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Sökning: WFRF:(Olson Sara H)

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51.
  • Stacey, Simon N, et al. (författare)
  • Ancestry-shift refinement mapping of the C6orf97-ESR1 breast cancer susceptibility locus.
  • 2010
  • Ingår i: PLoS genetics. - : Public Library of Science. - 1553-7404. ; 6:7, s. e1001029-
  • Tidskriftsartikel (refereegranskat)abstract
    • We used an approach that we term ancestry-shift refinement mapping to investigate an association, originally discovered in a GWAS of a Chinese population, between rs2046210[T] and breast cancer susceptibility. The locus is on 6q25.1 in proximity to the C6orf97 and estrogen receptor alpha (ESR1) genes. We identified a panel of SNPs that are correlated with rs2046210 in Chinese, but not necessarily so in other ancestral populations, and genotyped them in breast cancer case:control samples of Asian, European, and African origin, a total of 10,176 cases and 13,286 controls. We found that rs2046210[T] does not confer substantial risk of breast cancer in Europeans and Africans (OR = 1.04, P = 0.099, and OR = 0.98, P = 0.77, respectively). Rather, in those ancestries, an association signal arises from a group of less common SNPs typified by rs9397435. The rs9397435[G] allele was found to confer risk of breast cancer in European (OR = 1.15, P = 1.2 x 10(-3)), African (OR = 1.35, P = 0.014), and Asian (OR = 1.23, P = 2.9 x 10(-4)) population samples. Combined over all ancestries, the OR was 1.19 (P = 3.9 x 10(-7)), was without significant heterogeneity between ancestries (P(het) = 0.36) and the SNP fully accounted for the association signal in each ancestry. Haplotypes bearing rs9397435[G] are well tagged by rs2046210[T] only in Asians. The rs9397435[G] allele showed associations with both estrogen receptor positive and estrogen receptor negative breast cancer. Using early-draft data from the 1,000 Genomes project, we found that the risk allele of a novel SNP (rs77275268), which is closely correlated with rs9397435, disrupts a partially methylated CpG sequence within a known CTCF binding site. These studies demonstrate that shifting the analysis among ancestral populations can provide valuable resolution in association mapping.
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52.
  • Stevens, Kristen N, et al. (författare)
  • 19p13.1 is a triple negative-specific breast cancer susceptibility locus
  • 2012
  • Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 72, s. 1795-
  • Tidskriftsartikel (refereegranskat)abstract
    • The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with risk of ovarian cancer. Here we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 Odds Ratio (OR)=1.10, 95% Confidence Interval (CI) 1.05 - 1.15, p=3.49 x 10-5] and triple negative (TN) (ER, PR and HER2 negative) breast cancer [rs8170 OR=1.22, 95% CI 1.13 - 1.31, p=2.22 x 10-7]. However, rs8170 was no longer associated with ER-negative breast cancer risk when TN cases were excluded [OR=0.98, 95% CI 0.89 - 1.07, p=0.62]. In addition, a combined analysis of TN cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC) (n=3,566) identified a genome-wide significant association between rs8170 and TN breast cancer risk [OR=1.25, 95% CI 1.18 - 1.33, p=3.31 x 10-13]. Thus, 19p13.1 is the first triple negative-specific breast cancer risk locus and the first locus specific to a histological subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple negative tumors and other subtypes likely arise through distinct etiologic pathways.
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53.
  • Sun, Xiangqing, et al. (författare)
  • A variable age of onset segregation model for linkage analysis, with correction for ascertainment, applied to glioma
  • 2012
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:12, s. 2242-2251
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: We propose a two-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma.Methods: First, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N=281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N=74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are re-estimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis.Results: Using the best fitting segregation models in model-based multipoint linkage analysis, we identified two separate peaks on chromosome 17; the first agreed with a region identified by Shete et al. (1) who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum LOD.Conclusions/Impact: Our approach has the advantage of not requiring markers to be in linkage equilibrium unless the minor allele frequency is small (markers which tend to be uninformative for linkage), and of using more of the available information for LOD-based linkage analysis.
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54.
  • Takahashi, Hannah, et al. (författare)
  • Mendelian randomisation study of the relationship between vitamin D and risk of glioma
  • 2018
  • Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 8
  • Tidskriftsartikel (refereegranskat)abstract
    • To examine for a causal relationship between vitamin D and glioma risk we performed an analysis of genetic variants associated with serum 25-hydroxyvitamin D (25(OH) D) levels using Mendelian randomisation (MR), an approach unaffected by biases from confounding. Two-sample MR was undertaken using genome-wide association study data. Single nucleotide polymorphisms (SNPs) associated with 25(OH) D levels were used as instrumental variables (IVs). We calculated MR estimates for the odds ratio (OR) for 25(OH) D levels with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighted (IVW) and maximum likelihood estimation (MLE) methods. A non-significant association between 25(OH) D levels and glioma risk was shown using both the IVW (OR = 1.21, 95% confidence interval [CI] = 0.90-1.62, P = 0.201) and MLE (OR = 1.20, 95% CI = 0.98-1.48, P = 0.083) methods. In an exploratory analysis of tumour subtype, an inverse relationship between 25(OH)D levels and glioblastoma (GBM) risk was identified using the MLE method (OR = 0.62, 95% CI = 0.43-0.89, P = 0.010), but not the IVW method (OR = 0.62, 95% CI = 0.37-1.04, P = 0.070). No statistically significant association was shown between 25(OH) D levels and non-GBM glioma. Our results do not provide evidence for a causal relationship between 25(OH) D levels and all forms of glioma risk. More evidence is required to explore the relationship between 25(OH) D levels and risk of GBM.
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55.
  • Walsh, Naomi, et al. (författare)
  • Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer
  • 2019
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 111:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes.Methods: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided.Results: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets.Conclusion: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.
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56.
  • Wang, Xiaoliang, et al. (författare)
  • Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women
  • 2022
  • Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 x 10(-8) as genome-wide significant, and p-values < 1 x 10(-5) as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 x 10(5). The strongest evidence was found for rs4674019 (p-value = 2.27 x 10(-7)), which showed genome-wide significant interaction (p-value = 3.8 x 10(-8)) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.
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