapter serves to describe techniques that examine genome-wide methylation patterns including luminometric methylation assay, restriction landmark genome scanning, and the cytosine extension assay, which utilize methylation-sensitive restriction enzymes. Additional techniques such as nucleotide separation assays (nearest neighbor analysis and high-performance capillary electrophoresis) and the infinium methylation assay are discussed. These techniques allow for the determination of changes in global methylation levels, as well as regional changes in methylation throughout the genome.

Batch effect correction for genome-wide methylation data with Illumina Infinium platform

Background

Genome-wide methylation profiling has led to more comprehensive insights into gene regulation mechanisms and potential therapeutic targets. Illumina Human Methylation BeadChip is one of the most commonly used genome-wide methylation platforms. Similar to other microarray experiments, methylation data is susceptible to various technical artifacts, particularly batch effects. To date, little attention has been given to issues related to normalization and batch effect correction for this kind of data.

Methods

We evaluated three common normalization approaches and investigated their performance in batch effect removal using three datasets with different degrees of batch effects generated from HumanMethylation27 platform: quantile normalization at average β value (QNβ); two step quantile normalization at probe signals implemented in "lumi" package of R (lumi); and quantile normalization of A and B signal separately (ABnorm). Subsequent Empirical Bayes (EB) batch adjustment was also evaluated.

Results

Each normalization could remove a portion of batch effects and their effectiveness differed depending on the severity of batch effects in a dataset. For the dataset with minor batch effects (Dataset 1), normalization alone appeared adequate and "lumi" showed the best performance. However, all methods left substantial batch effects intact in the datasets with obvious batch effects and further correction was necessary. Without any correction, 50 and 66 percent of CpGs were associated with batch effects in Dataset 2 and 3, respectively. After QNβ, lumi or ABnorm, the number of CpGs associated with batch effects were reduced to 24, 32, and 26 percent for Dataset 2; and 37, 46, and 35 percent for Dataset 3, respectively. Additional EB correction effectively removed such remaining non-biological effects. More importantly, the two-step procedure almost tripled the numbers of CpGs associated with the outcome of interest for the two datasets.

Conclusion

Genome-wide methylation data from Infinium Methylation BeadChip can be susceptible to batch effects with profound impacts on downstream analyses and conclusions. Normalization can reduce part but not all batch effects. EB correction along with normalization is recommended for effective batch effect removal.

Epigenetic mechanism underlying the development of polycystic ovary syndrome (PCOS)-like phenotypes in prenatally androgenized rhesus monkeys

The pathogenesis of polycystic ovary syndrome (PCOS) is poorly understood. PCOS-like phenotypes are produced by prenatal androgenization (PA) of female rhesus monkeys. We hypothesize that perturbation of the epigenome, through altered DNA methylation, is one of the mechanisms whereby PA reprograms monkeys to develop PCOS. Infant and adult visceral adipose tissues (VAT) harvested from 15 PA and 10 control monkeys were studied. Bisulfite treated samples were subjected to genome-wide CpG methylation analysis, designed to simultaneously measure methylation levels at 27,578 CpG sites. Analysis was carried out using Bayesian Classification with Singular Value Decomposition (BCSVD), testing all probes simultaneously in a single test. Stringent criteria were then applied to filter out invalid probes due to sequence dissimilarities between human probes and monkey DNA, and then mapped to the rhesus genome. This yielded differentially methylated loci between PA and control monkeys, 163 in infant VAT, and 325 in adult VAT (BCSVD P<0.05). Among these two sets of genes, we identified several significant pathways, including the antiproliferative role of TOB in T cell signaling and transforming growth factor-β (TGF-β) signaling. Our results suggest PA may modify DNA methylation patterns in both infant and adult VAT. This pilot study suggests that excess fetal androgen exposure in female nonhuman primates may predispose to PCOS via alteration of the epigenome, providing a novel avenue to understand PCOS in humans.

Copy number and SNP arrays in clinical diagnostics

The ability of chromosome microarray analysis (CMA) to detect submicroscopic genetic abnormalities has revolutionized the clinical diagnostic approach to individuals with intellectual disability, neurobehavioral phenotypes, and congenital malformations. The recognition of the underlying copy number variant (CNV) in respective individuals may allow not only for better counseling and anticipatory guidance but also for more specific therapeutic interventions in some cases. The use of CMA technology in prenatal diagnosis is emerging and promises higher sensitivity for several highly penetrant, clinically severe microdeletion and microduplication syndromes. Genetic counseling complements the diagnostic testing with CMA, given the presence of CNVs of uncertain clinical significance, incomplete penetrance, and variable expressivity in some cases. While oligonucleotide arrays with high-density exonic coverage remain the gold standard for the detection of CNVs, single-nucleotide polymorphism (SNP) arrays allow for detection of consanguinity and most cases of uniparental disomy and provide a higher sensitivity to detect low-level mosaic aneuploidies.

Global DNA methylation and risk of subclinical atherosclerosis in young adults: the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study

OBJECTIVE

The association between hepatic global DNA methylation measured using pyrosequencing technology and the risk of subclinical atherosclerosis was examined in the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study. PDAY is a bi-racial investigation of the natural history of atherosclerosis and its risk factors involving 3013 individuals aged 15-34 years who underwent autopsy after dying of unrelated causes in 1987-1994.

METHODS

Raised atherosclerotic lesions were defined as the sum of the percentages of intimal surface area detected in the right coronary artery and left half of the abdominal and thoracic aorta harboring fibrous plaques, complicated lesions, and calcified lesions during a postmortem pathological examination. To conduct the case-control study, 300 cases selected with the highest raised lesion scores were paired with 300 controls without raised lesions after matching for age, race, and gender.

RESULTS

Global DNA methylation was not associated with disease risk in the study population considered as a whole using conditional logistic regression models to analyze matched pairs. Since the estimation of the risk of atherosclerosis associated with inter-individual variation in DNA methylation was similar if unconditional logistic regression was used, subgroup analyses were carried out after adjusting for matching variables. A modest association with methylation levels below the median value was found in white but not in African-American study participants (odds ratio = 1.59, 95% confidence interval = 1.02-2.49, p = 0.04).

CONCLUSIONS

Hepatic global DNA methylation does not appear to be a definitive determinant of atherosclerosis burden in a postmortem sample of young adults.

Identification of type 1 diabetes-associated DNA methylation variable positions that precede disease diagnosis

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.

Type 1 diabetes (T1D) is a complex autoimmune disease affecting >30 million people worldwide. It is caused by a combination of genetic and non-genetic factors, leading to destruction of insulin-secreting cells. Although significant progress has recently been made in elucidating the genetics of T1D, the non-genetic component has remained poorly defined. Epigenetic modifications, such as methylation of DNA, are indispensable for genomic processes such as transcriptional regulation and are frequently perturbed in human disease. We therefore hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology, and we performed a genome-wide DNA methylation analysis of a specific subset of immune cells (monocytes) from monozygotic twins discordant for T1D. This revealed the presence of T1D–specific methylation variable positions (T1D–MVPs) in the T1D–affected co-twins. Since these T1D–MVPs were found in MZ twins, they cannot be due to genetic differences. Additional experiments revealed that some of these T1D–MVPs are found in individuals before T1D diagnosis, suggesting they arise very early in the process that leads to overt T1D and are not simply due to post-disease associated factors (e.g. medication or long-term metabolic changes). T1D–MVPs may thus potentially represent a previously unappreciated, and important, component of type 1 diabetes risk.

Genome-wide analysis distinguishes hyperglycemia regulated epigenetic signatures of primary vascular cells

Emerging evidence suggests that poor glycemic control mediates post-translational modifications to the H3 histone tail. We are only beginning to understand the dynamic role of some of the diverse epigenetic changes mediated by hyperglycemia at single loci, yet elevated glucose levels are thought to regulate genome-wide changes, and this still remains poorly understood. In this article we describe genome-wide histone H3K9/K14 hyperacetylation and DNA methylation maps conferred by hyperglycemia in primary human vascular cells. Chromatin immunoprecipitation (ChIP) as well as CpG methylation (CpG) assays, followed by massive parallel sequencing (ChIP-seq and CpG-seq) identified unique hyperacetylation and CpG methylation signatures with proximal and distal patterns of regionalization associative with gene expression. Ingenuity knowledge-based pathway and gene ontology analyses indicate that hyperglycemia significantly affects human vascular chromatin with the transcriptional up-regulation of genes involved in metabolic and cardiovascular disease. We have generated the first installment of a reference collection of hyperglycemia-induced chromatin modifications using robust and reproducible platforms that allow parallel sequencing-by-synthesis of immunopurified content. We uncover that hyperglycemia-mediated induction of genes and pathways associated with endothelial dysfunction occur through modulation of acetylated H3K9/K14 inversely correlated with methyl-CpG content.

Decreased urine albumin:creatinine ratios in infants of diabetic mothers: does exposure to diabetic pregnancies alter fetal renal development?

Offspring of diabetic mothers experience an increased risk for type 2 diabetes but it is not known whether diabetic pregnancies also confer a higher inter-generational risk for diabetic complications. Because microalbuminuria is a sensitive indicator of glomerular damage, we compared the urine albumin:creatinine ratios (ACRs) between 65 infants of diabetic mothers (InfDM+) and 59 infants of non-diabetic mothers (InfDM−), and repeated the comparisons in 21 InfDM+ and 19 InfDM− when children were 5–19 months old. ACRs were higher among neonates compared with normal reference values for adults, but declined with increasing age. The only independent predictor of higher ACRs in a logistic regression model (⩾13 mg/mmol v. <13 mg/mmol) was the presence of delivery complications (odds ratio 2.95; P = 0.015). Neither high nor low birth weight was associated with higher neonatal ACRs. The most unique finding of the study was that InfDM+ had significantly lower ACRs than InfDM− [mean = 12.9 (median = 6.0) v. mean = 16.6 (median = 11.5), respectively at P = 0.05] even after adjusting for other variables using logistic regression (odds ratio 0.25; P = 0.001). In contrast, by 5–19 months, there was a trend toward higher ACRs among InfDM+ compared with InfDM− [mean = 6.3 mg/mmol (median = 1.9) v. mean = 3.0 mg/mmol (median = 2.5), respectively at P = 0.25]. Lower ACRs in InfDM+ may be due to developmental changes in fetal kidneys induced by hyperinsulinemia. Although the implications of this observation are unclear, it is possible that exposure to a diabetic intrauterine environment might influence the later risk for renal disease.

Epigenome-wide association studies for common human diseases

Despite the success of genome-wide association studies (GWASs) in identifying loci associated with common diseases, a substantial proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation. Such epigenome-wide association studies (EWASs) present novel opportunities but also create new challenges that are not encountered in GWASs. We discuss EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies. We also discuss how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.

Epigenetics: deciphering its role in diabetes and its chronic complications

1. Increasing evidence suggests that epigenetic factors might regulate the complex interplay between genes and the environment, and affect human diseases, such as diabetes and its complications. 2. Clinical trials have underscored the long lasting beneficial effects of strict glycaemic control for reducing the progression of diabetic complications. They have also shown that diabetic complications, such as diabetic nephropathy, a chronic kidney disorder, can continue even after blood glucose normalization, suggesting a metabolic memory of the prior glycaemic state. 3. Dysregulation of epigenetic post-transcriptional modifications of histones in chromatin, including histone lysine methylation, has been implicated in aberrant gene regulation associated with the pathology of diabetes and its complications. Genome-wide studies have shown cell-type specific changes in histone methylation patterns under diabetic conditions. In addition, studies in vascular cells have shown long lasting changes in epigenetic modifications at key inflammatory gene promoters after prior exposure to diabetic conditions, suggesting a possible mechanism for metabolic memory. 4. Recent studies have shown roles for histone methylation, DNA methylation, as well as microRNA in diabetic nephropathy. Whether these epigenetic factors play a role in metabolic memory of diabetic kidney disease is less well understood. 5. The incidence of diabetes is growing rapidly, as also the cost of treating the resulting complications. A better understanding of metabolic memory and the potential involvement of epigenetic mechanisms in this phenomenon could enable the development of new therapeutic targets for the treatment and/or prevention of sustained diabetic complications.

Remodeling is at the heart of chromatin: the heartaches of chromatin

Chromatin modifications are integral elements of chromosome structure and its function and the vasculature depends on tissue-specific genome regulation for its development. A general concept for the de-regulation of chromatin modifications in cardiac and vascular disease is also emerging. The recognition that metabolic memory contributes to disease persistence highlights the benefit of early and aggressive treatment. As for the importance of memory, we do know that good metabolic control delays the onset of long-term diabetic complications. There are striking parallels between the timing of disease and the development of complications. Landmark multicenter clinical trials on diabetes patients have popularized the concept that glucose is also a demonstrable determinant for the development of complications, indicating the prolonged benefit of intensive therapy and the lasting damage of conventional therapy. Each cell type experiences thousands of modifications to the epigenome in response to environmental changes it is exposed to. Therefore, history is neither lost nor forgotten and previous experiences and exposure may form future memories. There is now a strong resurgence in research trying to understand gene-environment interactions and to determine what commits specific vascular cell types to specific memories. Recent insights show that cardiac gene expression is distinguished by specific chromatin remodeling events and histone modifications that are associated with heart disease.

Epigenetic mechanisms

The incidence of diabetes and related complications like nephropathy is growing rapidly and has become a major health care issue. Changes in the environment and nutritional habits have been implicated as major players. Furthermore, it is becoming increasingly clear that epigenetic factors may modulate the connections between genes and the environment. While diabetes in itself is treatable to a large extent, it is still associated with significantly increased risk for complications including chronic kidney and cardiovascular diseases. Current treatments have added preventative approaches so as to avoid future diabetic complications. Unfortunately, diabetic patients are often plagued with the continued development of various complications even after achieving glucose control. This has been suggested to be attributable to a mysterious phenomenon termed 'metabolic memory' of the prior glycemic state. Recent studies have suggested that epigenetic changes to chromatin can affect gene expression in response to various stimuli, and changes in key biochemical pathways and epigenetic histone and DNA methylation patterns in chromatin have been observed in a diabetic milieu. These accumulating data suggest that metabolic or hyperglycemic memory may be due to epigenetic changes in specific target tissues altering gene expression without changing the genetic code itself. While the genetics of diabetes has long been the focus of scientific research, much less is known about the role of epigenetics and the related molecular pathways that might affect the development of diabetes and the associated complications. Further studies of epigenetic mechanisms are therefore timely and could provide valuable new insights into the pathology of diabetic complications and also uncover much needed new therapeutic targets.

Epigenetic mechanisms in diabetic vascular complications

There has been a rapid increase in the incidence of diabetes as well the associated vascular complications. Both genetic and environmental factors have been implicated in these pathologies. Increasing evidence suggests that epigenetic factors play a key role in the complex interplay between genes and the environment. Actions of major pathological mediators of diabetes and its complications such as hyperglycaemia, oxidant stress, and inflammatory factors can lead to dysregulated epigenetic mechanisms that affect chromatin structure and gene expression. Furthermore, persistence of this altered state of the epigenome may be the underlying mechanism contributing to a 'metabolic memory' that results in chronic inflammation and vascular dysfunction in diabetes even after achieving glycaemic control. Further examination of epigenetic mechanisms by also taking advantage of recently developed next-generation sequencing technologies can provide novel insights into the pathology of diabetes and its complications and lead to the discovery of much needed new drug targets for these diseases. In this review, we highlight the role of epigenetics in diabetes and its vascular complications, and recent technological advances that have significantly accelerated the field.

Maternal genome-wide DNA methylation patterns and congenital heart defects

The majority of congenital heart defects (CHDs) are thought to result from the interaction between multiple genetic, epigenetic, environmental, and lifestyle factors. Epigenetic mechanisms are attractive targets in the study of complex diseases because they may be altered by environmental factors and dietary interventions. We conducted a population based, case-control study of genome-wide maternal DNA methylation to determine if alterations in gene-specific methylation were associated with CHDs. Using the Illumina Infinium Human Methylation27 BeadChip, we assessed maternal gene-specific methylation in over 27,000 CpG sites from DNA isolated from peripheral blood lymphocytes. Our study sample included 180 mothers with non-syndromic CHD-affected pregnancies (cases) and 187 mothers with unaffected pregnancies (controls). Using a multi-factorial statistical model, we observed differential methylation between cases and controls at multiple CpG sites, although no CpG site reached the most stringent level of genome-wide statistical significance. The majority of differentially methylated CpG sites were hypermethylated in cases and located within CpG islands. Gene Set Enrichment Analysis (GSEA) revealed that the genes of interest were enriched in multiple biological processes involved in fetal development. Associations with canonical pathways previously shown to be involved in fetal organogenesis were also observed. We present preliminary evidence that alterations in maternal DNA methylation may be associated with CHDs. Our results suggest that further studies involving maternal epigenetic patterns and CHDs are warranted. Multiple candidate processes and pathways for future study have been identified.

Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis

Background

High-throughput profiling of DNA methylation status of CpG islands is crucial to understand the epigenetic regulation of genes. The microarray-based Infinium methylation assay by Illumina is one platform for low-cost high-throughput methylation profiling. Both Beta-value and M-value statistics have been used as metrics to measure methylation levels. However, there are no detailed studies of their relations and their strengths and limitations.

Results

We demonstrate that the relationship between the Beta-value and M-value methods is a Logit transformation, and show that the Beta-value method has severe heteroscedasticity for highly methylated or unmethylated CpG sites. In order to evaluate the performance of the Beta-value and M-value methods for identifying differentially methylated CpG sites, we designed a methylation titration experiment. The evaluation results show that the M-value method provides much better performance in terms of Detection Rate (DR) and True Positive Rate (TPR) for both highly methylated and unmethylated CpG sites. Imposing a minimum threshold of difference can improve the performance of the M-value method but not the Beta-value method. We also provide guidance for how to select the threshold of methylation differences.

Conclusions

The Beta-value has a more intuitive biological interpretation, but the M-value is more statistically valid for the differential analysis of methylation levels. Therefore, we recommend using the M-value method for conducting differential methylation analysis and including the Beta-value statistics when reporting the results to investigators.

The epigenomic interface between genome and environment in common complex diseases

The epigenome plays the pivotal role as interface between genome and environment. True genome-wide assessments of epigenetic marks, such as DNA methylation (methylomes) or chromatin modifications (chromatinomes), are now possible, either through high-throughput arrays or increasingly by second-generation DNA sequencing methods. The ability to collect these data at this level of resolution enables us to begin to be able to propose detailed questions, and interrogate this information, with regards to changes that occur due to development, lineage and tissue-specificity, and significantly those caused by environmental influence, such as ageing, stress, diet, hormones or toxins. Common complex traits are under variable levels of genetic influence and additionally epigenetic effect. The detection of pathological epigenetic alterations will reveal additional insights into their aetiology and how possible environmental modulation of this mechanism may occur. Due to the reversibility of these marks, the potential for sequence-specific targeted therapeutics exists. This review surveys recent epigenomic advances and their current and prospective application to the study of common diseases.