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1.  Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus 
BMC Medical Genomics  2010;3:33.
Background
Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease.
Methods
We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium® HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes.
Results
Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy.
Conclusion
This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy.
doi:10.1186/1755-8794-3-33
PMCID: PMC2924253  PMID: 20687937
2.  Advances in the identification and analysis of allele-specific expression 
Genome Medicine  2009;1(5):56.
Allele-specific expression (ASE) is essential for normal development and many cellular processes but, if impaired, can result in disease. ASE is a feature of organisms with genomes consisting of more than one set of homologous chromosomes. The higher the number of chromosome sets (ploidy) per cell, the higher the potential complexity of ASE. Humans, for instance, are diploid (except germ cells, which are haploid), resulting in multiple possible expression states in time and space for each set of alleles. ASE is invoked and modulated by both genetic and epigenetic changes, affecting the underlying DNA sequence or chromatin of each allele, respectively. Although numerous methods have been developed to assay ASE, they usually require RNA to be available and are dependent upon genetic polymorphisms (such as single nucleotide polymorphisms (SNPs)) to differentiate between allelic transcripts. The rapid convergence to second-generation sequencing as the method of choice to examine genomic, epigenomic and transcriptomic data enables an integrated and more general approach to define and predict ASE, independent of SNPs. This 'Omni-Seq' approach has the potential to advance our understanding of the biology and pathophysiology of ASE-mediated processes by elucidating subtle combinatorial effects, leading to the accurate delineation of sub-phenotypes with consequential benefit for improved insight into disease etiology.
doi:10.1186/gm56
PMCID: PMC2689448  PMID: 19490587

Results 1-2 (2)