Buccals are likely to be a more informative surrogate tissue than blood for epigenome-wide association studies
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE45529 | GEO | 2013/03/28
SECONDARY ACCESSION(S): PRJNA194524
REPOSITORIES: GEO
Similar Datasets
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals>6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs.
| S-EPMC3674053 | biostudies-literature
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals >6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs.
2013-05-02 | GSE46573 | GEO
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals >6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs.
2013-05-02 | GSE46572 | GEO
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals >6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs. Bisulphite converted DNA from the 22 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip
2013-03-28 | E-GEOD-45529 | biostudies-arrayexpress
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals >6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs. Buccal Profile generated from 14 Buccal Individuals
2013-05-02 | E-GEOD-46572 | biostudies-arrayexpress
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals >6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs. Bisulphite converted DNA from the 22 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip
2013-05-02 | E-GEOD-46573 | biostudies-arrayexpress
Project description:To better understand DNA methylation in Alzheimer's disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 - 0.770, P-value = 2.78 × 10-5). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery.
| S-EPMC9388493 | biostudies-literature
Project description:Epigenome-wide association study (EWAS) of blood samples from a case-control study of bladder cancer. The Illumina Infinium 27k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 27,000 CpGs in peripheral blood. Samples included peripheral blood samples from 223 incident cases of bladder cancer and 205 control subjects.
2013-08-29 | GSE50409 | GEO
Project description:Epigenome-wide studies of DNA methylation using blood-derived DNA from cancer patients are complicated by the heterogeneity of cell types within blood and the associated cell lineage specification of DNA methylation signatures. Here, we applied a novel set of analytic approaches to assess the association between cancer case-status and DNA methylation adjusted for leukocyte variation using blood specimens from three case-control cancer studies (bladder: 223 cases, 205 controls; head and neck: 92 cases, 92 controls; and ovarian: 131 cases, 274 controls). Using previously published data on leukocyte-specific CpG loci and a recently described approach to deconvolute subject-specific blood composition, we performed an epigenome-wide analysis to examine the association between blood-based DNA methylation patterns and each of the three aforementioned solid tumor types adjusted for cellular heterogeneity in blood. After adjusting for leukocyte profile in our epigenome-wide analysis, the omnibus association between case-status and methylation was significant for all three studies (bladder cancer: P = 0.047; HNSCC: P = 0.013; ovarian cancer: P = 0.0002). Subsequent analyses revealed that CpG sites associated with cancer were enriched for transcription factor binding motifs involved with cancer-associated pathways. These results support the existence of cancer-associated DNA methylation profiles in the blood of solid tumor patients that are independent of alterations in normal leukocyte distributions. Adoption of the methods developed here will make it feasible to rigorously assess the influence of variability of normal leukocyte profiles when investigating cancer related changes in blood-based epigenome-wide association studies.
| S-EPMC4065186 | biostudies-literature
Project description:BackgroundIn DNA methylation analyses like epigenome-wide association studies, effects in differentially methylated CpG sites are assessed. Two kinds of outcomes can be used for statistical analysis: Beta-values and M-values. M-values follow a normal distribution and help to detect differentially methylated CpG sites. As biological effect measures, differences of M-values are more or less meaningless. Beta-values are of more interest since they can be interpreted directly as differences in percentage of DNA methylation at a given CpG site, but they have poor statistical properties. Different frameworks are proposed for reporting estimands in DNA methylation analysis, relying on Beta-values, M-values, or both.ResultsWe present and discuss four possible approaches of achieving estimands in DNA methylation analysis. In addition, we present the usage of M-values or Beta-values in the context of bioinformatical pipelines, which often demand a predefined outcome. We show the dependencies between the differences in M-values to differences in Beta-values in two data simulations: a analysis with and without confounder effect. Without present confounder effects, M-values can be used for the statistical analysis and Beta-values statistics for the reporting. If confounder effects exist, we demonstrate the deviations and correct the effects by the intercept method. Finally, we demonstrate the theoretical problem on two large human genome-wide DNA methylation datasets to verify the results.ConclusionsThe usage of M-values in the analysis of DNA methylation data will produce effect estimates, which cannot be biologically interpreted. The parallel usage of Beta-value statistics ignores possible confounder effects and can therefore not be recommended. Hence, if the differences in Beta-values are the focus of the study, the intercept method is recommendable. Hyper- or hypomethylated CpG sites must then be carefully evaluated. If an exploratory analysis of possible CpG sites is the aim of the study, M-values can be used for inference.
| S-EPMC8086103 | biostudies-literature