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Genome-wide methylation analysis identifies differentially methylated CpG loci associated with severe obesity in childhood.

ABSTRACT: Childhood obesity is a major public health issue. Here we investigated whether differential DNA methylation was associated with childhood obesity. We studied DNA methylation profiles in whole blood from 78 obese children (mean BMI Z-score: 2.6) and 71 age- and sex-matched controls (mean BMI Z-score: 0.1). DNA samples from obese and control groups were pooled and analyzed using the Infinium HumanMethylation450 BeadChip array. Comparison of the methylation profiles between obese and control subjects revealed 129 differentially methylated CpG (DMCpG) loci associated with 80 unique genes that had a greater than 10% difference in methylation (P-value < 0.05). The top pathways enriched among the DMCpGs included developmental processes, immune system regulation, regulation of cell signaling, and small GTPase-mediated signal transduction. The associations between the methylation of selected DMCpGs with childhood obesity were validated using sodium bisulfite pyrosequencing across loci within the FYN, PIWIL4, and TAOK3 genes in individual subjects. Three CpG loci within FYN were hypermethylated in obese individuals (all P < 0.01), while obesity was associated with lower methylation of CpG loci within PIWIL4 (P = 0.003) and TAOK3 (P = 0.001). After building logistic regression models, we determined that a 1% increase in methylation in TAOK3, multiplicatively decreased the odds of being obese by 0.91 (95% CI: 0.86 - 0.97), and an increase of 1% methylation in FYN CpG3, multiplicatively increased the odds of being obese by 1.03 (95% CI: 0.99 - 1.07). In conclusion, these findings provide evidence that childhood obesity is associated with specific DNA methylation changes in whole blood, which may have utility as biomarkers of obesity risk.

SUBMITTER: Huang RC

PROVIDER: S-EPMC4844195 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Genome-wide methylation analysis identifies differentially methylated CpG loci associated with severe obesity in childhood.

Huang R C RC Garratt E S ES Pan H H Wu Y Y Davis E A EA Barton S J SJ Burdge G C GC Godfrey K M KM Holbrook J D JD Lillycrop K A KA

Epigenetics 20150101 11

Childhood obesity is a major public health issue. Here we investigated whether differential DNA methylation was associated with childhood obesity. We studied DNA methylation profiles in whole blood from 78 obese children (mean BMI Z-score: 2.6) and 71 age- and sex-matched controls (mean BMI Z-score: 0.1). DNA samples from obese and control groups were pooled and analyzed using the Infinium HumanMethylation450 BeadChip array. Comparison of the methylation profiles between obese and control subjec ...[more]

PMID: 26646899

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Project description:BACKGROUND:Environmental and endogenous factors under genetic predisposition are considered to initiate the human intervertebral disc (IVD) degeneration. DNA methylation is an essential mechanism to ensure cell-specific gene expression for normal development and tissue stability. Aberrant epigenetic alterations play a pivotal role in several diseases, including osteoarthritis. However, epigenetic alternations, including DNA methylation, in IVD degeneration have not been evaluated. The purpose of this study was to comprehensively compare the genome-wide DNA methylation profiles of human IVD tissues, specifically nucleus pulpous (NP) tissues, with early and advanced stages of disc degeneration. METHODS:Human NP tissues were used in this study. The samples were divided into two groups: early stage degeneration (n = 8, Pfirrmann's MRI grade: I-III) and advanced stage degeneration (n = 8, grade: IV). Genomic DNA was processed for genome-wide DNA methylation profiling using the Infinium MethylationEPIC BeadChip array. Extraction of raw methylation data, clustering and scatter plot of each group values of each sample were performed using a methylation module in GenomeStudio software. The identification of differentially methylated loci (DMLs) and the Gene Ontology (GO) analysis were performed using R software with the ChAMP package. RESULTS:Unsupervised hierarchical clustering revealed that early and advanced stage degenerated IVD samples segregated into two main clusters by their DNA methylome. A total of 220 DMLs were identified between early and advanced disc degeneration stages. Among these, four loci were hypomethylated and 216 loci were hypermethylated in the advanced disc degeneration stage. The GO enrichment analysis of genes containing DMLs identified two significant GO terms for biological processes, hemophilic cell adhesion and cell-cell adhesion. CONCLUSIONS:We conducted a genome-wide DNA methylation profile comparative study and observed significant differences in DNA methylation profiles between early and advanced stages of human IVD degeneration. These results implicate DNA methylation in the process of human IVD degeneration.

Project description:BackgroundHypermethylation of promoter CpG islands is strongly correlated to transcriptional gene silencing and epigenetic maintenance of the silenced state. As well as its role in tumor development, CpG island methylation contributes to the acquisition of resistance to chemotherapy. Differential Methylation Hybridisation (DMH) is one technique used for genome-wide DNA methylation analysis. The study of such microarray data sets should ideally account for the specific biological features of DNA methylation and the non-symmetrical distribution of the ratios of unmethylated and methylated sequences hybridised on the array. We have therefore developed a novel algorithm tailored to this type of data, Methylation Linear Discriminant Analysis (MLDA).ResultsMLDA was programmed in R (version 2.7.0) and the package is available at CRAN 1. This approach utilizes linear regression models of non-normalised hybridisation data to define methylation status. Log-transformed signal intensities of unmethylated controls on the microarray are used as a reference. The signal intensities of DNA samples digested with methylation sensitive restriction enzymes and mock digested are then transformed to the likelihood of a locus being methylated using this reference. We tested the ability of MLDA to identify loci differentially methylated as analysed by DMH between cisplatin sensitive and resistant ovarian cancer cell lines. MLDA identified 115 differentially methylated loci and 23 out of 26 of these loci have been independently validated by Methylation Specific PCR and/or bisulphite pyrosequencing.ConclusionMLDA has advantages for analyzing methylation data from CpG island microarrays, since there is a clear rational for the definition of methylation status, it uses DMH data without between-group normalisation and is less influenced by cross-hybridisation of loci. The MLDA algorithm successfully identified differentially methylated loci between two classes of samples analysed by DMH using CpG island microarrays.

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Genome-wide methylation analysis identifies differentially methylated CpG loci associated with severe obesity in childhood.

Publications

Genome-wide methylation analysis identifies differentially methylated CpG loci associated with severe obesity in childhood.

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