| 11. |
|
|
| 12. |
|
|
| 13. |
|
|
| 14. |
- Went, M, et al.
(author)
-
Author Correction: Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma
- 2019
-
In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 213-
-
Journal article (peer-reviewed)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.
|
|
| 15. |
- Dadaev, T, et al.
(author)
-
Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
- 2018
-
In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1, s. 2256-
-
Journal article (peer-reviewed)abstract
- 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.
|
|
| 16. |
|
|
| 17. |
|
|
| 18. |
- Grasha, K., et al.
(author)
-
Connecting young star clusters to CO molecular gas in NGC 7793 with ALMA-LEGUS
- 2018
-
In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 481:1, s. 1016-1027
-
Journal article (peer-reviewed)abstract
- We present an investigation of the relationship between giant molecular cloud (GMC) properties and the associated stellar clusters in the nearby flocculent galaxy NGC 7793. We combine the star cluster catalogue from the HST LEGUS (Legacy ExtraGalactic UV Survey) programme with the 15 pc resolution ALMA CO(2-1) observations. We find a strong spatial correlation between young star clusters and GMCs such that all clusters still associated with a GMC are younger than 11 Myr and display a median age of 2 Myr. The age distribution increases gradually as the cluster-GMC distance increases, with star clusters that are spatially unassociated with molecular gas exhibiting a median age of 7 Myr. Thus, star clusters are able to emerge from their natal clouds long before the time-scale required for clouds to disperse. To investigate if the hierarchy observed in the stellar components is inherited from the GMCs, we quantify the amount of clustering in the spatial distributions of the components and find that the star clusters have a fractal dimension slope of -0.35 +/- 0.03, significantly more clustered than the molecular cloud hierarchy with slope of -0.18 +/- 0.04 over the range 40-800 pc. We find, however, that the spatial clustering becomes comparable in strength for GMCs and star clusters with slopes of -0.44 +/- 0.03 and -0.45 +/- 0.06, respectively, when we compare massive (> 10(5) M-circle dot) GMCs to massive and young star clusters. This shows that massive star clusters trace the same hierarchy as their parent GMCs, under the assumption that the star formation efficiency is a few per cent.
|
|
| 19. |
- Law, Philip J., et al.
(author)
-
Association analyses identify 31 new risk loci for colorectal cancer susceptibility
- 2019
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
-
Journal article (peer-reviewed)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.
|
|
| 20. |
- Adams, Charleen, et al.
(author)
-
Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study
- 2019
-
In: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 28:1, s. 208-216
-
Journal article (peer-reviewed)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.
|
|
