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Träfflista för sökning "WFRF:(Muir Kenneth) srt2:(2015-2019);pers:(Teixeira Manuel R)"

Sökning: WFRF:(Muir Kenneth) > (2015-2019) > Teixeira Manuel R

  • Resultat 1-7 av 7
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1.
  • Lawrenson, Kate, et al. (författare)
  • Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus
  • 2016
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • Tidskriftsartikel (refereegranskat)abstract
    • A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
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2.
  • Zeng, Chenjie, et al. (författare)
  • Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus
  • 2016
  • Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 18
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. Method: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. Results: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 x 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 x 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 x 10(-4)) identified in the general populations, and rs113824616 (P = 7 x 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. Conclusion: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.
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3.
  • Adams, Charleen, et al. (författare)
  • Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study
  • 2019
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 28:1, s. 208-216
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: 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).MATERIALS AND METHODS: 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.RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (p <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.CONCLUSIONS: 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.IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
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4.
  • Law, Philip J., et al. (författare)
  • Association analyses identify 31 new risk loci for colorectal cancer susceptibility
  • 2019
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention.
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5.
  • Matejcic, Marco, et al. (författare)
  • Germline variation at 8q24 and prostate cancer risk in men of European ancestry
  • 2018
  • Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 x 10(-15)), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95% CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for similar to 25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.
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6.
  • Szulkin, Robert, et al. (författare)
  • Prediction of individual genetic risk to prostate cancer using a polygenic score.
  • 2015
  • Ingår i: The Prostate. - : Wiley. - 0270-4137 .- 1097-0045. ; 75:13, s. 1467-74
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction.METHODS: We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls.RESULTS: The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk.CONCLUSIONS: Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.
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7.
  • Wu, Lang, et al. (författare)
  • Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk : A Transcriptome-Wide Association Study in over 140,000 European Descendants
  • 2019
  • Ingår i: Cancer Research. - : AMER ASSOC CANCER RESEARCH. - 0008-5472 .- 1538-7445. ; 79:13, s. 3192-3204
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association study-identified prostate cancer risk variants explain only a relatively small fraction of its familial relative risk, and the genes responsible for many of these identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61 x 10(-6), a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61 x 10(-6) after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology. Significance: This study identifies novel prostate cancer genetic loci and possible causal genes, advancing our understanding of the molecular mechanisms that drive prostate cancer.
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