Genome-wide methylation profiles reveal quantitative views of human aging rates.

The ability to measure human aging from molecular profiles has practical implications in many fields, including disease prevention and treatment, forensics, and extension of life. Although chronological age has been linked to changes in DNA methylation, the methylome has not yet been used to measure and compare human aging rates. Here, we build a quantitative model of aging using measurements at more than 450,000 CpG markers from the whole blood of 656 human individuals, aged 19 to 101. This model measures the rate at which an individual's methylome ages, which we show is impacted by gender and genetic variants. We also show that differences in aging rates help explain epigenetic drift and are reflected in the transcriptome. Moreover, we show how our aging model is upheld in other human tissues and reveals an advanced aging rate in tumor tissue. Our model highlights specific components of the aging process and provides a quantitative readout for studying the role of methylation in age-related disease.

Pisces: an accurate and versatile variant caller for somatic and germline next-generation sequencing data.

MOTIVATION: Next-generation sequencing technology is transitioning quickly from research labs to clinical settings. The diagnosis and treatment selection for many acquired and autosomal conditions necessitate a method for accurately detecting somatic and germline variants. RESULTS: We have developed Pisces, a rapid, versatile and accurate small-variant calling suite designed for somatic and germline amplicon sequencing applications. Accuracy is achieved by four distinct modules, each incorporating a number of novel algorithmic strategies. AVAILABILITY AND IMPLEMENTATION: Pisces is distributed under an open source license and can be downloaded from https://github.com/Illumina/Pisces. Pisces is available on the BaseSpace™ SequenceHub. It is distributed on Illumina sequencing platforms such as the MiSeq™ and is included in the Praxis™ Extended RAS Panel test which was recently approved by the FDA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DNA methylation profiles in African American prostate cancer patients in relation to disease progression.

This study examined whether differential DNA methylation is associated with clinical features of more aggressive disease at diagnosis and prostate cancer recurrence in African American men, who are more likely to die from prostate cancer than other populations. Tumor tissues from 76 African Americans diagnosed with prostate cancer who had radical prostatectomy as their primary treatment were profiled for epigenome-wide DNA methylation levels. Long-term follow-up identified 19 patients with prostate cancer recurrence. Twenty-three CpGs were differentially methylated (FDR q≤0.25, mean methylation difference≥0.10) in patients with vs. without recurrence, including CpGs in GCK, CDKL2, PRDM13, and ZFR2. Methylation differences were also observed between men with metastatic-lethal prostate cancer vs. no recurrence (five CpGs), regional vs. local pathological stage (two CpGs), and higher vs. lower tumor aggressiveness (one CpG). These results indicate that differentially methylated CpG sites identified in tumor tissues of African American men may contribute to prostate cancer aggressiveness.

Substantial DNA methylation differences between two major neuronal subtypes in human brain.

The brain is built from a large number of cell types which have been historically classified using location, morphology and molecular markers. Recent research suggests an important role of epigenetics in shaping and maintaining cell identity in the brain. To elucidate the role of DNA methylation in neuronal differentiation, we developed a new protocol for separation of nuclei from the two major populations of human prefrontal cortex neurons--GABAergic interneurons and glutamatergic (GLU) projection neurons. Major differences between the neuronal subtypes were revealed in CpG, non-CpG and hydroxymethylation (hCpG). A dramatically greater number of undermethylated CpG sites in GLU versus GABA neurons were identified. These differences did not directly translate into differences in gene expression and did not stem from the differences in hCpG methylation, as more hCpG methylation was detected in GLU versus GABA neurons. Notably, a comparable number of undermethylated non-CpG sites were identified in GLU and GABA neurons, and non-CpG methylation was a better predictor of subtype-specific gene expression compared to CpG methylation. Regions that are differentially methylated in GABA and GLU neurons were significantly enriched for schizophrenia risk loci. Collectively, our findings suggest that functional differences between neuronal subtypes are linked to their epigenetic specification.

TP53 mutations, tetraploidy and homologous recombination repair defects in early stage high-grade serous ovarian cancer.

To determine early somatic changes in high-grade serous ovarian cancer (HGSOC), we performed whole genome sequencing on a rare collection of 16 low stage HGSOCs. The majority showed extensive structural alterations (one had an ultramutated profile), exhibited high levels of p53 immunoreactivity, and harboured a TP53 mutation, deletion or inactivation. BRCA1 and BRCA2 mutations were observed in two tumors, with nine showing evidence of a homologous recombination (HR) defect. Combined Analysis with The Cancer Genome Atlas (TCGA) indicated that low and late stage HGSOCs have similar mutation and copy number profiles. We also found evidence that deleterious TP53 mutations are the earliest events, followed by deletions or loss of heterozygosity (LOH) of chromosomes carrying TP53, BRCA1 or BRCA2. Inactivation of HR appears to be an early event, as 62.5% of tumours showed a LOH pattern suggestive of HR defects. Three tumours with the highest ploidy had little genome-wide LOH, yet one of these had a homozygous somatic frame-shift BRCA2 mutation, suggesting that some carcinomas begin as tetraploid then descend into diploidy accompanied by genome-wide LOH. Lastly, we found evidence that structural variants (SV) cluster in HGSOC, but are absent in one ultramutated tumor, providing insights into the pathogenesis of low stage HGSOC.

Prostate tumor DNA methylation is associated with cigarette smoking and adverse prostate cancer outcomes.

BACKGROUND: DNA methylation has been hypothesized as a mechanism for explaining the association between smoking and adverse prostate cancer (PCa) outcomes. This study was aimed at assessing whether smoking is associated with prostate tumor DNA methylation and whether these alterations may explain in part the association of smoking with PCa recurrence and mortality. METHODS: A total of 523 men had radical prostatectomy as their primary treatment, detailed smoking history data, long-term follow-up for PCa outcomes, and tumor tissue profiled for DNA methylation. Ninety percent of the men also had matched tumor gene expression data. A methylome-wide analysis was conducted to identify differentially methylated regions (DMRs) by smoking status. To select potential functionally relevant DMRs, their correlation with the messenger RNA (mRNA) expression of corresponding genes was evaluated. Finally, a smoking-related methylation score based on the top-ranked DMRs was created to assess its association with PCa outcomes. RESULTS: Forty DMRs were associated with smoking status, and 10 of these were strongly correlated with mRNA expression (aldehyde oxidase 1 [AOX1], claudin 5 [CLDN5], early B-cell factor 1 [EBF1], homeobox A7 [HOXA7], lectin galactoside-binding soluble 3 [LGALS3], microtubule-associated protein τ [MAPT], protocadherin γ A [PCDHGA]/protocadherin γ B [PCDHGB], paraoxonase 3 [PON3], synaptonemal complex protein 2 like [SYCP2L], and zinc finger and SCAN domain containing 12 [ZSCAN12]). Men who were in the highest tertile for the smoking-methylation score derived from these DMRs had a higher risk of recurrence (odds ratio [OR], 2.29; 95% confidence interval [CI], 1.42-3.72) and lethal disease (OR, 4.21; 95% CI, 1.65-11.78) in comparison with men in the lower 2 tertiles. CONCLUSIONS: This integrative molecular epidemiology study supports the hypothesis that smoking-associated tumor DNA methylation changes may explain at least part of the association between smoking and adverse PCa outcomes. Future studies are warranted to confirm these findings and understand the implications for improving patient outcomes. Cancer 2016;122:2168-77. © 2016 American Cancer Society.

Differences in DNA methylation between human neuronal and glial cells are concentrated in enhancers and non-CpG sites.

We applied Illumina Human Methylation450K array to perform a genomic-scale single-site resolution DNA methylation analysis in neuronal and nonneuronal (primarily glial) nuclei separated from the orbitofrontal cortex of postmortem human brain. The findings were validated using enhanced reduced representation bisulfite sequencing. We identified thousands of sites differentially methylated (DM) between neuronal and nonneuronal cells. The DM sites were depleted within CpG-island-containing promoters but enriched in predicted enhancers. Classification of the DM sites into those undermethylated in neurons (neuronal type) and those undermethylated in nonneuronal cells (glial type), combined with findings of others that methylation within control elements typically negatively correlates with gene expression, yielded large sets of predicted neuron-specific and non-neuron-specific genes. These sets of predicted genes were in excellent agreement with the available direct measurements of gene expression in human and mouse. We also found a distinct set of DNA methylation patterns that were unique for neuronal cells. In particular, neuronal-type differential methylation was overrepresented in CpG island shores, enriched within gene bodies but not in intergenic regions, and preferentially harbored binding motifs for a distinct set of transcription factors, including neuron-specific activity-dependent factors. Finally, non-CpG methylation was substantially more prevalent in neurons than in nonneuronal cells.

Whole-genome haplotyping by dilution, amplification, and sequencing.

Standard whole-genome genotyping technologies are unable to determine haplotypes. Here we describe a method for rapid and cost-effective long-range haplotyping. Genomic DNA is diluted and distributed into multiple aliquots such that each aliquot receives a fraction of a haploid copy. The DNA template in each aliquot is amplified by multiple displacement amplification, converted into barcoded sequencing libraries using Nextera technology, and sequenced in multiplexed pools. To assess the performance of our method, we combined two male genomic DNA samples at equal ratios, resulting in a sample with diploid X chromosomes with known haplotypes. Pools of the multiplexed sequencing libraries were subjected to targeted pull-down of a 1-Mb contiguous region of the X-chromosome Duchenne muscular dystrophy gene. We were able to phase the Duchenne muscular dystrophy region into two contiguous haplotype blocks with a mean length of 494 kb. The haplotypes showed 99% agreement with the consensus base calls made by sequencing the individual DNAs. We subsequently used the strategy to haplotype two human genomes. Standard genomic sequencing to identify all heterozygous SNPs in the sample was combined with dilution-amplification-based sequencing data to resolve the phase of identified heterozygous SNPs. Using this procedure, we were able to phase >95% of the heterozygous SNPs from the diploid sequence data. The N50 for a Yoruba male DNA was 702 kb whereas the N50 for a European female DNA was 358 kb. Therefore, the strategy described here is suitable for haplotyping of a set of targeted regions as well as of the entire genome.

Epigenome-wide ovarian cancer analysis identifies a methylation profile differentiating clear-cell histology with epigenetic silencing of the HERG K+ channel.

Ovarian cancer remains the leading cause of death in women with gynecologic malignancies, despite surgical advances and the development of more effective chemotherapeutics. As increasing evidence indicates that clear-cell ovarian cancer may have unique pathogenesis, further understanding of molecular features may enable us to begin to understand the underlying biology and histology-specific information for improved outcomes. To study epigenetics in clear-cell ovarian cancer, fresh frozen tumor DNA (n = 485) was assayed on Illumina Infinium HumanMethylation450 BeadChips. We identified a clear-cell ovarian cancer tumor methylation profile (n = 163) which we validated in two independent replication sets (set 1, n = 163; set 2, n = 159), highlighting 22 CpG loci associated with nine genes (VWA1, FOXP1, FGFRL1, LINC00340, KCNH2, ANK1, ATXN2, NDRG21 and SLC16A11). Nearly all of the differentially methylated CpGs showed a propensity toward hypermethylation among clear-cell cases. Several loci methylation inversely correlated with tumor gene expression, most notably KCNH2 (HERG, a potassium channel) (P = 9.5 × 10(-7)), indicating epigenetic silencing. In addition, a predicted methylation class mainly represented by the clear-cell cases (20 clear cell out of 23 cases) had improved survival time. Although these analyses included only 30 clear-cell carcinomas, results suggest that loss of expression of KCNH2 (HERG) by methylation could be a good prognostic marker, given that overexpression of the potassium (K(+)) channel Eag family members promotes increased proliferation and results in poor prognosis. Validation in a bigger cohort of clear-cell tumors of the ovary is warranted.

Epigenomic profiling of DNA methylation in paired prostate cancer versus adjacent benign tissue.

BACKGROUND: Aberrant DNA methylation may promote prostate carcinogenesis. We investigated epigenome-wide DNA methylation profiles in prostate cancer (PCa) compared to adjacent benign tissue to identify differentially methylated CpG sites. METHODS: The study included paired PCa and adjacent benign tissue samples from 20 radical prostatectomy patients. Epigenetic profiling was done using the Infinium HumanMethylation450 BeadChip. Linear models that accounted for the paired study design and False Discovery Rate Q-values were used to evaluate differential CpG methylation. mRNA expression levels of the genes with the most differentially methylated CpG sites were analyzed. RESULTS: In total, 2,040 differentially methylated CpG sites were identified in PCa versus adjacent benign tissue (Q-value < 0.001), the majority of which were hypermethylated (n = 1,946; 95%). DNA methylation profiles accurately distinguished between PCa and benign tissue samples. Twenty-seven top-ranked hypermethylated CpGs had a mean methylation difference of at least 40% between tissue types, which included 25 CpGs in 17 genes. Furthermore, for 10 genes over 50% of promoter region CpGs were hypermethylated in PCa versus benign tissue. The top-ranked differentially methylated genes included three genes that were associated with both promoter hypermethylation and reduced gene expression: SCGB3A1, HIF3A, and AOX1. Analysis of The Cancer Genome Atlas (TCGA) data provided confirmatory evidence for our findings. CONCLUSIONS: This study of PCa versus adjacent benign tissue showed many differentially methylated CpGs and regions in and outside gene promoter regions, which may potentially be used for the development of future epigenetic-based diagnostic tests or as therapeutic targets.

Application of a low cost array-based technique - TAB-Array - for quantifying and mapping both 5mC and 5hmC at single base resolution in human pluripotent stem cells.

5-hydroxymethylcytosine (5hmC), an oxidized derivative of 5-methylcytosine (5mC), has been implicated as an important epigenetic regulator of mammalian development. Current procedures use DNA sequencing methods to discriminate 5hmC from 5mC, limiting their accessibility to the scientific community. Here we report a method that combines TET-assisted bisulfite conversion with Illumina 450K DNA methylation arrays for a low-cost high-throughput approach that distinguishes 5hmC and 5mC signals at base resolution. Implementing this approach, termed "TAB-array", we assessed DNA methylation dynamics in the differentiation of human pluripotent stem cells into cardiovascular progenitors and neural precursor cells. With the ability to discriminate 5mC and 5hmC, we identified a large number of novel dynamically methylated genomic regions that are implicated in the development of these lineages. The increased resolution and accuracy afforded by this approach provides a powerful means to investigate the distinct contributions of 5mC and 5hmC in human development and disease.

Liquid biopsy for early detection of lung cancer.

Lung cancer is the leading cause of cancer-related mortality worldwide. Early cancer detection plays an important role in improving treatment success and patient prognosis. In the past decade, liquid biopsy became an important tool for cancer diagnosis, as well as for treatment selection and response monitoring. Liquid biopsy is a broad term that defines a non-invasive test done on a sample of blood or other body fluid to look for cancer cells or other analytes that can include DNA, RNA, or other molecules released by tumor cells. Liquid biopsies mainly include circulating tumor DNA, circulating RNA, microRNA, proteins, circulating tumor cells, exosomes, and tumor-educated platelets. This review summarizes the progress and clinical application potential of liquid biopsy for early detection of lung cancer.

A methyl-deviator epigenotype of estrogen receptor-positive breast carcinoma is associated with malignant biology.

We broadly profiled DNA methylation in breast cancers (n = 351) and benign parenchyma (n = 47) for correspondence with disease phenotype, using FFPE diagnostic surgical pathology specimens. Exploratory analysis revealed a distinctive primary invasive carcinoma subclass featuring extreme global methylation deviation. Subsequently, we tested the correlation between methylation remodeling pervasiveness and malignant biological features. A methyl deviation index (MDI) was calculated for each lesion relative to terminal ductal-lobular unit baseline, and group comparisons revealed that high-grade and short-survival estrogen receptor-positive (ER(+)) cancers manifest a significantly higher MDI than low-grade and long-survival ER(+) cancers. In contrast, ER(-) cancers display a significantly lower MDI, revealing a striking epigenomic distinction between cancer hormone receptor subtypes. Kaplan-Meier survival curves of MDI-based risk classes showed significant divergence between low- and high-risk groups. MDI showed superior prognostic performance to crude methylation levels, and MDI retained prognostic significance (P < 0.01) in Cox multivariate analysis, including clinical stage and pathological grade. Most MDI targets individually are significant markers of ER(+) cancer survival. Lymphoid and mesenchymal indexes were not substantially different between ER(+) and ER(-) groups and do not explain MDI dichotomy. However, the mesenchymal index was associated with ER(+) cancer survival, and a high lymphoid index was associated with medullary carcinoma. Finally, a comparison between metastases and primary tumors suggests methylation patterns are established early and maintained through disease progression for both ER(+) and ER(-) tumors.

High density DNA methylation array with single CpG site resolution.

We have developed a new generation of genome-wide DNA methylation BeadChip which allows high-throughput methylation profiling of the human genome. The new high density BeadChip can assay over 480K CpG sites and analyze twelve samples in parallel. The innovative content includes coverage of 99% of RefSeq genes with multiple probes per gene, 96% of CpG islands from the UCSC database, CpG island shores and additional content selected from whole-genome bisulfite sequencing data and input from DNA methylation experts. The well-characterized Infinium® Assay is used for analysis of CpG methylation using bisulfite-converted genomic DNA. We applied this technology to analyze DNA methylation in normal and tumor DNA samples and compared results with whole-genome bisulfite sequencing (WGBS) data obtained for the same samples. Highly comparable DNA methylation profiles were generated by the array and sequencing methods (average R2 of 0.95). The ability to determine genome-wide methylation patterns will rapidly advance methylation research.

DNA methylation and gene expression differences in children conceived in vitro or in vivo.

Epidemiological data indicate that children conceived in vitro have a greater relative risk of low birth-weight, major and minor birth defects, and rare disorders involving imprinted genes, suggesting that epigenetic changes may be associated with assisted reproduction. We examined DNA methylation at more than 700 genes (1536 CpG sites) in placenta and cord blood and measured gene expression levels of a subset of genes that differed in methylation levels between children conceived in vitro versus in vivo. Our results suggest that in vitro conception is associated with lower mean methylation at CpG sites in placenta and higher mean methylation at CpG sites in cord blood. We also find that in vitro conception-associated DNA methylation differences are associated with gene expression differences at both imprinted and non-imprinted genes. The range of inter-individual variation in gene expression of the in vitro and in vivo groups overlaps substantially but some individuals from the in vitro group differ from the in vivo group mean by more than two standard deviations. Several of the genes whose expression differs between the two groups have been implicated in chronic metabolic disorders, such as obesity and type II diabetes. These findings suggest that there may be epigenetic differences in the gametes or early embryos derived from couples undergoing treatment for infertility. Alternatively, assisted reproduction technology may have an effect on global patterns of DNA methylation and gene expression. In either case, these differences or changes may affect long-term patterns of gene expression.

New insights into the biology and origin of mature aggressive B-cell lymphomas by combined epigenomic, genomic, and transcriptional profiling.

Lymphomas are assumed to originate at different stages of lymphocyte development through chromosomal aberrations. Thus, different lymphomas resemble lymphocytes at distinct differentiation stages and show characteristic morphologic, genetic, and transcriptional features. Here, we have performed a microarray-based DNA methylation profiling of 83 mature aggressive B-cell non-Hodgkin lymphomas (maB-NHLs) characterized for their morphologic, genetic, and transcriptional features, including molecular Burkitt lymphomas and diffuse large B-cell lymphomas. Hierarchic clustering indicated that methylation patterns in maB-NHLs were not strictly associated with morphologic, genetic, or transcriptional features. By supervised analyses, we identified 56 genes de novo methylated in all lymphoma subtypes studied and 22 methylated in a lymphoma subtype-specific manner. Remarkably, the group of genes de novo methylated in all lymphoma subtypes was significantly enriched for polycomb targets in embryonic stem cells. De novo methylated genes in all maB-NHLs studied were expressed at low levels in lymphomas and normal hematopoietic tissues but not in nonhematopoietic tissues. These findings, especially the enrichment for polycomb targets in stem cells, indicate that maB-NHLs with different morphologic, genetic, and transcriptional background share a similar stem cell-like epigenetic pattern. This suggests that maB-NHLs originate from cells with stem cell features or that stemness was acquired during lymphomagenesis by epigenetic remodeling.

Differential allelic expression in the human genome: a robust approach to identify genetic and epigenetic cis-acting mechanisms regulating gene expression.

The recent development of whole genome association studies has lead to the robust identification of several loci involved in different common human diseases. Interestingly, some of the strongest signals of association observed in these studies arise from non-coding regions located in very large introns or far away from any annotated genes, raising the possibility that these regions are involved in the etiology of the disease through some unidentified regulatory mechanisms. These findings highlight the importance of better understanding the mechanisms leading to inter-individual differences in gene expression in humans. Most of the existing approaches developed to identify common regulatory polymorphisms are based on linkage/association mapping of gene expression to genotypes. However, these methods have some limitations, notably their cost and the requirement of extensive genotyping information from all the individuals studied which limits their applications to a specific cohort or tissue. Here we describe a robust and high-throughput method to directly measure differences in allelic expression for a large number of genes using the Illumina Allele-Specific Expression BeadArray platform and quantitative sequencing of RT-PCR products. We show that this approach allows reliable identification of differences in the relative expression of the two alleles larger than 1.5-fold (i.e., deviations of the allelic ratio larger than 60:40) and offers several advantages over the mapping of total gene expression, particularly for studying humans or outbred populations. Our analysis of more than 80 individuals for 2,968 SNPs located in 1,380 genes confirms that differential allelic expression is a widespread phenomenon affecting the expression of 20% of human genes and shows that our method successfully captures expression differences resulting from both genetic and epigenetic cis-acting mechanisms.

Identification and functional relevance of de novo DNA methylation in cancerous B-cell populations.

Epigenetic remodeling is a hallmark of cancer, with the frequent acquisition of de novo DNA methylation in CpG islands. However, the functional relevance of de novo DNA methylation in cancer is less well defined. To begin to address this issue in B-cells, we used BeadArray assays to survey the methylation status of over 1,500 cancer-related CpG loci in two molecular subtypes of diffuse large B-cell lymphoma (ABC-DLBCL and GCB-DLBCL) and cognate normal B-cell populations. We identified 81 loci that showed frequent de novo DNA methylation in GCB-DLBCL and 67 loci that showed frequent de novo DNA methylation in ABC-DLBCL. These de novo methylated CpG loci included reported targets of polycomb repressive complexes (PRC) in stem cells. All candidate loci in GCB-DLBCL are proximal to genes that are poorly expressed or silent in purified normal germinal center (GC) B-cells. This is consistent with the hypothesis that de novo DNA methylation in cancer is more frequently involved in the maintenance rather than the initiation of gene silencing (de novo repression). This suggests that epigenetic switching occurs during tumorigenesis with de novo DNA methylation locking in gene silencing normally mediated by transcriptional repressors. Furthermore, we propose that similar to de novo genetic mutations, the majority of de novo DNA methylation events observed in tumors are passengers not causally involved in tumorigenesis.

Array-based DNA methylation profiling of primary lymphomas of the central nervous system.

BACKGROUND: Although primary lymphomas of the central nervous system (PCNSL) and extracerebral diffuse large B-cell lymphoma (DLBCL) cannot be distinguished histologically, it is still a matter of debate whether PCNSL differ from systemic DLBCL with respect to their molecular features and pathogenesis. Analysis of the DNA methylation pattern might provide further data distinguishing these entities at a molecular level. METHODS: Using an array-based technology we have assessed the DNA methylation status of 1,505 individual CpG loci in five PCNSL and compared the results to DNA methylation profiles of 49 DLBCL and ten hematopoietic controls. RESULTS: We identified 194 genes differentially methylated between PCNSL and normal controls. Interestingly, Polycomb target genes and genes with promoters showing a high CpG content were significantly enriched in the group of genes hypermethylated in PCNSL. However, PCNSL and systemic DLBCL did not differ in their methylation pattern. CONCLUSIONS: Based on the data presented here, PCNSL and DLBCL do not differ in their DNA methylation pattern. Thus, DNA methylation analysis does not support a separation of PCNSL and DLBCL into individual entities. However, PCNSL and DLBCL differ in their DNA methylation pattern from non- malignant controls.

GoldenGate assay for DNA methylation profiling.

We describe a highly reproducible and multiplexed method, the GoldenGate assay for methylation, for high-throughput quantitative measurements of DNA methylation. It can analyze up to 1,536 targeted CpG sites in 96 samples simultaneously, using only 250 ng of genomic DNA. The method is akin to a "genotyping" of bisulfite-converted DNA. Assay probes can be designed to interrogate the Watson strand, the Crick strand, or both strands at each CpG site. Assay end products are processed using Illumina universal bead arrays. As a result, gene or CpG sets can be refined iteratively--no custom arrays need to be developed. This method allows the detection of as little as 2.5% methylation, and can distinguish 17% difference in absolute methylation level between samples. The method is highly reproducible and compares very well with other common methods of methylation detection, such as methylation-specific PCR and bisulfite sequencing. The Illumina GoldenGate Methylation technology should prove useful for DNA methylation analyses in large populations, with potential application to biomarker discovery and validation.