Dvir Aran

Genome-wide survey reveals predisposing diabetes type 2-related DNA methylation variations in human peripheral blood

Inter-individual DNA methylation variations were frequently hypothesized to alter individual susceptibility to Type 2 Diabetes Mellitus (T2DM). Sequence-influenced methylations were described in T2DM-associated genomic regions, but evidence for direct, sequence-independent association with disease risk is missing. Here, we explore disease-contributing DNA methylation through a stepwise study design: first, a pool-based, genome-scale screen among 1169 case and control individuals revealed an excess of differentially methylated sites in genomic regions that were previously associated with T2DM through genetic studies. Next, in-depth analyses were performed at selected top-ranking regions. A CpG site in the first intron of the FTO gene showed small (3.35%) but significant (P = 0.000021) hypomethylation of cases relative to controls. The effect was independent of the sequence polymorphism in the region and persists among individuals carrying the sequence-risk alleles. The odds of belonging to the T2DM group increased by 6.1% for every 1% decrease in methylation (OR = 1.061, 95% CI: 1.032-1.090), the odds ratio for decrease of 1 standard deviation of methylation (adjusted to gender) was 1.5856 (95% CI: 1.2824-1.9606) and the sensitivity (area under the curve = 0.638, 95% CI: 0.586-0.690; males = 0.675, females = 0.609) was better than that of the strongest known sequence variant. Furthermore, a prospective study in an independent population cohort revealed significant hypomethylation of young individuals that later progressed to T2DM, relative to the individuals who stayed healthy. Further genomic analysis revealed co-localization with gene enhancers and with binding sites for methylation-sensitive transcriptional regulators. The data showed that low methylation level at the analyzed sites is an early marker of T2DM and suggests a novel mechanism by which early-onset, inter-individual methylation variation at isolated non-promoter genomic sites predisposes to T2DM.

DNA methylation of distal regulatory sites characterizes dysregulation of cancer genes

BackgroundAbnormal epigenetic marking is well documented in gene promoters of cancer cells, but the study of distal regulatory siteshas lagged behind.We performed a systematic analysis of DNA methylation sites connected with gene expression profilesacross normal and cancerous human genomes.ResultsUtilizing methylation and expression data in 58 cell types, we developed a model for methylation-expression relationships in gene promoters and extrapolated it to the genome. We mapped numerous sites at which DNA methylation was associated with expression of distal genes. These sites bind transcription factors in a methylation-dependent manner, and carry the chromatin marks of a particular class of transcriptional enhancers. In contrast to the traditional model of one enhancer site per cell type, we found that single enhancer sites may define gradients of expression levels across many different cell types. Strikingly, the identified sites were drastically altered in cancers: hypomethylated enhancer sites associated with upregulation of cancer-related genes and hypermethylated sites with downregulation. Moreover, the association between enhancer methylation and gene deregulation in cancerwas significantly stronger than the association of promoter methylationwith gene deregulation.ConclusionsMethylation of distal regulatory sites is closely related to gene expression levels across the genome. Single enhancers may modulate ranges of cell-specific transcription levels, from constantlyopen promoters. In contrast to the remote relationships between promoter methylation and gene dysregulation in cancer, altered methylation of enhancer sites is closely related to gene expression profiles of transformed cells.

Replication timing-related and gene body-specific methylation of active human genes

Understanding how the epigenetic blueprint of the genome shapes human phenotypes requires systematic evaluation of the complex interplay between gene activity and the different layers of the epigenome. Utilizing microarray-based techniques, we explored the relationships between DNA methylation, DNA replication timing and gene expression levels across a variety of human tissues and cell lines. The analyses revealed unequal methylation levels among early- and late-replicating fractions of the genome: late-replicating DNA was hypomethylated compared with early-replicating DNA. Moreover, late-replicating regions were gradually demethylated with cell divisions, whereas the methylation of early-replicating regions was better maintained. As active genes concentrate at early-replicating regions, they are overall hypermethylated relative to inactive genes. Accordingly, we show that the previously reported positive correlation between gene-body methylation (methylation of the transcribed portion of genes) and gene expression is restricted to proliferative tissues and cell lines, whereas in tissues containing few proliferating cells, active and inactive genes have similar methylation levels. We further show that active gene bodies are hypermethylated not only compared with inactive gene bodies, but also compared with their flanking sequences. This specific hypermethylation of the active gene bodies is severely disrupted in cells of an immunodeficiency, centromeric region instability, facial anomalies (ICF) syndrome patient bearing mutated DNA methyltransferase 3B (DNMT3B). Our data show that a high methylation level is preferentially maintained in active gene bodies through independent cellular processes. Rather than serving as a distinctive mark between active and inactive genes, gene-body methylation appears to serve a vital, currently unknown function in active genes.

Systematic pan-cancer analysis of tumour purity

The tumour microenvironment is the non-cancerous cells present in and around a tumour, including mainly immune cells, but also fibroblasts and cells that comprise supporting blood vessels. These non-cancerous components of the tumour may play an important role in cancer biology. They also have a strong influence on the genomic analysis of tumour samples, and may alter the biological interpretation of results. Here we present a systematic analysis using different measurement modalities of tumour purity in >10,000 samples across 21 cancer types from the Cancer Genome Atlas. Patients are stratified according to clinical features in an attempt to detect clinical differences driven by purity levels. We demonstrate the confounding effect of tumour purity on correlating and clustering tumours with transcriptomics data. Finally, using a differential expression method that accounts for tumour purity, we find an immunotherapy gene signature in several cancer types that is not detected by traditional differential expression analyses.

DNA Methylation of Transcriptional Enhancers and Cancer Predisposition

Predisposition to common human diseases is frequently associated with polymorphisms in distal control regions, also known as gene enhancers. Li et al. (Li et al., 2013) evaluated the relative contributions of somatic and germline mutations to intertumor gene expression variation, with the aim of revealing links between genomic regions associated with cancer susceptibility and the expression of genes involved in cancer development. The authors assessed the contribution of DNA methylation in gene promoters to variation in intertumor gene expression and found that 3.3% of this variation can be attributed to methylation variation.

Aging is associated with highly defined epigenetic changes in the human epidermis

BackgroundAltered DNA methylation patterns represent an attractive mechanism for understanding the phenotypic changes associated with human aging. Several studies have described global and complex age-related methylation changes, but their structural and functional significance has remained largely unclear.ResultsWe have used transcriptome sequencing to characterize age-related gene expression changes in the human epidermis. The results revealed a significant set of 75 differentially expressed genes with a strong functional relationship to skin homeostasis. We then used whole-genome bisulfite sequencing to identify age-related methylation changes at single-base resolution. Data analysis revealed no global aberrations, but rather highly localized methylation changes, particularly in promoter and enhancer regions that were associated with altered transcriptional activity.ConclusionsOur results suggest that the core developmental program of human skin is stably maintained through the aging process and that aging is associated with a limited destabilization of the epigenome at gene regulatory elements.

xCell: digitally portraying the tissue cellular heterogeneity landscape

Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate cell subsets from transcriptomes. However, the available methods have used limited sources for training and give only a partial portrayal of the full cellular landscape. Here we present xCell, a novel gene signature-based method, and use it to infer 64 immune and stromal cell types. We harmonized 1822 pure human cell type transcriptomes from various sources and employed a curve fitting approach for linear comparison of cell types and introduced a novel spillover compensation technique for separating them. Using extensive in silico analyses and comparison to cytometry immunophenotyping, we show that xCell outperforms other methods. xCell is available at http://xCell.ucsf.edu/.

Cross-tissue Analysis of Gene and Protein Expression in Normal and Cancer Tissues

The central dogma of molecular biology describes the translation of genetic information from mRNA to protein, but does not specify the quantitation or timing of this process across the genome. We have analyzed protein and gene expression in a diverse set of human tissues. To study concordance and discordance of gene and protein expression, we integrated mass spectrometry data from the Human Proteome Map project and RNA-Seq measurements from the Genotype-Tissue Expression project. We analyzed 16,561 genes and the corresponding proteins in 14 tissue types across nearly 200 samples. A comprehensive tissue- and gene-specific analysis revealed that across the 14 tissues, correlation between mRNA and protein expression was positive and ranged from 0.36 to 0.5. We also identified 1,012 genes whose RNA and protein expression was correlated across all the tissues and examined genes and proteins that were concordantly and discordantly expressed for each tissue of interest. We extended our analysis to look for genes and proteins that were differentially correlated in cancer compared to normal tissues, showing higher levels of correlation in normal tissues. Finally, we explored the implications of these findings in the context of biomarker and drug target discovery.

Widespread parainflammation in human cancer

BackgroundChronic inflammation has been recognized as one of the hallmarks of cancer. We recently showed that parainflammation, a unique variant of inflammation between homeostasis and chronic inflammation, strongly promotes mouse gut tumorigenesis upon p53 loss. Here we explore the prevalence of parainflammation in human cancer and determine its relationship to certain molecular and clinical parameters affecting treatment and prognosis.ResultsWe generated a transcriptome signature to identify parainflammation in many primary human tumors and carcinoma cell lines as distinct from their normal tissue counterparts and the tumor microenvironment and show that parainflammation-positive tumors are enriched for p53 mutations and associated with poor prognosis. Non-steroidal anti-inflammatory drug (NSAID) treatment suppresses parainflammation in both murine and human cancers, possibly explaining a protective effect of NSAIDs against cancer.ConclusionsWe conclude that parainflammation, a low-grade form of inflammation, is widely prevalent in human cancer, particularly in cancer types commonly harboring p53 mutations. Our data suggest that parainflammation may be a driver for p53 mutagenesis and a guide for cancer prevention by NSAID treatment.

Premature aging of leukocyte DNA methylation is associated with type 2 diabetes prevalence.

BackgroundType 2 diabetes mellitus (T2D) is highly prevalent in Middle-Eastern and North African Arab populations, but the molecular basis for this susceptibility is unknown. Altered DNA methylation levels were reported in insulin-secreting and responding tissues, but whether methylation in accessible tissues such as peripheral blood is associated with T2D risk remains an open question. Age-related alteration of DNA methylation level was reported in certain methylation sites, but no association with T2D has been shown. Here we report on a population-based study of 929 men and women representing the East Jerusalem Palestinian (EJP) Arab population and compare with the findings among Israeli Ashkenazi Jews. This is the first reported epigenetic study of an Arab population with a characteristic high prevalence of T2D.ResultsWe found that DNA methylation of a prespecified regulatory site in peripheral blood leukocytes (PBLs) is associated with impaired glucose metabolism and T2D independent of sex, body mass index, and white blood cell composition. This CpG site (Chr16: 53,809,231-2; hg19) is located in a region within an intron of the FTO gene, suspected to serve as a tissue-specific enhancer. The association between PBL hypomethylation and T2D varied by age, revealing differential patterns of methylation aging in healthy and diabetic individuals and between ethnic groups: T2D patients displayed prematurely low methylation levels, and this hypomethylation was greater and occurred earlier in life among Palestinian Arabs than Ashkenazi Jews.ConclusionsOur study suggests that premature DNA methylation aging is associated with increased risk of T2D. These findings should stimulate the search for more such sites and may pave the way to improved T2D risk prediction within and between human populations.