Summary 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. Furthermore, we show that differences in aging rates help explain epigenetic drift and are reflected in the transcriptome. Our model highlights specific components of the aging process and provides a quantitative read-out for studying the role of methylation in age-related disease.

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.

We have extensively characterized the DNA methylomes of 139 patients with chronic lymphocytic leukemia (CLL) with mutated or unmutated IGHV and of several mature B-cell subpopulations through the use of whole-genome bisulfite sequencing and high-density microarrays. The two molecular subtypes of CLL have differing DNA methylomes that seem to represent epigenetic imprints from distinct normal B-cell subpopulations. DNA hypomethylation in the gene body, targeting mostly enhancer sites, was the most frequent difference between naive and memory B cells and between the two molecular subtypes of CLL and normal B cells. Although DNA methylation and gene expression were poorly correlated, we identified gene-body CpG dinucleotides whose methylation was positively or negatively associated with expression. We have also recognized a DNA methylation signature that distinguishes new clinico-biological subtypes of CLL. We propose an epigenomic scenario in which differential methylation in the gene body may have functional and clinical implications in leukemogenesis.

BACKGROUND & AIMS Cholangiocarcinoma, the second most common liver cancer, can be classified as intra-hepatic cholangiocarcinoma (ICC) or extrahepatic cholangiocarcinoma. We performed an integrative genomic analysis of ICC samples from a large series of patients. METHODS We performed a gene expression profile, high-density single-nucleotide polymorphism array, and mutation analyses using formalin-fixed ICC samples from 149 patients. Associations with clinicopathologic traits and patient outcomes were examined for 119 cases. Class discovery was based on a non-negative matrix factorization algorithm and significant copy number variations were identified by GISTIC analysis. Gene set enrichment analysis was used to identify signaling pathways activated in specific molecular classes of tumors, and to analyze their genomic overlap with hepatocellular carcinoma (HCC). RESULTS We identified 2 main biological classes of ICC. The inflammation class (38% of ICCs) is characterized by activation of inflammatory signaling pathways, overexpression of cytokines, and STAT3 activation. The proliferation class (62%) is characterized by activation of oncogenic signaling pathways (including RAS, mitogen-activated protein kinase, and MET), DNA amplifications at 11q13.2, deletions at 14q22.1, mutations in KRAS and BRAF, and gene expression signatures previously associated with poor outcomes for patients with HCC. Copy number variation– based clustering was able to refine these molecular groups further. We identified high-level amplifications in 5 regions, including 1p13 (9%) and 11q13.2 (4%), and several focal deletions, such as 9p21.3 (18%) and 14q22.1 (12% in coding regions for the SAV1 tumor suppressor). In a complementary approach, we identified a gene expression signature that was associated with reduced survival times of patients with ICC; this signature was enriched in the proliferation class (P < .001). CONCLUSIONS We used an integrative genomic analysis to identify 2 classes of ICC. The proliferation class has specific copy number alterations, many features of the poor-prognosis signatures for HCC, and is associated with worse outcome. Different classes of ICC, based on molecular features, therefore might require different treatment approaches.

Gastrointestinal stromal tumors (GIST) harbor driver mutations of signal transduction kinases such as KIT, or, alternatively, manifest loss-of-function defects in the mitochondrial succinate dehydrogenase (SDH) complex, a component of the Krebs cycle and electron transport chain. We have uncovered a striking divergence between the DNA methylation profiles of SDH-deficient GIST (n = 24) versus KIT tyrosine kinase pathway–mutated GIST (n = 39). Infinium 450K methylation array analysis of formalin-fixed paraffin-embedded tissues disclosed an order of magnitude greater genomic hypermethylation relative to SDH-deficient GIST versus the KIT-mutant group (84.9 K vs. 8.4 K targets). Epigenomic divergence was further found among SDH-mutant paraganglioma/pheochromocytoma (n = 29), a developmentally distinct SDH-deficient tumor system. Comparison of SDH -mutant GIST with isocitrate dehydrogenase -mutant glioma, another Krebs cycle–defective tumor type, revealed comparable measures of global hypo- and hypermethylation. These data expose a vital connection between succinate metabolism and genomic DNA methylation during tumorigenesis, and generally implicate the mitochondrial Krebs cycle in nuclear epigenomic maintenance. SIGNIFICANCE This study shows that SDH deficiency underlies pervasive DNA hypermethylation in multiple tumor lineages, generally defining the Krebs cycle as mitochondrial custodian of the methylome. We propose that this phenomenon may result from a failure of maintenance CpG demethylation, secondary to inhibition of the TET 5-methylcytosine dioxgenase demethylation pathway, by inhibitory metabolites that accumulate in tumors with Krebs cycle dysfunction.

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.

BackgroundWe have developed a gene expression assay (Whole-Genome DASL®), capable of generating whole-genome gene expression profiles from degraded samples such as formalin-fixed, paraffin-embedded (FFPE) specimens.Methodology/Principal FindingsWe demonstrated a similar level of sensitivity in gene detection between matched fresh-frozen (FF) and FFPE samples, with the number and overlap of probes detected in the FFPE samples being approximately 88% and 95% of that in the corresponding FF samples, respectively; 74% of the differentially expressed probes overlapped between the FF and FFPE pairs. The WG-DASL assay is also able to detect 1.3–1.5 and 1.5–2 -fold changes in intact and FFPE samples, respectively. The dynamic range for the assay is ∼3 logs. Comparing the WG-DASL assay with an in vitro transcription-based labeling method yielded fold-change correlations of R2 ∼0.83, while fold-change comparisons with quantitative RT-PCR assays yielded R2∼0.86 and R2∼0.55 for intact and FFPE samples, respectively. Additionally, the WG-DASL assay yielded high self-correlations (R2>0.98) with low intact RNA inputs ranging from 1 ng to 100 ng; reproducible expression profiles were also obtained with 250 pg total RNA (R2∼0.92), with ∼71% of the probes detected in 100 ng total RNA also detected at the 250 pg level. When FFPE samples were assayed, 1 ng total RNA yielded self-correlations of R2∼0.80, while still maintaining a correlation of R2∼0.75 with standard FFPE inputs (200 ng).Conclusions/SignificanceTaken together, these results show that WG-DASL assay provides a reliable platform for genome-wide expression profiling in archived materials. It also possesses utility within clinical settings where only limited quantities of samples may be available (e.g. microdissected material) or when minimally invasive procedures are performed (e.g. biopsied specimens).

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.