DNA methylation data from Reduced Representation Bisulphite sequencing in the Dutch Hunger Winter Families Study
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Elmar Tobi
PROVIDER: E-GEOD-54983 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:We report on genome-wide DNA methylation differences associated with early gestational famine exposure. We find that open chromatin regions and enhancers are especially sensitive to prenatal famine exposure.
2014-07-01 | GSE54983 | GEO
Project description:The dataset entails 48 RRBS libraries of 24 siblings.
24 individuals are conceived during the Dutch Famine, a severe 6 month famine at the end of World War 2. A same sex sibling was added as a control, allowing partial matching for (early) familial environment and genetics.
| EGAD00001000733 | EGA
Project description:Epigenetic changes may account for the doubled risk to develop schizophrenia in individuals exposed to famine in utero. We therefore investigated DNA methylation in a unique sample of patients and healthy individuals conceived during the great famine in China. Subsequently we examined two case-control samples without famine exposure in whole blood and brain tissue. To shed light on the causality of the relation between famine exposure and DNA methylation we exposed human fibroblasts to nutritional deprivation. In the famine exposed schizophrenia patients we found significant hypermethylation of the dual specificity phosphatase 22 (DUSP22) gene promoter (Chr6:291687-293285) (N=153, p=0.01). In this sample DUSP22 methylation was also significantly higher in patients independent of famine exposure (p=0.025), suggesting that hypermethylation of DUSP22 is also more generally involved in schizophrenia risk. Similarly, DUSP22 methylation was also higher in two separate case-control sample not exposed to famine using DNA from whole blood (N=64, p=0.03) and postmortem brains (N=214, p=0.007). DUSP22 methylation showed strong genetic regulation across chromosomes by a region on chromosome 16 which was consistent with new 3D genome interaction data. The presence of a direct link between famine and DUSP22 transcription was supported by data from cultured human fibroblasts that showed increased methylation (p=0.048) and expression (p=0.019) in response to nutritional deprivation (N=10). These results highlight a first epigenetic locus that is genetically regulated across chromosomes and that is involved in the response to early life exposure to famine and that is relevant for a major psychiatric disorder.
2018-06-29 | GSE116379 | GEO
Project description:Epigenetic changes may account for the doubled risk to develop schizophrenia in individuals exposed to famine in utero. We therefore investigated DNA methylation in a unique sample of patients and healthy individuals conceived during the great famine in China. Subsequently we examined two case-control samples without famine exposure in whole blood and brain tissue. To shed light on the causality of the relation between famine exposure and DNA methylation we exposed human fibroblasts to nutritional deprivation. In the famine exposed schizophrenia patients we found significant hypermethylation of the dual specificity phosphatase 22 (DUSP22) gene promoter (Chr6:291687-293285) (N=153, p=0.01). In this sample DUSP22 methylation was also significantly higher in patients independent of famine exposure (p=0.025), suggesting that hypermethylation of DUSP22 is also more generally involved in schizophrenia risk. Similarly, DUSP22 methylation was also higher in two separate case-control sample not exposed to famine using DNA from whole blood (N=64, p=0.03) and postmortem brains (N=214, p=0.007). DUSP22 methylation showed strong genetic regulation across chromosomes by a region on chromosome 16 which was consistent with new 3D genome interaction data. The presence of a direct link between famine and DUSP22 transcription was supported by data from cultured human fibroblasts that showed increased methylation (p=0.048) and expression (p=0.019) in response to nutritional deprivation (N=10). These results highlight a first epigenetic locus that is genetically regulated across chromosomes and that is involved in the response to early life exposure to famine and that is relevant for a major psychiatric disorder.
2018-06-29 | GSE116378 | GEO
Project description:Although it is assumed that epigenetic mechanisms, such as changes in DNA methylation (DNAm), underlie the relationship between adverse intrauterine conditions and adult metabolic health, evidence from human studies remains scarce. Therefore, we evaluated whether DNAm in whole blood mediated the association between prenatal famine exposure and metabolic health in 422 individuals exposed to famine in utero and 463 (sibling) controls. We implemented a two-step analysis, namely, a genome-wide exploration across 342,596 cytosine-phosphate-guanine dinucleotides (CpGs) for potential mediators of the association between prenatal famine exposure and adult body mass index (BMI), serum triglycerides (TG), or glucose concentrations, which was followed by formal mediation analysis. DNAm mediated the association of prenatal famine exposure with adult BMI and TG but not with glucose. DNAm at PIM3 (cg09349128), a gene involved in energy metabolism, mediated 13.4% [95% confidence interval (CI), 5 to 28%] of the association between famine exposure and BMI. DNAm at six CpGs, including TXNIP (cg19693031), influencing β cell function, and ABCG1 (cg07397296), affecting lipid metabolism, together mediated 80% (95% CI, 38.5 to 100%) of the association between famine exposure and TG. Analyses restricted to those exposed to famine during early gestation identified additional CpGs mediating the relationship with TG near PFKFB3 (glycolysis) and METTL8 (adipogenesis). DNAm at the CpGs involved was associated with gene expression in an external data set and correlated with DNAm levels in fat depots in additional postmortem data. Our data are consistent with the hypothesis that epigenetic mechanisms mediate the influence of transient adverse environmental factors in early life on long-term metabolic health. The specific mechanism awaits elucidation.
2018-01-31 | GSE78743 | GEO
Project description:Differential hyper- and hypo-methylation regions in G0 versus G4/G5 CMP The goal of this study is to evaluate changes in CpG methylation profilings of telomere dysfunctional common myeloid progenitor cells (CMP) as compared to their wild type controls Genomic DNA was extracted from sorted CMP populations isolated from 3 pools of G0 or 2 pools of G5 mice using UltraPure Phenol:Chloroform:Isoamyl Alcohol according to manufacturer’s instructions (Life Technologies). 14,000 to 30,000 cells were available for each sample, resulting in a minimum of 45ng of DNA. Genome-wide DNA methylation profiling was performed by RRBS. Library preparation and sequencing were performed at the UT MD Anderson Cancer Center’s DNA Methylation Analysis Core and Sequencing and Microarray Facility, according to published protocols. RRBS sequencing data were aligned and methylation was called using Bismark v0.7.119. In brief, bisulphite-treated DNA was aligned to UCSC Genome Browser mm10 reference genome using Bowtie. In total 29-38 million reads were generated per sample with alignment rates around 63%. Next, MethylKit10 implemented with Fisher’s exact test was used to compare the cytosine methylation profiles of G0 and G5 CMP. Gene promoter regions were calculated based on RefSeq gene annotations with regions starting 1 kb upstream of the annotated transcription start site (TSS) and extending 500 base pairs downstream of TSS. Exons, introns, and CpG islands coordinates were collected from the UCSC Genome Browser mm10 version.
2015-04-09 | E-GEOD-62392 | biostudies-arrayexpress
Project description:We sequenced mammary tissues of PyMT mice from 4 stages (hyperplasia at week 6, adenoma/MIN at week 8, early carcinoma at week 10, and late carcinoma at week 12) during tumor progression. We also sequenced mammary tissues of age-matched FVB controls.
2018-04-18 | GSE83623 | GEO
Project description:We report AICDA facilitates naïve pluripotency of mouse iPSCs by suppressing FGF/ERK signaling. In the absence of AICDA iPSCs fail to achive naïve pluripotent state and display chracteristics of EpiSCs and are primed for differentiation.
2019-04-03 | GSE129187 | GEO
Project description:The samples were collected from the participants of the Finnish Diabetes Prediction and Prevention (DIPP) Study, born between 1995 and 2006. DIPP is a prospective follow-up cohort of children with a moderate or high risk of type 1 diabetes, based on the HLA-DR-DQ genotype. Islet cell autoantibodies (ICA, GADA, IAA, IA2A and ZnT8A) were measured 1 - 4 times per year until age 15 or year 2018. The aim was to study associations between perinatal DNA methylation marks and later progression to type 1 diabetes. Case individuals who became persistently positive for at least two biochemical autoantibodies (GADA, IAA, IA2A or ZnT8A) and/or were diagnosed with type 1 diabetes during the follow-up were compared to the control individuals who remained autoantibody-negative throughout the follow-up. These data were also used in the development of data analysis methodology in bisulfite sequencing studies. To protect the privacy of the study participants, the sequence read data are not publicly available. However, the processed data can be downloaded here. These include two count matrices: \\"methylated_reads\\" and \\"total_reads\\". The matrix \\"methylated_reads\\" contains methylated read counts at each high-coverage CpG site (altogether approximately 2.5 million rows) at each of the 173 samples (173 columns), and the matrix \\"total_reads\\" contains the corresponding total read counts (coverage). Please notice that the methylated read counts are read counts, not percentages. Methylation proportions can be calculated as methylated_reads/total_reads. The row names are the genomic locations of these CpG sites in hg19 (GRCh37) coordinates (1,2). For privacy reasons, all potential SNPs were excluded from these publicly available count matrices. Specifically, we removed all common (minor allele frequency > 1 %) human SNPs, as listed in dbSNP (3). We also removed all SNPs that were detected in one or more samples even with \\"low\\" evidence by BS-SNPer, which is a software for detecting SNPs from bisulfite sequencing data (4). Altogether 204443 out of 2752981 rows were removed from the original coverage-filtered count matrices that were analyzed in the present study. Description of the sample attributes: Individual: The individual-specific identifiers, such as “Subject1”. Since each sample is from a different individual, these correspond to the sample identifiers (Subject1 == Sample 1 etc.) Experimental Group: The variable of interest (called \\"class\\" in the associated publications) with three possible values: 1) case, 2) control and 3) NA (neither case nor control). 1) Case: became persistently positive for at least two biochemical autoantibodies (GADA, IAA, IA2A or ZnT8A) and/or diagnosed with type 1 diabetes during the follow-up. 2) Control: remained autoantibody-negative throughout the follow-up. 3) NA: The remaining 51 individuals with a missing value (“NA”) did not qualify as cases or controls, since they were either persistently positive for only 1 biochemical autoantibody or transiently positive for one or more autoantibodies. We excluded these 51 individuals from the case-control-comparison but included them in the comparison between the sexes. Library preparation batch: The sequencing libraries were prepared in 7 batches. The names of the batches do not have any special meaning. That is, \\"1A\\" is not necessarily more similar to \\"1B\\" than it is to \\"3B\\". We treated this as a categorical technical variable with 7 categories. PC1 and PC2: Projections of the sample-specific methylation proportion vectors on the first two orthonormal principal components. The principal component analysis (PCA) was performed on the original coverage-filtered methylation proportion matrix (methylated/total reads), where missing values at each CpG site were imputed by the median over samples with non-missing values. The original methylation proportion matrix included 2752981 rows, whereas these publicly available matrices include 2548538 rows (all potential SNPs excluded). Hence, PCA on the publicly available data would result in slightly different values for PC1 and PC2. We included these as covariates in the differential methylation analysis to represent technical variation (in addition to the library preparation batches). References 1. Church DM, Schneider VA, Graves T, Auger K, Cunningham F, Bouk N, et al. Modernizing reference genome assemblies. PLoS Biol. 2011 Jul;9(7):e1001091. 2. Genome Reference Consortium. NCBI downloads: https://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz, accessed Feb 10th, 2019 3. NCBI. dbSNP: https://ftp.ncbi.nih.gov/snp/organisms/human_9606_b151_GRCh37p13/VCF/common_all_20180423.vcf.gz, accessed April 29th, 2021 4. Gao S, Zou D, Mao L, Liu H, Song P, Chen Y, et al. BS-SNPer: SNP calling in bisulfite-seq data. Bioinformatics. 2015 Dec 15;31(24):4006–8.
2022-06-06 | E-MTAB-10530 | biostudies-arrayexpress
Project description:We used a mouse model of paternal famine to simulate famine, our data show that paternal famine increases the susceptibility to metabolic disease in offspring through gametic epigenetic alterations.
2019-06-12 | GSE132521 | GEO