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1.  The interplay of DNA methylation over time with Th2 pathway genetic variants on asthma risk and temporal asthma transition 
Clinical Epigenetics  2014;6(1):8.
Genetic effects on asthma of genes in the T-helper 2 (Th2) pathway may interact with epigenetic factors including DNA methylation. We hypothesized that interactions between genetic variants and methylation in genes in this pathway (IL4, IL4R, IL13, GATA3, and STAT6) influence asthma risk, that such influences are age-dependent, and that methylation of some CpG sites changes over time in accordance with asthma transition. We tested these hypotheses in subsamples of girls from a population-based birth cohort established on the Isle of Wight, UK, in 1989.
Logistic regression models were applied to test the interaction effect of DNA methylation and SNP on asthma within each of the five genes. Bootstrapping was used to assess the models identified. From 1,361 models fitted at each age of 10 and 18 years, 8 models, including 4 CpGs and 8 SNPs, showed potential associations with asthma risk. Of the 4 CpGs, methylation of cg26937798 (IL4R) and cg23943829 (IL4) changes between ages 10 and 18 (both higher at 10; P = 9.14 × 10−6 and 1.07 × 10−5, respectively).
At age 10, the odds of asthma tended to decrease as cg12405139 (GATA3) methylation increased (log-OR = −12.15; P = 0.049); this effect disappeared by age 18. At age 18, methylation of cg09791102 (IL4R) was associated with higher risk of asthma among subjects with genotype GG compared to AG (P = 0.003), increased cg26937798 methylation among subjects with rs3024685 (IL4R) genotype AA (P = 0.003) or rs8832 (IL4R) genotype GG (P = 0.01) was associated with a lower asthma risk; these CpGs had no effect at age 10. Increasing cg26937798 methylation over time possibly reduced the risk of positive asthma transition (asthma-free at age 10 → asthma at age 18; log-OR = −3.11; P = 0.069) and increased the likelihood of negative transition (asthma at age 10 → asthma-free at age 18; log-OR = 3.97; P = 0.074).
The interaction of DNA methylation and SNPs in Th2 pathway genes is likely to contribute to asthma risk. This effect may vary with age. Methylation of some CpGs changed over time, which may influence asthma transition.
PMCID: PMC4023182  PMID: 24735657
Asthma risk; Asthma transition; DNA methylation and SNP interaction; Th2 pathway
2.  ArrayExpress update—from an archive of functional genomics experiments to the atlas of gene expression 
Nucleic Acids Research  2008;37(Database issue):D868-D872.
ArrayExpress consists of three components: the ArrayExpress Repository—a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse—a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas—a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200 000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently—ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.
PMCID: PMC2686529  PMID: 19015125
3.  MAGETabulator, a suite of tools to support the microarray data format MAGE-TAB 
Bioinformatics  2008;25(2):279-280.
Summary: The MAGE-TAB format for microarray data representation and exchange has been proposed by the microarray community to replace the more complex MAGE-ML format. We present a suite of tools to support MAGE-TAB generation and validation, conversion between existing formats for data exchange, visualization of the experiment designs encoded by MAGE-TAB documents and the mining of such documents for semantic content.
Availability: Software is available from
PMCID: PMC2638998  PMID: 19038988
4.  Genome-wide DNA methylation analysis of patients with imprinting disorders identifies differentially methylated regions associated with novel candidate imprinted genes 
Journal of Medical Genetics  2014;51(4):229-238.
Genomic imprinting is allelic restriction of gene expression potential depending on parent of origin, maintained by epigenetic mechanisms including parent of origin-specific DNA methylation. Among approximately 70 known imprinted genes are some causing disorders affecting growth, metabolism and cancer predisposition. Some imprinting disorder patients have hypomethylation of several imprinted loci (HIL) throughout the genome and may have atypically severe clinical features. Here we used array analysis in HIL patients to define patterns of aberrant methylation throughout the genome.
We developed a novel informatic pipeline capable of small sample number analysis, and profiled 10 HIL patients with two clinical presentations (Beckwith–Wiedemann syndrome and neonatal diabetes) using the Illumina Infinium Human Methylation450 BeadChip array to identify candidate imprinted regions. We used robust statistical criteria to quantify DNA methylation.
We detected hypomethylation at known imprinted loci, and 25 further candidate imprinted regions (nine shared between patient groups) including one in the Down syndrome critical region (WRB) and another previously associated with bipolar disorder (PPIEL). Targeted analysis of three candidate regions (NHP2L1, WRB and PPIEL) showed allelic expression, methylation patterns consistent with allelic maternal methylation and frequent hypomethylation among an additional cohort of HIL patients, including six with Silver–Russell syndrome presentations and one with pseudohypoparathyroidism 1B.
This study identified novel candidate imprinted genes, revealed remarkable epigenetic convergence among clinically divergent patients, and highlights the potential of epigenomic profiling to expand our understanding of the normal methylome and its disruption in human disease.
PMCID: PMC3963529  PMID: 24501229
Epigenetics; Genome-wide; Imprinting

Results 1-4 (4)