Dataset Information

European American stratification in ovarian cancer case control data: the utility of genome-wide data for inferring ancestry.

ABSTRACT: We investigated the ability of several principal components analysis (PCA)-based strategies to detect and control for population stratification using data from a multi-center study of epithelial ovarian cancer among women of European-American ethnicity. These include a correction based on an ancestry informative markers (AIMs) panel designed to capture European ancestral variation and corrections utilizing un-thinned genome-wide SNP data; case-control samples were drawn from four geographically distinct North-American sites. The AIMs-only and genome-wide first principal components (PC1) both corresponded to the previously described North or Northwest-Southeast axis of European variation. We found that the genome-wide PCA captured this primary dimension of variation more precisely and identified additional axes of genome-wide variation of relevance to epithelial ovarian cancer. Associations evident between the genome-wide PCs and study site corroborate North American immigration history and suggest that undiscovered dimensions of variation lie within Northern Europe. The structure captured by the genome-wide PCA was also found within control individuals and did not reflect the case-control variation present in the data. The genome-wide PCA highlighted three regions of local LD, corresponding to the lactase (LCT) gene on chromosome 2, the human leukocyte antigen system (HLA) on chromosome 6 and to a common inversion polymorphism on chromosome 8. These features did not compromise the efficacy of PCs from this analysis for ancestry control. This study concludes that although AIMs panels are a cost-effective way of capturing population structure, genome-wide data should preferably be used when available.

SUBMITTER: Raska P

PROVIDER: S-EPMC3348917 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

European American stratification in ovarian cancer case control data: the utility of genome-wide data for inferring ancestry.

Raska Paola P Iversen Edwin E Chen Ann A Chen Zhihua Z Fridley Brooke L BL Permuth-Wey Jennifer J Tsai Ya-Yu YY Vierkant Robert A RA Goode Ellen L EL Risch Harvey H Schildkraut Joellen M JM Sellers Thomas A TA Barnholtz-Sloan Jill J

PloS one 20120509 5

We investigated the ability of several principal components analysis (PCA)-based strategies to detect and control for population stratification using data from a multi-center study of epithelial ovarian cancer among women of European-American ethnicity. These include a correction based on an ancestry informative markers (AIMs) panel designed to capture European ancestral variation and corrections utilizing un-thinned genome-wide SNP data; case-control samples were drawn from four geographically ...[more]

PMID: 22590501

Similar Datasets

Project description:We reAggressive high-grade, estrogen receptor negative (ER-) breast cancer is more common among American women of African ancestry (AA) than those of European ancestry (EA). The reasons remain largely unknown. Epigenetic mechanisms, particularly DNA methylation and altered microRNA (miRNA) expression, may contribute to racial differences in breast cancer. However, the characterization of this epigenetic modification in relation to ER+ and ER- breast cancer, and its functional role in the regulation of miRNA expression remains to be investigated, especially among high risk AA women. In this study, we evaluated methylation patterns of miRNA genes and their effect on miRNA expression in breast tumors from both AA and EA women. The genome-wide methylation screen identified a number of differentially methylated loci (DML) between ER- and ER+ tumor subtypes in tumors from both races, or specific to AA or EA women. Integrated analysis of DNA methylation and miRNA expression further identified certain DMLs whose methylation levels were significantly correlated with the expression of relevant miRNAs, such as multiple CpGs highly correlated with miR-190b and miR-135b. In summary, our results suggest that DNA methylation patterns in miRNA encoding genes differ between breast cancers according to cancer subtype and race, and that this altered methylation may affect miRNA expression. Further pathway analysis identified their potential role in modulating cancer-related key biological processes. These findings shed light on the epigenetic regulation of miRNA expression and provide insights into the relations of clinical-relevant miRNAs to their target genes and to serve as potential preventative and therapeutic targets. port the application of single-molecule-based sequencing technology for high-throughput profiling of histone modifications in mammalian cells. By obtaining over four billion bases of sequence from chromatin immunoprecipitated DNA, we generated genome-wide chromatin-state maps of mouse embryonic stem cells, neural progenitor cells and embryonic fibroblasts. We find that lysine 4 and lysine 27 trimethylation effectively discriminates genes that are expressed, poised for expression, or stably repressed, and therefore reflect cell state and lineage potential. Lysine 36 trimethylation marks primary coding and non-coding transcripts, facilitating gene annotation. Trimethylation of lysine 9 and lysine 20 is detected at satellite, telomeric and active long-terminal repeats, and can spread into proximal unique sequences. Lysine 4 and lysine 9 trimethylation marks imprinting control regions. Finally, we show that chromatin state can be read in an allele-specific manner by using single nucleotide polymorphisms. This study provides a framework for the application of comprehensive chromatin profiling towards characterization of diverse mammalian cell populations.

Dataset Information

European American stratification in ovarian cancer case control data: the utility of genome-wide data for inferring ancestry.

Publications

European American stratification in ovarian cancer case control data: the utility of genome-wide data for inferring ancestry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure