Admixture mapping for Breast Cancer in Latinas
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ABSTRACT:
PROVIDER: PRJNA283157 | ENA |
REPOSITORIES: ENA
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Project description:Germline Genomic Analyses of Breast Cancer in Latinas
| PRJNA909904 | ENA
Project description:Germline Genomic Analyses of Breast Cancer in Latinas
| PRJNA909906 | ENA
Project description:Among US Latinas and Mexican women, those with higher European ancestry have increased risk of breast cancer. We combined an admixture mapping and genome-wide association mapping approach to search for genomic regions that may explain this observation. Latina women with breast cancer (n= 1497) and Latina controls (n= 1272) were genotyped using Affymetrix and Illumina arrays. We inferred locus-specific genetic ancestry and compared the ancestry between cases and controls. We also performed single nucleotide polymorphism (SNP) association analyses in regions of interest. Correction for multiple-hypothesis testing was conducted using permutations (P(corrected)). We identified one region where genetic ancestry was significantly associated with breast cancer risk: 6q25 [odds ratio (OR) per Indigenous American chromosome 0.75, 95% confidence interval (CI): 0.65-0.85, P= 1.1 × 10(-5), P(corrected)= 0.02]. A second region on 11p15 showed a trend towards association (OR per Indigenous American chromosome 0.77, 95% CI: 0.68-0.87, P= 4.3 × 10(-5), P(corrected)= 0.08). In both regions, breast cancer risk decreased with higher Indigenous American ancestry in concordance with observations made on global ancestry. The peak of the 6q25 signal includes the estrogen receptor 1 (ESR1) gene and 5' region, a locus previously implicated in breast cancer. Genome-wide association analysis found that a multi-SNP model explained the admixture signal in both regions. Our results confirm that the association between genetic ancestry and breast cancer risk in US Latinas is partly due to genetic differences between populations of European and Indigenous Americans origin. Fine-mapping within the 6q25 and possibly the 11p15 loci will lead to the discovery of the biologically functional variant/s behind this association.
| S-EPMC3313799 | biostudies-literature
Project description:Whole exome sequencing and RNA-seq to characterize the somatic breast cancer landscape among Latinas in California
| PRJNA940528 | ENA
Project description:Whole exome sequencing and RNA-seq to characterize the somatic breast cancer landscape among Latinas in California
| PRJNA940529 | ENA
Project description:Breast cancer development model
2020-10-08 | 627 | FAIRDOMHub
Project description:Modern genetic data combined with appropriate statistical methods have the potential to contribute substantially to our understanding of human history. We have developed an approach that exploits the genomic structure of admixed populations to date and characterize historical mixture events at fine scales. We used this to produce an atlas of worldwide human admixture history, constructed using genetic data alone and encompassing over 100 events occurring over the past 4,000 years. We identify events whose dates and participants suggest they describe genetic impacts of the Mongol Empire, Arab slave trade, Bantu expansion, first millennium CE migrations in eastern Europe, and European colonialism, as well as unrecorded events, revealing admixture to be an almost universal force shaping human populations. 158 indviduals of Eurasian descent included as part of a global analysis of admixture
2014-02-14 | E-GEOD-53626 | biostudies-arrayexpress
Project description:Altered metabolism is a hallmark of cancer, but little is still known about its regulation. Here we measure transcriptomic, proteomic, phospho-proteomic and fluxomics data in a breast cancer cell-line across three different conditions. Integrating these multiomics data within a genome scale human metabolic model in combination with machine learning we systematically chart the different layers of metabolic regulation in breast cancer, predicting which enzymes and pathways are regulated at which level. We distinguish between two types of reactions, directly or indirectly regulated. Directly-regulated reactions include those whose flux is regulated by transcriptomic alterations (~890) or via proteomic or phospho-proteomics alterations (~140) in the enzymes catalyzing them. Indirectly regulated reactions are those that currently lack evidence for direct regulation in our measurements or predictions (~930). Remarkably, we find that the flux of indirectly regulated reactions is strongly coupled to the flux of the directly regulated ones, uncovering a hierarchical organization of breast cancer metabolism. Furthermore, the predicted indirectly regulated reactions are predominantly bi-directional. Taken together, this architecture may facilitate the formation of stochiometrically consistent flux distributions in response to the varying environmental conditions incurred by the tumor cells. The approach presented lays a conceptual and computational basis for a more complete mapping of metabolic regulation in different cancers with incoming additional data.
2020-05-26 | PXD006449 | Pride