Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus

BackgroundDiabetic 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.MethodsWe 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.ResultsSingular 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.ConclusionThis 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.

[1]  A. Perna,et al.  Epigenetics in hyperhomocysteinemic states. A special focus on uremia. , 2009, Biochimica et biophysica acta.

[2]  Jian-Bing Fan,et al.  GoldenGate assay for DNA methylation profiling. , 2009, Methods in molecular biology.

[3]  A. Bird,et al.  Non-CpG methylation is prevalent in embryonic stem cells and may be mediated by DNA methyltransferase 3a. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[4]  G. V. Ommen,et al.  Medical genomics , 2001, European Journal of Human Genetics.

[5]  A. Feinberg,et al.  Genome-wide methylation analysis of human colon cancer reveals similar hypo- and hypermethylation at conserved tissue-specific CpG island shores , 2008, Nature Genetics.

[6]  K. Nakao,et al.  Altered Gene Expression Related to Glomerulogenesis and Podocyte Structure in Early Diabetic Nephropathy of db/db Mice and Its Restoration by Pioglitazone , 2006, Diabetes.

[7]  A. Krolewski,et al.  Familial factors determine the development of diabetic nephropathy in patients with IDDM , 1996, Diabetologia.

[8]  A. Teschendorff,et al.  An Epigenetic Signature in Peripheral Blood Predicts Active Ovarian Cancer , 2009, PloS one.

[9]  A. Paterson,et al.  Multiple Superoxide Dismutase 1/Splicing Factor Serine Alanine 15 Variants Are Associated With the Development and Progression of Diabetic Nephropathy , 2008, Diabetes.

[10]  S. Heath,et al.  G/T Substitution in Intron 1 of the UNC13B Gene Is Associated With Increased Risk of Nephropathy in Patients With Type 1 Diabetes , 2008, Diabetes.

[11]  S. Satchell,et al.  Diabetic nephropathy. , 2012, Clinical medicine.

[12]  Stephen S. Rich,et al.  Confirmation of Genetic Associations at ELMO1 in the GoKinD Collection Supports Its Role as a Susceptibility Gene in Diabetic Nephropathy , 2009, Diabetes.

[13]  E. Richards Inherited epigenetic variation — revisiting soft inheritance , 2006, Nature Reviews Genetics.

[14]  Tetsuhiro Tanaka,et al.  High glucose blunts vascular endothelial growth factor response to hypoxia via the oxidative stress-regulated hypoxia-inducible factor/hypoxia-responsible element pathway. , 2006, Journal of the American Society of Nephrology : JASN.

[15]  Jean YH Yang,et al.  Bioconductor: open software development for computational biology and bioinformatics , 2004, Genome Biology.

[16]  J. Tuomilehto,et al.  Association of genetic variants at 3q22 with nephropathy in patients with type 1 diabetes mellitus. , 2009, American journal of human genetics.

[17]  Stephen S. Rich,et al.  Genome-Wide Association Scan for Diabetic Nephropathy Susceptibility Genes in Type 1 Diabetes , 2009, Diabetes.

[18]  John D. Storey,et al.  Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[19]  J. Franklin,et al.  The elements of statistical learning: data mining, inference and prediction , 2005 .

[20]  E. Seaquist,et al.  Familial clustering of diabetic kidney disease. Evidence for genetic susceptibility to diabetic nephropathy. , 1989, The New England journal of medicine.

[21]  G. Lund,et al.  Atherosclerosis risk factors can impose aberrant DNA methylation patterns: a tale of traffic and homocysteine. , 2009, Current opinion in lipidology.

[22]  K. Eguchi,et al.  Recent Advancement of Understanding Pathogenesis of Type 1 Diabetes and Potential Relevance to Diabetic Nephropathy , 2007, American Journal of Nephrology.

[23]  Kari Stefansson,et al.  A common variant on chromosome 9p21 affects the risk of myocardial infarction. , 2007, Science.

[24]  Rinku Sutradhar,et al.  Multiple SOD1/SFRS15 variants are associated with the development and progression of diabetic nephropathy: The DCCT/EDIC Genetics study , 2007 .

[25]  U. Sauer,et al.  AP-1 proteins mediate hyperglycemia-induced activation of the human TGF-beta1 promoter in mesangial cells. , 2000, Journal of the American Society of Nephrology : JASN.

[26]  J. Rogers,et al.  DNA methylation profiling of human chromosomes 6, 20 and 22 , 2006, Nature Genetics.

[27]  D. Brutlag,et al.  A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[28]  R. Durbin,et al.  A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis , 2008, Nature Biotechnology.

[29]  T. Hudson,et al.  A genome-wide association study identifies novel risk loci for type 2 diabetes , 2007, Nature.

[30]  D. Moczulski,et al.  High-Density Single Nucleotide Polymorphism Genome-Wide Linkage Scan for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes , 2008, Diabetes.

[31]  J. Navarro-González,et al.  The role of inflammatory cytokines in diabetic nephropathy. , 2008, Journal of the American Society of Nephrology : JASN.

[32]  F. Chisena Diabetes and the kidney. , 1948, Medical times.

[33]  John D. Storey,et al.  Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis , 2007, PLoS genetics.

[34]  A. Bird,et al.  DNA methylation landscapes: provocative insights from epigenomics , 2008, Nature Reviews Genetics.

[35]  C. Langefeld,et al.  Variants in Intron 13 of the ELMO1 Gene are Associated with Diabetic Nephropathy in African Americans , 2009, Annals of human genetics.

[36]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[37]  N. Goldenberg,et al.  Rab34 and its effector munc13-2 constitute a new pathway modulating protein secretion in the cellular response to hyperglycemia. , 2009, American journal of physiology. Cell physiology.

[38]  G. David Poznik,et al.  High-density SNP genome wide linkage scan for susceptibility genes for diabetic nephropathy in type 1 diabetes: Discordant sib-pair approach. , 2008 .

[39]  K. Gunderson,et al.  Genome-wide DNA methylation profiling using Infinium® assay. , 2009, Epigenomics.

[40]  M. Turunen,et al.  Epigenetics and atherosclerosis. , 2009, Biochimica et biophysica acta.

[41]  T. Ekström,et al.  The epigenetic conductor: a genomic orchestrator in chronic kidney disease complications? , 2009, Journal of nephrology.

[42]  P. Casanello,et al.  Epigenetics: new concepts of old phenomena in vascular physiology. , 2009, Current vascular pharmacology.

[43]  Lee E. Edsall,et al.  Human DNA methylomes at base resolution show widespread epigenomic differences , 2009, Nature.

[44]  Stephan Beck,et al.  The methylome: approaches for global DNA methylation profiling. , 2008, Trends in genetics : TIG.

[45]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[46]  A. Buja,et al.  Remarks on Parallel Analysis. , 1992, Multivariate behavioral research.