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Sökning: WFRF:(Pashayan Nora)

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1.
  • Went, Molly, et al. (författare)
  • Author Correction: Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma
  • 2019
  • Ingår i: Nature communications. - 2041-1723. ; 10:1, s. 213
  • Tidskriftsartikel (refereegranskat)abstract
    • The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.
2.
  • Adams, Charleen, et al. (författare)
  • Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study.
  • 2018
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755.
  • Tidskriftsartikel (refereegranskat)abstract
    • <p><strong>BACKGROUND:</strong> Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR).</p><p><strong>MATERIALS AND METHODS:</strong> The case-control portion of the study was conducted in nine UK centres with men aged 50-69 years who underwent prostate-specific antigen (PSA) screening for prostate cancer within the Prostate testing for cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.</p><p><strong>RESULTS:</strong> Thirty-five metabolites were strongly associated with prostate cancer (p &lt;0.0014, multiple-testing threshold). These fell into four classes: i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); ii) fatty acids and ratios; iii) amino acids; iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.</p><p><strong>CONCLUSIONS:</strong> We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.</p><p><strong>IMPACT:</strong> The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.</p>
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3.
  • Dadaev, Tokhir, et al. (författare)
  • Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.
  • 2018
  • Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 9:1
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.</p>
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5.
  • Gusev, Alexander, et al. (författare)
  • Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation.
  • 2016
  • Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 7
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.</p>
6.
  • Jiang, Xia, et al. (författare)
  • Shared heritability and functional enrichment across six solid cancers
  • 2019
  • Ingår i: Nature Communications. - Nature Publishing Group. - 2041-1723 .- 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (<em>r</em><em>g</em> = 0.57, <em>p</em> = 4.6 × 10−8), breast and ovarian cancer (<em>r</em><em>g</em> = 0.24, <em>p</em> = 7 × 10−5), breast and lung cancer (<em>r</em><em>g</em> = 0.18, <em>p </em>=1.5 × 10−6) and breast and colorectal cancer (<em>r</em><em>g</em> = 0.15, <em>p</em> = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.</p>
7.
  • Jiang, Xia, et al. (författare)
  • Shared heritability and functional enrichment across six solid cancers
  • 2019
  • Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.</p>
8.
  • Kar, Siddhartha P., et al. (författare)
  • Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types
  • 2016
  • Ingår i: Cancer Discovery. - AMER ASSOC CANCER RESEARCH. - 2159-8274 .- 2159-8290. ; 6:9, s. 1052-1067
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P &lt; 10 -8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P &lt; 10(-5) in the three-cancer meta-analysis. SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. (C) 2016 AACR.</p>
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9.
  • Lophatananon, Artitaya, et al. (författare)
  • Height, selected genetic markers and prostate cancer risk : results from the PRACTICAL consortium.
  • 2017
  • Ingår i: British Journal of Cancer. - 0007-0920 .- 1532-1827. ; 117:5, s. 734-743
  • Tidskriftsartikel (refereegranskat)abstract
    • <p><strong>BACKGROUND:</strong> Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer.</p><p><strong>METHODS:</strong> We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions.</p><p><strong>RESULTS:</strong> The results suggest that height is associated with high-grade prostate cancer risk. Men with height &gt;180 cm are at a 22% increased risk as compared to men with height &lt;173 cm (OR 1.22, 95% CI 1.01-1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group.</p><p><strong>CONCLUSIONS:</strong> There was no evidence of gene-environment interaction between height and the selected candidate SNPs.Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.</p>
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