The epigenetic signature of systemic insulin resistance in obese women

Aims/hypothesis Insulin resistance (IR) links obesity to type 2 diabetes. The aim of this study was to explore whether white adipose tissue (WAT) epigenetic dysregulation is associated with systemic IR by genome-wide CG dinucleotide (CpG) methylation and gene expression profiling in WAT from insulin-resistant and insulin-sensitive women. A secondary aim was to determine whether the DNA methylation signature in peripheral blood mononuclear cells (PBMCs) reflects WAT methylation and, if so, can be used as a marker for systemic IR. Methods From 220 obese women, we selected a total of 80 individuals from either of the extreme ends of the distribution curve of HOMA-IR, an indirect measure of systemic insulin sensitivity. Genome-wide transcriptome and DNA CpG methylation profiling by array was performed on subcutaneous (SAT) and visceral (omental) adipose tissue (VAT). CpG methylation in PBMCs was assayed in the same cohort. Results There were 647 differentially expressed genes (false discovery rate [FDR] 10%) in SAT, all of which displayed directionally consistent associations in VAT. This suggests that IR is associated with dysregulated expression of a common set of genes in SAT and VAT. The average degree of DNA methylation did not differ between the insulin-resistant and insulin-sensitive group in any of the analysed tissues/cells. There were 223 IR-associated genes in SAT containing a total of 336 nominally significant differentially methylated sites (DMS). The 223 IR-associated genes were over-represented in pathways related to integrin cell surface interactions and insulin signalling and included COL5A1, GAB1, IRS2, PFKFB3 and PTPRJ. In VAT there were a total of 51 differentially expressed genes (FDR 10%); 18 IR-associated genes contained a total of 29 DMS. Conclusions/interpretation In individuals discordant for insulin sensitivity, the average DNA CpG methylation in SAT and VAT is similar, although specific genes, particularly in SAT, display significantly altered expression and DMS in IR, possibly indicating that epigenetic regulation of these genes influences metabolism. Electronic supplementary material The online version of this article (doi:10.1007/s00125-016-4074-5) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Qubit (Life technologies, Stockholm, Sweden). One SAT and one VAT sample were excluded due to insufficient DNA quality.
DNA extracted from SAT and VAT pieces, as well as in PBMCs, was assayed using the Infinium Human Methylation 450 (450K) BeadChips as described (Illumina, San Diego, CA, USA) [2]. Genomic DNA (500 ng) was bisulfite treated using the EZ DNA methylation kit (Zymo Research, Orange, CA, USA) with the alternative incubation conditions recommended when using the Infinium Methylation Assay. The methylation assay was performed on 4 μl bisulfite-converted genomic DNA (50 ng/μl) according to the Infinium HD Methylation Assay protocol (Part #15019519, Illumina). There were no replicates in the microarray experiment.
Group assignment was blinded during the above experiments.
BeadChip images were analyzed as described captured using the Illumina iScan. The raw methylation score for each probe represented as a methylation beta-value was calculated using the GenomeStudio Methylation module software (2010.3) [3]. All included samples showed high quality bisulfite conversion according to Zymo-control samples and also passed all GenomeStudio quality control steps based on built in control probes for staining, hybridization, extension and specificity. We used the Bioconductor Lumi package to perform color and quantitative normalization of the DNA methylation data [4]. The BMIQ package was used to adjust the beta-values of type 2 design microarray probes into a statistical distribution characteristic of type 1 probes [5]. For differential methylation analysis, beta-values were converted to M-values [M = log2(beta/(1-beta))], which have a more appropriate distribution for statistical tests of comparisons between groups. As beta-values are easier to interpret biologically, beta-values are retained when describing the results. Adjustment for array plate and bisulfite treatment batch was performed using ComBat [6].
The Infinium Human Methylation 450 BeadChip array contains 485,577 probes, which covers 21,231 RefSeq genes. Before analysis of differentially methylated sites (DMS) a number of filtering steps were performed. Probes containing common SNPs with minor allele frequency (MAF) >10% or with SNPs within 10 basepairs from the interrogated CpG sites according to Illumina file "humanmethylation450_dbsnp137.snpupdate.table.v2.sorted" were excluded leaving 319,569 probes for subsequent analysis. Next, non-specific probes, i.e. hybridizing to >2 sites, were excluded leaving 302,822 probes for the next step [7]. In analysis of DMS we further excluded probes not annotated to a gene according to Illumina leaving 236,147 probes. Finally, in each tissue separately we filtered to include only the probes that passed the threshold variance 0.1 in beta-value (Qlucore, www.qlucore.com); thus, 112,057 (SAT), 124,089 (VAT) and 99,462 (PBMCs) probes, respectively, were taken forward to identify DMS.

Validation experiments
Quantitative methylation analysis was performed using the EpiTYPER methodology [8] and the PCR primers for amplicons encompassing the 450K cg:s of interest were designed using EpiDesigner (Agena Biosciences) and checked for bisulfitome specificity by using BiSearch in silico PCR (http://bisearch.enzim.hu/?m=genompsearch). A 4-point dilution curve (0% methylated, 25% methylated, 50% methylated and 100% methylated) of EpiTect methylated and non-methylated bisulfite treated control DNA (Qiagen) was used to evaluate the quantitative recapture of methylation ratios of the amplicons. The 4-point dilution curve was run in triplicate and also provided data for standard deviation analysis. The amplicons used in this study all met the quality criteria of fully methylated and non-methylated data points measured at > 75% and < 20% methylation ratios, respectively, as well as standard deviation percentages < 10%. Samples were run in duplicate and standard deviation percentages >20% were removed from the study.
The remaining data points correlated with R 2 0.99. Bisulfite conversion efficiency in all samples was evaluated by analyzing 13 non-CpG C:s spread out in the amplicons analyzed in the study.
All data was checked by manually and visually inspecting the mass spectra. Group assignment was blinded during the above experiments.  a. We calculated correlation between expression of 647 differentially expressed genes and 10,746 DMS in SAT between IR and IS women. b. We calculated correlation between expression of 51 differentially expressed genes and 10,217 DMS in VAT between IR and IS women. c. Shown are Spearman correlation coefficient <-0.1 (CpG-sites in TSS1500, TSS200 or 5'UTR) or >0.1 (CpG-sites in gene body or 3'UTR).