Validation of DNA methylation profiling in formalin-fixed paraffin-embedded samples using the Infinium HumanMethylation450 Microarray

A formalin-fixed paraffin-embedded (FFPE) sample usually yields highly degraded DNA, which limits the use of techniques requiring high-quality DNA, such as Infinium Methylation microarrays. To overcome this restriction, we have applied an FFPE restoration procedure consisting of DNA repair and ligation processes in a set of paired fresh-frozen (FF) and FFPE samples. We validated the FFPE results in comparison with matched FF samples, enabling us to use FFPE samples on the Infinium HumanMethylation450 Methylation array.     

Validation of DNA methylation profiling in formalin-fixed paraffin-embedded samples using the Infinium HumanMethylation450 Microarray

A formalin-fixed paraffin-embedded (FFPE) sample usually yields highly degraded DNA, which limits the use of techniques requiring high-quality DNA, such as Infinium Methylation microarrays. To overcome this restriction, we have applied an FFPE restoration procedure consisting of DNA repair and ligation processes in a set of paired fresh-frozen (FF) and FFPE samples. We validated the FFPE results in comparison with matched FF samples, enabling us to use FFPE samples on the Infinium HumanMethylation450 Methylation array.     

Genome-wide methylation profiling identifies hypermethylated biomarkers in high-grade cervical intraepithelial neoplasia

Epigenetic modifications, such as aberrant DNA promoter methylation, are frequently observed in cervical cancer. Identification of hypermethylated regions allowing discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3), or worse, may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions was studied using genome-wide DNA methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methylated DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium. Hypermethylated differentially methylated regions (DMRs) were identified. Validation of nine selected DMRs using BSP and MSP in cervical tissue revealed methylation in 63.2–94.7% high-grade CIN and in 59.3–100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was conducted exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples. Clinical validation of both markers in cervical scrapings from patients with an abnormal cervical smear confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion and that ROC analysis was discriminative. These markers represent the COL25A1 and KATNAL2 and their observed increased methylation upon progression could intimate the regulatory role in carcinogenesis. In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and are candidate biomarkers for early detection.     

Genome-wide DNA methylation profiling in rheumatoid arthritis identifies disease-associated methylation changes that are distinct to individual T- and B-lymphocyte populations

Changes to the DNA methylome have been described in patients with rheumatoid arthritis (RA). In previous work, we reported genome-wide methylation differences in T-lymphocyte and B-lymphocyte populations from healthy individuals. Now, using HumanMethylation450 BeadChips to interrogate genome-wide DNA methylation, we have determined disease-associated methylation changes in blood-derived T- and B-lymphocyte populations from 12 female patients with seropositive established RA, relative to 12 matched healthy individuals. Array data were analyzed using NIMBL software and bisulfite pyrosequencing was used to validate array candidates. Genome-wide DNA methylation, determined by analysis of LINE-1 sequences, revealed higher methylation in B-lymphocytes compared with T-lymphocytes (P ≤ 0.01), which is consistent with our findings in healthy individuals. Moreover, loci-specific methylation differences that distinguished T-lymphocytes from B-lymphocytes in healthy individuals were also apparent in RA patients. However, disease-associated methylation differences were also identified in RA. In these cases, we identified 509 and 252 CpGs in RA-derived T- and B-lymphocytes, respectively, that showed significant changes in methylation compared with their cognate healthy counterparts. Moreover, this included a restricted set of 32 CpGs in T-lymphocytes and 20 CpGs in B-lymphocytes (representing 15 and 10 genes, respectively, and including two, MGMT and CCS, that were common to both cell types) that displayed more substantial changes in methylation. These changes, apparent as hyper- or hypo-methylation, were independently confirmed by pyrosequencing analysis. Validation by pyrosequencing also revealed additional sites in some candidate genes that also displayed altered methylation in RA. In this first study of genome-wide DNA methylation in individual T- and B-lymphocyte populations in RA patients, we report disease-associated methylation changes that are distinct to each cell type and which support a role for discrete epigenetic regulation in this disease.     

Genome-wide DNA methylation profiling in rheumatoid arthritis identifies disease-associated methylation changes that are distinct to individual T- and B-lymphocyte populations

Changes to the DNA methylome have been described in patients with rheumatoid arthritis (RA). In previous work, we reported genome-wide methylation differences in T-lymphocyte and B-lymphocyte populations from healthy individuals. Now, using HumanMethylation450 BeadChips to interrogate genome-wide DNA methylation, we have determined disease-associated methylation changes in blood-derived T- and B-lymphocyte populations from 12 female patients with seropositive established RA, relative to 12 matched healthy individuals. Array data were analyzed using NIMBL software and bisulfite pyrosequencing was used to validate array candidates. Genome-wide DNA methylation, determined by analysis of LINE-1 sequences, revealed higher methylation in B-lymphocytes compared with T-lymphocytes (P ≤ 0.01), which is consistent with our findings in healthy individuals. Moreover, loci-specific methylation differences that distinguished T-lymphocytes from B-lymphocytes in healthy individuals were also apparent in RA patients. However, disease-associated methylation differences were also identified in RA. In these cases, we identified 509 and 252 CpGs in RA-derived T- and B-lymphocytes, respectively, that showed significant changes in methylation compared with their cognate healthy counterparts. Moreover, this included a restricted set of 32 CpGs in T-lymphocytes and 20 CpGs in B-lymphocytes (representing 15 and 10 genes, respectively, and including two, MGMT and CCS, that were common to both cell types) that displayed more substantial changes in methylation. These changes, apparent as hyper- or hypo-methylation, were independently confirmed by pyrosequencing analysis. Validation by pyrosequencing also revealed additional sites in some candidate genes that also displayed altered methylation in RA. In this first study of genome-wide DNA methylation in individual T- and B-lymphocyte populations in RA patients, we report disease-associated methylation changes that are distinct to each cell type and which support a role for discrete epigenetic regulation in this disease.     

Epigenome-wide profiling identifies significant differences in DNA methylation between matched-pairs of T- and B-lymphocytes from healthy individuals

Multiple reports now describe changes to the DNA methylome in rheumatoid arthritis and in many cases have analyzed methylation in mixed cell populations from whole blood. However, these approaches may preclude the identification of cell type-specific methylation, which may subsequently bias identification of disease-specific changes. To address this possibility, we conducted genome-wide DNA methylation profiling using HumanMethylation450 BeadChips to identify differences within matched pairs of T-lymphocytes and B-lymphocytes isolated from the peripheral blood of 10 healthy females. Array data were processed and differential methylation identified using NIMBL software. Validation of array data was performed by bisulfite pyrosequencing. Genome-wide DNA methylation was initially determined by analysis of LINE-1 sequences and was higher in B-lymphocytes than matched T-lymphocytes (69.8% vs. 65.2%, P ≤ 0.01). Pairwise analysis identified 679 CpGs, representing 250 genes, which were differentially methylated between T-lymphocytes and B-lymphocytes. The majority of sites (76.6%) were hypermethylated in B-lymphocytes. Pyrosequencing of selected candidates confirmed the array data in all cases. Hierarchical clustering revealed perfect segregation of samples into two distinct clusters based on cell type. Differentially methylated genes showed enrichment for biological functions/pathways associated with leukocytes and T-lymphocytes. Our work for the first time shows that T-lymphocytes and B-lymphocytes possess intrinsic differences in DNA methylation within a restricted set of functionally related genes. These data provide a foundation for investigating DNA methylation in diseases in which these cell types play important and distinct roles.     

Genome-wide DNA methylation analysis identifies a metabolic memory profile in patient-derived diabetic foot ulcer fibroblasts

Diabetic foot ulcers (DFUs) are a serious complication of diabetes. Previous exposure to hyperglycemic conditions accelerates a decline in cellular function through metabolic memory despite normalization of glycemic control. Persistent, hyperglycemia-induced epigenetic patterns are considered a central mechanism that activates metabolic memory; however, this has not been investigated in patient-derived fibroblasts from DFUs. We generated a cohort of patient-derived lines from DFU fibroblasts (DFUF), and site- and age-matched diabetic foot fibroblasts (DFF) and non-diabetic foot fibroblasts (NFF) to investigate global and genome-wide DNA methylation patterns using liquid chromatography/mass spectrometry and the Illumina Infinium HumanMethylation450K array. DFFs and DFUFs demonstrated significantly lower global DNA methylation compared to NFFs (p = 0.03). Hierarchical clustering of differentially methylated probes (DMPs, p = 0.05) showed that DFFs and DFUFs cluster together and separately from NFFs. Twenty-five percent of the same probes were identified as DMPs when individually comparing DFF and DFUF to NFF. Functional annotation identified enrichment of DMPs associated with genes critical to wound repair, including angiogenesis (p = 0.07) and extracellular matrix assembly (p = 0.035). Identification of sustained DNA methylation patterns in patient-derived fibroblasts after prolonged passage in normoglycemic conditions demonstrates persistent metabolic memory. These findings suggest that epigenetic-related metabolic memory may also underlie differences in wound healing phenotypes and can potentially identify therapeutic targets.     

Plasma total homocysteine is associated with DNA methylation in patients with schizophrenia

Schizophrenia (SCZ) is a devastating psychiatric disorder with a median lifetime prevalence rate of 0.7–0.8%. Elevated plasma total homocysteine has been suggested as a risk factor for SCZ, and various biological effects of hyperhomocysteinemia have been proposed to be relevant to the pathophysiology of SCZ. As increased attention is paid to aberrant DNA methylation in SCZ, homocysteine is attracting additional interest as a potential key substance. Homocysteine is formed in the methionine cycle, which is involved in one-carbon methyl group-transfer metabolism, and it acts as a methyl donor when it is converted to S-adenosyl-methionine. To date, no studies have examined the relationship between homocysteine and genome-wide DNA methylation in SCZ. We examined the relationship between plasma total homocysteine and DNA methylation patterns in the peripheral leukocytes of patients with SCZ (n = 42) using a quantitative high-resolution DNA methylation array (485,764 CpG sites). Significant homocysteine-related changes in DNA methylation were observed at 1,338 CpG sites that were located across whole gene regions, including promoters, gene bodies and 3′-untranslated regions. Of the 1,338 sites, 758 sites (56.6%) were located in the CpG islands (CGIs) and in the regions flanking CGIs (CGI: 15.8%; CGI shore: 28.2%; CGI shelf: 12.6%), and positive correlations between plasma total homocysteine and DNA methylation were observed predominantly at CpG sites in the CGIs. Our results suggest that homocysteine might play a role in the pathogenesis of SCZ via a molecular mechanism that involves alterations to DNA methylation.     

Genome-wide DNA methylation profiling of recurrent and non-recurrent chordomas

Chordomas are an aggressive rare type of malignant bone tumors arising from the remnant of the notochord. Chordomas occur mainly in vertebral bones and account for 1–4% of malignant bone tumors. Management and treatment of chordomas are difficult as they are resistant to conventional chemotherapy; therefore, they are mainly treated with surgery and radiation therapy. In this study, we performed DNA methylation profiling of 26 chordomas and normal nucleus pulposus samples plus UCH-1 chordoma cell line using the Illumina Infinium HumanMethylation450 BeadChips. Combined bisulfite restriction analysis and bisulfite sequencing was used to confirm the methylation data. Gene expression was analyzed using RT-PCR before and after 5-aza-2’-deoxycytidine (5-azaDC) treatment of chordoma cell lines. Analysis of the HumanMethylation450 BeadChip data led to the identification of 8,819 loci (2.9%) that were significantly differentially methylated (>0.2 average β-value difference) between chordomas and nucleus pulposus samples (adjusted P < 0.05). Among these, 5,868 probes (66.5%) were hypomethylated, compared to 2,951 (33.5%) loci that were hypermethylated in chordomas compared to controls. From the 2,951 differentially hypermethylated probes, 33.3% were localized in the promoter region (982 probes) and, among these, 104 probes showed cancer-specific hypermethylation. Ingenuity Pathway Analysis indicates that the cancer-specific differentially methylated loci are involved in various networks including cancer disease, nervous system development and function, cell death and survival, cellular growth, cellular development, and proliferation. Furthermore, we identified a subset of probes that were differentially methylated between recurrent and non-recurrent chordomas. BeadChip methylation data was confirmed for these genes and gene expression was shown to be upregulated in methylated chordoma cell lines after treatment with 5-azaDC. Understanding epigenetic changes in chordomas may provide insights into chordoma tumorigenesis and development of epigenetic biomarkers.     

An evaluation of analysis pipelines for DNA methylation profiling using the Illumina HumanMethylation450 BeadChip platform

The proper identification of differentially methylated CpGs is central in most epigenetic studies. The Illumina HumanMethylation450 BeadChip is widely used to quantify DNA methylation; nevertheless, the design of an appropriate analysis pipeline faces severe challenges due to the convolution of biological and technical variability and the presence of a signal bias between Infinium I and II probe design types. Despite recent attempts to investigate how to analyze DNA methylation data with such an array design, it has not been possible to perform a comprehensive comparison between different bioinformatics pipelines due to the lack of appropriate data sets having both large sample size and sufficient number of technical replicates. Here we perform such a comparative analysis, targeting the problems of reducing the technical variability, eliminating the probe design bias and reducing the batch effect by exploiting two unpublished data sets, which included technical replicates and were profiled for DNA methylation either on peripheral blood, monocytes or muscle biopsies. We evaluated the performance of different analysis pipelines and demonstrated that: (1) it is critical to correct for the probe design type, since the amplitude of the measured methylation change depends on the underlying chemistry; (2) the effect of different normalization schemes is mixed, and the most effective method in our hands were quantile normalization and Beta Mixture Quantile dilation (BMIQ); (3) it is beneficial to correct for batch effects. In conclusion, our comparative analysis using a comprehensive data set suggests an efficient pipeline for proper identification of differentially methylated CpGs using the Illumina 450K arrays.     

Genome-wide differentially methylated genes in prostate cancer tissues from African-American and Caucasian men

Increasing evidence suggests that aberrant DNA methylation changes may contribute to prostate cancer (PCa) ethnic disparity. To comprehensively identify DNA methylation alterations in PCa disparity, we used the Illumina 450K methylation platform to interrogate the methylation status of 485,577 CpG sites focusing on gene-associated regions of the human genome. Genomic DNA from African-American (AA; 7 normal and 3 cancers) and Caucasian (Cau; 8 normal and 3 cancers) was used in the analysis. Hierarchical clustering analysis identified probe-sets unique to AA and Cau samples, as well as common to both. We selected 25 promoter-associated novel CpG sites most differentially methylated by race (fold change > 1.5-fold; adjusted P < 0.05) and compared the β-value of these sites provided by the Illumina, Inc. array with quantitative methylation obtained by pyrosequencing in 7 prostate cell lines. We found very good concordance of the methylation levels between β-value and pyrosequencing. Gene expression analysis using qRT-PCR in a subset of 8 genes after treatment with 5-aza-2′-deoxycytidine and/or trichostatin showed up-regulation of gene expression in PCa cells. Quantitative analysis of 4 genes, SNRPN, SHANK2, MST1R, and ABCG5, in matched normal and PCa tissues derived from AA and Cau PCa patients demonstrated differential promoter methylation and concomitant differences in mRNA expression in prostate tissues from AA vs. Cau. Regression analysis in normal and PCa tissues as a function of race showed significantly higher methylation prevalence for SNRPN (P = 0.012), MST1R (P = 0.038), and ABCG5 (P < 0.0002) for AA vs. Cau samples. We selected the ABCG5 and SNRPN genes and verified their biological functions by Western blot analysis and siRNA gene knockout effects on cell proliferation and invasion in 4 PCa cell lines (2 AA and 2 Cau patients-derived lines). Knockdown of either ABCG5 or SNRPN resulted in a significant decrease in both invasion and proliferation in Cau PCa cell lines but we did not observe these remarkable loss-of-function effects in AA PCa cell lines. Our study demonstrates how differential genome-wide DNA methylation levels influence gene expression and biological functions in AA and Cau PCa.