DNA-METHYLATION - Integrative multi-omics survey of effects carbon-based engineered nanomaterials on lung derived cell-lines
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Dario Greco
PROVIDER: E-MTAB-6397 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:In this study we exposed three human lung derived cell lines to sublethal dosages of nanomaterials for a limited amount of time. For the first time, we assessed the simultaneous effects of nanomaterials exposure on three distinct molecular layers along with their interactions in the determination of the MOA of 10 carbon based nanomaterials. By performing an integrative analysis we provide here a complete picture of the interaction between regulatory factors (DNA methylation and miRNAs) and mRNA deregulation subsequent to exposing different cellular systems to different nanomaterials.
2018-05-19 | E-MTAB-6396 | biostudies-arrayexpress
Project description:In this study we exposed three human lung derived cell lines to sublethal dosages of nanomaterials for a limited amount of time. For the first time, we assessed the simultaneous effects of nanomaterials exposure on three distinct molecular layers along with their interactions in the determination of the MOA of 10 carbon based nanomaterials. By performing an integrative analysis we provide here a complete picture of the interaction between regulatory factors (DNA methylation and miRNAs) and mRNA deregulation subsequent to exposing different cellular systems to different nanomaterials.
2018-05-19 | E-MTAB-6406 | biostudies-arrayexpress
Project description:DNA methylation likely plays a role in the regulation of human stress reactivity. In a genome-wide analysis of blood DNA methylation in 85 healthy individuals a locus in the Kit ligand (KITLG) gene (cg27512205) had the strongest association with cortisol stress reactivity (p=5.8x10-6). Replication was obtained in two independent samples, one using blood (N=45, p=0.001) and the other using buccal cells (N=255,p=0.004). KITLG methylation strongly mediated the relationship between childhood trauma and cortisol stress reactivity (32% mediation). Its genomic location (CpG island shore within an H3K27ac enhancer mark) provide further evidence that KITLG methylation is functionally relevant for the programming of stress reactivity. Our results extend preclinical evidence for epigenetic regulation of stress reactivity to humans and provide leads to enhance our understanding of the neurobiological pathways underlying stress vulnerability. Bisulphite converted DNA from whole blood of 85 healthy controls exposed to psychosocial stress task (TSST-G) was hybridised to the Illumina Infinium 450k Human Methylation Beadchip The DOI for this paper will be 10.1038/NCOMMS10967.
2016-03-16 | E-GEOD-77445 | biostudies-arrayexpress
Project description:Background: The mechanisms of how genetic variants (SNPs) identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to epigenetic and chromatin state of the genome to have an important role. Methods: 355 healthy young individuals were genotyped for 52 known obesity-associated SNPs and we obtained DNA methylation levels in their blood using the Illumina 450K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n=62; four brain regions, n=121-133) and an additional dataset in subcutaneous and visceral fat (n=149). Results: We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1,SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not be blood-specific as we successfully replicated four associations in skin fibroblasts. Conclusions: Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated to human diseases and traits. Bisulphite converted DNA from 355 individuals aged 14-34 were hybridised to the Illumina Infinium 450k Human Methylation Beadchip.
2015-09-17 | E-GEOD-73103 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-02-03 | E-GEOD-47592 | biostudies-arrayexpress
Project description:Background & aims: Stroke diagnosis is challenging in the acute phase. We aimed to determine biomarkers for the differentiation of ischemic stroke (IS) from intracerebral hemorrhage (ICH) using SWATH-MS and validate the discovered biomarkers within 24 hours using MRM proteomics. Methods: The study was conducted at Department of Neurology, All India Institute of Medical Sciences, New Delhi, India. Serum samples were collected within 24 hours from acute stroke (IS & ICH) patients & healthy controls. SWATH-MS proteomics identified significantly differentially expressed (SDE) proteins (fold change: 1.5, p<0.05 and confirmed/tentative selection using Boruta random forest) between IS and ICH which were then validated using protein MRM. Cut-off points were determined using Youden Index. Prediction models were developed using forward stepwise multivariate logistic regression analysis. Integrated discrimination improvement index determined the added value of biomarkers to clinical models. Results: Discovery phase included 20 IS, 20 ICH and 40 controls while validation phase included 150 IS and 150 ICH subjects. Total 365 proteins were quantified using SWATH-MS. Between IS and ICH, 20 SDE proteins were identified. Prediction model including clinical variables (sex, hypertension, atrial fibrillation, current smoking, baseline NIHSS) and biomarkers (GFAP, MMP9, APOC1) independently differentiated IS from ICH (accuracy: 92%, sensitivity: 96%, specificity: 69%). Addition of biomarkers improved the discrimination capacity by 26% (p<0.001) compared to clinical variables alone. Conclusion: Our study identified a range of potential protein biomarkers for the differentiation of IS. Protein biomarkers along with clinical predictors might be useful candidates in differentiating IS from ICH in acute settings.
2022-09-21 | PXD032917 | Pride
Project description:The principal aim of this work was to investigate the methylation profiles of specific ocular tissues, and compare this profile to matched peripheral blood. Matched human blood and eye tissue were obtained post-mortem (n=8) and DNA methylation profiling performed on blood, neurosensory retina, retinal pigment epithelium (RPE)/choroid and optic nerve tissue using the Illumina Infinium HumanMethylation450 platform.
2017-02-23 | E-MTAB-5535 | biostudies-arrayexpress
Project description:The potential for epigenetic changes in host cells following microbial infection has been widely suggested, but few examples have been reported. We assessed genome-wide patterns of DNA methylation in human macrophage-like U937 cells following infection with Burkholderia pseudomallei, an intracellular bacterial pathogen and the causative agent of human melioidosis. Our analyses revealed significant changes in host cell DNA methylation, at multiple CpG sites in the host cell genome, following infection. Infection induced differentially methylated probes (iDMPs) showing the greatest changes in DNA methylation were found to be in the vicinity of genes involved in inflammatory responses, intracellular signalling, apoptosis and pathogen-induced signalling. A comparison of our data with reported methylome changes in cells infected with M. tuberculosis revealed commonality of differentially methylated genes, including genes involved in T cell responses (BCL11B, FOXO1, KIF13B, PAWR, SOX4, SYK), actin cytoskeleton organisation (ACTR3, CDC42BPA, DTNBP1, FERMT2, PRKCZ, RAC1), and cytokine production (FOXP1, IRF8, MR1). Overall our findings show that pathogenic-specific and pathogen-common changes in the methylome occur following infection. The human leukemic monocyte lymphoma cell line (U937, ATCC CRL-1593.2) was maintained in RPMI 1640 supplemented with 10% foetal bovine serum (FBS) at 37°C. U937 cells were differentiated to macrophage-like cells following exposure to 20 ng/ml (final concentration) of phorbol 12-myristate 13-acetate (PMA) for 48 hours at 37°C and differentiation evidenced by increased adherence to tissue culture flasks. Overnight cultures of B. pseudomallei K96243 were diluted in L-15 medium and added to differentiated U937 cells at a multiplicity of infection (MOI) of 10. Uninfected controls were overlaid with L15 medium only. The cells were then incubated at 37°C to allow infection. The cells were washed 3 times with PBS and incubated with fresh L15 medium containing 1mg/ml kanamycin to kill extracellular bacteria. At appropriate time points the cells were washed 3 times in warm PBS and lysed with 0.1% (vol/vol) Triton X-100. DNA was isolated using an AllPrep kit (Qiagen) and stored at -80ºC until required. DNA yield was measured using a Nanodrop instrument with measurements between 22.8 â 50.6 ng/ul. Two experiments were carried out using the above procedure. In Experiment 1, DNA was collected from uninfected and infected cells at 2 hours (T2), and 4 hours (T4) post infection (2 biological replicates and 2 technical replicates from each group). In Experiment 2, DNA was collected from uninfected and infected cells at 1 hour (T1), 2 hours (T2), 3 hours (T3) and 4 hours (T4) post infection (1 sample from each group). The DNA methylation profile was determined using the Infinium HumanMethylation450 BeadChip (450K) (Illumina Inc.) following the manufacturerâs instructions. The data was extracted and the initial analysis was performed using GenomeStudio (2010.3) methylation module (1.8.5). Quality control checks and quantile normalisation were implemented using WateRmelon. Samples with more than 1% of sites with a detection p-value greater than 0.05 were removed as were probes with 1% of samples with a detection p-value greater than 0.05. Probes were removed if they had a bead count less than 3 in 1% of samples. Cross-hybridizing probes were removed, leaving 425496 probes for analysis. Here we report DNA methylation profile of 18 samples (10 infected and 8 control).
2016-06-16 | E-GEOD-83379 | biostudies-arrayexpress
Project description:Total RNA was extracted from liver tissues of lab-reared threespine stickleback. The dataset combines transcripts common to two experiments: first generation fish originating from the Baltic Sea near Helsinki (Finland) bred using a paternal half-sib design (E-MTAB-3098), and second generation fish originating from three different Fennoscandian populations bred from a full-sib design. Annotated R scripts defining the normalization procedures are available as additional files (see http://www.ebi.ac.uk/arrayexpress/files/E-MTAB-3099). Additional files also include a metadata file (matrix.df.csv) to facilitate construction of design matrices used by the snm package.
2014-12-03 | E-MTAB-3099 | biostudies-arrayexpress
Project description:Longitudinal samples were collected from neonates in the NICU at the Royal Womenâs Hospital in Melbourne, Australia. Blood collection occurred by heel stick and was collected on Whatman paper shortly after birth at 25 weeks gestation, one day post birth, and at the equivalent of 28, 32, 36, and 40 weeks gestation. DNA methylation was assessed in whole blood taken from 2 samples. DNA was extracted using the DNeasy Kit (Qiagen). DNA methylation was interrogated for each sample using the HumanMethylation450 BeadChip (Illumina).
2016-04-07 | E-GEOD-79969 | biostudies-arrayexpress