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Previous studies with nonhuman species have shown that animals exposed to early adversity show differential DNA methylation relative to comparison animals. The current study examined differential methylation among 14 children raised since birth in institutional care and 14 comparison children raised by their biological parents. Blood samples were taken from children in middle childhood. Analysis of whole-genome methylation patterns was performed using the Infinium HumanMethylation27 BeadChip assay (Illumina), which contains 27,578 CpG sites, covering approximately 14,000 gene promoters. Group differences were registered, which were characterized primarily by greater methylation in the institutionalized group relative to the comparison group, with most of these differences in genes involved in the control of immune response and cellular signaling systems, including a number of crucial players important for neural communication and brain development and functioning. The findings suggest that patterns of differential methylation seen in nonhuman species with altered maternal care are also characteristic of children who experience early maternal separation.

Background

Juvenile Idiopathic Arthritis (JIA) is a complex autoimmune rheumatic disease of largely unknown cause. Evidence is growing that epigenetic variation, particularly DNA methylation, is associated with autoimmune disease. However, nothing is currently known about the potential role of aberrant DNA methylation in JIA. As a first step to addressing this knowledge gap, we have profiled DNA methylation in purified CD4+ T cells from JIA subjects and controls. Genomic DNA was isolated from peripheral blood CD4+ T cells from 14 oligoarticular and polyarticular JIA cases with active disease, and healthy age- and sex-matched controls. Genome-scale methylation analysis was carried out using the Illumina Infinium HumanMethylation27 BeadChip. Methylation data at >25,000 CpGs was compared in a case-control study design.

Results

Methylation levels were significantly different (FDR adjusted p<0.1) at 145 loci. Removal of four samples exposed to methotrexate had a striking impact on the outcome of the analysis, reducing the number of differentially methylated loci to 11. The methotrexate-naive analysis identified reduced methylation at the gene encoding the pro-inflammatory cytokine IL32, which was subsequently replicated using a second analysis platform and a second set of case-control pairs.

Conclusions

Our data suggests that differential T cell DNA methylation may be a feature of JIA, and that reduced methylation at IL32 is associated with this disease. Further work in larger prospective and longitudinal sample collections is required to confirm these findings, assess whether the identified differences are causal or consequential of disease, and further investigate the epigenetic modifying properties of therapeutic regimens.

All tissues of the organism are affected by aging. This process is associated with epigenetic modifications such as methylation changes at specific cytosine residues in the DNA (CpG sites). Here, we have identified an Epigenetic-Aging-Signature which is applicable for many tissues to predict donor age. DNA-methylation profiles of various cell types were retrieved from public data depositories - all using the HumanMethylation27 BeadChip platform which represents 27,578 CpG sites. Five datasets from dermis, epidermis, cervical smear, T-cells and monocytes were used for Pavlidis Template Matching to identify 19 CpG sites that are continuously hypermethylated upon aging (R > 0.6; p-value <10−13). Four of these CpG sites (associated with the genes NPTX2, TRIM58, GRIA2 and KCNQ1DN) and an additional hypomethylated CpG site (BIRC4BP) were implemented in a model to predict donor age. This Epigenetic-Aging-Signature was tested on a validation group of eight independent datasets corresponding to several cell types from different tissues. Overall, the five CpG sites revealed age-associated DNA-methylation changes in all tissues. The average absolute difference between predicted and real chronological age was about 11 years. This method can be used to predict donor age in various cell preparations - for example in forensic analysis.

Background

There is an increasing demand for accurate biomarkers for early non-invasive colorectal cancer detection. We employed a genome-scale marker discovery method to identify and verify candidate DNA methylation biomarkers for blood-based detection of colorectal cancer.

Methodology/Principal Findings

We used DNA methylation data from 711 colorectal tumors, 53 matched adjacent-normal colonic tissue samples, 286 healthy blood samples and 4,201 tumor samples of 15 different cancer types. DNA methylation data were generated by the Illumina Infinium HumanMethylation27 and the HumanMethylation450 platforms, which determine the methylation status of 27,578 and 482,421 CpG sites respectively. We first performed a multistep marker selection to identify candidate markers with high methylation across all colorectal tumors while harboring low methylation in healthy samples and other cancer types. We then used pre-therapeutic plasma and serum samples from 107 colorectal cancer patients and 98 controls without colorectal cancer, confirmed by colonoscopy, to verify candidate markers. We selected two markers for further evaluation: methylated THBD (THBD-M) and methylated C9orf50 (C9orf50-M). When tested on clinical plasma and serum samples these markers outperformed carcinoembryonic antigen (CEA) serum measurement and resulted in a high sensitive and specific test performance for early colorectal cancer detection.

Conclusions/Significance

Our systematic marker discovery and verification study for blood-based DNA methylation markers resulted in two novel colorectal cancer biomarkers, THBD-M and C9orf50-M. THBD-M in particular showed promising performance in clinical samples, justifying its further optimization and clinical testing.

The role of DNA methylation of CpG islands in parathyroid tumorigenesis has not been analyzed in an unbiased, systematic fashion. DNA was isolated from normal and pathologic parathyroid tissues, bisulphite modified and analyzed using the Infinium HumanMethylation27 BeadChip. Distinct hierarchical clustering of genes with altered DNA methylation profiles in normal and pathologic parathyroid tissue was evident. Comparing normal parathyroid tissue with parathyroid adenomas, 367 genes were significantly altered, while 175 genes significantly differed when comparing parathyroid carcinomas and normal parathyroid tissues. A comparison between parathyroid adenomas and parathyroid carcinomas identified 263 genes with significantly distinct methylation levels. Results were confirmed for certain genes in a validation cohort of 40 parathyroid adenomas by methylation-specific PCR. Genes of known or putative importance in the development of parathyroid tumors showed significant and frequent hypermethylation. DNA hypermethylation of CDKN2B, CDKN2A, WT1, SFRP1, SFRP2 and SFRP4 was associated with reduced gene expression in both benign and malignant parathyroid tumors. Treatment with 5-aza-2′-deoxycytidine of primary cell cultures restores expression of hypermethylated genes in benign and malignant parathyroid tumors. In conclusion, the unbiased, genome-wide study of the parathyroid tumor DNA methylome identified a number of genes with altered DNA methylation patterns of putative importance to benign and malignant parathyroid tumorigenesis.

DNA methylation of CpGs located in two types of repetitive elements—LINE1 (L1) and Alu—is used to assess “global” changes in DNA methylation in studies of human disease and environmental exposure. L1 and Alu contribute close to 30% of all base pairs in the human genome and transposition of repetitive elements is repressed through DNA methylation. Few studies have investigated whether repetitive element DNA methylation is associated with DNA methylation at other genomic regions, or the biological and technical factors that influence potential associations. Here, we assess L1 and Alu DNA methylation by Pyrosequencing of consensus sequences and using subsets of probes included in the Illumina Infinium HumanMethylation27 BeadChip array. We show that evolutionary age and assay method affect the assessment of repetitive element DNA methylation. Additionally, we compare Pyrosequencing results for repetitive elements to average DNA methylation of CpG islands, as assessed by array probes classified into strong, weak and non-islands. We demonstrate that each of these dispersed sequences exhibits different patterns of tissue-specific DNA methylation. Correlation of DNA methylation suggests an association between L1 and weak CpG island DNA methylation in some of the tissues examined. We caution, however, that L1, Alu and CpG island DNA methylation are distinct measures of dispersed DNA methylation and one should not be used in lieu of another. Analysis of DNA methylation data is complex and assays may be influenced by environment and pathology in different or complementary ways.

Summary: The Illumina Infinium HumanMethylation450 BeadChip is a newly designed high-density microarray for quantifying the methylation level of over 450 000 CpG sites within human genome. Illumina Methylation Analyzer (IMA) is a computational package designed to automate the pipeline for exploratory analysis and summarization of site-level and region-level methylation changes in epigenetic studies utilizing the 450K DNA methylation microarray. The pipeline loads the data from Illumina platform and provides user-customized functions commonly required to perform exploratory methylation analysis for individual sites as well as annotated regions.

Availability: IMA is implemented in the R language and is freely available from http://www.rforge.net/IMA.

Contact: song.liu@roswellpark.org

African Americans have increased susceptibility to non-diabetic (non-DM) forms of end-stage renal disease (ESRD) and extensive evidence supports a genetic contribution. A genome-wide association study (GWAS) using pooled DNA was performed in 1,000 African Americans to detect associated genes. DNA from 500 non-DM ESRD cases and 500 non-nephropathy controls was quantified using gel electrophoresis and spectrophotometric analysis and pools of 50 case and 50 control DNA samples were created. DNA pools were genotyped in duplicate on the Illumina HumanHap550-Duo BeadChip. Normalization methods were developed and applied to array intensity values to reduce inter-array variance. Allele frequencies were calculated from normalized channel intensities and compared between case and control pools. Three SNPs had p values of <1.0E–6: rs4462445 (ch 13), rs4821469 (ch 22) and rs8077346 (ch 17). After normalization, top scoring SNPs (n = 65) were genotyped individually in 464 of the original cases and 478 of the controls, with replication in 336 non-DM ESRD cases and 363 non-nephropathy controls. Sixteen SNPs were associated with non-DM ESRD (p < 7.7E–4, Bonferroni corrected). Twelve of these SNPs are in or near the MYH9 gene. The four non-MYH9 SNPs that were associated with non-DM ESRD in the pooled samples were not associated in the replication set. Five SNPs that were modestly associated in the pooled samples were more strongly associated in the replication and/or combined samples. This is the first GWAS for non-DM ESRD in African Americans using pooled DNA. We demonstrate strong association between non-DM ESRD in African Americans with MYH9, and have identified additional candidate loci.

Background: Epigenetic modifications, such as DNA methylation, due to in utero exposures may play a critical role in early programming for childhood and adult illness. Maternal smoking is a major risk factor for multiple adverse health outcomes in children, but the underlying mechanisms are unclear.

Objective: We investigated epigenome-wide methylation in cord blood of newborns in relation to maternal smoking during pregnancy.

Methods: We examined maternal plasma cotinine (an objective biomarker of smoking) measured during pregnancy in relation to DNA methylation at 473,844 CpG sites (CpGs) in 1,062 newborn cord blood samples from the Norwegian Mother and Child Cohort Study (MoBa) using the Infinium HumanMethylation450 BeadChip (450K).

Results: We found differential DNA methylation at epigenome-wide statistical significance (p-value < 1.06 × 10–7) for 26 CpGs mapped to 10 genes. We replicated findings for CpGs in AHRR, CYP1A1, and GFI1 at strict Bonferroni-corrected statistical significance in a U.S. birth cohort. AHRR and CYP1A1 play a key role in the aryl hydrocarbon receptor signaling pathway, which mediates the detoxification of the components of tobacco smoke. GFI1 is involved in diverse developmental processes but has not previously been implicated in responses to tobacco smoke.

Conclusions: We identified a set of genes with methylation changes present at birth in children whose mothers smoked during pregnancy. This is the first study of differential methylation across the genome in relation to maternal smoking during pregnancy using the 450K platform. Our findings implicate epigenetic mechanisms in the pathogenesis of the adverse health outcomes associated with this important in utero exposure.

DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.

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.

To better understand the biology of hormone receptor-positive and negative breast cancer and to identify methylated gene markers of disease progression, we performed a genome-wide methylation array analysis on 103 primary invasive breast cancers and 21 normal breast samples using the Illumina Infinium HumanMethylation27 array that queried 27,578 CpG loci. Estrogen and/or progesterone receptor-positive tumors displayed more hypermethylated loci than ER-negative tumors. However, the hypermethylated loci in ER-negative tumors were clustered closer to the transcriptional start site compared to ER-positive tumors. An ER-classifier set of CpG loci was identified, which independently partitioned primary tumors into ER-subtypes. Forty (32 novel, 8 previously known) CpG loci showed differential methylation specific to either ER-positive or ER-negative tumors. Each of the 40 ER-subtype-specific loci was validated in silico using an independent, publicly available methylome dataset from The Cancer Genome Atlas (TCGA). In addition, we identified 100 methylated CpG loci that were significantly associated with disease progression; the majority of these loci were informative particularly in ER-negative breast cancer. Overall, the set was highly enriched in homeobox containing genes. This pilot study demonstrates the robustness of the breast cancer methylome and illustrates its potential to stratify and reveal biological differences between ER-subtypes of breast cancer. Further, it defines candidate ER-specific markers and identifies potential markers predictive of outcome within ER subgroups.

Loci contributing to complex disease have been identified by focusing on genome-wide scans utilising non-synonymous single nucleotide polymorphisms (nsSNPs). We employed Illumina’s HNS12 BeadChip (13,917 high-value SNPs) which was specifically designed to capture nsSNPs and ideally complements more dense genome-wide association studies that fail to consider many of these putatively functional variants. The HNS12 panel also includes 870 tag SNPs covering the major histocompatibility region. All individuals genotyped in this study were Caucasians with (cases) and without (controls) diabetic nephropathy. About 449 individuals with type 2 diabetes (203 cases, 246 controls) were genotyped in the initial study. 1,467 individuals with type 1 diabetes (718 cases, 749 controls) were genotyped in the follow up study. 11,152 SNPs were successfully analysed and ranked for association with diabetic nephropathy based on significance (P) values. The top ranked 32 SNPs were subsequently genotyped using MassARRAY iPLEX™ and TaqMan technologies to investigate association of these polymorphisms with nephropathy in individuals with type 1 diabetes. The top ranked nsSNP, rs1543547 (P = 10−5), is located in RAET1L, a major histocompatibility class I-related gene at 6q25.1. Of particular interest, multiple nsSNPs within the top ranked (0.2%) SNPs are within several plausible candidate genes for nephropathy on 3q21.3 and 6p21.3.

The placenta acts not only as a conduit of nutrient and waste exchange between mother and developing fetus, but also functions as a regulator of the intrauterine environment. Recent work has identified changes in the expression of candidate genes, often through epigenetic alteration, which alter the placenta's function and impact fetal growth. In this study, we used the Illumina Infinium HumanMethylation27 BeadChip array to examine genome-wide DNA methylation patterns in 206 term human placentas. Semi-supervised recursively partitioned mixture modeling was implemented to identify specific patterns of placental DNA methylation that could differentially classify intrauterine growth restriction (IUGR) and small for gestational age (SGA) placentas from appropriate for gestational age (AGA) placentas, and these associations were validated in a masked testing series of samples. Our work demonstrates that patterns of DNA methylation in human placenta are reliably and significantly associated with infant growth and serve as a proof of principle that methylation status in the human term placenta can function as a marker for the intrauterine environment, and could potentially play a critical functional role in fetal development.

Background

We performed a genome-wide scan of 27,578 CpG loci covering 14,475 genes to identify differentially methylated loci (DML) in colorectal carcinoma (CRC).

Methods

We used Illumina's Infinium methylation assay in paired DNA samples extracted from 24 fresh frozen CRC tissues and their corresponding normal colon tissues from 24 consecutive diagnosed patients at a tertiary medical center.

Results

We found a total of 627 DML in CRC covering 513 genes, of which 535 are novel DML covering 465 genes. We also validated the Illumina Infinium methylation data for top-ranking genes by non-bisulfite conversion q-PCR-based methyl profiler assay in a subset of the same samples. We also carried out integration of genome-wide copy number and expression microarray along with methylation profiling to see the functional effect of methylation. Gene Set Enrichment Analysis (GSEA) showed that among the major "gene sets" that are hypermethylated in CRC are the sets: "inhibition of adenylate cyclase activity by G-protein signaling", "Rac guanyl-nucleotide exchange factor activity", "regulation of retinoic acid receptor signaling pathway" and "estrogen receptor activity". Two-level nested cross validation showed that DML-based predictive models may offer reasonable sensitivity (around 89%), specificity (around 95%), positive predictive value (around 95%) and negative predictive value (around 89%), suggesting that these markers may have potential clinical application.

Conclusion

Our genome-wide methylation study in CRC clearly supports most of the previous findings; additionally we found a large number of novel DML in CRC tissue. If confirmed in future studies, these findings may lead to identification of genomic markers for potential clinical application.

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.

Background

In previous studies using candidate gene approaches, low sperm count (oligospermia) has been associated with altered sperm mRNA content and DNA methylation in both imprinted and non-imprinted genes. We performed a genome-wide analysis of sperm DNA methylation and mRNA content to test for associations with sperm function.

Methods and Results

Sperm DNA and mRNA were isolated from 21 men with a range of semen parameters presenting to a tertiary male reproductive health clinic. DNA methylation was measured with the Illumina Infinium array at 27,578 CpG loci. Unsupervised clustering of methylation data differentiated the 21 sperm samples by their motility values. Recursively partitioned mixture modeling (RPMM) of methylation data resulted in four distinct methylation profiles that were significantly associated with sperm motility (P = 0.01). Linear models of microarray analysis (LIMMA) was performed based on motility and identified 9,189 CpG loci with significantly altered methylation (Q<0.05) in the low motility samples. In addition, the majority of these disrupted CpG loci (80%) were hypomethylated. Of the aberrantly methylated CpGs, 194 were associated with imprinted genes and were almost equally distributed into hypermethylated (predominantly paternally expressed) and hypomethylated (predominantly maternally expressed) groups. Sperm mRNA was measured with the Human Gene 1.0 ST Affymetrix GeneChip Array. LIMMA analysis identified 20 candidate transcripts as differentially present in low motility sperm, including HDAC1 (NCBI 3065), SIRT3 (NCBI 23410), and DNMT3A (NCBI 1788). There was a trend among altered expression of these epigenetic regulatory genes and RPMM DNA methylation class.

Conclusions

Using integrative genome-wide approaches we identified CpG methylation profiles and mRNA alterations associated with low sperm motility.

Background

The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer.

Methodology/Principal Findings

We used the Illumina Infinium platform to analyze the DNA methylation status of 27,578 CpG sites in 41 ovarian tumors. We employed a marker selection strategy that emphasized sensitivity by requiring consistency of methylation across tumors, while achieving specificity by excluding markers with methylation in control leukocyte or serum DNA. Our verification strategy involved testing the ability of identified markers to monitor disease burden in serially collected serum samples from ovarian cancer patients who had undergone surgical tumor resection compared to CA-125 levels.

We identified one marker, IFFO1 promoter methylation (IFFO1-M), that is frequently methylated in ovarian tumors and that is rarely detected in the blood of normal controls. When tested in 127 serially collected sera from ovarian cancer patients, IFFO1-M showed post-resection kinetics significantly correlated with serum CA-125 measurements in six out of 16 patients.

Conclusions/Significance

We implemented an effective marker screening and verification strategy, leading to the identification of IFFO1-M as a blood-based candidate marker for sensitive detection of ovarian cancer. Serum levels of IFFO1-M displayed post-resection kinetics consistent with a reflection of disease burden. We anticipate that IFFO1-M and other candidate markers emerging from this marker development pipeline may provide disease detection capabilities that complement existing biomarkers.

DNA methylation is the most widely studied epigenetic mark and is known to be essential to normal development and frequently disrupted in disease. The Illumina HumanMethylation450 BeadChip assays the methylation status of CpGs at 485,577 sites across the genome. Here we present Subset-quantile Within Array Normalization (SWAN), a new method that substantially improves the results from this platform by reducing technical variation within and between arrays. SWAN is available in the minfi Bioconductor package.

Background

Both gastric and colorectal cancers (CRC) are the most frequently occurring malignancies worldwide with the overall survival of these patients remains unsatisfied. Identification of tumor suppressor genes (TSG) silenced by promoter CpG methylation uncovers mechanisms of tumorigenesis and identifies new epigenetic biomarkers for early cancer detection and prognosis assessment. Cystathionine-beta-synthase (CBS) functions in the folate metabolism pathway, which is intricately linked to methylation of genomic DNA. Dysregulation of DNA methylation contributes substantially to cancer development.

Methodology/Principal Findings

To identify potential TSGs silenced by aberrant promoter methylation in CRC, we analyzed tumor and adjacent tissues from CRC cases using the Illumina Human Methylation45 BeadChip. We identified hypermethylation of the CBS gene in CRC samples, compared to adjacent tissues. Methylation and decreased mRNA expression of CBS were detected in most CRC cell lines by methylation-specific PCR and semiquantitative RT-PCR, as well as in gastric cancer. Treatment with 5-aza-2'-deoxycytidine and/or trichostatin A reversed methylation and restored CBS mRNA expression indicating a direct effect. Aberrant methylation was further detected in 31% of primary CRCs (29 of 96) and 55% of gastric tumors (11 of 20). In contrast, methylation was seldom found in normal tissues adjacent to the tumor. CBS methylation was associated with KRAS mutations in primary CRCs (P = 0.04, by χ2-test). However, no association was found between CBS methylation or KRAS mutations with cancer relapse/metastasis in Stage II CRC patients.

Conclusion

A novel finding from this study is that the folate metabolism enzyme CBS mRNA levels are frequently downregulated through CpG methylation of the CBS gene in gastric cancer and CRC, suggesting that CBS functions as a tumor suppressor gene. These findings warrant further study of CBS as an epigenetic biomarker for molecular diagnosis of gastrointestinal cancers.

Systemic lupus erythematosus is a chronic-relapsing autoimmune disease of incompletely understood etiology. Recent evidence strongly supports an epigenetic contribution to the pathogenesis of lupus. To understand the extent and nature of dysregulated DNA methylation in lupus T cells, we performed a genome-wide DNA methylation study in CD4+ T cells in lupus patients compared to normal healthy controls. Cytosine methylation was quantified in 27,578 CG sites located within the promoter regions of 14,495 genes. We identified 236 hypomethylated and 105 hypermethylated CG sites in lupus CD4+ T cells compared to normal controls, consistent with widespread DNA methylation changes in lupus T cells. Of interest, hypomethylated genes in lupus T cells include CD9, which is known to provide potent T-cell co-stimulation signals. Other genes with known involvement in autoimmunity such as MMP9 and PDGFRA were also hypomethylated. The BST2 gene, an interferon-inducible membrane-bound protein that helps restrict the release of retroviral particles was also hypomethylated in lupus patients. Genes involved in folate biosynthesis, which plays a role in DNA methylation, were overrepresented among hypermethylated genes. In addition, the transcription factor RUNX3 was hypermethylated in patients, suggesting an impact on T-cell maturation. Protein-protein interaction maps identified a transcription factor, HNF4a, as a regulatory hub affecting a number of differentially methylated genes. Apoptosis was also an overrepresented ontology in these interaction maps. Further, our data suggest that the methylation status of RAB22A, STX1B2, LGALS3BP, DNASE1L1 and PREX1 correlates with disease activity in lupus patients.

Within 2–3 months of in vitro culture-expansion, mesenchymal stromal cells (MSC) undergo replicative senescence characterized by cell enlargement, loss of differentiation potential and ultimate growth arrest. In this study, we have analyzed DNA methylation changes upon long-term culture of MSC by using the HumanMethylation27 BeadChip microarray assessing 27 578 unique CpG sites. Furthermore, we have compared MSC from young and elderly donors. Overall, methylation patterns were maintained throughout both long-term culture and aging but highly significant differences were observed at specific CpG sites. Many of these differences were observed in homeobox genes and genes involved in cell differentiation. Methylation changes were verified by pyrosequencing after bisulfite conversion and compared to gene expression data. Notably, methylation changes in MSC were overlapping in long-term culture and aging in vivo. This supports the notion that replicative senescence and aging represent developmental processes that are regulated by specific epigenetic modifications.

Background

Hepatocellular carcinoma (HCC) is one of the most common cancers and frequently presents with an advanced disease at diagnosis. There is only limited knowledge of genome-scale methylation changes in HCC.

Methods and Findings

We performed genome-wide methylation profiling in a total of 47 samples including 27 HCC and 20 adjacent normal liver tissues using the Illumina HumanMethylation450 BeadChip. We focused on differential methylation patterns in the promoter CpG islands as well as in various less studied genomic regions such as those surrounding the CpG islands, i.e. shores and shelves. Of the 485,577 loci studied, significant differential methylation (DM) was observed between HCC and adjacent normal tissues at 62,692 loci or 13% (p<1.03e-07). Of them, 61,058 loci (97%) were hypomethylated and most of these loci were located in the intergenic regions (43%) or gene bodies (33%). Our analysis also identified 10,775 differentially methylated (DM) loci (17% out of 62,692 loci) located in or surrounding the gene promoters, 4% of which reside in known Differentially Methylated Regions (DMRs) including reprogramming specific DMRs and cancer specific DMRs, while the rest (10,315) involving 4,106 genes could be potential new HCC DMR loci. Interestingly, the promoter-related DM loci occurred twice as frequently in the shores than in the actual CpG islands. We further characterized 982 DM loci in the promoter CpG islands to evaluate their potential biological function and found that the methylation changes could have effect on the signaling networks of Cellular development, Gene expression and Cell death (p = 1.0e-38), with BMP4, CDKN2A, GSTP1, and NFATC1 on the top of the gene list.

Conclusion

Substantial changes of DNA methylation at a genome-wide level were observed in HCC. Understanding epigenetic changes in HCC will help to elucidate the pathogenesis and may eventually lead to identification of molecular markers for liver cancer diagnosis, treatment and prognosis.

Background

Diabetic nephropathy is the leading cause of end stage renal failure in the western world. There is substantial epidemiological evidence supporting a genetic predisposition to diabetic nephropathy, however the exact molecular mechanisms remain unknown. Transforming growth factor (TGFβ1) is a crucial mediator in the pathogenesis of diabetic nephropathy.

Methods

We investigated the role of five known single nucleotide polymorphisms (SNPs) in the TGFB1 gene for their association with diabetic nephropathy in an Irish, type 1 diabetic case (n = 272) control (n = 367) collection. The activity of TGFβ1 is facilitated by the action of type 1 and type 2 receptors, with both receptor genes (TGFBR1 and TGFBR2) shown to be upregulated in diabetic kidney disease. We therefore screened TGFBR1 and TGFBR2 genes for genomic variants using WAVE™ (dHPLC) technology and confirmed variants by direct capillary sequencing. Allele frequencies were determined in forty-eight healthy individuals. Data for all SNPs was assessed for Hardy Weinberg equilibrium, with genotypes and allele frequencies compared using the χ2 test for contingency tables. Patterns of linkage disequilibrium were established and common haplotypes estimated.

Results

Fifteen variants were identified in these genes, seven of which are novel, and putatively functional SNPs were subsequently genotyped using TaqMan™, Invader™ or Pyrosequencing® technology. No significant differences (p > 0.1) were found in genotype or allele distributions between cases and controls for any of the SNPs assessed.

Conclusion

Our results suggest common variants in TGFB1, TGFBR1 and TGFBR2 genes do not strongly influence genetic susceptibility to diabetic nephropathy in an Irish Caucasian population.

OBJECTIVE

Despite extensive evidence for genetic susceptibility to diabetic nephropathy, the identification of susceptibility genes and their variants has had limited success. To search for genes that contribute to diabetic nephropathy, a genome-wide association scan was implemented on the Genetics of Kidneys in Diabetes collection.

RESEARCH DESIGN AND METHODS

We genotyped ∼360,000 single nucleotide polymorphisms (SNPs) in 820 case subjects (284 with proteinuria and 536 with end-stage renal disease) and 885 control subjects with type 1 diabetes. Confirmation of implicated SNPs was sought in 1,304 participants of the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, a long-term, prospective investigation of the development of diabetes-associated complications.

RESULTS

A total of 13 SNPs located in four genomic loci were associated with diabetic nephropathy with P < 1 × 10−5. The strongest association was at the FRMD3 (4.1 protein ezrin, radixin, moesin [FERM] domain containing 3) locus (odds ratio [OR] = 1.45, P = 5.0 × 10−7). A strong association was also identified at the CARS (cysteinyl-tRNA synthetase) locus (OR = 1.36, P = 3.1 × 10−6). Associations between both loci and time to onset of diabetic nephropathy were supported in the DCCT/EDIC study (hazard ratio [HR] = 1.33, P = 0.02, and HR = 1.32, P = 0.01, respectively). We demonstratedexpression of both FRMD3 and CARS in human kidney.

CONCLUSIONS

We identified genetic associations for susceptibility to diabetic nephropathy at two novel candidate loci near the FRMD3 and CARS genes. Their identification implicates previously unsuspected pathways in the pathogenesis of this important late complication of type 1 diabetes.